Objective To evaluate the predictive value of different machine learning models constructed in a multicenter environment for potential organ donors and verify their clinical application feasibility. Methods The study included 2 000 inpatients admitted to five domestic tertiary hospitals from January 2020 to December 2023, who met the criteria for potential organ donation assessment. They were randomly divided into a training set and an internal validation set (7∶3). Another 300 similar patients admitted to the First Affiliated Hospital of Harbin Medical University from January 2024 to April 2025 were included as an external validation set. The area under the curve (AUC), sensitivity, specificity, accuracy and F1-score of three models were compared, and the consistency of the potential organ donor determination process was tested. Multivariate logistic regression analysis was used to identify predictive factors of potential organ donors. Decision curve analysis (DCA) was employed to verify the resource efficiency of each model, and the threshold interval and intervention balance point were assessed. Results Apart from age, there were no significant differences in other basic characteristics among the centers (all P>0.05). The consistency of the potential organ donor determination process among researchers in each center was good [all 95% confidence interval (CI) lower limits >0]. In the internal validation set, the XGBoost model had the best predictive performance (AUC=0.92, 95% CI 0.89-0.94) and the best calibration (P=0.441, Brier score 0.099). In the external validation set, the XGBoost model also had the best predictive performance (AUC=0.91, 95% CI 0.88-0.94), outperforming logistic regression and random forest models. Multivariate logistic regression showed that mechanical ventilation had the greatest impact (odds ratio=2.06, 95% CI 1.54-2.76, P<0.001). DCA indicated that the XGBoost model had the highest net benefit in the threshold interval of 0.2-0.6. The “treat all” strategy only had a slight advantage at extremely low thresholds. The recommended threshold interval, which balances intervention costs and clinical benefits, considers ≥50% positive predictive value (PPV) and ≤50 referrals per 100 high-risk patients. Conclusions The XGBoost model established in a multicenter environment is accurate and well-calibrated in predicting potential organ donors. Combined with DCA, it may effectively guide the timing of clinical interventions and resource allocation, providing new ideas for the assessment and management of organ donation after brain death.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

ObjectiveIn order to provide a reference for the optimization of preparation process of stir-fried Glycyrrhizae Radix et Rhizoma（sf-GRR）， the quality changes during the processing was studied. MethodsGlycyrrhizae Radix et Rhizoma was processed by stir-frying for 17 min， and samples were collected every 1 min during the processing. The appearance color of the samples was determined by visual analysis technology， the moisture and extract of the process samples were detected by the drying method and the hot extraction method of alcohol-soluble extract in the general rules of the 2020 edition of Chinese Pharmacopoeia（part Ⅳ）， and the contents of liquiritin apioside， liquiritin， isoliquiritin apioside， isoliquiritin， licoricesaponin G₂ and glycyrrhizic acid in the process samples were determined by high performance liquid chromatography（HPLC）. Then principal component analysis（PCA）， partial least squares-discriminant analysis（PLS-DA） and Spearman correlation analysis were used for clustering， discrimination and correlation analysis of the appearance color， moisture， extract and the contents of six internal components. Based on artificial neural network and random forest algorithm， the prediction model of processing degree of sf-GRR was established. On this basis， based on the five principles of quality marker（Q-Maker）， explore the monitoring Q-Maker of sf-GRR. ResultsThe color of Glycyrrhizae Radix et Rhizoma deepened after stir-frying， and the appearance color of the sample changed from light yellow to dark yellow during processing. During the stir-frying process， the moisture content showed a decreasing trend with the extension of processing time， while the extract content showed an increasing trend with the extension of processing time. After stir-frying， the contents of liquiritin apioside， liquiritin and licoricesaponin G₂ showed an overall decreasing trend， while the contents of isoliquiritin apioside and isoliquiritin increased， and the content of glycyrrhizic acid increased slightly. The correlation analysis showed that moisture was positively correlated with brightness（L^*） and red/green value（a^*）， and negatively correlated with yellow/blue value（b^*） and total color difference（E^*ab）. Isoliquiritin apioside and isoliquiritin had negative correlation with L^* and a^*， and positive correlation with b^* and E^*ab. The processing process of sf-GRR could be divided into two stages of the early stage（0-14 min） and the late stage（15-17 min）， and could be divided into three stages of the early stage（0-6 min）， the middle stage（7-14 min） and the late stage（15-17 min） by combining the moisture， extract， the contents of 6 components and color values. Based on artificial neural network analysis and random forest algorithm， isoliquiritin apioside， isoliquiritin， liquiritin and glycyrrhizic acid were selected as monitoring markers for sf-GRR. ConclusionBased on the analysis of the exterior-interior indicators of process samples of sf-GRR， this paper ultimately identifies four processing monitoring markers， which can provide a basis for optimizing the processing technology of sf-GRR.

