Mendelian randomization evidence for the causal effects of socio-economic inequality on human longevity among Europeans.

Human longevity correlates with socio-economic status, and there is evidence that educational attainment increases human lifespan. However, to inform meaningful health policies, we need fine-grained causal evidence on which dimensions of socio-economic status affect longevity and the mediating roles of modifiable factors such as lifestyle and disease. Here we performed two-sample Mendelian randomization analyses applying genetic instruments of education, income and occupation (n = 248,847 to 1,131,881) to estimate their causal effects and consequences on parental lifespan and self-longevity (n = 28,967 to 1,012,240) from the largest available genome-wide association studies in populations of European ancestry. Each 4.20 years of additional educational attainment were causally associated with a 3.23-year-longer parental lifespan independently of income and occupation and were causally associated with 30-59% higher odds of self-longevity, suggesting that education was the primary determinant. By contrast, each one-standard-deviation-higher income and one-point-higher occupation was causally associated with 3.06-year-longer and 1.29-year-longer parental lifespans, respectively, but not independently of the other socio-economic indicators. We found no evidence for causal effects of income or occupation on self-longevity. Mediation analyses conducted in predominantly European-descent individuals through two-step Mendelian randomization suggested that among 59 candidates, cigarettes per day, body mass index, waist-to-hip ratio, hypertension, coronary heart disease, myocardial infarction, stroke, Alzheimer's disease, type 2 diabetes, heart failure and lung cancer individually played substantial mediating roles (proportion mediated, >10%) in the effect of education on specific longevity outcomes. These findings inform interventions for remediating longevity disparities attributable to socio-economic inequality.

Cysteine supplementation enhanced inhibitor tolerance of Zymomonas mobilis for economic lignocellulosic bioethanol production.

Inhibitors in lignocellulosic hydrolysates are toxic to Zymomonas mobilis and reduce its bioethanol production. This study revealed cysteine supplementation enhanced furfural tolerance in Z. mobilis with a 2-fold biomass increase. Transcriptomic study illustrated that cysteine biosynthesis pathway was down-regulated while cysteine catabolism was up-regulated with cysteine supplementation. Mutants for genes involved in cysteine metabolism were constructed, and metabolites in cysteine metabolic pathway including methionine, glutathione, NaHS, glutamate, and pyruvate were supplemented into media. Cysteine supplementation boosted glutathione synthesis or H2S release effectively in Z. mobilis leading to the reduced accumulation of reactive oxygen species (ROS) induced by furfural, while pyruvate and glutamate produced in the H2S generation pathway promoted cell growth by serving as the carbon or nitrogen source. Finally, cysteine supplementation was confirmed to enhance Z. mobilis tolerance against ethanol, acetate, and corncob hydrolysate with an enhanced ethanol productivity from 0.38 to 0.55 g-1∙L-1∙h-1.

A Novel Fire Risk Assessment Approach for Large-Scale Commercial and High-Rise Buildings Based on Fuzzy Analytic Hierarchy Process (FAHP) and Coupling Revision.

In recent years, much more emphasis than before has been placed on fire safety regulations by the local and central authorities of China, which makes fire risk assessments more important. In this paper we propose a new fire risk assessment approach for large-scale commercial and high-rise buildings that aims to evaluate the performances of their fire safety systems; this should improve the fire risk management and public safety in those buildings. According to the features of large-scale commercial and high-rise buildings, a fire-risk indexing system was built, and based on it we established a scientific fire risk evaluation system. To this end, the fuzzy analytic hierarchy process (FAHP) was used to assign a reasonable weight to each fire risk factor in the evaluation system. In addition, we revised the original scores by analyzing the coupling relationships among the fire risk factors. To validate our system, we selected 11 buildings in Shandong province and collected their fire safety data. Then, we calculated the final scores for the fire safety management of those buildings, and the results show that: (1) our fire risk evaluation system can assign reasonable weights; (2) the proposed evaluation system is comprehensive and has strong interpretability, since it exploits the coupling relationships among the risk factors. The novelty of the proposed approach lies in that it integrates opinions from multiple experts and utilizes coupling relationships among the factors. Further, the feedback from the approach can find not only the weaknesses in fire risk management, but also the potential causes of fires. As a result, the feedback from our assessment can assist the safety chiefs and inspectors with improving fire risk management.

Towards accurate and interpretable surgical skill assessment: a video-based method for skill score prediction and guiding feedback generation.

PURPOSE: Recently, automatic surgical skill assessment has received the attention given the increasingly important role of surgical training. The assessment usually involves skill score prediction and further feedback generation. Existing work on skill score prediction is limited with several challenges and deserves more promising outcomes. For the feedback, most work identifies the flaws on the granularity of video frames or clips. It thus remains to be explored how to identify poorly performed gestures (segments) and further how to provide good references for improvement. METHODS: To overcome these problems, a novel method consisting of three correlated frameworks is proposed. The first framework learns to predict final skill scores of surgical trials with two auxiliary tasks. The second framework learns to predict running intermediate skill scores that indicate the problematic gestures, while the third framework explores the optimal gesture sequences as references through a new Policy Gradient based formulation. RESULTS: Our method is experimented on JIGSAWS dataset. The first framework pushes state-of-the-art prediction performance further to 0.83, 0.86 and 0.69 Spearman's correlations for the three surgical tasks under LOUO validation scheme. Moreover, the intermediate scores predicted by the second framework are better in accord with the experts'. Besides, the generated gesture sequences in the third framework reflect the optimality of the gesture flow. CONCLUSION: In summary, multi-task learning with semantic visual features successfully boosts the performance of skill score prediction, while exploring gesture-level annotations and score elements of the final skill score is useful for generating more interpretable feedback. Our presented method potentially contributes towards a complete loop of automated surgical training.

Systematic network assessment of the carcinogenic activities of cadmium.

Cadmium has been defined as type I carcinogen for humans, but the underlying mechanisms of its carcinogenic activity and its influence on protein-protein interactions in cells are not fully elucidated. The aim of the current study was to evaluate, systematically, the carcinogenic activity of cadmium with systems biology approaches. From a literature search of 209 studies that performed with cellular models, 208 proteins influenced by cadmium exposure were identified. All of these were assessed by Western blotting and were recognized as key nodes in network analyses. The protein-protein functional interaction networks were constructed with NetBox software and visualized with Cytoscape software. These cadmium-rewired genes were used to construct a scale-free, highly connected biological protein interaction network with 850 nodes and 8770 edges. Of the network, nine key modules were identified and 60 key signaling pathways, including the estrogen, RAS, PI3K-Akt, NF-κB, HIF-1α, Jak-STAT, and TGF-ß signaling pathways, were significantly enriched. With breast cancer, colorectal and prostate cancer cellular models, we validated the key node genes in the network that had been previously reported or inferred form the network by Western blotting methods, including STAT3, JNK, p38, SMAD2/3, P65, AKT1, and HIF-1α. These results suggested the established network was robust and provided a systematic view of the carcinogenic activities of cadmium in human.