Application of Covalent Binding Body Burden in the HμREL Human Hepatocyte Coculture Model for Reactivity Risk Assessment of Metabolically Low Turnover Drugs

The human hepatocyte suspension model has been a valuable tool to study covalent binding (CVB) for compounds that form reactive metabolites. However, accurately measuring CVB values with the suspension model becomes challenging for metabolically low turnover compounds. In this study, we evaluated the HμREL human hepatocyte coculture model relative to existing literature using human hepatocyte suspension for drugs of known drug-induced liver injury category. Our results indicate that this coculture model provides ample metabolic turnover to reproducibly measure CVB. It is sufficiently robust to apply a predefined 1 mg/day CVB body burden threshold for risk assessment to guide our discovery programs, allowing for expanded coverage to include metabolically low turnover compounds.

AI/ML Models to Predict the Severity of Drug-Induced Liver Injury for Small Molecules

Drug-induced liver injury (DILI), believed to be a multifactorial toxicity, has been a leading cause of attrition of small molecules during discovery, clinical development, and postmarketing. Identification of DILI risk early reduces the costs and cycle times associated with drug development. In recent years, several groups have reported predictive models that use physicochemical properties or in vitro and in vivo assay endpoints; however, these approaches have not accounted for liver-expressed proteins and drug molecules. To address this gap, we have developed an integrated artificial intelligence/machine learning (AI/ML) model to predict DILI severity for small molecules using a combination of physicochemical properties and off-target interactions predicted in silico. We compiled a data set of 603 diverse compounds from public databases. Among them, 164 were categorized as Most DILI (M-DILI), 245 as Less DILI (L-DILI), and 194 as No DILI (N-DILI) by the FDA. Six machine learning methods were used to create a consensus model for predicting the DILI potential. These methods include k-nearest neighbor (k-NN), support vector machine (SVM), random forest (RF), Naïve Bayes (NB), artificial neural network (ANN), logistic regression (LR), weighted average ensemble learning (WA) and penalized logistic regression (PLR). Among the analyzed ML methods, SVM, RF, LR, WA, and PLR identified M-DILI and N-DILI compounds, achieving a receiver operating characteristic area under the curve of 0.88, sensitivity of 0.73, and specificity of 0.9. Approximately 43 off-targets, along with physicochemical properties (fsp³, log S, basicity, reactive functional groups, and predicted metabolites), were identified as significant factors in distinguishing between M-DILI and N-DILI compounds. The key off-targets that we identified include: PTGS1, PTGS2, SLC22A12, PPARγ, RXRA, CYP2C9, AKR1C3, MGLL, RET, AR, and ABCC4. The present AI/ML computational approach therefore demonstrates that the integration of physicochemical properties and predicted on- and off-target biological interactions can significantly improve DILI predictivity compared to chemical properties alone.

Acyl Glucuronide and Coenzyme A Thioester Metabolites of Carboxylic Acid-Containing Drug Molecules: Layering Chemistry with Reactive Metabolism and Toxicology

Glucuronidation and CoA (coenzyme A) conjugation are common pathways for the elimination of carboxylic acid-containing drug molecules. In some instances, these biotransformations have been associated with toxicity (such as idiosyncratic hepatic injury, renal impairment, hemolytic anemia, gastrointestinal inflammation, and bladder cancer) attributed to, in part, the propensity of acyl glucuronides and acyl CoA thioesters to covalently modify biological macromolecules such as proteins and DNA. It is to be noted that, while acyl glucuronidation and CoA conjugation are indeed implicated in adverse effects, there are many safe drugs in the market that are cleared by these reactive pathways. It is therefore important that new molecular entities with carboxylic acid groups are evaluated for toxicity in a manner that is not unreasonably risk-averse. In the absence of truly predictable methods, therefore, the general approach is to apply a set of end points to generate a weight-of-evidence evaluation. In practice, the focus is to identify structural liabilities and provide structure-activity recommendations early in the program, at a stage where an attempt to improve reactive metabolism does not deoptimize other critical drug-quality criteria. This review will present a high-level overview of the chemistry of glucuronidation and CoA conjugation and provide a discussion of the possible mechanisms of adverse effects that have been associated with these pathways, as well as how such potential hazards are addressed while delivering a new chemical entity for clinical evaluation.

FlatNet3D: intensity and absolute depth from single-shot lensless capture

Lensless cameras are ultra-thin imaging systems that replace the lens with a thin passive optical mask and computation. Passive mask-based lensless cameras encode depth information in their measurements for a certain depth range. Early works have shown that this encoded depth can be used to perform 3D reconstruction of close-range scenes. However, these approaches for 3D reconstructions are typically optimization based and require strong hand-crafted priors and hundreds of iterations to reconstruct. Moreover, the reconstructions suffer from low resolution, noise, and artifacts. In this work, we propose FlatNet3D-a feed-forward deep network that can estimate both depth and intensity from a single lensless capture. FlatNet3D is an end-to-end trainable deep network that directly reconstructs depth and intensity from a lensless measurement using an efficient physics-based 3D mapping stage and a fully convolutional network. Our algorithm is fast and produces high-quality results, which we validate using both simulated and real scenes captured using PhlatCam.

FlatNet: Towards Photorealistic Scene Reconstruction From Lensless Measurements

Lensless imaging has emerged as a potential solution towards realizing ultra-miniature cameras by eschewing the bulky lens in a traditional camera. Without a focusing lens, the lensless cameras rely on computational algorithms to recover the scenes from multiplexed measurements. However, the current iterative-optimization-based reconstruction algorithms produce noisier and perceptually poorer images. In this work, we propose a non-iterative deep learning-based reconstruction approach that results in orders of magnitude improvement in image quality for lensless reconstructions. Our approach, called FlatNet, lays down a framework for reconstructing high-quality photorealistic images from mask-based lensless cameras, where the camera's forward model formulation is known. FlatNet consists of two stages: (1) an inversion stage that maps the measurement into a space of intermediate reconstruction by learning parameters within the forward model formulation, and (2) a perceptual enhancement stage that improves the perceptual quality of this intermediate reconstruction. These stages are trained together in an end-to-end manner. We show high-quality reconstructions by performing extensive experiments on real and challenging scenes using two different types of lensless prototypes: one which uses a separable forward model and another, which uses a more general non-separable cropped-convolution model. Our end-to-end approach is fast, produces photorealistic reconstructions, and is easy to adopt for other mask-based lensless cameras.

