Biology subjects

Ghimire, A.

Publications and source records attributed to Ghimire, A..

8 recordsLinked to original sources

bioRxiv2026

SpikeCleaner: An Algorithm to Label Unit Quality After Automated Spike Sorting

GapAutomated spike sorting algorithms have revolutionized the way neuronal activity is extracted from extracellular recordings, yet they remain imperfect. Specifically, inaccurate acceptance of noise-based units not only leaves researchers with clusters that require extensive manual curation, an essential but time-consuming process, that also leads to significant subjectivity in the selection of units. In an era of high-density probes like Neuropixels, where an hour of data can exceed 80 GB, manual curation is no longer scalable, automation of standard criteria can speed data curation and ensure quality of datasets. Here, we developed a semi-automated curation pipeline to label the quality of units after automated curation by Kilosort. ApproachOur algorithm standardizes criteria for labeling of Noise, Multi-Unit Activity (MUA), and Good Units using a combination of spike rate, spike timing metrics (from autocorrelogram), and waveform-based physiological features such as peak amplitude, slopes, half-width, and inter-channel correlation. Based on these features, clusters are assigned standardized labels (good, noise, multi-unit activity) that can be imported directly into Phy, where they serve as curation aids rather than absolute classifications, supporting but not replacing expert judgment. Heuristically, "noise" units are those unlikely to be neuronal in origin; "MUA" includes units with significant neural contribution (i.e., neuronal waveform) but with some degree of clear imperfection to be further cleaned, and "good" units are those without any clear deviation from ideal unit criteria. By ensuring accurate selection of acceptable units, we enable robust downstream analyses such as neural decoding and longitudinal tracking of neuron identity. Thresholds for all metrics were chosen to maximize the matching of algorithm output to that of 2 expert manual curators. Of note, users may alter thresholds either based on their own judgment or using an included tool to semi-automatically find thresholds that optimize SpikeCleaner with their own expert curation. ResultsTo benchmark, we compared the outputs of our algorithm to expert-labels curated in Phy by two expert users across three recordings. SpikeCleaner achieved an average of 97% accuracy vs. experts & 92% F1 score in classifying Single Units. It achieved an accuracy of 97% & 92% F1 score in full-category agreement (SU, MUA, Noise), and 97% accuracy & 95% F1 score in distinguishing Neuronal vs. Non-Neuronal units.

neuroscience↗

bioRxiv2026

Distinct melanoma EV subpopulations reflect immune- and stress-induced tumor states

Melanoma is the deadliest form of skin cancer, and improved non-invasive approaches to monitor tumor burden and immune dynamics are needed. Although extracellular vesicles (EVs) are increasingly explored as cancer biomarkers, how distinct EV subpopulations reflect dynamic tumor states induced by immune pressure remains insufficiently understood. Using proteomic analyses, we identified the melanoma-associated antigens gp100 (PMEL) and GPNMB in EVs derived from B16F10 melanoma cells and incorporated them into sandwich enzyme-linked immunosorbent assays (ELISAs) that capture total EVs while selectively detecting gp100 and GPNMB EV subpopulations. We subsequently evaluated these EV populations in murine models of anti-tumor vaccination and in plasma samples from melanoma patients. In vivo, melanoma-associated EV subpopulations increased in the serum of tumor-bearing mice and were further augmented following antigen-specific anti-tumor vaccination, whereas total CD81 EVs accumulated more gradually. Notably, gp100 EV levels, but not GPNMB EVs, correlated with tumor-infiltrating lymphocyte densities across multiple time points and treatment conditions. In vitro, TNF/IFN{gamma} stimulation preferentially increased total CD81 EV release, whereas gp100 EVs were promoted by IL-1{beta} stimulation. In contrast, GPNMB EVs accumulated more gradually and broadly across inflammatory, hypoxic, and cytotoxic stress conditions. Together, these findings indicate that immune and stress signals differentially remodel melanoma-associated EV composition. The assay translated to humans, revealing elevated gp100 EV levels in the plasma of melanoma patients compared with healthy donors, whereas GPNMB EVs identified a subset of melanoma patients. We describe a clinically feasible approach that enables direct detection of melanoma-associated EV subpopulations from blood without prior EV isolation. Conceptually, our findings suggest that immune and stress signals dynamically shape circulating EV composition, generating distinct EV signatures that reflect tumor state.

