Objective:To investigate the value of a deep learning radiomics (DLR) nomogram model based on intra-tumoral and peri-tumoral MRI features for differentiating IgG4-related ophthalmic disease (IgG4-ROD) from orbital mucosa-associated lymphoid tissue (MALT) lymphoma.Methods:This was a case-control study. The clinical and imaging data of 233 patients pathologically confirmed with either IgG4-ROD or orbital MALT lymphoma were retrospective collected between January 2020 and December 2024 from the Second Hospital of Jilin University (Center 1) and Beijing Tongren Hospital, Capital Medical University (Center 2). Patients from Center 1 ( n=158) were used as the training cohort, while those from Center 2 ( n=75) served as the validation cohort. Among the cases, 102 were IgG4-ROD (70 in training, 32 in validation) and 131 were orbital MALT lymphoma (88 in training, 43 in validation). Univariate and multivariate logistic regression analyses were used to identify independent clinical imaging predictors and build a clinical imaging model. Based on T 1WI, T 2WI, and diffusion weighted images, intra-tumoral regions were manually delineated, a 2 mm peri-tumoral margin was automatically generated, and both regions were combined as a single region of interest for radiomics feature extraction. Deep learning features were extracted using a ResNet-50 backbone, and after feature selection and dimensionality reduction, a DLR model was constructed. The clinical imaging features and DLR features were integrated to build a combined nomogram model. Model performance in differentiating IgG4-ROD from orbital MALT lymphoma was assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis. The area under the curve (AUC) were compared using the DeLong test. Results:Bilateral orbital involvement ( OR=1.983, 95% CI 1.166-2.843, P=0.046) and extraocular muscle involvement ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as independent predictors for distinguishing IgG4-ROD from orbital MALT lymphoma and were used to construct the clinical model. Fourteen features (9 radiomics and 5 deep learning features) were selected for the DLR model, and a nomogram was developed. In the training set, the AUCs for the clinical model, DLR model, and nomogram were 0.762 (95% CI 0.712-0.812), 0.865 (95% CI 0.822-0.908), and 0.943 (95% CI 0.909-0.953), respectively. In the validation set, the AUCs were 0.733 (95% CI 0.675-0.791), 0.823 (95% CI 0.762-0.884), and 0.924 (95% CI 0.902-0.958), respectively. The nomogram showed significantly higher AUCs than those of the clinical and DLR models alone (training set: Z=3.92, 2.87, P0.001, P=0.004; validation set: Z=3.25, 2.46, P=0.001, 0.014). Calibration curves indicated good agreement between predicted and actual IgG4-ROD incidence, and decision curve analysis demonstrated the highest net benefit for the nomogram. Conclusion:A nomogram that incorporates both intra-tumoral and peri-tumoral DLR features and clinical imaging characteristics demonstrates excellent performance in distinguishing IgG4-ROD from orbital MALT lymphoma.

OBJECTIVE To compare the efficacy and safety of different daily doses of aspirin in the prevention of preeclampsia （PE）. METHODS The case-control studies and prospective randomized controlled trials on aspirin with daily dose ≥ 100 mg （trial group） vs. ＜100 mg （control group） in the prevention of PE were retrieved from PubMed， Medline， Embase， the Cochrane Library， CNKI， China Biomedical Literatue Database and Wanfang Data from base-building to January 2025. After literature screening， data extraction and quality evaluation， meta-analysis was performed by using RevMan 5.3 software. RESULTS A total of 11 literatures were included， involving 3 052 pregnant women. Meta-analysis showed the incidence of PE [RR＝0.63， 95%CI （0.53，0.76）， P＜0.000 01]， gestational hypertension [RR＝0.69， 95%CI （0.50，0.94），P＝0.02]， preterm birth [RR＝0.56， 95%CI （0.47，0.66）， P＜0.000 01]， and intrauterine growth retardation [RR＝0.73，95%CI （0.61，0.87），P＝0.000 5] in trial groups were significantly lower than control group. The incidence of postpartum hemorrhage between the two groups had no statistically significant difference [RR＝1.17， 95%CI （0.90，1.53），P＝0.25]. Subgroup analysis showed that the incidence of PE in Chinese pregnant women taking 150 mg of aspirin was significantly higher than taking 100 mg of aspirin [RR＝3.40， 95%CI （1.29， 8.93）， P＝0.01]； but there was no significant difference between the two groups in the incidences of postpartum hemorrhage， preterm birth （P＞0.05）. CONCLUSIONS Aspirin with daily dose ≥100 mg is more effective in preventing PE than daily dose ＜100 mg， with lower rates of gestational hypertension， preterm birth， and intrauterine growth retardation. It does not increase the risk of postpartum hemorrhage. For pregnant women in China， daily dose 100 mg of aspirin may be more effective in preventing PE than 150 mg.

