Wireframes, UX audit, Workflow and Efficiency Audits, A/B testing, user journey mapping, email automation, internal platform automation, CRM/ESP Implementation, data infrastructure, list/user segmentation, platform integrations, data analytics, flow prioritization, email campaign analysis, content testing

This article proposes adaptive pool testing which involves testing a combined sample from multiple people as a methodology to increase testing capacity for Sars-COv2 using PCR. Pool tests involve that if a pool is detected positive, each sample from the pool will be tested separately. Also, this article proposes an optimization algorithm for the pool size-determine the optimum number of samples that can be combined into a single test in order to obtain the best results with a minimum number of tests. Romania and other countries use PCR testing for diagnosing COVID -19; this method offers the best detection rate compared with other testing methods but is expensive and is limited by availability of kitting tests and PCR testing machines; current capacity in Romania is around 4000 test per day; Currently testing in Romania and other countries with limited testing capacity are conducted only for peoples with specific symptoms and for contacts of infected persons; A PCR test examines the presence of a unique genetic sequence of viruses in a sample taken from the patient and takes several hours. Researchers at Technion – Israel Institute of Technology and Rambam Health Care Campus have successfully tested pooling methodology for COVID 19 that enables simultaneous testing of dozens of samples. “According to the new pooling approach that we have currently tested, molecular testing can be performed on a “combined sample,” taken from 32 or 64 patients. This way we can significantly accelerate the testing rate. Only in those rare cases, where the joint sample is found to be positive, will we conduct an individual test for each of the specific samples.” According to Prof. Roy Kishony, head of the research group in the Faculty of Biology at Technion, “This is not a scientific breakthrough, but a demonstration of the effectivity of using the existing method and even the existing equipment to significantly increase the volume of samples tested per day. This is done by pooling multiple samples in a single test tube. Even when we conducted a joint examination of 64 samples in which only one was a positive carrier, the system identified that there was a positive sample. ( ) https://www.technion.ac.il/en/2020/03/pooling-method-for-accelerated-testing-of-covid-19/ Similar research was performed in Germany by Goethe-Universität Frankfurt am Main with combined sample size from 5 patients and results were 10% accurate. (more details here: ) https://idw-online.de/en/news743899 In mathematics, group testing was first studied by Robert Dorfman in 1943; is a procedure that breaks up the task of identifying certain objects into tests on groups of items, rather than on individual ones. This methodology was applied in epidemiology  for other diseases like malaria and HIV for PCR testing; a related article for malaria: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4301903/ Pooled adaptive PCR testing strategy based on prevalence estimation Facts: It's possible to test a pool of up to 64 people for SARS-CoV-2 at once and the test will say whether at least one person in the pool is positive; Based on previous testing results we can calculate the prevalence rate; for example in Romania (as of April 6, 2020): we have 3.864 detected cases and we performed 38.629  tests to detect these cases (only peoples with specific symptoms and contacts of infected persons were tested); in this case prevalence rate is around 10% (10% of total test are positive); Proposed solution: Develop a pooling testing protocol (algorithm) based on prevalence estimation; this algorithm will be adaptive and pool size will be changed frequently based on estimated prevalence rate and changes in prevalence rate in previous days. There are two potential strategies: in cases where prevalence rate is relatively high (between 1% and 30%); if the prevalence of positive samples is greater than 30% it is never worth pooling and the recommended strategy is individual tests; for the cases when prevalence rate is between 1% and 30% the objective is to determine the optimal pool size in order to obtain the minimum number of tests; strategy in this case is to test each pool of tests and if the results of a pool is positive to test individual each test from the pool; One pool strategy second strategy proposed it is recommended for a prevalence rate below 1%; a huge decrease in number of tests required to test a large population can be obtained using two pools; in this case first round of testing will use large pools (between 32 and 64 samples) and a second round of testing will be performed for positive large pools with smaller pools; only for positive small pools will be performed individual testing. Two pools strategy: Tests and pool calculator Based on the above data I developed a used to estimate the number of tests required based on prevalence rate and pool size; also, this calculator allow to determine the optimum pool size in order to use a minimum number of tests; calculator This calculator uses as input prevalence rate and pool size and the output is the estimated number of tests required using pool methodology; calculator was developed in Excel and is available for Also, this calculator determines the optimum pool size for a selected prevalence rate download. Figure 1: Calculator Proposed methodology for targeted tests Calculate prevalence rate in testing region based on previous data: Prevalence rate = number of positive tests divided by total number of tests performed; prevalence can be calculated at country level or region/state based Prevalence rate can be calculated using data from the beginning of testing; maximum benefits can be obtained by calculating prevalence rate based on last three days test results; also better results can be obtained if we calculate based on region prevalence Use Excel calculator to determine optimal pool size: enter number of cases and number of positive tests; prevalence is automatically calculated and also optimal pool size; you can use also a fixed pool size; calculator will show the number of test required for both situations (fixed and optimum pool size); Perform pool testing and individual tests for samples from positive pools Proposed methodology for large population tests Calculate prevalence rate in testing region based on previous data: Prevalence rate = number of positive tests divided by total population; prevalence can be calculated at country level or region/state based; adjust number by adding a coefficient for undetected case (asymptomatic cases) Use Excel calculator to determine optimal pool size Perform pool testing and individual tests for samples from positive pools Advantages Pooled adaptive PCR testing strategy based on prevalence estimation can offer a major increase in testing capacity with a big impact also in testing costs: Reduce the number of tests required for targeted testing with up to 50% Test large population with low prevalence rates using large pools (up to 64 tests); for example, you can test 100.000 persons with around 12.000 tests using a pool size of 30 at a prevalence rate of 0.25%. This methodology can be used also for prevention (i.e. test all passengers from a plane with only few pools and several individual tests) A “Two pools strategy” can be also developed; this strategy it is recommended for a prevalence rate below 1%; a huge decrease in number of tests required to test a large population can be obtained using two pools; in this case first round of testing will use large pools (between 32 and 64 samples) and a second round of testing will be performed for positive large pools with smaller pools (4-8 tests); only for positive small pools will be performed individual testing. Below table is based on Worldometer data ( ) as of April 8, 2020 show the optimum pool size for several countries and US states; also the table show the estimated number of tests required using adaptive pool methodology for the same number of patients and the gain in tests: https://www.worldometers.info/coronavirus/ Figure 2: Individual testing versus adaptive pool methodology The number of tests required can vary based on positive tests distribution (number can be higher or lower); It is obvious that major gains can be obtained for lower prevalence rates: Figure 3: Reduction rate using pool testing Very good results can be obtained for prevalence rate less than 20%. From a testing resources perspective with less than 2,000 tests we can test 10,000 persons (2% prevalence rate) which is a huge gain for testing capacity.

