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Background Oxidative Balance Scores (OBS) is composite measures that assess the balance between pro-oxidant and antioxidant factors in an individual’s diet and lifestyle. Evidence on OBS and cardiovascular disease (CVD) in diabetic patients is scarce. This study investigates the potential association between OBS and CVD-prevalence and all-cause and CVD-related mortality in adult diabetic patients. Methods Participants were selected from the National Health and Nutrition Examination Survey (NHANES) 2007–2018. OBS-related data collection was initiated by linking the National Death Index to determine mortality due to all-cause and cardiovascular disease until December 31, 2019. Weighted logistic regression analyses explored the relationship between OBS and CVD. In addition, multivariable Cox proportional risk regression models and Kaplan–Meier curves were used to determine the correlation between OBS and mortality, with time to event as the time variable, as well as to estimate hazard ratios (HR) and 95% confidence interval (CI). Results A total of 3491 participants were included in the final analysis. Weighted logistic regression analysis of the relationship between OBS and CVD prevalence found that higher OBS was not associated with CVD prevalence compared with lower levels after fully adjustment in model 3 (OR: 0.82, 95% CI: 0.51–1.31, P  = 0.39). During 3,491 person-years of follow-up, 408 deaths were recorded, of which 105 deaths were attributed to CVD. In fully adjusted model 3, participants in the highest quartile of OBS had significant reductions in all-cause mortality of 53% [HR: 0.47, 95% CI: 0.29–0.77), P trend = 0.002] and in cardiovascular disease mortality of 78% [HR: 0.22, 95% CI: 0.08–0.56), P trend = 0.004], compared with the lowest quartile groups of OBS. The Kaplan–Meier analysis results showed that participants in the highest quartile of OBS had the lowest risk of all-cause and CVD-related mortality and were statistically different ( P  < 0.05). Subgroup analysis confirmed that P for interaction was significant only concerning the educational level attained and in individuals with a history of CKD ( P  < 0.05). Conclusions Although OBS wasn’t very useful for assessing CVD prevalence outcomes, higher OBS was significantly associated with lower all-cause and CVD-related mortality, suggesting that maintaining adequate OBS may reduce mortality in patients with DM. Graphical Abstract

Streptococcus iniae is a fish pathogenic bacterium distributed worldwide. It has a wide range of hosts, strong infectivity, causes high mortality, and severely hinders the healthy development of the aquaculture industry. A fish epidemic broke out in a Selenotoca multifasciata aquaculture farm, Hainan Province, China, and resulted in numerous deaths. Sick fish showed symptoms including erratic swimming, skin darkening with generalized hemorrhages, and internal organ and brain hemorrhages. A dominant strain, SI03, isolated from the brain of a dying S. multifasciata, exhibited high virulence, and was identified as serotype I γ‐hemolytic S. iniae. Subsequently, virulence gene mRNA expression, infection kinetics, as well as the histopathology in S. multifasciata infected with SI03 were analyzed. Results showed that the mRNA expression levels of scpI, simA, pdi, pgmA, and cfi genes in γ‐hemolytic S. iniae SI03 were significantly higher than those in β‐hemolytic S. iniae ATCC 29178. These genes are associated with adhesion, invasion, and immune evasion. While the mRNA expressions of sagA‐sagI genes, which are associated with the streptolysin S, were significantly lower than those of β‐hemolytic S. iniae ATCC 29178. After being challenged with SI03, the number of bacteria in all the tested fish tissues increased significantly in 24 h. The challenged fish showed symptoms similar to those of the fish from which SI03 was originally isolated. It appears that S. iniae SI03 may have developed a compensatory pathogenic mechanism for hemolysis deficiency. This mechanism enhances its adhesion, invasion, proliferation, and immune evasion abilities. The results of this research provide a reference basis for the prevention and control of S. iniae.

