As a distinctive resource of Chinese civilization， traditional Chinese medicine （TCM） technology transfer faces significant opportunities under the background of digital and intelligent transformation， while also being constrained by unique challenges such as the complexity of its theoretical system， lengthy industrial chains， and multidimensional policy restrictions， resulting in a "high-value-high-threshold" paradox. At present， TCM technology transfer is deeply trapped in a "threefold reluctance" dilemma， i.e.， unwillingness to transfer， inability to transfer， and lack of capacity to transfer. Specifically， the disconnection between scientific research evaluation systems and market demand leads to low conversion rates of research achievements， unclear ownership and compliance risks suppress innovation incentives， and the absence of professional services intensifies supply-demand mismatches. This article systematically analyzes the specific characteristics of TCM technology transfer and proposes a breakthrough pathway centered on full-chain digital and intelligent transformation. By integrating technologies such as intelligent sorting systems， blockchain-based traceability， and AI diagnostic models， the TCM ecosystem spanning "cultivation-production-service" can be reconstructed. In terms of standardization， promoting the progression from "experience-based data conversion" to "data standardization" and further to "intelligent standardization" is advocated to resolve quality control challenges. For example， a "three-no-one-full" certification system can strengthen quality trust. Policy coordination should focus on optimizing mechanisms for the transformation of scientific and technological achievements， while exploring intellectual property securitization and risk-sharing models to stimulate research momentum. In terms of internationalization， reliance on the Belt and Road Initiative platform to promote the export of geo-authentic medicinal material brands and standards is recommended to build a dual-driven model of "technology plus culture". Looking ahead， through the construction of national-level databases， the cultivation of interdisciplinary talent， and the mutual recognition of international standards， a new paradigm of "scientific intelligent manufacturing" can be formed， providing systematic solutions for the modernization of TCM and global health governance.

OBJECTIVE To clarify the roles and functions of full-time pharmacists in the management of early-phase clinical trials of antineoplastic drugs， and to provide theoretical and practical support for their transformation from traditional drug managers to multi-dimensional roles in clinical research. METHODS Combined with relevant regulations such as the Good Clinical Practice （GCP） （2020 Edition）， and based on the clinical practice experience of the Phase Ⅰ Clinical Ward in our hospital， this study systematically sorted out full-time pharmacists’ roles and functions in early-phase clinical trials of antineoplastic drugs， and explored the core challenges and optimization pathways for role transformation and capacity-building of domestic full-time clinical trial pharmacists. RESULTS & CONCLUSIONS Full-time pharmacists assumed multiple roles in early-phase clinical trials of antineoplastic drugs， including providing pharmaceutical support for protocol design， implementing whole-process standardized management of clinical trial drugs， ensuring medication safety for clinical trial subjects/participants， conducting quality control throughout the clinical trial process， and serving as a bridge for interdisciplinary collaboration and communication. Currently， there are challenges in this field in China， such as unclear roles， an imperfect capacity building system， and insufficient regulatory support. This paper proposes that by establishing a standardized role framework， clarifying the core responsibilities and authorities of full-time pharmacists， and leveraging cutting-edge technologies to provide comprehensive support for their roles， so as to fully harness their pharmaceutical expertise and contribute to the standardization and efficiency of the antineoplastic new drug development process.

Objective To investigate the effect of bone metabolic markers on sarcopenia in elderly patients with type 2 diabetes mellitus (T2DM). Methods A total of 412 patients with T2DM in the department of endocrinology of Nanjing Central Hospital from May 2020 to June 2025 were selected as the research subjects. According to Asian Working Group for Sarcopenia (AWGS) in 2019, these patients were evaluated for skeletal muscle mass index (ASMI), muscle strength, and muscle function, and were divided into a sarcopenia group (84 cases) and a non-sarcopenia group (328 cases). The glucolipid metabolic indexes were detected in both groups of patients, and the bone metabolic markers were evaluated, including procollagen type 1 N-terminal peptide (P1NP), beta-C-terminal telopeptide of type 1 collagen (β-CTX), and 25-hydroxy vitamin D [25-(OH)D]. The factors influencing the occurrence of sarcopenia in T2DM patients were analyzed by logistic regression analysis, and the diagnostic values of bone metabolic markers on sarcopenia in patients with T2DM were assessed by ROC curve. Results The levels of P1NP and 25-(OH)D were lower, while β-CTX level was higher in the sarcopenia group compared to the non-sarcopenia group, with statistical differences (P<0.05). After logistic correlation analysis, it was found that P1NP, β-CTX and 25-(OH)D were all influencing factors for the occurrence of sarcopenia in T2DM patients. ROC curve analysis suggested that combined detection of PINP, β-CTX, and 25-(OH)D had higher diagnostic value, with an area under the curve up to 0.805. Conclusion The abnormal expression of bone metabolic markers is associated with the increased risk of sarcopenia in patients with T2DM. The detection of serum bone metabolic markers expression level is of certain significance for the assessment of diabetes-related sarcopenia.

