The contribution of Alu exons to the human proteome.

BackgroundAlu elements are major contributors to lineage-specific new exons in primate and human genomes. Recent studies indicate that some Alu exons have high transcript inclusion levels or tissue-specific splicing profiles, and may play important regulatory roles in modulating mRNA degradation or translational efficiency. However, the contribution of Alu exons to the human proteome remains unclear and controversial. The prevailing view is that exons derived from young repetitive elements, such as Alu elements, are restricted to regulatory functions and have not had adequate evolutionary time to be incorporated into stable, functional proteins.ResultsWe adopt a proteotranscriptomics approach to systematically assess the contribution of Alu exons to the human proteome. Using RNA sequencing, ribosome profiling, and proteomics data from human tissues and cell lines, we provide evidence for the translational activities of Alu exons and the presence of Alu exon derived peptides in human proteins. These Alu exon peptides represent species-specific protein differences between primates and other mammals, and in certain instances between humans and closely related primates. In the case of the RNA editing enzyme ADARB1, which contains an Alu exon peptide in its catalytic domain, RNA sequencing analyses of A-to-I editing demonstrate that both the Alu exon skipping and inclusion isoforms encode active enzymes. The Alu exon derived peptide may fine tune the overall editing activity and, in limited cases, the site selectivity of ADARB1 protein products.ConclusionsOur data indicate that Alu elements have contributed to the acquisition of novel protein sequences during primate and human evolution

Novel role for the innate immune receptor toll-like receptor 4 (TLR4) in the regulation of the wnt signaling pathway and photoreceptor apoptosis

Recent evidence has implicated innate immunity in regulating neuronal survival in the brain during stroke and other neurodegenerations. Photoreceptors are specialized light-detecting neurons in the retina that are essential for vision. In this study, we investigated the role of the innate immunity receptor TLR4 in photoreceptors. TLR4 activation by lipopolysaccharide (LPS) significantly reduced the survival of cultured mouse photoreceptors exposed to oxidative stress. With respect to mechanism, TLR4 suppressed Wnt signaling, decreased phosphorylation and activation of the Wnt receptor LRP6, and blocked the protective effect of the Wnt3a ligand. Paradoxically, TLR4 activation prior to oxidative injury protected photoreceptors, in a phenomenon known as preconditioning. Expression of TNFα and its receptors TNFR1 and TNFR2 decreased during preconditioning, and preconditioning was mimicked by TNFα antagonists, but was independent of Wnt signaling. Therefore, TLR4 is a novel regulator of photoreceptor survival that acts through the Wnt and TNFα pathways. © 2012 Yi et al

Search for a Light Sterile Neutrino at Daya Bay

published_or_final_versio

The muon system of the Daya Bay Reactor antineutrino experiment

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Independent measure of the neutrino mixing angle θ13 via neutron capture on hydrogen at Daya Bay

published_or_final_versio

Microbial Indoles: Key Regulators of Organ Growth and Metabolic Function.

Gut microbes supporting body growth are known but the mechanisms are less well documented. Using the microbial tryptophan metabolite indole, known to regulate prokaryotic cell division and metabolic stress conditions, we mono-colonized germ-free (GF) mice with indole-producing wild-type Escherichia coli (E. coli) or tryptophanase-encoding tnaA knockout mutant indole-non-producing E. coli. Indole mutant E. coli mice showed multiorgan growth retardation and lower levels of glycogen, cholesterol, triglycerides, and glucose, resulting in an energy deficiency despite increased food intake. Detailed analysis revealed a malfunctioning intestine, enlarged cecum, and reduced numbers of enterochromaffin cells, correlating with a metabolic phenotype consisting of impaired gut motility, diminished digestion, and lower energy harvest. Furthermore, indole mutant mice displayed reduction in serum levels of tricarboxylic acid (TCA) cycle intermediates and lipids. In stark contrast, a massive increase in serum melatonin was observed-frequently associated with accelerated oxidative stress and mitochondrial dysfunction. This observational report discloses functional roles of microbe-derived indoles regulating multiple organ functions and extends our previous report of indole-linked regulation of adult neurogenesis. Since indoles decline by age, these results imply a correlation with age-linked organ decline and levels of indoles. Interestingly, increased levels of indole-3-acetic acid, a known indole metabolite, have been shown to correlate with younger biological age, further supporting a link between biological age and levels of microbe-derived indole metabolites. The results presented in this resource paper will be useful for the future design of food intervention studies to reduce accelerated age-linked organ decline

