Under the trend of increasing aging， integrated elderly care and medical services is an important measure to optimize the supply of elderly care services and promote the good death of the elderly. Using the cooperative production theory and the classical grounded theory， a qualitative analysis was conducted on 38 cases of elderly palliative care and 25 cases of hospital-based palliative care under the integrated elderly care and medical services model from a hospital in Nanning City using Nvivo 20.0 software. This paper found that the integrated elderly care and medical services mode emphasized the deep integration of medical and elderly care services by integrating resources and improving service efficiency， to achieve the basic experience of comprehensive health care for the elderly. The promotion of these experiences has a positive significance for building a multi-agent cooperative production system， strengthening personnel training， perfecting the performance distribution mechanism， and further promoting the development of the national palliative care pilot.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Objective To observe the value of machine learning(ML)models based on brain functional network features combining clinical indicators for predicting postoperative outcomes of patients with drug-resistant mesial temporal lobe epilepsy(DR-mTLE).Methods Totally 84 patients with unilateral DR-mTLE who underwent surgery were retrospectively enrolled and classified into seizure free(SF)group(n=55)and non-seizure free(NSF)group(n=29)according to one-year postoperative follow-up.Clinical data were analyzed to screen independent predictors of postoperative outcomes.Based on brain preoperative resting-state functional MRI,brain functional networks were constructed using graph theory analysis,and 587 features were extracted.Five-fold cross validation was used to divide the data into training set and test set,then the optimal brain functional network features related to postoperative outcomes of DR-mTLE patients were selected.Combining with clinically relevant independent predictors,ML models were constructed using classifiers including Gaussian process(GP),logistic regression(LR),support vector machine(SVM)and quadratic discriminant analysis(QDA),respectively,and the prediction efficacy,calibration and clinical value of each ML model were evaluated.Results Both course of disease and lesion location were clinically relevant independent predictors of postoperative outcome of DR-mTLE patients(OR=0.928,5.710,P=0.010,0.016).Four optimal brain function network features were selected,including betweenness centrality of the third zone of cerebellar vermis,degree centrality of right globus pallidus,nodal efficiency of temporal left inferior temporal gyrus and nodal clustering coefficient of left inferior parietal lobule.The average area under the curve(AUC)of GP,LR,SVM and QDA models in test set was 0.868,0.864,0.875 and 0.870,respectively.Calibration curves and decision curve analysis indicated that each ML model had good calibration and high clinical net benefit.Conclusion ML models based on brain functional network features combining with clinical indicators could be used to effectively predict postoperative outcomes in DR-mTLE patients.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Objective: This study aimed to systematically evaluate potential causal relationships between nine cathepsins and female infertility using Mendelian randomization (MR) methods. Methods: A bidirectional MR analysis was conducted utilizing single nucleotide polymorphisms as instrumental variables to investigate the potential causal effects between nine cathepsins and female infertility. Genetic data on female infertility were sourced from the FinnGen study, and cathepsin-related data were obtained from genome-wide association studies datasets of European ancestry. Results: Elevated levels of cathepsin E were significantly and inversely associated with the risk of female infertility, suggesting a potential protective role. This finding was further supported by multivariable MR analysis. However, no significant associations were observed between the other eight cathepsins and female infertility. Conclusion This study represents the first systematic MR analysis to identify a potential protective effect of cathepsin E on female infertility.

