Amyotrophic lateral sclerosis–specific quality of life–short form (ALSSQOL‐SF): A brief, reliable, and valid version of the ALSSQOL‐R

Introduction: The Amyotrophic Lateral Sclerosis (ALS)‐Specific Quality of Life instrument and its revised version (ALSSQOL and ALSSQOL‐R) have strong psychometric properties, and have demonstrated research and clinical utility. In this study we aimed to develop a short form (ALSSQOL‐SF) suitable for limited clinic time and patient stamina. Methods: The ALSSQOL‐SF was created using Item Response Theory and confirmatory factor analysis on 389 patients. A cross‐validation sample of 162 patients assessed convergent, divergent, and construct validity of the ALSSQOL‐SF compared with psychosocial and physical functioning measures. Results: The ALSSQOL‐SF consisted of 20 items. Compared with the ALSSQOL‐R, optimal precision was retained, and completion time was reduced from 15–25 minutes to 2–4 minutes. Psychometric properties for the ALSSQOL‐SF and its subscales were strong. Discussion: The ALSSQOL‐SF is a disease‐specific global QOL instrument that has a short administration time suitable for clinical use, and can provide clinically useful, valid information about persons with ALS. Muscle Nerve 58: 646–654, 2018Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/146574/1/mus26203_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/146574/2/mus26203.pd

Semantic inference using chemogenomics data for drug discovery

<p>Abstract</p> <p>Background</p> <p>Semantic Web Technology (SWT) makes it possible to integrate and search the large volume of life science datasets in the public domain, as demonstrated by well-known linked data projects such as LODD, Bio2RDF, and Chem2Bio2RDF. Integration of these sets creates large networks of information. We have previously described a tool called WENDI for aggregating information pertaining to new chemical compounds, effectively creating evidence paths relating the compounds to genes, diseases and so on. In this paper we examine the utility of automatically inferring new compound-disease associations (and thus new links in the network) based on semantically marked-up versions of these evidence paths, rule-sets and inference engines.</p> <p>Results</p> <p>Through the implementation of a semantic inference algorithm, rule set, Semantic Web methods (RDF, OWL and SPARQL) and new interfaces, we have created a new tool called Chemogenomic Explorer that uses networks of ontologically annotated RDF statements along with deductive reasoning tools to infer new associations between the query structure and genes and diseases from WENDI results. The tool then permits interactive clustering and filtering of these evidence paths.</p> <p>Conclusions</p> <p>We present a new aggregate approach to inferring links between chemical compounds and diseases using semantic inference. This approach allows multiple evidence paths between compounds and diseases to be identified using a rule-set and semantically annotated data, and for these evidence paths to be clustered to show overall evidence linking the compound to a disease. We believe this is a powerful approach, because it allows compound-disease relationships to be ranked by the amount of evidence supporting them.</p

Resistance of Dynamin-related Protein 1 Oligomers to Disassembly Impairs Mitophagy, Resulting in Myocardial Inflammation and Heart Failure

We have reported previously that a missense mutation in the mitochondrial fission gene Dynamin-related protein 1 (Drp1) underlies the Python mouse model of monogenic dilated cardiomyopathy. The aim of this study was to investigate the consequences of the C452F mutation on Drp1 protein function and to define the cellular sequelae leading to heart failure in the Python monogenic dilated cardiomyopathy model. We found that the C452F mutation increased Drp1 GTPase activity. The mutation also conferred resistance to oligomer disassembly by guanine nucleotides and high ionic strength solutions. In a mouse embryonic fibroblast model, Drp1 C452F cells exhibited abnormal mitochondrial morphology and defective mitophagy. Mitochondria in C452F mouse embryonic fibroblasts were depolarized and had reduced calcium uptake with impaired ATP production by oxidative phosphorylation. In the Python heart, we found a corresponding progressive decline in oxidative phosphorylation with age and activation of sterile inflammation. As a corollary, enhancing autophagy by exposure to a prolonged low-protein diet improved cardiac function in Python mice. In conclusion, failure of Drp1 disassembly impairs mitophagy, leading to a downstream cascade of mitochondrial depolarization, aberrant calcium handling, impaired ATP synthesis, and activation of sterile myocardial inflammation, resulting in heart failure

Epidemiological risk factors for adult dengue in Singapore: an 8-year nested test negative case control study

10.1186/s12879-016-1662-4BMC Infectious Diseases16132

The state of the Martian climate

60°N was +2.0°C, relative to the 1981–2010 average value (Fig. 5.1). This marks a new high for the record. The average annual surface air temperature (SAT) anomaly for 2016 for land stations north of starting in 1900, and is a significant increase over the previous highest value of +1.2°C, which was observed in 2007, 2011, and 2015. Average global annual temperatures also showed record values in 2015 and 2016. Currently, the Arctic is warming at more than twice the rate of lower latitudes