immunology↗

bioRxiv2025

Neurotype matching in monogamous rodents is modulated by early-life sleep experience

Studies of human sociability indicate stronger social affinity in matched-neurotype dyads (e.g., two individuals with autism or two without) compared to mixed-neurotype dyads (e.g., one individual with autism paired with one without). Is this neurotype matching phenomenon also quantifiable in non-human animals? Using deep learning tools, we analyzed dyadic male-female interactions in prairie voles, a highly social rodent species. To simulate "neurotypes", voles were exposed to either control conditions or early-life sleep disruption (ELSD) during a critical neurodevelopmental period (postnatal days 14-21), recapitulating two features of human autism: developmental sleep disruption and later-life atypical sociability. Analogous to human studies, voles showed signs of reduced social affinity in mixed dyads compared to matched dyads, including sex-specific changes in aggression and body orientation toward the conspecific. These findings advance our understanding of social affinity, providing a framework for new studies in both animal models and humans.

animal behavior and cognition↗

bioRxiv2025

Developmental time course of social touch, parvalbumin interneurons, perineuronal nets and Mef2c expression reveals a sensitive period of somatosensory cortex development in prairie voles

Social touch facilitates our attachment to others, especially early in life, which may be linked to the maturation of parvalbumin interneurons (PVI) in the somatosensory cortex (S1). These neurons respond to social touch, mature in a sensory experience-dependent manner, and influence both somatosensory processing and social behavior in models of Autism Spectrum Disorder. Prairie voles (Microtus ochrogaster) are an ideal rodent model for studying these concepts since they engage in a species-typical social touch called "huddling". This study first showed that over development from juvenile to adult, same-sex siblings huddled less and explored more. Next, we tracked two markers of plasticity indicative of PVI maturation, extracellular perineuronal nets (PNNs) and nuclear transcription factor Myocyte enhancing factor 2C (Mef2c) - across seven developmental timepoints. We found that, while PV expression in S1 was stable by P21, PNNs and Mef2c continued to shift afterwards, indicating a protracted development. Four unique clusters of PVIs converge during development between P14-P21, suggesting a sensitive period of PVI development. Finally, to determine environmental factors affecting these processes, environmental enrichment between P21-P28 led to accelerated PVI maturation. This developmental mapping provides a particularly salient model to investigate the molecular underpinnings of cortical and social development.

neuroscience↗

bioRxiv2025

Mouse Bio-behavioral Phenotyping Using a Digital Homecage Framework for Long-timescale, High-resolution, and Multi-factor Data Collection and Analytics

MOTIVATION Long-term monitoring of behavioral and physiological processes is critical for understanding complex brain-based phenomena and disorders that develop over extended periods, such as chronic stress, circadian disorders, and metabolic conditions. While digital phenotyping is available in humans using smart devices, there remains a deficit in rodent models. To address this lack of long-term rodent phenotyping, we introduce the "Digital Homecage" (DHC) system. Our system uses accessible components and is designed for seamless integration with brain recording technologies. The Digital Homecage (DHC) allows uninterrupted, long-timescale recording of more than 20 behavioral metrics in single-housed mice, captured at sub-second resolution via video, operant interactions, and wheel-running data. This report demonstrates the DHCs capacity to enable continuous, automated tracking of behaviors like actigraphy, sleep, grooming, and food choice options over weeks, thereby opening up new avenues for longitudinal analyses of chronic conditions. Data collected reveal circadian patterns in multiple spontaneous behaviors, aligning with known nocturnal tendencies. The systems potential to facilitate groundbreaking observations on the long-term behavioral correlates of various neuropsychiatric syndromes is aided by open-source software and relatively low cost. The DHC sets the stage for community-driven innovation, potentially transforming our approach to studying complex traits of brain function and behavior in laboratory settings.

