Objective: To investigate the current status of benefit finding among young and middle-aged patients with type 2 diabetes mellitus (T2DM) and analyze its influencing factors, so as to provide a reference for improving the level of benefit finding in this population. Methods: From November 2022 to May 2023, young and middle-aged patients with T2DM aged 18-59 years hospitalized in the endocrinology departments of 2 tertiary hospitals in Hengyang City, Hunan Province were selected as survey subjects by a convenience sampling method. Basic demographic information was collected using a general questionnaire survey. Benefit finding, resourcefulness, and stigma were evaluated using the Benefit Finding Scale, the Chinese Version of the Resourcefulness Scale, and the Type 2 Diabetes Stigma Assessment Scale, respectively. A multiple linear regression model was used to analyze the influencing factors of benefit finding among young and middle-aged patients with T2DM. Results: A total of 305 young and middle-aged patients with T2DM were investigated, including 222 males (72.79%) and 83 females (27.21%). There were 231 cases aged 45-59 years, accounting for 75.74%. The scores for benefit finding, resourcefulness, and stigma were (42.86±6.06), (75.12±11.30), and (41.20±10.10), respectively. Multiple linear regression analysis showed that young and middle-aged patients with T2DM who were male (β′=0.088), aged 18-<45 years (β′=0.083), absence of diabetes complications (β′=0.124), and had higher resourcefulness scores (β′=0.679) had higher levels of benefit finding, while patients with higher stigma scores (β′=-0.097) had lower levels of benefit finding. Conclusion The level of benefit finding among young and middle-aged patients with T2DM was moderate, and was related to gender, age, diabetes complications, resourcefulness, and stigma.

Objective To propose a lung artery segmentation method that integrates shape and position prior knowledge, aiming to solve the issues of inaccurate segmentation caused by the high similarity and small size differences between the lung arteries and surrounding tissues in CT images. Methods Based on the three-dimensional U-Net network architecture and relying on the PARSE 2022 database image data, shape and position prior knowledge was introduced to design feature extraction and fusion strategies to enhance the ability of lung artery segmentation. The data of the patients were divided into three groups: a training set, a validation set, and a test set. The performance metrics for evaluating the model included Dice Similarity Coefficient (DSC), sensitivity, accuracy, and Hausdorff distance (HD95). Results The study included lung artery imaging data from 203 patients, including 100 patients in the training set, 30 patients in the validation set, and 73 patients in the test set. Through the backbone network, a rough segmentation of the lung arteries was performed to obtain a complete vascular structure; the branch network integrating shape and position information was used to extract features of small pulmonary arteries, reducing interference from the pulmonary artery trunk and left and right pulmonary arteries. Experimental results showed that the segmentation model based on shape and position prior knowledge had a higher DSC (82.81%±3.20% vs. 80.47%±3.17% vs. 80.36%±3.43%), sensitivity (85.30%±8.04% vs. 80.95%±6.89% vs. 82.82%±7.29%), and accuracy (81.63%±7.53% vs. 81.19%±8.35% vs. 79.36%±8.98%) compared to traditional three-dimensional U-Net and V-Net methods. HD95 could reach (9.52±4.29) mm, which was 6.05 mm shorter than traditional methods, showing excellent performance in segmentation boundaries. Conclusion The lung artery segmentation method based on shape and position prior knowledge can achieve precise segmentation of lung artery vessels and has potential application value in tasks such as bronchoscopy or percutaneous puncture surgery navigation.

OBJECTIVE To analyze the components migrating to blood and metabolites of Polygonum cuspidatum in rats with acute gouty arthritis （AGA）. METHODS SD rats were randomly divided into blank group， model group and P. cuspidatum group （10 g/kg， by raw material）， with 6 rats in each group. Except for blank group， AGA model was induced in the remaining groups by injecting potassium oxonate and sodium urate； meanwhile， they were administered corresponding drug solutions or water intragastrically， once a day， for 10 consecutive days. The histopathological morphology of the knee joint tissues in rats was observed；rat serum samples were collected， and the components migrating to blood and metabolites of P. cuspidatum were analyzed by using UPLC-Q-Exactive-Orbitrap-MS. RESULTS Following the intervention with P. cuspidatum， the histopathological morphology of the knee joint synovial tissue in AGA rats showed significant improvement， with reduced inflammatory cell infiltration and hyperplasia， and the preservation of the honeycomb-like structure integrity. In both positive and negative ion modes， a total of 67 chemical components were detected in the serum of rats from P. cuspidatum group， including 25 prototype components and 42 metabolites. The involved compound types encompassed stilbenes， anthraquinones， naphthols， and flavonoids， among others. The metabolic reactions identified included methylation， acetylation， sulfation， and glucuronidation. Notably， compounds such as polydatin， resveratrol and emodin were capable of entering the bloodstream in their prototype forms and undergoing in vivo metabolism. CONCLUSIONS Compounds such as polydatin， resveratrol and emodin are likely to be the active components responsible for the anti-AGA effects of P. cuspidatum.

