Reasons for hospitalizations in patients with type 2 diabetes mellitus in the CANVAS Program:a secondary analysis

AIMS: To determine the reasons for hospitalizations in the CANagliflozin cardioVascular Assessment Study (CANVAS) Program and the effects of the sodium glucose co-transporter 2 inhibitor canagliflozin on hospitalization. MATERIALS AND METHODS: A secondary analysis was performed on the CANVAS Program that included 10,142 participants with type 2 diabetes mellitus randomized to canagliflozin or placebo. The primary outcome was total (first plus all recurrent) all-cause hospitalization (ACH). Secondary outcomes were total hospitalizations categorized by the Medical Dictionary for Regulatory Activities hierarchy at the system organ class level, reported by investigators at each center. Outcomes were assessed using negative binomial models. RESULTS: Of the 7115 hospitalizations reported, the most common reasons were cardiac disorders (23.7%), infections and infestations (15.0%), and nervous system disorders (9.0%). The rate of total ACH was lower in the canagliflozin group (n=5795) compared to the placebo group (n=4347): 197.9 versus 215.8 participants per 1000 patient-years, respectively (rate ratio [RR] 0.92; 95% confidence interval [CI] 0.86, 0.98). Canagliflozin reduced the rate of total hospitalizations due to cardiac disorders (RR 0.81; 95% CI 0.75, 0.88). There was no significant difference between the canagliflozin and placebo groups in the rates of total hospitalizations due to infections and infestations (RR 0.96; 95% CI 0.86, 1.02) or nervous system disorders (RR 0.96; 95% CI 0.88, 1.05). CONCLUSIONS: In the CANVAS Program, the most common reasons for hospitalization were cardiac disorders, infections and infestations, and nervous system disorders. Canagliflozin, compared with placebo, reduced the rate of total ACH. This article is protected by copyright. All rights reserved

Quantum Physics and Human Language

Human languages employ constructions that tacitly assume specific properties of the limited range of phenomena they evolved to describe. These assumed properties are true features of that limited context, but may not be general or precise properties of all the physical situations allowed by fundamental physics. In brief, human languages contain `excess baggage' that must be qualified, discarded, or otherwise reformed to give a clear account in the context of fundamental physics of even the everyday phenomena that the languages evolved to describe. The surest route to clarity is to express the constructions of human languages in the language of fundamental physical theory, not the other way around. These ideas are illustrated by an analysis of the verb `to happen' and the word `reality' in special relativity and the modern quantum mechanics of closed systems.Comment: Contribution to the festschrift for G.C. Ghirardi on his 70th Birthday, minor correction

Systems-Scale Analysis Reveals Pathways Involved in Cellular Response to Methamphetamine

Background: Methamphetamine (METH), an abused illicit drug, disrupts many cellular processes, including energy metabolism, spermatogenesis, and maintenance of oxidative status. However, many components of the molecular underpinnings of METH toxicity have yet to be established. Network analyses of integrated proteomic, transcriptomic and metabolomic data are particularly well suited for identifying cellular responses to toxins, such as METH, which might otherwise be obscured by the numerous and dynamic changes that are induced. Methodology/Results: We used network analyses of proteomic and transcriptomic data to evaluate pathways in Drosophila melanogaster that are affected by acute METH toxicity. METH exposure caused changes in the expression of genes involved with energy metabolism, suggesting a Warburg-like effect (aerobic glycolysis), which is normally associated with cancerous cells. Therefore, we tested the hypothesis that carbohydrate metabolism plays an important role in METH toxicity. In agreement with our hypothesis, we observed that increased dietary sugars partially alleviated the toxic effects of METH. Our systems analysis also showed that METH impacted genes and proteins known to be associated with muscular homeostasis/ contraction, maintenance of oxidative status, oxidative phosphorylation, spermatogenesis, iron and calcium homeostasis. Our results also provide numerous candidate genes for the METH-induced dysfunction of spermatogenesis, which have not been previously characterized at the molecular level. Conclusion: Our results support our overall hypothesis that METH causes a toxic syndrome that is characterized by the altered carbohydrate metabolism, dysregulation of calcium and iron homeostasis, increased oxidative stress, and disruption of mitochondrial functions

