To develop and validate a model for predicting intensive care unit (ICU) mortality risk in patients with malignant tumors complicated by acute respiratory failure (ARF) based on an explainable machine learning framework.

Background Per- and poly-fluoroalkyl substances (PFAS) can influence gestational diabetes mellitus (GDM); however, current studies on their association are limited and have yielded inconsistent findings. Objective To investigate the association between maternal exposure to PFAS, as measured by urinary concentrations in early pregnancy, and the risk of developing GDM. Methods Based on the Wuhu Birth Cohort in Anhui Province conducted between 2020 and 2023, this study included 1910 pregnant women. Urine samples were collected during the first trimester, and a 75 g oral glucose tolerance test (OGTT) was completed at 24–28 gestational weeks. The concentrations of six PFAS in urine were measured using ultra-performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS). Participants were categorized into low, medium, and high exposure groups according to tertiles of individual PFAS concentrations. Logistic regression analysis was employed to assess the potential impact of early-pregnancy PFAS exposure levels on the risk of GDM, with stratified analyses by maternal age and fetal sex. A generalized weighted quantile sum regression (gWQS) model was applied to evaluate the relative weight distribution of the six PFAS in their mixture effect. Results The logistic regression results revealed that both medium exposure to perfluorohexane sulfonate (PFHxS) (OR=1.475, 95%CI: 1.040, 2.093) and high exposure to perfluorononanoic acid (PFNA) (OR=1.430, 95%CI: 1.013, 2.018) were positively associated with diagnosed GDM. This association was more pronounced among women older than 28 years. Among pregnant women carrying male fetuses, high-level exposures to per fluorohexanoic acid (PFHxA) (OR=1.708, 95%CI: 1.006, 2.899) and PFHxS (OR=2.116, 95%CI: 1.247, 3.584) showed positive associations with diagnosed GDM. In contrast, among those carrying female fetuses, moderate perfluorooctanesulfonic acid (PFOS) exposure was associated with a lower risk of GDM (OR=0.542, 95%CI: 0.311, 0.946). The gWQS results demonstrated that PFOS (0.48) and perfluorobutane sulfonate (PFBS) (0.34) contributed the most to the mixture effect. Conclusion Early-pregnancy exposure to PFAS (particularly PFHxS and PFNA) may be an etiological factor for GDM, with maternal age and fetal sex potentially acting as effect modifiers in this association.

Objective To analyze the quality of medical record home pages for discharged patients in a tertiary hospital in Guangzhou in 2023 based on the dual dimensions of Diagnosis-Related Groups(DRG)and Disease Intervention Program(DIP),and to provide a basis for improving the refinement of medical record home page quality management.Methods Dis-charge medical records from a tertiary general hospital in 2023 were selected.All medical records were grouped using DRG,while medical records under Guangzhou medical insurance and cross-province medical insurance implemented under DIP were simulated for DIP grouping.The writing defects in the discharge medical records were analyzed,as well as the DRG grouping,RW,and DIP standard scores of medical records with home page filling defects.Results Among 172 230 discharge medical records,171 786 were grouped into DRG,91 768 were grouped into DIP,and 91 604 were grouped into both DRG and DIP.A significant positive correlation was found between RW and DIP standard scores(r2=0.681,P＜0.001).Among the 91 604 medical records grouped into both DRG and DIP,1 942(2.12％)had writing defects,including 837(0.91％)with home page defects.DRG groups with more home page defect records included NC15,HK2,EJ13,EB15,HJ13,and RE19.Conclusion Quality defects in medical record home pages impact the accuracy of DRG and DIP grouping.Systematic measures such as strengthening medical record writing training and establishing scientific reward and punishment mechanisms should be implemented to provide data sup-port for the further advancement of DRG/DIP payment reform.

