Nonlinear Associations Between Working Hours and Overwork-Related Cerebrovascular and Cardiovascular Diseases (CCVD)

Long working hours are recognized as a risk factor for cerebrovascular and cardiovascular diseases (CCVD). We investigated the relationship between working hours and different CCVD severity outcomes—death, disability, and illness—across industries in Taiwan from 2006 to 2016. We applied a generalized additive mixed model to estimate the association between working hours and the rate of each severity outcome, adjusted for salary, unemployment rate, time, and a random intercept. Industry-average working hours were significantly associated with each outcome level of overwork-related CCVD, especially when monthly working hours increased from 169 (relative risk [RR] = 1.46, 95% confidence interval [CI] 1.002–2.12) to 187 (RR = 5.73, 95% CI 3.61–9.08). Although RR trends declined after monthly working hours exceeded 187, excess risks remained statistically significant. Each 1-hour increase in working hours had a stronger effect on the RR increase in death and disability than on illness. Variations in CCVD risks existed across industries, with the highest risk in transportation and information. Reducing working hours is essential to preventing overwork-related CCVD, especially the more severe outcomes. We recommend further research to address possible underreporting of less severe cases, and to explore actions to narrow the gaps in risk across industries

Political and social determinants of life expectancy in less developed countries: A longitudinal study

EstE livro corrEspondE à primeira experiência didática do Grupo de trabalho desenvolvimento Urbano do conselho latinoamericano de ciências sociais (clAcso), que reúne cerca de quarenta pesquisadores de diferentes instituições da região. Esta experiência tornou-se possível, graças ao fato da proposta deste curso ter sido aprovada no âmbito da cátedra Florestan Fernandes do conselho. completamente desenvolvida através do campus virtual do clAcso, teve, por principal objetivo, estimular a reflexão sobre alguns dos principais eixos teórico-conceituais e empíricos orientadores da análise da urbanização latino-americana

Loss of vesicular dopamine release precedes tauopathy in degenerative dopaminergic neurons in a Drosophila model expressing human tau.

While a number of genome-wide association studies have identified microtubule-associated protein tau as a strong risk factor for Parkinson's disease (PD), little is known about the mechanism through which human tau can predispose an individual to this disease. Here, we demonstrate that expression of human wild-type tau is sufficient to disrupt the survival of dopaminergic neurons in a Drosophila model. Tau triggers a synaptic pathology visualized by vesicular monoamine transporter-pHGFP that precedes both the age-dependent formation of tau-containing neurofibrillary tangle-like pathology and the progressive loss of DA neurons, thereby recapitulating the pathological hallmarks of PD. Flies overexpressing tau also exhibit progressive impairments of both motor and learning behaviors. Surprisingly, contrary to common belief that hyperphosphorylated tau could aggravate toxicity, DA neuron degeneration is alleviated by expressing the modified, hyperphosphorylated tau(E14). Together, these results show that impairment of VMAT-containing synaptic vesicle, released to synapses before overt tauopathy may be the underlying mechanism of tau-associated PD and suggest that correction or prevention of this deficit may be appropriate targets for early therapeutic intervention

Distributed Training Large-Scale Deep Architectures

Scale of data and scale of computation infrastructures together enable the current deep learning renaissance. However, training large-scale deep architectures demands both algorithmic improvement and careful system configuration. In this paper, we focus on employing the system approach to speed up large-scale training. Via lessons learned from our routine benchmarking effort, we first identify bottlenecks and overheads that hinter data parallelism. We then devise guidelines that help practitioners to configure an effective system and fine-tune parameters to achieve desired speedup. Specifically, we develop a procedure for setting minibatch size and choosing computation algorithms. We also derive lemmas for determining the quantity of key components such as the number of GPUs and parameter servers. Experiments and examples show that these guidelines help effectively speed up large-scale deep learning training

KCNN2 polymorphisms and cardiac tachyarrhythmias

Potassium calcium-activated channel subfamily N member 2 (KCNN2) encodes an integral membrane protein that forms small-conductance calcium-activated potassium (SK) channels. Recent studies in animal models show that SK channels are important in atrial and ventricular repolarization and arrhythmogenesis. However, the importance of SK channels in human arrhythmia remains unclear. The purpose of the present study was to test the association between genetic polymorphism of the SK2 channel and the occurrence of cardiac tachyarrhythmias in humans. We enrolled 327 Han Chinese, including 72 with clinically significant ventricular tachyarrhythmias (VTa) who had a history of aborted sudden cardiac death (SCD) or unexplained syncope, 98 with a history of atrial fibrillation (AF), and 144 normal controls. We genotyped 12 representative tag single nucleotide polymorphisms (SNPs) across a 141-kb genetic region containing the KCNN2 gene; these captured the full haplotype information. The rs13184658 and rs10076582 variants of KCNN2 were associated with VTa in both the additive and dominant models (odds ratio [OR] 2.89, 95% confidence interval [CI] = 1.505-5.545, P = 0.001; and OR 2.55, 95% CI = 1.428-4.566, P = 0.002, respectively). After adjustment for potential risk factors, the association remained significant. The population attributable risks of these 2 variants of VTa were 17.3% and 10.6%, respectively. One variant (rs13184658) showed weak but significant association with AF in a dominant model (OR 1.91, CI = 1.025-3.570], P = 0.042). There was a significant association between the KCNN2 variants and clinically significant VTa. These findings suggest an association between KCNN2 and VTa; it also appears that KCNN2 variants may be adjunctive markers for risk stratification in patients susceptible to SCD