Driving to a Better Understanding of Acyl Glucuronide Transformations Using NMR and Molecular Modeling

Acyl glucuronide (AG) metabolites of carboxylic acid-containing drugs and products of their transformations have long been implicated in drug-induced liver injury (DILI). To inform on the DILI risk arising from AG reactive intermediates, a comprehensive mechanistic study of enzyme-independent AG rearrangements using nuclear magnetic resonance (NMR) and density functional theory (DFT) was undertaken. NMR spectroscopy was utilized for structure elucidation and kinetics measurements of nine rearrangement and hydrolysis products of 1β-O-acyl glucuronide of ibufenac. To extract rate constants of rearrangement, mutarotation, and hydrolysis from kinetic data, 11 different kinetic models were examined. Model selection and estimated rate constant verification were supported by measurements of H/D kinetic isotope effects. DFT calculations of ground and transition states supported the proposed kinetic mechanisms and helped to explain the unusually fast intramolecular transacylation rates found for some of the intermediates. The findings of the current study reinforce the notion that the short half-life of parent AG and slow hydrolysis rates of AG rearrangement products are the two key factors that can influence the in vivo toxicity of AGs.

Determinants of treatment interruption and outcome among smear-positive pulmonary tuberculosis patients in a tuberculosis unit of Purba Bardhaman district of West Bengal

Context:

The adoption of directly observed treatment short course (DOTS) in Revised National Tuberculosis Control Programme has given impressive results with higher treatment success. But interruption of treatment has been one of the major obstacles to treatment of tuberculosis.

Aims:

The aim of the study was to evaluate the determinants of treatment interruption and outcome. It also evaluated the impact of treatment interruption on treatment outcomes.

Settings and Design:

The study was carried out in the area covered under Bhatar tuberculosis unit (TU) of Burdwan district of West Bengal. The study was a descriptive cross-sectional study.

Methods and Material:

Smear-positive pulmonary tuberculosis patients were taken as study subjects in both the components of study. Complete enumeration technique, rather than sampling, was followed in this study. Data were collected in a predesigned and pretested schedule.

Statistical Analysis Used:

Data were analyzed by percentages and proportion. Chi-square test was used to find the association between variables.

Results:

Gender, religion, and substance abuse were found to be statistically significant factors with interruption. It was also observed that treatment outcome was not statistically significant with age, gender, religion, and category of treatment. In the study, 84.6% of the study subjects with interruption less than 1 week had favorable outcome. But in study subjects with longer duration of interruption (≥2 weeks), only 12.5% had favorable outcome. Not only interruption, duration of interruption was found to be adversely affecting the treatment outcome.

Conclusions:

Interruption had an impact on the treatment outcome in the present study. Unfavorable outcomes were significantly more frequent among patients with interruption as compared to those without any interruption.

Association of Mid-sagittal Anteroposterior Diameter of Lumbar Canal in Patients with Low Back Pain using MRI: A Cross-sectional Study from West Bengal, India

Introduction: Lumbar spinal canal stenosis is the progressive narrowing of spinal canal that causes compression of nerve roots before their exit. The presenting symptoms of spinal canal stenosis includes bilateral lower extremity pain, altered sensation in both legs and poorly localised weakness and generally associated with low back pain. Determination of normal diameter and its variation with development of low back pain could prove useful in determining the aetiology and outcome of congenital or acquired causes of stenosis like spondylolisthesis, Paget’s disease, fluorosis, etc. Aim: To measure and compare the mid-sagittal anteroposterior diameter of lumbar canal in symptomatic cases with low back pain and asymptomatic subjects using Magnetic Resonance Imaging (MRI). Materials and Methods: The present study was a hospitalbased cross-sectional, observational study involving Out Patient Department (OPD) patients of Bangur Institute of Neurosciences, Kolkata, West Bengal, India, was undertaken from May 2012 to July 2012. The study participants were selected by systematic random sampling. Total number of 102 cases were investigated in this study. Out of these, 52 cases were symptomatic patients of low back pain and rest 50 cases were asymptomatic. MRI was done to estimate the mid-sagittal anteroposterior diameter at different levels of lumbar canal. Unpaired t-test was used as test of significance using Statistical Package for the Social Sciences (SPSS) version 19.0. A p-value <0.05 was considered as statistically significant. Results: In this study, in the asymptomatic group, the anteroposterior diameter at the intervertebral disc level -between L1-L2-18.364±1.4351 mm, L2-L3-17.470±1.3298 mm, L3- L4-16.670±1.6042 mm, L4-L5-15.200±1.8906 mm, L5-S1- 14.196±2.1092 mm. Mean diameter of central lumbar vertebral was found to be lower in symptomatic cases with low back pain at different vertebral levels and the difference was found to be statistically significant between symptomatic and asymptomatic subjects. It was found that age of presentation did not show any statistical significance with the presence of low back pain. Conclusion: The lumbar vertebral canal diameter was found to be significantly lower in subjects with low back pain than subjects having no complaints.

