Objective: To explore the association between the HLA antibody positivity rate in female blood donors and pregnancy history, number of pregnancies, interval from the last pregnancy to blood donation, and age, to identify associated variables using a univariate generalized additive model (GAM), and to further analyze the predictive role of characteristic variables for HLA antibody positivity using a random forest model. Methods: HLA antibody detection was performed on 391 female blood donors using the Luminex immunomagnetic bead method. The correlation between pregnancy-related factors and HLA antibodies was analyzed using the Chi-square test. Based on R software, a univariate GAM was first constructed to analyze the association types between characteristic variables and the HLA antibody positivity rate, followed by the construction of a random forest model to evaluate the predictive value of the variables. Results: Among the 391 female blood donors without a transfusion history, the overall HLA antibody positivity rate was 26.34%. The positivity rate in donors with a pregnancy history was significantly higher than that in those without (30.09% vs 9.72%, P<0.05), and HLA antibody positivity rate increased linearly with the number of pregnancies (P<0.05). In the univariate GAM, age and number of deliveries exhibited a non-linear association with the HLA antibody positivity rate (the positivity rate increased sharply between 25-35 years of age and stabilized after 3 deliveries). Besides, the interval from the last pregnancy to blood donation showed a linear association with the HLA antibody positivity rate, and the positivity rate decreased as the interval prolonged (P<0.05). In the random forest model, age (mean decrease gini=29.26) and interval from the last pregnancy to blood donation (mean decrease gini=22.02) were core predictive variables: age was more conducive to identifying positive samples, while the interval from the last pregnancy to blood donation was more helpful for excluding negative samples. The number of deliveries (mean decrease accuracy=16.98) made a significant contribution to predicting positive samples, whereas the number of abortions had no impact. The model had an AUC of 0.583 (95% CI: 0.593 8-0.770 2), indicating a certain predictive value. Conclusion: The associated variables identified by the univariate GAM model, including age, interval from the last pregnancy to blood donation, and number of deliveries, provide a basis for key variables in the random forest model. All three variables have predictive value for HLA antibody positivity, which can provide evidence-based support for personalized transfusion management and stratified screening of female blood donors in this region.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

This article summarizes Professor HAN Mingxiang's clinical experience in treating lung cancer based on the theory of "deficiency-phlegm-stasis-toxin". It is believed that depletion of healthy qi， together with binding of phlegm and stasis forming into toxin is the core pathogenesis of lung cancer occurrence and development. In clinical practice， the core treatment principle should be reinforcing healthy qi， resolving phlegm， removing stasis， and relieving toxins. The treatment should be given based on syndrome differentiation. For the syndrome of lung-spleen qi deficiency， the self-formulated Jianpi Huatan Zhike Decoction （健脾化痰止咳汤） can be applied to fortify the spleen and replenish qi， thereby reinforcing healthy qi. For the syndrome of deficiency of both qi and yin， the self-formulated Shenmai Yuzhu Decoction （参麦玉竹汤） is used to nourish yin and moisten the lungs， thereby clearing the source. For the syndrome of phlegm-dampness accumulating in the lungs， the self-formulated Sizi Wenfei Decoction （四子温肺汤） is applied to warm the lungs and resolve phlegm， thereby diffusing the lung qi. For the syndrome of qi stagnation and blood stasis， the self-formulated Yiqi Zhuyu Decoction （益气逐瘀汤） is used to activate blood and resolve stasis， thereby unblocking the collaterals. For the syndrome of binding of phlegm and stasis， the self-formulated Jiejie Decoction （结节方） is utilized to resolve phlegm and remove stasis， thereby dissipating nodules. For the syndrome of lung deficiency with toxin accumulation， the self-formulated Qiyu Sanlong Decoction （芪玉三龙汤） is applied to reinforce healthy qi and remove toxins， thereby combating cancer. Medications are flexibly prescribed based on syndrome differentiation， with an emphasis on reinforcing healthy qi and eliminating pathogenic factors， and maintaining the balance of zang-fu （脏腑） organ functions as well as qi， blood， yin and yang.

