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Background Obesity (waist circumference, body mass index (BMI)) and lifestyle factors (dietary habits, smoking, alcohol drinking, Sedentary behavior) have been associated with risk of benign prostatic hyperplasia (BPH) in observational studies, but whether these associations are causal is unclear. Methods We performed a univariable and multivariable Mendelian randomization study to evaluate these associations. Genetic instruments associated with exposures at the genome-wide significance level ( P  < 5 × 10 –8 ) were selected from corresponding genome-wide associations studies (n = 216,590 to 1,232,091 individuals). Summary-level data for BPH were obtained from the UK Biobank (14,126 cases and 169,762 non-cases) and FinnGen consortium (13,118 cases and 72,799 non-cases). Results from UK Biobank and FinnGen consortium were combined using fixed-effect meta-analysis. Results The combined odds ratios (ORs) of BPH were 1.24 (95% confidence interval (CI), 1.07–1.43, P  = 0.0045), 1.08 (95% CI 1.01–1.17, P  = 0.0175), 0.94 (95% CI 0.67–1.30, P  = 0.6891), 1.29 (95% CI 0.88–1.89, P  = 0.1922), 1.23 (95% CI 0.85–1.78, P  = 0.2623), and 1.04 (95% CI 0.76–1.42, P  = 0.8165) for one standard deviation (SD) increase in waist circumference, BMI, and relative carbohydrate, fat, protein and sugar intake, 1.05 (95% CI 0.92–1.20, P  = 0.4581) for one SD increase in prevalence of smoking initiation, 1.10 (95% CI 0.96–1.26, P  = 0.1725) and 0.84 (95% CI 0.69–1.02, P  = 0.0741) for one SD increase of log-transformed smoking per day and drinks per week, and 1.31 (95% CI 1.08–1.58, P  = 0.0051) for one SD increase in sedentary behavior. Genetically predicted waist circumference (OR = 1.26, 95% CI 1.11–1.43, P  = 0.0004) and sedentary behavior (OR = 1.14, 95% CI 1.05–1.23, P  = 0.0021) were associated with BPH after the adjustment of BMI. Conclusion This study supports independent causal roles of high waist circumference, BMI and sedentary behavior in BPH.

Backgrounds The study aimed to estimate bladder cancer burden and its attributable risk factors in China, Japan, South Korea, North Korea and Mongolia from 1990 to 2019, to discuss the potential causes of the disparities. Methods Data were obtained from the Global Burden of Disease Study 2019. The annual percent change (APC) and average annual percent change (AAPC) were calculated by Joinpoint analysis, and the independent age, period and cohort effects were estimated by age-period-cohort analysis. Results In 2019, the highest incidence (7.70 per 100,000) and prevalence (51.09 per 100,000) rates of bladder cancer were in Japan, while the highest mortality (2.31 per 100,000) and DALY rates (41.88 per 100,000) were in South Korea and China, respectively. From 1990 to 2019, the age-standardized incidence and prevalence rates increased in China, Japan and South Korea (AAPC > 0) and decreased in Mongolia (AAPC < 0), while mortality and DALY rates decreased in all five countries (AAPC < 0). Age effects showed increasing trends for incidence, mortality and DALY rates, while the prevalence rates increased first and then decreased in older groups. The cohort effects showed downward trends from 1914–1918 to 2004–2008. Smoking was the greatest contributor and males had the higher burden than females. Conclusion Bladder cancer was still a major public health problem in East Asia. Male and older population suffered from higher risk, and smoking played an important role. It is recommended that more efficient preventions and interventions should be operated among high-risk populations, thereby reduce bladder cancer burden in East Asia.