AIM:This study aims to investigate the effects of aerobic exercise on hypothalamic autophagy and central leptin resistance in obese mice,and to explore the potential mechanisms.METHODS:Forty male C57BL/6J mice,aged 7 to 8 weeks,were randomly assigned to 5 groups:normal control(CON)group,high-fat diet(HFD)group,HFD+exercise(HFD+Exe)group,HFD+phosphate-buffered saline(PBS)group,and HFD+rilmenidine(autophagy ago-nist)group,with 8 mice in each group.Additionally,twelve fibronectin type Ⅲ domain-containing protein 5(Fndc5)gene(encoding irisin precursor protein)knockout(Fndc5 KO)mice were randomly allocated to Fndc5 KO+HFD group and Fndc5 KO+HFD+Exe group,with 6 mice in each group.All mice were fed for 28 weeks.The mice in CON group re-ceived a normal diet,while those in the remaining groups were provided with an HFD.The mice in HFD+Exe and Fndc5 KO+HFD+Exe groups engaged in aerobic treadmill exercise while continuing an HFD from weeks 17 to 28.The mice in HFD+PBS group received intraperitoneal injections of PBS as a control,while those in HFD+rilmenidine group received in-traperitoneal injections of rilmenidine(10 mg?kg-1?d-1),4 times a week over a total duration of 12 weeks(weeks 17 to 28).Following the intervention,serum metabolite levels,as well as concentrations of leptin and irisin,were quantified by ELISA.Morphological alterations in the liver and white adipose tissues were evaluated through oil red O staining and he-matoxylin-eosin(HE)staining.Western blot was utilized to assess the hypothalamic protein levels of autophagy markers,autophagy-related protein 7(ATG7),beclin-1,microtubule-associated protein 1 light chain 3(LC3)and p62,and leptin resistance markers,suppressor of cytokine signaling 3(SOCS3)and protein tyrosine phosphatase 1B(PTP1B).RE-SULTS:Observations of mouse phenotypes indicated that HFD feeding significantly increased body weight,blood lipid content and serum leptin level(P<0.05).The results of HE and oil red O staining demonstrated that HFD feeding marked-ly promoted lipid accumulation in the liver and caused ballooning of white adipocytes.Western blot analyses revealed that HFD feeding significantly down-regulated the protein levels of ATG7,beclin-1 and LC3-Ⅱ/LC3-I,but up-regulated the pro-tein level of p62(P<0.05),thus reducing cellular autophagy capacity.Furthermore,HFD feeding elevated the protein levels of leptin resistance markers SOCS3 and PTP1B(P<0.05).Aerobic exercise and autophagy agonist were found to partially reverse these changes,enhancing cellular autophagy capacity and alleviating leptin resistance.However,these effects were diminished after knockout of Fndc5 gene,further substantiating the role of irisin in exercise-mediated en-hancement of cellular autophagy and attenuation of leptin resistance.CONCLUSION:Aerobic exercise alleviates hypo-thalamic autophagy defect and central leptin resistance in obese mice,which may be associated with exercise-induced irisin.

Objective:To explore the application value of the artificial intelligence (AI) morphological assisted analysis system in the pre-classification of blood cells in patients with acute myeloid leukemia, myelodysplasia-related (AML-MR).Methods:A retrospective analysis was conducted on the bone marrow and peripheral blood cell morphology of patients initially diagnosed with AML-MR at Taizhou Hospital in Zhejiang Province from September 1, 2022, to December 31, 2023. A total of 44 patients, including 25 males and 19 females, with a median age of 71 (63.5, 75.3) years. Bone marrow and peripheral blood morphology were examined using the Morphogo cell morphology assisted analysis system, with the artificial classification results serving as the gold standard. A confusion matrix was constructed to evaluate the precision, sensitivity, and specificity of the AI system in identifying various cell types in bone marrow and peripheral blood for AML-MR diagnosis. The impact of dysplastic hematopoiesis on AI pre-classification was analyzed by comparing AI and manual classification results.Results:The AI system completed the pre-classification of 44 bone marrow smears and 42 corresponding peripheral blood smears from AML-MR patients. For bone marrow smears, the precision, sensitivity, and specificity of AI in pre-classifying blast cells were 85.78%, 91.01%, and 94.58%, respectively. For peripheral blood smears, these values were 87.11%, 87.05%, and 98.29%, respectively. The precision and sensitivity of AI in pre-classifying promyelocytes were 54.26% and 46.93%, respectively, while for monocytes, they were 58.16% and 68.34%, both lower than those for blast cells. The precision and sensitivity of AI in identifying myelocytes and metamyelocytes also decreased (77.47%, 66.25% and 81.91%, 63.29%, respectively). The precision and sensitivity of AI in pre-classifying erythroblasts/proerythroblasts (67.71%, 69.89%) were lower than those for polychromatic and orthochromatic normoblasts (83.43%, 85.53% and 92.97%, 86.96%, respectively). The confusion matrix and comparative analysis of AI and manual classification indicated that the decline in AI pre-classification precision and sensitivity was due to frequent misclassification between promonocytes and monocytes, as well as between monocytes and promyelocytes. Additionally, this decline is associated with dysplasia. However, the impact of dysplasia on the AI pre-classification of mature-stage granulocytes was minimal.Conclusion:The AI system demonstrated high precision, sensitivity, and specificity in pre-classifying blast cells in bone marrow and peripheral blood smears from AML-MR patients. The AI-assisted morphological analysis system can be effectively utilized for the pre-classification of blood cells in AML-MR patients.

