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Superoxide dismutase (SOD) is a class of enzymes that restrict the biological oxidant cluster enzyme system in the body, which can effectively respond to cellular oxidative stress, lipid metabolism, inflammation, and oxidation. Published studies have shown that SOD enzymes (SODs) could maintain a dynamic balance between the production and scavenging of biological oxidants in the body and prevent the toxic effects of free radicals, and have been shown to be effective in anti-tumor, anti-radiation, and anti-aging studies. This research summarizes the types, biological functions, and regulatory mechanisms of SODs, as well as their applications in medicine, food production, and cosmetic production. SODs have proven to be a useful tool in fighting disease, and mimetics and conjugates that report SODs have been developed successively to improve the effectiveness of SODs. There are still obstacles to solving the membrane permeability of SODs and the persistence of enzyme action, which is still a hot spot and difficulty in mining the effect of SODs and promoting their application in the future.

Ferulic acid is a ubiquitous ingredient in cereals, vegetables, fruits and Chinese herbal medicines. Due to the ferulic phenolic nucleus coupled to an extended side chain, it readily forms a resonant-stable phenoxy radical, which explains its potent antioxidant potential. In addition, it also plays an important role in anti-cancer, pro-angiogenesis, anti-thrombosis, neuroprotection, food preservation, anti-aging, and improving the antioxidant performance of livestock and poultry. This review provides a comprehensive summary of the structure, mechanism of antioxidation, application status, molecular mechanism of pharmacological activity, existing problems, and application prospects of ferulic acid and its derivatives. The aim is to establish a theoretical foundation for the utilization of ferulic acid in medicine, food, cosmetics, livestock, and poultry.

Venous blood collection is a widely used medical diagnostic technique, and with rapid advancements in robotics, robotic venous blood collection has the potential to replace traditional manual methods. The success of this robotic approach is heavily dependent on the quality of vein imaging. In this paper, we develop a vein imaging device based on the simulation analysis of vein imaging parameters and propose a U-Net+ResNet18 neural network for vein image segmentation. The U-Net+ResNet18 neural network integrates the residual blocks from ResNet18 into the encoder of the U-Net to form a new neural network. ResNet18 is pre-trained using the Bootstrap Your Own Latent (BYOL) framework, and its encoder parameters are transferred to the U-Net+ResNet18 neural network, enhancing the segmentation performance of vein images with limited labelled data. Furthermore, we optimize the AD-Census stereo matching algorithm by developing a variable-weight version, which improves its adaptability to image variations across different regions. Results show that, compared to U-Net, the BYOL+U-Net+ResNet18 method achieves an 8.31% reduction in Binary Cross-Entropy (BCE), a 5.50% reduction in Hausdorff Distance (HD), a 15.95% increase in Intersection over Union (IoU), and a 9.20% increase in the Dice coefficient (Dice), indicating improved image segmentation quality. The average error of the optimized AD-Census stereo matching algorithm is reduced by 25.69%, and the improvement of the image stereo matching performance is more obvious. Future research will explore the application of the vein imaging system in robotic venous blood collection to facilitate real-time puncture guidance.

Background Sleep disordered breathing (SDB) plays a significant role in both sleep quality and cognition and whether it has an impact on the relationship between above two factors remains to be clear. The study aimed to explore the association between sleep quality and cognitive performance in general population by considering influence of sleep disordered breathing (SDB). Methods In this cross-sectional study, we enrolled subjects aged ≥ 18 years using a multi-stage random sampling method. Cognitive status was assessed using Mini Mental State Examination (MMSE) questionnaire, sleep quality using Pittsburgh Sleep Quality Index (PSQI) and SDB was assessed using No-SAS scale, respectively. Multi-variable logistic regression was applied to examine the association of sleep quality and cognitive performance. Subgroup analyses were performed in different age groups, and in those with and without SDB. Results Finally, 30,872 participants aged 47.5 ± 13.8 years with 53.5% women were enrolled, of whom 32.4% had poor sleep quality and 18.6% had low cognitive performance. Compared with good sleepers, subjects with poor sleep quality exhibited significantly higher presence of low cognitive performance (23.7% vs 16.2%, P < 0.001). Poor sleepers revealed 1.26 (95%CI: 1.16,1.36), 1.26 (1.08,1.46) and 1.25 (1.14,1.37) fold odds for low cognitive performance in general population and in subjects with and without self-reported SDB respectively. Stratified by age and SDB, the association was observed in young and middle-aged group without SDB (OR = 1.44, 95%CI: 1.30,1.59) and in the elderly group with SDB (OR = 1.30, 95%CI: 1.07,1.58). Conclusions Sleep quality is in a negative association with cognitive performance in general population independent of SDB, implying improvement of sleep disturbances is a potential objective of intervention strategies for cognitive protection at population level.

