An Expert's Guide to Training Physics-informed Neural Networks

Physics-informed neural networks (PINNs) have been popularized as a deep learning framework that can seamlessly synthesize observational data and partial differential equation (PDE) constraints. Their practical effectiveness however can be hampered by training pathologies, but also oftentimes by poor choices made by users who lack deep learning expertise. In this paper we present a series of best practices that can significantly improve the training efficiency and overall accuracy of PINNs. We also put forth a series of challenging benchmark problems that highlight some of the most prominent difficulties in training PINNs, and present comprehensive and fully reproducible ablation studies that demonstrate how different architecture choices and training strategies affect the test accuracy of the resulting models. We show that the methods and guiding principles put forth in this study lead to state-of-the-art results and provide strong baselines that future studies should use for comparison purposes. To this end, we also release a highly optimized library in JAX that can be used to reproduce all results reported in this paper, enable future research studies, as well as facilitate easy adaptation to new use-case scenarios.Comment: 36 pages, 25 figures, 13 table

Identification of prognostic and susceptibility markers in chronic myeloid leukemia using next generation sequencing

Background: Incidence of Chronic Myeloid Leukemia (CML) is continuously increasing and expected to reach 100,000 patients every year by 2030. Though the discovery of Imatinib Mesylate (IM) has brought a paradigm shift in CML treatment, 20% patients show resistance to this tyrosine kinase inhibiter (TKI). Therefore, it is important to identify markers, which can predict the occurrence and prognosis of CML. Clinical Exome Sequencing, panel of more than 4800 genes, was performed in CML patients to identify prognostic and susceptibility markers in CML.Methods: Enrolled CML patients (n=18) were segregated as IM responders (n=10) and IM failures (n=8) as per European Leukemia Net (ELN), 2013 guidelines. Healthy controls (n=5) were also enrolled. DNA from blood of subjects was subjected to Next Generation Sequencing. Rare mutations present in one patient group and absent in another group were considered as prognostic markers, whereas mutations present in more than 50% patients were considered as susceptibility markers.Result: Mutations in genes associated with cancer related functions were found in different patient groups. Four variants: rs116201358, rs4014596, rs52897880 and rs2274329 in C8A, UNC93B1, APOH and CA6 genes, respectively, were present in IM responders; whereas rs4945 in MFGE8 was present in IM failures. Mutations in HLA-DRB1 (rs17878951), HLA-DRB5 (rs137863146), RPHN2 (rs193179333), CYP2F1 (rs116958555), KCNJ12 (rs76684759) and FUT3 (rs151218854) were present as susceptibility markers.Conclusion: The potential genetic markers discovered in this study can help in predicting response to IM as frontline therapy. Susceptibility markers may also be used as panel for individuals prone to have CML.Keywords: Chronic Myeloid Leukemia, Genetic Markers, Next Generation Sequencing (NGS

Mycobactin Analogues with Excellent Pharmacokinetic Profile Demonstrate Potent Antitubercular Specific Activity and Exceptional Efflux Pump Inhibition

In this study, we have designed and synthesized pyrazoline analogues that partially mimic the structure of mycobactin, to address the requirement of novel therapeutics to tackle the emerging global challenge of antimicrobial resistance (AMR). Our investigation resulted in the identification of novel lead compounds 44 and 49 as potential mycobactin biosynthesis inhibitors against mycobacteria. Moreover, candidates efficiently eradicated intracellularly surviving mycobacteria. Thermofluorimetric analysis and molecular dynamics simulations suggested that compounds 44 and 49 bind to salicyl-AMP ligase (MbtA), a key enzyme in the mycobactin biosynthetic pathway. To the best of our knowledge, these are the first rationally designed mycobactin inhibitors to demonstrate an excellent in vivo pharmacokinetic profile. In addition, these compounds also exhibited more potent whole-cell efflux pump inhibition than known efflux pump inhibitors verapamil and chlorpromazine. Results from this study pave the way for the development of 3-(2-hydroxyphenyl)-5-(aryl)-pyrazolines as a new weapon against superbug-associated AMR challenges

Mycobactin analogues with excellent pharmacokinetic profile demonstrate potent antitubercular specific activity and exceptional efflux pump inhibition

In this study, we have designed and synthesized pyrazoline analogues that partially mimic the structure of mycobactin, to address the requirement of novel therapeutics to tackle the emerging global challenge of antimicrobial resistance (AMR). Our investigation resulted in the identification of novel lead compounds 44 and 49 as potential mycobactin biosynthesis inhibitors against mycobacteria. Moreover, candidates efficiently eradicated intracellularly surviving mycobacteria. Thermofluorimetric analysis and molecular dynamics simulations suggested that compounds 44 and 49 bind to salicyl-AMP ligase (MbtA), a key enzyme in the mycobactin biosynthetic pathway. To the best of our knowledge, these are the first rationally designed mycobactin inhibitors to demonstrate an excellent in vivo pharmacokinetic profile. In addition, these compounds also exhibited more potent whole-cell efflux pump inhibition than known efflux pump inhibitors verapamil and chlorpromazine. Results from this study pave the way for the development of 3-(2-hydroxyphenyl)-5-(aryl)-pyrazolines as a new weapon against superbug-associated AMR challenges

Screening of over 1000 Indian patients with breast and/or ovarian cancer with a multi-gene panel: prevalence of BRCA1/2 and non-BRCA mutations

Breast and/or ovarian cancers are among the most common cancers in women across the world. In the Indian population, the healthcare burden of breast and/or ovarian cancers has been steadily rising, thus stressing the need for early detection, surveillance, and disease management measures. However, the burden attributable to inherited mutations is not well characterized. We sequenced 1010 unrelated patients and families from across India with an indication of breast and/or ovarian cancers, using the TruSight Cancer panel which includes 14 genes, strongly associated with risk of hereditary breast and/or ovarian cancers. Genetic variations were identified using the StrandNGS software and interpreted using the StrandOmics platform. We were able to detect mutations in 304 (30.1%) cases, of which, 56 mutations were novel. A majority (84.9%) of the mutations were detected in the BRCA1/2 genes as compared to non-BRCA genes (15.1%). When the cases were stratified on the basis of age at diagnosis and family history of cancer, the high rate of 75% of detection of hereditary variants was observed in patients whose age at diagnosis was below 40 years and had first-degree family member(s) affected by breast and/or ovarian cancers. Our findings indicate that in the Indian population, there is a high prevalence of mutations in the high-risk breast cancer genes: BRCA1, BRCA2, TP53, and PALB2. In India, socioeconomic inequality limiting access to treatment is a major factor towards increased cancer burden; therefore, incorporation of a cost-effective and comprehensive multi-gene test will be helpful in ensuring widespread implementation of genetic screening in the clinical practice for hereditary breast and/or ovarian cancers