Recent Smell Loss Is the Best Predictor of COVID-19 Among Individuals With Recent Respiratory Symptoms.

In a preregistered, cross-sectional study, we investigated whether olfactory loss is a reliable predictor of COVID-19 using a crowdsourced questionnaire in 23 languages to assess symptoms in individuals self-reporting recent respiratory illness. We quantified changes in chemosensory abilities during the course of the respiratory illness using 0-100 visual analog scales (VAS) for participants reporting a positive (C19+; n = 4148) or negative (C19-; n = 546) COVID-19 laboratory test outcome. Logistic regression models identified univariate and multivariate predictors of COVID-19 status and post-COVID-19 olfactory recovery.

Identification of Potential Phosphorylation in the Cytoplasmic Domain of Epithelial Cell Adhesion Molecule.

The epithelial cell adhesion molecule (EpCAM) is a transmembrane cell adhesion glycoprotein, which primarily contributes to stemness, proliferation, and metastasis properties of tumor cells. Regulated intramembrane proteolysis by ADAM proteases and γ-secretase cleaves EpCAM into an ∼27 kDa soluble extracellular and an ∼4 kDa cytoplasmic domain (EpICD). After the EpICD fragment is released inside the cell, the formation of a nuclear signaling complex with the FHL2 molecule is critical for exerting its regulatory role.

Correction to: Molecular signature comprising 11 platelet-genes enables accurate blood-based diagnosis of NSCLC.

An amendment to this paper has been published and can be accessed via the original article.

Molecular signature comprising 11 platelet-genes enables accurate blood-based diagnosis of NSCLC.

Background: Early diagnosis is crucial for effective medical management of cancer patients. Tissue biopsy has been widely used for cancer diagnosis, but its invasive nature limits its application, especially when repeated biopsies are needed. Over the past few years, genomic explorations have led to the discovery of various blood-based biomarkers.

UniPath: a uniform approach for pathway and gene-set based analysis of heterogeneity in single-cell epigenome and transcriptome profiles.

Recent advances in single-cell open-chromatin and transcriptome profiling have created a challenge of exploring novel applications with a meaningful transformation of read-counts, which often have high variability in noise and drop-out among cells. Here, we introduce UniPath, for representing single-cells using pathway and gene-set enrichment scores by a transformation of their open-chromatin or gene-expression profiles. The robust statistical approach of UniPath provides high accuracy, consistency and scalability in estimating gene-set enrichment scores for every cell.

RecipeDB: a resource for exploring recipes.

Cooking is the act of turning nature into the culture, which has enabled the advent of the omnivorous human diet. The cultural wisdom of processing raw ingredients into delicious dishes is embodied in their cuisines. Recipes thus are the cultural capsules that encode elaborate cooking protocols for evoking sensory satiation as well as providing nourishment.

AlgPred 2.0: an improved method for predicting allergenic proteins and mapping of IgE epitopes.

AlgPred 2.0 is a web server developed for predicting allergenic proteins and allergenic regions in a protein. It is an updated version of AlgPred developed in 2006.

A Web-Based Platform on Coronavirus Disease-19 to Maintain Predicted Diagnostic, Drug, and Vaccine Candidates.

A web-based resource CoronaVIR (https://webs.iiitd.edu.

Computer-aided prediction and design of IL-6 inducing peptides: IL-6 plays a crucial role in COVID-19.

Interleukin 6 (IL-6) is a pro-inflammatory cytokine that stimulates acute phase responses, hematopoiesis and specific immune reactions. Recently, it was found that the IL-6 plays a vital role in the progression of COVID-19, which is responsible for the high mortality rate. In order to facilitate the scientific community to fight against COVID-19, we have developed a method for predicting IL-6 inducing peptides/epitopes.

Analysis of single-cell transcriptomes links enrichment of olfactory receptors with cancer cell differentiation status and prognosis.

Ectopically expressed olfactory receptors (ORs) have been linked with multiple clinically-relevant physiological processes. Previously used tissue-level expression estimation largely shadowed the potential role of ORs due to their overall low expression levels. Even after the introduction of the single-cell transcriptomics, a comprehensive delineation of expression dynamics of ORs in tumors remained unexplored.

GROEL/ES Buffers Entropic Traps in Folding Pathway during Evolution of a Model Substrate.

The folding landscape of proteins can change during evolution with the accumulation of mutations that may introduce entropic or enthalpic barriers in the protein folding pathway, making it a possible substrate of molecular chaperones in vivo. Can the nature of such physical barriers of folding dictate the feasibility of chaperone-assistance? To address this, we have simulated the evolutionary step to chaperone-dependence keeping GroEL/ES as the target chaperone and GFP as a model protein in an unbiased screen. We find that the mutation conferring GroEL/ES dependence in vivo and in vitro encode an entropic trap in the folding pathway rescued by the chaperonin.

The Cellular basis of loss of smell in 2019-nCoV-infected individuals.