Bibenzyl compounds are one of the most important bioactive components of natural medicine. However, Dendrobium officinale as a traditional herbal medicine is rich in bibenzyl compounds and performs functions such as acting as an antioxidant, inhibiting cancer cell growth, and assisting in neuro-protection. The biosynthesis of bibenzyl products is regulated by bibenzyl synthase (BBS). In this study, we have cloned the cDNA gene of the bibenzyl synthase (DoBS1) from D. officinale using PCR with degenerate primers, and we have identified a novel type III polyketide synthase (PKS) gene by phylogenetic analyses. In a series of perfect experiments, DoBS1 was expressed in Escherichia coli, purified and some catalytic properties of the recombinant protein were investigated. The molecular weight of the recombinant protein was verified to be approximately 42.7 kDa. An enzyme activity analysis indicated that the recombinant DoBS1-HisTag protein was capable of using 4-coumaryol-CoA and 3 malonyl-CoA as substrates for dihydroresveratrol (DHR) in vitro. The Vmax and Km of the recombinant protein for DHR were 3.57 ± 0.23 nmol·min−1·mg−1 and 0.30 ± 0.08 mmol, respectively. The present study provides further insights into the catalytic mechanism of the active site in the biosynthetic pathway for the catalytic production of dihydroresveratrol by bibenzylase in D. officinale. The results can be used to optimize a novel biosynthetic pathway for the industrial synthesis of DHR.

In response to problems such as large target scale variations, strong background noise, and blurred features leading by low contrast in infrared target detection in near space environments, this paper proposes an efficient detection model, YOLO-MARS, which is based on YOLOv8. The model introduces a Space-to-Depth (SPD) convolution module into the backbone section, which retains the detailed features of smaller targets by downsampling operations without information loss, alleviating the loss of the target feature caused by traditional downsampling. The Grouped Multi-Head Self-Attention (GMHSA) module is added after the backbone’s SPPF module to improve cross-scale global modeling capabilities for target area feature responses while suppressing complex thermal noise background interference. In addition, a Light Adaptive Spatial Feature Fusion (LASFF) detector head is designed to mitigate the scale sensitivity issue of infrared targets (especially smaller targets) in the feature pyramid. It uses a shared weighting mechanism to achieve adaptive fusion of multi-scale features, reducing computational complexity while improving target localization and classification accuracy. To address the extreme scarcity of near space data, we integrated 284 near space images with the HIT-UAV dataset through physical equivalence analysis (atmospheric transmittance, contrast, and signal-to-noise ratio) to construct the NS-HIT dataset. The experimental results show that mAP@0.5 increases by 5.4% and the number of parameters only increase 10% using YOLO-MARS compared to YOLOv8. YOLO-MARS improves the accuracy of detection significantly while considering the requirements of model complexity, which provides an efficient and reliable solution for applications in near space infrared target detection.

Tree peony (Paeonia suffruticosa Andr.) is a popular ornamental plant in China due to its showy and colorful flowers. However, yellow-colored flowers are rare in both wild species and domesticated cultivars. The molecular mechanisms underlying yellow pigmentation remain poorly understood. Here, petal tissues of two tree peony cultivars, “High Noon” (yellow flowers) and “Roufurong” (purple–red flowers), were sampled at five developmental stages (S1–S5) from early flower buds to full blooms. Five petal color indices (brightness, redness, yellowness, chroma, and hue angle) and the contents of ten different flavonoids were determined. Compared to “Roufurong,” which accumulated abundant anthocyanins at S3–S5, the yellow-colored “High Noon” displayed relatively higher contents of tetrahydroxychalcone (THC), flavones, and flavonols but no anthocyanin production. The contents of THC, flavones, and flavonols in “High Noon” peaked at S3 and dropped gradually as the flower bloomed, consistent with the color index patterns. Furthermore, RNA-seq analyses at S3 showed that structural genes such as PsC4Hs, PsDFRs, and PsUFGTs in the flavonoid biosynthesis pathway were downregulated in “High Noon,” whereas most PsFLSs, PsF3Hs, and PsF3’Hs were upregulated. Five transcription factor (TF) genes related to flavonoid biosynthesis were also upregulated in “High Noon.” One of these TFs, PsMYB111, was overexpressed in tobacco, which led to increased flavonols but decreased anthocyanins. Dual-luciferase assays further confirmed that PsMYB111 upregulated PsFLS. These results improve our understanding of yellow pigmentation in tree peony and provide a guide for future molecular-assisted breeding experiments in tree peony with novel flower colors.