Toward Unaligned Guided Thermal Super-Resolution

Thermography is a useful imaging technique as it works well in poor visibility conditions. High-resolution thermal imaging sensors are usually expensive and this limits the general applicability of such imaging systems. Many thermal cameras are accompanied by a high-resolution visible-range camera, which can be used as a guide to super-resolve the low-resolution thermal images. However, the thermal and visible images form a stereo pair and the difference in their spectral range makes it very challenging to pixel-wise align the two images. The existing guided super-resolution (GSR) methods are based on aligned image pairs and hence are not appropriate for this task. In this paper, we attempt to remove the necessity of pixel-to-pixel alignment for GSR by proposing two models: the first one employs a correlation-based feature-alignment loss to reduce the misalignment in the feature-space itself and the second model includes a misalignment-map estimation block as a part of an end-to-end framework that adequately aligns the input images for performing guided super-resolution. We conduct multiple experiments to compare our methods with existing state-of-the-art single and guided super-resolution techniques and show that our models are better suited for the task of unaligned guided super-resolution from very low-resolution thermal images.

1041 A Systematic Review of the Reporting Quality of Surgical Randomised Controlled Trials in Head and Neck Cancer using the CONSORT Statement

Introduction

Randomised controlled trials (RCTs) are considered the gold standard for evaluating the efficacy of an intervention. However, previous research has shown that surgical specialities poorly report RCTs, making it difficult to ascertain if various biases have been appropriately minimised. This systematic review assesses the reporting quality of surgical head and neck cancer RCTs.

Method

A literature search of PubMed and Embase was performed. Papers were included if they reported RCTs which assessed a surgical technique used to treat or diagnose head and neck cancer published during or after 2011. Therefore, the CONSORT 2010 checklist was used to evaluate the reporting quality of these trials.

Results

41 papers were included. The mean CONSORT score was 16.5/25 (66% adherence) and the scores ranged from 7.5 (30%) to 25. The most common omissions were full trial protocol (found in 14.6%), participant recruitment method (22%) and effect size with precision estimate for all outcome measures (29.3%). The full design and implementation of the randomisation method was reported in 6 (14.6%). Papers published in journals which endorsed CONSORT had significantly higher scores (p = 0.02) and journal impact factor was significantly correlated with CONSORT score (p = 0.01).

Conclusions

We have identified several pieces of information that are underreported in surgical head and neck cancer RCTs. These omissions make understanding and comparing the methodologies and conclusions of RCTs more difficult. The endorsement of CONSORT by journals improved adherence, suggesting that wider adoption of the checklist may improve reporting.

An observational study on pattern of mortalities as per ICD-10 classification system in a tertiary care hospital in India

Background: Records of vital events like death constitute an important component of the Health Information System. Patterns of mortality decline that occur with the demographic transition is a change in the distribution of deaths by cause away from a pattern dominated by communicable diseases toward one in which non-communicable diseases account for the overwhelming majority of deaths. Aims and Objective: To identify the mortality pattern in Burdwan Medical College as per ICD-10 classification in the year 2017.The study also evaluated socio-demographic distribution and causes of deaths during that period. Materials and Methods: It was an Institution based retrospective observational study. Complete enumeration of all hospital records of medically certified deaths of in-patients from different departments except the Paediatrics who died in 2017 was done. The underlying cause of death was classified according to I.C.D 10th revision, version 16. Information collected included also the demographic characteristics like age, gender, date of admission, place of residence and date of death for the study. Results: In this study, most of the deaths were seen in males (59.99%), with a sex ratio of female to male deaths to be 667 per thousand. The major proportion of deaths was in the age group of 55 to 64 years (23.53%). The percentage distribution of ten major cause groups of death for the period from January to December during 2017 reveals that the group “Diseases of the Circulatory System” had occupied the position of the top-most killer and it had maintained the trend throughout the year with the highest rate in the month of March (43.9%). The cause of death was more in Non-Communicable diseases (Chapter IX, Chapter XIX) compared to that of Communicable diseases. Conclusion: Procedures for death certification and coding of underlying causes of death need to be streamlined to improve reliability of registration data needed for epidemiological research or public health policy formulation.

Invention of MK-8262, a Cholesteryl Ester Transfer Protein (CETP) Inhibitor Backup to Anacetrapib with Best-in-Class Properties

Cholesteryl ester transfer protein (CETP) represents one of the key regulators of the homeostasis of lipid particles, including high-density lipoprotein (HDL) and low-density lipoprotein (LDL) particles. Epidemiological evidence correlates increased HDL and decreased LDL to coronary heart disease (CHD) risk reduction. This relationship is consistent with a clinical outcomes trial of a CETP inhibitor (anacetrapib) combined with standard of care (statin), which led to a 9% additional risk reduction compared to standard of care alone. We discuss here the discovery of MK-8262, a CETP inhibitor with the potential for being the best-in-class molecule. Novel in vitro and in vivo paradigms were integrated to drug discovery to guide optimization informed by a critical understanding of key clinical adverse effect profiles. We present preclinical and clinical evidence of MK-8262 safety and efficacy by means of HDL increase and LDL reduction as biomarkers for reduced CHD risk.

Development and Application of a Transcriptomic Signature of Bioactivation in an Advanced In Vitro Liver Model to Reduce Drug-induced Liver Injury Risk Early in the Pharmaceutical Pipeline

Early risk assessment of drug-induced liver injury (DILI) potential for drug candidates remains a major challenge for pharmaceutical development. We have previously developed a set of rat liver transcriptional biomarkers in short-term toxicity studies to inform the potential of drug candidates to generate a high burden of chemically reactive metabolites that presents higher risk for human DILI. Here, we describe translation of those NRF1-/NRF2-mediated liver tissue biomarkers to an in vitro assay using an advanced micropatterned coculture system (HEPATOPAC) with primary hepatocytes from male Wistar Han rats. A 9-day, resource-sparing and higher throughput approach designed to identify new chemical entities with lower reactive metabolite-forming potential was qualified for internal decision making using 93 DILI-positive and -negative drugs. This assay provides 81% sensitivity and 90% specificity in detecting hepatotoxicants when a positive test outcome is defined as the bioactivation signature score of a test drug exceeding the threshold value at an in vitro test concentration that falls within 3-fold of the estimated maximum drug concentration at the human liver inlet following highest recommended clinical dose administrations. Using paired examples of compounds from distinct chemical series and close structural analogs, we demonstrate that this assay can differentiate drugs with lower DILI risk. The utility of this in vitro transcriptomic approach was also examined using human HEPATOPAC from a single donor, yielding 68% sensitivity and 86% specificity when the aforementioned criteria are applied to the same 93-drug test set. Routine use of the rat model has been adopted with deployment of the human model as warranted on a case-by-case basis. This in vitro transcriptomic signature-based strategy can be used early in drug discovery to derisk DILI potential from chemically reactive metabolites by guiding structure-activity relationship hypotheses and candidate selection.

