Biology subjects

Lalu, M. M.

Publications and source records attributed to Lalu, M. M..

3 recordsLinked to original sources

bioRxiv2026

Early sex-specific organ transcriptional divergence without physiological differences in a murine model of fecal-induced peritonitis

Sepsis is defined as a dysregulated response to infection, leading to life-threatening organ dysfunction that particularly affects parenchymal organs. Clinical studies remain inconclusive regarding the impact of biological sex on sepsis, and preclinical studies are predominantly performed in male animals. We examined early (8 h) septic responses in male and female mice using a fecal-induced peritonitis (FIP) model. Blood biochemical parameters, body temperature, and murine sepsis scores provided evidence of a septic response in animals randomized to FIP compared to controls, but showed no physiological differences between male and female mice. Transcriptomic analysis of the liver, kidney, and lung showed consistent inflammatory activation in response to sepsis as compared to controls. Notably, in the kidney and lung, female mice exhibited stronger immune activation and a heightened inflammatory response compared to males. Thus, biological sex differences in the septic response can be detected in early acute sepsis without apparent physiological differences.

pathology↗

bioRxiv2025

Artificial Intelligence-enabled Histological Analysis in Preclinical Respiratory Disease Models: A Scoping Review

Histological analysis is a cornerstone of preclinical respiratory disease research, enabling assessment of pathology, therapeutic effects, and mechanisms. However, conventional approaches rely on manual scoring, which is subjective, time-consuming, and difficult to scale due to low throughput and inter-observer variability. Artificial intelligence (AI), particularly deep learning, offers potential to automate histology workflows, but its use and evaluation in preclinical respiratory models have not been synthesized. We conducted a scoping review following Joanna Briggs Institute guidelines, searching MEDLINE and Embase (inception-January 2025) for preclinical studies using AI to analyze histology in respiratory disease models. Screening, full-text review, and data extraction were performed in duplicate. Of 6271 studies screened, 29 met inclusion criteria. Most used murine models (76%) and investigated lung cancer (28%), pulmonary fibrosis (24%), or tuberculosis (17%). Hematoxylin and eosin was the most common stain (48%), with others targeting collagen or immune markers. AI tasks included image classification (n=20), segmentation (n=10), and object detection (n=4), predominantly using convolutional neural networks (69%). Preprocessing methods (e.g., stain normalization) were common, but annotation and training practices were inconsistently reported. Performance was generally high (accuracy [≥]90%; 7 studies) though validation metrics varied, and external validation was absent. Most studies used "black box" models, with minimal application of explainability techniques. Reproducibility measures, such as sharing datasets or code were rarely reported. AI tools are poised to transform histological analysis in preclinical respiratory research. By addressing gaps in validation, transparency, and standardization, the field can harness these technologies to deliver robust, efficient, and scalable workflows. Registration: Open Science Framework https://doi.org/10.17605/OSF.IO/NM94E

cell biology↗

bioRxiv2024

CCR5 antagonists as neuroprotective and stroke recovery enhancing agents: a preclinical systematic review and meta-analysis

C-C chemokine receptor type 5 (CCR5) antagonists may improve both acute stroke outcome and long-term recovery. Despite their evaluation in ongoing clinical trials, gaps remain in the evidence supporting their use. With a panel of patients with lived experiences of stroke, we performed a systematic review of animal models of stroke that administered a CCR5 antagonist and assessed infarct size or behavioural outcomes. MEDLINE, Web of Science, and Embase were searched. Article screening and data extraction were completed in duplicate. We pooled outcomes using random effects meta-analyses. We assessed risk of bias using the Systematic Review Centre for Laboratory Animal Experimentation (SYRCLE) tool and alignment with the Stroke Treatment Academic Industry Roundtable (STAIR) and Stroke Recovery and Rehabilitation Roundtable (SRRR) recommendations. Five studies representing 10 experiments were included. CCR5 antagonists reduced infarct volume (standard mean difference -1.02; 95% confidence interval -1.58 to -0.46) when compared to stroke-only controls. Varied timing of CCR5 administration (pre- or post-stroke induction) produced similar benefit. CCR5 antagonists significantly improved 11 of 16 behavioural outcomes reported. High risk of bias was present in all studies and critical knowledge gaps in the preclinical evidence were identified using STAIR/SRRR. CCR5 antagonists demonstrate promise; however, rigorously designed preclinical studies that better align with STAIR/SRRR recommendations and downstream clinical trials are warranted. Prospective Register of Systematic Reviews (PROSPERO CRD42023393438).

neuroscience↗