Methods to study splicing from high-throughput RNA Sequencing data

The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq) has provided a very powerful mean to study splicing under multiple conditions at unprecedented depth. However, the complexity of the information to be analyzed has turned this into a challenging task. In the last few years, a plethora of tools have been developed, allowing researchers to process RNA-Seq data to study the expression of isoforms and splicing events, and their relative changes under different conditions. We provide an overview of the methods available to study splicing from short RNA-Seq data. We group the methods according to the different questions they address: 1) Assignment of the sequencing reads to their likely gene of origin. This is addressed by methods that map reads to the genome and/or to the available gene annotations. 2) Recovering the sequence of splicing events and isoforms. This is addressed by transcript reconstruction and de novo assembly methods. 3) Quantification of events and isoforms. Either after reconstructing transcripts or using an annotation, many methods estimate the expression level or the relative usage of isoforms and/or events. 4) Providing an isoform or event view of differential splicing or expression. These include methods that compare relative event/isoform abundance or isoform expression across two or more conditions. 5) Visualizing splicing regulation. Various tools facilitate the visualization of the RNA-Seq data in the context of alternative splicing. In this review, we do not describe the specific mathematical models behind each method. Our aim is rather to provide an overview that could serve as an entry point for users who need to decide on a suitable tool for a specific analysis. We also attempt to propose a classification of the tools according to the operations they do, to facilitate the comparison and choice of methods.Comment: 31 pages, 1 figure, 9 tables. Small corrections adde

Symmetry and topology in antiferromagnetic spintronics

Antiferromagnetic spintronics focuses on investigating and using antiferromagnets as active elements in spintronics structures. Last decade advances in relativistic spintronics led to the discovery of the staggered, current-induced field in antiferromagnets. The corresponding N\'{e}el spin-orbit torque allowed for efficient electrical switching of antiferromagnetic moments and, in combination with electrical readout, for the demonstration of experimental antiferromagnetic memory devices. In parallel, the anomalous Hall effect was predicted and subsequently observed in antiferromagnets. A new field of spintronics based on antiferromagnets has emerged. We will focus here on the introduction into the most significant discoveries which shaped the field together with a more recent spin-off focusing on combining antiferromagnetic spintronics with topological effects, such as antiferromagnetic topological semimetals and insulators, and the interplay of antiferromagnetism, topology, and superconductivity in heterostructures.Comment: Book chapte

MicroRNAs targeting oncogenes are down-regulated in pancreatic malignant transformation from benign tumors

BACKGROUND MicroRNA (miRNA) expression profiles have been described in pancreatic ductal adenocarcinoma (PDAC), but these have not been compared with pre-malignant pancreatic tumors. We wished to compare the miRNA expression signatures in pancreatic benign cystic tumors (BCT) of low and high malignant potential with PDAC, in order to identify miRNAs deregulated during PDAC development. The mechanistic consequences of miRNA dysregulation were further evaluated. METHODS Tissue samples were obtained at a tertiary pancreatic unit from individuals with BCT and PDAC. MiRNA profiling was performed using a custom microarray and results were validated using RT-qPCR prior to evaluation of miRNA targets. RESULTS Widespread miRNA down-regulation was observed in PDAC compared to low malignant potential BCT. We show that amongst those miRNAs down-regulated, miR-16, miR-126 and let-7d regulate known PDAC oncogenes (targeting BCL2, CRK and KRAS respectively). Notably, miR-126 also directly targets the KRAS transcript at a "seedless" binding site within its 3'UTR. In clinical specimens, miR-126 was strongly down-regulated in PDAC tissues, with an associated elevation in KRAS and CRK proteins. Furthermore, miR-21, a known oncogenic miRNA in pancreatic and other cancers, was not elevated in PDAC compared to serous microcystic adenoma (SMCA), but in both groups it was up-regulated compared to normal pancreas, implicating early up-regulation during malignant change. CONCLUSIONS Expression profiling revealed 21 miRNAs down-regulated in PDAC compared to SMCA, the most benign lesion that rarely progresses to invasive carcinoma. It appears that miR-21 up-regulation is an early event in the transformation from normal pancreatic tissue. MiRNA expression has the potential to distinguish PDAC from normal pancreas and BCT. Mechanistically the down-regulation of miR-16, miR-126 and let-7d promotes PDAC transformation by post-transcriptional up-regulation of crucial PDAC oncogenes. We show that miR-126 is able to directly target KRAS; re-expression has the potential as a therapeutic strategy against PDAC and other KRAS-driven cancers