The safe and stable operation of critical substation equipment is paramount to the power system, and its intelligent inspection relies on highly efficient and accurate object detection technology. However, the demanding requirements for both accuracy and efficiency in complex environments pose significant challenges for lightweight models. To address this, this paper proposes SD-FINE, a lightweight object detection technique specifically designed for detecting critical substation equipment. Specifically, we introduce a novel Fine-grained Distribution Refinement (FDR) approach, which fundamentally transforms the bounding box regression process in DETR from predicting coordinates to iteratively optimizing edge probability distributions. Central to the new FDR is an adaptive weight function learning mechanism that learns weights for these distributions. This mechanism is designed to enhance the model’s perception capability regarding equipment location information within complex substation environments. Additionally, this paper develops a new Efficient Hybrid Encoder that provides adaptive scale weighting for feature information at different scales during cross-scale feature fusion, enabling more flexible and efficient lightweight feature extraction. Experimental validation on a critical substation equipment detection dataset demonstrates that SD-FINE achieves an accuracy of 93.1% while maintaining model lightness. It outperforms mainstream object detection networks across various metrics, providing an efficient and reliable detection solution for intelligent substation inspection.

Background Severe periodontitis is a global public health challenge, disproportionately affecting low- and middle-income countries. BRICS-Plus nations (35 emerging economies representing > 50% world population) face unique pressures from socioeconomic inequalities and aging populations, yet their epidemiological trends remain understudied. This study aims to quantify the burden of severe periodontitis and project future trends in these nations. Methods Using data from the Global Burden of Disease Study 2021 (GBD 2021), we analyzed historical trends (1990–2021) of incidence and years lived with disability (YLDs) via the estimated annual percentage change (EAPC). A Bayesian age-period-cohort (BAPC) model was used to generate future projections (2022–2040) that comprehensively account for age, period, and cohort effects. Results In 2021, BRICS-Plus contributed 62.52% of global incident cases (89.61 million) and 64.31% of YLDs (6.90 million). Regional disparities were pronounced: Mercosur and SAARC showed the highest age-standardized burdens (incidence: 1132.20/100,000; YLD: 95.52/100,000), while SACU had the lowest (incidence: 600.50/100,000; YLD: 36.78/100,000). Laos exhibited the sharpest historical rises (incidence EAPC = 1.33, 95%CI: 1.02 to 1.65; YLD EAPC = 1.62, 95%CI: 1.18 to 2.06). BAPC projections indicate sustained growth in Laos, with 40–60-year-olds remaining as the high-risk group, while over half of BRICS-Plus nations may experience downward trends by 2040. Conclusions Severe periodontitis exhibits divergent trends across BRICS-Plus, with Laos facing escalating burden while most nations show projected declines. Implementing targeted interventions—including tailored dental healthcare strengthening in high-prevalence regions and evidence-based preventive strategies targeting vulnerable middle-aged demographics—is essential for effectively addressing these divergent trends and reducing the overall disease burden.

Depression is one of the main diseases that lead to disability and loss of ability to work. As a traditional Chinese medicine, Zhi-zi-chi decoction is utilized to regulate and improve depression. However, the research on the antidepressant mechanism and efficacy material basis of Zhi-zi-chi decoction has not been reported yet. Our previous research has found that Zhi-Zi-chi decoction can reduce glutamate-induced oxidative stress damage to PC 12 cells, which can exert a neuroprotective effect, and the antidepressant effect of Zhi-Zi-chi decoction was verified in CUMS rat models. In this study, the animal model of depression was established by chronic unpredictable mild stimulation combined with feeding alone. The brain metabolic profile of depressed rats was analyzed by the method of metabolomics based on ultra-performance liquid chromatography-quadrupole/time-of-flight mass. 26 differential metabolites and six metabolic pathways related to the antidepressant of Zhi-zi-chi decoction were screened and analyzed. The targeted metabolism of the glutathione metabolic pathway was analyzed. At the same time, the levels of reactive oxygen species, superoxide dismutase, glutathione reductase, glutathione peroxidase in the brain of depressed rats were measured. Combined with our previous study, the antioxidant effect of the glutathione pathway in the antidepressant effect of Zhi-zi-chi decoction was verified from the cellular and animal levels respectively. These results indicated that Zhi-zi-chi decoction exerted a potential antidepressive effect associated with reversing the imbalance of glutathione and oxidative stress in the brain of depressed rats.