Whole genome analysis of more than 10 000 SARS-CoV-2 virus unveils global genetic diversity and target region of NSP6

Whole genome analysis of SARS-CoV-2 is important to identify its genetic diversity. Moreover, accurate detection of SARS-CoV-2 is required for its correct diagnosis. To address these, first we have analysed publicly available 10 664 complete or near-complete SARS-CoV-2 genomes of 73 countries globally to find mutation points in the coding regions as substitution, deletion, insertion and single nucleotide polymorphism (SNP) globally and country wise. In this regard, multiple sequence alignment is performed in the presence of reference sequence from NCBI. Once the alignment is done, a consensus sequence is build to analyse each genomic sequence to identify the unique mutation points as substitutions, deletions, insertions and SNPs globally, thereby resulting in 7209, 11700, 119 and 53 such mutation points respectively. Second, in such categories, unique mutations for individual countries are determined with respect to other 72 countries. In case of India, unique 385, 867, 1 and 11 substitutions, deletions, insertions and SNPs are present in 566 SARS-CoV-2 genomes while 458, 1343, 8 and 52 mutation points in such categories are common with other countries. In majority (above 10%) of virus population, the most frequent and common mutation points between global excluding India and India are L37F, P323L, F506L, S507G, D614G and Q57H in NSP6, RdRp, Exon, Spike and ORF3a respectively. While for India, the other most frequent mutation points are T1198K, A97V, T315N and P13L in NSP3, RdRp, Spike and ORF8 respectively. These mutations are further visualised in protein structures and phylogenetic analysis has been done to show the diversity in virus genomes. Third, a web application is provided for searching mutation points globally and country wise. Finally, we have identified the potential conserved region as target that belongs to the coding region of ORF1ab, specifically to the NSP6 gene. Subsequently, we have provided the primers and probes using that conserved region so that it can be used for detecting SARS-CoV-2. Contact:  indrajit@nitttrkol.ac.in  Supplementary information: Supplementary data are available at http://www.nitttrkol.ac.in/indrajit/projects/COVID-Mutation-10K

Mito-SinCe2 Approach to Analyze Mitochondrial Structure-Function Relationship in Single Cells

The cross talk between mitochondrial dynamic structure, determined primarily by mitochondrial fission and fusion events, and mitochondrial function of energetics, primarily ATP and ROS production, is widely appreciated. Understanding the mechanistic details of such cross talk between mitochondrial structure and function needs integrated quantitative analyses between mitochondrial dynamics and energetics. Here we describe our recently designed approach of mito-SinCe² that involves high resolution confocal microscopy of genetically expressed ratiometric fluorescent probes targeted to mitochondria, and its quantitative analyses. Mito-SinCe² analyses allows for quantitative analyses of mitochondrial structure-function relationship in single cells toward understanding the role of mitochondria and their heterogeneity in various physiological and pathological conditions.

Harnessing Multi-View Perspective of Light Fields for Low-Light Imaging

Light Field (LF) offers unique advantages such as post-capture refocusing and depth estimation, but low-light conditions severely limit these capabilities. To restore low-light LFs we should harness the geometric cues present in different LF views, which is not possible using single-frame low-light enhancement techniques. We propose a deep neural network L3Fnet for Low-Light Light Field (L3F) restoration, which not only performs visual enhancement of each LF view but also preserves the epipolar geometry across views. We achieve this by adopting a two-stage architecture for L3Fnet. Stage-I looks at all the LF views to encode the LF geometry. This encoded information is then used in Stage-II to reconstruct each LF view. To facilitate learning-based techniques for low-light LF imaging, we collected a comprehensive LF dataset of various scenes. For each scene, we captured four LFs, one with near-optimal exposure and ISO settings and the others at different levels of low-light conditions varying from low to extreme low-light settings. The effectiveness of the proposed L3Fnet is supported by both visual and numerical comparisons on this dataset. To further analyze the performance of low-light restoration methods, we also propose the L3F-wild dataset that contains LF captured late at night with almost zero lux values. No ground truth is available in this dataset. To perform well on the L3F-wild dataset, any method must adapt to the light level of the captured scene. To do this we use a pre-processing block that makes L3Fnet robust to various degrees of low-light conditions. Lastly, we show that L3Fnet can also be used for low-light enhancement of single-frame images, despite it being engineered for LF data. We do so by converting the single-frame DSLR image into a form suitable to L3Fnet, which we call as pseudo-LF. Our code and dataset is available for download at https://mohitlamba94.github.io/L3Fnet/.

