The prevalence of female pelvic floor dysfunction (PFD) ranges from 17.8% to 74.07%, with approximately 30% of patients experiencing comorbid anxiety, depression, or other psychological disorders, severely impairing their quality of life. Current assessment methods for PFD are primarily based on clinical techniques such as the pelvic organ prolapse quantification and two-dimensional ultrasound. But they are limited by high subjectivity, operational complexity, and the inability to provide real-time dynamic evaluation. In recent years, emerging technologies including high-density electromyography, three-dimensional ultrasound, specific biomarkers, and artificial intelligence have complemented conventional clinical methods by providing dynamic functional data and molecular-level evidence, achieving multidimensional “structure-function-molecular”assessment of PFD. The relevant literature on PFD assessment published in CNKI, PubMed, and other databases from 2019 to 2024 were retrieved. The current application status and value of commonly used clinical techniques, the core characteristics of emerging technology assessments, and the integration path between the two were reviewed, so as to provide the evidence for individualized diagnosis and treatment of PFD.

Objective To evaluate the efficacy and safety of using stent semi-retrieval technique during mechanical thrombectomy(MT)for acute anterior cerebral artery(ACA)occlusion.Methods We made a retrospective analysis of 38 patients with acute ACA occlusion treated by stent semi-retrieval technique at Tangdu Hospital and Xi'an No.1 Hospital from June 2019 to September 2023.The successful recanalization,first-pass effect(FPE),perioperative complications and postoperative recovery of all the patients were analyzed.Modified thrombolytic test in cerebral infarction(mTICI)was used to evaluate the recanalization(unsuccessful recanalization,mTICI 0-2a;successful recanalization,mTICI 2b-3).FPE was defined as mTICI 3 after one thrombectomy.The clinical outcome was evaluated by modified Rankin Scale(mRS)3 months postoperatively.A good prognosis was defined as a mRS 0-2.Results Of the 38 patients,36(94.7％)got successful recanalization(mTICI 2b-3),with an FPE of 73.7％(28/38).Two cases of mild vascular spasm(5.3％)occurred during the mechanical thrombectomy,which completely relieved without further treatment.None of the 38 patients experienced vascular rupture or dissection,and no thrombus escaped during the thrombus removal process.There was no subarachnoid hemorrhage or parenchymal hemorrhage in the area related to ACA occlusion.Ninety days after operation,14 cases(36.8％)reached good outcome(mRS 0-2),18 cases(47.4％)reached mRS 3-5,and 6 cases(15.8％)died.Conclusion Our preliminary experience suggests that the stent semi-retrieval technique may be a safe and effective method for treating acute anterior cerebral artery occlusion.

Medical imaging large-scale models demonstrate broad application prospects in the field of tumor diagnosis and treatment.Their powerful high-dimensional feature extraction and data analysis capabilities have brought revolutionary breakthroughs to precision oncology,driving the transformation of diagnostic and therapeutic paradigms.However,current research in this field still faces numerous challenges and technical bot-tlenecks.Based on the research background of artificial intelligence(AI)large-scale models,this article sys-tematically reviews the current research status of medical imaging large-scale models from three key dimensions:the construction of large-scale medical imaging datasets,optimization of large-scale model algorithms,and com-putational resource requirements.Furthermore,it elaborates on the application scenarios of these models in pre-cision oncology and provides a forward-looking perspective on their future development.The aim is to offer prac-tical guidance for advancing precision diagnosis and treatment of tumors.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Objective:To investigate the relationship between dietary behavior and sarcopenia in older adults aged ≥65 years in longevity areas of China based on latent class analysis.Methods:A total of 4 358 older adults aged ≥65 years were selected from the 2021 Healthy Aging and Biomarkers Cohort Study. The information about their demographic characteristics, lifestyles, and chronic disease histories were collected. A simplified food frequency questionnaire was used to collect information about their dietary intake in the last month. The food intake frequency and food category score were calculated, and the higher the food category score, the richer the dietary intake. Latent class analysis was used to identify the latent classes of the dietary behavior. Sarcopenia was diagnosed using the SARC-CalF. Multivariate logistic regression model was used to analyze the association of food category scores and different latent classes of the dietary behavior with the risk for sarcopenia.Results:In 4 358 older adults, 1 841 (42.24%) had sarcopenia. The frequencies of intakes of cereals and potatoes, vegetable and fruit, meat and bean products were lower in the sarcopenia group than in the non-sarcopenia group. The risk for sarcopenia decreased with the increase of food category score in older adults ( OR=0.850, 95% CI: 0.796-0.907). Latent class analysis identified 4 latent classes of the dietary behavior. Compared with those with class 1 (frequency of intake of all 5 food species was higher probability in T3 group), those with class 2 (frequency of intake of vegetables and fruits and energy-only foods were less likely to be in the T3 group) and class 3 (frequency of intake of all 5 food species was lower probability in T3 group) had significantly increased risk for sarcopenia ( OR=1.377, 95% CI: 1.131-1.676) and ( OR=1.354, 95% CI: 1.091-1.680), 37.7% and 35.4% increased risk for sarcopenia, respectively. Conclusion:Increasing dietary intake category and sufficient intake of various foods for a balanced dietary pattern can reduce the risk of sarcopenia in older adults.