Abstract Childhood hypertension is becoming a substantial public health challenge with profound implications for children s quality of life and long term health. The study analyzes the global prevalence of childhood hypertension and the relationship between macroecological factors, meso environmental factors, and micro individual factors based on the perspective of life course and childhood hypertension. And it further summarizes existing prevention and control strategies: systematic prevention and control based on policy and social support, health promotion based on behavioral science theory, and dynamic monitoring and management based on individualized prevention and control, to provide a reference for promoting the advancement of childhood hypertension prevention and control strategies.

This study aims to explore the intervention effects of isorhamnetin(Isor) on acute lung injury(ALI) and its regulatory effects on pyroptosis mediated by the NOD-like receptor family pyrin domain containing 3(NLRP3)/apoptosis-associated speck-like protein containing a CARD(ASC)/cysteine aspartate-specific protease-1(caspase-1) axis. In the in vivo experiments, 60 BALB/c mice were divided into five groups. Except for the control group, the other groups were administered Isor by gavage 1 hour before intratracheal instillation of LPS to induce ALI, and tissues were collected after 12 hours. In the in vitro experiments, RAW264.7 cells were divided into five groups. Except for the control group, the other groups were pretreated with Isor for 2 hours before LPS stimulation and subsequent assessments. Hematoxylin-eosin(HE) staining was used to observe pathological changes in lung tissue, while lung swelling, protein levels in bronchoalveolar lavage fluid(BALF), and myeloperoxidase(MPO) levels in lung tissue were measured. Cell proliferation toxicity and viability were assessed using the cell counting kit-8(CCK-8) method. Enzyme-linked immunosorbent assay(ELISA) was used to detect the levels of interleukin-1β(IL-1β), IL-6, IL-18, and tumor necrosis factor-α(TNF-α). Protein levels of NLRP3, ASC, cleaved caspase-1, and the N-terminal fragment of gasdermin D(GSDMD-N) were evaluated using immunohistochemistry, immunofluorescence, and Western blot. The results showed that in the in vivo experiments, Isor significantly improved pathological damage in lung tissue, reduced lung swelling, protein levels in BALF, MPO levels in lung tissue, and levels of inflammatory cytokines such as IL-1β, IL-6, IL-18, and TNF-α, and inhibited the high expression of the NLRP3/ASC/caspase-1 axis and the pyroptosis core gene GSDMD-N. In the in vitro experiments, the safe dose of Isor was determined through cell proliferation toxicity assays. Isor reduced cell death and inhibited the expression levels of the NLRP3/ASC/caspase-1 axis, GSDMD-N, and inflammatory cytokines. In conclusion, Isor may alleviate ALI by modulating pyroptosis mediated by the NLRP3/ASC/caspase-1 axis.
Animals ; Pyroptosis/drug effects* ; NLR Family, Pyrin Domain-Containing 3 Protein/genetics* ; Acute Lung Injury/physiopathology* ; Mice ; Mice, Inbred BALB C ; Quercetin/pharmacology* ; Caspase 1/genetics* ; CARD Signaling Adaptor Proteins/genetics* ; Male ; RAW 264.7 Cells ; Humans ; Lung/metabolism*