Pooled Adaptive PCR Testing

This paper is available on arxiv under CC 4.0 license. Authors: (1) Jeffrey Ouyang-Zhang, UT Austin (2) Daniel J. Diaz, UT Austin (3) Adam R. Klivans, UT Austin (4) Philipp Krähenbühl, UT Austin Table of Links Abstract & Introduction Related Works Preliminary Methodology Results Limitations Conclusion, Acknowledgements, & References Experimental Setting & Additional Results 7 Conclusion We present a method that efficiently scales thermodynamic stability prediction from single mutations to higher-order mutations. Our key insight is that the effects of mutations on the same protein are correlated. Thus, for a target protein, it suffices to run a deep backbone once and decode the effect of all mutations simultaneously using a shallow decoder. With the AlphaFold model as our backbone, our method outperforms existing methods on a variety of single and multiple mutation benchmarks. Our method scales to millions of mutations with minimal computational overhead and runs in a fraction of the time it would take prior works. 8 Acknowledgements This work is supported by the NSF AI Institute for Foundations of Machine Learning (IFML). References [1] Randomization of genes by pcr mutagenesis. Genome research 2(1), 28–33 (1992) 2 [2] Adams, J.P., Brown, M.J., Diaz-Rodriguez, A., Lloyd, R.C., Roiban, G.D.: Biocatalysis: A Pharma Perspective. Advanced Synthesis and Catalysis 361(11), 2421–2432 (2019). https://doi.org/10.1002/adsc.201900424 1 [3] Ahdritz, G., Bouatta, N., Kadyan, S., Xia, Q., Gerecke, W., O’Donnell, T.J., Berenberg, D., Fisk, I., Zanichelli, N., Zhang, B., Nowaczynski, A., Wang, B., Stepniewska-Dziubinska, M.M., Zhang, S., Ojewole, A., Guney, M.E., Biderman, S., Watkins, A.M., Ra, S., Lorenzo, P.R., Nivon, L., Weitzner, B., Ban, Y.E.A., Sorger, P.K., Mostaque, E., Zhang, Z., Bonneau, R., AlQuraishi, M.: Openfold: Retraining alphafold2 yields new insights into its learning mechanisms and capacity for generalization. bioRxiv (2022). https://doi.org/10.1101/2022.11.20.517210 6 [4] Arnold, F.H.: Design by directed evolution. Accounts of chemical research 31(3), 125–131 (1998) 1, 2, 3 [5] Bell, E.L., Finnigan, W., France, S.P., Green, A.P., Hayes, M.A., Hepworth, L.J., Lovelock, S.L., Niikura, H., Osuna, S., Romero, E., Ryan, K.S., Turner, N.J., Flitsch, S.L.: Biocatalysis. Nature Reviews Methods Primers 1(1), 1–21 (2021). https://doi.org/10.1038/s43586-021-00044-z 1 [6] Benevenuta, S., Pancotti, C., Fariselli, P., Birolo, G., Sanavia, T.: An antisymmetric neural network to predict free energy changes in protein variants. Journal of Physics D: Applied Physics 54(24), 245403 [7] Benevenuta, S., Pancotti, C., Fariselli, P., Birolo, G., Sanavia, T.: An antisymmetric neural network to predict free energy changes in protein variants. Journal of Physics D: Applied Physics 54(24), 245403 (2021) 8 [8] Benevenuta, S., Birolo, G., Sanavia, T., Capriotti, E., Fariselli, P.: Challenges in predicting stabilizing variations: An exploration. Frontiers in Molecular Biosciences 9, 1075570 (2023) 5, 6, 17 [9] Brückner, A., Polge, C., Lentze, N., Auerbach, D., Schlattner, U.: Yeast two-hybrid, a powerful tool for systems biology. International journal of molecular sciences 10(6), 2763–2788 (2009) 1 [10] Cadet, F., Saavedra, E., Syren, P.O., Gontero, B.: Machine learning, epistasis, and protein engineering: From sequence-structure-function relationships to regulation of metabolic pathways. Frontiers in Molecular Biosciences 9, 1098289 (2022) 1 [11] Capriotti, E., Fariselli, P., Casadio, R.: I-mutant2. 0: predicting stability changes upon mutation from the protein sequence or structure. Nucleic acids research 33(suppl_2), W306–W310 (2005) 3, 8 [12] Chen, K., Arnold, F.H.: Tuning the activity of an enzyme for unusual environments: sequential random mutagenesis of subtilisin e for catalysis in dimethylformamide. Proceedings of the National Academy of Sciences 90(12), 5618–5622 (1993) 1, 3 [13] Chen, T., Gong, C., Diaz, D.J., Chen, X., Wells, J.T., Wang, Z., Ellington, A., Dimakis, A., Klivans, A., et al.: Hotprotein: A novel framework for protein thermostability prediction and editing. In: The Eleventh International Conference on Learning Representations (2022) 3 [14] Chen, Y., Lu, H., Zhang, N., Zhu, Z., Wang, S., Li, M.: Premps: Predicting the impact of missense mutations on protein stability. PLoS computational biology 16(12), e1008543 (2020) 3, 8 [15] Cheng, J., Randall, A., Baldi, P.: Prediction of protein stability changes for single-site mutations using support vector machines. Proteins: Structure, Function, and Bioinformatics 62(4), 1125–1132 (2006) 3, 8 [16] Dehghanpoor, R., Ricks, E., Hursh, K., Gunderson, S., Farhoodi, R., Haspel, N., Hutchinson, B., Jagodzinski, F.: Predicting the effect of single and multiple mutations on protein structural stability. Molecules 23(2), 251 (2018) 4, 7 [17] Dehouck, Y., Kwasigroch, J.M., Gilis, D., Rooman, M.: Popmusic 2.1: a web server for the estimation of protein stability changes upon mutation and sequence optimality. BMC bioinformatics 12(1), 1–12 (2011) 3, 8 [18] Diaz, D.J., Gong, C., Ouyang-Zhang, J., Loy, J.M., Wells, J.T., Yang, D., Ellington, A.J., Dimakis, A., Klivans, A.R.: Stability oracle: A structure-based graph-transformer for identifying stabilizing mutations (2023). https://doi.org/10.1101/2023.05.15.540857 3, 4, 7, 8, 16, 17, 18, 19 [19] Diaz, D.J., Kulikova, A.V., Ellington, A.D., Wilke, C.O.: Using machine learning to predict the effects and consequences of mutations in proteins. Current Opinion in Structural Biology 78, 102518 (2023) 3 [20] d’Oelsnitz, S., Diaz, D.J., Acosta, D.J., Schechter, M.W., Minus, M.B., Howard, J.R., Do, H., Loy, J., Alper, H., Ellington, A.D.: Synthetic microbial sensing and biosynthesis of amaryllidaceae alkaloids. bioRxiv pp. 2023–04 (2023) 3 [21] d’Oelsnitz, S., Kim, W., Burkholder, N.T., Javanmardi, K., Thyer, R., Zhang, Y., Alper, H.S., Ellington, A.D.: Using fungible biosensors to evolve improved alkaloid biosyntheses. Nature Chemical Biology 18(9), 981–989 (2022) 1 [22] Ellefson, J.W., Gollihar, J., Shroff, R., Shivram, H., Iyer, V.R., Ellington, A.D.: Synthetic evolutionary origin of a proofreading reverse transcriptase. Science 352(6293), 1590–1593 (2016) 1 [23] Feng, X., Sanchis, J., Reetz, M.T., Rabitz, H.: Enhancing the efficiency of directed evolution in focused enzyme libraries by the adaptive substituent reordering algorithm. Chemistry–A European Journal 18(18), 5646–5654 (2012) 3 [24] Frazer, J., Notin, P., Dias, M., Gomez, A., Min, J.K., Brock, K., Gal, Y., Marks, D.S.: Disease variant prediction with deep generative models of evolutionary data. Nature 599(7883), 91–95 (2021) 9 [25] Gebauer, M., Skerra, A.: Engineered protein scaffolds as next-generation therapeutics. Annual Review of Pharmacology and Toxicology 60, 391–415 (2020). https://doi.org/10.1146/annurev-pharmtox-010818- 021118 1 [26] Gerasimavicius, L., Livesey, B.J., Marsh, J.A.: Correspondence between functional scores from deep mutational scans and predicted effects on protein stability. bioRxiv pp. 2023–02 (2023) 9 [27] Giver, L., Gershenson, A., Freskgard, P.O., Arnold, F.H.: Directed evolution of a thermostable esterase. Proceedings of the National Academy of Sciences 95(22), 12809–12813 (1998) 2, 3 [28] Hie, B.L., Shanker, V.R., Xu, D., Bruun, T.U., Weidenbacher, P.A., Tang, S., Wu, W., Pak, J.E., Kim, P.S.: Efficient evolution of human antibodies from general protein language models. Nature Biotechnology (2023) 3 [29] Jaroszewicz, W., Morcinek-Orłowska, J., Pierzynowska, K., Gaffke, L., W˛egrzyn, G.: Phage display and other peptide display technologies. FEMS Microbiology Reviews 46(2), fuab052 (2022) 1 [30] Järvelin, K., Kekäläinen, J.: Cumulated gain-based evaluation of ir techniques. ACM Transactions on Information Systems (TOIS) 20(4), 422–446 (2002) 6, 17 [31] Jumper, J., Evans, R., Pritzel, A., Green, T., Figurnov, M., Ronneberger, O., Tunyasuvunakool, K., Bates, R., Žídek, A., Potapenko, A., et al.: Highly accurate protein structure prediction with alphafold. Nature 596(7873), 583–589 (2021) 2, 3, 4, 6, 9, 10 [32] Kellogg, E.H., Leaver-Fay, A., Baker, D.: Role of conformational sampling in computing mutation-induced changes in protein structure and stability. Proteins: Structure, Function, and Bioinformatics 79(3), 830–838 (2011) 3 [33] Klabunde, T., Petrassi, H.M., Oza, V.B., Raman, P., Kelly, J.W., Sacchettini, J.C.: Rational design of potent human transthyretin amyloid disease inhibitors. Nature structural biology 7(4), 312–321 (2000) 1, 2 [34] Kouba, P., Kohout, P., Haddadi, F., Bushuiev, A., Samusevich, R., Sedlar, J., Damborsky, J., Pluskal, T., Sivic, J., Mazurenko, S.: Machine learning-guided protein engineering. ACS Catalysis 13, 13863–13895 (2023) 3 [35] Laimer, J., Hofer, H., Fritz, M., Wegenkittl, S., Lackner, P.: Maestro-multi agent stability prediction upon point mutations. BMC bioinformatics 16(1), 1–13 (2015) 3, 4, 7, 8 [36] Li, B., Yang, Y.T., Capra, J.A., Gerstein, M.B.: Predicting changes in protein thermodynamic stability upon point mutation with deep 3d convolutional neural networks. PLoS computational biology 16(11), e1008291 (2020) 3, 4, 8 [37] Li, G., Panday, S.K., Alexov, E.: Saafec-seq: a sequence-based method for predicting the effect of single point mutations on protein thermodynamic stability. International journal of molecular sciences 22(2), 606 (2021) 3 [38] Lin, Z., Akin, H., Rao, R., Hie, B., Zhu, Z., Lu, W., Smetanin, N., dos Santos Costa, A., Fazel-Zarandi, M., Sercu, T., Candido, S., et al.: Language models of protein sequences at the scale of evolution enable accurate structure prediction. bioRxiv (2022) 3, 4, 6, 9, 10, 18 [39] Loell, K., Nanda, V.: Marginal protein stability drives subcellular proteome isoelectric point. Proceedings of the National Academy of Sciences 115(46), 11778–11783 (2018) 1 [40] Lu, H., Diaz, D.J., Czarnecki, N.J., Zhu, C., Kim, W., Shroff, R., Acosta, D.J., Alexander, B.R., Cole, H.O., Zhang, Y., et al.: Machine learning-aided engineering of hydrolases for pet depolymerization. Nature 604(7907), 662–667 (2022) 3 [41] Meghwanshi, G.K., Kaur, N., Verma, S., Dabi, N.K., Vashishtha, A., Charan, P.D., Purohit, P., Bhandari, H.S., Bhojak, N., Kumar, R.: Enzymes for pharmaceutical and therapeutic applications. Biotechnology and Applied Biochemistry 67(4), 586–601 (2020). https://doi.org/10.1002/bab.1919 1 [42] Meier, J., Rao, R., Verkuil, R., Liu, J., Sercu, T., Rives, A.: Language models enable zero-shot prediction of the effects of mutations on protein function. Advances in Neural Information Processing Systems 34, 29287–29303 (2021) 9, 18 [43] Mirdita, M., Schütze, K., Moriwaki, Y., Heo, L., Ovchinnikov, S., Steinegger, M.: Colabfold: making protein folding accessible to all. Nature methods 19(6), 679–682 (2022) 6 [44] Montanucci, L., Capriotti, E., Frank, Y., Ben-Tal, N., Fariselli, P.: Ddgun: an untrained method for the prediction of protein stability changes upon single and multiple point variations. BMC bioinformatics 20, 1–10 (2019) 3, 4, 7, 8, 16, 18 [45] Montanucci, L., Savojardo, C., Martelli, P.L., Casadio, R., Fariselli, P.: On the biases in predictions of protein stability changes upon variations: the inps test case. Bioinformatics 35(14), 2525–2527 (2019) 16 [46] Musdal, Y., Govindarajan, S., Mannervik, B.: Exploring sequence-function space of a poplar glutathione transferase using designed information-rich gene variants. Protein Engineering, Design and Selection 30(8), 543–549 (2017) 3 [47] Nijkamp, E., Ruffolo, J., Weinstein, E.N., Naik, N., Madani, A.: Progen2: exploring the boundaries of protein language models. arXiv preprint arXiv:2206.13517 (2022) 9 [48] Nikam, R., Kulandaisamy, A., Harini, K., Sharma, D., Gromiha, M.M.: Prothermdb: thermodynamic database for proteins and mutants revisited after 15 years. Nucleic acids research 49(D1), D420–D424 (2021) 2, 16 [49] Notin, P., Dias, M., Frazer, J., Hurtado, J.M., Gomez, A.N., Marks, D., Gal, Y.: Tranception: protein fitness prediction with autoregressive transformers and inference-time retrieval. In: International Conference on Machine Learning. pp. 16990–17017. PMLR (2022) 2, 3, 9, 16, 18 [50] Notin, P.M., Van Niekerk, L., Kollasch, A.W., Ritter, D., Gal, Y., Marks, D.: Trancepteve: Combining family-specific and family-agnostic models of protein sequences for improved fitness prediction. bioRxiv pp. 2022–12 (2022) 9 [51] Nutschel, C., Fulton, A., Zimmermann, O., Schwaneberg, U., Jaeger, K.E., Gohlke, H.: Systematically scrutinizing the impact of substitution sites on thermostability and detergent tolerance for bacillus subtilis lipase a. Journal of chemical information and modeling 60(3), 1568–1584 (2020) 9 [52] Paik, I., Ngo, P.H., Shroff, R., Diaz, D.J., Maranhao, A.C., Walker, D.J., Bhadra, S., Ellington, A.D.: Improved bst dna polymerase variants derived via a machine learning approach. Biochemistry (2021) 3 [53] Pak, M.A., Markhieva, K.A., Novikova, M.S., Petrov, D.S., Vorobyev, I.S., Maksimova, E.S., Kondrashov, F.A., Ivankov, D.N.: Using alphafold to predict the impact of single mutations on protein stability and function. Plos one 18(3), e0282689 (2023) 3 [54] Pancotti, C., Benevenuta, S., Birolo, G., Alberini, V., Repetto, V., Sanavia, T., Capriotti, E., Fariselli, P.: Predicting protein stability changes upon single-point mutation: a thorough comparison of the available tools on a new dataset. Briefings in Bioinformatics 23(2), bbab555 (2022) 2, 8, 16, 17 [55] Pancotti, C., Benevenuta, S., Repetto, V., Birolo, G., Capriotti, E., Sanavia, T., Fariselli, P.: A deep-learning sequence-based method to predict protein stability changes upon genetic variations. Genes 12(6), 911 (2021) 8 [56] Pires, D.E., Ascher, D.B., Blundell, T.L.: Duet: a server for predicting effects of mutations on protein stability using an integrated computational approach. Nucleic acids research 42(W1), W314–W319 (2014) 3, 8 [57] Pires, D.E., Ascher, D.B., Blundell, T.L.: mcsm: predicting the effects of mutations in proteins using graph-based signatures. Bioinformatics 30(3), 335–342 (2014) 8 [58] Pucci, F., Schwersensky, M., Rooman, M.: Artificial intelligence challenges for predicting the impact of mutations on protein stability. Current opinion in structural biology 72, 161–168 (2022) 17 [59] Qiu, Y., Wei, G.W.: Persistent spectral theory-guided protein engineering. Nature Computational Science pp. 1–15 (2023) 3, 6, 17 [60] Rao, R.M., Liu, J., Verkuil, R., Meier, J., Canny, J., Abbeel, P., Sercu, T., Rives, A.: Msa transformer. In: International Conference on Machine Learning. pp. 8844–8856. PMLR (2021) 3, 9, 10 [61] Riesselman, A.J., Ingraham, J.B., Marks, D.S.: Deep generative models of genetic variation capture the effects of mutations. Nature methods 15(10), 816–822 (2018) 9 [62] Rives, A., Meier, J., Sercu, T., Goyal, S., Lin, Z., Liu, J., Guo, D., Ott, M., Zitnick, C.L., Ma, J., Fergus, R.: Biological structure and function emerge from scaling unsupervised learning to 250 million protein sequences. PNAS (2019). https://doi.org/10.1101/622803 3, 7 [63] Rodrigues, C.H., Pires, D.E., Ascher, D.B.: Dynamut: predicting the impact of mutations on protein conformation, flexibility and stability. Nucleic acids research 46(W1), W350–W355 (2018) 3, 8 [64] Rodrigues, C.H., Pires, D.E., Ascher, D.B.: Dynamut2: Assessing changes in stability and flexibility upon single and multiple point missense mutations. Protein Science 30(1), 60–69 (2021) 3, 4, 7 [65] Sanavia, T., Birolo, G., Montanucci, L., Turina, P., Capriotti, E., Fariselli, P.: Limitations and challenges in protein stability prediction upon genome variations: towards future applications in precision medicine. Computational and Structural Biotechnology Journal 18, 1968–1979 (2020). https://doi.org/10.1016/j.csbj.2020.07.011, https://doi.org/10.1016/j.csbj.2020.07.011 6, 17 [66] Savojardo, C., Fariselli, P., Martelli, P.L., Casadio, R.: Inps-md: a web server to predict stability of protein variants from sequence and structure. Bioinformatics 32(16), 2542–2544 (2016) 3, 8 [67] Schymkowitz, J., Borg, J., Stricher, F., Nys, R., Rousseau, F., Serrano, L.: The foldx web server: an online force field. Nucleic acids research 33(suppl_2), W382–W388 (2005) 3, 7, 8, 18 [68] Shroff, R., Cole, A.W., Diaz, D.J., Morrow, B.R., Donnell, I., Annapareddy, A., Gollihar, J., Ellington, A.D., Thyer, R.: Discovery of novel gain-of-function mutations guided by structure-based deep learning. ACS synthetic biology 9(11), 2927–2935 (2020) 3 [69] Starr, T.N., Thornton, J.W.: Epistasis in protein evolution. Protein science 25(7), 1204–1218 (2016) 1 [70] Steinegger, M., Soding, J.: Mmseqs2 enables sensitive protein sequence searching for the analysis of massive data sets. Nature biotechnology 35(11), 1026–1028 (2017) 6 [71] Stemmer, W.P.: Rapid evolution of a protein in vitro by dna shuffling. Nature 370(6488), 389–391 (1994) 2, 3 [72] Tsuboyama, K., Dauparas, J., Chen, J., Laine, E., Mohseni Behbahani, Y., Weinstein, J.J., Mangan, N.M., Ovchinnikov, S., Rocklin, G.J.: Mega-scale experimental analysis of protein folding stability in biology and protein design. bioRxiv pp. 2022–12 (2022) 1, 2, 6, 16 [73] Tung, J.W., Heydari, K., Tirouvanziam, R., Sahaf, B., Parks, D.R., Herzenberg, L.A., Herzenberg, L.A.: Modern flow cytometry: a practical approach. Clinics in laboratory medicine 27(3), 453–468 (2007) 1 [74] Umerenkov, D., Shashkova, T.I., Strashnov, P.V., Nikolaev, F., Sindeeva, M., Ivanisenko, N.V., Kardymon, O.L.: Prostata: Protein stability assessment using transformers. bioRxiv pp. 2022–12 (2022) 3, 4, 6, 7, 8, 18, 19 [75] Wittmann, B.J., Johnston, K.E., Wu, Z., Arnold, F.H.: Advances in machine learning for directed evolution. Current opinion in structural biology 69, 11–18 (2021) 3 [76] Wittmann, B.J., Yue, Y., Arnold, F.H.: Informed training set design enables efficient machine learningassisted directed protein evolution. Cell Systems 12(11), 1026–1045 (2021) 3 [77] Worth, C.L., Preissner, R., Blundell, T.L.: Sdm—a server for predicting effects of mutations on protein stability and malfunction. Nucleic acids research 39(suppl_2), W215–W222 (2011) 3, 8 [78] Wu, S., Snajdrova, R., Moore, J.C., Baldenius, K., Bornscheuer, U.T.: Biocatalysis: Enzymatic Synthesis for Industrial Applications. Angewandte Chemie - International Edition 60(1), 88–119 (2021). https://doi.org/10.1002/anie.202006648 1 [79] Yeung, N., Lin, Y.W., Gao, Y.G., Zhao, X., Russell, B.S., Lei, L., Miner, K.D., Robinson, H., Lu, Y.: Rational design of a structural and functional nitric oxide reductase. Nature 462(7276), 1079–1082 (2009) 1, 2 [80] Zhou, B., Lv, O., Yi, K., Xiong, X., Tan, P., Hong, L., Wang, Y.G.: Accurate and definite mutational effect prediction with lightweight equivariant graph neural networks. arXiv preprint arXiv:2304.08299 (2023) 3 [81] Zhou, Y., Pan, Q., Pires, D.E., Rodrigues, C.H., Ascher, D.B.: Ddmut: predicting effects of mutations on protein stability using deep learning. Nucleic Acids Research p. gkad472 (2023) 3

