Biology subjects

Krishnamurthy, R.

Publications and source records attributed to Krishnamurthy, R..

7 recordsLinked to original sources

bioRxiv2026

Deformability screening identifies NUDT5 as a mediator of cellular mechanobiology

How cells deform, sense, and respond to mechanical cues drives physiological and disease processes ranging from development to cancer metastasis; however, unbiased approaches to identify mechanical mediators are lacking. We screened 1280 compounds to identify modulators of cancer cell deformability using a cellular filtration assay and identified 92 compounds that significantly reduced deformability of ovarian cancer cells; top hits also reduced migration and invasion. Connectivity mapping of the top 21 compounds identified NUDT5 (Nudix hydrolase 5) as a predicted mechanical mediator; transcriptomic analyses implicated NUDT5 in mechanobiology and metabolic processes. We confirmed that NUDT5 mediates intracellular ATP and cellular mechanical behaviors, including morphology and deformability. In ovarian cancer, increased NUDT5 levels were associated with higher tumor stage and worse patient survival; NUDT5 inhibition reduced migration and colony formation in vitro and peritoneal tumor burden in mice. These findings establish deformability-based screening as a platform for discovering mechanical mediators and identify NUDT5 as a therapeutic target in ovarian cancer. TeaserScreening cells based on deformability provides an unbiased approach to identify NUDT5 as a mediator of cell mechanics

cell biology↗

bioRxiv2026

Brain Structural and Resting-state Functional Network Changes Following Expiratory Musculature Targeted Resistance Training in Healthy Young Adults: A Pilot Study

Multimodal imaging approaches that combine structural and functional neuroimaging provide a robust framework for examining neuroplastic adaptations that may not be captured by any single modality. The present study investigated the effects of a four-week expiratory muscle strength training (EMST) program on structural and resting-state functional connectivity in healthy young adults. Five healthy young adult males (aged 19-35 years) completed a standard four-week EMST protocol and underwent pre- and post-training imaging assessments. Structural neuroimaging included T1-weighted and diffusion-weighted MRI, which were analyzed using voxel-based morphometry, surface-based morphometry, and white-matter structural connectivity. Functional neuroimaging consisted of resting-state fMRI to assess training-related changes in functional architecture, network connectivity, and global network measures. Structural MRI analyses revealed no significant changes in gray or white matter volume, cortical morphology, or white-matter structural connectivity following EMST (all FWE- or FDR-corrected p > .05). In contrast, resting-state fMRI demonstrated a significant increase in whole-brain functional connectivity (FDR-corrected p = .036), accompanied by greater network integration, reflected in increased local efficiency and transitivity and reduced modularity. Network-level analyses showed enhanced within- and between-network connectivity in sensorimotor and cognitive circuits. Our findings demonstrate robust functional reorganization following EMST, despite the absence of detectable macrostructural or large-scale white-matter connectivity changes, at least within the timescale and sample characteristics of the current study. These results reflect early-stage neuroplasticity, both globally and within the networks underlying speech and swallowing control and suggest that functional reorganization occurs early in training and likely precedes longer-term structural modifications in these networks.

neuroscience↗

bioRxiv2025

Of Shared Homes and Pathways: Free-Ranging Dog Movement and Habitat Use in a Human-Wildlife Landscape in India

BackgroundFree-ranging dogs are widely considered to have negative impacts on wildlife in shared landscapes. Understanding their use of these landscapes is therefore essential to develop effective management strategies in wildlife-adjacent regions. In this study, we investigated the movement patterns of free-ranging dogs in the protected area matrix of Mudumalai Tiger Reserve (MTR) in Southern India. MethodsFifteen owned free-ranging dogs (FRD) were collared from two adjacent villages with different levels of human habitation. We hypothesized that increased settlement cover would provide dogs with a greater human shield effect, allowing them more freedom of movement. We estimated dog activity ranges and movement patterns using autocorrelated kernel density estimates (AKDE). Large-scale movement was characterized through multiple metrics (intensity of space use and mean distance from home) and compared across villages to understand underlying drivers. Lastly, we quantified fine-scale movement and habitat selection using integrated step selection analysis (iSSA). ResultsWe found that FRD in MTR had directionally dependent home-ranging behavior and small activity ranges, with the mean AKDE activity range being 9.88 {+/-} 7.69 ha (median = 6.09 ha, range 3.28-26.16 ha), and primarily utilized the area within 500 m of their homes. None of the movement metrics varied significantly between villages, except for intensity of use, which was higher in one village than the other, suggesting that dogs in the less populated village perceived a greater threat from surrounding wildlife and were more driven to seek refuge inside their activity ranges. iSSA revealed that dogs selected strongly for human settled or human- modified habitats, and moved significantly faster in forest land than any other habitat. ConclusionsOur findings indicate that owned FRD pose a relatively lower threat to wildlife in MTR than feral dogs may. They also support the human shield hypothesis, show that FRD display behavioral plasticity at fine scales of <5km, and highlight the role of human land use intensity in shaping the movement of domestic dogs. As humans can thus mediate potential effects of dogs on wildlife, anthropogenic factors should be taken in consideration when designing management strategies that aim to curb dog movement.

