1.
Deep learning features from diffusion tensor imaging improve glioma stratification and identify risk groups with distinct molecular pathway activities.
Yan, J, Zhao, Y, Chen, Y, Wang, W, Duan, W, Wang, L, Zhang, S, Ding, T, Liu, L, Sun, Q, et al
EBioMedicine. 2021;:103583
Abstract
BACKGROUND To develop and validate a deep learning signature (DLS) from diffusion tensor imaging (DTI) for predicting overall survival in patients with infiltrative gliomas, and to investigate the biological pathways underlying the developed DLS. METHODS The DLS was developed based on a deep learning cohort (n = 688). The key pathways underlying the DLS were identified on a radiogenomics cohort with paired DTI and RNA-seq data (n=78), where the prognostic value of the pathway genes was validated in public databases (TCGA, n = 663; CGGA, n = 657). FINDINGS The DLS was associated with survival (log-rank P < 0.001) and was an independent predictor (P < 0.001). Incorporating the DLS into existing risk system resulted in a deep learning nomogram predicting survival better than either the DLS or the clinicomolecular nomogram alone, with a better calibration and classification accuracy (net reclassification improvement 0.646, P < 0.001). Five kinds of pathways (synaptic transmission, calcium signaling, glutamate secretion, axon guidance, and glioma pathways) were significantly correlated with the DLS. Average expression value of pathway genes showed prognostic significance in our radiogenomics cohort and TCGA/CGGA cohorts (log-rank P < 0.05). INTERPRETATION DTI-derived DLS can improve glioma stratification by identifying risk groups with dysregulated biological pathways that contributed to survival outcomes. Therapies inhibiting neuron-to-brain tumor synaptic communication may be more effective in high-risk glioma defined by DTI-derived DLS. FUNDING A full list of funding bodies that contributed to this study can be found in the Acknowledgements section.
2.
Contribution of TRPV channels to osmosensory transduction, thirst, and vasopressin release.
Sharif-Naeini, R, Ciura, S, Zhang, Z, Bourque, CW
Kidney international. 2008;(7):811-5
Abstract
Systemic osmoregulation is an integrated physiological process through which water intake and excretion are continuously balanced against salt intake and excretion to maintain the osmolality of the extracellular fluid near an optimal 'set-point' value. The behaviors (that is, thirst and sodium appetite) and renal responses (diuresis and natriuresis) that are modulated to mediate osmoregulatory homeostasis are mainly controlled by the nervous system. Appropriate regulation of these parameters depends in large part on specialized osmosensitive neurons, termed osmoreceptors, which convert changes in plasma osmolality into electrical signals that ultimately modulate effector functions to achieve homeostasis. Previous work has shown that mechanosensitive cation channels expressed in osmoreceptor neurons play a key role in the process of osmosensory transduction. Although the molecular identity of these channels remains unknown, a growing body of evidence, reviewed here, indicates that members of the transient receptor potential vanilloid family of ion channels may contribute to osmosensory transduction and to homeostatic responses implicated in the control of water balance.