Objective To systematically analyze the spatiotemporal distribution characteristics and epidemiological trends of tracheal, bronchus, and lung cancer (TBL) disease burden attributed to air pollution globally and in China and the United States from 1990 to 2021, and to assess the patterns of disease burden changes from 2022 to 2031 based on predictive models, providing a scientific basis for formulating targeted TBL prevention and control strategies. Methods Based on the Global Burden of Disease (GBD) 2021 database, we analyzed the disease burden data of TBL attributed to air pollution globally and in China and the United States from 1990 to 2021. R Studio 4.3.2 software was used to analyze the corresponding trends and the Bayesian age-period-cohort (BAPC) prediction model was used to predict the status of the disease burden of TBL attributed to air pollution in the world and in China and the United States from 2022 to 2031. Results In 2021, China had the highest number of deaths and disability-adjusted life years attributed to air pollution (211 400 patients and 4.8947 million person-years), followed by the United States (6 000 patients and 124 300 person-years). The age-standardized mortality rate (ASMR) and age-standardized disability-adjusted life years rate (ASDR) of TBL due to air pollution in the world and in China and the United States showed a decreasing trend. From 1990 to 2021, the ASMR and ASDR of TBL in China due to air pollution were much higher than those in the United States and the global average. In terms of gender, from 1990 to 2021, the disease burden of male patients with TBL attributed to air pollution was much higher than that of female patients. The BAPC prediction model showed that from 2022 to 2031, the ASMR and ASDR of TBL attributed to air pollution showed an upward trend globally, while they showed a downward trend in China and the United States. Conclusion Over the past 30 years, the air pollution-related TBL disease burden in the world and in China and the United States has continued to decline, but China's disease burden is still significantly higher than the global average. The disease burden in men far exceeds that in women, with men and the population aged ≥50 years being high-risk groups. In the future, the global disease trend may reverse and rise, while China and the United States are expected to continuously decline. However, precise prevention and control for high-risk groups remains a key challenge.

Objective To assess the clinical value of multimodal ultrasound score for assessment of endometrial receptivity among patients with polycystic ovary syndrome (PCOS), and to provide guidance for improving pregnancy outcomes among PCOS patients. Methods A total of 48 PCOS patients admitted to Jiangning Hospital Affiliated to Nanjing Medical University between January and December 2023 were enrolled as the case group, while 50 healthy women of childbearing age received ovulation monitoring at the same hospital during the same period served as the control group. Subjects received two-dimensional grayscale ultrasound during the implantation window (19 to 23 days of the menstrual cycle) for measurement of endometrial thickness, Gonen classification, and endometrial peristalsis. Two-dimensional color Doppler ultrasound was used for assessment of endometrial blood flow and three-dimensional ultrasound was used for assessment of endometrial volume and vascularization flow index (VFI). The endometrium multimodal ultrasound scores were estimated, and various parameters were compared between the two groups. The diagnostic performance of these parameters for PCOS was evaluated with receiver operating characteristic (ROC) curves. Results The age of subjects in the case group ranged from 20 to 38 years, with a mean age of (28.20 ± 2.82) years, and their body mass index (BMI) ranged from 21.23 to 29.11 kg/m², with a mean BMI of (26.25 ± 1.60) kg/m². The age of subjects in the control group ranged from 22 to 38 years, with a mean age of (28.10 ± 1.99) years, and their BMI ranged from 21.33 to 29.03 kg/m², with a mean BMI of (26.10 ± 1.78) kg/m². There were no significant differences between the case and control groups in terms of mean age, BMI, estradiol, and testosterone (t = 0.218, 0.422, 0.010, and 0.221; all P > 0.05). The endometrial thickness, endometrial volume, and VFI were significantly higher in the control group than in the case group (t = 4.838, 4.978, and 7.115; all P < 0.05). There were significant differences between the two groups in terms of endometrial classification, endometrial peristalsis pattern, and endometrial and sub-endometrial blood flow (Z = −4.136, −4.048, and −3.884; all P < 0.05). The scores of endometrial classification, endometrial peristalsis, endometrial and sub-endometrial blood flow, endometrial volume, VFI, and multimodal ultrasound were significantly lower in the case group than in the control group (t = 4.539, 4.449, 4.205, 3.209, 5.206, and 4.495; all P < 0.05). No significant difference was detected in the endometrial thickness score between the two groups (t = -0.149, P = 0.882). The areas under the ROC curves for endometrial thickness, endometrial volume, VFI, and multimodal ultrasound scores in diagnosis of PCOS were 0.753, 0.747, 0.809, and 0.858, respectively. Conclusion Multimodal ultrasound score provides a comprehensive assessment of the endometrium, and is effective in the assessment of endometrial receptivity, which may provide a reference for guiding pregnancy planning in PCOS patients.

