BACKGROUND:The most common complication of traumatic femoral neck fractures after internal fixation is femoral head necrosis.Currently,many studies have reported on the risk factors that affect the occurrence and development of postoperative femoral head necrosis,but there is still a lack of tools to predict the risk of femoral head necrosis after internal fixation of femoral neck fractures.OBJECTIVE:To develop a predictive model that estimates the risk of femoral head necrosis shortly after patients with femoral neck fractures receive cannulated screw internal fixation.METHODS:A retrospective analysis reviewed clinical records of 172 patients who underwent cannulated screw internal fixation for femoral neck fractures at Department of Orthopedics of Mianyang Central Hospital from January 2013 to June 2023.Patients were categorized into two groups based on the presence or absence of femoral head necrosis within one year post-operation:the necrosis group and the non-necrosis group.Univariate analysis,Lasso regression,and multivariate Logistic regression techniques were employed to identify the determinants of femoral head necrosis.A nomogram prediction model was constructed using R language's"rms"package,version 4.0.The receiver operating characteristic curve was used to evaluate the discriminatory ability of the model.The Hosmer-Lemeshow test was used to evaluate the goodness of fit of the model,and the decision curve analysis was used to determine its clinical application benefits.Internal validation of the study was conducted using the Bootstrap method,involving 1 000 repeated samplings.To delve deeper into the primary factors influencing femoral head necrosis post-internal fixation of the femoral neck,this paper employed the SHAP method for data set analysis.RESULTS AND CONCLUSION:(1)The risk factors leading to femoral head necrosis in the short term after cannulated screw fixation of femoral neck fractures include:smoking,diabetes,Garden classification,fracture line location,reduction quality,age,and operation time.(2)The prediction model demonstrated robust performance,evidenced by an area under the curve of 0.940(95％Confidence Interval:0.903 to 0.977),indicating a high level of prediction accuracy.The model achieved a sensitivity of 90.2％and a specificity of 87.6％,indicating that its diagnostic performance was stable.The Hosmer-Lemeshow goodness-of-fit test yielded a chi-square value of 6.593 with a P-value of 0.581,confirming that the model's predictions closely align with the observed outcomes.(3)The calibration curve of the model also performed well,and its overall trend was very close to the ideal curve,further proving the high accuracy of the model.(4)The internal validation was carried out by the Bootstrap method with 1 000 repeated samplings,and the area under the curve of the model internal validation was still as high as 0.939,proving that the model had good stability.(5)Through the decision curve,it is found that within the probability threshold range of 1％to 92％,the model can obtain the maximum net benefit value.(6)The SHAP analysis results show that among the risk factors analyzed in this study,the location of the fracture line serves as the most significant predictor of femoral head necrosis following internal fixation with cannulated screws in femoral neck fractures,and subcapital fractures are extremely prone to femoral head necrosis after surgery.(7)It is concluded that the validated prediction model demonstrates strong discriminative power and reliability,offering practical clinical utility.It serves as a useful reference tool for short-term risk assessment of femoral head necrosis following internal fixation of femoral neck fractures.

