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Abstract The night-time temperature-related injury risks and burdens were unclear. Using 11,512,467 non-fatal injury cases in 243 surveillance hospitals across China from 2006-2021, we estimated the associations between daytime or night-time temperature and injury by a time-stratified case-crossover study, and compared their injury burden during 1990s–2010s. We found the excess risk (ER) for per 1°C rise in night-time temperature (ER = 1.21%, 95%CI:1.03%,1.39%) was greater than that in daytime (ER = 0.86%, 95%CI:0.72%,1.00%). Compared with the 1980s, the attributable fractions (AFs) for daytime and night-time temperature change during the 1990s–2010s were 0.59% (95%eCI:0.54%,0.67%) and 0.73% (95%eCI:0.69%,0.77%), respectively. Spatially, the higher AFs of night-time temperature were more widely distributed than daytime temperature. The non-fatal injury risk attributed to night-time temperature was stronger than daytime temperature, and increased night-time temperatures posed a heavier injury burden compared with daytime temperature in China. Our findings indicate that high night-time temperature is an important injury risk in the context of climate change.

This study aims to improve the tensile and high-cycle fatigue properties of a high-speed-extruded BA53 (Mg–5Bi–3Al, wt.%) alloy using a non-homogenized extrusion billet. Homogenization treatment of the BA53 billet leads to a significant reduction in the area fraction of Mg3Bi2 particles from 12.9% to 2.5% and an increase in the average grain size from 142 to 189 μm. The BA53 material produced via the high-speed extrusion of the cast billet (Cast-E) and that produced via the high-speed extrusion of the homogenized billet (Homo-E) both exhibit a fully recrystallized microstructure. However, Cast-E has a finer grain size and many more Mg3Bi2 particles than Homo-E. In addition, the tensile yield strength and elongation of Cast-E are 211 MPa and 9.4%, respectively, higher than those of Homo-E (198 MPa and 7.9%). This higher strength is attributed to the strengthening effects of the higher number of Mg3Bi2 particles, the finer grain size, and the higher internal strain energy. The fatigue limit for Cast-E is 100 MPa, which is 25% higher than that of Homo-E (80 MPa). This occurs because the numerous fine Mg3Bi2 particles in Cast-E inhibit the formation of persistent slip bands on the specimen surface and impede crack propagation. This study proposes a new manufacturing process that does not require billet homogenization, thus simultaneously improving the productivity of the extrusion process and the tensile and fatigue properties of the resulting BA53 alloy.

Abstract PDGFRA+ cells have been identified as adipocyte stem cells (ASCs) that differentiate into beige adipocytes in white adipose tissue (WAT) following thermogenic stimuli. To elucidate the molecular heterogeneity of ASCs, we conducted single-cell transcriptomic profiling of PDGFRA+ cells isolated from the inguinal WAT (iWAT) of mice treated with the beta3 adrenergic receptor agonist CL316243. Single-cell RNA-seq revealed nine major clusters, which were categorized into four groups: resting, proliferating, differentiating, and adipogenic factor-expressing cells (AFECs). Trajectory analysis revealed sequential activation of molecular pathways, including the Hedgehog and Notch signaling pathways, during beige adipogenesis. AFECs expressed Dpp4 and did not differentiate into adipocytes in culture or after transplantation. Furthermore, genetic lineage tracing studies indicated that DPP4+ cells did not differentiate into adipocytes in iWAT during CL316243-induced beige adipogenesis. However, high-fat diet feeding led to the recruitment of adipocytes from DPP4+ cells in iWAT. Overall, this study improved our understanding of the dynamic molecular basis of beige adipogenesis and the potential contribution of DPP4+ adipocyte lineages to the pathological expansion of WAT during diet-induced obesity.

