Alzheimer’s disease (AD) is a central neurodegenerative disease characterized by progressive cognitive decline and memory impairment in clinical. Currently, there are no effective treatments for AD. In recent years, a variety of therapeutic approaches from different perspectives have been explored to treat AD. Although the drug therapies targeted at the clearance of amyloid β-protein (Aβ) had made a breakthrough in clinical trials, there were associated with adverse events. Neuroinflammation plays a crucial role in the onset and progression of AD. Continuous neuroinflammatory was considered to be the third major pathological feature of AD, which could promote the formation of extracellular amyloid plaques and intracellular neurofibrillary tangles. At the same time, these toxic substances could accelerate the development of neuroinflammation, form a vicious cycle, and exacerbate disease progression. Reducing neuroinflammation could break the feedback loop pattern between neuroinflammation, Aβ plaque deposition and Tau tangles, which might be an effective therapeutic strategy for treating AD. Traditional Chinese herbs such as Polygonum multiflorum and Curcuma were utilized in the treatment of AD due to their ability to mitigate neuroinflammation. Non-steroidal anti-inflammatory drugs such as ibuprofen and indomethacin had been shown to reduce the level of inflammasomes in the body, and taking these drugs was associated with a low incidence of AD. Biosynthetic nanomaterials loaded with oxytocin were demonstrated to have the capability to anti-inflammatory and penetrate the blood-brain barrier effectively, and they played an anti-inflammatory role via sustained-releasing oxytocin in the brain. Transplantation of mesenchymal stem cells could reduce neuroinflammation and inhibit the activation of microglia. The secretion of mesenchymal stem cells could not only improve neuroinflammation, but also exert a multi-target comprehensive therapeutic effect, making it potentially more suitable for the treatment of AD. Enhancing the level of TREM2 in microglial cells using gene editing technologies, or application of TREM2 antibodies such as Ab-T1, hT2AB could improve microglial cell function and reduce the level of neuroinflammation, which might be a potential treatment for AD. Probiotic therapy, fecal flora transplantation, antibiotic therapy, and dietary intervention could reshape the composition of the gut microbiota and alleviate neuroinflammation through the gut-brain axis. However, the drugs of sodium oligomannose remain controversial. Both exercise intervention and electromagnetic intervention had the potential to attenuate neuroinflammation, thereby delaying AD process. This article focuses on the role of drug therapy, gene therapy, stem cell therapy, gut microbiota therapy, exercise intervention, and brain stimulation in improving neuroinflammation in recent years, aiming to provide a novel insight for the treatment of AD by intervening neuroinflammation in the future.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

Background: and Purpose Symptomatic intracranial hemorrhage (sICH) following endovascular thrombectomy (EVT) is a severe complication associated with adverse functional outcomes and increased mortality rates. Currently, a reliable predictive model for sICH risk after EVT is lacking. Methods: This study used data from patients aged ≥20 years who underwent EVT for anterior circulation stroke from the nationwide Taiwan Registry of Endovascular Thrombectomy for Acute Ischemic Stroke (TREAT-AIS). A predictive model including factors associated with an increased risk of sICH after EVT was developed to differentiate between patients with and without sICH. This model was compared existing predictive models using nationwide registry data to evaluate its relative performance. Results: Of the 2,507 identified patients, 158 developed sICH after EVT. Factors such as diastolic blood pressure, Alberta Stroke Program Early CT Score, platelet count, glucose level, collateral score, and successful reperfusion were associated with the risk of sICH after EVT. The TREAT-AIS score demonstrated acceptable predictive accuracy (area under the curve [AUC]=0.694), with higher scores being associated with an increased risk of sICH (odds ratio=2.01 per score increase, 95% confidence interval=1.64–2.45, P<0.001). The discriminatory capacity of the score was similar in patients with symptom onset beyond 6 hours (AUC=0.705). Compared to existing models, the TREAT-AIS score consistently exhibited superior predictive accuracy, although this difference was marginal. Conclusions The TREAT-AIS score outperformed existing models, and demonstrated an acceptable discriminatory capacity for distinguishing patients according to sICH risk levels. However, the differences between models were only marginal. Further research incorporating periprocedural and postprocedural factors is required to improve the predictive accuracy.