The study focuses on the concept of multifunctional traditional Chinese medicine (TCM) formulas and aims to evaluate the efficacy of the classical formula Xiaoyao San (逍遥散). Study employs the integrated evidence chain (Eff-iEC) method to organize, integrate, and evaluate its therapeutic efficacy in treating different diseases with the same therapy, and to investigate the feasibility of using Eff-iEC to evaluate the multifunctionality of TCM formulas. The evaluation covered Xiaoyao San's therapeutic effects on depression, premenstrual syndrome, chronic hepatitis, irritable bowel syndrome, dyspepsia, and menopausal syndrome. Concurrently, the Grading of Recommendations, Assessment, Development, and Evaluation (GRADE) system was used for evaluation, and authoritative medical documents were incorporated to corroborate the recognition of Xiaoyao San within the medical community. Depression and menopausal syndrome received higher ratings than other conditions in the Eff-iEC, GRADE, and Medical Community Recognition assessments. The Eff-iEC evidence grade for Xiaoyao San was rated as "High" or above for chronic hepatitis, irritable bowel syndrome, dyspepsia, and menopausal syndrome. Premenstrual syndrome received a "Moderate ⁺" rating. The GRADE evidence level was "Low-〇〇⨁⨁" for depression, premenstrual syndrome, and chronic hepatitis; "Moderate-〇⨁⨁⨁" for dyspepsia and menopausal syndrome; and "Very Low-〇〇〇⨁" for irritable bowel syndrome. Depression and menopausal syndrome had the highest inclusion frequency, appearing in all 4 categories. Premenstrual syndrome, chronic hepatitis, and dyspepsia are not recommended in Western medical guidelines, but they are included in TCM guidelines, the China National Basic Medical Insurance Drug List, and the China National Essential Drug List. Irritable bowel syndrome appears only in the China National Basic Medical Insurance Drug List and China National Essential Drug List. The evaluation results obtained using the Eff-iEC method align with Medical Community Recognition, providing an objective and comprehensive assessment of Xiaoyao San's efficacy. The findings suggest that Xiaoyao San has strong evidence for treating depression and menopausal syndrome. However, further experimental and clinical trials are needed to assess its efficacy in treating premenstrual syndrome, chronic hepatitis, irritable bowel syndrome, and dyspepsia. These results support the clinical efficacy and rational use of Xiaoyao San, expand the application scope of the Eff-iEC method, and offer valuable insights and methodological references for the comparative evaluation of multifunctional TCM formulas.

bjective To analyze the growth trends of height and weight among primary and secondary school students, and explore the developmental characteristics and gender differences at different age groups, and to provide a scientific basis for adolescent health policy formulation. Methods Based on 675 175 health examination records of 227 978 students aged 6-17 years in Shiyan City from 2015 to 2024, a logistic growth model was employed to fit the curves of height and weight changes with age. Results From 2015 to 2024, height and weight showed steady increases across all age groups, exhibiting typical sigmoidal growth patterns. The growth rates varied across age groups: the younger age group (6-9 years) showed a moderate growth (annual height increase of 0.5-1.0 cm, weight increase of 0.03-0.06 kg/year), while the older age group (10-17 years) demonstrated a significant growth (annual height increase of 1.5-2.0 cm, weight increase of 0.22-0.38 kg/year). The growth rate curves displayed a unimodal distribution. The growth inflection points of male students occurred later than that of female students (height inflection point: 9.87 years for males vs. 8.98 years for females; weight inflection point: 10.70 years for males vs. 9.99 years for females). Female students experienced a more concentrated but shorter period of growth and development. The peak height growth rate was 7.40 cm/year at age 9 for females and 7.09 cm/year at age 10 for males, while the peak weight growth rate was 5.04 kg/year at age 10 for females and 5.27 kg/year at age 11 for males. Conclusion The physical development of primary and secondary school students in Shiyan City follows a logistic growth pattern, with significant gender differences and characteristics of adolescent growth spurts. Female students exhibit an earlier and more concentrated growth process.

Antimicrobial resistance (AMR) poses a critical global health threat. This review systematically examines AMR surveillance technology advances, from conventional culture methods to modern molecular diagnostics (e.g., whole-genome sequencing) and artificial intelligence-assisted approaches. It focuses on the current application of mass spectrometry, machine learning predictive models, and real-time surveillance networks. To address challenges including inadequate technical standardization, clinical translation barriers, and data-sharing limitations, we propose integrated ^"genotype-phenotype^" strategies and global standardization framework, while exploring future applications of CRISPR-based portable detection, single-cell sequencing, and blockchain technologies.

Objective To investigate the prevalence of thyroid nodules in the physical examination population in Mianyang region and analyze its association with metabolic syndrome. Methods A retrospective study was conducted on 9 978 individuals who underwent health examinations at our hospital from January 2024 to May 2025. Thyroid examinations were performed using color Doppler ultrasound to analyze the prevalence of thyroid nodules in this population. Clinical data of all subjects were collected, and logistic regression analysis was employed to assess the association between metabolic syndrome and the risk of thyroid nodule development. Results The prevalence of thyroid nodules in the physical examination population of Mianyang region was 17.98% (1 794/9 978). The logistic regression results showed that after adjusting for gender, age, BMI, occupation, consumption of non-iodized salt, staying up late, daily sleep duration, anxiety, and depression, metabolic syndrome (OR=6.593, 95% CI: 3.961-10.975) was associated with thyroid nodules (P<0.05). Conclusion The prevalence of thyroid nodules among the physical examination population in the Mianyang area is 17.98%, and metabolic syndrome remains associated with the risk of thyroid nodules after effectively controlling for confounding factors.