Objective:To investigate the clinical characteristics of adult patients with autoimmune disease-associated hemophagocytic syndrome (AID-HPS) and enhance clinical recognition of this condition.Methods:A retrospective analysis was performed on 85 adult AID-HPS patients admitted to the department of rheumatology and immunology at Peking Union Medical College Hospital from January 2012 to December 2020. Clinical data included demographics, predisposing factors, manifestations, laboratory/imaging findings, treatments, and outcomes. Patients were stratified into three groups based on underlying AIDs: adult-onset Still′s disease with HPS (AOSD-HPS) group, systemic lupus erythematosus with HPS (SLE-HPS) group, and other AID with HPS (other AID-HPS) group. Comparative analyses were conducted to identify intergroup differences. Continuous variables were analyzed using one-way ANOVA, Welch′s test, or Kruskal-Wallis′s test based on data distribution and homogeneity of variance. Categorical variables (rates and proportions) were compared with the chi-square test or Fisher-Freeman-Halton exact test according to expected cell frequencies.Results:Among 85 patients, 67 were female. Underlying AIDs included AOSD (32 cases, 37.6%), SLE (32 cases, 37.6%), and other AIDs (21 cases, 24.7%). Infections (≥1 type) were identified in 54 patients (63.5%), predominantly viral (48 cases, 56.5%), including cytomegalovirus (CMV) (40 cases), Epstein-Barr virus (EBV) (11 cases), and 6 cases were coinfected with both CMV and EBV. All patients presented with fever; hepatomegaly, splenomegaly, and lymphadenopathy were observed in 39 (45.9%), 59 (69.4%), and 70 (82.4%) cases, respectively. Additional manifestations included arthralgia (63 cases, 74.1%) and rash (65 cases, 76.5%). Pancytopenia in 31 cases (36.5%) and bicytopenia in 29 cases (34.1%). Liver dysfunction was noted in 79 cases (92.9%). Elevated lactate dehydrogenase (LDH) (83 cases, 97.6%), elevated triglyceride (TG) (76 cases, 89.4%), decreased fibrinogen (Fbg) (55 cases, 64.7%), and elevated serum ferritin (SF) (84 cases, 98.8%) were common. Elevated soluble CD25(sCD25) (53cases) and reduced NK cell activity (49 cases) were observed. Bone marrow examination revealed hemophagocytosis in 49 cases. There were statistically significant differences in age( F=3.763, P=0.031), lymphadenopathy( χ2=7.098, P=0.029), rash( χ2=12.816, P=0.002), reductions in WBC( H=22.284, P<0.001)、NEU( H=18.882, P<0.001)、PLT( H=15.127, P=0.001), and elevations in LDH( H=7.842; P=0.020)、TG( H=6.177, P=0.046)、CRP( H=6.915, P=0.032)、SF( H=9.661, P=0.008)、sCD25( χ2=5.154, P=0.035) among the three groups: (1) The SLE-HPS group was significantly younger [(28.1 ± 10.4) years) than the other AID-HPS group [(39.5 ± 17.3) years, P=0.028]. (2) The AOSD-HPS group had higher incidence rates of lymphadenopathy (93.8%) and rash (93.8%) than the SLE-HPS group (68.8% and 56.3%, respectively), (lymphadenopathy: χ2=7.098, P=0.029; rash: χ2=12.816, P=0.002). (3) ① WBC in the SLE-HPS group [1.62 (1.18, 2.92) ×10 9/L] were significantly lower than those in the AOSD-HPS group [5.66 (2.75, 11.57)×10 9/L] and the other AID-HPS group [6.05 (2.49, 14.55)×10 9/L] ( Z=-4.032, P<0.001; Z=3.993, P<0.001). ② NEU in the SLE-HPS group [1.10 (0.60, 1.93)×10 9/L] were markedly reduced compared to the AOSD-HPS group [3.73 (1.54, 9.04)×10 9/L] and the other AID-HPS group [2.23 (1.43, 11.57)×10 9/L] ( Z=-3.859, P<0.001; Z=3.506, P=0.001). ③ PLT in the SLE-HPS group [59.50 (28.50, 81.00)×10 9/L] were significantly lower than those in the AOSD-HPS group [109.00 (65.75, 232.00)×10 9/L] and the other AID-HPS group [150.00 (55.00, 221.00)×10 9/L] ( Z=-3.421, P=0.002; Z=3.179, P=0.004). (4) LDH levels in the AOSD-HPS group [1 178 (645, 1 875) U/L] were significantly higher than those in the other AID-HPS group [598 (410, 771) U/L] ( Z=2.795, P=0.016). (5) TG levels in the SLE-HPS group [3.61 (2.46, 6.09) mmol/L] were significantly higher than those in the other AID-HPS group [2.68 (1.71, 3.30)mmol/L] ( Z=2.402, P=0.049). (6) CRP and SF levels in the AOSD-HPS group [79.20 (28.02, 179.53)mg/L and 30 225 (13 494, 53 598)μg/L, respectively] were significantly higher than those in the SLE-HPS group [26.05 (9.41, 83.31)mg/L and 9 862 (4 467, 22 315) μg/L, respectively] ( Z=2.547, P=0.033; Z=3.069, P=0.006 ). (7) The incidence rates with elevated sCD25 in the AOSD-HPS group (100.0%) was significantly higher than that in the other AID-HPS group (76.9%), ( χ2=5.154, P=0.035). After treatment, 83 patients improved, while 2 deaths occurred in the other AID-HPS group. Conclusion:Adult AID-HPS predominantly affects young to middle-aged females, with SLE and AOSD being the most common underlying AIDs. The condition manifests with severe clinical features, frequently triggered by viral infections (particularly CMV and EBV). Distinct differences in clinical and laboratory profiles exist among AID-HPS subtypes. Early recognition and aggressive treatment are critical for improving prognosis.

