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.

Objective To longitudinally investigate the characteristics of postoperative weight changes in patients with esophageal cancer and analyze its influencing factors, which can provide certain guidance for nutritional intervention in patients with esophageal cancer. Methods Patients with esophageal cancer who underwent surgical treatment at the Sichuan Cancer Hospital from December 2020 to February 2022 were prospectively included. The general information questionnaire and body composition analyzer were used to longitudinally investigate the patients’ weight and body composition before surgery (T0), 1 month after surgery (T1), 3 months after surgery (T2) and 6 months after surgery (T3), and the change characteristics were analyzed. The generalized estimating equation was used to analyze the influencing factors for postoperative weight changes in patients with esophageal cancer. Results A total of 130 patients were enrolled, including 110 males and 20 females, aged 42-79 (63.33±8.16) years. The weight and body composition of patients with esophageal cancer showed a continuous slow downward trend within 6 months after surgery. The weight loss rate of patients at 1, 3, and 6 months after surgery was 5.10%, 7.76%, and 9.86%, respectively. The analysis results of the influencing factors for postoperative weight showed that patients with the following characteristics had more weight loss: female (β=−7.703, P=0.001), ≥60 years (β=−3.657, P=0.010), smoking (β=4.622, P=0.010), low tumor differentiation degree (β=4.314, P=0.039), and high frequency of eating (β=−3.400, P=0.008). Conclusion Weight loss is an important health problem for patients with esophageal cancer after surgery, and patients have a continuous downward trend in weight within 6 months after surgery. Medical staff should pay special attention to the patients who are female, ≥60 years, having smoking history and low tumor differentiation degree.

Objective To construct a lung cancer surgery-oriented disease-specific database covering the entire perioperative care pathway, thereby improving the quality and usability of key surgical data elements. Methods Real-world clinical data were extracted from a single-center thoracic surgery department. A standardized data model was established based on the open electronic health record (openEHR) standard. Large language model (LLM), optical character recognition (OCR), and artificial intelligence (AI)-driven techniques were employed to extract, structure, and perform quality control on unstructured clinical narratives, imaging reports, and radiological data, with a focus on capturing surgically relevant perioperative indicator. Results A multimodal database comprising 19 917 patients was established, including 7 930 males and 11 987 females, with ages ranging from 15 to 97 (61.7±9.7) years. The database includes 582 structured data variables, textual report data corresponding to 69 clinical indicators, 13 000 pulmonary function test PDF reports, and chest CT imaging data from 16 884 patients. This database comprehensively covers major information relevant to surgical diagnosis and treatment of lung cancer, significantly improving the completeness and granularity of surgical detail data. Large language models (LLMs) and optical character recognition (OCR) technologies enhanced the efficiency of converting unstructured data into structured formats, while a multi-level manual verification process ensured data accuracy and traceability. The database supports real-world research including comparisons of surgical procedures, prediction of postoperative complications, prognosis assessment, and multimodal data association analyses.

Objective: To systematically evaluate the application effectiveness of the full disinfection process in blood stations, identify key optimization links, and provide a scientific evidence for the formulation of specialized disinfection and hygiene standards for blood collection and supply institutions. Methods: On-site microbiological monitoring was conducted using techniques such as the plate settling method and cotton swab method. Stratified random sampling was performed on eight key control points: including evironmental air, hand hygiene, skin disinfection, blood transport boxes, pressure steam sterilization, sewage treatment, ultraviolet disinfection, and sterile swabs. Statistical analysis was performed using SPSS 20.0. Measurement data were expressed as mean ± standard deviation(x-±s), and inter-group comparisons were conducted using t-tests or analysis of variance (ANOVA). Count data were expressed as rates, and inter-group comparisons were conducted using the χ test. Trend analysis was performed using the Cochran-Armitage test, with a significance level of α=0.05. Results: The colony removal rate of plasma air disinfection machines (94.2%±0.8%) was significantly higher than that of the ultraviolet group (P<0.05). The qualification rate of quick-drying disinfectant hand was 100% within 30 days after opening the bottle, but decreased to 93.3% after 40 days (P<0.01). The qualification rate of disinfection for blood transport boxes using 500 mg/L chlorine-containing disinfectant (100%) was significant higher 75% alcohol (60%, P< 0.05). Skin disinfection with 2% alcoholic chlorhexidine gluconate balanced effectiveness and user experience (satisfaction score 4.8±0.3). The qualification rates for core procedures such as pressure steam sterilization and sewage treatment were both 100%. Conclusion: The current disinfection procedures in blood collection and supply institutions are reliable. The effective usage period of hand disinfectants, disinfection methods for transport boxes, and usage duration of sterile swabs are the main points for optimization. It is recommended that the opened hand disinfectants be used for ≤30 days and that chlorine-containing disinfectants be prioritized for wiping transport boxes, providing empirical support for the revision of protocols and the formulation of standards.