To clarify the species, pathogenicity, and distribution of the pathogens causing the root rot of Atractylodes lancea in Hubei province, the tissue separation method was used to isolate the pathogens from root rot samples in the main planting areas of A. lancea in Hubei. Based on the preliminary identification of the Fusarium genus by the internal transcribed spacer(ITS) sequence, three housekeeping genes, EF1/EF2, Btu-F-FO1/Btu-F-RO1, and FF1/FR1, were amplified and sequenced. Subsequently, a phylogenetic tree was constructed based on these TEF gene sequences to classify the pathogens. The pathogenicity of these strains was determined using the root irrigation method. A total of 194 pathogen strains were isolated using the tissue separation method. Molecular identification using the three housekeeping genes identified the pathogens as F. solani, F. oxysporum, F. commune, F. equiseti, F. tricinctum, F. redolens, F. fujikuroi, F. avenaceum, F. acuminatum, and F. incarnatum. Among them, F. solani and F. oxysporum were the dominant strains, widely distributed in multiple regions, with F. solani accounting for approximately 54% of the total isolated strains and F. oxysporum accounting for approximately 34%. Other strains accounted for a relatively small proportion, totaling approximately 12%. The results of pathogenicity determination showed that there were certain differences in pathogenicity among strains. The analysis of the pathogenicity differentiation of the widely distributed F. solani and F. oxysporum strains revealed that these dominant strains in Hubei were mainly highly pathogenic. This study determined the species, pathogenicity, and distribution of the pathogens causing the root rot of A. lancea in Hubei province. The results provide a scientific basis for further understanding the root rot of A. lancea and its epidemic occurrence and scientifically preventing and controlling this disease.
Plant Diseases/microbiology* ; Atractylodes/microbiology* ; Phylogeny ; Plant Roots/microbiology* ; Fusarium/classification* ; China ; Virulence ; Fungal Proteins/genetics*

Objective: To review the current development of artificial intelligence (AI) technology in the field of transfusion medicine. Methods: A systematic search was conducted in the Clarivate Web of Science Database from inception to December 2024 for literature related to AI and transfusion. A total of 4 775 publications were identified. Based on inclusion and exclusion criteria, 133 original studies were ultimately included and analyzed using a narrative synthesis approach. Results: Research on AI in transfusion has surged since 2020 (accounting for 77% of all publications), with China ranking second globally in publication volume. Among the included studies, 69.2% focused on predicting individual transfusion needs, followed by inventory management (8.3%), diagnosis and prediction of adverse transfusion reactions (6.0%), factors influencing transfusion outcomes (5.3%), blood group identification (5.3%), blood quality testing (4.5%), and precise blood volume measurement (1.5%). Additionally, 4.5% of the studies were published in journals with an impact factor greater than 10; 19.5% developed software or applications; 31.5% were multi-center studies; 48.1% utilized decision tree methods, while 31.5% employed neural network approaches; and 14.2% conducted external validation of the algorithms. Conclusion: AI demonstrates significant potential in transfusion risk prediction, decision support, and blood management. However, challenges remain, including limited model generalizability, insufficient algorithm interpretability, and barriers to clinical translation. The deep integration of AI with transfusion medicine will accelerate the advent of precision transfusion era, maximizing blood resource utilization, reducing waste, and ensuring transfusion safety.