Objective To evaluate the efficacy and safety of using stent semi-retrieval technique during mechanical thrombectomy(MT)for acute anterior cerebral artery(ACA)occlusion.Methods We made a retrospective analysis of 38 patients with acute ACA occlusion treated by stent semi-retrieval technique at Tangdu Hospital and Xi'an No.1 Hospital from June 2019 to September 2023.The successful recanalization,first-pass effect(FPE),perioperative complications and postoperative recovery of all the patients were analyzed.Modified thrombolytic test in cerebral infarction(mTICI)was used to evaluate the recanalization(unsuccessful recanalization,mTICI 0-2a;successful recanalization,mTICI 2b-3).FPE was defined as mTICI 3 after one thrombectomy.The clinical outcome was evaluated by modified Rankin Scale(mRS)3 months postoperatively.A good prognosis was defined as a mRS 0-2.Results Of the 38 patients,36(94.7％)got successful recanalization(mTICI 2b-3),with an FPE of 73.7％(28/38).Two cases of mild vascular spasm(5.3％)occurred during the mechanical thrombectomy,which completely relieved without further treatment.None of the 38 patients experienced vascular rupture or dissection,and no thrombus escaped during the thrombus removal process.There was no subarachnoid hemorrhage or parenchymal hemorrhage in the area related to ACA occlusion.Ninety days after operation,14 cases(36.8％)reached good outcome(mRS 0-2),18 cases(47.4％)reached mRS 3-5,and 6 cases(15.8％)died.Conclusion Our preliminary experience suggests that the stent semi-retrieval technique may be a safe and effective method for treating acute anterior cerebral artery occlusion.

Objective:To analyze the association between inflammation-related dietary patterns and the risk for cognitive impairment in older adults aged ≥65 years in longevity areas in China by using reduced rank regression (RRR) analysis.Methods:This study used cross-sectional data from the 2021 Healthy Aging and Biomarkers Cohort Study, including the information about study participants' demographic characteristics, lifestyles, daily life activities, and disease histories. Dietary intake was obtained by using a simplified food frequency questionnaire. Cognitive impairment was evaluated based on the Mini-Mental State Examination Scale combined with years of education. Fasting venous blood samples were collected to detect inflammatory markers, especially high-sensitivity C-reactive protein (hs-CRP) and the platelet-to-lymphocyte ratio (PLR). RRR analysis was used to obtain inflammation-related dietary patterns using hs-CRP and PLR as response variables. Multivariate logistic regression model was used to analyze the association between dietary pattern score and the risk for cognitive impairment. Restricted cubic spline was used to explore the dose response relationship, and mediation analysis was used to quantify the mediating effects of hs-CRP and PLR.Results:Two dietary patterns were identified with RRR. The primary pattern was characterized by higher intakes of flour, red meat, and dairy products, and lower intake of fresh vegetables, explaining 6.84% of the variance in food intake and 0.50% of the variance in inflammatory markers. Compared with the T1 group, the T3 group had significantly higher risk for cognitive impairment ( OR=1.242, 95% CI: 1.034-1.491). Each one standard deviation increase in the dietary pattern score was associated with an 8.7% increase in the risk for cognitive impairment ( OR=1.087, 95% CI: 1.008-1.172), with a significant linear trend (overall-model P<0.001, non-linear P=0.295). Mediation analysis indicated that hs-CRP mediated 6.2% of the association between the dietary pattern and the risk for cognitive impairment. Conclusion:The inflammation- related dietary pattern characterized by higher consumption of flour, red meat, and dairy products and lower consumption of fresh vegetables is associated with an increased risk for cognitive impairment in older adults, and hs-CRP partially mediates this association.

