Orr Kaae (galleypoppy2)

In addition, our results cannot corroborate the widely held assumption in evidence-based medicine that an important component of clinical expertise consists of experience of patients' preferences.Technological advances have enabled us to profile multiple molecular layers at unprecedented single-cell resolution and the available datasets from multiple samples or domains are growing. These datasets, including scRNA-seq data, scATAC-seq data and sc-methylation data, usually have different powers in identifying the unknown cell types through clustering. So, methods that integrate multiple datasets can potentially lead to a better clustering performance. Here we propose coupleCoC+ for the integrative analysis of single-cell genomic data. coupleCoC+ is a transfer learning method based on the information-theoretic co-clustering framework. In coupleCoC+, we utilize the information in one dataset, the source data, to facilitate the analysis of another dataset, the target data. coupleCoC+ uses the linked features in the two datasets for effective knowledge transfer, and it also uses the information of the features in the target data that are unlinked with the source data. In addition, coupleCoC+ matches similar cell types across the source data and the target data. By applying coupleCoC+ to the integrative clustering of mouse cortex scATAC-seq data and scRNA-seq data, mouse and human scRNA-seq data, mouse cortex sc-methylation and scRNA-seq data, and human blood dendritic cells scRNA-seq data from two batches, we demonstrate that coupleCoC+ improves the overall clustering performance and matches the cell subpopulations across multimodal single-cell genomic datasets. coupleCoC+ has fast convergence and it is computationally efficient. The software is available at https//github.com/cuhklinlab/coupleCoC_plus.Nutrient-responsive protein kinases control the balance between anabolic growth and catabolic processes such as autophagy. Aberrant regulation of these kinases is a major cause of human disease. We report here that the vertebrate nonreceptor tyrosine kinase Src-related kinase lacking C-terminal regulatory tyrosine and N-terminal myristylation sites (SRMS) inhibits autophagy and promotes growth in a nutrient-responsive manner. Under nutrient-replete conditions, SRMS phosphorylates the PHLPP scaffold FK506-binding protein 51 (FKBP51), disrupts the FKBP51-PHLPP complex, and promotes FKBP51 degradation through the ubiquitin-proteasome pathway. This prevents PHLPP-mediated dephosphorylation of AKT, causing sustained AKT activation that promotes growth and inhibits autophagy. SRMS is amplified and overexpressed in human cancers where it drives unrestrained AKT signaling in a kinase-dependent manner. SRMS kinase inhibition activates autophagy, inhibits cancer growth, and can be accomplished using the FDA-approved tyrosine kinase inhibitor ibrutinib. This illuminates SRMS as a targetable vulnerability in human cancers and as a new target for pharmacological induction of autophagy in vertebrates.Neosadocus harvestmen are endemic to the Southern Brazilian Atlantic Forest. Although they are conspicuous and display great morphological variation, their evolutionary history and the biogeographical events underlying their diversification and distribution are still unknown. This contribution about Neosadocus includes the following a taxonomic revision; a molecular phylogenetic analysis using mitochondrial and nuclear markers; an investigation of the genetic structure and species' diversity in a phylogeographical framework. Our results show that Neosadocus is a monophyletic group and comprises four species N. bufo, N. maximus, N. robustus and N. misandrus (which we did not find on fieldwork and only studied the female holotype). There is astonishing male polymorphism in N. robustus, mostly related to reproductive strategies. The following synonymies have resulted from this work "