Biology subjects

Joshi, N. R.

Publications and source records attributed to Joshi, N. R..

5 recordsLinked to original sources

bioRxiv2024

Combining supervised and unsupervised analyses to quantify behavioral phenotypes and validate therapeutic efficacy in a triple transgenic mouse model of Alzheimer's disease

Behavioral testing is an essential tool for evaluating cognitive function and dysfunction in preclinical research models. This is of special importance in the study of neurological disorders such as Alzheimers disease. However, the reproducibility of classic behavioral assays is frequently compromised by interstudy variation, leading to ambiguous conclusions about the behavioral markers characterizing the disease. Here, we identify age- and genotype-driven differences between 3xTg-AD and non-transgenic control mice using a low-cost, highly customizable behavioral assay that requires little human intervention. Through behavioral phenotyping combining both supervised and unsupervised behavioral classification methods, we are able to validate the preventative effects of the immunosuppressant cyclosporine A in a rodent model of Alzheimers disease, as well as the partially ameliorating effects of candidate drugs nebivolol and cabozantinib. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=158 SRC="FIGDIR/small/597924v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@1c61729org.highwire.dtl.DTLVardef@1abd0corg.highwire.dtl.DTLVardef@1719439org.highwire.dtl.DTLVardef@1ba4491_HPS_FORMAT_FIGEXP M_FIG C_FIG

animal behavior and cognition↗

bioRxiv2023

An 8-cage imaging system for automated analyses of mouse behavior

The analysis of mouse behavior is used in biomedical research to study brain function in health and disease. Well-established rapid assays allow for high-throughput analyses of behavior but have several drawbacks, including measurements of daytime behaviors in a nocturnal animal, effects of animal handling, and the lack of an acclimation period in the testing apparatus. We developed a novel 8-cage imaging system, with animated visual stimuli, for automated analyses of mouse behavior in 22-hour overnight recordings. Software for image analysis was developed in two open-source programs, ImageJ and DeepLabCut. The imaging system was used to measure multiple behaviors, including acclimation to the novel cage environment, day and nighttime activity, stretch-attend postures, location in various cage areas, and habituation to animated visual stimuli. These behaviors were summarized in behavioral profiles, which may be used in further studies to examine treatments for neural disorders.

animal behavior and cognition↗

bioRxiv2022

Enteroendocrine cell lineages that differentially control feeding and gut motility

Enteroendocrine cells are specialized sensory cells of the gut-brain axis that are sparsely distributed along the intestinal epithelium. The functions of enteroendocrine cells have classically been inferred by the gut hormones they release. However, individual enteroendocrine cells typically produce multiple, sometimes apparently opposing, gut hormones in combination, and some gut hormones are also produced elsewhere in the body. Here, we developed approaches involving intersectional genetics to enable selective access to enteroendocrine cells in vivo. We constructed Villin1-p2a-FlpO knock-in mice to restrict reporter expression to intestinal epithelium and through combined use of Cre and Flp alleles, effectively targeted major transcriptome-defined enteroendocrine cell lineages that produce serotonin, glucagon-like peptide 1, cholecystokinin, somatostatin, or glucose insulinotropic peptide. Chemogenetic activation of different enteroendocrine cell types variably impacted feeding behavior, nausea-associated behaviors (conditioned flavor avoidance), and gut motility. Defining the physiological roles of different enteroendocrine cell types provides an essential framework for understanding sensory biology of the intestine.

neuroscience↗

bioRxiv2022

Endometriotic Organoids as an In Vitro Model of Endometriotic Lesion Development.

The development and progression of endometriotic lesions are poorly understood, but immune cell dysfunction and inflammation are closely associated with the pathophysiology of endometriosis. A lack of suitable 3D in vitro models permitting the study of interactions between cell types and the microenvironment is a contributing factor. To address this limitation, we developed endometriotic organoids (EO) to explore the role of epithelial-stromal interactions and model peritoneal cell invasion associated with lesion development. Using a non-adherent microwell culture system, spherical organoids were generated with endometriotic epithelial cells (12Z) combined with immortalized endometriotic stromal cells (iEc-ESC) or immortalized uterine stromal cells (iHUF). Organoids self-organized with stromal cells occupying the center and epithelial cells on the periphery of the organoid. Endometriotic organoids (EO), containing iEc-ESC, resulted in the development of stratified 12Z epithelial cells compared to those with iHUF where the 12Z cells developed as a single layered epithelium. Transcriptomic analysis found 4,522 differentially expressed genes (DEG) between EO and 12Z/iHUF organoids, and the top DEG included increased expression of interleukins and prostaglandin synthase enzymes. An overlap of the EO DEG with baboon endometriotic lesions was highly significant. Finally, to mimic invasion of endometrial tissue into the peritoneum, a model was developed using EO and extracellular matrix containing human peritoneal mesothelial cells (LP9). Invasion of EO into the extracellular matrix-LP9 layer was increased in presence of estrogen or THP1-derived proinflammatory macrophages. Taken together, our results strongly support the concept that EO are an appropriate model for dissecting mechanisms that contribute to endometriotic lesion development. One Sentence SummaryEndometriotic organoids are an appropriate model to study epithelial-stromal interactions and model cell invasion associated with lesion development.

cell biology↗

bioRxiv2020

Developmental effects on pattern visual evoked potentials characterized by principal component analysis

PurposePeak amplitude and peak latency in the pattern reversal visual evoked potential (prVEP) vary with maturation. We considered that principal component analysis (PCA) may be used to describe age-related variation over the entire prVEP time course and provide a means of modeling and removing variation due to developmental age. MethodsprVEP was recorded from 155 healthy subjects ages 11-19 years at two timepoints. We created a model of the prVEP by identifying principal components (PCs) that explained >95% of the variance in a "training" dataset of 40 subjects. We examined the ability of the PCs to explain variance in an age- and sex-matched "validation" dataset (n=40) and calculated the intra-subject reliability of the PC coefficients between the two timepoints. We explored the effect of subject age and sex upon the PC coefficients. ResultsSeven PCs accounted for 96.0% of the variability of the training dataset and 90.5% of the variability in the validation dataset with good within-subject reliability across timepoints (R>0.7 for all PCs). The PCA model revealed narrowing and amplitude reduction of the P100 peak with maturation, and a broader and smaller P100 peak in males compared to females. ConclusionsPCA is a generalizable, reliable, and unbiased method of analyzing prVEP. The PCA model revealed changes across maturation and biological sex not fully described by standard peak analysis. Translational relevanceWe describe a novel application of PCA to characterize developmental changes of prVEP in youth that can be used to compare healthy and pathologic pediatric cohorts.

neuroscience↗