Objective:To analyze the preferences of medical staff in TCM hospitals in Beijing regarding the achievements transformation of hospital traditional Chinese medicine preparations,and to provide a reference for formulating incentive policies.Methods:233 medical staff from five TCM hospitals in Beijing were taken as the research objects,and surveyed with a questionnaire designed based on the discrete choice experiment(DCE).Mixed logit models and latent class models were then used to analyze their transformation preferences.Results:The mixed Logit model revealed that seven key attributes significantly influenced medical staff's preferences for the achievements transformation of traditional Chinese medicine preparations(P<0.05).Latent class analysis identified three distinct preference groups among respondents:an organization-dependent group(27.0%),a pro-transformation group(61.4%),and a conservative group(11.6%).Conclusions:Medical Staff preferred transformation conditions that increased monthly income;utilized"human use+re-experimentation";involved the hospital's achievements transformation department as the entity;were funded by the hospital;offered a 70%profit share;enabled promotion three years earlier,and assigned patents to the hospital.The study recommends implementing diverse incentive measures and developing differentiated strategies tailored to the distinct Medical Staff categories to facilitate the transformation of hospital traditional Chinese medicine preparations into new drugs.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

Objective:By using cognitive interviews,the interviewees' cognition and understanding of the inflammatory bowel disease(IBD) self-efficacy scale for adolescents and young adults (IBDSES-A) were evaluated,and the semantic content of IBDSES-A,which was initially translated into Chinese,was tested and revised.Methods:Using purposive sampling,15 IBD patients aged 12-18 were selected from Beijing Children's Hospital,Capital Medical University,between January and February 2025,stratified by age group and disease type.Two rounds of cognitive interviews were conducted.Feedback and suggestions from interviewees were analyzed using a question appraisal system for coding and integration.Based on expert panel discussions,ambiguous items were revised to finalize the Chinese version of the IBDSES-A.Results:In the first round,10 interviewees were interviewed,followed by 5 interviewees in the second round.There were no statistically significant differences ( P>0.05) between the interviewees of two rounds in terms of age,gender,and education level.During the first round of interview,interviewees expressed comprehension difficulties with 76.9% (10/13) of the items.Coding analysis revealed that the primary issue was "clarification",as unclear wording made it difficult for interviewees to fully grasp the intended meaning of certain items.Based on these findings,the expert panel revised 10 of the 13 items in the IBDSES-A.The second round of cognitive interview showed that the interviewees generally understood the revised items，achieving linguistic and semantic consistency with the original scale. Conclusion:The application of cognitive interviews in the translation process of the IBDSES-A helps reduce comprehension biases caused by inappropriate wording，ensuring that the localized version of the scale is more accessible and understandable to the target population.

The working principle of Bausch&Lomb BL11110 phacoemulsification system was described.Three cases of typical faults of the phacoemulsification system were introduced,and the causes were analyzed,then the maintenance measures were given accordingly.References were provided for diagnosing and eliminating the faults of the phacoemulsification system.[Chinese Medical Equipment Journal,2025,46(4):118-120]

Objective To compare the value of ultrashort echo time(UTE)and T1W sequences for detecting bone erosions of gouty arthritis.Methods Forty-four gouty patients were prospectively enrolled,including 32 cases with affected feet and 12 cases with affected knee.MR UTE and T1W sequence scanning of the affected area were performed,and subjectively scoring of imaging quality of 2 kinds of MRI were evaluated,respectively.Then total number and total score of bone erosions of each case were calculated according to all affected bones.Taken DECT as reference standard,the efficacy of UTE and T1WI for detecting bone erosions was assessed through comparing with DECT using Kappa coefficient.Results The imaging quality score of T1WI was lower than that of DECT(all P＜0.05),while no significant difference was found between UTE and DECT(all P＞0.05).There was high agreement between UTE and DECT for detecting bone erosions(κ=0.949),while the agreement between T1WI and DECT ranged from good to high(κ=0.718 to 0.805).The total number and total score of bone erosions based on T1WI were significantly lower than those based on DECT(all P＜0.05),while no significant difference was found between UTE and DECT(all P＞0.05).Conclusion UTE was better than T1WI for detecting bone erosions of gouty arthritis.