Objective To investigate the inhibitory effect of MKK6(E)fusion protein on the growth of o-varian cancer graft tumors in nude mice and its possible mechanism.Methods A subcutaneous transplantation tumor model in nude mice was constructed using subcutaneous injection of human ovarian cancer HO8910PM cells,which were divided into model group,paclitaxel(positive control,3 mg/mL)group,MKK6(E)fusion protein(1.2 mmol/L)group and MKK6(E)fusion protein+SB202190(p38 agonist,10 μmol/L)group by numerical randomization table,each with 6 animals.The drug was administered continuously in the tail vein for 21 d,once every 3 d.At the end of the administration,the tumor was exfoliated and the tumor volume,mass and tumor inhibition rate were calculated.Serum carbohydrate antigen(CA)125 level was detected by enzyme linked immunosorbent assay(ELISA),histopathology of the tumor was detected by HE staining,and apoptosis of the tumor cells was detected by TUNEL staining.In addition,expression of Fibronectin,matrix metallo-peptidase(MMP)2,and MMP9 were detected by immunohistochemistry,apoptosis and the p38/ATF-2 pathway-related proteins were detected by Western blot.Results Compared with the model group,the tumor volume,mass and serum CA125 level of nude mice in the paclitaxel group and the MKK6(E)fusion protein group were reduced,the tumor suppression rate and the apoptosis rate of cancer cells were increased,the volume of cancer cells in the transplanted tumor tissue was reduced,the nucleus was lightly stained,the di-viding heterogeneity was reduced compared with that of the model group,and the large area of lamellar nec-rotic zone and apoptotic cells were seen,and the expression of Fibronectin,MMP2 and MMP9 was reduced.Bax and Cleaved caspase 3 expression was up-regulated,and Bcl-2 expression and phosphorylated p38(p-p38)/p38 and p-ATF-2/ATF-2 were down-regulated(P＜0.05).Compared with the MKK6(E)fusion pro-tein group,nude mice in the MKK6(E)fusion protein+SB202190 group showed increased tumor volume,mass and serum CA125 levels,decreased tumor suppression and cancer cell apoptosis,better cancer cell status,decreased necrotic areas,increased expression of Fibronectin,MMP2 and MMP9,and down-regulated Bax and Cleaved caspase 3 expression was down-regulated,and Bcl-2 expression and p-p38/p38 and p-ATF-2/ATF-2 were up-regulated(P＜0.05).While p-ERK/ERK and p-JNK/JNK were compared among the 4 groups,the difference was not statistically significant(P＞0.05).Conclusion MKK6(E)fusion protein inhibits the growth of ovarian cancer subcutaneous graft tumors,and its mechanism may be related to the inhibition of p38/ATF-2 signa-ling pathway activation.

