Biology subjects

Ramesh, P.

Publications and source records attributed to Ramesh, P..

8 recordsLinked to original sources

bioRxiv2026

Benchmarking Imputation Methods for Single-Cell RNA Sequencing Data Using Peripheral Blood Mononuclear Cells from Acute Myocardial Infarction Patients

Acute myocardial infarction (AMI) remains one of the leading causes of mortality worldwide, and the following post-effects, such as post-AMI inflammation and tissue repair, involve peripheral blood mononuclear cells playing a critical role. The influence of imputation methods in biological data is assessed with respect to high-resolution single-cell RNA sequencing (scRNAseq) data relevant to these cells. Still scRNAseq data often encounter a lot of dropout events, leading to sparse and noisy datasets, hampering downstream results. To assess the influence of the missingness in the data, we artificially impose different levels of dropout in available scRNAseq data by leveraging various imputation techniques. Specifically, we introduce artificial missingness at 10%, 20%, and 30% levels under a missing completely at random (MCAR) framework, repeated across 10 independent runs. We benchmarked six imputation strategies - MAGIC, IterativeImputer, KNNImputer, Mean Imputation, SoftImpute, and a Generative adversarial network (GAN) - based approaches using multiple evaluation metrics: marker gene preservation, clustering consistency (Adjusted Rand Index - ARI), gene-wise correlation with ground truth, and structural separation (silhouette scores). The results clearly underline that no single imputation method dominated across all metrics. Overall, Mean and KNN imputers showed limited recovery across all benchmarks. GAN excelled in global transcriptional recovery and SoftImpute in preserving biologically meaningful cell-type signals. Our results highlight the importance of selecting the imputation methods as part of the pre-processing step towards the downstream biological questions related to transcriptome recovery, detection of marker genes, or maintaining cell-type-specific resolution.

bioinformatics↗

bioRxiv2025

Memory by a thousand rules: Automated discovery of functional multi-type plasticity rules reveals variety and degeneracy at the heart of learning.

Synaptic plasticity is the basis of learning and memory, but the link between synaptic changes and neural function remains elusive. Here, we used automated search algorithms to obtain thousands of strikingly diverse quadruplets of excitatory(E)-to-E, E-to-inhibitory(I), IE, and II plasticity rules, cooperating to stabilize recurrent spiking networks. Despite the fact that quadruplets were selected for homeostasis, more than 90% of them performed well in simple and more difficult memory tasks such as novelty detection, contextual novelty and sequence replay. Co-activity was crucial, i.e., most rules failed in isolation. Our purely local, unsupervised plasticity rules could also help solve computer games such as pong. Our work showcases automated discovery augmenting human intuition to find en masse solutions for high dimensional problems.

neuroscience↗

bioRxiv2025

Avoidance of pyroptosis accounts for the relatively high metastatic potential observed in early hybrid EMT states

EMT converts epithelial (E) phenotypes to invasive mesenchymal (M) states. However, analyses of circulating tumor cells (CTCs) indicated that biphenotypic (E+M) CTCs better correlate with metastasis. Similarly, investigations of murine tumors undergoing EMT concluded that early E+M states posses the highest metastatic potential. To explore this, we selected in animals with breast cancer CTCs having progressively increasing intravasation abilities. This revealed that downregulation of arrestin Arrdc4 associates with CTC aggressiveness. In xenografts, depleting Arrdc4 accelerated tumor progression, whereas overexpression hindered progression in immunocompetent, but not in immunocompromised mice. Mechanistically, high Arrdc44 suppresses glucose uptake and enhances gasdermin E, triggering pyroptosis a type of pro-inflammatory cell death. Consistently, Arrdc4s lowest levels characterize the most metastatic biphenotypic states. In patients, both epigenetic and chromosomal aberrations downregulate ARRDC4 and predict poor prognosis. In summary, the uncovered mechanism portrays pyroptosis of biphenotypic EMT cells as a rheostat of CTCs, which may resolve the controversy on the role played by EMT in metastasis.

cancer biology↗

bioRxiv2023

Indistinguishable network dynamics can emerge from unalike plasticity rules

Synaptic plasticity is thought to be critical for building and maintaining brain circuits. Models of plasticity, or plasticity rules, are typically designed by hand, and evaluated based on their ability to elicit similar neuron or circuit properties to ground truth. While this approach has provided crucial insights into plasticity mechanisms, it is limited in its scope by human intuition and cannot identify all plasticity mechanisms that are consistent with the empirical data of interest. In other words, focusing on individual hand-crafted rules ignores the potential degeneracy of plasticity mechanisms that explain the same empirical data, and may thus lead to inaccurate experimental predictions. Here, we use an unsupervised, adversarial approach to infer plasticity rules directly from neural activity recordings. We show that even in a simple, idealised network model, many mechanistically different plasticity rules are equally compatible with empirical data. Our results suggest the need for a shift in the study of plasticity rules, considering as many degenerate plasticity mechanisms consistent with data as possible, before formulating experimental predictions.

neuroscience↗

bioRxiv2022

Identification of Banana heat responsive long non-coding RNAs and their gene expression analysis.