Objective:To investigate the anti-inflammatory activity of alcohol extract of Polyrhachis dives(PDAEs)against rheumatoid arthritis(RA)in vitro and in vivo.Methods:In vivo and in vitro anti-RA inflammatory response of PDAEs was investigated using a rat model of collagenous arthritis induced by bovine type Ⅱ collagen and an LPS-induced RAW264.7 cell inflammatory model.Results:PDAEs inhibited the polarization of M1 type macrophages in vivo and in vitro,reduced expressions of TNF-α,IL-1β,IL-6,iNOS,and promoted polarization of M2 type macrophages,enhanced expressions of anti-inflammatory cytokines,such as IL-10 and TGF-β,so as to achieve the anti-inflammatory effect.The experiments in vivo also showed that PDAEs had the immunomodulatory effect,the potential mechanism may be the regulation of Th17/Treg balance by regulating the expression of PD-1 and TGF-β,thus correcting the over-strong autoimmune response.Conclusion:PDAEs may reduce the inflammatory reaction of RA through anti-inflam-matory and immunomodulatory effects.

Objective To observe the value of machine learning(ML)models based on brain functional network features combining clinical indicators for predicting postoperative outcomes of patients with drug-resistant mesial temporal lobe epilepsy(DR-mTLE).Methods Totally 84 patients with unilateral DR-mTLE who underwent surgery were retrospectively enrolled and classified into seizure free(SF)group(n=55)and non-seizure free(NSF)group(n=29)according to one-year postoperative follow-up.Clinical data were analyzed to screen independent predictors of postoperative outcomes.Based on brain preoperative resting-state functional MRI,brain functional networks were constructed using graph theory analysis,and 587 features were extracted.Five-fold cross validation was used to divide the data into training set and test set,then the optimal brain functional network features related to postoperative outcomes of DR-mTLE patients were selected.Combining with clinically relevant independent predictors,ML models were constructed using classifiers including Gaussian process(GP),logistic regression(LR),support vector machine(SVM)and quadratic discriminant analysis(QDA),respectively,and the prediction efficacy,calibration and clinical value of each ML model were evaluated.Results Both course of disease and lesion location were clinically relevant independent predictors of postoperative outcome of DR-mTLE patients(OR=0.928,5.710,P=0.010,0.016).Four optimal brain function network features were selected,including betweenness centrality of the third zone of cerebellar vermis,degree centrality of right globus pallidus,nodal efficiency of temporal left inferior temporal gyrus and nodal clustering coefficient of left inferior parietal lobule.The average area under the curve(AUC)of GP,LR,SVM and QDA models in test set was 0.868,0.864,0.875 and 0.870,respectively.Calibration curves and decision curve analysis indicated that each ML model had good calibration and high clinical net benefit.Conclusion ML models based on brain functional network features combining with clinical indicators could be used to effectively predict postoperative outcomes in DR-mTLE patients.