Objective To compare and analyze the biological effects of two types of helmets,which have different masses and centroids,on the neck of pilots under rapid braking condition,and provide new ideas for improving the ergonomic design of helmets for pilots.Methods A finite element model of the head,neck,helmet,and restraint system was established using Hyper Mesh 14.0 software.Finite element simulation was used to study the neck biological effects of pilots wearing different helmets for rapid braking.Results After wearing Type Ⅰ and Type Ⅱ helmets,the trend,occurrence time,and location of the maximum stress borne by each vertebra and intervertebral disc are basically consistent.The maximum stress on the vertebrae above C3 is smaller when wearing a Type Ⅰ helmet,while the maximum stress on the vertebrae below C3 is smaller when wearing a Type Ⅱ helmet.The maximum stress on the C2～C3 intervertebral disc is relatively small when wearing a TypeⅠhelmet,while the intervertebral discs below it are relatively small when wearing a Type Ⅱ helmet.The ligament elongation rate and maximum neck injury index Nij of wearing Type Ⅰ helmets are both relatively high.Conclusion Type Ⅰ helmet has a significant biological impact on the neck of pilots during rapid braking.

Objective: To investigate the prevalence and influencing factors of menopausal syndrome among postmenopausal women in Pan'an County, Zhejiang Province, so as to provide the basis for guiding the health management of postmenopausal women. Methods: From May 2023 to April 2024, the postmenopausal women aged 40 to 69 years in Pan'an County were selected using the random cluster sampling method. Demographic information, lifestyle and prevalence of gynecological diseases were collected through questionnaire surveys. The prevalence of menopausal syndrome was assessed by modified Kupperman Score Scale. Factors affecting menopausal syndrome were analyzed by a multivariable logistic regression model. Results: A total of 816 postmenopausal women were surveyed, with an mean age of (57.63±2.92) years and a mean natural menopause age of (49.85±2.13) years. There were 574 cases with menopausal syndrome, with a prevalence of 70.34%. Flashes and sweating, insomnia and irritability were common symptoms, accounting for 62.87%, 47.43% and 41.18%, respectively. Multivariable logistic regression analysis showed that monthly personal income of ≤5 000 yuan (<3 000 yuan, OR=3.124, 95%CI: 1.829-5.335; 3 000-5 000 yuan, OR=2.399, 95%CI: 1.370-4.201) and having gynecological diseases (OR=1.970, 95%CI: 1.292-3.004) were associated with a higher risk of menopausal syndrome, while average (OR=0.141, 95%CI: 0.072-0.276) or sufficient sleep quality (OR=0.095, 95%CI: 0.049-0.185) were associated with a lower risk of menopausal syndrome. Conclusion The prevalence of menopausal syndrome among postmenopausal women in Pan'an County is relatively high, and is mainly influenced by personal economic status, sleep quality and the presence of gynecological diseases.

Objective:To examine the distribution of pathogens that cause postoperative nosocomial infections in patients with rectal cancer(RC)and to construct a predictive nomogram for nosocomial infection.Methods:The clinical data of 1537 RC patients admitted to Sir Run Run Shaw Hospital between January 2021 and December 2022 were collected.Patients were assigned 1∶1 by propensity score matching(PSM)to the infection group(n=83)and control group(n=83)based on the occurrence of nosocomial infection.The dis-tribution and drug resistance of bacteria in patients with nosocomial infection were analyzed.Risk factors for postoperative nosocomial infection were identified by least absolute shrinkage and selection operator(LASSO)regression,and a predictive nomogram was con-structed using multivariate logistics regression.The predictive performance of the model was evaluated by receiver operating character-istic(ROC)curve,calibration curve,and decision curve analysis(DCA).Results:A total of 93 strains of pathogens were isolated from the 83 infected patients,including 62 strains of Gram-negative bacteria(66.67%;predominantly Escherichia coli and Pseudomonas ae-ruginosa),25 strains of Gram-positive bacteria(26.88%;mainly Enterococcus faecalis),and 6 strains of fungi(6.45%;all Candida albicans).LASSO and multivariate logistics regression showed that smoking(odds ratio[OR]=3.97,95%CI=1.27-12.43),the dwelling time of drainage tube(OR=1.19,95%CI=1.08-1.30),difference in preoperative and postoperative neutrophil counts(OR=1.23,95%CI=1.01-1.49),and difference between preoperative and postoperative C-reactive protein levels(OR=1.05,95%CI=1.03-1.07)were inde-pendent risk factors for postoperative nosocomial infection in RC patients.The area under the ROC curve of the nomogram constructed based on the above factors was 0.933(95%CI=0.896-0.969).The calibration curve showed that the predicted risk was in good agree-ment with the actual observed risk of infection.In addition,DCA demonstrated that the nomogram has good clinical utility and high net clinical benefits in predicting nosocomial infection.Conclusion:The nomogram constructed in this study has a good predictive perfor-mance in postoperative nosocomial infection in RC patients.