Identification and characterization of long non-coding RNAs (lncRNAs) in the last decade has attained great attention because of their importance in gene regulatory functions in response to various plant stresses. Rising temperature is a potential threat to the agriculture world. Banana being an important economic crop, identification and characterization of genes and RNAs that regulate high temperature stress is imperative. As the prediction of lncRNAs in response to heat stress in banana is largely unknown, the present study was focused to identify the heat stress responsive lncRNA in banana (DH Pahang). Perl script was written to identify the novel transcripts, using the work flow. StringTie and CPC softwares were used and a total of 363 novel HS-lncRNA were identified in banana. Further, lncRNA were classified as 288 lincRNAs, 71 antisense LncRNA, 5 sense lncRNAs. The functional classification was done and transcripts were broadly classified into molecular function, cellular components and biological processes. Differential expression of lncRNA showed the varied patterns at different stages of heat stress. Finally, qPCR results confirmed DGE expression pattern of lncRNAs. Further, the Cytoscape analysis was performed which showed protein coding genes involved in membrane integrity and other signal transduction pathways. Taken together, these findings expand our understanding of lncRNAs as ubiquitous regulators under heat stress conditions in banana.

molecular biology↗

bioRxiv2021

MPA_Pathway_Tool: User-friendly, automatic assignment of microbial community data on metabolic pathways

MotivationTaxonomic and functional characterization of microbial communities from diverse environments such as the human gut or biogas plants by multi-omics methods plays an ever more important role. Researchers assign all identified genes, transcripts, or proteins to biological pathways to better understand the function of single species and microbial communities. However, due to the versatility of microbial metabolism and a still increasing number of new biological pathways, linkage to standard pathway maps such as the KEGG (Kyoto Encyclopedia of Genes and Genomes) central carbon metabolism is often problematic. ResultsWe successfully implemented and validated a new user-friendly, stand-alone web application, the MPA_Pathway_Tool. It consists of two parts, called Pathway-Creator and Pathway-Calculator. The Pathway-Creator enables an easy setup of user-defined pathways with specific taxonomic constraints. The Pathway-Calculator automatically maps microbial community data from multiple measurements on selected pathways and visualizes the results. Availability and ImplementationThe MPA_Pathway_Tool is implemented in Java and ReactJS. It is freely available on http://mpa-pathwaymapper.ovgu.de/. Further documentation and the complete source code are available on GitHub (https://github.com/danielwalke/MPA_Pathway_Tool). Contactdaniel.walke@ovgu.de, mailto:heyer@mpi-magdeburg.mpg.de heyer@mpi-magdeburg.mpg.de Supplementary InformationAdditional files and images are available at MDPI online. Highlightsuser-friendly generation of pathways, re-using of existent metabolic pathways, automated mapping of data

bioinformatics↗

bioRxiv2021

Relish plays a dynamic role in the niche to modulate Drosophila bloodprogenitor homeostasis in development and infection.

Immune challenges demand the gearing up of basal hematopoiesis to combat infection. Little is known about how during development, this switch is achieved to take care of the insult. Here, we show that the hematopoietic niche of the larval lymph gland of Drosophila senses immune challenge and reacts to it quickly through the nuclear factor-{kappa}B (NF-{kappa}B), Relish, a component of the immune deficiency (Imd) pathway. During development, Relish is triggered by ecdysone signaling in the hematopoietic niche to maintain the blood progenitors. Loss of Relish causes an alteration in the cytoskeletal architecture of the niche cells in a Jun Kinase dependent manner, resulting in the trapping of Hh implicated in progenitor maintenance. Notably, during infection, downregulation of Relish in the niche tilts the maintenance program towards precocious differentiation, thereby bolstering the cellular arm of the immune response.

developmental biology↗

bioRxiv2021

Development of a Triazolobenzodiazepine-Based PET Probe for Subtype-Selective Vasopressin 1A Receptor Imaging

ObjectivesTo enable non-invasive real-time quantification of vasopressin 1A (V1A) receptors in peripheral organs, we sought to develop a suitable PET probe that would allow specific and selective V1A receptor imaging in vitro and in vivo. MethodsWe synthesized a high-affinity and -selectivity ligand, designated compound 17. The target structure was labeled with carbon-11 and tested for its utility as a V1A-targeted PET tracer by cell uptake studies, autoradiography, in vivo PET imaging and ex vivo biodistribution experiments. ResultsCompound 17 (PF-184563) and the respective precursor for radiolabeling were synthesized in an overall yield of 49% (over 7 steps) and 40% (over 8 steps), respectively. An inhibitory constant of 0.9 nM towards the V1A receptor was measured, while excellent selectivity over the related V1B, V2 and OT receptor (IC50 >10,000 nM) were obtained. Cell uptake studies revealed considerable V1A binding, which was significantly reduced in the presence of V1A antagonists. Conversely, there was no significant blockade in the presence of V1B and V2 antagonists. In vitro autoradiography and PET imaging studies in rodents indicated specific tracer binding mainly in the liver. Further, the pancreas, spleen and the heart exhibited specific binding of [11C]17 ([11C]PF-184563) by ex vivo biodistribution experiments. ConclusionWe have developed the first V1A-targeted PET ligand that is suitable for subtype-selective receptor imaging in peripheral organs including the liver, heart, pancreas and spleen. Our findings suggest that [11C]PF-184563 can be a valuable tool to study the role of V1A receptors in liver diseases, as well as in cardiovascular pathologies.

pharmacology and toxicology↗