Background Home garden is identified as a kind of small-scale land-use system which is used to manage and cultivate useful plants by local people, and home gardens can provide various plant products and services. Investigating home gardens was regarded as an effective way to understand the biodiversity-related local knowledge and culture of native people in Ethnobiology and Ethnoecology. Home garden is important in less developed and remote areas. The grand canyon of Yarlung Tsangpo is designed as one of the biodiversity hotspots of China, and it is one of the most remote regions of China, because of the rough traffic conditions. The aim of the present study is to collect, record, and document the plants and their local knowledge and functions in the local home gardens, then attempt to answer the question: “why local people selected these plants?” Material and methods The study area was in Beibeng Township of Motuo County in the grand canyon of Yarlung Tsangpo. Observation and semi-structure interviews with informed consent were used to collect data in field study. All information was collected and organized, then documented based on “ethno-species” as a fundamental unit. All of the information of local use and knowledge were organized as the list of “use-report” for quantitative analysis, and the local uses of plants were merged into 14 use categories. Frequency of citation (FC), relative frequency of citation (RFC), cultural importance index (CI), and cultural value index (CV) were used in quantitative analysis. Besides, the Jaccard Index was used to compare the similarity in plant species selection among different communities. Results A total of 78 home gardens in the 9 communities of Beibeng Township were visited, and 196 ethno-species were collected. These ethno-species were identified into 188 Botanical taxa. A total of 87 home garden owners as informants were interviewed in the present study, and they provided 625 use-reports to us. The top 5 important plants were Su-lan-tsao ( Dendrobium nobile ), Sa-ga ( Zingiber officinale ), Soe-lu ( Capsicum annuum ), Snying-pa ( Citrus medica ), and Kham-pu ( Prunus persica ), according to the quantitative analysis. The most citied use-category was “vegetable,” followed by “ornamental plant,” “medicine,” and “fruit.” The altitude might be the most important impact factor of the plant diversity and composition of home gardens, and the traffic conditions, local terrain, also impact the plant diversity and composition of home gardens. Conclusion In remote areas such as the Yarlung Tsangpo Grand Canyon, the plants in home gardens are important sources of plant products such as foods, herbal medicines, and fibers to support daily lives. The local home gardens in Tsang-la communities had high diversity of plants, and these plants provided many functions and services to support daily lives of local people. Local plant knowledge, including the features, life forms, habits, habitats, and use values of plants, were the summary of the understanding of local people to their surrounding plant worlds. Local people selected appropriate plants to cultivate and manage in their home gardens under the guidance of the local plant knowledge. That is the answer to the question “why local people selected these plants?”

The solidification structure of Ti-6Al-4V round ingot during the electron beam cold hearth melting (EBCHM) directly determines the quality of the ingot and the performance of the subsequent rolled coil. In this paper, the Cellular Automaton Finite Element (CAFE) method is used to numerically simulate the solidification structure of Ti-6Al-4V ingot. Firstly, the mathematical model is established with a numerical solution. Secondly, effects of process parameters including the pouring temperature and pulling speed on the solidification structure are revealed. The results show that the microstructures predicted by the numerical method match the experimental results. For the case of fixed pulling speed, a reduction in the pouring temperature leads to the grain refinement and the decreased volatilization of Al. With an increase of the pulling speed, the number of grains first increases and then decreases, but the average grain size first decreases and then increases. Furthermore, the maximum grain size monotonically increases with increasing the pulling speed. Thus, the fine solidified structure with fine grains can be obtained at the pouring temperature of 1700 °C and the pulling speed of 4 × 10 −4 m s −1 .

The phase field model is established for the eutectic growth system in this paper, and the finite difference method is used to solve the model. The evolution of tilted eutectic interface morphology under isothermal solidification and directional solidification conditions, respectively, was investigated. The effects of solid-solid interface anisotropy, solid-liquid interface anisotropy, eutectic spacing and pulling speed on the evolution of the tilted eutectic structure were simulated to reveal the growth mechanism of the tilted eutectic structure. It is found that under isotropic and directional solidification conditions, eutectic growth is influenced by both of the direction of heat flow and the solid-liquid interface anisotropy. When the solid-solid interface anisotropy is small, the direction of heat flow dominates the growth direction of eutectic structure, and as the solid-solid interface anisotropy increases, the growth direction of eutectic structure starts to tilt. Two kinds of instability phenomena, bifurcation or merger and fault line, are also found in the eutectic growth.