Objective:To investigate the value of a deep learning radiomics (DLR) nomogram model based on intra-tumoral and peri-tumoral MRI features for differentiating IgG4-related ophthalmic disease (IgG4-ROD) from orbital mucosa-associated lymphoid tissue (MALT) lymphoma.Methods:This was a case-control study. The clinical and imaging data of 233 patients pathologically confirmed with either IgG4-ROD or orbital MALT lymphoma were retrospective collected between January 2020 and December 2024 from the Second Hospital of Jilin University (Center 1) and Beijing Tongren Hospital, Capital Medical University (Center 2). Patients from Center 1 ( n=158) were used as the training cohort, while those from Center 2 ( n=75) served as the validation cohort. Among the cases, 102 were IgG4-ROD (70 in training, 32 in validation) and 131 were orbital MALT lymphoma (88 in training, 43 in validation). Univariate and multivariate logistic regression analyses were used to identify independent clinical imaging predictors and build a clinical imaging model. Based on T 1WI, T 2WI, and diffusion weighted images, intra-tumoral regions were manually delineated, a 2 mm peri-tumoral margin was automatically generated, and both regions were combined as a single region of interest for radiomics feature extraction. Deep learning features were extracted using a ResNet-50 backbone, and after feature selection and dimensionality reduction, a DLR model was constructed. The clinical imaging features and DLR features were integrated to build a combined nomogram model. Model performance in differentiating IgG4-ROD from orbital MALT lymphoma was assessed using receiver operating characteristic curves, calibration curves, and decision curve analysis. The area under the curve (AUC) were compared using the DeLong test. Results:Bilateral orbital involvement ( OR=1.983, 95% CI 1.166-2.843, P=0.046) and extraocular muscle involvement ( OR=1.246, 95% CI 1.079-1.764, P=0.015) were identified as independent predictors for distinguishing IgG4-ROD from orbital MALT lymphoma and were used to construct the clinical model. Fourteen features (9 radiomics and 5 deep learning features) were selected for the DLR model, and a nomogram was developed. In the training set, the AUCs for the clinical model, DLR model, and nomogram were 0.762 (95% CI 0.712-0.812), 0.865 (95% CI 0.822-0.908), and 0.943 (95% CI 0.909-0.953), respectively. In the validation set, the AUCs were 0.733 (95% CI 0.675-0.791), 0.823 (95% CI 0.762-0.884), and 0.924 (95% CI 0.902-0.958), respectively. The nomogram showed significantly higher AUCs than those of the clinical and DLR models alone (training set: Z=3.92, 2.87, P0.001, P=0.004; validation set: Z=3.25, 2.46, P=0.001, 0.014). Calibration curves indicated good agreement between predicted and actual IgG4-ROD incidence, and decision curve analysis demonstrated the highest net benefit for the nomogram. Conclusion:A nomogram that incorporates both intra-tumoral and peri-tumoral DLR features and clinical imaging characteristics demonstrates excellent performance in distinguishing IgG4-ROD from orbital MALT lymphoma.