animal behavior and cognition↗

bioRxiv2023

Swi4-dependent SWI4 transcription couples cell size to cell cycle commitment

Growth-dependent accumulation of the limiting SBF transcription factor, composed of Swi4 and Swi6, occurs in G1 phase in budding yeast and is limiting for commitment to division, termed Start. Here we measure size-dependence of Swi4 protein copy number under different genetic contexts using the scanning number and brightness technique. Mutation of SBF binding sites in the SWI4 promoter or disruption of SBF activation resulted in [~]33-50% decrease in Swi4 accumulation rate and concordantly increased cell size at Start. Ectopic inducible expression of Swi4 in G1 phase cells increased production of Swi4 from the endogenous promoter, upregulated transcription of the G1/S regulon, and accelerated Start. Despite the potential for Swi4 positive feedback, G1 phase Swi4 accumulation was linear unless the Whi5 transcriptional repressor was inactivated. A threshold model in which Swi4 titrates SBF binding sites in G1/S promoters predicted the effects of nutrients, ploidy, and G1/S regulatory mutations on cell size. These results exemplify how transcription factor auto-production can contribute to a cell state transition.

cell biology↗

bioRxiv2022

Sleep alterations in a mouse model of Spinocerebellar ataxia type 3

BackgroundSpinocerebellar ataxia type 3 (SCA3) is a neurodegenerative disorder showing progressive neuronal loss in several brain areas and a broad spectrum of motor and non-motor symptoms, including ataxia and altered sleep. While sleep disturbances are known to play pathophysiologic roles in other neurodegenerative disorders, their impact on SCA3 is unknown. ObjectivesUsing state-of-the art spectrographic measurements, we sought to quantitatively characterize sleep electroencephalography (EEG) in a SCA3 transgenic mouse model with confirmed disease phenotype. MethodsWe first measured motor phenotypes in 18-31-week-old homozygous and hemizygous SCA3 YACMJD84.2 mice and non-transgenic wild-type littermate mice during lights-on and lights-off periods. We next implanted electrodes to obtain 12-hour (zeitgeber time 0-12) EEG recordings for three consecutive days when the mice were 26-36 weeks old. We then analyzed EEG-based sleep structure data to quantify differences between homozygous, hemizygous, and wild-type mice. ResultsCompared to wild-type littermates, SCA3 homozygous mice display: i) increased duration of rapid-eye movement sleep (REM) and fragmentation in all sleep and wake states; ii) higher beta power oscillations during REM and non-REM (NREM); and iii) additional spectral power band alterations during REM and wake. ConclusionsOur data show that sleep architecture and EEG spectral power are dysregulated in homozygous SCA3 mice, indicating that common sleep-related etiologic factors may underlie mouse and human SCA3 phenotypes.

neuroscience↗

bioRxiv2022

LabGym: A versatile computational tool for automatic quantification of user-defined animal behaviors

Quantifying animal behavior is important for many branches of biological research. Current computational tools for behavioral quantification typically rely on a few pre-defined, simplified features to identify a behavior. However, such an approach restricts the information used and the tools applicability to a limited range of behavior types or species. Here we report a new tool, LabGym, for quantifying animal behaviors without such limitations. Combining a novel approach for effective evaluation of animal motion with customizable convolutional recurrent networks for capturing spatiotemporal details, LabGym provides holistic behavioral assessment and accurately identify user-defined animal behaviors without restrictions on behavior types or animal species. It then provides quantitative measurements of each behavior, which quantify the behavior intensity and the body kinematics during the behavior. LabGym requires neither any intermediate step for processing features that causes information loss nor programming knowledge from users for post-hoc analysis. It tracks multiple animals simultaneously in various experimental settings for high-throughput and versatile analysis. It also provides users a way to generate visualizable behavioral datasets that are valuable resources for the research community. We demonstrate its efficacy in capturing subtle behavioral changes in animals ranging from soft-bodied invertebrates to mammals.

animal behavior and cognition↗