OBJECTIVE To provide reference for improving the pre-prescription review system and reducing the occurrence of medication error by analyzing the drug-related problems （DRPs） in the pre-prescription review orders of pediatric outpatient clinics using the Pharmaceutical Care Network Europe （PCNE） classification system. METHODS The data of pre-prescription review orders were retrospectively collected from outpatient department of Shanghai Children’s Medical Center， Shanghai Jiao Tong University School of Medicine from July 2022 to June 2023； DRPs in the pre-prescription review orders were classified and summarized by using the PCNE classification system （version 9.1）， and then analyzed in terms of types and causes of issues， and the acceptance of interventions. RESULTS A total of 66 017 DRPs orders were included， involving 41 165 patients. The proportion of DRPs orders in children aged ≤5 years old was the highest （58.25%）， followed by children aged 6-12 years old （33.52%）； the department with the highest proportion of DRPs was internal medicine of pediatrics department （71.41%）； the department with the highest incidence of DRPs was thoracic surgery department （9.73%）； top three drug categories of DRPs orders were systemic anti- infective drugs （25.26%）， Chinese patent medicines （24.74%） and respiratory drugs （22.38%）. Referring to PCNE classification system， the types of DRPs mainly focused on treatment safety （64.86%）； the reasons of DRPs orders mainly focused on dose selection （82.09%）， of which 41.26% were due to excessive drug dosage； 92.13% of interventions could be accepted and fully executed by doctors. CONCLUSIONS DRPs orders identified by the pre-prescription review system can be effectively analyzed by using PCNE classification system. Pharmacists should focus on medication use in children aged ≤5 years old， update and develop personalized prescription review rules timely， and meet the rational needs of clinical medication for children.

OBJECTIVE To improve the efficiency and quality of dispensed oral drug management in the inpatient pharmacy， and ensure the safety of drug use in patients. METHODS SWOT （strength， weakness， opportunity， threat） analysis method was used to analyze the internal strengths and weaknesses， as well as the external opportunities and threats in the construction of a closed-loop management system for dispensed oral drugs in the inpatient pharmacy of our hospital， and propose improvement strategies. RESULTS & CONCLUSIONS A refined， full-process， closed-loop traceability management system for dispensed oral drugs in the inpatient pharmacies was successfully established， which is traceable in origin， trackable in destination， and accountable in responsibility. After the application of this system， the registration rate of dispensed drug information and the correctness rate of registration content both reached 100%. The proportion of overdue drug varieties in the same period of 2024 decreased by 77.78% compared to March 2020， the inventory volume decreased by 29.50% compared to the first quarter of 2020， the per-bed medication volume decreased by 32.14% compared to the first quarter of 2020； the average workload per post in the same period of 2023 increased by 49.09% compared to 2019， the dispensing accuracy rate reached 100%， and the improvement rate of quality control problem increased by 25.25% compared to 2021. This system effectively improves the safety and accuracy of dispensed oral drug management in the inpatient pharmacy.