Objective:To construct a Harvard cancer index-based risk predictive model for perioperative venous thromboembolism (VTE) in elderly patients with femoral neck fracture and assess its predictive effectiveness.Methods:A retrospective cohort study was conducted to analyze the clinical data of 610 elderly patients with femoral neck fracture admitted to Peking Union Medical College Hospital between January 2013 and December 2022, including 193 males and 417 females, aged 60-99 years [(77.3±9.0)years]. The patients were divided into VTE group ( n=125) and non-VTE group ( n=485) according to occurrence of VTE during the perioperative period. The two groups were compared in terms of gender, age, body mass index, smoking status, alcohol consumption, time from fracture to admission, surgical waiting time, comorbidities, perioperative electrolyte disorders, past or present history of malignancy, past history of deep vein thrombosis (DVT) or pulmonary embolism (PE), and preoperative use of oral anticoagulants. Univariate analysis and multivariable stepwise Logistic regression analysis were conducted to evaluate and identify independent risk factors for perioperative VTE in elderly patients with femoral neck fracture. A perioperative VTE risk predictive model for elderly patients with femoral neck fracture was constructed using the Harvard cancer index: (1) assigning a risk score to each variable according to the corresponding conversion criteria of the Harvard cancer index and risk score, based on the magnitude of their ORs; (2) determining the exposure rate of each risk factor based on the population distribution observed in this study; (3) calculating the average population risk score; (4) computing the individual VTE risk score; (5) deriving the ratio (X) of each individual ′s VTE risk score to the population average. Based on the Harvard cancer index classification criteria for disease risk levels, individual VTE risk categories were determined. The predictive performance of the risk stratification was evaluated by comparing the incidence of VTE across different risk levels. The predictive performance of the model was evaluated based on sensitivity, specificity, and the area under the receiver operating characteristic (ROC) curve (AUC). The calibration of the model was assessed using the Hosmer-Lemeshow (H-L) test and internal validation was performed using the bootstrap resampling method with 1000 iterations. Results:Univariate analysis showed that gender, age, time from fracture to admission, surgical waiting time, previous cerebral infarction, stroke within the past month, Alzheimer′s disease, primary Parkinson′s syndrome, hysterectomy with bilateral adnexectomy, perioperative electrolyte disorders, history of DVT or PE, and preoperative use of oral anticoagulant drug were moderately associated with the occurrence of VTE in elderly patients with femoral neck fracture ( P<0.10). Multivariable stepwise logistic regression analysis demonstrated that female gender ( OR=2.26, 95% CI 1.34, 3.80, P<0.01), time from fracture to admission>1 day ( OR=3.70, 95% CI 2.24, 6.12, P<0.01), surgical waiting time>70 hours ( OR=2.06, 95% CI 1.29, 3.30, P<0.01), previous cerebral infarction ( OR=3.78, 95% CI 1.04, 13.76, P<0.05), stroke within the past month ( OR=11.57, 95% CI 1.21, 110.44, P<0.05), Alzheimer′s disease ( OR=3.26, 95% CI 1.12, 9.49, P<0.05), primary Parkinson ′s syndrome ( OR=3.47, 95% CI 1.22, 9.85, P<0.05), previous hysterectomy with bilateral adnexectomy ( OR=4.75, 95% CI 2.09, 10.80, P<0.01), perioperative electrolyte disorders ( OR=2.73, 95% CI 1.39, 5.35, P<0.01), and preoperative oral anticoagulant use ( OR=3.86, 95% CI 1.18, 12.67, P<0.05) were significantly associated with the occurrence of perioperative VTE in elderly patients with femoral neck fracture. Based on the above 10 risk factors, a perioperative VTE risk predictive model for elderly patients with femoral neck fracture was constructed with the Harvard cancer index. The formula was as follows: X=[10×(female gender)+25×(time from fracture to admission>1 day)+10×(surgical waiting time>70 hours)+25×(previous cerebral infarction)+50×(stroke within the past month)+25×(Alzheimer′s disease)+25×(primary Parkinson′s disease)+25×(previous hysterectomy with bilateral adnexectomy)+10×(perioperative electrolyte disorders)+25×(preoperative use of oral anticoagulant drug)]/33. Individualized VTE risk was classified into five levels: very low, low, moderate, high, and very high, with corresponding VTE rates of 4.8%, 11.8%, 14.9%, 32.3%, and 73.5%, respectively ( χ2=87.71, P<0.01). The VTE risk predictive model demonstrated an AUC of 0.74 (95% CI 0.69, 0.79, P<0.01), with a sensitivity of 63.2% and specificity of 74.8%. The H-L goodness-of-fit test indicated satisfactory model calibration ( P>0.05). The internal validation with the bootstrap method confirmed that the AUC remained 0.74. Conclusions:Female gender, time from fracture to admission>1 day, surgical waiting time>70 hours, previous cerebral infarction, stroke within the past month, Alzheimer′s disease, primary Parkinson′s syndrome, hysterectomy with bilateral adnexectomy, perioperative electrolyte disorders, and preoperative use of oral anticoagulant drug are independent risk factors for perioperative VTE in elderly patients with femoral neck fracture. Based on these factors, the perioperative VTE risk predictive model constructed using the Harvard cancer index demonstrates good clinical predictive value. Individualized VTE risk stratification can effectively identify high-, intermediate-, and low-risk populations, providing a valuable reference for tailoring anticoagulant prophylaxis strategies and enhancing postoperative surveillance.