ObjectiveCerebrospinal fluid (CSF) plays a crucial role in maintaining the homeostasis of the central nervous system (CNS). CSF rapidly exchanges with interstitial fluid (ISF) via the glymphatic system within the brain parenchyma. CSF-ISF circulation and its associated mechanisms are often referred to as the brain lymphatic system. This system is connected directly to meningeal lymphatic vessels (mLVs), jointly performing the function of clearing metabolic waste from the CNS. Emerging evidence indicates that this system is closely associated with the onset and progression of neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD). Importantly, abnormal CSF circulation is not only a downstream consequence of AD pathology, but also a risk factor. In AD, the dynamics of CSF flow within the CNS are diminished, immune dysregulation occurs, and this may increase the risk of AD by exacerbating the burden of amyloid β-protein (Aβ). In the mouse model of AD, impaired CSF flow compromises this clearance function, leading to cognitive deficits. Clinically, acupuncture at cognition-related acupoints is commonly used for the prevention and treatment of AD. However, whether its therapeutic effects are mediated through the modulation of CSF dynamics remains unclear. This study aimed to evaluate the impact of acupuncture on CSF flow and investigate its acupoint specificity. MethodsMice were randomly assigned to experimental groups for the different electroacupuncture groups with the following acupoints: Baihui point (GV 20), Ear point, Neiguan point (PC 6), and Tianshu point (ST 25). Wild-type mice on a C57BL/6J background were used as controls. Fluorescent tracer was injected into the cisterna magna to label CSF flow. Fluorescence imaging was employed to assess the distribution of CSF within the brain before and after acupuncture stimulation. ResultsFollowing tracer injection into the cisterna magna, fluorescence signals rapidly reached the cerebellum and medulla—the regions closest to the injection site. Fluorescence intensity was higher in ventral brain regions compared to dorsal regions, likely due to greater vascular density in ventral areas facilitating CSF-ISF exchange. Electroacupuncture at the GV 20 produced the most pronounced enhancement of CSF across the whole brain, while stimulation at the ST 25 primarily augmented flow within subcortical regions. In contrast, electroacupuncture at the Ear point or the PC 6 had no observable effect on CSF in mice. ConclusionElectroacupuncture promotes CSF flow into the brain parenchyma in an acupoint-specific manner, with GV 20 exhibiting the most pronounced enhancement of CSF dynamics. These findings suggest that acupuncture-mediated facilitation of CSF flow may represent a potential therapeutic strategy for preventing or delaying age-related cognitive decline.

ObjectiveCerebrospinal fluid (CSF) plays a crucial role in maintaining the homeostasis of the central nervous system (CNS). CSF rapidly exchanges with interstitial fluid (ISF) via the glymphatic system within the brain parenchyma. CSF-ISF circulation and its associated mechanisms are often referred to as the brain lymphatic system. This system is connected directly to meningeal lymphatic vessels (mLVs), jointly performing the function of clearing metabolic waste from the CNS. Emerging evidence indicates that this system is closely associated with the onset and progression of neurodegenerative diseases (NDs) such as Alzheimer’s disease (AD). Importantly, abnormal CSF circulation is not only a downstream consequence of AD pathology, but also a risk factor. In AD, the dynamics of CSF flow within the CNS are diminished, immune dysregulation occurs, and this may increase the risk of AD by exacerbating the burden of amyloid β-protein (Aβ). In the mouse model of AD, impaired CSF flow compromises this clearance function, leading to cognitive deficits. Clinically, acupuncture at cognition-related acupoints is commonly used for the prevention and treatment of AD. However, whether its therapeutic effects are mediated through the modulation of CSF dynamics remains unclear. This study aimed to evaluate the impact of acupuncture on CSF flow and investigate its acupoint specificity. MethodsMice were randomly assigned to experimental groups for the different electroacupuncture groups with the following acupoints: Baihui point (GV 20), Ear point, Neiguan point (PC 6), and Tianshu point (ST 25). Wild-type mice on a C57BL/6J background were used as controls. Fluorescent tracer was injected into the cisterna magna to label CSF flow. Fluorescence imaging was employed to assess the distribution of CSF within the brain before and after acupuncture stimulation. ResultsFollowing tracer injection into the cisterna magna, fluorescence signals rapidly reached the cerebellum and medulla—the regions closest to the injection site. Fluorescence intensity was higher in ventral brain regions compared to dorsal regions, likely due to greater vascular density in ventral areas facilitating CSF-ISF exchange. Electroacupuncture at the GV 20 produced the most pronounced enhancement of CSF across the whole brain, while stimulation at the ST 25 primarily augmented flow within subcortical regions. In contrast, electroacupuncture at the Ear point or the PC 6 had no observable effect on CSF in mice. ConclusionElectroacupuncture promotes CSF flow into the brain parenchyma in an acupoint-specific manner, with GV 20 exhibiting the most pronounced enhancement of CSF dynamics. These findings suggest that acupuncture-mediated facilitation of CSF flow may represent a potential therapeutic strategy for preventing or delaying age-related cognitive decline.