BACKGROUND:Studies have shown that metformin has anti-inflammatory,anti-tumor,anti-aging and vasoprotective effects,and can inhibit the progression of osteoarthritis,but its specific mechanism of action remains unclear. OBJECTIVE:To investigate the mechanism of metformin on cartilage protection in a rat model of osteoarthritis. METHODS:Forty male Sprague-Dawley rats were randomly divided into four groups(n=10 per group):blank,control,sham-operated,and metformin groups.The blank group did not undergo any surgery.In the sham-operated group,the joint cavity was exposed.In the model group and the metformin group,the modified Hulth method was used to establish the osteoarthritis model.At 1 day after modeling,the rats in the metformin group were given 200 mg/kg/d metformin by gavage,and the model,blank,and sham-operated groups were given normal saline by gavage.Administration in each group was given for 4 weeks consecutively.Hematoxylin-eosin staining,toluidine blue staining,and safranin O-fast green staining were used to observe the morphological structure of rat knee joints.Immunohistochemical staining and western blot were used to detect the protein expression of SOX9,type Ⅱ collagen,a disintegrin and metalloproteinase with thrombospondin motifs 5(ADAMTS5),Beclin1,P62,phosphatidylinositol 3-kinase(PI3K),p-PI3K,protein kinase B(AKT),p-AKT,mammalian target of rapamycin(Mtor),and p-Mtor in rat cartilage tissue. RESULTS AND CONCLUSION:The results of hematoxylin-eosin,toluidine blue and safranin O-fast green staining showed smooth cartilage surface of the knee joints and normal histomorphology in the blank group and the sham-operated group,while in the model group,there was irregular cartilage surface of the knee joint and cartilage damage,with a decrease in the number of chondrocytes and the content of proteoglycans in the cartilage matrix.In the metformin group,there was a significant improvement in the damage to the structure of the cartilage in the knee joints of the rats,and the cartilage surface tended to be smooth,with an increase in the number of chondrocytes and the content of proteoglycans in the cartilage matrix.Immunohistochemistry staining and western blot results showed that compared with the control and sham-operated groups,the expression of SOX9,type Ⅱ collagen,and Beclin1 proteins in the cartilage tissue of rats in the model group was significantly decreased(P<0.05).Conversely,the expression of ADAMTS5,P62,as well as p-PI3K,p-AKT,and p-Mtor proteins was significantly increased(P<0.05).Furthermore,compared with the model group,the expression of SOX9,type Ⅱ collagen,and Beclin1 proteins in the cartilage tissue of rats in the metformin group was significantly increased(P<0.05),while the expression of ADAMTS5,P62,as well as p-PI3K,p-AKT,and p-Mtor proteins was significantly decreased(P<0.05).To conclude,Metformin can improve the autophagy activity of chondrocytes and reduce the degradation of cartilage matrix in osteoarthritis rats by inhibiting the activation of PI3K/AKT/Mtor signaling pathway,thus exerting a protective effect on articular cartilage.

With the widespread use of antibiotics, drug-resistant bacterial infections have become a significant threat to human health. Finding new antibacterial strategies that can effectively control drug-resistant bacterial infections has become an urgent task. Unlike small molecule drugs that target bacterial proteins, antisense oligonucleotide (ASO) can target genes related to bacterial resistance, pathogenesis, growth, reproduction and biofilm formation. By regulating the expression of these genes, ASO can inhibit or kill bacteria, providing a novel approach for the development of antibacterial drugs. To overcome the challenge of delivering antisense oligonucleotide into bacterial cells, various drug delivery systems have been applied in this field, including cell-penetrating peptides, lipid nanoparticles and inorganic nanoparticles, which have injected new momentum into the development of antisense oligonucleotide in the antibacterial realm. This review summarizes the current development of small nucleic acid drugs, the antibacterial mechanisms, targets, sequences and delivery vectors of antisense oligonucleotide, providing a reference for the research and development of antisense oligonucleotide in the treatment of bacterial infections.

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.

Guided by Academician Zhang Boli's theory of "dampness， turbidity， phlegm， and fluid-related diseases"，this paper elaborated on the pathogenesis and syndrome differentiation treatment of heart failure from the perspective of the "spleen-mitochondria". It analyzed the essential similarities between "spleen-mitochondria" and "dampness， turbidity， phlegm， and fluid-related diseases"， as well as their close association with the onset of heart failure. Furthermore，it explored the connection between spleen function and mitochondrial function in traditional Chinese medicine （TCM），positing that the spleen's role in transportation and transformation is analogous to mitochondrial material metabolism and energy conversion，with spleen deficiency closely related to mitochondrial dysfunction. It thus concluded that mitochondrial material metabolism and energy conversion represent the microscopic essence of the spleen's role in transportation and transformation，and mitochondrial dysfunction is a contributing factor to pathological products like dampness and turbid phlegm，which are closely associated with the occurrence of heart failure. The four elements of dampness，turbidity，phlegm，and fluid are a series of related symptoms resulting from abnormal fluid transportation and transformation，serving as both factors in the onset of heart failure and the core pathological basis for its deterioration. Therefore，during the treatment of heart failure，it is essential to regulate mitochondrial function. Early intervention should focus on eliminating dampness and turbidity to improve mitochondrial function and restore normal energy metabolism. In the middle and late stages，emphasis should be placed on resolving phlegm，promoting blood circulation，warming Yang，and reducing water retention to alleviate mitochondrial damage and improve cardiac function. Supporting Qi and strengthening the spleen should be a continuous approach，and treatment should be adjusted to enhance mitochondrial function and stabilize the condition，thereby improving prognosis. This paper discussed the role of the spleen and mitochondria in the pathogenesis of heart failure，examined the evolution of heart failure mechanisms from the perspective of dampness， turbidity， phlegm， and fluid-related diseases，and proposed a phased treatment strategy. It enriched the theory of dampness， turbidity， phlegm， and fluid-related diseases and offered new strategies for heart failure treatment. However，in practical application，TCM strategies for treating heart failure need to be integrated with modern medical approaches to provide a more solid scientific foundation for treatment.