This study applied the grading of recommendations assessment, development and evaluation(GRADE) system and the integrated evidence chain-based effectiveness evaluation of traditional Chinese medicine(Eff-iEC) to evaluate the evidence for 12 commonly used Chinese patent medicines for the treatment of osteoporosis, which are frequently recommended in guidelines or expert consensuses. The results showed that Xianling Gubao Capsules/Tablets were rated as C(low-level evidence) according to the GRADE system, and as BA~+B~+(intermediate evidence) according to the Eff-iEC system. Jintiange Capsules were rated as C(low-level evidence) by the GRADE system, and as AA~+B(high-level evidence) by the Eff-iEC system. Gushukang Granules/Capsules were rated as C(low-level evidence) by GRADE system, and as BA~+B~+(intermediate evidence) by Eff-iEC system. Zuogui Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Qianggu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B~+(high-level evidence) by Eff-iEC system. Zhuanggu Zhitong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BA~+B(intermediate evidence) by Eff-iEC system. Jingui Shenqi Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~+B(high-level evidence) by Eff-iEC system. Quanduzhong Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AD~+B~+(low-level evidence) by Eff-iEC system. Epimedium Total Flavones Capsules were rated as D(extremely low-level evidence) by GRADE system, and as AAB~+(high-level evidence) by Eff-iEC system. Yougui Pills were rated as D(extremely low-level evidence) by GRADE system, and as AA~(++)B~(+ )(high-level evidence) by Eff-iEC system. Qigu Capsules were rated as D(extremely low-level evidence) by GRADE system, and as BB~+B(intermediate evidence) by Eff-iEC system. Liuwei Dihuang Pills were rated as C(low-level evidence) by GRADE system, and as AA~(++)B~+(high-level evidence) by Eff-iEC system. Overall, the Eff-iEC system provides a more comprehensive assessment of the effectiveness evidence for traditional Chinese medicine(TCM) than the GRADE system. However, it still has certain limitations that hinder its wider promotion and application. In terms of clinical evidence evaluation, both the Eff-iEC and GRADE systems reflect that the current clinical research quality on Chinese patent medicines for the treatment of osteoporosis is generally low. High-quality clinical trials are still needed in the future to further validate clinical efficacy.
Drugs, Chinese Herbal/therapeutic use* ; Osteoporosis/drug therapy* ; Humans ; Nonprescription Drugs/therapeutic use* ; Evidence-Based Medicine ; Medicine, Chinese Traditional

Transformer models have emerged as pivotal tools within the realm of drug discovery, distinguished by their unique architectural features and exceptional performance in managing intricate data landscapes. Leveraging the innate capabilities of transformer architectures to comprehend intricate hierarchical dependencies inherent in sequential data, these models showcase remarkable efficacy across various tasks, including new drug design and drug target identification. The adaptability of pre-trained transformer-based models renders them indispensable assets for driving data-centric advancements in drug discovery, chemistry, and biology, furnishing a robust framework that expedites innovation and discovery within these domains. Beyond their technical prowess, the success of transformer-based models in drug discovery, chemistry, and biology extends to their interdisciplinary potential, seamlessly combining biological, physical, chemical, and pharmacological insights to bridge gaps across diverse disciplines. This integrative approach not only enhances the depth and breadth of research endeavors but also fosters synergistic collaborations and exchange of ideas among disparate fields. In our review, we elucidate the myriad applications of transformers in drug discovery, as well as chemistry and biology, spanning from protein design and protein engineering, to molecular dynamics (MD), drug target identification, transformer-enabled drug virtual screening (VS), drug lead optimization, drug addiction, small data set challenges, chemical and biological image analysis, chemical language understanding, and single cell data. Finally, we conclude the survey by deliberating on promising trends in transformer models within the context of drug discovery and other sciences.

Nine compounds were isolated and purified from 90% ethanol extract of Alstonia mairei Lévl by using various chromatographic methods, including silica gel, SephadexLH-20, MCI Gel and ODS column chromatography, combined with semi-preparative liquid phase separation methods. Modern spectroscopic methods (1D and 2D NMR, UV, IR, MS, etc.) were used to identify the structures of the isolated compounds. They were identified as mairoside A (1), 3′,6-di-O-sinaloylsucrose (2), myristic acid (3), methyl myristate (4), ethyl myristate (5), 3,4,5-trimethoxycinnamic acid (6), 3,4,5-trimethoxybenzoic acid (7), vinoline (8), kaempferol-3-O-rutinoside (9), among which compound 1 is a new glycoside, compounds 4 and 5 are new natural products, and the nuclear magnetic data of compound 4 were reported for the first time.

