Biology subjects

Chen, T. X.

Publications and source records attributed to Chen, T. X..

4 recordsLinked to original sources

bioRxiv2025

Identification of biomarkers for ulcerative morphology in carotid atherosclerosis plaques through single-cell RNA sequencing data

BackgroundCarotid atherosclerotic stenosis (CAS) is a major risk factor for stroke, particularly when associated with ulcerative plaque morphology. However, the molecular mechanisms underlying ulceration remain inadequately defined. In this study, we aimed to construct single-cell atlases of ulcerative and non-ulcerative CAS plaques to identify biomarkers associated with ulcerative lesions. MethodsPlaque tissues from four ulcerative and three non-ulcerative CAS samples were collected and subjected to single-cell RNA sequencing (scRNA-seq). Cell types were identified through scRNA-seq analysis, and differential cell types were determined by comparing their proportions between the 2 groups. Candidate genes were identified by intersecting differentially expressed genes (DEGs) within these differential cell populations. Subsequently, the Molecular Complex Detection (MCODE) plugin in Cytoscape was employed to confirm the biomarkers. Functional annotation and regulatory network analysis were then performed to investigate underlying biological mechanisms. ResultsscRNA-seq analysis identified 7 cell types, of which 6 showed differential proportions, leading to the identification of 61 candidate genes and 7 key biomarkers (KLF2, JUNB, FOS, HSPA1A, DUSP1, JUND, and ZFP36). Enrichment analysis indicated that these biomarkers may influence ulcerative CAS plaques via RNA polymerase II-mediated transcription and stress-response pathways. Regulatory network analysis revealed complex interactions, with RBMX, STAT3, YTHDF3, DDX3X, and ELAVL1 identified as potential upstream regulators. ConclusionsKLF2, JUNB, FOS, HSPA1A, DUSP1, JUND, and ZFP36 were identified as biomarkers, offering novel insights into the molecular mechanisms underlying ulcerative morphology in CAS.

pathology↗

bioRxiv2023

Dissociable roles of thalamic nuclei in the refinement of reaches to spatial targets

Reaches are complex movements that are critical for survival, and encompass the control of different aspects such as direction, speed, and endpoint precision. Complex movements have been postulated to be learned and controlled through distributed motor networks, of which the thalamus is a highly connected node. Still, the role of different thalamic circuits in learning and controlling specific aspects of reaches has not been investigated. We report dissociable roles of two distinct thalamic nuclei - the parafascicular (Pf) and ventroanterior/ventrolateral (VAL) nuclei - in the refinement of spatial target reaches in mice. Using 2-photon calcium imaging in a head-fixed joystick task where mice learned to reach to a target in space, we found that glutamatergic neurons in both areas were most active during reaches early in learning. Reach-related activity in both areas decreased late in learning, as movement direction was refined and reaches increased in accuracy. Furthermore, the population dynamics of Pf, but not VAL, covaried in different subspaces in early and late learning, but eventually stabilized in late learning. The neural activity in Pf, but not VAL, encoded the direction of reaches in early but not late learning. Accordingly, bilateral lesions of Pf before, but not after learning, strongly and specifically impaired the refinement of reach direction. VAL lesions did not impact direction refinement, but instead resulted in increased speed and target overshoot. Our findings provide new evidence that the thalamus is a critical motor node in the learning and control of reaching movements, with specific subnuclei controlling distinct aspects of the reach early in learning.

neuroscience↗

bioRxiv2023

Exploration biases how forelimb reaches to a spatial target are learned

The brain can learn to generate actions, such as reaching to a target, using different movement strategies. Understanding how different variables bias which strategies are learned to produce such a reach is important for our understanding of the neural bases of movement. Here we introduce a novel spatial forelimb target task in which perched head-fixed mice learn to reach to a circular target area from a set start position using a joystick. These reaches can be achieved by learning to move into a specific direction or to a specific endpoint location. We find that mice gradually learn to successfully reach the covert target. With time, they refine their initially exploratory complex joystick trajectories into controlled targeted reaches. The execution of these controlled reaches depends on the sensorimotor cortex. Using a probe test with shifting start positions, we show that individual mice learned to use strategies biased to either direction or endpoint-based movements. The degree of endpoint learning bias was correlated with the spatial directional variability with which the workspace was explored early in training. Furthermore, we demonstrate that reinforcement learning model agents exhibit a similar correlation between directional variability during training and learned strategy. These results provide evidence that individual exploratory behavior during training biases the control strategies that mice use to perform forelimb covert target reaches.

neuroscience↗

bioRxiv2017

High-throughput single-cell DNA sequencing of AML tumors with droplet microfluidics

To enable the characterization of genetic heterogeneity in tumor cell populations, we developed a novel microfluidic approach that barcodes amplified genomic DNA from thousands of individual cancer cells confined to droplets. The barcodes are then used to reassemble the genetic profiles of cells from next generation sequencing data. Using this approach, we sequenced longitudinally collected AML tumor populations from two patients and genotyped up to 62 disease relevant loci across more than 16,000 individual cells. Targeted single-cell sequencing was able to sensitively identify tumor cells during complete remission and uncovered complex clonal evolution within AML tumors that was not observable with bulk sequencing. We anticipate that this approach will make feasible the routine analysis of heterogeneity in AML leading to improved stratification and therapy selection for the disease.

genomics↗