Self-supervised Outdoor Scene Relighting

Outdoor scene relighting is a challenging problem that requires good understanding of the scene geometry, illumination and albedo. Current techniques are completely supervised, requiring high quality synthetic renderings to train a solution. Such renderings are synthesized using priors learned from limited data. In contrast, we propose a self-supervised approach for relighting. Our approach is trained only on corpora of images collected from the internet without any user-supervision. This virtually endless source of training data allows training a general relighting solution. Our approach first decomposes an image into its albedo, geometry and illumination. A novel relighting is then produced by modifying the illumination parameters. Our solution capture shadow using a dedicated shadow prediction map, and does not rely on accurate geometry estimation. We evaluate our technique subjectively and objectively using a new dataset with ground-truth relighting. Results show the ability of our technique to produce photo-realistic and physically plausible results, that generalizes to unseen scenes.Comment: Published in ECCV '20, http://gvv.mpi-inf.mpg.de/projects/SelfRelight

Gene encoder: a feature selection technique through unsupervised deep learning-based clustering for large gene expression data

© 2020, Springer-Verlag London Ltd., part of Springer Nature. Cancer is a severe condition of uncontrolled cell division that results in a tumor formation that spreads to other tissues of the body. Therefore, the development of new medication and treatment methods for this is in demand. Classification of microarray data plays a vital role in handling such situations. The relevant gene selection is an important step for the classification of microarray data. This work presents gene encoder, an unsupervised two-stage feature selection technique for the cancer samples’ classification. The first stage aggregates three filter methods, namely principal component analysis, correlation, and spectral-based feature selection techniques. Next, the genetic algorithm is used, which evaluates the chromosome utilizing the autoencoder-based clustering. The resultant feature subset is used for the classification task. Three classifiers, namely support vector machine, k-nearest neighbors, and random forest, are used in this work to avoid the dependency on any one classifier. Six benchmark gene expression datasets are used for the performance evaluation, and a comparison is made with four state-of-the-art related algorithms. Three sets of experiments are carried out to evaluate the proposed method. These experiments are for the evaluation of the selected features based on sample-based clustering, adjusting optimal parameters, and for selecting better performing classifier. The comparison is based on accuracy, recall, false positive rate, precision, F-measure, and entropy. The obtained results suggest better performance of the current proposal

Expression of pendrin in benign and malignant human thyroid tissues

The Pendred syndrome gene (PDS) encodes a transmembrane protein, pendrin, which is expressed in follicular thyroid cells and participates in the apical iodide transport. Pendrin expression has been studied in various thyroid neoplasms by means of immunohistochemistry (IHC), Western blot and RT–quantitative real-time PCR. The expression was related to the functional activity of the thyroid tissue. Follicular cells of normal, nodular goitre and Graves' disease tissues express pendrin at the apical pole of the thyrocytes. In follicular adenomas, pendrin was detected in cell membranes and cytoplasm simultaneously in 10 out of 15 cases. Pendrin protein was detected in 73.3 and 76.7% of the follicular (FTC) and papillary (PTC) thyroid carcinomas, respectively, where pendrin was solely localised inside the cytoplasm. An extensive intracellular immunostaining of pendrin was observed in six out of 11 (54.5%) of positive FTCs and 19 out of 23 (82%) of PTCs. Focal reactivity was detected in one follicular- and three papillary carcinomas, whereas pendrin protein was absent in three of 15 FTC and four of 30 PTC; mRNA of pendrin was detected in 92.4% of thyroid tumours. The relative mRNA expression of pendrin was lower in cancers than in normal thyroid tissues (P<0.001). The pendrin protein level was found to parallel its mRNA expression, which was not, however, related to the tumour size and tumour stage. In conclusion, pendrin is expressed in the majority of differentiated thyroid tumours with high individual variability but its targeting to the apical cell membrane is affected