OBJECTIVE To formulate the Expert Consensus on the Implementation and Management of Drug Selection for Centralized Volume-Based Procurement in Medical Institutions of Guangxi （hereinafter referred to as the “ Consensus ”）， and to provide decision-making support and practical guidance for the drug selection and management of centralized volume-based procurement （hereinafter referred to as “centralized procurement”） drugs in medical institutions at all levels in Guangxi. METHODS A systematic review was conducted on the materials from previous batches of centralized procurement implemented in Guangxi. A comprehensive search was carried out for drug-related works and books， along with a systematic collation of guidelines on drug selection， expert consensus on centralized procurement， and policy documents. Through three rounds of specialized seminars， combined with existing evidence-based data and the practical drug selection experiences of medical institutions at various levels， this Consensus was formulated after thorough discussion and successive rounds of revision. RESULTS & CONCLUSIONS The Consensus systematically outlines the three key stages in the implementation of centralized procurement in medical institutions： procurement volume reporting， confirmation of agreed procurement volume， and procurement and usage implementation. It proposes drug selection strategies for centralized procurement bas ed on multiple dimensions， including specifications， dosage forms， packaging materials， fill volume， and manufacturing enterprises. In response to practical challenges encountered in the selection process， corresponding countermeasures are proposed， such as establishing a regularized information reserve mechanism， strengthening information technology support， and implementing categorized selection approaches. The Consensus advocates for medical institutions to construct an integrated “policy， data， and quality” decision-making system to promote full-cycle management of centralized procurement. This Consensus will provide scientific and practical guidance for medical institutions at all levels in Guangxi in the drug selection of centralized procurement， facilitating the smooth implementation and sustainable development of centralized procurement policies at the institutional level.

Objective: To investigate the impact of milk and egg supplementation on body composition and bone mineral density of rural primary school students in Yunnan Province, so as to provide a reference for developing targeted nutritional intervention strategies. Methods: In December 2023, a cluster sampling method was adopted to select students from grades one to three in four primary schools each from Jinggu and Shidian countys of Yunnan Province, as the intervention group (662 students). Additionally, two boarding primary schools were selected from each county based on the principle of matching scale and student numbers as the control group (455 students). Starting from April 2023, the intervention group received 200 mL milk and 50 g eggs during the break on school days for 8 months, while the control group maintained their usual diet behavior. Body composition was measured by using bioelectrical impedance analysis, and distal radial bone mineral density was assessed via dual energy X-ray absorptiometry in April and December 2023. The intervention effects were analyzed by using a difference in-differences approach. Results: The final measurements of body fat percentage, skeletal muscle mass and fat free mass of the intervention group and the control group of primary school students were significantly higher than the baseline values, and the net effect of milk and egg intervention on these body composition indicators was not statistically significant ( P >0.05, both before and after adjustment). In contrast, bone mineral density increased significantly by 0.02 g/cm 2 in the intervention group. The net intervention effect on bone mineral density was statistically significant ( β=0.02, 95%CI =0.00-0.04), and remained significant after model adjustment ( β=0.02, 95%CI =0.00-0.04) (both P < 0.05). Subgroup analysis showed statistically significant effects of the intervention among girls ( β=0.02, 95%CI =0.00-0.04), day students ( β=0.04, 95%CI =0.01-0.07), and students with normal nutritional status ( β=0.02, 95%CI =0.00-0.04) (all P <0.05). No significant effect of milk and egg supplementation was observed on body composition indicators (all P <0.05). Conclusions Milk and egg supplementation can improve bone mineral density among rural primary school students in Yunnan Province. It is recommended that rural school aged children should increase intake of milk and eggs to support growth and development.