Predicting a Protein’s Stability
under a Million Mutations: Conclusion, Acknowledgement & References

This paper is available on arxiv under CC 4.0 license. Authors: (1) Jeffrey Ouyang-Zhang, UT Austin (2) Daniel J. Diaz, UT Austin (3) Adam R. Klivans, UT Austin (4) Philipp Krähenbühl, UT Austin Table of Links Abstract & Introduction Related Works Preliminary Methodology Results Limitations Conclusion, Acknowledgements, & References Experimental Setting & Additional Results 2 Related Works 2.1 Protein Engineering Protein engineering is the process of mutating a natural protein to improve particular phenotypes, such as thermodynamic stability and function. The field has historically relied on rational design and stochastic methods, such as error-prone PCR [1], DNA shuffling [71], and directed evolution (DE) [4, 27], to identify gain-of-function mutations. Rational design is limited to proteins with solved structures and requires an extensive understanding of biochemistry and specific knowledge of the particular protein to select mutations highly likely to improve the target phenotypes [33, 79]. Directed evolution requires little to no knowledge of the protein and instead generates a library of protein variants that are then screened for the target phenotypes (e.g. fluorescence brightness, antibiotic resistance, stability, activity) [4, 27]. The library can be generated via site-saturated mutagenesis of a handful of positions in the sequence [12] or DNA shuffling, in which the gene is digested into random fragments and reassembled into full-length sequences [71]. After screening the library, the most "fit" variant is then selected as the initial sequence for the next round of directed evolution. This iterative process repeats until it obtains a protein variant with the desired phenotypes. Machine learning has demonstrated its ability to augment rational design and accelerate the stabilization of a variety of proteins [20, 28, 40, 52, 68]. Separately, machine learning-guided directed evolution (MLDE)[75] has been shown to improve the likelihood of obtaining the global fitness maximum by 81-fold compared to traditional DE [76]. MLDE has accelerated the engineering of several proteins, such as the enantioselectivity of enzymes for kinetic resolution of epoxides [23] and the activity and expression of a glutathione transferase [46]. Mutate Everything empowers the experimentalist to accelerate the stabilization of a protein for both rational design and MLDE. 2.2 Machine Learning for Protein Structure Prediction Recent advances in machine learning have led to remarkable progress in protein structure prediction. AlphaFold [31] has demonstrated that deep learning is highly effective at predicting protein structures from a sequence by using evolutionary history via a multiple sequence alignment (MSA). AlphaFold passes the MSA and a pairwise representation of the sequence into Evoformer to capture the coevolutionary patterns between residues. The Evoformer output is then processed by the Structure Module, which predicts the protein’s structure. We challenge prior works postulating that AlphaFold cannot be used for stability prediction and show that fine-tuning these rich co-evolutionary and structural features yield highly performant stability predictors [53]. Evolutionary Scale Modeling (ESM) [38, 62] has shown that protein structure prediction can be performed without MSAs and specialized architectures by leveraging large transformers pre-trained on masked token prediction. Other works extended this masked pre-training framework, including MSA-Transformer [60] which incorporates a sequence’s MSA as input, and Tranception [49], which develops a hybrid convolution and attention based autoregressive architecture. We show that finetuning these evolutionary representations excels at protein stability assessment without MSAs. 2.3 Protein Stability Assessment Traditional approaches to protein stability assessment relied on a combination of physics-based methods, statistical analysis, and traditional machine learning techniques. Physics-based tools, such as FoldX, Rosetta, and SDM, utilize energy functions and statistical patterns to assess how mutations affect a protein’s stability [32, 67, 77]. DDGun [44] directly inferred ∆∆G from heuristics, including Blosum substitution scores, differences in interaction energy with neighboring residues, and changes in hydrophobicity. Many traditional machine learning approaches used support vector machines and decision trees with physics-based feature engineering [11, 14, 15, 17, 37, 66]. Others ensemble existing machine learning methods [35, 56, 59, 63, 64]. Recently, deep learning-based approaches have recently begun to outperform existing physics and traditional machine learning approaches [13, 19, 34]. ACDC-NN [6] trains an asymmetric convolutional neural network for predicting forward and reverse mutation effects. Thermonet [36] voxelizes and feeds both the wild-type and mutant protein structures into a 3D-CNN to regress a ∆∆G value. PROSTATA feeds the wild-type and mutant protein sequence into a pre-trained ESM2 model and then regresses a ∆∆G value [74]. Stability Oracle takes the native and mutant amino acid type along with the local structure as input and regresses ∆∆G [18]. Several deep learning frameworks [64, 80, 81] model multiple mutations in addition to single mutations. In this paper, we develop a framework that models the protein to enable efficient enumeration of all mutation candidates.

Predicting a Protein’s Stability
under a Million Mutations: Related Works

254 Stories To Learn About Healthcare

207 Stories To Learn About Health

196 Stories To Learn About Covid19

278 Stories To Learn About Covid 19

- that's what the experts say. And what is left for the naughty ones who want to efficiently search through a huge number of templates? "Don't use regular expressions, otherwise you'll have 2 problems instead of 1" Sure, there are cool solutions like or for this specific problem. However, for my project it seemed impractical to master these fine technologies for the time being. Ragel re2c In this article, we will look at alternatives to the standard regexp library in Go and benchmark them for speed and memory consumption. We will also consider the differences between them from a practical point of view. Analogues At the moment, I've found the following working alternatives to the default that can be used to find patterns in Go (the versions used in the benchmarks are given in brackets): regexp (1.3.0) - as simple as possible replaces the default regexp. Uses to improve performance when dealing with large inputs or complex expressions; go-re2 C++ re2 (1.10.0) - a feature-rich regexp engine for . It does not have runtime guarantees like the built-in regexp package, but is compatible with Perl5 and .NET; regexp2 Go (1.0.0) - provides support for compatible regular expressions using or . JIT compilation is available, making this fork much faster than its counterparts. On the downside, you'll need the dependency; go-pcre Perl libpcre libpcre++ libpcre3-dev (regex 1.9.3) - uses the regex engine with bindings. The downside is a library dependency that needs to be compiled; rure-go Rust CGo Rust (1.2.2 + hs5.4.1) - regex engine designed for high performance. It is implemented as a library that provides a simple . It also requires compilation and linking of third-party dependencies; gohs C-API - A tool for identifying and classifying malware samples. Although has functionality for templating and regular expressions, it is very limited, so I will not include this library in the upcoming tests. go-yara YARA Existing benchmarks Before we start comparing the aforementioned solutions, it is worth to show how bad things are with the standard regex library in . I found the where the author compares the performance of standard regex engines of various languages. The point of this benchmark is to repeatedly run 3 regular expressions over a predefined text. came in in this benchmark! Go project Go 3rd place From the end... Language Email(ms) URI(ms) IP(ms) Total(ms) Nim Regex 1.32 26.92 7.84 36.09 Nim 22.70 21.49 6.75 50.94 Rust 26.66 25.70 5.28 57.63 ... ... ... ... ... Python PyPy3 258.78 221.89 257.35 738.03 Python 3 273.86 190.79 319.13 783.78 Go 248.14 241.28 360.90 850.32 C++ STL 433.09 344.74 245.66 1023.49 C# Mono 2859.05 2431.87 145.82 5436.75 . From other benchmarks I can highlight the following: As far as I can tell, benchmarking regex engines is not the easiest topic, because you need to know implementation and algorithm details for a correct comparison - comparison of engines with optimized versions for each language. For example, is no longer at the bottom, but it is still far from ideal there... And of course it does not use a native library, but a wrapper over PCRE - , which was specified in analogues. Benchmarks Game Go go-pcre - Comparison of different regex engines (PCRE, PCRE-DFA, TRE, Oniguruma, RE2, PCRE-JIT). Performance comparison of regular expression engines - here the author tries to compare engines using different regular expressions, which can complicate things depending on the engine implementation. In this benchmark, the author's top three engines are: Hyperscan, PCRE (with JIT compilation) and Rust regex ( uses it): A comparison of regex engines rure Benchmark #1 Now let's try to compare the analogues with default regex engine libraries of other languages. And also see how much faster they are compared to the default . To do this, I updated the above project by adding new libraries code. Here is what I got after running it on my machine: Go regex Language Email(ms) URI(ms) IP(ms) Total(ms) Go Rure 2.61 2.11 3.33 8.05 C++ SRELL 1.74 3.03 10.67 15.45 Rust 11.66 1.70 5.13 18.48 Nim 13.98 14.35 3.13 31.46 PHP 14.43 14.63 4.87 33.93 Go PCRE 14.18 14.98 6.21 35.37 C# .Net Core 10.83 5.10 26.71 42.64 Javascript 42.78 30.17 0.92 73.87 Go Re2 35.81 37.86 33.79 107.46 Go Hyperscan 90.17 31.64 8.68 130.49 Perl 92.51 66.42 22.51 181.44 Dart 73.48 63.60 80.52 217.59 C PCRE2 110.87 100.57 10.50 221.94 Kotlin 120.31 163.53 293.69 577.53 Java 205.14 201.55 295.68 702.36 Python 3 246.26 176.01 303.08 725.34 C++ STL 328.87 273.43 230.35 832.64 Go 270.19 275.73 504.79 1050.71 Go Regexp2 1703.51 1482.60 64.46 3250.57 C# Mono 2543.82 2139.44 110.37 4793.64 . Ps. Shortened the table a bit, so please check the to see all the results. project fork Pss. In this case, virtualization might have affected the results (the tests were performed in a Docker environment on Windows 11). Still, you can see how much faster regexps can be with some libraries! We even outperformed Rust with a Go library that uses the Rust library 🥴🙆🏼‍♂️. Perhaps this is what the author of this solution is trying to explain to us in his . repository As a result, almost all alternative solutions give us a speedup of times! Except for , which turns out to be slower than the standard library. 8-130 Regexp2 Benchmark #2 Questions While studying the existing benchmarks and the results of , I was lacking the answers to the following questions: Benchmark#1 How fast do the above libraries process large files? How much faster is the processing when grouping regular expressions? How fast will regular expressions with no matches in the text be processed? How much memory do the different libraries use? How many regexps will I be able to compile using grouping? Benchmarker differences To answer these questions, I wrote a small benchmarking program that can be used to compare different regex engines in terms of speed and memory usage. If you want to test it yourself or evaluate the correctness of the used methods, here is the . code The following features of this benchmark are worth mentioning: In the tests below, I used different regular expressions: 5 allRegexps["email"] = `(?P<name>[-\w\d\.]+?)(?:\s+at\s+|\s*@\s*|\s*(?:[\[\]@]){3}\s*)(?P<host>[-\w\d\.]*?)\s*(?:dot|\.|(?:[\[\]dot\.]){3,5})\s*(?P<domain>\w+)`
allRegexps["bitcoin"] = `\b([13][a-km-zA-HJ-NP-Z1-9]{25,34}|bc1[ac-hj-np-zAC-HJ-NP-Z02-9]{11,71})`
allRegexps["ssn"] = `\d{3}-\d{2}-\d{4}`
allRegexps["uri"] = `[\w]+://[^/\s?#]+[^\s?#]+(?:\?[^\s#]*)?(?:#[^\s]*)?`
allRegexps["tel"] = `\+\d{1,4}?[-.\s]?$?\d{1,3}?$?[-.\s]?\d{1,4}[-.\s]?\d{1,4}[-.\s]?\d{1,9}` In a good way, I should have used tricky regular expressions, like other benchmark authors do - to check the "weaknesses" of the algorithms. But I don't have much insight into the under-the-hood details of engines, so I used general-purpose regexps. That's why I think it should be possible to evaluate different parameters of libraries from a practical point of view. Instead of a static file, we will use a string containing our matches, repeated many times in memory to simulate files of different sizes: var data = bytes.Repeat([]byte("123@mail.co nümbr=+71112223334 SSN:123-45-6789 http://1.1.1.1 3FZbgi29cpjq2GjdwV8eyHuJJnkLtktZc5 Й"), config.repeatScanTimes) In addition to running the regexps sequentially over the data, there will be a separate run with named grouping of regular expressions, where they will take the following form: `(?P<name_1>regexp_1)|(?P<name_2>regexp_2)|...|(?P<name_N>regexp_N)` By the way, Hyperscan has a special functionality where we can build a database of regexps and use it against data. In the benchmarks I will use this method. Unlike in , for each regexp I will measure the time to find the result, without taking into account the compilation time; Benchmark#1 In the end, we will get the results for each library and each regexp in the following form: Generate data...
Test data size: 100.00MB