ecology↗

bioRxiv2022

Parallel Mechanosensory Systems are Required for Negative Gravitaxis in C. elegans

The ability to sense Earths gravitational pull is essential for orientation, navigation, and proprioception in many organisms. We report here that C. elegans exhibits pronounced negative gravitaxis, or movement away from the Earths center, independent of orientation of the geomagnetic field. This behavior is antagonized by light and electromagnetic fields, suggesting that it is integrated with other sensory inputs. We found that MEC-5/7/12, and TRPA-1, but not MEC-4/10 DEG/ENaC channels or other proteins involved in gentle touch transduction, are essential for negative gravitaxis, suggesting that the sensory system for detecting and responding to gravity is separable from touch sensation. We also found that the PVD neurons but not touch receptor neurons (TRNs) are required for this behavior. These findings implicate an interconnected mechanism for gravity sensation involving an ion channel that is also present in the mammalian vestibular system, suggesting possible homology in gravity sensing across animal phylogeny.

neuroscience↗

bioRxiv2022

Memory Consolidation with Orthogonal Gradients for avoiding Catastrophic Forgetting

The memory consolidation process enables the accumulation of recent and remote memories in the long-term memory store. In general, the deep network models of memory suffer from forgetting old information while learning new information, called catastrophic forgetting/interference. The human brain overcomes this problem quite effectively, a problem that continues to challenge current deep neural network models. We propose a regularization-based model to solve the problem of catastrophic forgetting. According to the proposed training mechanism, the network parameters are constrained to vary in a direction orthogonal to the average of the error gradients corresponding to the previous tasks. We also ensure that the constraint used in parameter updating satisfies the locality principle. The proposed models performance is compared with Elastic Weight Consolidation on standard datasets such as permuted MNIST and split MNIST on classification tasks using fully connected networks, and Convolution-based networks. The model performance is also compared to an autoencoder on split MNIST dataset, and to complex core50 dataset on two types of classification tasks with EWC. The proposed model gives a new view on plasticity at the neuronal level. In the proposed model, the parameter updating is controlled by the neuronal level plasticity rather than synapse level plasticity as in other standard models. The biological plausibility of the proposed model is discussed by linking the extra parameters to synaptic tagging, which represents the state of the synapse involved in Long Term Potentiation (LTP).

neuroscience↗

bioRxiv2020

Depsipeptide nucleic acids: prebiotic formation, oligomerization, and self-assembly of a new candidate proto-nucleic acid

The mechanism by which genetic polymers spontaneously formed on the early Earth is currently unknown. The RNA World hypothesis implies that RNA oligomers were produced prebiotically, but the demonstration of this process has proven challenging. Alternatively, RNA may be the product of evolution and some, or all, of its chemical components may have been preceded by functionally analogous moieties that were more readily accessible under plausible early-Earth conditions. We report a new class of nucleic acid analog, depsipeptide nucleic acid, which displays several properties that make it an attractive candidate for the first informational polymer to arise on the Earth. The monomers of depsipeptide nucleic acids can form under plausibly prebiotic conditions. These monomers oligomerize spontaneously when dried from aqueous solutions to form nucleobase-functionalized depsipeptides. Once formed, these depsipeptide nucleic acid oligomers are capable of complementary self-assembly, and are resistant to hydrolysis in the assembled state. These results suggest that the initial formation of primitive, self-assembling, informational polymers may have been relatively facile.

biochemistry↗

bioRxiv2020

deepMINE - Natural Language Processing based Automatic Literature Mining and Research Summarization for Early Stage Comprehension in Pandemic Situations specifically for COVID-19

The recent pandemic created due to Novel Coronavirus (nCOV-2019) from Wuhan, China demanding a large scale of a general health emergency. This demands novel research on the vaccine to fight against this pandemic situation, re-purposing of the existing drugs, phylogenetic analysis to identify the origin and determine the similarity with other known viruses, etc. The very preliminary task from the research community is to analyze the wide verities of existing related research articles, which is very much time-consuming in such situations where each minute counts for saving hundreds of human lives. The entire manual processing is even lower down the efficiency in mining the information. We have developed a complete automatic literature mining system that delivers efficient and fast mining from existing biomedical literature databases. With the help of modern-day deep learning algorithms, our system also delivers a summarization of important research articles that provides ease and fast comprehension of critical research articles. The system is currently scanning nearly 1,46,115,136 English words from 29,315 research articles in not greater than 1.5 seconds with multiple search keywords. Our research article presents the criticality of literature mining, especially in pandemic situations with the implementation and online deployment of the system.

bioinformatics↗