Estimating the Risk of Middle East Respiratory Syndrome (MERS) Death During the Course of the Outbreak in the Republic of Korea

Objectives: A large cluster of the Middle East respiratory syndrome (MERS) linked to healthcare setting occurred from May to July 2015 in the Republic of Korea. The present study aimed to estimate the case fatality ratio (CFR) by appropriately taking into account the time delay from illness onset to death. We then compare our estimate against previously published values of the CFR for MERS, i.e., 20% and 40%. Methods: Dates of illness onset and death of the MERS outbreak in the Republic of Korea were extracted from secondary data sources. Using the known distribution of time from illness onset to death and an integral equation model, we estimated the delay-adjusted risk of MERS death for the South Korean cluster. Results: Our most up-to-date estimate of CFR for the MERS outbreak in South Korea was estimated at 20.0% (95% confidence intervals (CI): 14.6, 26.2). During the course of the outbreak, estimate of the CFR in real time appeared to have decreased and become significantly lower than 40%. Conclusions: The risk of MERS death in Korea was consistent with published CFR. The estimate decreased with time perhaps due to time-dependent increase in case ascertainment. Crude ratio of cumulative deaths t

Real-time Characterization of Risks of Death Associated With the Middle East Respiratory Syndrome (MERS) in the Republic of Korea, 2015

Background: An outbreak of the Middle East respiratory syndrome (MERS), comprising 185 cases linked to healthcare facilities, occurred in the Republic of Korea from May to July 2015. Owing to the nosocomial nature of the outbreak, it is particularly important to gain a better understanding of the epidemiological determinants characterizing the risk of MERS death in order to predict the heterogeneous risk of death in medical settings. Methods: We have devised a novel statistical model that identifies the risk of MERS death during the outbreak in real time. While accounting for the time delay from illness onset to death, risk factors for death were identified using a linear predictor tied to a logit model. We employ this approach to (1) quantify the risks of death and (2) characterize the temporal evolution of the case fatality ratio (CFR) as case ascertainment greatly improved during the course of the outbreak. Results: Senior persons aged 60 years or over were found to be 9.3 times (95 % confidence interval (CI), 5.3–16.9) more likely to die compared to younger MERS cases. Patients under treatment were at a 7.8-fold (95 % CI, 4.0–16.7) significantly higher risk of death compared to other MERS cases. The CFR among patients aged 60 years or older under treatment was estimated at 48.2 % (95 % CI, 35.2–61.3) as of July 31, 2015, while the CFR among other cases was estimated to lie below 15 %. From June 6, 2015, onwards, the CFR declined 0.3-fold (95 % CI, 0.1–1.1) compared to the earlier epidemic period, which may perhaps reflect enhanced case ascertainment following major contact tracing efforts. Conclusions: The risk of MERS death was significantly associated with older age as well as treatment for underlying diseases after explicitly adjusting for the delay between illness onset and death. Because MERS outbreaks are greatly amplified in the healthcare setting, enhanced infection control practices in medical facilities should strive to shield risk groups from MERS exposure

Constructing Machine-learned Interatomic Potentials for Covalent Bonding Materials and MD Analyses of Dislocation and Surface

As machine learning potentials for molecular dynamics (MD) simulations, Spectral Neighbor Analysis Potential (SNAP) and quadratic SNAP (qSNAP) were constructed for silicon (Si) and silicon carbide (SiC). The reproducibility of the basic material properties about perfect crystal, free surface and dislocation cores in Si and 3C-SiC was investigated. The coefficients of SNAP and qSNAP were optimized using liner regression to present energy and force obtained by DFT. In addition, hyperparameters (cutoff length and weights for optimization, here) were determined using genetic algorithm to reproduce elastic moduli obtained by DFT. Lattice constant and elastic moduli of Si crystal by MD using our SNAP or qSNAP agree well with the values of DFT, and they have higher accuracy than those by any empirical potential. Additionally, melting point and specific heat at constant pressure were calculated by MD correctly. Especially in qSNAP of Si, the surface energy of {100} and {111} planes and the reconstructed {100} surface structure were almost reproduced. For 3C-SiC, SNAP reproduces lattice constant and elastic moduli of DFT. Furthermore, edge dislocation cores were generated successfully. However, the potentials we constructed have insufficient reproducibility in the plastic region, so it is necessary to continue development

Atg9a deficiency causes axon-specific lesions including neuronal circuit dysgenesis

Conditional knockout mice for Atg9a, specifically in brain tissue, were generated to understand the roles of ATG9A in the neural tissue cells. The mice were born normally, but half of them died within one wk, and none lived beyond 4 wk of age. SQSTM1/p62 and NBR1, receptor proteins for selective autophagy, together with ubiquitin, accumulated in Atg9a-deficient neurosoma at postnatal d 15 (P15), indicating an inhibition of autophagy, whereas these proteins were significantly decreased at P28, as evidenced by immunohistochemistry, electron microscopy and western blot. Conversely, degenerative changes such as spongiosis of nerve fiber tracts proceeded in axons and their terminals that were occupied with aberrant membrane structures and amorphous materials at P28, although no clear-cut degenerative change was detected in neuronal cell bodies. Different from autophagy, diffusion tensor magnetic resonance imaging and histological observations revealed Atg9a-deficiency-induced dysgenesis of the corpus callosum and anterior commissure. As for the neurite extensions of primary cultured neurons, the neurite outgrowth after 3 d culturing was significantly impaired in primary neurons from atg9a-KO mouse brains, but not in those from atg7-KO and atg16l1-KO brains. Moreover, this tendency was also confirmed in Atg9a-knockdown neurons under an atg7-KO background, indicating the role of ATG9A in the regulation of neurite outgrowth that is independent of autophagy. These results suggest that Atg9a deficiency causes progressive degeneration in the axons and their terminals, but not in neuronal cell bodies, where the degradations of SQSTM1/p62 and NBR1 were insufficiently suppressed. Moreover, the deletion of Atg9a impaired nerve fiber tract formation

Signal-transducing adaptor protein-2 modulates T-cell functions

Immune responses are orchestrated by controlling the initiation, magnitude, and duration of various signaling pathways. Adaptor proteins act as positive or negative regulators by targeting critical molecules of signaling cascades. Signal-transducing adaptor protein-2 (STAP-2) contains typical features of adaptor proteins, like a pleckstrin homology (PH) domain in the N-terminal region and a Src homology 2 (SH2) domain in the central region. STAP-2 binds to a variety of signaling or transcriptional molecules to control multiple steps of inflammatory/immune responses. STAP-2 enhances T-cell receptor (TCR)-mediated signaling via the association with TCR-proximal CD3ζ immunoreceptor tyrosine-based activation motifs (ITAMs) and lymphocyte-specific protein tyrosine kinase (Lck). STAP-2 decreases adherence of T-cells to fibronectin (FN) through an association with focal adhesion kinase (Fak) and Casitas B-lineage Lymphoma (c-Cbl), and increases chemotaxis of T-cells toward stromal cell-derived factor-1α (SDF-1α) through interactions with Vav1 and Ras-related C3 botulinum toxin substrate 1 (Rac1). STAP-2 positively regulates activation-induced cell deathrough the association with Fas and caspase-8. This review describes the current knowledge of the roles of STAP-2 in T-cell-dependent immune responses and the possible clinical utility of STAP-2-targeting therapies