Run RURE:
  [bitcoin] count=1000000, mem=16007.26KB, time=2.11075s 
  [ssn] count=1000000, mem=16007.26KB, time=62.074ms 
  [uri] count=1000000, mem=16007.26KB, time=69.186ms 
  [tel] count=1000000, mem=16007.26KB, time=83.101ms 
  [email] count=1000000, mem=16007.26KB, time=172.915ms 
Total. Counted: 5000000, Memory: 80.04MB, Duration: 2.498027s
... 1-2. Processing large files and grouping regular expressions By "large file" I mean the amount of data generated from our predefined string in memory equal to . Of course it's hardly a big file, but I didn't want to wait hours for results in some cases 😅. 100MB Also, it makes sense to try grouping all regular expressions into one and see how much it affects performance. The hypothesis is that a sequential run of regexps over the data should take longer than a single run with a grouped regexp. Well, let's run the benchmark and see how fast each library processes the data. You can do this with my tool as follows: # Bench all libs, repeat the line 1000000 times (100MB)
regexcmp 1000000 
# Bench individual lib
regexcmp 1000000 rure
# See all options
regexcmp -h As a result, we have the following data: Lib Email Tel URI SSN Bitcoin Total Total-group Rure 0.173s 0.083s 0.069s 0.062s 2.11s 2.49s 10.13s PCRE 49.5s 0.367s 2.92s 2.07s 2.19s 57.07s 9.94s Re2 0.954s 0.63s 0.956s 0.945s 1.05s 4.54s 3.24s Hyperscan 0.469s 1.09s 0.669s 0.174s 1.97s 4.38s 4.97s Regexp2 126.4s 1.02s 21.51s 2.63s 3.38s 154.9s 20.65s Go regexp 11.22s 1.52s 3.62s 2.66s 3.32s 22.36s 26.49s The plot below shows the processing time of 100MB of data by all regexps in sequential mode and using grouping: : Conclusions Grouping can indeed significantly improve execution speed, but in some cases it can make it worse :); The fastest in sequential processing turned out to be - , with grouping - ; Rure Re2 Certain regexps may cause problems with some libraries (time to find in and ); email Regexp2 PCRE Now it is hard to say that some solutions are 180 times faster than the standard library, the maximum gain is . x8-9 3. Non-matching regexps In the previous case, we simulated the ideal situation where there are always matches in the data. But what if there are no hits for regexp in the text, how much will that affect performance? In this test, I additionally added modified regexps for SSN that do not match the data. In this case, means regexp, and - . Not a big difference? But let's see how it affects the time it takes to find all the matches: 5 SSN \d{3}-\d{2}-\d{4} Non-matching \d{3}-\d{2}-\d{4}1 Lib SSN Non-matching Total Total-group Rure 0.06s 0.083s 2.93s 15.68s PCRE 2.06s 4.21s 81.02s 13.52s Re2 0.960s 0.449s 6.75s 3.26s Hyperscan 0.175s 0.043s 4.61s 4.94s Regexp2 2.73s 3.09s 171.1s 15.72s Go regexp 2.66s 2.57s 35.13s 37.66s The plot below shows the time taken to process all regexps, sorted by processing time: 10 Non-matching : Conclusions This time is the same: the fastest in sequential processing was - , with grouped expressions - ; Rure Re2 is once again different, with time to process regexps in sequential mode; PCRE 2x non-matching Some algorithms are much faster when there are no matches ( , ); Re2 Hyperscan 4. Memory consumption Now let's see how much memory the different solutions consume when processing a 100MB file. Below, I have provided the results for each individual regexp and the total amount of memory consumed: Lib Email, MB Tel, MB URI, MB SSN, MB Bitcoin, MB Non-matching, KB Total, GB Total-group, GB Rure 16 16 16 16 16 0.0001 0.08 0.08 PCRE 186 186 186 186 186 0.38 0.93 0.9 Re2 254 254 254 255 254 100473 1.77 0.97 Hyperscan 314 314 314 314 314 0.68 1.57 1.7 Regexp2 997 854 854 854 902 396006 6.44 5.23 Go regex 191 144 144 160 208 3.62 0.78 1.8 The graph below shows the memory used by the libraries to process regexps (as in the last test), sorted by the time of `non-mathcing': 10 Conclusions: surprises with its practically zero memory consumption; Rure is resource hungry, consuming significantly more memory than its competitors; Regexp2 , despite its speed, is not the most memory-efficient solution; Re2 is on the good side, with relatively low costs in sequential mode. Go regex 5. Maximum number of regexps The main questions seem to be answered. Now let's see the maximum number of regexps we can compile with different solutions. In this case we will take a single regexp and repeat it many times in groups. For this purpose I will use the regexp: URI `[\w]+://[^/\s?#]+[^\s?#]+(?:\?[^\s#]*)?(?:#[^\s]*)?` Next, I've listed the results of compiling the regexps, along with the memory they use. The numbers in the first line are the number of expressions in the group: URI Lib 100 250 500 1000 5000 10000 Rure 0.38MB ❌ ❌ ❌ ❌ ❌ PCRE 0.40MB 2.37MB ❌ ❌ ❌ ❌ Re2 7.10MB 15.51MB 38.35MB 92.79MB 1181MB ❌ Hyperscan 0.03MB 0.06MB 0.12MB 0.25MB 1.21MB 2.52MB Regexp2 1.06MB 3.96MB 12.56MB 43.93MB 926MB 3604MB Go regex 1.29MB 4.52MB 14.02MB 47.18MB 942MB 3636MB : Conclusions As we can see, some solutions have limitations on the size of compiled regexps; not only allows to use a large number of regexps, but also uses minimal memory for compiled regexps; Hyperscan and have comparable memory consumption and also allow to compile a large number of regexps; Regexp2 Go Regex consumes the most memory at compile time. Re2 Conclusion I hope it was useful for you to learn about alternative solutions for regexps in , and based on the data I presented, everyone will be able to draw some conclusions for themselves, which will allow you to choose the most suitable regex solution for your situation. Go We can compare these libraries, the algorithms they use, their best/worst sides in details and for a long time. I just wanted to show the difference between them in the most general cases. Thus, I would advise you to look at for maximum speedup of regexps, but if you need the easiest library installation without dependencies, that is . And in the case of handling a large number of regexps would be a good choice. Also, don't forget the cost of using in some libraries. rure-go go-re2 hyperscan CGo As for me, I will definitely use these "findings" in my future :). project

Best Regexp Alternative for Go; Benchmarks and Plots

Nowadays, implementing full-text search is one of the most important parts of application development. In applications that rely heavily on search functionality, such as music services or online stores, the configuration and customization of answer ranking is vital. In order to better understand why you need to implement such a solution, let's consider the problems in its absence Enhancing Search Functionality Often developers are tasked with improving search in an application, and in many cases, quite a lot of time is spent putting together a clear set of refinements for the project. Common tasks to improve search might include the following: Speeding up search performance Add error tolerance Add the ability to search beyond the item name Add the ability to search by words not necessarily in the same order Add the ability to search other forms of words from a query Add the ability to manage search rules for the same word with different values Evaluation Criteria The main criteria for evaluating search performance can be defined as the speed of response, completeness and accuracy. While response rates can be easily measured and evaluated, the other two are a bit more difficult to calculate. Search completeness is the result of dividing the number of items returned by the number of matching items. When solving a problem of the first kind, with the exclusion of matching items, the problem of an incorrect query with an error or typo is often solved as well. The precision of the search is the result of dividing the number of matching items in the answer by the number of items in the answer. Those items that made it into the answer, but should not have, are called errors of the second kind. Accordingly, we need the fastest answer, with the highest percentages of completeness and search accuracy. The balance between these elements is unique to each project. Let's try to consider possible solutions to this problem without implementing full-text search. Attempting a solution via SQL LIKE The simplest solution may be the use of LIKE in SQL. If you try to implement this search on several fields, the query can look like this: SELECT p.id,
  p.title,
  p.image,
  u.name,
  p.created_at
FROM posts p
JOIN users u ON p.author_id = u.id
WHERE p.title LIKE '%query%'
  OR p.text LIKE '%query%'
  OR u.name LIKE '%query%'
  OR u.email LIKE '%query%'; However, this is far from the most optimal variant and if the records in the posts table are more than 1000, then even considering that the indexes are set, the queries will still be processed on the verge of timeouts. Furthermore, this type of query is appropriate solely for addressing a specific task, where all fields are utilized in the search. However, other tasks, notably rearranging the word order within the query, prioritizing elements, and enhancing the query's search speed, remain largely unresolved. Full-text search in PostgreSQL/MySQL The second solution with the existing set of tools in the application can be to use the full-text search features of PostgreSQL and MySQL. In this case, the query will be of the following form: SELECT ... MATCH (field) AGAINST ('word'). The decision to use SQL gives us 100% accuracy and completeness of search but also has a large number of disadvantages. Among them are the need for constant customization of the database and limitations on the type of fields and lack of ranking, as well as the final cost of such a solution. Laravel Scout To solve all of the above problems there are special services that quickly produce full-text search and solve problems with tokenization and morphological analysis. Laravel Scout allows you to work with many of these services and provides a unified interface for working with search, as well as linking entity search with Laravel models. Below is a list of popular tools that work with full-text search. Bolded are those tools that have a driver to work with Laravel Scout. Underlined are those that have such a driver out of the box. ElasticSearch Apache Solr Sphinx Algolia MultiSearch MeiliSearch The principle of working with full-text in Laravel does not differ much depending on the driver. I chose Algolia to demonstrate how it works. Laravel Scout makes it easy to add data to the Algolia index and just as easy to retrieve it from there by searching many fields. Of course, when choosing any vendor, your project will acquire a dependency that needs to be kept in mind. Laravel Scout will help make the dependency less, thanks to its interfaces. Customization Features To customize Algolia, we need to download the algolia/algoliasearch-client-php package. and set the id and secret from your application to Algolia. This is all we need for Algolia and our application to work and communicate properly. It's also worth noting that for the production solution, we need to add full queue support, as under the hood, when updating data in the selected service asynchronously, that can speed up the search performance a lot. Let's consider our further actions with full-text search on the example of Algolia. Working with full-text search on Algolia Service Algolia is partially free, but its minimum free package is probably not enough for any popular site. The important thing to emphasize is that if you choose other options that will run on your servers, such as the popular , the server, and support costs can easily overlap the cost of using Algolia. ElasticSearch After creating the application and adding credentials to the .env file and customizing the cache, we need to connect the Searchable trait to the models we need. After that the standard customization is complete, however, in some cases, we need to add a few customizations. Additional settings For example, in the model, we can specify which fields we will stack in Algolia using the method toSearchableArray() public function toSearchableArray(): array
{
   return [
       'id' => $this->id,
       'title' => $this->title,
       'author_id' => $this->author_id
   ];
} Also, if the primary key of our model is not id, we can change it and add its name, for example, this way: public function getScoutKey(): string
{
   return $this->title;
}