To investigate the effects of fermented Chinese herbal medicine on growth performance, diarrhea rate, nutrient digestibility, and intestinal health of weaned piglets, and to provide the theoretical basis for applying fermented Chinese herbal medicines to weaned piglet production, a total of 162 weaned and castrated piglets at 25 days of age (Duroc × Landrace × Yorkshire, half male and half female) with an initial body weight of 7.77 ± 0.03 kg were randomly divided into the following three groups according to the principle of similar body weight: basal diet (CON) group, basal diet + 3 kg/t fermented Chinese herbal medicine (LFHM) group, and basal diet + 5 g/kg fermented Chinese herbal medicine (HFHM) group. Each group underwent six replicates and there were nine piglets in each replicate. The experiment lasted 24 days, i.e., 3 days for preliminary feeding, and 21 days for the experiment. From Day 1 of the experiment, the piglets were observed and recorded for diarrhea each day. As compared with the CON group, the results indicated: Following the addition of fermented Chinese herbal medicine, the piglets in the LFHM and HFHM groups increased final weight (FW); average daily feed intake (ADFI); average daily gain (ADG) (p < 0.01); apparent digestibility of crude protein (CP) (p < 0.05); as well as chymotrypsin, α-amylase, and lipase activities (p < 0.01). In addition, α-amylase activity in the LFHM group was higher than that in the HFHM group (p < 0.05); chymotrypsin activity in the LFHM group was lower than that in the HFHM group (p < 0.05); as compared with the CON group, the LFHM and the HFHM increased villus height (VH) and crypt depth (CD) in piglet jejunum; isovaleric acid concentration with the HFHM was higher than those with the CON and the LFHM (p < 0.05), but butyrate concentration with the HFFM was lower than those with the CON and the LFHM (p < 0.05). The high-throughput 16S rRNA sequencing of intestinal microbiota results showed that the LFHM and the HFHM affected the microbial α diversity index in weaned piglet colon (p < 0.01). In conclusion, fermented Chinese herbs can improve the growth performance of weaned piglets by promoting the secretion of intestinal digestive enzymes, changing intestinal microbial diversity, regulating the contents of intestinal short chain fatty acids (SCFAs), promoting intestinal health, and improving nutrients digestibility.

In order to predict the regular temperature change in tuna during the freezing process for cold chain transportation, improve the quality of frozen tuna, and reduce the energy consumption of freezing equipment, a three-dimensional numerical model for freezing tuna of different sizes was established. An unsteady numerical simulation of the air velocity and flow field was combined with an analysis of the freezing process of tuna. This paper also studied the effect of air velocity, temperature, and tuna size on the freezing process. The numerical results show that there was a positive correlation between the cold source environment and the tuna-freezing process. Lower temperatures and higher air increased the velocity at which the tuna moved through the maximum ice crystal formation zone, maintaining a better aquatic product quality. In some cases, however, the smaller tuna models achieved a longer freezing time. Due to the difficulty of obtaining the whole tuna sample, the temperature curve and freezing rate over time obtained during the freezing process were tested using a tuna block of a specific size. The maximum error did not exceed 6.67%, verifying the authenticity and feasibility of the simulation.

The cable-driven snake arm maintainer (SAM) simplifies the electronics of the entire snake arm and is well suited for operation in narrow and high-risk environments. However, the structural features of the SAM, the large slenderness ratio and the effects of variable loads and rigid-flexible coupling deformation lead to large end position error. In order to improve the positional accuracy, a joint space error compensation model of a SAM is constructed using the matrix differentiation method. The error parameters under different loads and different poses are identified based on the principles of variable parameter error compensation and a linearized variable-load variable-parameter model. Parameter errors are then calculated by the Levenberg-Marquardt nonlinear damped least-squares algorithm. Finally, we verify the effectiveness of the proposed algorithm by simulation and error compensation experiments. The results of the study provide a theoretical basis for further accuracy improvement and application expansion of the SAM.

