Biology subjects

Sharma, A. D.

Publications and source records attributed to Sharma, A. D..

7 recordsLinked to original sources

bioRxiv2026

Rationalizing the application of spatial capture-recapture versus space-to-event models for monitoring populations of an endangered social carnivore

Reliable estimates of population size are fundamental to understanding wildlife population status and informing conservation. Obtaining such estimates remains challenging for unmarked species, particularly in tropical countries where logistical and financial constraints limit intensive monitoring. The endangered dhole (Cuon alpinus), a highly social canid without natural markings, is one such species for which robust population estimates remain scarce. We estimated dhole density in the Valparai plateau, a human-dominated agroforest-forest mosaic in India's Western Ghats. We compared Spatially Explicit Capture-Recapture (SECR) models based on individual identification from fecal DNA and Space-to-Event (STE) models based on camera-trap detections. We additionally applied both approaches to individually identifiable leopards (Panthera pardus) to cross-validate STE versus SECR estimates. SECR estimated dhole density at 22 individuals per 100 sq.km, with STE estimates varying substantially depending on how the camera viewshed area was defined. STE estimates based on post hoc viewshed measurements, particularly after reducing the viewshed by 10%, were comparable to SECR estimates. In contrast, STE underestimated leopard density relative to SECR (7 versus 12 per 100 sq.km), although uncertainty intervals overlapped. Ecologically, our results indicate that human-use agroforest mosaics can support dhole densities comparable to, or exceeding, those reported from several Protected Areas, highlighting their potential importance for dhole conservation. More broadly, we argue that STE models may offer a practical and relatively inexpensive approach for baseline monitoring of dholes from camera-trap surveys, but their reliability depends strongly on accurate characterization of the effective viewshed and may vary across species and landscapes.

ecology↗

bioRxiv2026

Real Science Is Harder Than Benchmarks: Evaluating Advanced AI Frameworks on Published Studies. I. Uncertainty Quantification, ML on Therapeutic Data Commons, and Agent-Based Modeling

Artificial Intelligence (AI) frameworks for automating scientific research have shown strong performance on benchmarks, but their capacity to routinely reproduce results from multiple real-life published studies remains largely untested. We evaluated five advanced AI research frameworks (Kosmos, K-Dense, ToolUniverse, BioAgents from bio.xyz, and the AI Scientist-v2 from Sakana AI) on three real-life tasks (including two recently published papers) spanning uncertainty quantification for molecular property predictions, machine learning on Therapeutic Data Commons benchmarks, and agent-based modeling. AI frameworks demonstrated genuine strengths: generating original hypotheses, competently executing routine data acquisition and coding tasks, providing statistical measures of confidence often absent from the original papers, and producing well-formatted final reports. At the same time, our experiments revealed that real-world scientific tasks remain considerably harder than current benchmarks suggest. No AI framework matched the scope or depth of the original studies, results varied across multiple runs of the same framework with the same prompt, and we documented cases of severe hallucinations in final reports, gaps in literature coverage, and overconfident conclusions. Verification of AI outputs required substantial domain expertise. While these three tasks are only partially representative of the broader scientific landscape, they offer a starting point for developing a more rigorous methodology for evaluation of AI performance than what is currently practiced. We conclude that AI frameworks are already valuable for prototyping research directions and stress-testing completed studies, and some of the limitations documented here appear largely tractable through infrastructure improvements and continued development.

bioinformatics↗

bioRxiv2026

A metabolic labelling-based lipid imaging technology establishes VPS13A as a phosphatidylethanolamine lipid transfer protein

The ability to image specific lipid subtypes within cells can have a transformative impact on the study of lipid dynamics and trafficking mechanisms. Herein, we describe a technology for imaging phosphatidylethanolamine (PE) lipids in live mammalian cells that involved screening a library of ethanolamine derivatives to identify an azido compound that efficiently metabolically labels PE. Crucially, this probe evades the cellular methylation machinery specifically labelling PE without forming labelled methylated PE and phosphatidylcholine (PC) lipids. The administration of cyclooctyne dyes to cells metabolically labelled with this probe rendered azido PE lipids fluorescent via strain-promoted click chemistry, enabling imaging. We employed this technology to image PE in various cellular organelles, visualize PE externalization during apoptosis, and discover that the VPS13A protein transports PE from the endoplasmic reticulum to the mitochondria. This technology will facilitate addressing fundamental questions in PE biology and studying dysregulation of PE dynamics and trafficking in disease states.

cell biology↗

bioRxiv2026

Direct RNA Sequencing reveals epitranscriptomic regulation of brain cells and Alzheimer's Disease pathology