Objective:To establish a model based on the characteristics of breast cancer ultrasound images through deep learning methods to predict the risk of axillary lymph node metastasis（ALNM）in patients with breast cancer（maximum diameter ≤2.5 cm）before surgery.Methods:A total of 419 patients（3 433 breast tumor ultrasound images）with breast cancer（maximum diameter ≤2.5 cm）who underwent axillary lymph node dissection at Beijing Tiantan Hospital，Capital Medical University from January 2019 to December 2024 were retrospectively included. According to the pathological results of axillary lymph nodes，they were divided into 220 cases in the ALNM occurrence group（positive group）and 199 cases in the non-ALNM occurrence group（negative group）. The breast cancer ultrasound images of the two groups of cases were randomly classified into the training set（2 404 images），the validation set（687 images）and the test set（342 images）according to a ratio of 7∶2∶1. YOLOv8 was used as the basic model of You Only Look Once（YOLO）and optimized. The optimized model was applied to locate and capture the potential ultrasound features of breast cancer cases in the training set. A prediction model was constructed based on the captured ultrasound features. The model was adjusted and optimized through the validation set，and then matched with the case images in the test set. The confusion classification matrix graph and the curve graph for measuring the model performance were used to evaluate the model prediction performance and interpret the model，and the efficacy of this model in identifying breast cancer patients at risk of ALNM was analyzed.Results:There were statistically significant differences between the positive and negative groups in terms of the pathological maximum diameter of breast tumors，pathological T staging，the differentiation degree，the presence of distant metastasis，the maximum diameter measured by ultrasound，the quadrant of breast tumor occurrence，the Breast Imaging - Reporting and Data System（BI-RADS）classification of breast tumors，and the presence of abnormal ultrasound features of lymph node（all P<0.05）. The established deep learning model could automatically perform bounding box localization for the breast cancer of patients.The breast tumors in the positive group had potential ultrasound features that could be captured by the model compared with those in the negative group. The mean average precision（mAP）50 was 0.883，mAP 50-95 was 0.636，PR-AUC was 0.884 5，strict PR-AUC was 0.636 4，the sensitivity was 90.5%，and the specificity was 91.2%，and it had a good predictive efficacy. Conclusions:This prediction model based on the ultrasound characteristics of breast cancer through deep learning can effectively predict breast cancer（maximum diameter ≤ 2.5 cm）with the risk of ALNM，providing an effective basis for the clinical management of axillary lymph nodes in breast cancer patients.

AIM:This study aims to investigate the effects of aerobic exercise on hypothalamic autophagy and central leptin resistance in obese mice,and to explore the potential mechanisms.METHODS:Forty male C57BL/6J mice,aged 7 to 8 weeks,were randomly assigned to 5 groups:normal control(CON)group,high-fat diet(HFD)group,HFD+exercise(HFD+Exe)group,HFD+phosphate-buffered saline(PBS)group,and HFD+rilmenidine(autophagy ago-nist)group,with 8 mice in each group.Additionally,twelve fibronectin type Ⅲ domain-containing protein 5(Fndc5)gene(encoding irisin precursor protein)knockout(Fndc5 KO)mice were randomly allocated to Fndc5 KO+HFD group and Fndc5 KO+HFD+Exe group,with 6 mice in each group.All mice were fed for 28 weeks.The mice in CON group re-ceived a normal diet,while those in the remaining groups were provided with an HFD.The mice in HFD+Exe and Fndc5 KO+HFD+Exe groups engaged in aerobic treadmill exercise while continuing an HFD from weeks 17 to 28.The mice in HFD+PBS group received intraperitoneal injections of PBS as a control,while those in HFD+rilmenidine group received in-traperitoneal injections of rilmenidine(10 mg?kg-1?d-1),4 times a week over a total duration of 12 weeks(weeks 17 to 28).Following the intervention,serum metabolite levels,as well as concentrations of leptin and irisin,were quantified by ELISA.Morphological alterations in the liver and white adipose tissues were evaluated through oil red O staining and he-matoxylin-eosin(HE)staining.Western blot was utilized to assess the hypothalamic protein levels of autophagy markers,autophagy-related protein 7(ATG7),beclin-1,microtubule-associated protein 1 light chain 3(LC3)and p62,and leptin resistance markers,suppressor of cytokine signaling 3(SOCS3)and protein tyrosine phosphatase 1B(PTP1B).RE-SULTS:Observations of mouse phenotypes indicated that HFD feeding significantly increased body weight,blood lipid content and serum leptin level(P<0.05).The results of HE and oil red O staining demonstrated that HFD feeding marked-ly promoted lipid accumulation in the liver and caused ballooning of white adipocytes.Western blot analyses revealed that HFD feeding significantly down-regulated the protein levels of ATG7,beclin-1 and LC3-Ⅱ/LC3-I,but up-regulated the pro-tein level of p62(P<0.05),thus reducing cellular autophagy capacity.Furthermore,HFD feeding elevated the protein levels of leptin resistance markers SOCS3 and PTP1B(P<0.05).Aerobic exercise and autophagy agonist were found to partially reverse these changes,enhancing cellular autophagy capacity and alleviating leptin resistance.However,these effects were diminished after knockout of Fndc5 gene,further substantiating the role of irisin in exercise-mediated en-hancement of cellular autophagy and attenuation of leptin resistance.CONCLUSION:Aerobic exercise alleviates hypo-thalamic autophagy defect and central leptin resistance in obese mice,which may be associated with exercise-induced irisin.