In order to solve the problem of low efficiency and high cost in designing inserts with groove, finite element simulation (FEM) method has been employed to directly simulate the chip breaking condition. However, the current methods tend to involve a large number of cutting experiments and a user subroutine program used for secondary development, causing inconveniency in engineering application. Here, we propose a high-efficient three-dimensional (3D) FEM method to analyze the chip breakage properties of complicate-grooved insert. For the simulation, a three-dimensional cutting simulation model is established by Deform 3D FE package, and the Johnson-Cook (J-C) material constitutive model and Cockcroft-Latham (C-L) ductile fracture criterion are adopted. To verify the validity of the model, the simulations and corresponding turning experiments of AISI 1045 steel are performed with complicate-grooved insert at several combination groups of cutting depth and feed rate. The estimated chip morphology, chip breaking process, and cutting force from the simulation are in good consistency with those from the experiments. Additionally, the comparisons between the simulations and corresponding turning experiments with complicate-grooved insert and flat rake insert are conducted. The results show that the chip breaking groove can significantly change the chip flow angle and the chip geometry and that the complicate-grooved insert can more efficiently promote chip breakage than the flat rake insert. Therefore, the 3D FEM method proposed can be used to effectively investigate the chip formation mechanism and chip breakage properties and has promising application prospects in complicate-grooved insert design and cutting parameter optimization.

Nickel-based superalloy Inconel 718 is one of the hardest materials owing to its high hardness and additional physical properties. It is the most commonly used superalloy in gas turbine, aerospace, and automobile sectors. Micro-milling is generally employed for precision manufacturing of tiny structures, but it is difficult to obtain good surface quality with micro-milling Inconel 718 because of its excellent mechanical properties like high strength and hardness. Atmospheric pressure cold plasma jet can effectively improve surface wettability without changing surface micromorphology, which is expected to have positive lubricating effects in micro-machining of difficult-to-cut materials. In addition, minimum quantity lubrication can induce coolants into the machining area more efficiently, and is especially appropriate for micro-machining. In this paper, we propose a composite micro-milling method combining plasma jet and minimum quantity lubrication to machine Inconel 718. The effect of plasma jet on machinability is investigated by performing micro-milling experiments under different atmospheres (dry, nitrogen jet, plasma jet, minimum quantity lubrication, and plasma + minimum quantity lubrication). Surface roughness, cutting forces, and residual stress are the measures using corresponding techniques. The results indicate that the atmospheric pressure cold plasma jet can efficiently improve surface quality and reduce cutting forces of Inconel 718.

Background. Hypertensive patients commonly experience comorbid depression, which is closely associated with adverse health outcomes. This study aimed to examine the association between depression and uncontrolled hypertension in primary care setting of Northwest China. Methods. We used a stratified multistage random sampling method to obtain 1856 hypertensives subjects aged ≥18 years among primary care setting in Xinjiang, Northwest China, between April and October 2019. Depression was evaluated by Hospital Anxiety and Depression Scale (HADS), with a cut-off score ≥8. We related depression to uncontrolled hypertension, using multiple logistic regression, adjusting for minimally sufficient adjustment set of variables retrieved from a literature-based directed acyclic graphs (DAGs) and optimal adjustment set of variables derived from the least absolute shrinkage and selection operator (LASSO) regression. Results. A total of 1,653 (89.1%) patients had uncontrolled hypertension. The prevalence of depression was 14.5% and 7.4% among patients with uncontrolled and controlled hypertension. Depression was associated with 1.12-fold increased odds of uncontrolled hypertension [odds ratio (OR) 2.12, 95% confidence interval (CI): 1.23–3.65]. The association remained significant even after adjusting for the minimal sufficient adjustment sets and the optimal adjustment set of variables. Conclusion. Depression is significantly associated with uncontrolled hypertension in primary care setting of northwest China. The integrated management of depression and hypertension in the setting might be warranted.