Genome-wide analysis of Indian SARS-CoV-2 genomes for the identification of genetic mutation and SNP

The wave of COVID-19 is a big threat to the human population. Presently, the world is going through different phases of lock down in order to stop this wave of pandemic; India being no exception. We have also started the lock down on 23rd March 2020. In this current situation, apart from social distancing only a vaccine can be the proper solution to serve the population of human being. Thus it is important for all the nations to perform the genome-wide analysis in order to identify the genetic variation in Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) so that proper vaccine can be designed. This fast motivated us to analyze publicly available 566 Indian complete or near complete SARS-CoV-2 genomes to find the mutation points as substitution, deletion and insertion. In this regard, we have performed the multiple sequence alignment in presence of reference sequence from NCBI. After the alignment, a consensus sequence is built to analyze each genome in order to identify the mutation points. As a consequence, we have found 933 substitutions, 2449 deletions and 2 insertions, in total 3384 unique mutation points, in 566 genomes across 29.9 K bp. Further, it has been classified into three groups as 100 clusters of mutations (mostly deletions), 1609 point mutations as substitution, deletion and insertion and 64 SNPs. These outcomes are visualized using BioCircos and bar plots as well as plotting entropy value of each genomic location. Moreover, phylogenetic analysis has also been performed to see the evolution of SARS-CoV-2 virus in India. It also shows the wide variation in tree which indeed vivid in genomic analysis. Finally, these SNPs can be the useful target for virus classification, designing and defining the effective dose of vaccine for the heterogeneous population.

Application of a Rat Liver Drug Bioactivation Transcriptional Response Assay Early in Drug Development That Informs Chemically Reactive Metabolite Formation and Potential for Drug-induced Liver Injury

Drug-induced liver injury is a major reason for drug candidate attrition from development, denied commercialization, market withdrawal, and restricted prescribing of pharmaceuticals. The metabolic bioactivation of drugs to chemically reactive metabolites (CRMs) contribute to liver-associated adverse drug reactions in humans that often goes undetected in conventional animal toxicology studies. A challenge for pharmaceutical drug discovery has been reliably selecting drug candidates with a low liability of forming CRM and reduced drug-induced liver injury potential, at projected therapeutic doses, without falsely restricting the development of safe drugs. We have developed an in vivo rat liver transcriptional signature biomarker reflecting the cellular response to drug bioactivation. Measurement of transcriptional activation of integrated nuclear factor erythroid 2-related factor 2 (NRF2)/Kelch-like ECH-associated protein 1 (KEAP1) electrophilic stress, and nuclear factor erythroid 2-related factor 1 (NRF1) proteasomal endoplasmic reticulum (ER) stress responses, is described for discerning estimated clinical doses of drugs with potential for bioactivation-mediated hepatotoxicity. The approach was established using well benchmarked CRM forming test agents from our company. This was subsequently tested using curated lists of commercial drugs and internal compounds, anchored in the clinical experience with human hepatotoxicity, while agnostic to mechanism. Based on results with 116 compounds in short-term rat studies, with consideration of the maximum recommended daily clinical dose, this CRM mechanism-based approach yielded 32% sensitivity and 92% specificity for discriminating safe from hepatotoxic drugs. The approach adds new information for guiding early candidate selection and informs structure activity relationships (SAR) thus enabling lead optimization and mechanistic problem solving. Additional refinement of the model is ongoing. Case examples are provided describing the strengths and limitations of the approach.

Novel advances in biotransformation and bioactivation research-2019 year in review

Biotransformation is one of the main mechanisms used by the body to eliminate drugs. As drug molecules become more complicated, the involvement of drug metabolizing enzymes increases beyond those that are typically studied, such as the cytochrome P450 enzymes. In this review, we try to capture the many outstanding articles that were published in the past year in the field of biotransformation (see Table 1). We have divided the articles into two categories of (1) metabolites and drug metabolizing enzymes, and (2) bioactivation and safety.  This annual review is the fifth of its kind since 2016 (Baillie et al. 2016; Khojasteh et al. 2017, 2018, 2019). This effort in itself also continues to evolve. We have followed the same format we used in previous years in terms of the selection of articles and the authoring of each section. I am pleased of the continued support of Rietjens, Miller, Zhang, Driscoll and Mitra to this review. We would like to welcome Klarissa D. Jackson as a new author for this year's issue. We strive to maintain a balance of authors from academic and industry settings.  We would be pleased to hear your opinions of our commentary, and we extend an invitation to anyone who would like to contribute to a future edition of this review. Cyrus Khojasteh, on behalf of the authors.

Interplay of mitochondrial fission-fusion with cell cycle regulation: Possible impacts on stem cell and organismal aging

Declining mitochondrial function and homeostasis is a hallmark of aging. It is appreciated that the role of mitochondria is much more complex than generating reactive oxygen species to cause aging-related tissue damage. More recent literature describes that the ability of mitochondria to undergo fission or fusion events with each other impacts aging processes. A dynamic balance of mitochondrial fission and fusion events is required to sustain critical cellular functions including cell cycle. Specifically, cell cycle regulators modulate molecular activities of the mitochondrial fission (and fusion) machinery towards regulating cell cycle progression. In this review, we discus literature leading to our understanding on how shifts in the dynamic balance of mitochondrial fission and fusion can modulate progression through, exit from, and re-entry to the cell cycle or in undergoing senescence. Importantly, core regulators of mitochondrial fission or fusion are emerging as crucial stem cell regulators. We discuss the implication of such regulation in stem cells in the context of aging, given that aberrations in adult stem cells promote aging. We also propose a few hypotheses that may provide direction for further understanding about the roles of mitochondrial fission-fusion dynamics in aging biology.

Biotransformation and bioactivation reactions - 2018 literature highlights

In the past three decades, ADME sciences have become an integral component of the drug discovery and development process. At the same time, the field has continued to evolve, thus, requiring ADME scientists to be knowledgeable of and engage with diverse aspects of drug assessment: from pharmacology to toxicology, and from in silico modeling to in vitro models and finally in vivo models. Progress in this field requires deliberate exposure to different aspects of ADME; however, this task can seem daunting in the current age of mass information. We hope this review provides a focused and brief summary of a wide array of critical advances over the past year and explains the relevance of this research ( Table 1 ). We divided the articles into categories of (1) drug optimization, (2) metabolites and drug metabolizing enzymes, and (3) bioactivation. This annual review is the fourth of its kind (Baillie et al. 2016 ; Khojasteh et al. 2017 , 2018 ). We have followed the same format we used in previous years in terms of the selection of articles and the authoring of each section. This effort in itself also continues to evolve. I am pleased that Rietjens, Miller, and Mitra have again contributed to this annual review. We would like to welcome Namandjé N. Bumpus, James P. Driscoll, and Donglu Zhang as authors for this year's issue. We strive to maintain a balance of authors from academic and industry settings. We would be pleased to hear your opinions of our commentary, and we extend an invitation to anyone who would like to contribute to a future edition of this review. Cyrus Khojasteh, on behalf of the authors.

