Targeting PIKfyve-driven lipid homeostasis as a metabolic vulnerability in pancreatic cancer.

Pancreatic ductal adenocarcinoma (PDAC) subsists in a nutrient-deregulated microenvironment, making it particularly susceptible to treatments that interfere with cancer metabolism. For example, PDAC utilizes and is dependent on high levels of autophagy and other lysosomal processes. Although targeting these pathways has shown potential in preclinical studies, progress has been hampered by the challenge of identifying and characterizing favorable targets for drug development.

Comparative impact assessment of COVID-19 policy interventions in five South Asian countries using reported and estimated unreported death counts during 2020-2021.

There has been raging discussion and debate around the quality of COVID death data in South Asia. According to WHO, of the 5.5 million reported COVID-19 deaths from 2020-2021, 0.

BaySyn: Bayesian Evidence Synthesis for Multi-system Multiomic Integration.

The discovery of cancer drivers and drug targets are often limited to the biological systems - from cancer model systems to patients. While multiomic patient databases have sparse drug response data, cancer model systems databases, despite covering a broad range of pharmacogenomic platforms, provide lower lineage-specific sample sizes, resulting in reduced statistical power to detect both functional driver genes and their associations with drug sensitivity profiles. Hence, integrating evidence across model systems, taking into account the pros and cons of each system, in addition to multiomic integration, can more efficiently deconvolve cellular mechanisms of cancer as well as learn therapeutic associations.

Role of multiresolution vulnerability indices in COVID-19 spread in India: a Bayesian model-based analysis.

Objectives: COVID-19 has differentially affected countries, with health infrastructure and other related vulnerability indicators playing a role in determining the extent of its spread. Vulnerability of a geographical region to COVID-19 has been a topic of interest, particularly in low-income and middle-income countries like India to assess its multifactorial impact on incidence, prevalence or mortality. This study aims to construct a statistical analysis pipeline to compute such vulnerability indices and investigate their association with metrics of the pandemic growth.

Randomized controlled trial of EndoRings assisted colonoscopy versus standard colonoscopy.

Objectives: The EndoRings device is a distal attachment consisting of two layers of circular flexible rings that evert mucosal folds. The aim of this study was to investigate whether EndoRing assisted colonoscopy (ER) improves polyp and adenoma detection compared to standard colonoscopy (SC).

Methods: Multicenter, parallel group, randomized controlled trial.

Lessons from SARS-CoV-2 in India: A data-driven framework for pandemic resilience.

India experienced a massive surge in SARS-CoV-2 infections and deaths during April to June 2021 despite having controlled the epidemic relatively well during 2020. Using counterfactual predictions from epidemiological disease transmission models, we produce evidence in support of how strengthening public health interventions early would have helped control transmission in the country and significantly reduced mortality during the second wave, even without harsh lockdowns. We argue that enhanced surveillance at district, state, and national levels and constant assessment of risk associated with increased transmission are critical for future pandemic responsiveness.

A comparison of five epidemiological models for transmission of SARS-CoV-2 in India.

Background: Many popular disease transmission models have helped nations respond to the COVID-19 pandemic by informing decisions about pandemic planning, resource allocation, implementation of social distancing measures, lockdowns, and other non-pharmaceutical interventions. We study how five epidemiological models forecast and assess the course of the pandemic in India: a baseline curve-fitting model, an extended SIR (eSIR) model, two extended SEIR (SAPHIRE and SEIR-fansy) models, and a semi-mechanistic Bayesian hierarchical model (ICM).

Methods: Using COVID-19 case-recovery-death count data reported in India from March 15 to October 15 to train the models, we generate predictions from each of the five models from October 16 to December 31.

Incorporating false negative tests in epidemiological models for SARS-CoV-2 transmission and reconciling with seroprevalence estimates.

Susceptible-Exposed-Infected-Removed (SEIR)-type epidemiologic models, modeling unascertained infections latently, can predict unreported cases and deaths assuming perfect testing. We apply a method we developed to account for the high false negative rates of diagnostic RT-PCR tests for detecting an active SARS-CoV-2 infection in a classic SEIR model. The number of unascertained cases and false negatives being unobservable in a real study, population-based serosurveys can help validate model projections.

Comprehensive public health evaluation of lockdown as a non-pharmaceutical intervention on COVID-19 spread in India: national trends masking state-level variations.

Objectives: To evaluate the effect of four-phase national lockdown from March 25 to May 31 in response to the COVID-19 pandemic in India and unmask the state-wise variations in terms of multiple public health metrics.

Design: Cohort study (daily time series of case counts).

Setting: Observational and population based.

Predictions, role of interventions and effects of a historic national lockdown in India's response to the COVID-19 pandemic: data science call to arms.

With only 536 cases and 11 fatalities, India took the historic decision of a 21-day national lockdown on March 25. The lockdown was first extended to May 3 soon after the analysis of this paper was completed, and then to May 18 while this paper was being revised. In this paper, we use a Bayesian extension of the Susceptible-Infected-Removed (eSIR) model designed for intervention forecasting to study the short- and long-term impact of an initial 21-day lockdown on the total number of COVID-19 infections in India compared to other less severe non-pharmaceutical interventions.