public function getScoutKeyName(): string
{
   return 'title';
} Laravel Scout also has the option to set the search engine to search separately for each model using the method. searchableUsing() Indexing records Most often, full-text search is implemented in a project after a large number of records have appeared in the project. In order to index these records in Algolia we need to use the command . php artisan scout:import "App\Models\Post" You can also add special conditions or related models when indexing using the method if needed. After indexing, you can see the indexed records in Algolia in an index formed by the same principles as the table name in migrations i.e for Post, there will be posts. makeAllSearchableUsing() If you see the records here, the indexing was successful. Further adding and updating of indexed records will happen automatically as Laravel Scout listens to events in the model. It is also possible to add and modify indexes via a method to the Builder or to the Collection that contains the Model objects Post::where('id', '>', 100)->searchable(); Or $user->posts()->searchable();
//OR
$posts = Post::where('id', '>', 100)->get();
$posts->searchable(); For the last case, we can specify additional links using a separate method makeSearchableUsing() If we need to limit the records that should be included in the index when using or , we can apply the method save() update() shouldBeSearchable() public function shouldBeSearchable(): bool
{
   return $this->status === 'published';
} Deletion To remove records from the index, simply use the method for the same Model, Builder, Models Collection, and relation entities. Also in Laravel Scout, you have the option to enable SoftDelete, so that deletion from the database is not so critical. unsearchable() Search Finally, we get to the most important thing - checking that our full-text search works. In order to test this, we can use the method. search() Post::search('repudiandae')->get(); Also, our model can be in several indexes at the same time for different checks. In this case, we specify the index in the method. within() Additionally, Scout search has the ability to use pagination through the method, as well as to use simple checks in . Thus a query can look like this: paginate() where() Post::search('repudiandae')
   ->within('another_index_with_posts')
   ->where('author_id',  $authorId)
   ->paginate(15); Customizing search The search method searches all fields by default. To change this, you need to specify the list of fields in the index that should be checked. already has error tolerance by default, but this can also be changed in the Typo-tolerance tab. As you may have noticed in the previous screenshot, there are a large number of full-text search settings. Algolia Often, to properly handle customization, Algolia requires a clear set of rules that determine which element to reflect above. You can also configure stop words or set up context for certain words and queries. Once full-text is implemented, there is supposed to be a lot of ongoing work to tune it to continually increase the completeness and accuracy of the search. To understand why the tool selected a particular element and why one is higher and the other lower, you can use the method instead of . raw() get() Conclusion As we have seen today, implementing is an important task for a large number of projects, but the initial setup may not take much time. Implementing search right away will give a big boost in search performance and search efficiency. The important issues in this matter are the choice of tool and the subsequent customization iterations. full-text search

How to Implement Full-text Search in a Laravel Project

In the ever-evolving landscape of cyber threats, ransomware has proven to be one of the most notorious and damaging forms of attack. Among the various ransomware variants, RagnarLocker has garnered significant attention for its sophisticated tactics and impact on critical infrastructure sectors. In this blog post, we delve into the world of RagnarLocker ransomware, exploring its indicators of compromise (IOCs), technical intricacies, and the havoc it wreaks on targeted systems. 💥🔓 Ransomware Strikes Israeli Hospital: Ragnar_Locker Takes Responsibility 🏥 In a chilling turn of events, RagnarLocker’s menace struck closer to home as it targeted Mayanei Hayeshua Medical Center in Bnei Brak, Israel a few days ago. The ransomware attack wreaked havoc on the hospital’s administrative computer systems. The aftermath was devastating — medical treatments were disrupted, and the emergency room was compelled to redirect patients to other hospitals for urgent care. Emerging from the chaos, Ragnar_Locker took responsibility for this audacious attack. However, I’ve made a detailed investigation that yielded no signs of any leaked data or information on the group’s Onion site or Telegram group. This marks an unusual departure from the norm, where cybercriminals often flaunt their exploits on such platforms. This incident serves as a grim reminder of the vulnerabilities lurking in critical infrastructure sectors, with healthcare being no exception. It underscores the pressing need for fortified cybersecurity measures to shield essential services from such malicious onslaughts. As the investigation into this unsettling event progresses, the global cybersecurity community will undoubtedly be closely monitoring further developments. 🌐🔒🦠 The Emergence of RagnarLocker 🌄💻 The first traces of RagnarLocker ransomware came to light in April 2020, catching the attention of cybersecurity experts and organizations worldwide. Notably, the Federal Bureau of Investigation (FBI) issued an initial report detailing known IOCs associated with RagnarLocker. Over time, this ransomware variant has evolved, refining its obfuscation techniques and evading traditional detection methods. 🚀🔍 A Persistent Threat 🎯🌐 As of January 2022, the FBI has identified over 52 entities spanning across 10 critical infrastructure sectors affected by RagnarLocker ransomware. These sectors encompass critical manufacturing, energy, financial services, government, and information technology, underscoring the ransomware’s indiscriminate targeting. 💼🏢🔒 Technical Insights 🔍💡 Ransom Note and Identification: RagnarLocker is recognizable by the “.RGNR_<ID>” extension appended to encrypted files. The actors, self-identifying as “RAGNAR_LOCKER,” accompany this extension with a .txt ransom note, containing instructions for payment and data decryption. 💰🔐📄 Advanced Packing Techniques: The ransomware employs advanced techniques like VMProtect, UPX, and custom packing algorithms, adding layers of complexity to its execution. This obfuscation serves to complicate detection efforts. 🧩🔒🔍 Geographical Targeting: RagnarLocker uses the Windows API GetLocaleInfoW to identify the infected machine’s location. If the victim’s location falls within certain geopolitical areas, the ransomware terminates its processes, potentially hinting at the attackers’ geopolitical motivations. 🗺️🌍🔍 Selective Encryption: Instead of opting for a widespread encryption approach, RagnarLocker selectively encrypts files. It designates folders it won’t encrypt, allowing the system to function “normally” while encrypting files with valuable data. This method minimizes disruptions while maximizing the potential payout. 📁🔒🤖 Before encryption, Ragnar Locker spawns the following child processes: This system command deletes all shadow copies on the victim’s system, preventing data recovery by the victim : wmic.exe shadowcopy delete This system command also deletes shadow copies, preventing data recovery by the victim : vssadmin delete shadows /all /quiet This command launches Notepad.exe to show the ransom note to the victim. : notepad.exe [User path]\RGNR_AABBCCDD.txt After the ransom note is created, the actual file encryption process initiates using the __ __algorithm. It excludes files ending in . Salsa20 db, .sys, .dll, lnk, .msi, .drv and .exe. Neutralizing Defenses 🛡️🚫 Service Termination: RagnarLocker goes a step further in its attack strategy by identifying and terminating services commonly used by managed service providers (MSPs) for remote network administration. This further hampers recovery efforts. 💔🔧 Shadow Copy Deletion: Preventing victim recovery efforts, the ransomware erases Volume Shadow Copies, a mechanism used to restore files to previous states. The malware employs various methods, including >vssadmin delete shadows /all /quiet and >wmic.exe.shadowcopy.delete. 🗑️🔮 Conclusion 📢🔐 RagnarLocker ransomware presents a multifaceted threat that combines advanced technical techniques with an intricate attack strategy. Its evolution since its discovery in 2020, along with its targeting of critical infrastructure sectors, underscores the urgency of bolstering cybersecurity measures to defend against this and similar threats. As organizations and security experts continue to dissect RagnarLocker’s mechanisms, it becomes increasingly evident that the fight against ransomware demands a proactive and collaborative approach, where vigilance and innovation go hand in hand. 🛡️🌐🔒 References: https://www.timesofisrael.com/liveblog_entry/bnei-brak-hospital-bracing-for-release-of-sensitive-patient-information-after-hack/ https://www.ic3.gov/Media/News/2022/220307.pdf https://www.linkedin.com/showcase/dailydarkweb/ https://www.pcrisk.com/removal-guides/17018-ragnar-locker-ransomware Also published . here

Uncovering Ragnar_Locker Ransomware: Exploring IOCs

Does Google’s Ad Business Fund Disinformation? The Truth

After the global population went through a pandemic and was in lockdown,  the silver lining finally arrived. All the innovations created in this period have been helping reshape the world as we know it, and in this specific case, Finland has invested in healthcare that can aid us in the future. And so, in this slogging thread, we discussed what other ways technology has helped the community get back to normal after dealing with the virus. This Slogging thread by Sara Pinto, Jack Boreham and Mónica Freitas occurred in slogging's official #technology channel, and has been edited for readability. Sara Pinto Mar 22, 2022, 11:38 PM How can tech reshape the post-pandemic world? https://www.med-technews.com/news/Medtech-Diagnostics-news/how-finnish-innovations-are-helping-reshape-the-post-pandemi/ Sara Pinto Mar 22, 2022, 11:39 PM " Finnish health tech innovations and solutions are part of the diagnostic technology and applications that are reshaping healthcare as we emerge into a post-pandemic world." Sara Pinto Mar 22, 2022, 11:39 PM "From platforms that provide digital processes to shorten patient backlogs and manage staff time more effectively, personal monitors that help people take control of their own health, and a COVID-19 vaccine administered directly into the nose, that can be developed to use against future pandemics, Finnish innovations are leading the way in ground-breaking global health technology and solutions." Sara Pinto Mar 22, 2022, 11:40 PM "COVID-19 and the latest wave of Omicron have resulted in global demand for diagnostic innovations and applications. As we emerge from the pandemic, people are increasingly taking control of their health, and patient and home monitoring devices developed in Finland are helping to empower a healthier life for many." Sara Pinto Mar 22, 2022, 11:41 PM With the pandemic getting under control, we search for ways to get back to our old life. In this case, Finland companies have invested in solutions regarding healthcare. Sara Pinto Mar 22, 2022, 11:42 PM Jack Boreham Abeer Limarc Ambalina, in which ways did technology help you get back to normal? Jack Boreham Mar 24, 2022, 11:59 AM Sara PintoGaming has always been a focal point for me; I use it as a normalization tool. It's a great way to relax and connect with friends. I know Limarc Ambalina will agree. Likewise, I used to play cod with Limarc during our meetings (we still need to do this!) But great times, gaming normalizes things! Sara Pinto Mar 25, 2022, 8:36 PM Jack Boreham, that's a great way to make things a little more natural in difficult situations. Gaming is a good communication tool, and it's definitely a way to bring us closer! Mónica Freitas Apr 1, 2022, 1:11 PM Sara Pinto a vaccine administrated through the nose?! That's interesting. Mónica Freitas Apr 1, 2022, 1:13 PM Sara Pinto for me it was the SNS (national health system) app. It made a lot of things easier, especially during the pandemic. We can access a lot of data with just one app, when before it was a nightmare to have all our medical info. Sara Pinto Apr 9, 2022, 1:38 PM Mónica Freitas, I thought so too! The way we adapted and innovated during the pandemic was extraordinary 🔥 1 Sara Pinto Apr 9, 2022, 1:39 PM Mónica Freitas, I agree. Everything is more transparent and reachable. Most of the stuff you need to know in your appointments, you can find there. It was really useful Mónica Freitas Apr 11, 2022, 10:04 AM Sara Pinto it must be painful though. Being hit with a needle in your nose... PCR tests already hurt, let alone a needle 😂 😂 1 Mónica Freitas Apr 11, 2022, 10:06 AM Sara Pinto and it's such a big difference from how it used to be. We used to have these notebooks with all of our vaccine records and all. I don't even know where that is anymore. So the app makes it 10x better! And I feel like it even makes it easier for health professionals. Sara Pinto Apr 11, 2022, 4:02 PM Mónica Freitas, exactly. It was an outdated system. We had to hold on to so many papers. It became messy. I definitely think it helped both parties. I hope they keep investing in the app Mónica Freitas Apr 13, 2022, 2:39 PM Sara Pinto same and I hope they'll make it easier to access for everyone, specifically older people that don't really get tech

How Can Tech Reshape the Post Pandemic World?