Measurement of the Bottom-Strange Meson Mixing Phase in the Full CDF Data Set

We report a measurement of the bottom-strange meson mixing phase \beta_s using the time evolution of B0_s -> J/\psi (->\mu+\mu-) \phi (-> K+ K-) decays in which the quark-flavor content of the bottom-strange meson is identified at production. This measurement uses the full data set of proton-antiproton collisions at sqrt(s)= 1.96 TeV collected by the Collider Detector experiment at the Fermilab Tevatron, corresponding to 9.6 fb-1 of integrated luminosity. We report confidence regions in the two-dimensional space of \beta_s and the B0_s decay-width difference \Delta\Gamma_s, and measure \beta_s in [-\pi/2, -1.51] U [-0.06, 0.30] U [1.26, \pi/2] at the 68% confidence level, in agreement with the standard model expectation. Assuming the standard model value of \beta_s, we also determine \Delta\Gamma_s = 0.068 +- 0.026 (stat) +- 0.009 (syst) ps-1 and the mean B0_s lifetime, \tau_s = 1.528 +- 0.019 (stat) +- 0.009 (syst) ps, which are consistent and competitive with determinations by other experiments.Comment: 8 pages, 2 figures, Phys. Rev. Lett 109, 171802 (2012

Clinical Features of Dengue in a Large Vietnamese Cohort: Intrinsically Lower Platelet Counts and Greater Risk for Bleeding in Adults than Children

Dengue is a common and potentially serious viral illness. Complications include plasma leakage from small blood vessels causing shock and dysfunction of the systems that control blood clotting, resulting in bleeding. The disease used to affect children predominantly, but in recent years, the number of adult patients has been increasing. As there is limited data describing the patterns of complications by age, we performed this study to compare clinical and laboratory features, management, and outcomes of the disease for over 1,500 children and adults with confirmed dengue recruited at the same time at a single hospital in the Southern Vietnam. We found that plasma leakage and shock were more common and severe in children than adults, while bleeding and organ dysfunction were more frequent in adults. Adults had lower platelet counts throughout the illness course as well as at a follow-up visit several weeks after recovery. Platelets are a crucial element in controlling bleeding, and the intrinsically lower counts in adults compared to children may contribute to the greater risk for bleeding in this patient group. Knowledge about differences in the patterns of dengue-related complications between children and adults should help clinicians to diagnose and treat patients more effectively

Decision Tree Algorithms Predict the Diagnosis and Outcome of Dengue Fever in the Early Phase of Illness

Dengue illness appears similar to other febrile illness, particularly in the early stages of disease. Consequently, diagnosis is often delayed or confused with other illnesses, reducing the effectiveness of using clinical diagnosis for patient care and disease surveillance. To address this shortcoming, we have studied 1,200 patients who presented within 72 hours from onset of fever; 30.3% of these had dengue infection, while the remaining 69.7% had other causes of fever. Using body temperature and the results of simple laboratory tests on blood samples of these patients, we have constructed a decision algorithm that is able to distinguish patients with dengue illness from those with other causes of fever with an accuracy of 84.7%. Another decision algorithm is able to predict which of the dengue patients would go on to develop severe disease, as indicated by an eventual drop in the platelet count to 50,000/mm3 blood or below. Our study shows a proof-of-concept that simple decision algorithms can predict dengue diagnosis and the likelihood of developing severe disease, a finding that could prove useful in the management of dengue patients and to public health efforts in preventing virus transmission

ASIRI : an ocean–atmosphere initiative for Bay of Bengal

Author Posting. © American Meteorological Society, 2016. This article is posted here by permission of American Meteorological Society for personal use, not for redistribution. The definitive version was published in Bulletin of the American Meteorological Society 97 (2016): 1859–1884, doi:10.1175/BAMS-D-14-00197.1.Air–Sea Interactions in the Northern Indian Ocean (ASIRI) is an international research effort (2013–17) aimed at understanding and quantifying coupled atmosphere–ocean dynamics of the Bay of Bengal (BoB) with relevance to Indian Ocean monsoons. Working collaboratively, more than 20 research institutions are acquiring field observations coupled with operational and high-resolution models to address scientific issues that have stymied the monsoon predictability. ASIRI combines new and mature observational technologies to resolve submesoscale to regional-scale currents and hydrophysical fields. These data reveal BoB’s sharp frontal features, submesoscale variability, low-salinity lenses and filaments, and shallow mixed layers, with relatively weak turbulent mixing. Observed physical features include energetic high-frequency internal waves in the southern BoB, energetic mesoscale and submesoscale features including an intrathermocline eddy in the central BoB, and a high-resolution view of the exchange along the periphery of Sri Lanka, which includes the 100-km-wide East India Coastal Current (EICC) carrying low-salinity water out of the BoB and an adjacent, broad northward flow (∼300 km wide) that carries high-salinity water into BoB during the northeast monsoon. Atmospheric boundary layer (ABL) observations during the decaying phase of the Madden–Julian oscillation (MJO) permit the study of multiscale atmospheric processes associated with non-MJO phenomena and their impacts on the marine boundary layer. Underway analyses that integrate observations and numerical simulations shed light on how air–sea interactions control the ABL and upper-ocean processes.This work was sponsored by the U.S. Office of Naval Research (ONR) in an ONR Departmental Research Initiative (DRI), Air–Sea Interactions in Northern Indian Ocean (ASIRI), and in a Naval Research Laboratory project, Effects of Bay of Bengal Freshwater Flux on Indian Ocean Monsoon (EBOB). ASIRI–RAWI was funded under the NASCar DRI of the ONR. The Indian component of the program, Ocean Mixing and Monsoons (OMM), was supported by the Ministry of Earth Sciences of India.2017-04-2