Metabolic Network Topology Reveals Transcriptional Regulatory Signatures of Type 2 Diabetes

Type 2 diabetes mellitus (T2DM) is a disorder characterized by both insulin resistance and impaired insulin secretion. Recent transcriptomics studies related to T2DM have revealed changes in expression of a large number of metabolic genes in a variety of tissues. Identification of the molecular mechanisms underlying these transcriptional changes and their impact on the cellular metabolic phenotype is a challenging task due to the complexity of transcriptional regulation and the highly interconnected nature of the metabolic network. In this study we integrate skeletal muscle gene expression datasets with human metabolic network reconstructions to identify key metabolic regulatory features of T2DM. These features include reporter metabolites—metabolites with significant collective transcriptional response in the associated enzyme-coding genes, and transcription factors with significant enrichment of binding sites in the promoter regions of these genes. In addition to metabolites from TCA cycle, oxidative phosphorylation, and lipid metabolism (known to be associated with T2DM), we identified several reporter metabolites representing novel biomarker candidates. For example, the highly connected metabolites NAD+/NADH and ATP/ADP were also identified as reporter metabolites that are potentially contributing to the widespread gene expression changes observed in T2DM. An algorithm based on the analysis of the promoter regions of the genes associated with reporter metabolites revealed a transcription factor regulatory network connecting several parts of metabolism. The identified transcription factors include members of the CREB, NRF1 and PPAR family, among others, and represent regulatory targets for further experimental analysis. Overall, our results provide a holistic picture of key metabolic and regulatory nodes potentially involved in the pathogenesis of T2DM

Multi-messenger observations of a binary neutron star merger

On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transient’s position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta

Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency-Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research.Peer reviewe

Simulation Study of Aircraft AC Generator with Electrical Fault Insertion

The aim of this paper is to model a typical Aircraft Generator along with its control system and study the behaviour / performance during fault, particularly in the rectifier block which is used in the field circuit and fault in the winding. The study shows that there is no considerable change in the Generator supply characteristic up to a certain extent of fault, but the significant change in the field excitation was observed. The output of the developed model was successfully corroborated with the MIL-STD 704F power supply characteristics

Impact response in glass-epoxy system with and without perforated PTFE-bearing material at the mid-thickness

The work looks at the differences in impact response between plain glass fabric-epoxy and the same system containing PTFE-bearing layer having regular circular perforations inserted at the entire mid-thickness position during fabrication stage of the laminate by the hand lay-up technique. Instrumented impact data showed a drop in maximum load, total energy and ductility index following the insertion. There was a difference in the way the load-time data appeared between the plain and the mid-layer inserted PTFE bearing material cases. The plain ones showed a sharp drop after the peak whereas such a feature was absent for the mid-layer material inserted ones. Also noticed were the changes in the number of steps seen both before and after peak load following the insertion of the PTFE bearing material. These features are analyzed with the help of optical microscopy, which showed a delamination exactly at the PTFE inserted interface region while for the plain, i.e. for the non-mid-layer inserted cases, the separation seemed to occur along the ply that had the poor bonding. These and other features are analyzed in this work

Molecularly Imprinted Polymer

Methyl parathion (MP) is an organophosphate chemical agent. Due to low solubility and bioaccumulation, it results in serious health problems. Electrochemical recognition based on graphitic carbon nitride (CN) incorporated hexagonal boron nitride (HBN) nanosheets and molecularly imprinted polymer (MIP) was presented formethyl parathion (MP) detection. Scanning electron microscopy (SEM), X-ray diffraction (XRD) method, cyclic voltammetry (CV) and electrochemical impedance spectroscopy (EIS) were utilized for characterizations. After that, MP imprinted voltammetric sensor on CN-HBN nanocomposite was carried out in the presence of 100.0 mMpyrrole containing 25.0 mMMP via CV. 1.0 x 10(-12)-2.0 x 10(-9) Mand 2.0 x 10(-13) Mwere found as the linearity range and the detection limit (LOD). Finally, MP imprinted sensor was applied to orange juice samples for MP analysis. (C) 2019 The Electrochemical Society.C1 [Kiran, Tugba Raika; Yola, Mehmet Lutfi] Iskenderun Tech Univ, Fac Engn & Nat Sci, Dept Biomed Engn, Antakya, Turkey.[Atar, Necip] Pamukkale Univ, Fac Engn, Dept Chem Engn, Denizli, Turkey