Insight into the Stability of Cross-β Amyloid Fibril from VEALYL Short Peptide with Molecular Dynamics Simulation

Amyloid fibrils are found in many fatal neurodegenerative diseases such as Alzheimer's disease, Parkinson's disease, type II diabetes, and prion disease. The VEALYL short peptide from insulin has been confirmed to aggregate amyloid-like fibrils. However, the aggregation mechanism of amyloid fibril is poorly understood. Here, we utilized molecular dynamics simulation to analyse the stability of VEALYL hexamer. The statistical results indicate that hydrophobic residues play key roles in stabilizing VEALYL hexamer. Single point and two linkage mutants confirmed that Val1, Leu4, and Tyr5 of VEALYL are key residues. The consistency of the results for the VEALYL oligomer suggests that the intermediate states might be trimer (3-0) and pentamer(3-2). These results can help us to obtain an insight into the aggregation mechanism of amyloid fibril. These methods can be used to study the stability of amyloid fibril from other short peptides

Novel copy number variants in children with autism and additional developmental anomalies

Autism is a neurodevelopmental disorder characterized by three core symptom domains: ritualistic-repetitive behaviors, impaired social interaction, and impaired communication and language development. Recent studies have highlighted etiologically relevant recurrent copy number changes in autism, such as 16p11.2 deletions and duplications, as well as a significant role for unique, novel variants. We used Affymetrix 250K GeneChip Microarray technology (either NspI or StyI) to detect microdeletions and duplications in a subset of children from the Autism Genetic Resource Exchange (AGRE). In order to enrich our sample for potentially pathogenic CNVs we selected children with autism who had additional features suggestive of chromosomal loss associated with developmental disturbance (positive criteria filter) but who had normal cytogenetic testing (negative criteria filter). We identified families with the following features: at least one child with autism who also had facial dysmorphology, limb or digit abnormalities, or ocular abnormalities. To detect changes in copy number we used a publicly available program, Copy Number Analyser for GeneChip® (CNAG) Ver. 2.0. We identified novel deletions and duplications on chromosomes 1q24.2, 3p26.2, 4q34.2, and 6q24.3. Several of these deletions and duplications include new and interesting candidate genes for autism such as syntaxin binding protein 5 (STXBP5 also known as tomosyn) and leucine rich repeat neuronal 1 (LRRN1 also known as NLRR1). Lastly, our data suggest that rare and potentially pathogenic microdeletions and duplications may have a substantially higher prevalence in children with autism and additional developmental anomalies than in children with autism alone

RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome

<p>Abstract</p> <p>Background</p> <p>RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments.</p> <p>Results</p> <p>We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM's ability to effectively use ambiguously-mapping reads, we show that accurate gene-level abundance estimates are best obtained with large numbers of short single-end reads. On the other hand, estimates of the relative frequencies of isoforms within single genes may be improved through the use of paired-end reads, depending on the number of possible splice forms for each gene.</p> <p>Conclusions</p> <p>RSEM is an accurate and user-friendly software tool for quantifying transcript abundances from RNA-Seq data. As it does not rely on the existence of a reference genome, it is particularly useful for quantification with de novo transcriptome assemblies. In addition, RSEM has enabled valuable guidance for cost-efficient design of quantification experiments with RNA-Seq, which is currently relatively expensive.</p

Adenovirus-Vectored Drug-Vaccine Duo as a Rapid-Response Tool for Conferring Seamless Protection against Influenza

Few other diseases exert such a huge toll of suffering as influenza. We report here that intranasal (i.n.) administration of E1/E3-defective (ΔE1E3) adenovirus serotype 5 (Ad5) particles rapidly induced an anti-influenza state as a means of prophylactic therapy which persisted for several weeks in mice. By encoding an influenza virus (IFV) hemagglutinin (HA) HA1 domain, an Ad5-HA1 vector conferred rapid protection as a prophylactic drug followed by elicitation of sustained protective immunity as a vaccine for inducing seamless protection against influenza as a drug-vaccine duo (DVD) in a single package. Since Ad5 particles induce a complex web of host responses, which could arrest influenza by activating a specific arm of innate immunity to impede IFV growth in the airway, it is conceivable that this multi-pronged influenza DVD may escape the fate of drug resistance that impairs the current influenza drugs