ObjectiveTo collate and compare the characteristics and differences in the methods for constructing animal models of different subtypes of gastroesophageal reflux disease （GERD） based on literature， providing a reference for researchers in this field regarding animal model construction. MethodsExperimental studies related to GERD including reflux esophagitis （RE）， nonerosive reflux disease （NERD） and Barrett's esophagus （BE） model construction from January 1， 2014 to January 27， 2024， were retrieved from databases such as CNKI， Wanfang， VIP， Web of Science， and Pubmed. Information on animal strains， genders， modeling methods including disease-syndrome combination models， modeling cycles were extracted； for studies with model evaluation， the methods of model evaluation were also extracted； then analyzing all those information. ResultsA total of 182 articles were included. SD rats were most frequently selected when inducing animal models of RE （88/148， 59.46%） and NERD （9/14， 64.29%）. For BE， C57BL/6 mice were most commonly used （11/20， 55.00%）. Male animals （RE： 111/135， 82.22%； NERD： 11/14， 78.57%； BE： 10/12， 83.33%） were the most common gender among the three subtypes. The key to constructing RE animal models lies in structural damage to the esophageal mucosal layer， gastric content reflux， or mixed reflux， among which forestomach ligation + incomplete pylorus ligation （42/158， 26.58%） was the most common modeling method； the key to constructing NERD animal models lies in micro-inflammation of the esophageal mucosa， visceral hypersensitivity， and emotional problems， and intraperitoneal injection of a mixed suspension of ovalbumin and aluminum hydroxide combined with acid perfusion in the lower esophagus （8/14， 57.14%） was the most common modeling method； the key to constructing BE animal models lies in long-term inflammatory stimulation of the esophageal mucosa and bile acid reflux， and constructing interleukin 2-interleukin 1β transgenic mice （7/25， 28.00%） was the most common modeling method. Adverse psychological stress was the most common method for inducing liver depression. ConclusionsThe construction key principles and methodologies for RE， NERD， and BE animal models exhibit significant differences. Researchers should select appropriate models based on subtype characteristics （e.g.， RE focusing on structural damage， NERD emphasizing visceral hypersensitivity）. Current studies show insufficient exploration of traditional Chinese medicine disease-syndrome combination models. Future research needs to optimize syndrome modeling approaches （e.g.， composite etiology simulation） and establish integrated Chinese-Western medicine evaluation systems to better support mechanistic investigations of traditional Chinese medicine.

BackgroundPrenatal depression has an important impact on maternal health and pregnancy outcomes. Previous studies have shown that maternal prenatal depression is associated with social support， and social support is related to fear of childbirth. However， there is limited research on the relationship among maternal prenatal depression， social support and fear of childbirth， and no studies have specifically explored the influence of social support and fear of childbirth on prenatal depression in primiparous women. ObjectiveTo investigate the current status of prenatal depression among primiparous women， and to analyze the correlation between social support and fear of childbirth， and to further explore the influence of social support and fear of childbirth on prenatal depression in this population， so as to provide references for improving their mental health. MethodsA total of 380 primiparous women admitted to the inpatient department of Chengdu Wenjiang District People's Hospital from December 2022 to September 2023 were enrolled as study subjects. A self-made questionnaire， Edinburgh Postnatal Depression Scale （EPDS）， Social Support Rating Scale （SSRS） and Childbirth Attitudes Questionnaire （CAQ） were used to conduct the survey. Pearson correlation analysis was employed to examine the relationships between scale scores. Multiple linear regression analysis was conducted to identify influencing factors of prenatal depression. ResultsA total of 380 questionnaires were distributed， with 372 （97.89%） valid responses collected. Among the participants， 222 cases （59.68%） were identified with prenatal depression. Pearson correlation analysis revealed that EPDS score was negatively correlated with SSRS score （r=-0.283， P<0.01） and positively correlated with CAQ score （r=0.341， P<0.01）. Multiple linear regression analysis indicated that social support （β=-0.166， P<0.01） and fear of childbirth （β=0.269， P<0.01） were influencing factors of prenatal depression in primiparous women. ConclusionThe prevalence of prenatal depression among primiparous women is concerning， with depression levels showing significant associations with both social support and fear of childbirth.