So here we are, on our beautiful earth. Chemtrails in the sky, floride in the water, mandatory vaccines that don’t work, a f , war in Ukraine, soaring oil prices, , GMO food, declining standards of living, higher taxes, fiscal mismanagement, that never stops despite the revelations, and much more besides. ailing airline system 24/7 digital surveillance pharmaceutical warfare And that’s just what has been publicly exposed. What Is The New World Order And One World Government? The terms “New World Order”, “One World Government”, and “Great Reset” are more or less interchangeable. You don’t need a PHD in political theory; it means greater control and domination for those in charge. What we have got, except even worse. It’s the difference between the super centralized internet and the decentralized internet. Conceivably, we will have a global currency with everything tracked and monitored, with all transactions linked on a blockchain and tied to location. Any contrary ideas can result in a suspension of your finances. And there won’t be any independent media to complain to. Justin Trudeau has, by the way, effectively . socialized all independent media The New World Order essentially means super centralization with a lack of transparency for those on the bottom, but ultimate transparency for those on top, who can see everything. If the controllers can tie transactions to individuals, they can then harass and enslave individuals. This is why they are so fanatical about KYC and compliance in the realm of Web3. And this is why the decentralized, anonymous, Web3 internet is so important. While the decentralized internet promises interoperability and privacy, the New World Order promises interoperability and domination. It’s the difference between being able to access everything securely, and being able to access everything once you sign your rights away. Why I’m Excited About The New World Order Despite appearances, the New World order has a 0% chance of succeeding in its current Orwellian format. We have already won, though few realize this fact. The (True) New World Order is already being built on the decentralized internet of distributed ledgers. And you and I are the ones who are both users controllers. and The farce that we have all been witnessing on television paints a certain picture, but innovations within Web3 portray quite another. We are building our own financial system, our own governance systems, our own education systems, and our own media systems. All without compromising on the personal information of users. It’s all optional and transparent. The penny has not yet dropped for most people, but we are literally building a new planet, and the ongoing scandals are necessary to push more people towards blockchain and the decentralized internet. People don’t move unless pushed; that's a sad but accurate fact of human existence. The Orwellian New World Order takes its power from a centralized internet. The True New World order takes its power from the decentralized internet. The Benefits Of A Sovereign Planet As a digital nomad of 10+ years, I have had significant frustrations due to legacy government systems. I’ve got of sim cards, with lots of pin codes. I’ve also filled out of visas, waited in a lot of queues, and lost no small number of bags. a lot a lot Losing a passport is not fun either, nor is theft or getting your card blocked. Then there is the annoying cost of currency exchange, and the ATM charges. Some countries, like India, have a poor ATM infrastructure and you have to walk miles for cash, then wait in a queue. This was the vaccine/PCR test fiasco, which adds to the stress considerably. before What has all this got to do with the decentralized internet and the New World Order? Everything. Actually, the core ideals of the New World Order are applicable from the perspective of efficiency. The issue is that there happens to be a bunch of delusional zealots that have strange notions about planetary governance. The reality is that an international planet makes . Think about it. One phone number, one generally accepted cryptocurrency, a digital passport that cannot be lost; the benefits are huge. It would save on quite a lot of bureaucracy and make travel easier and cheaper. a lot of sense And I believe this is where we are heading. Imagine being able to book an affordable no-bulls*** flight to a different country with reliable luggage tracking and fast boarding. Moreover, the login code to your apartment would also be tied to a digital key, making the rental process a lot smoother. A Global Upgrade Aside from personal convenience, of course, is being able to prevent individuals making decisions that the public are clearly opposed to. The world government recently shut down all business for 2 years in response to a , putting draconian (and largely unconstitutional) measures in place. hugely exaggerated virus Regardless of your ideological position, these measures were swift, far reaching, and not subject to any sort of individual consent or alternative opinion. In other words, it’s a precedent to follow. Because the centralized powers can define the terms of what constitutes a crisis and then mandate lockdowns based on a definition not subject to scrutiny. It’s a closed door system. terrible I’m also not convinced that one man should be able to put a nation at war with another, as has happened throughout history and as recently as earlier this year with the . Ukraine invasion Given that tens of thousands of men will have to fight, why should tens of thousands of men not be able to vote? A New World Order Based On A Decentralized Internet There will be a One World Government and  a New World Order. The One World Government shall consist of more than 7 billion people who cast their vote through crypto staking and other mechanisms. Each individual nation can vote to join the wider international nation, with strict bottom up control. The decentralized internet is the means to facilitate the birth of the True New World Order. Despite the repeated attempts to control and the ecosystem, it is anti-fragile and censorship resistant. All that is required is global and active participation by Earths residents. Passivity is what got us in this mess. Action will get us out. only attack Imagine if the United Nations actually consisted of nations that were united? The idea is wonderful, though the implementation is clearly corrupted. With the assistance of distributed ledgers where all decisions are subject to review by the many, this dream can become a reality.

Why I Dream Of A One World Government & New World Order

Por qué sueño con un gobierno mundial único y un nuevo orden mundial

Pourquoi je rêve d'un gouvernement mondial et d'un nouvel ordre mondial

मैं एक विश्व सरकार और नई विश्व व्यवस्था का सपना क्यों देखता हूं

私が世界統一政府と新世界秩序を夢見る理由

Por que eu sonho com um governo mundial e uma nova ordem mundial

Tại sao tôi mơ về một chính phủ một thế giới và trật tự thế giới mới

为什么我梦想一个世界政府和新的世界秩序

Since the start of the pandemic, covid-19 tests have become an integral part of many peoples’ routines in different countries. It has been the main resource to keep communities safe and restore normal business and leisure activities. eyeson and Rex Solutions joined forces to address the increased need for covid tests and mitigate costs and time involved. Making tests easily available unlocks activities, relieves stress and helps normalize business and leisure activities that are otherwise restricted. An easy and quick solution for covid-19 online testing The covid-19 app project presented several requirements such as easy access, traceability and tamper-proof storage of the video recordings for examination purposes. With only one integration on all devices, eyeson merges all participants, media & live data into one video stream in the cloud to guarantee constant low bandwidth to all devices and clients (max. 1 Mbits up/max. 1.5 Mbits down). It is this technology that enabled an easy and reliable setup for conducting the online PCR and Antigen tests. The implementation was made possible with 2 elements As the development partner, Rex Solutions showed notable authority and adaptability. They needed to accelerate development and implementation processes but had to consider that the eyeson SDK wasn’t yet released. The Rex Solutions mobile app is in React Native and for the video implementation, the solution came from the developers. In native mobile apps, any website interface can be shown by using the react native web view library. So two elements were needed to be implemented to embed it in the solution: the webserver deployment of the eyeson implementation and the react native web view. eyeson provides a JavaScript library to help developers add their API easily to their projects. Rex Solutions used the React Native developer framework that combines universal JavaScript frontend components with native code on multiple platforms including iOS and Android-based mobile devices. For the front-end, the JavaScript-based open-source front-end web framework Angular.js was used. With Angular.js, dynamic and interactive web apps can be efficiently built. To integrate video communication functionality eyeson provided a JavaScript library to easily integrate with the other components. The web pages are managed by a web server where everything needed to manage the video recording is implemented. Specific actions were created as “Start the recording”, “start the stopwatch”, and “stop the recording” as well as instructions to create and join the virtual rooms. Moreover, this solution’s implementation allows sending streaming data to eyeson by using the library and also calling the REST APIs to store streaming responses in Rex Solution’s database. Enabling user authentication on web and mobile applications Developers used the web view library to keep user authentication on the web since in native mobile applications they are passing the user authentication and booking details data to the web server by using URL. The web server initiates a new session to keep the validity of the user by fetching user authentication data from this URL. Alert messages and guiding steps were also needed in the case of the covid tests where users have to follow a specific procedure and wait a specific amount of time to receive the results. The next challenge was to be able to view and listen to the alert messages from the webserver in mobile apps. For alert messages like the ringing notification after 15 minutes of recording, developers used the concept of , as on both sides there was the advantage of JavaScript/typescript programming languages. JavaScript injection is a technology leader in cloud-based video communication. eyeson provides an API video service to easily integrate live video including live media, data and participants into any kind of use-case based on its unique patented single stream technology. To secure customers performance eyeson offers the service to manage cloud capacity, scalable video coding performance and data management. eyeson provides browser-based video integrations on all desktop and mobile devices. eyeson Also Published here

