Rho-kinase-dependent F-actin rearrangement is involved in the inhibition of PI3-kinase/Akt during ischemia–reperfusion-induced endothelial cell apoptosis

Activation of cytoskeleton regulator Rho-kinase during ischemia–reperfusion (I/R) plays a major role in I/R injury and apoptosis. Since Rho-kinase is a negative regulator of the pro-survival phosphatidylinositol 3-kinase (PI3-kinase)/Akt pathway, we hypothesized that inhibition of Rho-kinase can prevent I/R-induced endothelial cell apoptosis by maintaining PI3-kinase/Akt activity and that protective effects of Rho-kinase inhibition are facilitated by prevention of F-actin rearrangement. Human umbilical vein endothelial cells were subjected to 1 h of simulated ischemia and 1 or 24 h of simulated reperfusion after treatment with Rho-kinase inhibitor Y-27632, PI3-kinase inhibitor wortmannin, F-actin depolymerizers cytochalasinD and latrunculinA and F-actin stabilizer jasplakinolide. Intracellular ATP levels decreased following I/R. Y-27632 treatment reduced I/R-induced apoptosis by 31% (P < 0.01) and maintained Akt activity. Both effects were blocked by co-treatment with wortmannin. Y-27632 treatment prevented the formation of F-actin bundles during I/R. Similar results were observed with cytochalasinD treatment. In contrast, latrunculinA and jasplakinolide treatment did not prevent the formation of F-actin bundles during I/R and had no effect on I/R-induced apoptosis. Apoptosis and Akt activity were inversely correlated (R2 = 0.68, P < 0.05). In conclusion, prevention of F-actin rearrangement by Rho-kinase inhibition or by cytochalasinD treatment attenuated I/R-induced endothelial cell apoptosis by maintaining PI3-kinase and Akt activity

Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88

The filamentous fungus Aspergillus niger is widely exploited by the fermentation industry for the production of enzymes and organic acids, particularly citric acid. We sequenced the 33.9-megabase genome of A. niger CBS 513.88, the ancestor of currently used enzyme production strains. A high level of synteny was observed with other aspergilli sequenced. Strong function predictions were made for 6,506 of the 14,165 open reading frames identified. A detailed description of the components of the protein secretion pathway was made and striking differences in the hydrolytic enzyme spectra of aspergilli were observed. A reconstructed metabolic network comprising 1,069 unique reactions illustrates the versatile metabolism of A. niger. Noteworthy is the large number of major facilitator superfamily transporters and fungal zinc binuclear cluster transcription factors, and the presence of putative gene clusters for fumonisin and ochratoxin A synthesis

Privacy-preserving distributed learning of radiomics to predict overall survival and HPV status in head and neck cancer

A major challenge in radiomics is assembling data from multiple centers. Sharing data between hospitals is restricted by legal and ethical regulations. Distributed learning is a technique, enabling training models on multicenter data without data leaving the hospitals (“privacy-preserving” distributed learning). This study tested feasibility of distributed learning of radiomics data for prediction of two year overall survival and HPV status in head and neck cancer (HNC) patients. Pretreatment CT images were collected from 1174 HNC patients in 6 different cohorts. 981 radiomic features were extracted using Z-Rad software implementation. Hierarchical clustering was performed to preselect features. Classification was done using logistic regression. In the validation dataset, the receiver operating characteristics (ROC) were compared between the models trained in the centralized and distributed manner. No difference in ROC was observed with respect to feature selection. The logistic regression coefficients were identical between the methods (absolute difference  0.05). In conclusion, both feature selection and classification are feasible in a distributed manner using radiomics data, which opens new possibility for training more reliable radiomics models

Genome sequencing and analysis of the versatile cell factory Aspergillus niger CBS 513.88

The filamentous fungus Aspergillus niger is widely exploited by the fermentation industry for the production of enzymes and organic acids, particularly citric acid. We sequenced the 33.9-megabase genome of A. niger CBS 513.88, the ancestor of currently used enzyme production strains. A high level of synteny was observed with other aspergilli sequenced. Strong function predictions were made for 6,506 of the 14,165 open reading frames identified. A detailed description of the components of the protein secretion pathway was made and striking differences in the hydrolytic enzyme spectra of aspergilli were observed. A reconstructed metabolic network comprising 1,069 unique reactions illustrates the versatile metabolism of A. niger. Noteworthy is the large number of major facilitator superfamily transporters and fungal zinc binuclear cluster transcription factors, and the presence of putative gene clusters for fumonisin and ochratoxin A synthesis

Setting a baseline for global urban virome surveillance in sewage

The rapid development of megacities, and their growing connectedness across the world is becoming a distinct driver for emerging disease outbreaks. Early detection of unusual disease emergence and spread should therefore include such cities as part of risk-based surveillance. A catch-all metagenomic sequencing approach of urban sewage could potentially provide an unbiased insight into the dynamics of viral pathogens circulating in a community irrespective of access to care, a potential which already has been proven for the surveillance of poliovirus. Here, we present a detailed characterization of sewage viromes from a snapshot of 81 high density urban areas across the globe, including in-depth assessment of potential biases, as a proof of concept for catch-all viral pathogen surveillance. We show the ability to detect a wide range of viruses and geographical and seasonal differences for specific viral groups. Our findings offer a cross-sectional baseline for further research in viral surveillance from urban sewage samples and place previous studies in a global perspective

Genomic analysis of sewage from 101 countries reveals global landscape of antimicrobial resistance

Antimicrobial resistance (AMR) is a major threat to global health. Understanding the emergence, evolution, and transmission of individual antibiotic resistance genes (ARGs) is essential to develop sustainable strategies combatting this threat. Here, we use metagenomic sequencing to analyse ARGs in 757 sewage samples from 243 cities in 101 countries, collected from 2016 to 2019. We find regional patterns in resistomes, and these differ between subsets corresponding to drug classes and are partly driven by taxonomic variation. The genetic environments of 49 common ARGs are highly diverse, with most common ARGs carried by multiple distinct genomic contexts globally and sometimes on plasmids. Analysis of flanking sequence revealed ARG-specific patterns of dispersal limitation and global transmission. Our data furthermore suggest certain geographies are more prone to transmission events and should receive additional attention