Objective:To investigate the relationship between dietary behavior and sarcopenia in older adults aged ≥65 years in longevity areas of China based on latent class analysis.Methods:A total of 4 358 older adults aged ≥65 years were selected from the 2021 Healthy Aging and Biomarkers Cohort Study. The information about their demographic characteristics, lifestyles, and chronic disease histories were collected. A simplified food frequency questionnaire was used to collect information about their dietary intake in the last month. The food intake frequency and food category score were calculated, and the higher the food category score, the richer the dietary intake. Latent class analysis was used to identify the latent classes of the dietary behavior. Sarcopenia was diagnosed using the SARC-CalF. Multivariate logistic regression model was used to analyze the association of food category scores and different latent classes of the dietary behavior with the risk for sarcopenia.Results:In 4 358 older adults, 1 841 (42.24%) had sarcopenia. The frequencies of intakes of cereals and potatoes, vegetable and fruit, meat and bean products were lower in the sarcopenia group than in the non-sarcopenia group. The risk for sarcopenia decreased with the increase of food category score in older adults ( OR=0.850, 95% CI: 0.796-0.907). Latent class analysis identified 4 latent classes of the dietary behavior. Compared with those with class 1 (frequency of intake of all 5 food species was higher probability in T3 group), those with class 2 (frequency of intake of vegetables and fruits and energy-only foods were less likely to be in the T3 group) and class 3 (frequency of intake of all 5 food species was lower probability in T3 group) had significantly increased risk for sarcopenia ( OR=1.377, 95% CI: 1.131-1.676) and ( OR=1.354, 95% CI: 1.091-1.680), 37.7% and 35.4% increased risk for sarcopenia, respectively. Conclusion:Increasing dietary intake category and sufficient intake of various foods for a balanced dietary pattern can reduce the risk of sarcopenia in older adults.

Medical imaging large-scale models demonstrate broad application prospects in the field of tumor diagnosis and treatment.Their powerful high-dimensional feature extraction and data analysis capabilities have brought revolutionary breakthroughs to precision oncology,driving the transformation of diagnostic and therapeutic paradigms.However,current research in this field still faces numerous challenges and technical bot-tlenecks.Based on the research background of artificial intelligence(AI)large-scale models,this article sys-tematically reviews the current research status of medical imaging large-scale models from three key dimensions:the construction of large-scale medical imaging datasets,optimization of large-scale model algorithms,and com-putational resource requirements.Furthermore,it elaborates on the application scenarios of these models in pre-cision oncology and provides a forward-looking perspective on their future development.The aim is to offer prac-tical guidance for advancing precision diagnosis and treatment of tumors.

Objective:To evaluate the efficacy and safety of hybutimibe in the treatment of hypercholesterolemia.Methods:Relevant databases and clinical trial registration websites at home and abroad were searched (up to March 27, 2023), and randomized controlled trials (RCTs) of hybutimibe in the treatment of hypercholesterolemia have been collected. Patients in the trial group were given hybutimibe with or without other hypolipidemic agents, and those in the control group were given placebo or other hypolipidemic agents as same as that in the trial group. The primary outcome in effectiveness was the change rate of low-density lipoprotein cholesterol (LDL-C). The primary outcomes in safety were incidences of overall adverse events (AEs), serious AEs (SAEs), the trial termination due to AEs, and trial drug-related AEs. The secondary outcome in safety was incidence of the major AE reported in ≥ 2 trials. Meta-analysis was performed using RevMan 5.4 software. The effect sizes of counting data were expressed by the relative risk ( RR) and its 95% confidence interval ( CI). The effect sizes of measurement data were expressed by mean difference ( MD) and its 95% CI. Results:A total of 4 RCTs and 1 488 patients were entered in the analysis, including 952 patients in the trial group and 536 in the control group. The results of meta-analysis showed that at 8-12 weeks of treatment, the decrease rate of LDL-C in the trial group (hybutimibe 20 or 10 mg daily with or without atorvastatin 10 mg daily) was significantly greater than that in the control group (hybutimibe 20 mg daily: MD=-13.36%, 95% CI: -15.28% - -11.44%, P<0.001; hybutimibe 10 mg daily: MD=-10.80%, 95% CI: -14.90%- -6.71%, P<0.001); at 52 weeks of treatment, the average decrease rate (from baseline) of LDL-C in the trial group (hybutimibe 20 or 10 mg combined with atorvastatin 10 mg daily) was significantly greater than that in the control group with atorvastatin 10 mg daily monotherapy (-41.92% and -39.34% vs. -31.56%, all P<0.001); the incidences of overall AEs [47.94% (338/705) vs. 49.75% (202/406), RR=0.99, 95% CI: 0.87-1.12], SAEs[2.64% (16/606) vs. 2.79% (10/358), RR=1.19, 95% CI: 0.53-2.66], trial termination due to AEs[4.11% (29/705) vs. 4.68% (19/406), RR=0.67, 95% CI: 0.17-2.65], and trial drug-related AEs [12.38% (75/606) vs. 11.45% (41/358), RR=0.87, 95% CI: 0.37-2.06] were similar between the 2 groups at 8-12 weeks of treatment (all P>0.05). Conclusion:Hybutimibe could effectively reduce LDL-C level in patients with hypercholesterolemia, with good medication safety.