Building an Online Covid Testing Application Using Eyeson

The major recent breakthroughs in diagnostics and treatment. Even 50 or 70 years ago, personalized medicine existed solely as the talking point of science fiction writers and scientific visionaries. However, as genetic technologies emerged, the individual approach to diagnostics and therapy of many hereditary and incurable diseases became a routine or at least a common solution. These diseases include various cancer types, autoimmune disorders, and numerous orphan (i.e., rare) pathologies. Although such developments are infamous for their high (sometimes exorbitant) costs, they can no longer be considered unavailable. Genomics and molecular genetics have laid the groundwork for a complete overhaul of the healthcare system, following the P4 principle[1] where both personalization and predictability play pivotal roles. It is becoming possible to detect genetic predisposition to a disease before conception, prevent an illness during pregnancy, learn about individual genetic specifics, and define a personal healthy lifestyle. This market is on the upturn: Mordor Intelligence marketing agency forecasts that these services will develop most intensively in Asia-Pacific countries. Europe and North America also demonstrate a slightly lower yet constantly growing demand, while Russia, Africa, and South America are falling behind .[2] These changes are expected to revolutionize medicine and shift the focus from disease treatment to health preservation. For patients with orphan and cancer diseases, gene therapy already gives a chance to get a cure. Given the overwhelming amount of global research, this therapy will soon become the ultimate method of treating other non-infectious diseases that cause early death or disability and have a detrimental effect on the quality of life. In this article, I will provide an overview of major genetic technologies in medicine that proved their effectiveness and became part of clinical practice, as well as of new developments at the final stages of their trials. Genetic testing: finding the “weakest link” of a malignant tumor The late 1990s were the milestone of cancer diagnostics, as genetic information on mutations became the starting point for specifying a targeted therapy. 3] [ Every tumor has its specific mutations, its gene "breakdowns" that the targeted effect of medication seeks to cope with. For example, the information on BRCA1/2 mutation helped establish a targeted breast cancer treatment and prevent this disease among the patient's relatives. Eventually, this experience has converted into the list of most common disorders, both hereditary and acquired, with molecular gene testing becoming a must of all medical guidelines and changing the course of pharmaceutical development. There is a gradual shift from developing medications against specific nosologies to adopting the target concept. For instance, the translocation of the NTRK gene can be found in different tumors but can be effectively treated by the same drug. Although this mutation is rare (found only in 1% of all tumors), its therapy can provide a positive response in 80% of all cases. 4] [ At first, "damages" in tumor tissues and the blood were diagnosed using low-effective methods that enabled the study of small DNA sequences, such as polymerase chain reaction (PCR) and Sanger sequencing, known since the 1970-the 1980s, and fluorescence in situ hybridization (FISH) of the 1990s. These tools were of great assistance, helping patients with solid tumors to avoid a needless or mismatching therapy and get a significant clinical effect; besides, oncohematology patients got an alternative to expensive procedures like marrow transplants. Nowadays, attempts are made to apply gene testing for specifying the diagnosis and even predicting the treatment efficiency. Another breakthrough happened in the 2010s: the Next Generation Sequencing (NGS) technology made it available to check the whole genome for damages. Here is the classic example of this method's capacities: it took over a decade and 3 billion dollars from the US budget to complete the Human Genome Project that described 3 billion DNA nucleotides using the standard tools. Meanwhile, the NGS sequenator can reveal the whole genome sequence in less than a year, at the cost of several thousand dollars. 5] [ Higher speed (several days compared to weeks and months) and fewer expenses are the self-evident advantages offered by the NGS. What is also important, this is almost the only way to collect more data from a smaller amount of material, e.g., from the blood plasma. Thanks to the NGS, liquid biopsy could provide information on potential mutations of up to 400 genes and has been approved for use against non-small-cell lung arcinoma and metastatic castration-resistant prostate cancer. Besides, the NGS makes it possible to perform population screenings and reveal various hereditary mutations, including breast cancer. Scientists believe that in high— or medium-income countries, it is easier and less expensive to test all women above 30, even those without family anamnesis, and then perform additional radiology diagnostics for the mutation carriers .[6] There is only one problem with the NGS application in oncology — it provides too much information, and we still do not fully understand how to use it, especially if a person is healthy. However, implementation of genome data in the clinical process is not as far away as it may seem — many countries, including Russia, are already considering collecting and storing large volumes of genetic data, creating specialized scientific centers, and adopting national strategies for developing genetic technologies .[7] Non-invasive prenatal testing (NIPT) Attempts to detect the risk of various genetic disorders (Down syndrome being the most commonly known) at the gestation stage were made even before the NGS, but this method made this procedure non-invasive — and thus much safer. Mutations can be found since the 10th week of pregnancy by analyzing the fetus' DNA circulating in the mother's blood — to do this, only 0.01 ml of the mother's plasma is needed. 8] [ The person who revolutionized the embryonic-stage diagnostics of Down syndrome was Dennis Lo, a professor at the Chinese University of Hong Kong. At the turn of the millennium, he discovered the way to distinguish the fetal DNA in the pregnant women’s blood, giving an impetus to the rapid development of NITP methods that are harmless both to the mother and the future child. The main prerequisites for NIPT involve chromosome anomalies in the mother's or father's family history. Although this possibility is very low, the testing remains widespread, even though this procedure is not covered by general medical insurance in Russia and many other countries (except for some regional programs). There is another genetic test that enables risk assessment long before pregnancy. It focuses on gene mutations that cause disorders like mucoviscidosis, spinal muscular atrophy (SMA), and others — around 24 hereditary diseases in total. An Australian study shows that couples undergoing infertility treatment often turn out to be carriers of CFTR mutations (mucoviscidosis). 9] In some countries, this screening is offered to all couples applying for IVF, despite the ethical ambiguity of this initiative. 10] [ [ While the medical community keeps discussing the potential social and cultural damage of mass preconception screenings, the IT industry is looking for ways to optimize child diagnostics. It may take days to complete an NGS analysis, so in cases when any delay poses a risk to life and a decision needs to be made within 24 hours, the scientists suggest using artificial intelligence. AI can "notice" a genome decrypted by the NGS faster, even if no description is available. A recent comparative study demonstrates that AI can find a mutated gene in 92% of cases, while other methods fail to pass the 60%-threshold. 11] [ Gene therapy for orphan diseases The international scientific community began to take gene therapy seriously in the 1970s when Theodore Friedmann and Richard Roblin published their paper in Science. Back then, there were no tools for specifying the mutations, so Friedmann and Roblin emphasized that gene therapy required a careful approach. 12] However, the outcome was the opposite: the research continued, and the first clinical trials of gene therapy methods were launched for severe and rare diseases. [ When one patient died during the trials, those initiatives were put to stop (the US even suspended their specialized federal program) until 2003, when China relaunched the process and licensed gene therapy for head and neck squamous cell carcinoma (HNSCC). 13] Although this genetic product aimed to affect “broken” genes saw no further development, pharmaceutical companies from all over the world realized their ideas could finally be greenlit. [ As a result, gene therapy drugs began to be applied in various branches of medicine. In 2018, for example, the first virus vector-based drug was approved for use in ophthalmology. Luxturna targets RPE65 mutations that cause blindness. Oncohematology has a pool of developments built around CAR-T technology, the first of them being Kymriah, approved in the US in 2017. This method seeks to modify the patient's T cells genetically and codify the antigen receptor to target tumor cells. Four medications of this type are now used; Russia also has the practice of introducing its developments. 14] Zolgensma, approved in the US in 2019, deserves a special mention, as only one injection of this medicine can cure SMA. It is one of the most expensive drugs on the market, with one vial costing approximately 2.1 million USD. [ The FDA predicts that by 2025, they will be approving 10 to 20 cell and gene therapy products a year. 15] These expectations seem realistic — first of all, many clinical trials are undergoing their later stages right now. One of the examples is von Gierke disease (glycogen storage disease type I) that for years has been treated only by regular consumption of corn starch. [ Via a single injection of a virus, a new copy of a gene is delivered to the patient’s liver and “reboots” the body's glucose control. The first positive clinical trial results were published in 2019. 16] The drug has already received orphan medication status in the US and the UK, with its Stage III trial planned to be completed this December. 17] [ [ Meanwhile, we are witnessing the CRISPR gene editing technology in its prime. As I wrote earlier, its founders were rightfully awarded the Nobel Prize in 2020. The method involves "cutting" the DNA using Cas9 nuclease and putting together the ends of this "cut" in a way that makes a defect impossible. The most successful case of integrating CRISPR into clinical practice was demonstrated by Sarah Cannon Research Institute specialists — in summer 2019, they applied this therapy for the first time to a patient with sickle cell anemia. This disease (a mutation in the ) causes red blood cells to deform and lose their elasticity and flexibility, as well as leads to dangerous drops in the hemoglobin level. 18] After a year of therapy, the medics reported qualitative improvements in the patient's life: her hemoglobin level went up, and she needed inpatient assistance less often. In March 2021, similar trials began in several US research centers. 19] β-globin gene [ [ COVID-19 etiology Countermeasures against the COVID-19 pandemic — testing systems, vaccines, and medication — require the assistance of genetics. In early 2021, the WHO emphasized the importance of collecting genome data on SARS-CoV-2 and sequencing the virus. 20] To facilitate this process, scientists propose using AI, the way it is applied for disease diagnostics. 21] [ [ At the same time, research has been conducted to find mutations that make their carriers vulnerable to the coronavirus. The COVID-19 Host Genetics Initiative consortium found 40 "candidate genes" that affect susceptibility to this virus. The scientists analyzed the genomes of about 50,000 people affected by the disease with various degrees of severity. They concluded that the TYK2 gene and its variations increase susceptibility to viruses, bacteria, and fungi. Another potentially dangerous "breakdown" was found in the DPP9 gene that also increases the risk of lung fibrosis. 22] [ The French scientists have found a set of genes among patients hospitalized in critical condition, with ADAM9 being particularly expressed. All these patients did not belong to the general risk group: they had no chronic diseases and were younger than 50. The study shows that this gene not only determines a more severe progression of COVID-19 but can also be potentially affected by targeted therapy. 23] [ As of now, this "COVID" research is more probing by nature than applicable here and now. Advanced technologies enable us to study the coronavirus more assiduously than any other virus in human history; in the next decade, they can give us many opportunities to defeat dozens of infectious diseases. How can we do it? We can study how a virus evolves online — so we will know what to be prepared for. Genetic technologies today and tomorrow How soon will all these achievements become part of our everyday life? The answer to this question depends on their availability and cost. The coronavirus pandemic, with new strains being detected much faster in countries applying advanced genome sequencing technologies, has emphasized the importance of the economic factor. Furthering the IT progress is the way to make genetic technologies less expensive and more widespread: availability of big data to the global medical and scientific communities helps save time and money by avoiding repetitive studies or therapeutic developments. While the importance of big data has become clear to almost every scientist, data transparency will become the key issue for the next few decades. About the Author Rustam Gilfanov is an IT entrepreneur and a venture partner of the LongeVC fund. In 2006, Rustam Gilfanov, together with his partners, opened an international IT outsourcing company in Kyiv. Today, this company is the largest developer of software for the gaming, marketing and finance industries. [1] P4 — predictive, preventive, personalized, and participatory medicine [2] https://www.mordorintelligence.com/industry-reports/global-genetic-testing-market-industry [3] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6243123/ [4] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7815373/ [5] von Bubnoff A. Next-generation sequencing: the race is on. Cell. 2008;132(5):721–723^ doi: 10.1016/j.cell.2008.02.028. [6] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7409094/ [7] https://www.mja.com.au/journal/2014/201/1/impact-genomics-future-medicine-and-health#5 [8] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3893900/ [9] https://pubmed.ncbi.nlm.nih.gov/21875427/ [10] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7880037/ [11] https://genomemedicine.biomedcentral.com/articles/10.1186/s13073-021-00965-0 [12] https://www.science.org/doi/10.1126/science.175.4025.949 [13] https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7097065/ [14] https://vademec.ru/article/car-t-_dengi_i_stvoly-_kto_pervym_legalizuet_v_rossii_perspektivnyy_metod_lecheniya_raka_krovi/ [15] https://www.fda.gov/news-events/press-announcements/statement-fda-commissioner-scott-gottlieb-md-and-peter-marks-md-phd-director-center-biologics [16] https://www.sciencedaily.com/releases/2019/09/190920124645.htm [17] https://clinicaltrials.gov/ct2/show/NCT04708015?term=DTX401&draw=2&rank=3 [18] http://stm.sciencemag.org/content/8/360/360ra134 [19] https://innovativegenomics.org/news/crispr-clinical-trials-2021/ [20] https://apps.who.int/iris/bitstream/handle/10665/338480/9789240018440-eng.pdf?sequence=1&isAllowed=y [21] https://link.springer.com/article/10.1007/s12539-021-00465-0 [22] https://www.nature.com/articles/d41586-021-01773-7 [23] https://www.science.org/doi/10.1126/scitranslmed.abj7521

How Genetic Technologies Transform Medicine

Today, tons of free tools can be found online to take care of normal issues developers face each day. In this article, I will share my main 22 most loved web tools that make your life as an engineer simpler. learn X in Y minutes Each conceivable language, clarified in one page, in pretty much every language, through substantial instances of code. Frontegg Your end-users expect much more than just a login; they expect a full self-service admin experience. Frontegg provides that in 5 lines of code. Web Usability Checklist Catch common usability problems before user testing. Regex101 Regular expression tester with syntax highlighting, explanation, cheat sheet for PHP/PCRE, Python, GO, JavaScript, Java. Features a regex quiz & library. Resolution Test An extension for developers to test web pages in different screen resolutions, with an option to define your own resolutions API Background Remover "Slazzer is an AI-powered tool that uses advanced computer vision algorithms to remove background from any image online and replace background automatically with the best detailing in just a few seconds." Features Automatic background removal Easy integration with the cheap API Cloud-hosted: Expansive & Dependable BundlePhobia Bundlephobia helps you find the performance impact of npm packages. Find the size of any javascript package and its effect on your frontend bundle. JustGetFlux Is your computer keeping you up late? f.lux is a free download that warms up your computer display at night to match your indoor lighting. Priortize Built by a PM for PMs. Use this tool to create, visualize, and prioritize tasks on a drag and drop interface with different priority boards. Cron Cron expression generator by Cronhub. Schedule and monitor jobs without any infra work. Namae Check the availability of your new app name for major registries at once. Flaticon Access +4.9M vector icons & stickers. Download free vector icons and stickers for your projects. Resources made by and for designers. PNG, SVG, EPS, PSD, and BASE 64 formats. nTile Service for collaborative work with docs and tables. Use the pre-made solutions, create your own information portals and surveys. IFTTT Begin with IFTTT, the least demanding approach to accomplish more with your most loved applications and gadgets free of charge. Make your home seriously unwinding. Make your work more useful. Keep your information hidden and secure. ExplainShell Write down a command-line to see the help text that matches each argument. LinearApp Linear helps streamline software projects, sprints, tasks, and bug tracking. It's built for high-performance teams. GetTerms Custom Privacy Policy in 2 minutes. Trusted by over 300k customers. GDPR & CalOPPA Ready. Rated 5 Stars, written by lawyers. 100% guarantee. EpochConverter Easy epoch/Unix timestamp converter for computer programmers. Includes epoch explanation and conversion syntax in various programming languages. Aerobatic Turbocharged static web hosting. Blazing fast performance on our highly tuned, purpose-built CDN. Expand the possibilities of static sites with plugins. TextCompare Text Compare! is an online diff tool that can find the difference between two text documents. Just paste and compare. Cafecito Cafecito connects technical and non-tech creatives for casual and informal virtual chats. Meet like-minded creatives from all over the world for a coffee break while you work from home. UserAgent Switcher With this extension, you can quickly and easily switch between user-agent strings. Also, you can set up specific URLs that you want to spoof every time. CloudConvert File converter service - more than 200 different audio, video, document, ebook, archive, image, spreadsheet, and presentation formats supported. SipAPP A superior Color Picker for your Mac. An advanced shading picker for originators and designers that permits you to gather, arrange and alter colors. It enables you to impart tones to everybody and connection them between different tools in your work process. All the referenced web tools are certainly not special of their sort. You may know different sites with similar usefulness and most likely better. There are likewise other VSCode modules or Chrome extensions that can do basically exactly the same thing. Also Published Here