Enhancing Sustainable Urban Mobility Prediction with Telecom Data: A Spatio-Temporal Framework Approach

Traditional traffic prediction, limited by the scope of sensor data, falls short in comprehensive traffic management. Mobile networks offer a promising alternative using network activity counts, but these lack crucial directionality. Thus, we present the TeltoMob dataset, featuring undirected telecom counts and corresponding directional flows, to predict directional mobility flows on roadways. To address this, we propose a two-stage spatio-temporal graph neural network (STGNN) framework. The first stage uses a pre-trained STGNN to process telecom data, while the second stage integrates directional and geographic insights for accurate prediction. Our experiments demonstrate the framework's compatibility with various STGNN models and confirm its effectiveness. We also show how to incorporate the framework into real-world transportation systems, enhancing sustainable urban mobility.Comment: 8 Figures, 5 Tables. Just accepted by IJCAI (to appear

TelTrans: Applying Multi-Type Telecom Data to Transportation Evaluation and Prediction via Multifaceted Graph Modeling

To address the limitations of traffic prediction from location-bound detectors, we present Geographical Cellular Traffic (GCT) flow, a novel data source that leverages the extensive coverage of cellular traffic to capture mobility patterns. Our extensive analysis validates its potential for transportation. Focusing on vehicle-related GCT flow prediction, we propose a graph neural network that integrates multivariate, temporal, and spatial facets for improved accuracy. Experiments reveal our model's superiority over baselines, especially in long-term predictions. We also highlight the potential for GCT flow integration into transportation systems.Comment: 7 pages, 7 figures, 4 tables. Accepted by AAAI-24-IAAI, to appea

THE RELATIONSHIPS BETWEEN THE FUNCTIONAL MOVEMENT SCREEN AND THE POSTURAL STABILITY IN COLLEGIATE ATHLETES

The Functional Movement Screen (FMS) is a tool developed recently not only to aid in the prevention of injury by objectively measuring dysfunction and asymmetries within movement patterns, but also could be used as a baseline for further strength, conditioning, or athletic development. The purpose of this study was to examine the relationships between the scores of FMS in relation to the postural stability (PS) in collegiate athletes. A total of 30 male, basketball athletes volunteered to join this study. The PS were measured by the Biodex Balance System as the displacements of the center of foot pressure (COP) in the limits of stability. The score of FMS were evaluated by one certified professional experts. The results showed that the score of FMS has relation to the performance of the PS in a certain extent, especially in the FMS-shoulder mobility to the LOS overall level 6 (r=.26-.41), in the FMS-active straight leg raise to the LOS forward, backward, right, right-back level 6 (r=.30-.39), and in the FMS-trunk stability push-up to the LOS right, back, and right-forward. It was concluded that the score of FMS might be used to evaluate and/or predict the performance of the PS in young, collegiate athletes

Prokaryotic assemblages and metagenomes in pelagic zones of the South China Sea

BACKGROUND: Prokaryotic microbes, the most abundant organisms in the ocean, are remarkably diverse. Despite numerous studies of marine prokaryotes, the zonation of their communities in pelagic zones has been poorly delineated. By exploiting the persistent stratification of the South China Sea (SCS), we performed a 2-year, large spatial scale (10, 100, 1000, and 3000 m) survey, which included a pilot study in 2006 and comprehensive sampling in 2007, to investigate the biological zonation of bacteria and archaea using 16S rRNA tag and shotgun metagenome sequencing. RESULTS: Alphaproteobacteria dominated the bacterial community in the surface SCS, where the abundance of Betaproteobacteria was seemingly associated with climatic activity. Gammaproteobacteria thrived in the deep SCS, where a noticeable amount of Cyanobacteria were also detected. Marine Groups II and III Euryarchaeota were predominant in the archaeal communities in the surface and deep SCS, respectively. Bacterial diversity was higher than archaeal diversity at all sampling depths in the SCS, and peaked at mid-depths, agreeing with the diversity pattern found in global water columns. Metagenomic analysis not only showed differential %GC values and genome sizes between the surface and deep SCS, but also demonstrated depth-dependent metabolic potentials, such as cobalamin biosynthesis at 10 m, osmoregulation at 100 m, signal transduction at 1000 m, and plasmid and phage replication at 3000 m. When compared with other oceans, urease at 10 m and both exonuclease and permease at 3000 m were more abundant in the SCS. Finally, enriched genes associated with nutrient assimilation in the sea surface and transposase in the deep-sea metagenomes exemplified the functional zonation in global oceans. CONCLUSIONS: Prokaryotic communities in the SCS stratified with depth, with maximal bacterial diversity at mid-depth, in accordance with global water columns. The SCS had functional zonation among depths and endemically enriched metabolic potentials at the study site, in contrast to other oceans. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/s12864-015-1434-3) contains supplementary material, which is available to authorized users