Objective:To construct an artificial intelligence (AI)-assisted system based on deep learning for corneal in vivo confocal microscopy (IVCM) image recognition and to evaluate its value in clinical applications. Methods:A diagnostic study was conducted.A total of 18 860 corneal images were collected from 331 subjects who underwent IVCM examination at Renmin Hospital of Wuhan University and Zhongnan Hospital of Wuhan University from May 2021 to September 2022.The collected images were used for model training and testing after being reviewed and classified by corneal experts.The model design included a low-quality image filtering model, a corneal image diagnosis model, and a 4-layer identification model for corneal epithelium, Bowman membrane, stroma, and endothelium, to initially determine normal and abnormal corneal images and corresponding corneal layers.A human-machine competition was conducted with another 360 database-independent IVCM images to compare the accuracy and time spent on image recognition by three senior ophthalmologists and the AI system.In addition, 8 trainees without IVCM training and with less than three years of clinical experience were selected to recognize the same 360 images without and with model assistance to analyze the effectiveness of model assistance.This study adhered to the Declaration of Helsinki.The study protocol was approved by the Ethics Committee of Renmin Hospital of Wuhan University (No.WDRY2021-K148).Results:The accuracy of this diagnostic model in screening high-quality images was 0.954.Its overall accuracy in identifying normal/abnormal corneal images was 0.916 and 0.896 in the internal and external test sets, respectively.Its accuracy reached 0.983, 0.925 in the internal test sets and 0.988, 0.929 in the external test sets in identifying corneal layers of normal and abnormal images, respectively.In the human-machine competition, the overall recognition accuracy of the model was 0.878, which was similar to the average accuracy of the three senior physicians and was approximately 300 times faster than the experts in recognition speed.Trainees assisted by the system achieved an accuracy of 0.816±0.043 in identifying corneal layers of normal and abnormal images, which was significantly higher than 0.669±0.061 without model assistance ( t=6.304, P<0.001). Conclusions:A deep learning-based assistant system for corneal IVCM image recognition is successfully constructed.This system can discriminate normal/abnormal corneal images and diagnose the corresponding corneal layer of the images, which can improve the efficiency of clinical diagnosis and assist doctors in training and learning.

Clinical application of mass spectrometry technology has attracted the attention of clinical laboratory experts due to its high sensitivity, high specificity, and capacities of simultaneous detection of multiple compounds. In recent years, mass spectrometry technology has made significant achievements in the fields of identification of pathogenic microorganism, detection of trace elements and heavy metals, small molecule hormones, vitamins, amino acids, peptides and proteins, as well as therapeutic drug monitoring (TDM) and poisoning drugs screening. In order to further clarify the opportunities and challenges brought by this complex mass spectrometry technology in the field of clinical laboratory, the Chinese Journal of Laboratory Medicine invited experts and scholars of laboratory medicine to share their experience and opinions on related items focusing on the positioning of mass spectrometry technology in the clinical laboratory, the development and improvement of the clinical laboratory by mass spectrometry technology, the challenges of interpreting mass spectrometry test results, the challenges of operating and managing clinical mass spectrometry laboratories, and ways of improving the application of clinical mass spectrometry laboratories with this technology. Agreement was achieved in that the introduction of mass spectrometry technology into the clinical laboratory could bring new directions and opportunities for clinical testing and research, and also is associated with a series of challenges such as the difficulty of sample pretreatment, the high cost and complexity of mass spectrometry technology, the complexity of data processing and interpretation, the lack of standards and norms, and the issue of determining the price of mass spectrometry examinations.

Objective:To investigate the application effect of research-assisted teaching mode in histology teaching by taking the construction of rat spinal cord injury model as an example.Methods:A convenient sampling method was used to select 52 freshmen majoring in clinical medicine of grade 2020 in our school as the research subjects.They were randomly divided into the conventional teaching group and the research-assisted teaching group,with 26 students in each group.The conventional teaching group received traditional classroom teaching combined with experimental teaching.On this basis,research elements were added to the experimental teaching in the research-assisted teaching group to provide more in-depth research methods and experimental design,so as to cultivate students'research abilities.The theoretical assessment and practical skills assessment of histology course were compared between the two groups.A subjective evaluation questionnaire on experimental animal models teaching was used to evaluate the advantages of teaching programs in three dimensions:psychological quality training,technical skill enhancement,and theoretical knowledge expansion.The research abilities of the two groups were compared.Pearson correlation analysis was used to analyze the correlation between research ability scores and comprehensive scores.Results:The usual score and comprehensive score in the research-assisted teaching group were significantly higher than those in the conventional teaching group(P＜0.05).The scores of adaptability to challenging tasks,determination and perseverance in problem-solving,communication skills in teamwork,literature reading,integration of practical experience with theoretical knowledge,practical application value of the course,and innovation of teaching resources in the research-assisted teaching group were higher than those in the conventional teaching group(P＜0.05).The scores in experimental design ability,background knowledge in literature review,communication and reporting skills,awareness of evidence-based medicine,and overall research ability in the research-assisted teaching group were higher than those in the conventional teaching group(P＜0.05).The total score of students'research abilities was positively correlated with comprehensive scores(r=0.716,P＜0.01).Conclusions:The application of research-assisted teaching significantly improved students'research abilities in histology teaching.The enhancement of research abilities can promote the mastery of theoretical knowledge and the improvement of experimental skills.