Objective To analyze the quality of medical record home pages for discharged patients in a tertiary hospital in Guangzhou in 2023 based on the dual dimensions of Diagnosis-Related Groups(DRG)and Disease Intervention Program(DIP),and to provide a basis for improving the refinement of medical record home page quality management.Methods Dis-charge medical records from a tertiary general hospital in 2023 were selected.All medical records were grouped using DRG,while medical records under Guangzhou medical insurance and cross-province medical insurance implemented under DIP were simulated for DIP grouping.The writing defects in the discharge medical records were analyzed,as well as the DRG grouping,RW,and DIP standard scores of medical records with home page filling defects.Results Among 172 230 discharge medical records,171 786 were grouped into DRG,91 768 were grouped into DIP,and 91 604 were grouped into both DRG and DIP.A significant positive correlation was found between RW and DIP standard scores(r2=0.681,P＜0.001).Among the 91 604 medical records grouped into both DRG and DIP,1 942(2.12％)had writing defects,including 837(0.91％)with home page defects.DRG groups with more home page defect records included NC15,HK2,EJ13,EB15,HJ13,and RE19.Conclusion Quality defects in medical record home pages impact the accuracy of DRG and DIP grouping.Systematic measures such as strengthening medical record writing training and establishing scientific reward and punishment mechanisms should be implemented to provide data sup-port for the further advancement of DRG/DIP payment reform.

Objective:To quantitatively assess the participation of social medical insurance in palliative care medical insurance payment policies in different regions of China,explore the characteristics,find the weak points,and provide a basis for subsequent policy formulation.Methods:Based on text mining and literature review,it established a Policy Modeling Consistency(PMC)index model with 9 primary indicators and 38 secondary indicators,and quantitatively evaluated the palliative care insurance payment policies from 2017 to 2024.Results:A total of 24 policies were included,and the overall PMC index was 5.65,which was an acceptable grade,including 10 good grade policies,13 acceptable grade policies,and 1 poor grade policy.Conclusion:Overall,palliative care medical insurance payment policies are good,with relatively complete provisions in terms of coverage,medical insurance payment mechanism,supervision and management.However,there are still shortcomings in terms of financing channels,policy recipients,and incentive constraints.The follow-up should focus on broadening the financing channels,expanding the scope of recipients,and improving the incentive and constraint mechanism,so as to promote the optimization and improvement of the palliative care insurance payment system.

Objective: To explore the association of latent profiles of mobile phone dependence and self control with physical exercise among junior high school students, so as to provide references for the prevention of mobile phone dependence and the improvement of self control among junior high school students. Methods: From April to May 2024, a stratified random cluster sampling method was used to select a total of 2 311 students from grade 7 to grade 9 in three public junior high schools in Xiangxi Autonomous Prefecture, Hunan Province. Latent profile analysis was conducted to identify the latent profiles of mobile phone dependence and self control among junior high school students. Pearson correlation analysis was used to examine the correlation between mobile phone dependence and self control, and Chi square test was used to analyze the distribution differences of latent profiles of adolescents across different demographic characteristics. Multiple Logistic regression analysis was applied to explore the association between mobile phone dependence, self control, and physical exercise. Results: Four latent profiles of mobile phone dependence and self control were identified: low dependence-moderate self control group ( n =885, 38.3%), moderate dependence-low self control group ( n =910, 39.4%), high dependence-no self control group ( n =232, 10.0%), and no dependence-high self control group ( n =284, 12.3%). Significant differences were observed in the distribution of latent profiles across gender, grade and only child status ( χ 2=10.85, 35.72, 13.85， P <0.05). Logistic regression analysis showed that, after controlling for demographic variables, compared with the low dependence-moderate self control group, physical exercise was negatively associated with the moderate dependence-low self control group ( OR =0.79) and the high dependence-no self control group ( OR =0.81), while positively associated with the no dependence-high self control group ( OR =1.58) ( P <0.01). Conclusions The influence of physical exercise on junior high school students different potential profile types of mobile phone dependence and self control is different. Schools and families should adopt targeted physical exercise interventions based on the characteristics of different profiles to promote the physical and mental health of junior high school students.