Objective: To analyze the trajectories of blood pressure and body mass index (BMI) among primary and secondary school students aged 7-17 in Shunyi District of Beijing, and to explore the association between different growth trajectories and visual outcomes, so as to provide a scientific basis for the prevention and control of common diseases in children and adolescents. Methods: Health examination data (including vision, blood pressure and BMI) of primary and secondary school students in Shunyi District of Beijing from 2019 to 2023 were collected and analyzed. Group based trajectory modeling was used to classify the trajectories of BMI and blood pressure (systolic and diastolic) into distinct groups among students aged 7-17 years. The relationship between these trajectories and visual outcomes was examined using binary Logistic regression analysis. Results: The prevalence of screening myopia among students in Shunyi District was 57.2%, while the rate of moderate to severe visual impairment was 55.8%. Based on the latent growth model, the trajectories of systolic blood pressure, diastolic blood pressure, and BMI were divided into three groups:low growth trajectory, moderate growth trajectory and high maintenance trajectory. Logistic regression analysis revealed that, compared to the low growth trajectory group, the moderate growth and high maintenance trajectory groups for systolic blood pressure, diastolic blood pressure, and BMI were associated with an increased risk of screening myopia ( OR =1.14, 1.11; 1.07, 1.19 ; 1.06, 1.08, P <0.05). Similarly, the moderate growth and high maintenance trajectory groups for systolic blood pressure, diastolic blood pressure, and BMI were similarly associated with an increased risk of moderate to severe visual impairment ( OR = 1.12 , 1.12; 1.09, 1.17; 1.08, 1.11, P <0.05). Conclusions Moderate growth and high maintenance trajectories of blood pressure and BMI are associated with an increased risk of screening myopia and moderate to severe visual impairment among students. It is recommended to closely monitor changes in blood pressure and overweight/obesity trajectories in primary and secondary school students, conduct regular assessments, and actively prevent the development and progression of multimorbidity and comorbidity.

Objective: To analyze the change trends in the body shape indicators and proportions of students in Harbin from 2010 to 2024, and to investigate ergonomic compatibility of functional dimensions of school desks and chairs with current student shape indicators, so as to provide a reference for revising furniture standards of desks and chairs. Methods: Between September and November of both 2010 and 2024, a combination of convenience sampling and stratified cluster random sampling was conducted across three districts in Harbin, yielding samples of 6 590 and 6 252 students, respectively. Anthropometric shape indicators cluding height, sitting height, crus length, and thigh length-and their proportional changes were compared over the 15-year period. The 2024 data were compared with current standard functional dimensions of school furniture. The statistical analysis incorporated t-test and Mann-Whitney U- test. Results: From 2010 to 2024, average height increased by 1.8 cm for boys and 1.5 cm for girls; sitting height increased by 1.5 cm for both genders; crus length increased by 0.3 cm for boys and 0.4 cm for girls; and thigh length increased by 0.5 cm for both genders. The ratios of sitting height to height, and sitting height to leg length increased by less than 0.1 . The difference between desk chair height and 1/3 sitting height ranged from 0.4-0.8 cm. Among students matched with size 0 desks and chairs, 22.0% had a desk to chair height difference less than 0, indicating that the desk to chair height difference might be insufficient for taller students. The differences between seat height and fibular height ranged from -1.4 to 1.1 cm; and the differences between seat depth and buttock popliteal length ranged from -9.8 to 3.4 cm. Among obese students, the differences between seat width and 1/2 hip circumference ranged from -20.5 to -8.7 cm, while it ranged from -12.2 to -3.8 cm among non obese students. Conclusion Current furniture standards basically satisfy hygienic requirements; however, in the case of exceptionally tall and obese students, ergonomic accommodations such as adaptive seating allocation or personalized adjustments are recommended to meet hygienic requirements.

Phase Ⅰ clinical trials play a crucial role in the research and development of new drugs, serving as the initial studies to assess their safety, tolerability, effectiveness, and pharmacokinetic properties in humans. These trials involve uncertainties regarding safety and efficacy. Comprehensive management of all aspects of phase Ⅰ clinical trials for anti-tumor drugs is crucial to protect the rights and safety of participants. This article provides an in-depth analysis of the key points and precautions necessary for effective quality control throughout the process. The analysis is informed by guidelines such as the “Good Clinical Practice for Drugs” “Key Points and Judgment Principles for Drug Registration Verification” “Key Points and Judgment Principles for Supervision and Inspection of Drug Clinical Trial Institutions” and the standard operating procedures for quality control of the center. Topics discussed include informed consent, inclusion criteria, experimental drugs, biological samples, adverse events, and serious adverse events. The goal is to standardize quality control in phase Ⅰ clinical trials of anti-tumor drugs, ensure the authenticity and reliability of clinical trial data, and protect the rights and safety of participants.