Background  This study aims to analyze breast cancer burden attributable to high body mass index (BMI) and high fasting plasma glucose (FPG) in China from 1990 to 2019. Methods Data were obtained from the Global Burden of Disease (GBD) study 2019. Deaths and disability‐adjusted life years (DALYs) were used for attributable burden, and age‐period‐cohort (APC) model was used to evaluate the independent effects of age, period and birth cohort. Results In 2019, the age‐standardized mortality and DALY rates of breast cancer attributable to high BMI were 1.107 (95% UI: 0.311, 2.327) and 29.990 (8.384, 60.713) per 100 000, and mortality and DALY rates attributable to high FPG were 0.519 (0.095, 1.226) and 13.662 (2.482, 32.425) per 100 000. From 1990 to 2019, the age‐standardized mortality and DALY rates of breast cancer attributable to high BMI increased by 1.192% and 1.180%, and the trends of high FPG were not statistically significant. The APC results showed that the age effects of high BMI and high FPG‐mortality and DALY rates increased, with the highest rates in the age group over 80 years. The birth cohort effects of high BMI showed “inverted V” shapes, while high FPG showed downward trends. Conclusions Age was the main reason for the increase of attributable burden, and postmenopausal women were the high‐risk groups. Therefore, targeted prevention measures should be developed to improve postmenopausal women's awareness and effectively reduce the prevalence of obesity and diabetes, thereby reducing the breast cancer burden caused by metabolic factors in China. Breast cancer burden caused by metabolic factors remains a serious health challenge among Chinese women, with the deaths and DALYs attributed to high BMI and high FPG showing significant upward trends over the past 30 years. Age was the main reason for the increase of attributable burden. Postmenopausal women might be the high‐risk groups, and the earlier birth cohorts were vulnerable groups for the development of breast cancer.

ObjectivesTo explore the relationships between the pulse/breathing rate ratio (PBR) and the risk of death and critical illness.DesignThis was a retrospective observational study.SettingThis was a single-centre study from a tertiary hospital in Tianjin, China.ParticipantsThe study population consisted of patients aged ≥16 years who underwent consultation and were monitored for medical purposes at the clinic.InterventionsBetween April 2021 and December 2021. Before the patients received any medical intervention, vital signs were measured, and the PBR and the National Early Warning Score (NEWS) were calculated on the basis of the above measured indicators.Primary and secondary outcome measuresThe associations of PBRs with death and critical illness were evaluated.ResultsA total of 1048 outpatients with fever were included. Restricted cubic spline (RCS) bars were used to explore potential nonlinear associations between PBR and mortality and critical illness. The abilities of the PBR and NEWS to predict the risk of death and critical illness were compared through decision curve analysis (DCA). The RCS showed a U-shaped nonlinear distribution of associations between PBRs and death and critical illness (nonlinear p values of p=0.036 and p=0.005, respectively). The risk of mortality was lowest between 4.6 and 6.2 for PBR, with the risk of mortality increasing progressively with decreasing PBR for PBR<4.6, and the risk of mortality increasing progressively with increasing PBR for PBR>6.2. The risk of critical illness was lowest when the PBR was between 4.6 and 5.5, and the risk increased gradually with decreasing PBR for PBR<4.6 and with increasing PBR for PBR>5.5. The DCA results revealed that the value of the PBR in predicting death was similar to that of the NEWS. In the DCA, the net benefit achieved by the NEWS ranged from 3% to 10% threshold probability, and the net benefit achieved by the PBR ranged from 4% to 10% threshold probability, with similar net benefits for the NEWS and PBR and 1% for both the PBR and the NEWS when the threshold probability was 7% (equivalent to correctly identifying 10 mortalities per 100 patients).ConclusionsThe PBR helps to predict the risk of mortality and critical illness in acutely ill patients, and its value in predicting mortality is similar to that of the NEWS.