ObjectiveTo construct a novel KPC mouse model of type 2 diabetes mellitus （T2DM） comorbid with spontaneous pancreatic cancer based on the gene editing-metabolic intervention dual-driven strategy， and to compare it with traditional models. MethodsA total of 14 male KPC mice were randomly divided into novel model group （T2DM-KPC group with 7 mice） and control group （KPC group with 7 mice）， and 14 male BALB/c-nu nude mice were randomly divided into traditional model group （T2DM-pancreatic cancer group with 7 mice） and control group （pancreatic cancer group with 7 mice）. The mice in the KPC group and the pancreatic cancer group were fed with normal diet， and those in the T2DM-KPC group and the T2DM-pancreatic cancer group were fed with a high-fat diet. After 4 weeks， the mice in the T2DM-KPC group and the T2DM-pancreatic cancer group were given intraperitoneal injection of streptozotocin. Subsequently， the mice in the KPC group and the T2DM-KPC group developed primary pancreatic tumor spontaneously over time， while those in the T2DM-pancreatic cancer group and the pancreatic cancer group were inoculated with tumor cells to form subcutaneous tumor xenograft at 2 weeks after stabilization of blood glucose. The 4 groups were observed in terms of tumor formation rate， tumor formation time， body weight， and the change in blood glucose； RNA sequencing was performed for tumors from the KPC group and the T2DM-KPC group， and then molecular subtyping was performed； HE staining， Masson staining， and immunohistochemical staining were used to assess the histopathological features and tumor microenvironment of pancreatic tumor from the T2DM-KPC group， which were compared with those of the T2DM-pancreatic cancer group. A one-way analysis of variance was used for comparison of continuous data between multiple groups， and the least significant difference t-test was used for further comparison between two groups； the Fisher’s exact test was used for comparison of categorical data between multiple groups. ResultsThe T2DM-KPC group had a tumor formation rate of 85.71% and a tumor formation time of 104.40±2.87 days， while the T2DM-pancreatic cancer group had a tumor formation rate of 71.43% and a tumor formation time of 95.20±9.47 days， and there were no significant differences between the two groups in tumor formation rate， tumor formation time， body weight， and blood glucose （all P>0.05）. Molecular subtyping showed that the model in the KPC group highly resembled the pancreatic progenitor subtype of human pancreatic ductal adenocarcinoma （PDAC）， and the model in the T2DM-KPC group highly resembled the immunogenic subtype of PDAC. HE staining showed that tumor cells in the T2DM-KPC group were arranged into glandular tubular structures of varying shapes， exhibiting significant cellular atypia， and this model faithfully recapitulated the pathological features of primary pancreatic cancer and showed greater invasiveness than the KPC group. Immunohistochemical staining and Masson staining showed that compared with the T2DM-pancreatic cancer group， the T2DM-KPC group had significantly higher degrees of tumor proliferation （assessed by Ki-67 expression） and fibrosis （assessed by α-SMA and Masson） （all P<0.05）， suggesting that the mouse model in the T2DM-KPC group could better recapitulate the features of hyperproliferation and pronounced desmoplasia in human pancreatic cancer. ConclusionA novel KPC mouse model of T2DM comorbid with spontaneous pancreatic cancer is successfully constructed in this study. This model can accurately mimic the histopathological architecture and stromal microenvironment of T2DM comorbid with pancreatic cancer， realize the longitudinal simulation of the progression of pancreatic tissue from intraepithelial neoplasia to invasive carcinoma and metastasis in the presence of T2DM， and support the translational research on immunotherapy， thereby providing a novel experimental carrier for in vivo studies on spontaneous pancreatic cancer in T2DM.