Objective To develop a machine learning-based risk prediction model for postoperative acute kidney injury(AKI)and a model for mortality in obese patients admitted to intensive care unit(ICU)in order to improve early warning and prognostic evaluation to support clinical decision-making.Methods Data of obese postoperative ICU patients were retrospectively retrieved from the MIMIC-Ⅳ and eICU databases for statistical analysis.Ultimately,2 520 patients(670 from MIMIC-Ⅳ and 1 850 from eICU databases)were included to build the risk prediction models for AKI and mortality.The data included demographic information,vital signs,laboratory findings,surgical types,comorbidities,and medication use.After data cleaning and preprocessing,Boruta feature selection was applied,followed by the construction of prediction models using 7 machine learning algorithms,that is,Gradient Boosting Machine(GBM),Generalized Linear Model(GLM),k-Nearest Neighbors(KNN),Na?ve Bayes(NB),Neural Network(NNET),Support Vector Machine(SVM),and XGBoost.Model performance was evaluated through cross-validation and external validation.Results In the risk prediction models of AKI,the SVM model achieved the highest AUC value of 0.80 in the testing set and 0.71 in the external validation test.For the risk prediction models of mortality,the GBM model outperformed others in the prediction,attaining an AUC value of 0.91 in the testing set.Conclusion Risk predictive models for postoperative AKI and mortality in obese ICU patients are successfully constructed,and are valuable tools for clinicians to optimize early intervention and improve clinical outcomes for the patients.

In this study,an ON/OFF type micro-valve with a sandwich(glass-silicon-glass)structure was designed and fabricated based on the micro-electro-mechanical system(MEMS)technique.The deformable membrane of this micro-valve was prepared on the silicon on insulator(SOI)substrate and sealed using Si-Si bonding and anodic bonding methods.The micro-valve had high-temperature stability and was suitable for integration with other gas chromatography components.The deformable membrane with a thickness of 10 μm was processed on the top silicon of the SOI substrate.The flow control of the micro-valve could be achieved by changing the driving pressure applied to the deformable membrane to deform it.Compared with polymer membranes,the deformable membrane prepared on the top layer silicon of SOI had better temperature stability and could be released using the deep reactive ion etching technique after silicon-silicon bonding,avoiding deformation during the preparation process.In addition,due to the small gap between the membrane and the inlet/outlet holes,the dead volume of the microvalve was very small.The test results indicated that the micro-valve achieved flow control and ON/OFF functions with good repeatability.

A novel analytical method was developed in this study by combining online solid phase extraction with ultra performance liquid chromatography-tandem mass spectrometry(Online SPE-UPLC-MS/MS)for simultaneous determination of 50 kinds of steroid hormones in surface water.Specifically,after high-speed centrifugation of 4 mL water samples,the supernatant was directly injected into an Oasis HLB online SPE column for enrichment and purification.Subsequently,the target compounds were transferred to the analytical column via valve switching for separation and analysis.The chromatographic separation was performed on a Thermo Acclaim RSLC C18 column(100 mm×2.1 mm,2.2 μm),using a mobile phase composed of 5 mmol/L ammonium fluoride aqueous solution and acetonitrile.Mass spectrometric detection was conducted in positive ion mode,utilizing multiple reaction monitoring(MRM)with quantification achieved by the internal standard method.The method validation demonstrated that the limits of detection(LOD)for the 50 kinds of steroid hormones ranged from 0.02 to 0.50 ng/L,while the limits of quantification(LOQ)were between 0.08 and 1.67 ng/L.The average recoveries in surface water samples at spiked concentrations of 5,20 and 200 ng/L were between 74.1％and 119％,with relative standard deviations(RSDs)of 0.2％to 9.9％.This method was applied to analyze 11 surface water samples collected from sites surrounding a pharmaceutical and chemical industrial park.A total of 44 kinds of steroid hormones were detected,with concentrations ranging from 0.11 to 88.6 ng/L,revealing the presence of hormone contamination in the environmental waters surrounding industrial areas.Compared with the traditional offline SPE methods,the proposed online SPE technique significantly reduced sample volume requirements and pretreatment time,while minimizing the loss of target compounds during the pretreatment process.Moreover,compared to reported online SPE techniques,this method achieved high-throughput analysis of multiple classes of steroid hormones,with lower detection limits and higher recoveries.Overall,this method provided rapid sample preparation,high sensitivity,and excellent stability,making it suitable for the direct analysis of trace steroid hormones in surface water.

A monolithic integrated gas chromatography chip,consisting of a micro gas chromatography column(μGCC)and a micro helium discharge ionization detector(μHDID)was proposed.The chip was fabricated using micro electromechanical system(MEMS)technique,and its sensitivity was improved from two aspects.On one hand,open tubular column was selected as the separation device,and the auxiliary helium channel width of μHDID was modulated based on the microchannel width of the μGCC to match the flow rates of μHDID and μGCC.On the other hand,the electrode structure inside the μHDID collection zone was optimized,a bias electrode group around the collection electrode was constructed,and the ion collection efficiency was improved.After coating HKUST-1 as the stationary phase,the monolithic integrated gas chromatography chip could achieve baseline separation and detection of light hydrocarbon gas mixture(methane,ethane,propane,andn-butane),with a detection limit for propane as low as 25 pg.The chip could carried out test under temperature-programmed conditions,with a resolution of 9.24 for ethane and propane.