Disorders of consciousness (DOC) are pathological conditions characterized by severely suppressed brain function and the persistent interruption or loss of consciousness. Accurate diagnosis and evaluation of DOC are prerequisites for precise treatment. Traditional assessment methods are primarily based on behavioral scales, which are inherently subjective and rely on observable behaviors. Moreover, traditional methods have a high misdiagnosis rate, particularly in distinguishing minimally conscious state (MCS) from vegetative state/unresponsive wakefulness syndrome (VS/UWS). This diagnostic uncertainty has driven the exploration of objective, reliable, and efficient assessment tools. Among these tools, electroencephalography (EEG) has garnered significant attention for its non-invasive nature, portability, and ability to capture real-time neurodynamics. This paper systematically reviews the application of EEG biomarkers in DOC assessment. These biomarkers are categorized into 3 main types: resting-state EEG features, task-related EEG features, and features derived from transcranial magnetic stimulation-EEG (TMS-EEG). Resting-state EEG biomarkers include features based on spectrum, microstates, nonlinear dynamics, and brain network metrics. These biomarkers provide baseline representations of brain activity in DOC patients. Studies have shown their ability to distinguish different levels of consciousness and predict clinical outcomes. However, because they are not task-specific, they are challenging to directly associate with specific brain functions or cognitive processes. Strengthening the correlation between resting-state EEG features and consciousness-related networks could offer more direct evidence for the pathophysiological mechanisms of DOC. Task-related EEG features include event-related potentials, event-related spectral modulations, and phase-related features. These features reveal the brain’s responses to external stimuli and provide dynamic information about residual cognitive functions, reflecting neurophysiological changes associated with specific cognitive, sensory, or behavioral tasks. Although these biomarkers demonstrate substantial value, their effectiveness rely on patient cooperation and task design. Developing experimental paradigms that are more effective at eliciting specific EEG features or creating composite paradigms capable of simultaneously inducing multiple features may more effectively capture the brain activity characteristics of DOC patients, thereby supporting clinical applications. TMS-EEG is a technique for probing the neurodynamics within thalamocortical networks without involving sensory, motor, or cognitive functions. Parameters such as the perturbational complexity index (PCI) have been proposed as reliable indicators of consciousness, providing objective quantification of cortical dynamics. However, despite its high sensitivity and objectivity compared to traditional EEG methods, TMS-EEG is constrained by physiological artifacts, operational complexity, and variability in stimulation parameters and targets across individuals. Future research should aim to standardize experimental protocols, optimize stimulation parameters, and develop automated analysis techniques to improve the feasibility of TMS-EEG in clinical applications. Our analysis suggests that no single EEG biomarker currently achieves an ideal balance between accuracy, robustness, and generalizability. Progress is constrained by inconsistencies in analysis methods, parameter settings, and experimental conditions. Additionally, the heterogeneity of DOC etiologies and dynamic changes in brain function add to the complexity of assessment. Future research should focus on the standardization of EEG biomarker research, integrating features from resting-state, task-related, and TMS-EEG paradigms to construct multimodal diagnostic models that enhance evaluation efficiency and accuracy. Multimodal data integration (e.g., combining EEG with functional near-infrared spectroscopy) and advancements in source localization algorithms can further improve the spatial precision of biomarkers. Leveraging machine learning and artificial intelligence technologies to develop intelligent diagnostic tools will accelerate the clinical adoption of EEG biomarkers in DOC diagnosis and prognosis, allowing for more precise evaluations of consciousness states and personalized treatment strategies.