Can Galactose Be Converted to Glucose in HepG2 Cells? Improving the in Vitro Mitochondrial Toxicity Assay for the Assessment of Drug Induced Liver Injury

Human hepatocellular carcinoma cells, HepG2, are often used for drug mediated mitochondrial toxicity assessments. Glucose in HepG2 culture media is replaced by galactose to reveal drug-induced mitochondrial toxicity as a marked shift of drug IC50 values for the reduction of cellular ATP. It has been postulated that galactose sensitizes HepG2 mitochondria by the additional ATP consumption demand in the Leloir pathway. However, our NMR metabolomics analysis of HepG2 cells and culture media showed very limited galactose metabolism. To clarify the role of galactose in HepG2 cellular metabolism, U-¹³C₆-galactose or U-¹³C₆-glucose was added to HepG2 culture media to help specifically track the metabolism of those two sugars. Conversion to U-¹³C₃-lactate was hardly detected when HepG2 cells were incubated with U-¹³C₆-galactose, while an abundance of U-¹³C₃-lactate was produced when HepG2 cells were incubated with U-¹³C₆-glucose. In the absence of glucose, HepG2 cells increased glutamine consumption as a bioenergetics source. The requirement of additional glutamine almost matched the amount of glucose needed to maintain a similar level of cellular ATP in HepG2 cells. This improved understanding of galactose and glutamine metabolism in HepG2 cells helped optimize the ATP-based mitochondrial toxicity assay. The modified assay showed 96% sensitivity and 97% specificity in correctly discriminating compounds known to cause mitochondrial toxicity from those with prior evidence of not being mitochondrial toxicants. The greatest significance of the modified assay was its improved sensitivity in detecting the inhibition of mitochondrial fatty acid β-oxidation (FAO) when glutamine was withheld. Use of this improved assay for an empirical prediction of the likely contribution of mitochondrial toxicity to human DILI (drug induced liver injury) was attempted. According to testing of 65 DILI positive compounds representing numerous mechanisms of DILI together with 55 DILI negative compounds, the overall prediction of mitochondrial mechanism-related DILI showed 25% sensitivity and 95% specificity.

Perceived psychological stress among undergraduate medical students: Role of academic factors

Recently, there is a growing concern about stress during undergraduate medical training. The objectives of our study were to assess perceived stress among undergraduate medical students and to find out academic factors as determinants. A cross-sectional, questionnaire-based survey was carried out among undergraduate medical students of R. G. Kar Medical College, India, during July 2011-June 2012. Perceived stress was assessed using the Perceived Stress Scale-14. A 10-item questionnaire was used to assess academic sources of stress and their severity. The overall mean perceived stress score was 29.58 (standard deviation [SD] = 6.60), and 46.3% of the participants were in the group of more stressed (perceived stress score ≥28). The academic stressor factors predicted 78% of variability of perceived stress. A higher level of perceived stress was reported by the students. The students should be taught different stress management techniques to improve their ability to cope with a demanding professional course.

Biotransformation and bioactivation reactions - 2017 literature highlights *

This annual review is the third one to highlight recent advances in the study and assessment of biotransformations and bioactivations ( Table 1 ). We followed the same format as the previous years with selection and authoring each section (see Baillie et al. 2016 ; Khojasteh et al. 2017 ). We acknowledge that many universities no longer train students in mechanistic biotransformation studies reflecting a decline in the investment for those efforts by public funded granting institutions. We hope this work serves as a resource to appreciate the knowledge gained each year to understand and hopefully anticipate toxicological outcomes dependent on biotransformations and bioactivations. This effort itself also continues to evolve. I am pleased that Drs. Rietjens and Miller have again contributed to this annual review. We would like to welcome Kaushik Mitra as an author for this year's issue, and we thank Deepak Dalvie for his contributions to last year's edition. We have intentionally maintained a balance of authors such that two come from an academic setting and two come from industry. As always, please drop us a note if you find this review helpful. We would be pleased to hear your opinions of our commentary, and we extend an invitation to anyone who would like to contribute to a future edition of this review.

Socio-demographic and Clinico-Epidemiological Study of Scrub Typhus in Two Tertiary Care Hospitals of Kolkata

BACKGROUND AND AIMS

Scrub typhus is the commonest of the rickettsial diseases in India and is difficult to diagnose. Untreated cases have fatality rates of 30-45%. Eschar is present in 7-97% cases. Pneumonia and acute respiratory distress syndrome (ARDS) are frequent complications. Serum immunoglobulin M capture ELISA is the most sensitive test. Doxycycline is the drug of choice. Our objectives were to study the socio-demographic and clinic-epidemiological profiles of scrub typhus cases in two tertiary care hospitals in Kolkata, India. This was the first study of scrub typhus in Southern West Bengal and its neighboring areas. .

METHODS

Study was conducted over 16 months and all fever cases of Tropical Medicine / Medicine outpatients' clinics were evaluated.

RESULTS

Fourteen cases were diagnosed. 78.6% were from rural areas and 35.7% were farmers. Headache and fever were the commonest presenting complaints while eschar was found in only 21.4%. Serum IgM scrub typhus antibody was positive in all cases .

CONCLUSION

Scrub typhus should be a differential diagnosis in acute febrile illness cases, as early diagnosis and therapy prevents complications.

