Biology subjects

Ravi, D.

Publications and source records attributed to Ravi, D..

4 recordsLinked to original sources

bioRxiv2026

Deep learning-based identification and quantification of rare circulating hybrid cells in orthotopic pancreatic cancer models

SignificanceRare-cell identification in fluorescence microscopy remains challenging because targets are sparse and background varies between specimens. Combining specimen-specific fluorescence enrichment with image classification may enable efficient and more specific automated detection of rare cells. AimWe developed a two-stage framework to identify and quantify candidate rare circulating hybrid neoplastic cells (CHCs, ECAD+/CD45+) in peripheral blood mononuclear cell (PBMC) preparations from tumor-bearing and tumor-naive mice. ApproachPBMCs from 28 mice were imaged by multichannel fluorescence microscopy. Matched unstained samples established animal-specific ECAD and CD45 background distributions for candidate cell enrichment. Blinded multi-annotator consensus labels were used to train a convolutional neural network (CNN) from DAPI, ECAD, and CD45 image crops. Generalization was evaluated by leave-one-animal-out validation across 10 random initializations. Final classification used a 10-model ensemble, and rare-cell burden was compared between groups using negative-binomial regression with total segmented-cell count as an exposure. ResultsOf the 1,065,512 segmented cells, enrichment retained 10,176 candidates (0.96%), reducing the search space by >99%. Four of five evaluable tumor-bearing animals showed reproducible held-out discrimination, with median quantified area under the receiver operator characteristic curve (AUROCs) of 0.918-0.951; one animal was a reproducible outlier (median AUROC, 0.338). Ensemble deployment identified 157.94 positive-consensus cells per 50,000 segmented cells in tumor-bearing animals versus 49.55 in controls. The estimated rare-cell rate was 3.15-fold higher in tumor-bearing animals (95% CI, 0.91-10.99; two-sided p=0.071; prespecified one-sided p=0.036). ConclusionsSpecimen-specific fluorescence enrichment combined with supervised image classification reduced the cellular search space and enabled automated quantification of a rare CHC (ECAD+/CD45+) phenotypes. Cross-animal validation also identified specimen-specific generalization failure, highlighting the importance of biological-specimen-level validation.

cancer biology↗

bioRxiv2026

Cyclic immunofluorescence platform using photocleavable linkers for direct antibody labeling enables cancer phenotyping

Advances in spatial proteomics through the development of multiplexed immunostaining platforms have facilitated analyses with increasing cellular and molecular granularity. However, currently available approaches are limited by harsh conditions for signal removal, restricting the number of antigens that can be probed in a single specimen without significant alterations to sample quality and structure. Here we present an approach for direct labeling of primary antibodies with fluorophores using a photocleavable linker (PCL) with a polyethylene glycol spacer (PEG) to enable cyclic immunofluorescence (cyCIF) with gentle signal removal conditions. Our innovative approach uses directly labeled primary antibodies to enhance staining specificity and cyclic immunostaining efficiency, while minimizing nonspecific background signal. Additionally, through integration of the PCL, this approach facilitates gentle cleavage of antibody conjugated fluorophore, preserving sample integrity over multiple rounds of staining. Direct PEG-PCL antibody labeling will promote greater multiplexing by minimizing specimen damage and allow for quantitative analyses of cyCIF spatial data. We demonstrate that cyCIF with PEG-PCL conjugated antibodies can be applied across a variety of cancer subtypes to identify and characterize rare neoplastic cell populations in both tumor tissue and fragile peripheral blood specimens.

biochemistry↗

bioRxiv2026

Cell fusion reprograms tumor cells and promotes RUNX1-mediated invasion and dissemination in colorectal cancer

Metastasis remains the primary cause of cancer-related morbidity and mortality, despite significant advances in targeted therapies. Although metastatic dissemination requires tumor cells to escape the primary lesion and colonize distant organs, the mechanisms by which primary tumor cells gain metastatic competence remain poorly understood. Increasing evidence demonstrates that fusion of tumor (i.e., neoplastic) and immune (e.g., macrophages) cells generate a distinct population of tumor-immune hybrid cells with enhanced functional ability to migrate and disseminate into peripheral blood. Herein, our study investigates tumor-macrophage hybrid cells, an underexplored population of disseminated tumor cells, and their inherent heterogeneity and acquisition of molecular mechanisms underlying their dissemination as metastatic effectors in colorectal cancer (CRC). Through hybrid cell phenotyping utilizing integrative single-cell RNA sequencing (scRNA-seq), cyclic immunofluorescence (cyCIF) and functional assays with an in vitro model of CRC hybrid cells, we identify Runt-related transcription factor 1 (Runx1) as a central regulator of hybrid cell motility and invasion. Runx1 depletion in hybrid cells suppressed functional protease expression, chemotactic activity and extracellular matrix (ECM) invasion. Furthermore, pharmacologic inhibition of RUNX1 in an in vivo model reduced hybrid tumor growth and dissemination into peripheral blood, key attributes of metastatic spread of disease. In patients with CRC, RUNX1+ hybrid cells were identified in both primary tumor and peripheral blood, where circulating hybrid cells (CHCs) exhibited enriched migratory and epithelial-to-mesenchymal transition (EMT) phenotypes. Taken together, these findings reveal a mechanistic role for RUNX1 in driving invasive behavior of tumor-immune hybrids and highlight disseminated CHCs as an under-recognized contributor to metastatic spread and a promising noninvasive biomarker for tumor progression.

cancer biology↗

bioRxiv2025

Effects of Single-Session Perturbation-Based Balance Training with Progressive Intensities on Resilience and Dynamic Gait Stability in Healthy Older Adults

Single-session perturbation-based balance training (PBT) has demonstrated improvements in dynamic stability during the initial step following perturbation in older adults. However, its broader effects on comprehensive balance recovery remain inconclusive. This pilot randomized controlled trial investigated the impact of personalized single-session PBT on reactive balance control during walking, employing advanced stability analysis techniques. Ten participants in the training group underwent a single session consisting of 32 unpredictable treadmill-induced slips and trips of progressively increasing intensity, while ten participants in the control group engaged in unperturbed treadmill walking. Key outcome measures included margin of stability (MoS) parameters: minimum MoS and the number of recovery steps, and resilience parameters: peak instability and recovery time, assessed at baseline, immediately post-intervention, and three months post-intervention following an unexpected treadmill slip. The training group exhibited significant immediate and sustained improvements (p < 0.05) in minimum MoS values, alongside a notable reduction in peak instability (p < 0.05) immediately post-intervention. These changes were not observed in the control group. However, neither group demonstrated significant alterations in the number of recovery steps or recovery time across the assessment periods. In conclusion, single-session PBT enhanced reactive balance control by improving the magnitude of post-perturbation responses, but it did not significantly influence the speed of recovery to baseline conditions.

physiology↗