22+ Dev Tools, Websites, and Plugins that Help You Become a Better Developer

One of the most important annual tech events, with thousands of people attending, the Web Summit this year was an epic return of an offline gathering, after two years of lockdown. As always, Web Summit is a place to meet thousands of CEOs and investors, form collaborations, improve brand awareness, generate sales, and establish networking connections like no other place on the planet. People from completely different backgrounds are on the same page and open to learning from one another. Especially considering that this year, attendees from 128 countries travelled to Lisbon to share their values and knowledge. As we all know, such opportunities as Web Summit bring a lot of advantages to all the tech people. Even if you have attended such an event, but came home with no qualified leads, you’ll still benefit from it. This forum is full of business meetings, presentations of startups, which leads to the establishment of strong networking connections for the future. Moreover, it builds an understanding of how to continue business development with the consideration of analyzed views, values, demands, heard and seen on the Web Summit. As one of the initiatives, Web Summit supports Women in Tech. They integrated such an idea, to shift the female representation at their events by cultivating tech women in the community. Of course, we decided to endorse this initiative and participate in it already for the second time. So among the 50.5% of women out of 42,751 attendees this year, were our colleagues Alina Hirna and Yuliia Pokolodna – Business Development Representatives on behalf of our Incora team. With the help of our colleagues, who attended the event, we gathered some useful information about how the renewed after lockdown Web Summit looked like. So, let’s dive in together. The Magnitude of the Event Visiting Web Summit you should be prepared that this is the kind of event, that affects all the Lisbon ordinary life flow. Multiple huge stands cover up the most well-known squares all over the town, with the Web Summit’s logo. Lisbon is overwhelmed with foreign visitors, that surely wouldn’t miss a chance not just to attend the forum, but to have a look at the most popular landmarks. With the influx of foreigners, the city’s public transport suffers, so make sure you head towards the Web Summit’s location in advance. To relieve congestion, the administration of Web Summit organized the registration places right inside the airport, so the coming attendees won’t crowd around the entrance. So the organization this year was definitely magnitude, especially considering the COVID limitations, which encouraged the administration to create some ways for offloading the most crowded spaces. A Variety of Activities Web Summit speaker stages are one of the greatest venues to witness industry professionals address issues that are relevant to your industry. Every year they feature hundreds of experts from the world’s largest biggest corporations, and this year was not an exception. 748 speakers gathered in one place, talking about both global issues and business ideas for future growth, that might someday lead to startups. They were global leaders, investors, entrepreneurs, software developers, pro athletes, artists, and actors who are making a difference in their chosen fields and have distinct perspectives to give. Among the guests were Ayọ (fka Opal) Tometi (the co-founder of Black Lives Matter and a 2021 Nobel Peace Prize nominee), Frances Haugen (Facebook whistleblower), Carlos Moedas (Lisbon’s Mayor), Nick Clegg (VP of global affairs and communications at Meta (Facebook)) and many other notorious and less known experts. The speakers performed on the main stage – the IT arena, but there were also many other smaller ones, where CEOs, entrepreneurs, and business owners discussed in smaller circles ongoing issues with their industries. Besides the speeches, there were also pavilions with booths, where startups are presented, and attendees discuss opportunities for collaboration, for developing these business ideas. This sector is the most valuable part of the Web Summit for those who attended to generate leads, conduct business meetings, and have revenue at the end of it. COVID Influence As we already mentioned, COVID surely had an influence on how these kinds of events are held. But the question is, how much does it affect the value of the Web Summit? Obviously, to make this global gathering happen, the Summit’s safety guidelines were strict: vaccination certificates or PCR tests for everyone, masks everywhere, and social distancing every time you interact with someone. Probably in the era of COVID, for the next Web Summit the situation with such restrictions will remain the same, so be prepared. If we are talking about the influence on business possibilities Web Summit always provided with, the limits are not so dramatic. Surely, the number of attendees is less than the previous years, and the communication in masks interferes with the partnership-building. But after two years of ‘silence’, it is nice to have such opportunities back, even though they are somehow limited. In some way, COVID helped to develop some business ideas into startups, since a lot of people moved to the tech industry, striving to create something digitally, that won’t be influenced by the lockdowns anymore. So this wave gave a push to digital development, which was introduced at the Summit. Networking Connections for Business Development Web Summit is the perfect environment to build networks, find partners, search for business ideas, and hunt for startups’ investors. This is why the pavilions with the booths are always overwhelmed with people. Thus, if you want to attend some speeches as well, plan your schedule ahead in detail, because there is a huge chance that you will stay near the booths, moving from one team to another. For convenience, Web Summit has accurate separation into groups distinguishing startups: – startups, that are still on the stage of pitching their idea to find investors, or has less than $1 million in financing; Alpha – launched startups that are already on the market, which are searching for additional development teams to expand; Beta – startups, that are profitable already, that have raised more than $3 million, and they are now on the stage of global expansion. Growth Knowing about such a division, you can better plan on what pavilions of the Summit are worth your time, and which groups would be the most beneficial for you. Web Summit’s App To make the conference even more beneficial there is an app, which would be an essential thing attending this event. It allows you to build connections even before the Summit, so during the forum, you’ll have scheduled business meetings and won’t waste your time going over each team and wondering if they would be a good fit for the collaboration. The Web Summit’s App would make your life easier because it has filters, where you can select by different criteria what startups are looking for, and who do you want to interact with. Inside an app, you can create connections, and chat with each other. To help you with that, Web Summit provides a QR code on each personal badge, which redirects other people to an app, where they can add you to connections. So, it makes future communication simpler, since after the discussion you can just scan each other’s QR codes, and get in touch later. Night Summit Your business development opportunities don’t end when the lights go down, and the pavilions close. Night Summit – is one more option to expand social interactions. In the friendly and relaxing atmosphere sometimes the best deals are cut. The Web Summit did not skimp on entertainment, as they planned evening festivities for each day. So, besides the Night Summit, there are also the Opening Party and the Closing Party. Web Summit’s organization team created a list on the website, of the main places to visit in Lisabon for the Night Summit. This way they encourage attendees to gather in small groups to discover this magnificent city. The neighborhoods they advise to visit as a part of Night Summit, are: Baixa and Terreiro do Paço, Avenida da Liberdade, Príncipe Real, Parque das Nações, Graça/Arroios, and Marvila. All these spots are equipped with everything you and your future business partners would need: from food to different activities. Concluding From our experience, the Web Summit was a pleasant journey, which ended up with a lot of far-sighted collaborations both in 2019 and in 2021. But, to get all the advantages from this conference, it’s better to attend not just as a visitor but to book a booth to represent your company’s interests. This way there is more chance to find valuable connections and increase awareness of your company’s performance. Undoubtedly, even without the unambiguous plans to get as many leads as you can through the Web Summit, this event is worth visiting. But the next year you are attending, make sure you are fully prepared for all the limits the new COVID era brings, and you figured out what your main goal there would be. See you at the Web Summit 2022! Also published here

We Hosted a Web Summit in 2021: Our Experience with Post-COVID Conferencing

Since the tale laid here is , I'll refrain from using specific names or locations. It might put me in some awkward situation. If you've been through something similar, it may sound familiar. real Having said that, the identifying details have little to do with the story itself. It is not a new or sophisticated hack. This is developers' laziness at its best. Assuming users are all non-technical sheep. For the most part, they're right, but one greedy naughty user can change the picture. Disclaimer: I did not actually use what I got and reported the bug. I do not suggest scoring free services through exploitations of lousy systems. This is meant to help secure those that are exposed. I hope that developers become more vigilant with systems, especially those involving the personal and medical information of literally everyone that crosses their country's border. I do think, however, that testing at home for these kinds of bugs is contributing to the greater good of the internet . Once upon a time I've been traveling a lot. More so during covid than "normal" times, to get the vaccine, medical checkups, and other personal obligations. Traveling became this huge payment burden annoyance where you have to pay for tests before boarding and right after landing. Oh, and all over again when traveling back. While I don't have any criticism on the necessity of the test (nor have I got the professional background to comment on it), the pile of tests I had to undertake and pay for started to feel like a tax. Throughout the last year, I've been traveling to my home country and had to take a PCR test right at the airport. Scheduling the appointments in an online dedicated system using the same discount code every time: . free Free1 A couple of days ago, while planning for another trip home, I was going over the same long routine. Filling a passenger locator form (both for out and inbound travel - 🤷) and pre-ordering my Airport Covid PCR test. To my surprise, the test name has changed from "Covid PCR - mandatory" to something like "Covid PCR - $80 mandatory". *Wait, what?* Yep, it seems that from now on, an $80 fine (excuse me, charge) per person is a must if you want to leave the airport. The other option is paying with cash $100 upon arrival (some deal ay?). I retried the same code that used to work over the last year. and "Apply". The screen reported a red error message. " ". Free1 Invalid Voucher Code I did what any cybercriminal would do at that point - retried the same thing 3-5 times (genius). When that didn't work, I tried , , and a few others. Free2 Free80 When I checked the outgoing request, I found that it was being sent to endpoint. It returned a strange HTTP error; and a , hmmm.. What "appointment"? /api/validate-voucher 422 (Unprocessable entity) {statusCode: 422, message: "Invalid Voucher or Appointment ID"} I was trying to apply a discount code. Upon bad response, the UI deletes the code entered, effectively "preventing" the use of the code. The fact that it actually got deleted could have been a good user experience but a lousy prevention mechanism at the same time. I thought. 😈 "Why not test it myself?" I fire up Firefox and everything through Burp. BurpSuit to the rescue! proxy Going through the outgoing requests, I see metrics and more metrics, 3rd party trackers, and whatnot. Sometimes I wish I haven't seen the pile of crap these websites make us send. Forwarding everything that's not interesting until WHOOPS, what's that? A request holding the JSON data: POST { : , : } appointmentId "12345" voucher "" There we go - But wait, this sounds familiar.. earlier, when I just tried entering my old discount code, I got an " ...", could the same system actually be used for both purposes - validating the codes creating appointments? how about sliding the previously valid voucher through? Invalid appointmentId and It feels off. A hunch tells me I'm going to see something funny. I edit the object on the fly and forward it with burp: { : , : } appointmentId "12345" voucher "Free1" And what do you know, a huge shiny green label appeared on the screen: " ". Five seconds later, the screen reloaded, and a new QR with an appointment was generated. PAID Moral of the story Some of them may not have the skills or energy to dig in. But if a system that holds personal medical records and results is this easily exploited, what happens in other areas? Users are not dumb. Businesses are founded and run to make money. As such, they would always serve as a target for exploits. Let alone for a service that up until recently was free and is now forced upon all returning passengers, preventing them from going home. One must check each and every incoming request as if it's coming from the wild (it actually is!). Employ zero trust Ways to handle First and foremost, . Much like checking if the front door is locked, applications should make sure users can only do what they're intended to. assume you're going to get exploited Checking whether a discount code is valid in the UI? Excellent, what about the backend? The browser lives in userland, where the developers don't have control over how the application is manipulated or used. One must check each and every incoming request as if it's coming from the wild (it actually is...). . mis Employ zero trust On the same note - rate-limit incoming requests; when I couldn't apply my old discount code, I tried , then and so on with different permutations. It seemed odd that I can just keep pushing codes through and learn whether they're valid or not, so I did what anyone would; I wrote a script. Tried a few dozens of them just for fun. Free1 Free2 Free3 Although nothing came up, I had fun fuzzing again with , and I just learned that the system doesn't rate-limit requests. With enough time at their disposal, different users can run a similar script for hours and days. This is bad for two main reasons : ffuf Servers are bombarded with requests. In case it was built correctly, it scales up to serve brute force attacks (funny on its own). In the worse case, it crashes. At some point, a valid discount code will pop up. Another " " exploit (which I hadn't tried after getting a full price reduction), is a where a user can re-apply the same discount code, usually giving a discount percentage multiple times. . discount code friendly race condition Here's a famous one found on Dropbox a few years back To sum up, systems' security should be high on the priority list - if not for revenue, at least for customer's privacy. Web applications can be "hacked" in more than one way, and the ways . My go-to approach when testing my own apps is thinking like a malicious actor. might be simple Not necessarily a top-notch security expert, which I'm far from, but a user with minimal skills and a couple of simple wishes. Like getting a free service, or a discount I do not deserve. Thank you for reading 🖤 Feel free to reach out with questions or comments. Also published on https://omerxx.com/covid-hack/ .

Stories, News & Mentions about PCR

Pcr’s Stories on HackerNoon