Spinal cord injury represents a severe central nervous system trauma characterized by prolonged treatment duration, limited neural regeneration, and delayed functional recovery, greatly affecting patients′ quality of life. The impaired neural tissue struggles to recover effectively due to both the hostile microenvironment and its own compromised state. Current clinical interventions, including early reduction, laminectomy decompression, and intravenous or intrathecal methylprednisolone administration, fail to simultaneously modulate the microenvironment and improve the neural status. Zinc, a trace element abundant in the central nervous system, plays a critical role in gene expression regulation, synaptic plasticity, and neuronal activity. Clinical evidences have indicated that lower serum zinc concentration in patients with spinal cord injury correlates with poorer outcomes and animal experiments have also demonstrated the neuroprotective effects of zinc. In fact, zinc supplementation therapy has not yet been developed into a mature clinical protocol. Besides, related animal studies still lack comprehensive understanding. To this end, the authors reviewed the biological characteristics of zinc, its administration routes, neuroprotective effects and mechanisms in the management of spinal cord injury, aiming to provide references for future basic research and clinical practice.

Spinal cord injury is a highly disabling central nervous system disorder whose pathological progression is closely associated with blood-spinal cord barrier (BSCB) disruption. Physical trauma to the spine or spinal cord may compromise BSCB integrity, triggering secondary damage including spinal edema, hemorrhage, oxidative stress, and excessive inflammatory responses. For the pivotal role of protecting the spinal cord microenvironment, the repair of BSCB is crucial in the treatment of spinal cord injury. Although present studies have explored BSCB repair strategies such as biological factor regulation, biomaterial applications, and traditional Chinese medicine interventions, most studies focus on improving the overall barrier function and fail to systematically elucidate how these strategies target the core functional units of BSCB, namely the endothelial cells and their junction structures, to achieve functional and structural restoration of the barrier. Therefore, the authors reviewed the composition and key repair targets of BSCB, along with research advances in BSCB repair strategies based on endothelial cells and junction structures, aiming to provide insights for basic research and clinical treatment of spinal cord injury.

Objective:To identify and validate secreted effector proteins of Chlamydia psittaci ( C. psittaci) through bioinformatic prediction and experimental verification, and to characterize their subcellular localization in host cells. Methods:Potential effector proteins were predicted using bioinformatics tools. Candidate effectors were fused to β-lactamase through the constructed expression vectors, and these vectors were transformed into C. psittaci. The secretion of these candidate effectors was evaluated by β-lactamase translocation assays. Eukaryotic expression vectors of confirmed effectors were transfected into host cells to determine their intracellular localization patterns. Results:Bioinformatic analysis identified 29 candidate effector proteins. Experimental validation confirmed the secretion of five effectors, with four exhibiting cytoplasmic localization and one displaying nuclear localization in host cells.Conclusion:This study characterizes five novel C. psittaci secreted effector proteins, providing critical insights for investigating the molecular pathogenesis of psittacosis.