Abstract Breast cancer (BC) is a major contributor to female mortality worldwide, particularly in young women with aggressive tumors. Despite the need for accurate prognosis in this demographic, existing studies primarily focus on broader age groups, often using the SEER database, which has limitations in variable selection. This study aimed to develop an ML-based model to predict survival outcomes in young BC patients using the BC public staging database. A total of 3,401 patients with BC were included in the study. Patients were categorized as younger (n = 1574) and older (n = 1827). We applied several survival models—Random Survival Forest, Gradient Boosting Survival, Extra Survival Trees (EST), and penalized Cox models (Lasso and ElasticNet)—to compare mortality characteristics. The EST model outperformed others in predicting mortality for both age groups. Older patients exhibited a higher prevalence of comorbidities compared to younger patients. Tumor stage was the primary variable used to train the model for mortality prediction in both groups. COPD was a significant variable only in younger patients with BC. Other variables exhibited varying degrees of consistency in each group. These findings can help identify high-risk young female patients with BC who require aggressive treatment by predicting the risk of mortality.

Abstract Accurate estimation of wind power is essential for predicting and maintaining the power balance in the power system. This paper proposes a novel approach to enhance the accuracy of wind power estimation through a hybrid model integrating neural networks and error discrimination‐correction techniques. In order to improve the accuracy of estimation, a bidirectional gating recurrent unit is developed, forming an initial wind power estimation curve through training. Additionally, a sequential model‐based algorithmic configuration optimizes bidirectional gating recurrent unit's network hyperparameters. To tackle estimation errors, a multi‐layer perceptron combined with sequential model‐based algorithmic configuration is employed to create a classification model that automatically discerns the quality of estimates. Subsequently, an innovative correction model, based on grey relevancy degree and relevancy errors, is devised to rectify erroneous estimates. The final estimates result from a summation of the initial estimates and the values derived from error corrections. By analysing the real data from a wind farm in northwest China, a simulation test validates the proposed hybrid model. Experimental results demonstrate a substantial improvement in modelling accuracy when compared to the initial model.

Abstract Background Previous research has shown that the use of renin-angiotensin system (RAS) blockers is linked to a lower prevalence of posttraumatic stress disorder (PTSD), but longitudinal studies are scarce. We aimed to estimate the association between the use of RAS blockers and the risk of PTSD among individuals taking antihypertensive medications. Methods This longitudinal study included participants aged 40–69 from the UK Biobank. Exposure data were obtained from the initial assessment (2006–10), while outcome data were obtained from the online mental health questionnaire administered 6–11 years later (2016–17). We included participants who were under antihypertensive treatment and did not have a prior diagnosis of PTSD before the initial assessment. Use of RAS blockers was defined as self-reported regular use, at the initial assessment, of angiotensin-converting enzyme inhibitor (ACEi) or angiotensin receptor blocker (ARB). Among participants who experienced adverse life experiences, cases of probable PTSD were defined with the six-item PTSD Checklist-Civilian version score ≥ 14. Logistic regression with inverse probability of treatment weighting was used to estimate the odds ratios (ORs) and 95% confidence interval (CI) for the association between RAS blocker use and the risk of probable PTSD. Results Of the 15,954 participants (mean age = 59.9 years; 42.6% women) under antihypertensive treatment with no prior history of PTSD at the initial assessment, 64.5% were taking RAS blockers. After a mean follow-up of 7.5 years, 1,249 (7.8%) were newly identified with probable PTSD. RAS blocker users had a lower risk of probable PTSD than RAS blocker non-users (OR = 0.84 [95% CI: 0.75–0.94]), whereas the use of other antihypertensive medications showed no such association (users vs. non-users; calcium channel blockers, OR = 0.99 [95% CI: 0.88–1.11]; beta-blockers, 1.20 [1.08–1.34]; and thiazide-related diuretics, 1.15 [1.03–1.29]). The association between probable PTSD risk and the use of ACEi vs. ARB showed no significant difference (p = 0.96). Conclusions Among individuals under antihypertensive treatment, the use of RAS blockers was associated with a decreased risk of probable PTSD. This added benefit of RAS blockers should be considered in the selection of antihypertensive medications.