The purpose of this work is, based on CAFE method, to study the microstructure evolution and optimize the quality of the large-scale titanium slab ingot during EBCHM. The nucleation parameters of the microstructure simulation of titanium ingot are determined based on one of the actual experimental results. For the determined parameters, our theoretical results are agreement with other experimental results. The effects of pouring temperature and pulling speed on the microstructure are presented based on CAFE method. The quantitative analyses of the simulated results show that with the pulling speed increasing, the number of grains decreases, whereas the mean grain radius increases under identical thermal condition; with the pouring temperature increasing, the mean grain radius increases under the given pulling speed. Our results are very important to obtain the optimal structure of the ingots by controlling pulling speed and pouring temperature.

A numerical and experimental investigation is performed into the flow characteristics and mixing performance of three microfluidic polydimethylsiloxane blood plasma mixing devices incorporating square-wave, curved and zigzag microchannels, respectively. For each device, the plasma is introduced into the microfluidic channel under the effects of capillary action alone. Of the three devices, that with the square-wave microchannel is found to yield the best mixing performance, and is therefore selected for design optimization. Four microfluidic micromixers incorporating square-wave microchannels with different widths in the x- and y-directions are fabricated using conventional photolithography techniques. The mixing performance of the four microchannels is investigated both numerically and experimentally. The results show that given an appropriate specification of the microchannel geometry, a mixing efficiency of approximately 76 % can be obtained within 4 s. The practical feasibility of the micromixer is demonstrated by performing prothrombin time (PT) tests using a total liquid volume of 4.0 μL (2.0 μL of plasma and 2.0 μL of PT reagent). It is shown that the mean time required to complete the entire PT test (including loading, mixing and coagulation) is less than 30 s.

In the study, the functional recovery and relative comprehensive quality of life of cases of global brachial plexus treated with free functioning muscle transfers were investigated. Patients who received functioning gracilis muscle transfer between August 1999 and October 2014 to reconstruct elbow flexion, wrist and fingers extension were recruited. The mean age of the patients was 26.36 (range, 16–42) years. The mean period of time from gracilis transfer to the last follow-up was 54.5 months (range, 12–185 months). Muscle power, active range of motion of the elbow flexion, wrist extension and total active fingers extension were recorded. SDS, SAS and DASH questionnaires were given to estimate patients’ quality of life. 35.71% reported good elbow flexion and 50.00% reported excellent elbow flexion. The average ROM of the elbow flexion was 106.5° (range, 0–142°) and was 17.00° (range, 0–72°) for wrist extension. The average DASH score was 51.14 (range, 17.5–90.8). The prevalence of anxiety and depression were 42.86% and 45.24%. Thrombosis and bowstringing were the most common short and long-term complications. Based on these findings, free gracilis transfer using accessory nerve as donor nerve is a satisfactory treatment to reconstruct the elbow flexion and wrist extension in global-brachial-plexus-injured patients.

The ship-sway is a non-stationary time series while ship sailing in the sea , when using the traditional orthogonal polynomial fitting,index filtering or Kalman filtering to predict ship-sway, the prediction error may be large, because the model parameters are fixed and cannot be adjusted in real time according to the measured data. Multi-level recursive method treats the dynamic system as a time-varying parameters of the system, and can be more in line with the objective reality of rocking the ship. After analyzing the characteristics of the ship-sway, the predict model established by multi-level recursive has been built and test results showed that this model can improve the prediction accuracy of the ship-sway data, and has some practical value in the prediction of the ship-sway.

In this investigation, three-class classification models of aqueous solubility (logS) and lipophilicity (logP) have been developed by using a support vector machine (SVM) method combined with a genetic algorithm (GA) for feature selection and a conjugate gradient method (CG) for parameter optimization. A 5-fold cross-validation and an independent test set method were used to evaluate the SVM classification models. For logS, the overall prediction accuracy is 87.1% for training set and 90.0% for test set. For logP, the overall prediction accuracy is 81.0% for training set and 82.0% for test set. In general, for both logS and logP, the prediction accuracies of three-class models are slightly lower by several percent than those of two-class models. A comparison between the performance of GA–CG–SVM models and that of GA–SVM models shows that the SVM parameter optimization has a significant impact on the quality of SVM classification model.