Cardiovascular disease (CVD), chronic kidney disease (CKD), and metabolic disorders are the 3 major chronic diseases threatening human health, which are closely related and often coexist, significantly increasing the difficulty of disease management. In response, the American Heart Association (AHA) proposed a novel disease concept of “cardiovascular-kidney-metabolic (CKM) syndrome” in October 2023, which has triggered widespread concern about the co-treatment of heart and kidney diseases and the prevention and treatment of metabolic disorders around the world. This review posits that effectively managing CKM syndrome requires a new and multidimensional paradigm for diagnosis and risk prediction that integrates biological insights, advanced technology and social determinants of health (SDoH). We argue that the core pathological driver is a “metabolic toxic environment”, fueled by adipose tissue dysfunction and characterized by a vicious cycle of systemic inflammation and oxidative stress, which forms a common pathway to multi-organ injury. The at-risk population is defined not only by biological characteristics but also significantly impacted by adverse SDoH, which can elevate the risk of advanced CKM by a factor of 1.18 to 3.50, underscoring the critical need for equity in screening and care strategies. This review systematically charts the progression of diagnostic technologies. In diagnostics, we highlight a crucial shift from single-marker assessments to comprehensive multi-marker panels. The synergistic application of traditional biomarkers like NT-proBNP (reflecting cardiac stress) and UACR (indicating kidney damage) with emerging indicators such as systemic immune-inflammation index (SII) and Klotho protein facilitates a holistic evaluation of multi-organ health. Furthermore, this paper explores the pivotal role of non-invasive monitoring technologies in detecting subclinical disease. Techniques like multi-wavelength photoplethysmography (PPG) and impedance cardiography (ICG) provide a real-time window into microcirculatory and hemodynamic status, enabling the identification of early, often asymptomatic, functional abnormalities that precede overt organ failure. In imaging, progress is marked by a move towards precise, quantitative evaluation, exemplified by artificial intelligence-powered quantitative computed tomography (AI-QCT). By integrating AI-QCT with clinical risk factors, the predictive accuracy for cardiovascular events within 6 months significantly improves, with the area under the curve (AUC) increasing from 0.637 to 0.688, demonstrating its potential for reclassifying risk in CKM stage 3. In the domain of risk prediction, we trace the evolution from traditional statistical tools to next-generation models. The new PREVENT equation represents a major advancement by incorporating key kidney function markers (eGFR, UACR), which can enhance the detection rate of CKD in primary care by 20%-30%. However, we contend that the future lies in dynamic, machine learning-based models. Algorithms such as XGBoost have achieved an AUC of 0.82 for predicting 365-day cardiovascular events, while deep learning models like KFDeep have demonstrated exceptional performance in predicting kidney failure risk with an AUC of 0.946. Unlike static calculators, these AI-driven tools can process complex, multimodal data and continuously update risk profiles, paving the way for truly personalized and proactive medicine. In conclusion, this review advocates for a paradigm shift toward a holistic and technologically advanced framework for CKM management. Future efforts must focus on the deep integration of multimodal data, the development of novel AI-driven biomarkers, the implementation of refined SDoH-informed interventions, and the promotion of interdisciplinary collaboration to construct an efficient, equitable, and effective system for CKM screening and intervention.

Objective To study the bioequivalence of test and reference olmesartan tablet in Chinese healthy subjects after single dose under fasting and fed conditions.Methods A single-center,random,open,single-dose,two-preparations,double-period,crossover study was adopted.A total of 48 healthy adult male and female subjects(24 cases of fasting test and 24 cases of fed test)were included in the random crossover administration.Single oral dose 20 mg of test and reference were taken under fasting and postprandial conditions,respectively.Plasma concentration of olmesartan in plasma were determined by liquid chromatography tandem mass spectrometry.The main pharmacokinetic parameters were calculated by Phoenix WinNonlin 8.0 software.Results The main pharmacokinetic parameters of the test and reference preparations of olmesartan tablets in the fasting group were as follows:Cmax were(653.06±133.53)and(617.37±151.16)ng·mL-1,AUC0-t were(4 201.18±1 035.21)and(4 087.38±889.99)ng·mL-1·h,AUC0-∞ were(4 254.30±1 058.90)and(4 135.69±905.29)ng·mL-1·h.The main pharmacokinetic parameters of the test and reference preparations of olmesartan tablets in the postprandial group were as follows:Cmax were(574.78±177.05)and(579.98±107.74)ng·mL-1,AUC0-t were(3 288.37±866.06)and(3 181.51±801.06)ng·mL-1·h,AUC0-∞ were(3 326.11±874.26)and(3 242.01±823.09)ng·mL-1·h.Under fasting and postprandial conditions,the 90％confidence intervals of the main pharmacokinetic parameters of the test and reference preparations are both 80.00％-125.00％.Conclusion Under fasting and postprandial conditions,a single oral dose of test and reference preparations olmesartan tablets in Chinese healthy adult volunteers showed bioequivalence.