Abstract Employees in enterprises face numerous challenges due to the severe employment situation and job pressure. Sales personnel and research and development (R&D) personnel in companies are particularly susceptible to mental health issues due to the unique nature and complexity of their work. This study aims to explore the psychological health issues among sales personnel and R&D personnel in high-tech enterprises. Twenty-four R&D personnel (23 males and 1 female) and twenty-six sales personnel (25 males and 1 female) were recruited. The participants’ psychological health conditions were assessed using the Symptom Checklist-90 (SCL-90) and verbal fluency tasks combined with functional near-infrared spectroscopy (VFT-fNIRS), while their work stress level was evaluated using the Personal Stress Questionnaire (PSQ) and Personal Resources Questionnaire (PRQ). The results indicated significantly higher brain activities in the right dorsolateral prefrontal cortex and bilateral Broca’s areas of the R&D group compared to the sales group. The R&D group had significantly lower scores in the total score and multiple dimensions of SCL-90, such as somatization, obsession-compulsion, depression, anxiety, hostility, and paranoia. In addition, the R&D group exhibited significantly lower psychological and physical tension reactions compared to the sales group in PSQ. Based on the PRQ, the R&D group obtained significantly higher scores in self-care compared to the sales group. In conclusion, the mental health status of the R&D group is better than that of the sales group, the difference in self-care may be the most important factor leading to the difference in work stress and mental health of the two groups, VFT-fNIRS might be used to assist in detecting the mental health status of employees.

Mycotoxins are toxic secondary metabolites produced by certain fungal species under specific conditions. Research has found that exposure to various fungal toxins can cause embryonic developmental toxicity, such as embryo arrest, abortion, and intrauterine fetal developmental delay. There are no systematic reports on the impact of exposure to fungal toxins during pregnancy on the toxicity of intrauterine fetal development and biological monitoring. Therefore, in order to prevent and reduce the harm of fungal toxins during pregnancy, this paper summarizes the research status of embryonic developmental toxicity, as well as the research status of biological monitoring technologies based on biomarkers such as exposure biomarkers and biomakers of effect, which are caused by traditional fungal toxins such as aflatoxin, deoxynivalenol, zearalenone, and emerging fungal toxins such as Alternaria toxins, beauverin, and enniatins. The aim of the paper is for construction of the healthy China.

Abstract Background Linkage errors that occur according to linkage levels can adversely affect the accuracy and reliability of analysis results. This study aimed to identify the differences in results according to personally identifiable information linkage level, sample size, and analysis methods through empirical analysis. Methods The difference between the results of linkage in directly identifiable information (DII) and indirectly identifiable information (III) linkage levels was set as III linkage based on name, date of birth, and sex and DII linkage based on resident registration number. The datasets linked at each level were named as databaseIII (DBIII) and databaseDII (DBDII), respectively. Considering the analysis results of the DII-linked dataset as the gold standard, descriptive statistics, group comparison, incidence estimation, treatment effect, and moderation effect analysis results were assessed. Results The linkage rates for DBDII and DBIII were 71.1% and 99.7%, respectively. Regarding descriptive statistics and group comparison analysis, the difference in effect in most cases was “none” to “very little.” With respect to cervical cancer that had a relatively small sample size, analysis of DBIII resulted in an underestimation of the incidence in the control group and an overestimation of the incidence in the treatment group (hazard ratio [HR] = 2.62 [95% confidence interval (CI): 1.63–4.23] in DBIII vs. 1.80 [95% CI: 1.18–2.73] in DBDII). Regarding prostate cancer, there was a conflicting tendency with the treatment effect being over or underestimated according to the surveillance, epidemiology, and end results summary staging (HR = 2.27 [95% CI: 1.91–2.70] in DBIII vs. 1.92 [95% CI: 1.70–2.17] in DBDII for the localized stage; HR = 1.80 [95% CI: 1.37–2.36] in DBIII vs. 2.05 [95% CI: 1.67–2.52] in DBDII for the regional stage). Conclusions To prevent distortion of the analyses results in health and medical research, it is important to check that the patient population and sample size by each factor of interest (FOI) are sufficient when different data are linked using DBDII. In cases involving a rare disease or with a small sample size for FOI, there is a high likelihood that a DII linkage is unavoidable.

