Bacterial community changes in a glacial-fed Tibetan lake are correlated with glacial melting

Climate change-induced glacial melting is a global phenomenon. The effects of climate change-induced melting on the microbial ecology in different glacial-fed aquatic systems have been well illuminated, but the resolution of seasonal dynamics was still limited. Here, we studied bacterial community composition and diversity in a glacial-fed Tibetan lake, Lake Ranwu, to elucidate how glacial-fed aquatic ecosystems respond to the seasonal glacial melting. Obvious seasonal variations of bacterial dominant groups were found in Lake Ranwu and inlet rivers. In April, the majority of OTUs belonged to the Bacteroidetes, Actinobacteria and Proteobacteria. The Proteobacteria increased to the most abundant phylum in July and November, while the Bacteroidetes and Actinobacteria decreased about 50% over seasons. Most key discriminant taxa of each season's community strongly associated with specific environmental variables, suggesting their adaptation to seasonal environments. Bacterial alpha diversity varied among seasons and exhibited strongly negative correlations with conductivity. Conductivity was the major driving force in determining the seasonal variation of bacterial community composition. Fluctuated conductivity was one of the consequences of seasonal melting of glaciers. This study offered evidence for the unique seasonal dynamics pattern of bacterial communities responding to glacial melting. Moreover, this study may provide a reference for assessing the long-term effects of glacial retreat on glacial-fed aquatic ecosystems. (C) 2018 Elsevier B.V. All rights reserved

Artificial intelligence-based MRI radiomics and radiogenomics in glioma

Abstract The specific genetic subtypes that gliomas exhibit result in variable clinical courses and the need to involve multidisciplinary teams of neurologists, epileptologists, neurooncologists and neurosurgeons. Currently, the diagnosis of gliomas pivots mainly around the preliminary radiological findings and the subsequent definitive surgical diagnosis (via surgical sampling). Radiomics and radiogenomics present a potential to precisely diagnose and predict survival and treatment responses, via morphological, textural, and functional features derived from MRI data, as well as genomic data. In spite of their advantages, it is still lacking standardized processes of feature extraction and analysis methodology among different research groups, which have made external validations infeasible. Radiomics and radiogenomics can be used to better understand the genomic basis of gliomas, such as tumor spatial heterogeneity, treatment response, molecular classifications and tumor microenvironment immune infiltration. These novel techniques have also been used to predict histological features, grade or even overall survival in gliomas. In this review, workflows of radiomics and radiogenomics are elucidated, with recent research on machine learning or artificial intelligence in glioma

Geographic distance and pH drive bacterial distribution in alkaline lake sediments across Tibetan Plateau.

Continent-scale biogeography has been extensively studied in soils and marine systems, but little is known about biogeographical patterns in non-marine sediments. We used barcode pyrosequencing to quantify the effects of local geochemical properties and geographic distance for bacterial community structure and membership, using sediment samples from 15 lakes on the Tibetan Plateau (4-1670 km apart). Bacterial communities were surprisingly diverse, and distinct from soil communities. Four of 26 phyla detected were dominant: Proteobacteria, Bacteroidetes, Firmicutes and Actinobacteria, albeit 20.2% of sequences were unclassified at the phylum level. As previously observed in acidic soil, pH was the dominant factor influencing alkaline sediment community structure, phylotype richness and phylogenetic diversity. In contrast, archaeal communities were less affected by pH. More geographically distant sites had more dissimilar communities (r=0.443, P=0.030). Variance partitioning analysis showed that geographic distance (historical contingencies) contributed more to bacterial community variation (12.2%) than any other factor, although the environmental factors explained more variance when combined (28.9%). Together, our results show that pH is the best predictor of bacterial community structure in alkaline sediments, and confirm that both geographic distance and chemical factors govern bacterial biogeography in lake sediments

Geographic distance and pH drive bacterial distribution in alkaline lake sediments across Tibetan Plateau.

Continent-scale biogeography has been extensively studied in soils and marine systems, but little is known about biogeographical patterns in non-marine sediments. We used barcode pyrosequencing to quantify the effects of local geochemical properties and geographic distance for bacterial community structure and membership, using sediment samples from 15 lakes on the Tibetan Plateau (4-1670 km apart). Bacterial communities were surprisingly diverse, and distinct from soil communities. Four of 26 phyla detected were dominant: Proteobacteria, Bacteroidetes, Firmicutes and Actinobacteria, albeit 20.2% of sequences were unclassified at the phylum level. As previously observed in acidic soil, pH was the dominant factor influencing alkaline sediment community structure, phylotype richness and phylogenetic diversity. In contrast, archaeal communities were less affected by pH. More geographically distant sites had more dissimilar communities (r=0.443, P=0.030). Variance partitioning analysis showed that geographic distance (historical contingencies) contributed more to bacterial community variation (12.2%) than any other factor, although the environmental factors explained more variance when combined (28.9%). Together, our results show that pH is the best predictor of bacterial community structure in alkaline sediments, and confirm that both geographic distance and chemical factors govern bacterial biogeography in lake sediments