Objective:To examine the impact of intrinsic capacity(IC), comorbidity, and their interaction on the occurrence of adverse outcomes in community-dwelling older adults.Methods:This 2-year observational cohort study included 230 residents aged 75 and above who lived in the Beijing Taikang Yanyaun community active area from June to August 2018.The study evaluated the IC scale, Charlson comorbidity index(CCI), and activity of daily living(ADL).In September 2020, adverse outcomes such as functional decline(defined as a decline of at least one point on the ADL scores at 2-year follow-up compared with baseline)and falls were assessed.The structure equation model(SEM)path analysis was employed to examine the direct and indirect effects of IC and CCI on adverse outcomes.Results:Among the 212 older adults who completed a 2-year follow-up, aged 75-93(mean age 83.8±4.4)years, 59.4%(126 cases)were female.Out of these participants, 51.4%(109 cases)experienced functional decline and 33.5%(71 cases)had falls.Path analysis revealed that the direct effects of IC on functional decline and falls were significantly positive, with standardized coefficients of 0.430 and 0.369, respectively.However, the effect of CCI was not found to be significant.The multi-variable Logistic regression model showed that the total effect of IC on functional decline and falls remained significantly positive, with values of 1.184 and 0.915, respectively.CCI acted as a mediating factor, with indirect effects on functional decline and falls accounting for 5.4% and 0.8%, respectively.In terms of the relationship between age and adverse outcomes, the indirect effect of IC was significantly higher than that of CCI(functional decline: 0.192 vs.0.037; falls: 0.158 vs.0.017). Conclusions:The maintenance of IC in the health management of community-dwelling older adults should be given more attention as it can significantly affect the incidence of functional decline and falls.Comorbidity, on the other hand, has a weaker influence.

Objective To explore the feasibility of peritoneal dialysis catheter placement assisted by flexible ureteroscope.Methods A retrospective analysis was conducted on clinical data of 54 cases of end-stage renal disease receiving peritoneal dialysis catheter placement from May 2019 to March 2023.The placement method was chosen by the patient.In the conventional group,23 cases were guided by a metal guide wire for insertion of the peritoneal dialysis catheter,while in the flexible ureteroscope group,31 cases were guided by flexible ureteroscope instead of guide wire for insertion of the peritoneal dialysis catheter.The success rate of catheterization,surgical time,use of postoperative analgesic,complications related to peritoneal dialysis catheter,and postoperative creatinine decrease were compared between the two groups.Results The catheter placement was successfully performed in both groups.The total incidence of complications related to peritoneal dialysis catheter in the flexible ureteroscope group was lower than that in the conventional group[6.5%(2/31)vs.30.4%(7/23),χ2 =3.878,P =0.049].Between the conventional group and the flexible ureteroscope group,there were no statistically significant differences in the surgical time,postoperative analgesic usage,and the decrease of creatinine at 2 weeks after surgery(P>0.05).The median postoperative follow-up period was10 months(range,3-24 months)in the two groups,and there were no complications such as peritoneal leakage,intestinal perforation,or intraperitoneal bleeding.Conclusion The placement of peritoneal dialysis catheter guided by the flexible ureteroscope instead of metal guide wire is a safe,visible,and accurate method,which can reduce complications related to peritoneal dialysis catheter,and detect and manage comorbidities in the abdominal cavity.