A method for simultaneous determination of 21 kinds of Aconitum alkaloids(ATS)in biological specimens and infused liquor using ultra-performance liquid chromatography-tandem mass spectrometry(UPLC-MS/MS)was developed.The biological samples were pretreated with methanol-acetonitrile(1∶2,V/V)for protein precipitation,while infused liquors were diluted 100-fold with acetonitrile,followed by centrifugation,and filtration by a 0.22-μm membrane.Chromatographic separation was carried out on an EC-C18 column using gradient elution with the mixture of 10 mmol/L ammonium acetate and 0.2%formic acid as mobile phase A and acetonitrile as mobile phase B.With this method,all the analytes were separated within 9.5 min.The samples were detected in positive ESI mode with dynamic multiple reaction monitoring(MRM)and quantified via external standard calibration.The results showed that the concentrations of the analytes in the range of 2-1000 ng/mL had excellent linearity(R2>0.9992)with the peak area.The developed method was successfully used for detection of 21 kinds of aconitum alkaloids,with limits of detection of 0.5-2 ng/mL,quantification limits of 2-6 ng/mL,intra/inter-day precision≤6.0%,spiked recoveries of 89.4%-100.9%,extraction recoveries of 74.2%-104.4%,and matrix effects ranging from-11.1%to 9.2%in blood/urine.The method was applied to detection of 12 samples from 4 fatal aconite poisoning cases,and all 21 kinds of ATS with total alkaloid concentrations of 0.04-4.18 μg/mL in blood and 154.96-422.83 μg/mL in medicinal liquors were detected.Tissue distribution revealed that the order of concentrations from highest to lowest is as follows:urine(157.22 μg/mL)>gastric contents(51.37 μg/mL)>kidney(21.6 μg/g)>whole blood(4.18 μg/mL)>liver(0.03 μg/g).This method showed many advantages such as simple pretreatment,low detection limits,accurate quantification,broad analyte coverage,and superior anti-interference capability in complex matrices,proving ideal for forensic and toxicological analysis of aconitum alkaloids.

Objective:To explore the association between occupational noise perception and cardiovascular disease (CVD), depression symptoms, as well as their comorbidity in occupational population and provide evidence for the prevention and control of physical and mental illnesses.Methods:A cross-sectional survey design was adopted, based on baseline data in population in 28 prefectures in Sichuan Province and Guizhou Province, and 33 districts (counties) in Chongqing municipality from Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd. during October to December 2021. A questionnaire survey was conducted to collect information about noise perception, depressive symptoms, and the history of CVD. Latent profile analysis model was used to determine identify noise perception type, and multinomial logistic regression analysis was conducted to explore the relationship between different occupational noise perception types and CVD, depression symptoms and their comorbidity.Results:A total of 30 509 participants were included, the mean age was (36.6±10.5) years, and men accounted for 82.0%. The direct perception of occupational noise, psychological effects and hearing/sleep impact of occupational noise increased the risk for CVD, depressive symptoms, and their comorbidity. By using latent profile analysis, occupational noise perception was classified into four levels: low, medium, high, and very high. As the level of noise perception increased, the association with CVD, depressive symptoms, and their comorbidity increased. In fact, very high level occupational noise perception were found to increase the risk for CVD, depressive symptoms, and their comorbidity by 2.14 (95% CI: 1.73-2.65) times, 8.80 (95% CI: 7.91-9.78) times, and 17.02 (95% CI: 12.78-22.66) times respectively compared with low-level occupational noise perception. Conclusions:Different types of occupational noise perception are associated with CVD and depression symptom, especially in the form of CVD complicated with depression symptom. Furthermore, the intensity of occupational noise in the work environment should be reduced to lower the risk for physical and mental health.