A Comprehensive Public Health Evaluation of Lockdown as a Non-pharmaceutical Intervention on COVID-19 Spread in India: National Trends Masking State Level Variations.

Introduction: India has been under four phases of a national lockdown from March 25 to May 31 in response to the COVID-19 pandemic. Unmasking the state-wise variation in the effect of the nationwide lockdown on the progression of the pandemic could inform dynamic policy interventions towards containment and mitigation.

Methods: Using data on confirmed COVID-19 cases across 20 states that accounted for more than 99% of the cumulative case counts in India till May 31, 2020, we illustrate the masking of state-level trends and highlight the variations across states by presenting evaluative evidence on some aspects of the COVID-19 outbreak: case-fatality rates, doubling times of cases, effective reproduction numbers, and the scale of testing.

Personalized Network Modeling of the Pan-Cancer Patient and Cell Line Interactome.

Purpose: Personalized network inference on diverse clinical and in vitro model systems across cancer types can be used to delineate specific regulatory mechanisms, uncover drug targets and pathways, and develop individualized predictive models in cancer.

Methods: We developed TransPRECISE (personalized cancer-specific integrated network estimation model), a multiscale Bayesian network modeling framework, to analyze the pan-cancer patient and cell line interactome to identify differential and conserved intrapathway activities, to globally assess cell lines as representative models for patients, and to develop drug sensitivity prediction models. We assessed pan-cancer pathway activities for a large cohort of patient samples (> 7,700) from the Cancer Proteome Atlas across ≥ 30 tumor types, a set of 640 cancer cell lines from the MD Anderson Cell Lines Project spanning 16 lineages, and ≥ 250 cell lines' response to > 400 drugs.

Network-Based Matching of Patients and Targeted Therapies for Precision Oncology.

The extensive acquisition of high-throughput molecular profiling data across model systems (human tumors and cancer cell lines) and drug sensitivity data, makes precision oncology possible - allowing clinicians to match the right drug to the right patient. Current supervised models for drug sensitivity prediction, often use cell lines as exemplars of patient tumors and for model training. However, these models are limited in their ability to accurately predict drug sensitivity of individual cancer patients to a large set of drugs, given the paucity of patient drug sensitivity data used for testing and high variability across different drugs.

Endocuff-assisted vs. standard colonoscopy in the fecal occult blood test-based UK Bowel Cancer Screening Programme (E-cap study): a randomized trial.

 Up to 25 % colorectal adenomas are missed during colonoscopy. The aim of this study was to investigate whether the endocuff could improve polyp detection in an organized bowel cancer screening program (BCSP).  This parallel group, single-blinded, randomized controlled trial included patients with positive fecal occult blood test (FOBT) who were attending for BCSP colonoscopy.

A randomized controlled trial of pre-procedure simethicone and N-acetylcysteine to improve mucosal visibility during gastroscopy - NICEVIS.

Mucosal views can be impaired by residual bubbles and mucus during gastroscopy. This study aimed to determine whether a pre-gastroscopy drink containing simethicone and N-acetylcysteine improves mucosal visualisation. We conducted a randomized controlled trial recruiting 126 subjects undergoing routine gastroscopy.

Knife-assisted snare resection (KAR) of large and refractory colonic polyps at a Western centre: Feasibility, safety and efficacy study to guide future practice.

Objective: Endoscopic mucosal resection (EMR) is widely practiced in western countries. Endoscopic submucosal dissection (ESD) is very effective for treating complex polyps but colonic ESD in the western setting remains challenging. We have developed a novel technique of knife-assisted snare resection (KAR) for the resection of these complex lesions.

Knife-assisted snare resection: a novel technique for resection of scarred polyps in the colon.

Background And Study Aims: There have been significant advances in the management of complex colorectal polyps. Previous failed resection or polyp recurrence is associated with significant fibrosis, making endoscopic resection extremely challenging; the traditional approach to these lesions is surgery. The aim of this study was to evaluate the efficacy of a novel, knife-assisted snare resection (KAR) technique in the resection of scarred colonic polyps.

The role of acetic acid in the management of Barrett's oesophagus.

Barrett's oesophagus is of significant importance due to its premalignant potential. Acetic acid chromoendoscopy is a simple technique that can be used with any endoscope system. It has been utilised for the identification of Barrett's intestinal metaplasia; and more importantly, for the localisation of early neoplasia within Barrett's, which is often focal, subtle and very easy to miss by random quadrantic biopsies alone.

Acetic acid chromoendoscopy in Barrett's esophagus surveillance is superior to the standardized random biopsy protocol: results from a large cohort study (with video).

Background: Currently, various advanced endoscopic techniques are available with varying success rates. These technologies are manufacturer dependent, which has financial implications in the current era of austerity. Acetic acid is a commonly available dye that has been used in the detection of neoplasia within Barrett's esophagus.