A prominent clinical symptom of 2019-novel coronavirus (nCoV) infection is hyposmia/anosmia (decrease or loss of sense of smell), along with general symptoms such as fatigue, shortness of breath, fever and cough. The identity of the cell lineages that underpin the infection-associated loss of olfaction could be critical for the clinical management of 2019-nCoV-infected individuals. Recent research has confirmed the role of angiotensin-converting enzyme 2 (ACE2) and transmembrane protease serine 2 (TMPRSS2) as key host-specific cellular moieties responsible for the cellular entry of the virus.

AntiCP 2.0: an updated model for predicting anticancer peptides.

Increasing use of therapeutic peptides for treating cancer has received considerable attention of the scientific community in the recent years. The present study describes the in silico model developed for predicting and designing anticancer peptides (ACPs). ACPs residue composition analysis show the preference of A, F, K, L and W.

Experimental demonstration of broadband solar absorption beyond the lambertian limit in certain thin silicon photonic crystals.

The tantalizing possibility of 31% solar-to-electric power conversion efficiency in thin film crystalline silicon solar cell architectures relies essentially on solar absorption well beyond the Lambertian light trapping limit (Bhattacharya and John in Nat Sci Rep 9:12482, 2019). Up to now, no solar cell architecture has exhibited above-Lambertian solar absorption, integrated over the broad solar spectrum. In this work, we experimentally demonstrate two types of photonic crystal (PhC) solar cells architectures that exceed Lambertian light absorption, integrated over the entire 300-1,200 nm wavelength band.

Identification of prognostic biomarkers for major subtypes of non-small-cell lung cancer using genomic and clinical data.

Purpose: Intra-tumor heterogeneity and high mortality among patients with non-small-cell lung carcinoma (NSCLC) emphasize the need to identify reliable prognostic markers unique to each subtype.

Methods: In this study, univariate cox regression and prognostic index (PI)-based approaches were used to develop models for predicting NSCLC patients' subtype-specific survival.

Results: Prognostic analysis of TCGA dataset identified 1334 and 2129 survival-specific genes for LUSC (488 samples) and LUAD (497 samples), respectively.

Development of data dictionary for neonatal intensive care unit: advancement towards a better critical care unit.

Background: Critical care units (CCUs) with extensive use of various monitoring devices generate massive data. To utilize the valuable information of these devices; data are collected and stored using systems like clinical information system and laboratory information management system. These systems are proprietary, allow limited access to their database and, have the vendor-specific clinical implementation.

GABA Concentration in the Left Ventral Premotor Cortex Associates With Sensory Hyper-Responsiveness in Autism Spectrum Disorders Without Intellectual Disability.

Individuals with autism spectrum disorder (ASD) often exhibit abnormal processing of sensory inputs from multiple modalities and higher-order cognitive/behavioral response to those inputs. Several lines of evidence suggest that altered γ-aminobutyric acid (GABA), the main inhibitory neurotransmitter in the brain, is a central characteristic of the neurophysiology of ASD. The relationship between GABA in particular brain regions and atypical sensory processing in ASD is poorly understood.

Graph transform learning.

Transform learning is a new representation learning framework where we learn an operator/transform that analyses the data to generate the coefficient/representation. We propose a variant of it called the graph transform learning; in this we explicitly account for the correlation in the dataset in terms of graph Laplacian. We will give two variants; in the first one the graph is computed from the data and fixed during the operation.

Neural Basis of Extremely High Temporal Sensitivity: Insights From a Patient With Autism.

The human brain is sensitive to incoming sensory information across multiple time scales. Temporal scales of information represented in the brain generally constrain behavior. Despite reports of the neural correlates of millisecond timing, how the human brain processes sensory stimuli in the sub-second range (≤100 ms) and its behavioral implications are areas of active scientific inquiry.

CancerEnD: A database of cancer associated enhancers.

CancerEnD is an integrated resource developed for annotating 8524 unique expressed enhancers, associated genes, somatic mutations and copy number variations of 8063 cancer samples from 18 cancer types of TCGA. Somatic mutation data was taken from the COSMIC repository. To delineate the relationship of change in copy number of enhancer elements with the prognosis of cancer patients, survival analysis was done using the survival package in R.

Computer-aided designing of oncolytic viruses for overcoming translational challenges of cancer immunotherapy.

Wild-type and genetically engineered oncolytic viruses (OVs) represent powerful therapeutic agents in cancer immunotherapy. Several OV species are in clinical trials for cancer treatment. Preclinical and clinical trials revealed several issues related to OV therapy in terms of viral delivery, spread, antiviral immune response, and tumor resistance.

Integrative Analysis and Machine Learning based Characterization of Single Circulating Tumor Cells.

We collated publicly available single-cell expression profiles of circulating tumor cells (CTCs) and showed that CTCs across cancers lie on a near-perfect continuum of epithelial to mesenchymal (EMT) transition. Integrative analysis of CTC transcriptomes also highlighted the inverse gene expression pattern between PD-L1 and MHC, which is implicated in cancer immunotherapy. We used the CTCs expression profiles in tandem with publicly available peripheral blood mononuclear cell (PBMC) transcriptomes to train a classifier that accurately recognizes CTCs of diverse phenotype.