Biology subjects

Chan, J.

Publications and source records attributed to Chan, J..

75 records · Page 5Linked to original sources

bioRxiv2017

The Anatomical Tracings of Lesions After Stroke (ATLAS) Dataset - Release 1.1

Stroke is the leading cause of adult disability worldwide, with up to two-thirds of individuals experiencing long-term disabilities. Large-scale neuroimaging studies have shown promise in identifying robust biomarkers (e.g., measures of brain structure) of long-term stroke recovery following rehabilitation. However, analyzing large rehabilitation-related datasets is problematic due to barriers in accurate stroke lesion segmentation. Manually-traced lesions are currently the gold standard for lesion segmentation on T1-weighted MRIs, but are labor intensive and require anatomical expertise. While algorithms have been developed to automate this process, the results often lack accuracy. Newer algorithms that employ machine-learning techniques are promising, yet these require large training datasets to optimize performance. Here we present ATLAS (Anatomical Tracings of Lesions After Stroke), an open-source dataset of 304 T1-weighted MRIs with manually segmented lesions and metadata. This large, diverse dataset can be used to train and test lesion segmentation algorithms and provides a standardized dataset for comparing the performance of different segmentation methods. We hope ATLAS release 1.1 will be a useful resource to assess and improve the accuracy of current lesion segmentation methods.

neuroscience↗

bioRxiv2017

Type 2 diabetes promotes cell centrosome amplification and the role of AKT-ROS-dependent signalling of ROCK1 and 14-3-3σ

Type2 diabetes is associated with oxidative stress which can cause cell centrosome amplification. The study investigated centrosome amplification in type 2 diabetes and the underlying mechanisms. We found that centrosome amplification was increased in the peripheral blood mononuclear cells (PBMC) from the type 2 diabetic patients, which correlated with the levels of fasting blood glucose and HbA1c. High glucose, insulin and palmitic acid, alone or in combinations, induced ROS production and centrosome amplification. Together, they increased AKT activation as well as the expression, binding and centrosome translation of ROCK1 and 14-3-3{sigma}. Results from further analyses showed that AKT-ROS-dependent upregulations of expression, binding and centrosome translocation of ROCK1 and 14-3-3{sigma} was the molecular pathway underlying the centrosome amplification induced by high glucose, insulin and palmitic acid. Moreover, the increases in AKT activation and ROS production as well as expression, binding and centrosome distribution of ROCK1 and 14-3-3{sigma} were confirmed in the PBMC from the patients with type 2 diabetes. In conclusion, our results show that type 2 diabetes promotes cell centrosome amplification, and suggest that the diabetic pathophysiological factors-activated AKT-ROS-dependent signalling of ROCK1 and 14-3-3{sigma} is the underlying molecular mechanism.

cell biology↗

bioRxiv2017

Phenotype and gene ontology enrichment as guides for disease modeling in C. elegans

Genome-wide experiments have the capacity to generate massive amounts of unbiased data about an organism. In order to interpret this data, dimensionality reduction techniques are required. One approach is to annotate genes using controlled languages and to test experimental datasets for term enrichment using probabilistic methods. Although gene, phenotype and anatomy ontologies exist for C. elegans, no unified software offers enrichment analyses of all the ontologies using the same methodology. Here, we present the WormBase Enrichment Suite, which offers users the ability to test all nematode ontologies simultaneously. We show that the WormBase Enrichment Suite provides valuable insight into different biological problems. Briefly, we show that phenotype enrichment analysis (PEA) can help researchers identify disease phenologs, phenotypes that are homologous across species, which can inform disease modeling in C. elegans. The WormBase Enrichment Suite analysis can also shed light on RNA-seq datasets by showing what molecular functions are enriched, which phenotypes these functions are implicated in and what tissues are overrepresented in the dataset. Finally, we explore the phenotype-anatomy relationship, showing that a small subset of highly specific tissues are disproportionately likely to cause an Egl phenotype, but inferring tissue expression from an Egl phenotype is limited to the largest tissues.

bioinformatics↗