Finite element modeling, validation, and parametric investigations of a retinal reattachment stent

A new retinal reattachment surgical procedure is based on a stent that is deployed to press the retina back in place. An eye-stent finite element model studied the strain induced by the stent on retina. Finite element model simulations were performed for several stent geometric configurations (number of loops, wire diameter, and intraocular pressure). The finite element model was validated against experiment. Parametric studies demonstrated that stents could be successfully designed so that the maximum strain would be below permanent damage strain threshold of 2%.

Relationship between Nutritional Support and Tuberculosis Treatment Outcomes in West Bengal, India

Introduction

Poverty and poor nutrition are associated with the risk of developing tuberculosis (TB). Socioeconomic factors may interfere with anti-tuberculosis treatment compliance and its outcome. We examined whether providing nutritional support (monthly supply of rice and lentil beans) to TB patients who live below the poverty line was associated with TB treatment outcome.

Methods

This was a retrospective cohort study of sputum smear-positive pulmonary TB patients living below the poverty line (income of <$1.25 per day) registered for anti-tuberculosis treatment in two rural districts of West Bengal, India during 2012 to 2013. We compared treatment outcomes among patients who received nutritional support with those who did not. A log-binomial regression model was used to assess the relation between nutritional support and unsuccessful treatment outcome (loss-to-follow-up, treatment failure and death).

Results

Of 173 TB patients provided nutritional support, 15 (9%) had unsuccessful treatment outcomes, while 84 (21%) of the 400 not provided nutrition support had unsuccessful treatment outcomes (p < 0.001). After adjusting for age, sex and previous treatment, those who received nutritional support had a 50% reduced risk of unsuccessful treatment outcome than those who did not receive nutritional support (Relative Risk: 0.51; 95% Confidence Intervals: 0.30 - 0.86).

Conclusion

Under programmatic conditions, monthly rations of rice and lentils were associated with lower risk of unsuccessful treatment outcome among impoverished TB patients. Given the relatively small financial commitment needed per patient ($10 per patient per month), the national TB programme should consider scaling up nutritional support among TB patients living below the poverty line.

Discovery and Clinical Evaluation of MK-8150, A Novel Nitric Oxide Donor With a Unique Mechanism of Nitric Oxide Release

Background

Nitric oxide donors are widely used to treat cardiovascular disease, but their major limitation is the development of tolerance, a multifactorial process to which the in vivo release of nitric oxide is thought to contribute. Here we describe the preclinical and clinical results of a translational drug development effort to create a next‐generation nitric oxide donor with improved pharmacokinetic properties and a unique mechanism of nitric oxide release through CYP3A4 metabolism that was designed to circumvent the development of tolerance.

Methods and Results

Single‐ and multiple‐dose studies in telemetered dogs showed that MK‐8150 induced robust blood‐pressure lowering that was sustained over 14 days. The molecule was safe and well tolerated in humans, and single doses reduced systolic blood pressure by 5 to 20 mm Hg in hypertensive patients. Multiple‐dose studies in hypertensive patients showed that the blood‐pressure–lowering effect diminished after 10 days, and 28‐day studies showed that the hemodynamic effects were completely lost by day 28, even when the dose of MK‐8150 was increased during the dosing period.

Conclusions

The novel nitric oxide donor MK‐8150 induced significant blood‐pressure lowering in dogs and humans for up to 14 days. However, despite a unique mechanism of nitric oxide release mediated by CYP3A4 metabolism, tolerance developed over 28 days, suggesting that tolerance to nitric oxide donors is multifactorial and cannot be overcome solely through altered in vivo release of nitric oxide.

Clinical Trial Registration

URL: http://www.clinicaltrials.gov. Unique identifiers: NCT01590810 and NCT01656408.

Discovery of Novel Indoline Cholesterol Ester Transfer Protein Inhibitors (CETP) through a Structure-Guided Approach

Using the collective body of known (CETP) inhibitors as inspiration for design, a structurally novel series of tetrahydroquinoxaline CETP inhibitors were discovered. An exemplar from this series, compound 5, displayed potent in vitro CETP inhibition and was efficacious in a transgenic cynomologus-CETP mouse HDL PD (pharmacodynamic) assay. However, an undesirable metabolic profile and chemical instability hampered further development of the series. A three-dimensional structure of tetrahydroquinoxaline inhibitor 6 was proposed from (1)H NMR structural studies, and this model was then used in silico for the design of a new class of compounds based upon an indoline scaffold. This work resulted in the discovery of compound 7, which displayed potent in vitro CETP inhibition, a favorable PK-PD profile relative to tetrahydroquinoxaline 5, and dose-dependent efficacy in the transgenic cynomologus-CETP mouse HDL PD assay.

α-Solanine induces ROS-mediated autophagy through activation of endoplasmic reticulum stress and inhibition of Akt/mTOR pathway

α-Solanine is a glycoalkaloid found in species of the nightshade family including potato. It was primarily reported to have toxic effects in humans. However, there is a growing body of literature demonstrating in vitro and in vivo anticancer activity of α-solanine. Most of these studies have shown activation of apoptosis as the underlying mechanism in antitumor activity of α-solanine. In this study, we report α-solanine as a potential inducer of autophagy, which may act synergistically or in parallel with apoptosis to exert its cytotoxic effect. Induction of autophagy was demonstrated by several assays including electron microscopy, immunoblotting of autophagy markers and immunofluorescence for LC3 (microtubule-associated protein 1 (MAP1) light chain-3) puncta. α-Solanine-induced autophagic flux was demonstrated by additionally enhanced – turnover of LC3-II and – accumulation of LC3-specific puncta after co-incubation of cells with either of the autophagolysosome inhibitors – chloroquine and – bafilomycin A1. We also demonstrated α-solanine-induced oxidative damage in regulating autophagy where pre-incubation of cells with reactive oxygen species (ROS) scavenger resulted in suppression of CM-H₂DCFDA (5 (and 6)-chloromethyl-2′,7′-dichlorodihydrofluorescein diacetate acetyl ester) fluorescence as well as decrease in LC3-II turnover. α-Solanine treatment caused an increase in the expression of endoplasmic reticulum (ER) stress proteins (BiP, activating transcription factor 6 (ATF6), X-box-binding protein 1, PERK, inositol-requiring transmembrane kinase/endonuclease 1, ATF4 and CCAAT-enhancer-binding protein (C/EBP)-homologous protein) suggesting activation of unfolded protein response pathway. Moreover, we found downregulation of phosphorylated Akt (Thr³⁰⁸ and Ser⁴⁷³), mammalian target of rapamycin (mTOR; Ser²⁴⁴⁸ and Ser²⁴⁸¹) and 4E-BP1 (Thr^37/46) by α-solanine implying suppression of the Akt/mTOR pathway. Collectively, our results signify that α-solanine induces autophagy to exert anti-proliferative activity by triggering ER stress and inhibiting Akt/mTOR signaling pathway.