Objective:To explore the clinical characteristics and healthcare burden in patients with McCune-Albright syndrome (MAS).Methods:A cross-sectional study was conducted at the Children′s Hospital, Zhejiang University School of Medicine. Clinical and healthcare burden data were systematically collected through structured questionnaires in 164 children with MAS from February 2022 to May 2023. According to the clinical characteristics, patients were categorized into 3 groups: monosymptomatic, bisymptomatic and trisymptomatic groups. Patients were also divided into 3 groups according to the age of <7, 7-<10 and 10-18 years. Comparative analyses of clinical characteristics and healthcare burden were conducted across age, sex, and symptom categories.Results:The cohort comprised 59 males (36.0%) and 105 females (64.0%) with an age of 4.6 (2.0, 7.4) years. Age stratification revealed 117 cases (71.3%) aged 0-<7 years, 29 cases (17.7%) aged 7-<10 years, and 18 cases (11.0%) aged 10-<18 years. Among monosymptomatic (67 cases, 40.9%), the cohort comprised 32 females (47.8%) and 35 males (52.2%), predominantly presenting with fibrous dysplasia (57 cases, 85.1%). This subgroup showed peak prevalence in the 0-<7 years age range (29 cases (50.9%)). The bisymptomatic cohort (56 cases, 34.1%) consisted of 39 females (69.6%) and 17 males (30.4%), predominantly manifesting fibrous dysplasia with skin hyperpigmentation (25 cases, 44.6%). Peak prevalence occurred in the 0-<7 years subgroup(16 cases (64.0%)). The trisymptomatic cohort (41 cases, 25.0%) consisted of 34 females (82.9%) and 7 males (17.1%), with peak prevalence occurring in the 0-<7 years subgroup (36 cases (87.8%)). The diagnostic journey analysis revealed 94 cases (57.3%) required 1-3 referrals, and 34 cases (20.7%) necessitated >3 referrals from symptom onset to definitive diagnosis. Healthcare expenditure analysis revealed 69 families (42.1%) incurred direct medical costs of 10 000-100 000 CNY, with 11 families (6.7%) exceeding >100 000 CNY. Direct non-medical costs reached of 10 000-100 000 CNY for 62 families (37.8%) and >100 000 CNY for 4 families (2.4%). Productivity loss affected 58 families (35.4%) at 10 000-100 000 CNY and 8 families (4.9%) above 100 000 CNY during the study period.Conclusion:MAS requires increased attention to skeletal manifestations, especially in children aged 0-<7 years. Moreover, the significant financial burden on families necessitates a society-wide support system.

Gut microbiota,implicated in obesity,insulin resistance,depression,and cardiovascular risk,can be modulated by probiotics to mitigate cardiovascular disease risk.Vascular calcification(VC),a regulated process involving mineral deposits in vessels and valves,is a significant risk factor.Diet profoundly impacts both gut micro-biota and VC,influencing cardiovascular health via microbial metabolites.While the link between gut microbiota and VC is established,the precise dietary effects on vascular health remain unclear.This article reviews mecha-nisms through which dietary patterns shape gut microbiota and metabolites,influence VC and highlights directions for future research on VC diagnosis and treatment.

Coronary heart disease(CHD)is one of the most prevalent cardiovascular diseases in China,with a continuously growing patient population,presenting numerous challenges for personalized and precise treatment.Artificial intelligence(AI),leveraging its advantages in processing and analyzing medical data,integrates clinical information,imaging examinations,and various omics analyses to provide clinicians with accurate diag-nostic and treatment recommendations.AI plays a crucial role in risk prediction,diagnostic optimization,and the development of personalized treatment strategies.This article explores the applications of AI in the diagnosis and treatment of CHD,analyzing its contributions and challenges in risk prediction,diagnostic optimization,and treatment decision-making,while also envisioning its future developmental in the field of cardiovascular medicine.