Precise prediction of the remaining useful life (RUL) of rolling bearings is crucial for ensuring the smooth functioning of machinery and minimizing maintenance costs. The time-domain features can reflect the degenerative state of the bearings and reduce the impact of random noise present in the original signal, which is often used for life prediction. However, obtaining ideal training data for RUL prediction is challenging. Thus, this paper presents a bearing RUL prediction method based on unsupervised learning sample augmentation, establishes a VAE-GAN model, and expands the time-domain features that are calculated based on the original vibration signals. By combining the advantages of VAE and GAN in data generation, the generated data can better represent the degradation state of the bearings. The original data and generated data are mixed to realize data augmentation. At the same time, the dynamic time warping (DTW) algorithm is introduced to measure the similarity of the dataset, establishing the mapping relationship between the training set and target sequence, thereby enhancing the prediction accuracy of supervised learning. Experiments employing the XJTU-SY rolling element bearing accelerated life test dataset, IMS dataset, and pantograph data indicate that the proposed method yields high accuracy in bearing RUL prediction.

BackgroundAnlotinib, a highly selective inhibitor of VEGFR2, has demonstrated significant anti-tumor effects in various cancers. However, its potential synergistic effects with DDP (cisplatin) in breast cancer (BRCA) remain to be fully elucidated. This study aims to discover the therapeutic efficacy of anlotinib on BRCA, specifically the synergistic effects with DDP, and to elucidate the underlying molecular mechanisms.MethodsBRCA cells were treated with anlotinib and/or DDP. The proliferation, migration and invasion capabilities of BRCA cells were evaluated using CCK-8 assays, cell cycle distribution, clone formation assays, wound healing assays and transwell assays. Cell apoptosis was detected by flow cytometry technique and Hoechst33342 fluorescence staining. The potential mechanism of anlotinib in the development of BRCA was predicted through bioinformatics analysis, and the mRNA or protein levels were subsequently quantified using qPCR, immunofuorescence and western blot. The anti-breast cancer efficacy of anlotinib was evaluated in vivo using a xenograft tumor model.ResultsOur findings reveal that increased VEGFA expression in BRCA patients is associated with poorer prognosis, underscoring the need for targeted therapeutic strategies. We also demonstrate that both anlotinib and DDP independently inhibit BRCA cell growth, migration, and invasion, while their combination exhibits a synergistic effect, significantly enhancing the inhibition of these oncogenic processes. This synergy is further evident through the induction of apoptosis and autophagy in BRCA cells. Mechanistically, anlotinib’s effectiveness is linked to its inhibition of the JAK2/STAT3 pathway, a critical axis in BRCA progression. In vivo study further support these results, showing that anlotinib markedly inhibits tumor growth in xenografted mice.ConclusionThis study confirms the efficacy of anlotinib or in combination with DDP and elucidates the mechanism behind anlotinib’s effectiveness, highlighting its role in inhibiting the JAK2/STAT3 pathway.

Off-target pesticide drift in paddy fields following unmanned aerial vehicle (UAV) spraying was evaluated using cellulose deposition samplers (CDSs). An analytical method for quantifying ferimzone Z and E isomers deposited on CDSs was developed using LC-MS/MS. The suitability of the CDS method was confirmed by comparing deposition patterns on CDSs with residue levels in rice plant samples. To assess pesticide deposition in paddy fields, CDSs were strategically placed at varying distances from target areas, followed by UAV spraying. The fungicide agrochemicals were applied with and without adjuvants, and wind direction affected the drift trajectory for all treatment groups. Adjuvants, particularly soy lecithin as the major component, significantly enhanced pesticide deposition within the spray pathway while reducing drift rates relatively by 47.9–68.0 %. Higher wind speeds were found to exacerbate drift, but adjuvant-treated sprays showed less variability in deposition patterns under these conditions. Pesticide residues in harvested brown rice were found to be below the maximum residue limits (MRLs), ensuring safety for consumption. These findings highlight the importance of selecting appropriate adjuvants in UAV-based pesticide applications to optimize deposition efficiency and minimize environmental contamination.