As the global population ages and cancer diagnostic and treatment technologies improve, the number of elderly cancer survivors continues to increase, and their complex care needs challenge the traditional mono-disciplinary care model. This paper explores the dilemmas of implementing a long-term care system and suggestions for future research through a comprehensive overview of the care needs of elderly cancer survivors and the progress of interdisciplinary research, with the aim of providing a theoretical basis and practical reference for improving the long-term care system and enhancing patients' quality of life.

Objective:To analyze the epidemiological characteristics and trends of preterm births in China using medical institution survey data, thereby providing epidemiological data support for perinatal care.Methods:Based on a nationwide sampling survey on healthcare quality data from 2017 to 2022, this study included 3 547, 4 436, 4 513, 4 535, 5 068, and 5 790 medical institutions, with 7 039 107, 8 926 441, 9 006 420, 7 051 984, 7 311 862, and 7 354 062 parturient women, respectively. The overall rates of preterm birth (live births at 28 to 36 +6 weeks of gestation/overall live births) and early preterm birth (live births at 28 to <34 weeks of gestation/overall live births) were calculated at the national level, across diverse provinces, autonomous regions, municipalities and Xinjiang Production and Construction Corps, and for various levels of medical institutions. Generalized estimating equations were used to analyze the influence of maternal characteristics and medical institution characteristics on the rates of preterm birth and early preterm birth. Results:From 2017 to 2022, both the preterm birth rate and the early preterm birth rate in China showed a continuous increase. The preterm birth rate rose from 5.13% (363 036/7 079 454) in 2017 to 6.56% (487 150/7 424 734) in 2022, and the early preterm birth rate increased from 1.32% (118 021/8 971 870) in 2018 to 1.43% (106 157/7 424 734) in 2022. These rates showed an overall increasing trend in private, secondary public specialty, and general hospitals. In tertiary public specialty hospitals, these rates fluctuated around 8.0% and 2.0% from the year 2018, respectively, while in tertiary public general hospitals, these rates peaked in 2020 at 8.63% (205 570/2 381 523) and 2.19% (52 197/2 381 523), respectively. Compared with 2017, by 2022, the preterm birth rate had increased to varying degrees in all provinces, autonomous regions, municipalities and Xinjiang Production and Construction Corps, except for Henan Province [preterm birth rate in 2017 was 6.22% (27 173/437 187); preterm birth rate in 2022 was 5.83% (37 604/645 104)]. As for the early preterm birth rate, it showed a decline in Fujian, Guangdong, Guangxi, Hainan, Henan, Jiangsu, Shanghai, Xinjiang, Yunnan, and Zhejiang, but had increased to varying degrees in all other provinces , autonomous regions, municipalities and Xinjiang Production and Construction Corps across the country. The grade and location of medical institutions both had a significant impact on the preterm birth rate and early preterm birth rate (both P<0.05). For every 1% increase in the proportions of multiparous women, women of advanced maternal age, or twin pregnancies, the preterm birth rate increased by 0.014%, 0.042%, and 0.763%, and the early preterm birth rate increased by 0.004%, 0.013%, and 0.239%, respectively (all P<0.05). Conclusion:From 2017 to 2022, the preterm birth rate and early preterm birth rate in China have continued to rise, reflecting the dual challenges of changing characteristics in the childbearing population and the uneven distribution of medical and health resources faced by maternal and child healthcare in China.

As the global population ages and cancer diagnostic and treatment technologies improve, the number of elderly cancer survivors continues to increase, and their complex care needs challenge the traditional mono-disciplinary care model. This paper explores the dilemmas of implementing a long-term care system and suggestions for future research through a comprehensive overview of the care needs of elderly cancer survivors and the progress of interdisciplinary research, with the aim of providing a theoretical basis and practical reference for improving the long-term care system and enhancing patients' quality of life.