Generalized assorted camera arrays: robust cross-channel registration and applications

One popular technique for multimodal imaging is generalized assorted pixels (GAP), where an assorted pixel array on the image sensor allows for multimodal capture. Unfortunately, GAP is limited in its applicability because of the need for multimodal filters that are amenable with semiconductor fabrication processes and results in a fixed multimodal imaging configuration. In this paper, we advocate for generalized assorted camera (GAC) arrays for multimodal imaging--i.e., a camera array with filters of different characteristics placed in front of each camera aperture. The GAC provides us with three distinct advantages over GAP: ease of implementation, flexible application-dependent imaging since filters are external and can be changed and depth information that can be used for enabling novel applications (e.g., postcapture refocusing). The primary challenge in GAC arrays is that since the different modalities are obtained from different viewpoints, there is a need for accurate and efficient cross-channel registration. Traditional approaches such as sum-of-squared differences, sum-of-absolute differences, and mutual information all result in multimodal registration errors. Here, we propose a robust cross-channel matching cost function, based on aligning normalized gradients, which allows us to compute cross-channel subpixel correspondences for scenes exhibiting nontrivial geometry. We highlight the promise of GAC arrays with our cross-channel normalized gradient cost for several applications such as low-light imaging, postcapture refocusing, skin perfusion imaging using color + near infrared, and hyperspectral imaging.

A Framework for Analysis of Computational Imaging Systems: Role of Signal Prior, Sensor Noise and Multiplexing

Over the last decade, a number of computational imaging (CI) systems have been proposed for tasks such as motion deblurring, defocus deblurring and multispectral imaging. These techniques increase the amount of light reaching the sensor via multiplexing and then undo the deleterious effects of multiplexing by appropriate reconstruction algorithms. Given the widespread appeal and the considerable enthusiasm generated by these techniques, a detailed performance analysis of the benefits conferred by this approach is important. Unfortunately, a detailed analysis of CI has proven to be a challenging problem because performance depends equally on three components: (1) the optical multiplexing, (2) the noise characteristics of the sensor, and (3) the reconstruction algorithm which typically uses signal priors. A few recent papers [12], [30], [49] have performed analysis taking multiplexing and noise characteristics into account. However, analysis of CI systems under state-of-the-art reconstruction algorithms, most of which exploit signal prior models, has proven to be unwieldy. In this paper, we present a comprehensive analysis framework incorporating all three components. In order to perform this analysis, we model the signal priors using a Gaussian Mixture Model (GMM). A GMM prior confers two unique characteristics. First, GMM satisfies the universal approximation property which says that any prior density function can be approximated to any fidelity using a GMM with appropriate number of mixtures. Second, a GMM prior lends itself to analytical tractability allowing us to derive simple expressions for the `minimum mean square error' (MMSE) which we use as a metric to characterize the performance of CI systems. We use our framework to analyze several previously proposed CI techniques (focal sweep, flutter shutter, parabolic exposure, etc.), giving conclusive answer to the question: `How much performance gain is due to use of a signal prior and how much is due to multiplexing? Our analysis also clearly shows that multiplexing provides significant performance gains above and beyond the gains obtained due to use of signal priors.

Short-Pulse Laser-Based System for Detection of Tumors: Administration of Gold Nanoparticles Enhances Contrast

The objective of this paper is to demonstrate the use of gold nanoparticles, which accumulate in tumors due to the leakiness of tumor vasculature, as contrast agents for enhanced imaging in a time-resolved optical tomography system using short-pulse lasers for skin cancer detection in mouse model. It is found that intravenously administrated spherical gold nanoparticles broadened the temporal profile of reflected optical signals and enhanced the contrast between surrounding normal tissue and tumors. These results show that gold nanoparticles tuned to the wavelength of the laser can enhance the resolution and precision of laser-based cancer detection system.

Mucoadhesive nanoparticles for prolonged ocular delivery of natamycin: In vitro and pharmacokinetics studies

The aim of this study was to prepare natamycin encapsulated lecithin/chitosan mucoadhesive nanoparticles (NPs) for prolonged ocular application. These NPs were characterized by their mean particle size 213nm, encapsulation efficiency 73.57%, with a theoretical drug loading 5.09% and zeta potential +43. In vitro release exhibited a biphasic drug release profile with initial burst followed by a very slow drug release. The MIC(90) and zone of inhibition of NPs showed similar antifungal activity as compared to marketed suspension and free natamycin against Candida albicans and Aspergillus fumigates. The ocular pharmacokinetics of NPs and marketed formulation were evaluated in NZ rabbits. The NPs exhibit significant mucin adhesion. The AUC((0-∞)) was increased up to 1.47 fold and clearance was decreased up to 7.4-fold as compared to marketed suspension. The PK-PD and pharmacokinetic simulation was carried out to estimate optimum dosing regimen for good efficacy. Thus, lecithin/chitosan NPs could be considered useful approach aiming to prolong ocular residence and reduce dosing frequency.