Biology subjects

ZHOU, Z.

Publications and source records attributed to ZHOU, Z..

2 recordsLinked to original sources

bioRxiv2025

Deep-Learning Cortical Registration Guided by Structural and Diffusion MRI and Connectivity

Accurate cortical surface registration is crucial for group-level neuroimaging analyses, yet geometry-based methods often yield suboptimal functional alignment across subjects due to substantial inter-individual variability. We present a novel deep-learning approach that incorporates white matter structural connectivity features from diffusion MRI (dMRI) tractography into the Joint Surface-based Registration and Atlas Construction (JOSA) framework. Our method generates vertex-wise connectivity maps by detecting streamline-surface intersections, followed by heat diffusion smoothing on the cortical manifold. We combine these connectivity features with scalar diffusion metrics (fractional anisotropy and apparent diffusion coefficient) and structural features as input to JOSA (which we call "JOSAConn"). Evaluated on HCP-YA subjects across 15 task contrasts, our method significantly outperforms FreeSurfer in functional alignment (Bonferroni-corrected p < 0.05 for 12 of 15 contrasts). This multimodal approach demonstrates that structural connectivity effectively bridges the gap between cortical geometry and functional organization while maintaining clinical applicability.

bioinformatics↗

bioRxiv2022

Dynamic characteristics and Functional Analysis Provide new insights into the role of GauERF105 in resistance against Verticillium wilt in Cotton

Verticillium wilt is the most devastating disease of cotton and it results in huge yield losses every year in the fields. The underlying mechanisms of VW in cotton are not well explored yet. In the current approach we used the transcriptome data from G. australe in response to Verticillium wilt attack to mine the ERF TFs and prove their potential role in resistance against VW attack in cotton. We identified 23 ERFs in total, and on the basis of expression at different time points i.e., 24h, 48h and 72h post inoculation and selected GauERF105 for further validation. We performed VIGS in cotton and over expression in Arabidopsis respectively. Moreover, DAB and trypan staining also suggests that the impact of disease was more in the wildtype as compared to transgene lines. On the basis of our results, we confirmed that GauERF105 is the key candidate and playing a key role for defending cotton against VW attack. Current finding might be helpful for generating resistance germplasm in cotton and it will be beneficial to recover the yield losses in field.

pathology↗