Alternative mRNA splicing and post-transcriptional RNA modification are key mechanisms that regulate transcript function; however, their role in neuronal activity and neurodegenerative disease remains poorly defined. In this study, we evaluated two nanopore-based long-read sequencing (LR-seq) formats: cDNA-PCR sequencing (CPS) and direct RNA sequencing (DRS). We then applied DRS to profile both full-length isoforms and RNA modifications in major brain cell types derived from induced pluripotent stem cells (iPSCs) and post-mortem Alzheimers disease (AD) brains. Relative to CPS, DRS achieved higher accuracy and sensitivity for transcript quantification, de novo transcript model construction, and open reading frame (ORF) annotation across neuropathological gene sets. Focusing on iPSC-derived neurons, we built a multi-omic atlas to connect transcriptional output with translational engagement and protein abundance, by integrating DRS-based mRNA abundance, N6-methyladenosine (m6A) status and poly(A) tail length with ribosome profiling (Ribo-seq) and mass spectrometry (MS). The combination of DRS and Ribo-seq data demonstrated synergism in predicting protein abundance. This analysis also uncovered a significant inverse relationship between m6A modification and mRNA abundance, which was dependent on the engagement of the ribosomal A-site. Lastly, we applied DRS to the epitranscriptomic analysis of AD brain samples, demonstrating that m6A profiles can be used to distinguish early-versus late-stage disease.

neuroscience↗

bioRxiv2025

Hypoimmunogenic human motor neurons induced from iPSCs in vivo substantially ameliorate ALS disease in large animal models

Stem cell-based therapy holds great potential for substituting degenerated motor neurons (MNs) in amyotrophic lateral sclerosis (ALS). Missing protocols for advanced differentiation of transplanted cells into MNs, immune rejection, and the lack of suitable ALS models for preclinical trials have slowed the development of effective therapies. Here, we employed multiplex genetic-editing to generate a novel human pluripotent stem cell line containing doxycycline (Dox)-inducible MNs-specific transcription factors and comprehensively modified immunomodulatory genes. We transplanted these cells into the spinal cord of ALS large animal models (SOD1G93A pigs and TIA1P362L rabbits), which faithfully recapitulate pathologies and symptoms observed in ALS patients. The transplanted cells could efficiently differentiate into functional MNs upon Dox treatment in vivo, distribute throughout the spinal cord and motor cortex via extensive migration, survive long-term without the need for immunosuppression. Notably, these MNs integrated into host neural circuits, as evidenced by their long projection of peripheral axons to target muscle and reformation of neuromuscular junctions. As result, pathologies and motor deficits were substantially ameliorated in both animal models. One Sentence SummaryHypoimmunogenic human motor neurons induced from iPSCs in vivo reform neuromuscular junctions and ameliorate ALS disease in pig and rabbit models.

neuroscience↗

bioRxiv2024

Decoding the Dewlap: Multiple signals in females and males of a gliding lizard

Social interactions across taxa are often mediated through multiple signals. Studies examining the maintenance of multiple signals are mostly focused on males and often fail to capture female signalling diversity and strategies. In the recent decade, there has been a surge in the documentation of female signalling, however, our understanding of the functional relevance of multiple signals in females still lags behind. In this study, we examined multiple signals in females of an arboreal gliding lizard, Draco dussumieri, and compared them to those in males. We specifically tested the relative role of the backup signal and the multiple receiver hypotheses in the maintenance of multiple signals in both sexes. Female D.dussumieri used a variety of signals to socially interact with conspecifics, especially using their dewlap. The signalling repertoire of females was as diverse as that of males, although the relative use of the signals varied. In females, a few signals seem to be maintained by the backup signal hypothesis, with limited support for the multiple receiver hypothesis as well. For males too, both mechanisms appeared to maintain multiple signals. Interestingly, for some signals, the sexes differed in the context in which they used a given signal. Overall, these findings highlight the functional role of multiple signals in females, which can differ from that observed in males. Therefore, traits conventionally considered male-exclusive when also examined in females can provide finer insights into trait function and evolution.

animal behavior and cognition↗

bioRxiv2018

Human Nerve-on-a-Chip. Engineering 3D functional human peripheral nerve in vitro

Development of \"organ-on-a-chip\" systems in the space of the nervous system is lagging because of lack of availability of human neuronal & glial cells and the structural complexity of the nervous system. Furthermore, a sizeable challenge in the drug development pipeline and an often-cited reason for failure in a vast number of clinical trials conducted for neuropathological ailments is the lack of translation from animal models. A preclinical in vitro model capable of mimicking the function and structure of the human nervous system is well desired. We present an in vitro biomimetic model of all-human peripheral nerve tissue capable of showing a robust neurite outgrowth (~5mm), myelination of human induced pluripotent stem cells (iPSCs)-derived neurons by primary human Schwann cells and evaluation of nerve conduction velocity (NCV), previously unrealized for any human cell-based in vitro system. This Human Nerve-on-a-chip (HNoaC) system is the first microphysiological system of human peripheral nerve which can be used for evaluating electrophysiological and histological metrics, which are gold-standard assessment techniques previously only possible with in vivo studies.

bioengineering↗