ObjectiveTo analyze the factors influencing meropenem-related liver injury （MRLI） and to explore their clinical predictive value. MethodsA retrospective case-control study was conducted， and the Chinese Hospital Pharmacovigilance System （CHPS） was used to establish a retrieval scheme. A total of 1 625 hospitalized cases using meropenem from January 2018 to December 2022 were collected. Patients were divided into case group （n=62） and control group （n=1 563） based on the presence or absence of liver injury. Clinical data and laboratory indicators from both groups were collected and analyzed. The t-test was used for comparison of normally distributed continuous data between the two groups， while the Mann-Whitney U test was used for comparison of continuous data not conforming to a normal distribution. The chi-square test was used for comparison of categorical data between the two groups. A multivariate Logistic regression analysis was performed to identify the influencing factors for MRLI. A Logistic regression equation was established， and the predictive value of these factors was assessed using the receiver operating characteristic （ROC） curve. ResultsThe results of univariate analysis indicated that the rates of male patients， hypoproteinemia， shock， intensive care unit （ICU） admissions， sepsis， and liver， gallbladder， and cardiovascular diseases， the levels of alanine aminotransferase （ALT）， alkaline phosphatase （ALP）， gamma-glutamyl transpeptidase （GGT）， aspartate aminotransferase （AST）， creatinine （CREA）， and procalcitonin （PCT）， and the number of hospitalization days were significantly higher in the case group than in the control group （P<0.05）， and that the platelet levels in the case group were significantly lower than those in the control group （P<0.05）. The multivariate Logistic regression analysis showed that male sex （odds ratio ［OR］=2.080， 95% confidence interval ［CI］： 1.050 — 4.123， P=0.036）， admission to the ICU （OR=8.207， 95%CI： 4.094‍ ‍—‍ ‍16.453， P<0.001）， comorbidity with gallbladder disease （OR=8.240， 95%CI： 3.605‍ ‍—‍ ‍18.832， P<0.001）， ALP （OR=1.012， 95%CI： 1.004‍ ‍—‍ ‍1.019， P=0.004）， GGT （OR=1.010， 95%CI： 1.005‍ ‍—‍ ‍1.015， P<0.001）， and PLT （OR=0.997， 95%CI： 0.994‍ ‍—‍ ‍0.999， P=0.020） were the influential factors for MRLI. The areas under the ROC curve of ALP， GGT， and PLT were 0.589， 0.637， and 0.595， respectively， and the AUC of them combined was 0.837. ConclusionMale sex， ICU admission， comorbidity with gallbladder disease， increased ALP， increased GGT， and decreased PLT were influencing factors for MRLI， and a combination of factors has a better predictive value for the occurrence of MRLI.

Background The adverse effects of long working hours, shift rotation, and job stress on the physical and mental health of occupational populations require urgent attention. Objective To investigate and compare the positive rates of WMSDs between different industries, analyze the exposure status of long working hours, shift rotation, and job stress among key occupational groups, and evaluate the impacts of these factors on WMSDs in the manufacturing and service industries. Methods The study subjects were derived from key occupational populations in Yunnan Province, recruited by the Chinese National Occupational Health Literacy Monitoring Survey in 2022. A cross-sectional design was used for this survey. The key occupational populations were recruited from the secondary industry (manufacturing industry, metal mining and beneficiation industry, and non-metal mining and beneficiation industry) by stratified random sampling and from the tertiary industry (medical and healthcare industry, education industry, environmental sanitation industry, transportation industry, and express/takeaway delivery industry) by proportional probability sampling, and 12014 front-line workers were finally included as survey participants. General information, work-related factors (shift rotation, weekly working hours, job stress, etc.) and WMSDs assessment results were obtained through a web-based self-reported questionnaire, and the associations of long working hours, shift rotation, and job stress with WMSDs were analyzed using χ² test and logistic regression. Results The average positive rate of WMSDs among the key occupational groups in Yunnan Province was 77.2%. The positive rate of WMSDs in the secondary industry group was 69.4%, while it was 81.6% in the tertiary industry group, with a statistically significant difference (P<0.001). Among the eight surveyed sectors, the education sector had the highest positive rate of WMSDs (94.2%). The single-site WMSDs mainly involved the neck, shoulders, and low back. In the secondary industry, WMSDs was reported in 1−2 body parts, while in the tertiary industry, WMSDs was mainly reported in multiple (≥5) body parts. Long working hours (OR: 1.119, 1.165, 1.163, respectively), shift rotation (OR: 1.094, 1.199, 1.230, respectively), and job stress (OR: 1.795, 1.854, 2.006, respectively) were risk factors for WMSDs in the neck, shoulder, or low back, and all three were also risk factors for multi-site WMSDs. Moreover, as the number of involved body parts increased, the effects of long working hours and job stress became more pronounced. For 1-2, 3-4, and 5 or more body parts compared to no pain reported, their OR values were 0.971 (95%CI: 0.871, 1.082), 1.133 (95%CI: 1.004, 1.279), and 1.285 (95%CI: 1.155, 1.429) for long working hours, respectively, and the OR values were 1.009 (95%CI: 0.878, 1.160), 1.360 (95%CI: 1.174, 1.575), and 2.797 (95%CI: 2.471, 3.166) for job stress, respectively. Conclusion The positive rate of WMSDs is higher in the tertiary industry than that in the secondary industry among the key occupational groups in Yunnan Province. Long working hours, rotating shift work, and job stress could significantly increase the risk of WMSDs.