Clubbing and Digitalization of Government ID Proofs

Clubbing and Digitalization of Government ID Proofs is a software system for organizing and storing different kinds of documents required for a person�s identity proof. This software system handles digital documents, rather than paper documents, although in some instances, this system may also handle digital scanned versions of original paper documents. This system includes important legal documents like Birth Certificate, Aadhaar Card, PAN Card, Driving Licence, Passport, etc, a more general type of storage system that helps users to organize and store paper or digital documents. Each and every user can access by logging into the application using their username and password. This centralized system would help in providing the user to store a large volume of data and efficiently retrieve their data. This system will also help the users to update or edit any changes in their previously added information conveniently

Novel Humanized Recombinant T Cell Receptor Ligands Protect the Female Brain After Experimental Stroke

Transmigration of peripheral leukocytes to the brain is a major contributor to cerebral ischemic cell death mechanisms. Humanized partial major histocompatibility complex class II constructs (pMHC), covalently linked to myelin peptides, are effective for treating experimental stroke in males, but new evidence suggests that some inflammatory cell death mechanisms after brain injury are sex-specific. We here demonstrate that treatment with pMHC constructs also improves outcomes in female mice with middle cerebral artery occlusion (MCAO). HLA-DR2 transgenic female mice with MCAO were treated with RTL1000 (HLA-DR2 moiety linked to human MOG-35-55 peptide), HLA-DRa1-MOG-35-55, or vehicle (VEH) at 3, 24, 48, and 72 h after reperfusion and were recovered for 96 h or 2 weeks post-injury for measurement of histology (TTC staining) or behavioral testing. RTL1000- and DRa1-MOG-treated mice had profoundly reduced infarct volumes as compared to the VEH group, although higher doses of DRa1-MOG were needed for females vs. males evaluated previously. RTL1000-treated females also exhibited strongly improved functional recovery in a standard cylinder test. In novel studies of post-ischemic ultrasonic vocalization (USV), as measured by animal calls to their cage mates, we modeled in mice the post-stroke speech deficits common in human stroke survivors. The number of calls was reduced in injured animals relative to pre-MCAO baseline regardless of RTL1000 treatment status. However, call duration was significantly improved by RTL1000 treatment, suggesting benefit to the animal’s recovery of vocalization capability. We conclude that both the parent RTL1000 molecule and the novel non-polymorphic DRα1-MOG-35-55 construct were highly effective immunotherapies for treatment of transient cerebral ischemia in females

BoostMe accurately predicts DNA methylation values in whole-genome bisulfite sequencing of multiple human tissues

Abstract Background Bisulfite sequencing is widely employed to study the role of DNA methylation in disease; however, the data suffer from biases due to coverage depth variability. Imputation of methylation values at low-coverage sites may mitigate these biases while also identifying important genomic features associated with predictive power. Results Here we describe BoostMe, a method for imputing low-quality DNA methylation estimates within whole-genome bisulfite sequencing (WGBS) data. BoostMe uses a gradient boosting algorithm, XGBoost, and leverages information from multiple samples for prediction. We find that BoostMe outperforms existing algorithms in speed and accuracy when applied to WGBS of human tissues. Furthermore, we show that imputation improves concordance between WGBS and the MethylationEPIC array at low WGBS depth, suggesting improved WGBS accuracy after imputation. Conclusions Our findings support the use of BoostMe as a preprocessing step for WGBS analysis.https://deepblue.lib.umich.edu/bitstream/2027.42/143848/1/12864_2018_Article_4766.pd

Genetic regulatory signatures underlying islet gene expression and type 2 diabetes

The majority of genetic variants associated with type 2 diabetes (T2D) are located outside of genes in noncoding regions that may regulate gene expression in disease-relevant tissues, like pancreatic islets. Here, we present the largest integrated analysis to date of high-resolution, high-throughput human islet molecular profiling data to characterize the genome (DNA), epigenome (DNA packaging), and transcriptome (gene expression). We find that T2D genetic variants are enriched in regions of the genome where transcription Regulatory Factor X (RFX) is predicted to bind in an islet-specific manner. Genetic variants that increase T2D risk are predicted to disrupt RFX binding, providing a molecular mechanism to explain how the genome can influence the epigenome, modulating gene expression and ultimately T2D risk