Objective:To investigate the association between alcohol consumption and hypertension and SBP, DBP and the mediating effects of body mass index (BMI) and lipid level in occupational population, and provide reference for the intervention and prevention of hypertension.Methods:Based on the data of Southwest Occupational Population Cohort from China Railway Chengdu Group Co., Ltd., the information about the demographic characteristics, behavior and lifestyle, blood pressure and lipids level of the participants were collected through questionnaire survey, physical examination and blood biochemical test. Logistic/linear regression was used to analyze the association between alcohol consumption and hypertension, SBP and DBP. The individual and joint mediating effects of BMI, HDL-C, LDL-C, TG, and TC were explored through causal mediating analysis. A network analysis was used to explore the correlation between alcohol consumption, BMI and lipid levels, and hypertension.Results:A total of 22 887 participants were included, in whom 1 825 had newly detected hypertension. Logistic regression analysis found that current/former drinkers had a 33% increase of risk for hypertension compared with never-drinkers ( OR=1.33, 95% CI:1.19-1.48). Similarly, alcohol consumption could increase SBP ( β=1.05, 95% CI:0.69-1.40) and DBP ( β=1.10, 95% CI:0.83-1.38). Overall, BMI and lipid levels could mediate the associations between alcohol consumption and hypertension, SBP and DBP by 21.91%, 28.40% and 22.64%, respectively. BMI and TG were the main mediators, and they were also the two nodes with the highest edge weight and bridge strength centrality in the network of alcohol consumption, BMI, lipid levels and hypertension. Conclusions:Alcohol consumption was associated with increased risk for hypertension, and BMI and TG were important mediators and key nodes in the network. It is suggested that paying attention to the alcohol consumption, BMI and TG might help prevent hypertension in occupational population.

Following the principles of evidence-based medicine,in accordance with the structure and drafting rules of standardized documents,based on literature research,according to the characteristics of chronic cough in children and issues that need to form a consensus,the TCM Guidelines for Diagnosis and Treatment of Chronic Cough in Children was formulated based on the Delphi method,expert discussion meetings,and public solicitation of opinions.The guideline includes scope of application,terms and definitions,eti-ology and diagnosis,auxiliary examination,treatment,prevention and care.The aim is to clarify the optimal treatment plan of Chinese medicine in the diagnosis and treatment of this disease,and to provide guidance for improving the clinical diagnosis and treatment of chronic cough in children with Chinese medicine.

Objective:To develop a deep learning architecture based on 3D Transformers to predict dose distribution within intensity modulated radiation therapy (IMRT) plans for lung cancer.Methods:Clinical data of 174 lung cancer patients treated with IMRT in Chongqing University Cancer Hospital between January 2020 and December 2022 were retrospectively analyzed. All patients were divided into the training ( n=116), validation ( n=29), and test ( n=29) sets. We employed the Swin Unet Transformer (Swin Unetr) model to predict the three-dimensional dose distribution. The model was trained using computed tomography (CT) images, planning target volume (PTV) images, organs at risk (OAR) images, beam configuration information images, and distance images. We used various evaluation metrics such as mean absolute errors (MAE), Dice similarity coefficients (DSC), and dose volume histogram (DVH) dosimetric parameters to assess the performance of Swin Unetr and compared it with three mainstream deep learning models: CGAN, ResSEUnet, and ResUnet. Results:The MAE of the dose distribution prediction by Swin Unetr was recorded at 0.0143±0.0055. Conversely, the values of CGAN, ResSEUnet, and ResUnet were 0.0162±0.0055, 0.0167±0.0063, and 0.0164±0.0057, respectively. Furthermore, Swin Unetr achieved the highest DSC values (>0.85) across all isodose volumes. Regarding DVH dosimetric parameters, excluding D 2% of PTV and D mean of the heart, Swin Unetr exhibited no statistically significant differences in the remaining DVH dosimetric parameters (all P>0.05), demonstrating the best evaluation results in 66.67% of the overall dosimetric parameters and 75% of the PTV dosimetric parameters. Conclusions:Swin Unetr achieves the best score in multiple dosimetric evaluation indicators, and the highest DSC across all isodose volumes. Swin Unetr has significantly improved the accuracy of three-dimensional dose prediction during IMRT for lung cancer.