Background Microparticles (MPs) are one of the main medium of inflammatory reaction with an important role in atherosclerotic progression. Studies on association of air pollution exposure and levels of peripheral blood MPs are limited among human. Objective To evaluate the effects of short-term exposure to air pollution on levels of peripheral blood MPs. Method A panel of 73 healthy adults was followed with 4 repeated follow-ups in Beijing, China, from November 2014 to January 2016. During each visit, we collected questionnaire information, fasting venous blood, urine, and exposures to fine particulate matter (PM_2.5), black carbon, nitric oxide, nitrogen dioxide, nitrogen oxide, sulfur dioxide, carbon monoxide, and ozone. We used linear mixed-effect models to analyze associations of air pollution exposure with levels of total MPs (TMPs) and MPs derived from various cells. Stratified analysis was conducted by levels of C-reactive protein (CRP) and malondialdehyde (MDA). Results The results showed significant associations between air pollution exposure and peripheral blood TMPs at 2 h-6 d prior to the follow-ups (P<0.05), while no statistical associations were found for MPs derived from different cell types. Significant increases in TMPs of 7.8% (95%CI: 0.7%, 15.3%) and 14.3% (95%CI: 2.8%, 27.2%) were observed with each interquartile range (IQR) increase in PM_2.5 (IQR=64.9 μg·m⁻³) at prior 18 h and NO (IQR=40.5 μg·m⁻³) at prior 48 h. Among participants with low levels of CRP and MDA, significantly positive associations were observed between air pollution exposure and levels of TMPs (P<0.05). Conclusion Short-term exposure to air pollution is significantly associated with increased levels of circulating MPs in healthy adults, and in people with lower systemic inflammation, peripheral blood MPs levels are more easily affected after exposure to air pollutants.

OBJECTIVE Identify the incentive and constraint factors of artificial intelligence （AI） application in the pharmaceutical field， and promote the application of AI in the field of pharmacy. METHODS Based on the technology acceptance model （TAM）， technology-organization-environment （TOE） framework， and diffusion of innovation theory （DOI）， a TAM-TOE-DOI integrated framework was constructed through a four-stage research process of “theoretical review → dimension mapping → mechanism integration → proposition development”. Combining the analytical pathways of the above three theories in AI application in pharmacy with the integration mechanisms and core propositions of the TAM-TOE-DOI， literature review and deductive reasoning were employed to systematically identify the incentive and constraint factors of AI application in pharmacy from three levels：micro （TAM）， meso （TOE）， and macro （DOI）， and to propose optimization strategies. RESULTS & CONCLUSIONS At the micro level， the efficiency transformation and quality improvement brought by AI technology were the main incentive factors for perceived usefulness， while technological complexity and algorithmic opacity were the main constraint factors for perceived ease of use. At the meso level， the completeness of technological infrastructure， the strength of top management support and innovation climate， as well as external institutional pressure and competitive driving forces were the core incentive factors， whereas scarcity of organizational resources and talent shortage were the main constraint factors. At the macro level， relative advantage and observability were typical incentive factors， while technological complexity was a typical constraint factor. China’s health administration， medical insurance authorities， and other relevant departments should coordinate efforts at the macro， meso， and micro levels to advance AI application in pharmacy： optimizing human-computer interaction and implementing tiered training programs at the micro level； reinforcing organizational support systems and capacity building at the meso level； dismantling data barriers and building social trust at the macro level. Differentiated implementation pathways should be developed for medical institutions at different tiers.