Background: Serum C-peptide results from various routine methods used in China are highly variable, warranting well-performing methods to serve as an accuracy base to improve the harmonization of C-peptide measurements in China. We developed an accurate isotope dilution liquid chromatography-tandem mass spectrometry (ID-LC–MS/MS) method for serum C-peptide measurement and explored its use in harmonization. Methods: After protein precipitation with ZnSO4 solution, C-peptide was extracted from serum samples by anion-exchange solid-phase extraction and quantified by ID-LC–MS/MS in positive ion mode. The precision and analytical recovery of the ID-LC–MS/MS method were assessed. Seventy-six serum samples were analyzed using the ID-LC–MS/MS method and six routine immunoassays. Ordinary linear regression (OLR) and Bland-Altman (BA) analyses were conducted to evaluate the relationship between the ID-LC–MS/MS method and routine immunoassays. Five serum pool samples assigned using the ID-LC–MS/MS method were used to recalibrate the routine assays. OLR and BA analyses were re-conducted after recalibration. Results: The within-run, between-run, and total precision for the ID-LC–MS/MS method at four concentrations were 1.0%–2.1%, 0.6%–1.2%, and 1.3%–2.2%, respectively. The analytical recoveries for the ID-LC–MS/MS method at three concentrations were 100.3%–100.7%, 100.4%–101.0%, and 99.6%–100.7%. The developed method and the immunoassays were strongly correlated, with all R2 >0.98. The comparability among the immunoassays was substantially improved after recalibration. Conclusions The performance of the ID-LC–MS/MS method was carefully validated, and this method can be used to improve the harmonization of serum C-peptide measurements in China.

Lead poisoning severely threatens human health with its cumulation and durability in the body. The analysis of lead in blood is vital for screening, diagnosis, treatment, and prognostication of lead poisoning and for indirectly monitoring the level of lead in the environment. Although the detection programs are available throughout our country, the accuracy and comparability of the results cannot meet the expectation. A variety of factors can affect the accuracy of blood lead testing. To promote the application of blood lead analysis in clinical trials and reduce the bias of results, a better reference system for blood lead analysis should be established to evaluate the accuracy of traditional methods, promote the standardization of blood lead analysis and achieve accurate blood lead testing.

Objective:To construct a prokaryotic expression vector for human retinol binding protein 4 (hRBP4) that allows technicians to obtain hRBP4 purified protein with low cost, high efficiency, high concentration and high purity.Methods:The hRBP4 coding sequence provided by National Center for Biotechnology Information was optimized by E. coli codons, and a synthetic DNA fragment was cloned into the PET-28A (+) prokaryotic expression vector to construct a recombinant hRBP4 expression plasmid. The recombinant protein was transformed into E. coli BL21, and the induced expression conditions (temperature, rotate speed and isopropyl β-d-thiogalactoside concentration) were optimized. The recombinant protein was purified by His fusion tag. Results:The recombinant hRBP4 prokaryotic expression plasmid was successfully constructed, and the expression concentration and induction temperature of the recombinant protein were optimized. The results of sodium dodecyl sulfate polyacrylamide gel electrophoresis showed that a band with a relative molecular weight of 26 000 daltons was clearly visible in the purified product. The purified hRBP4 protein could be detected clinically, and there was a good linear relationship between the dilution ratio and the detection concentration.Conclusions:The recombinant hRBP4 protein has high purity, high concentration, and short production cycle. It has the potential to become a candidate for reference materials for laboratory quality evaluations.

Venous thromboembolism is one of the serious and common complications of gynecological malignant tumors, and it is also the main cause of death of patients besides the tumor itself. Nursing staff plays an important role in the prevention of venous thrombosis. Step-by-step systematic nursing intervention can effectively reduce the occurrence of venous thrombosis. This article reviews the research progress of prevention and nursing of perioperative venous thromboembolism in patients with gynecological malignant tumors, aiming to provide help for the establishment and effective implementation of preventive nursing strategies for venous thromboembolism in patients with gynecological malignant tumors.

Objective:To establish O-(2-[ 18F]fluoroethyl)- L-tyrosine( 18F-FET) PET radiomics features-based model and investigate its predictive efficacy for isocitrate dehydrogenase type 1 (IDH1) genotyping in untreated gliomas. Methods:From November 2017 to February 2019, 58 pathologically confirmed glioma patients (36 males, 22 females; age (41.8±15.1) years) with preoperative 18F-FET PET/CT imaging in Huashan Hospital, Fudan University were retrospectively enrolled. PyRadiomics software package was used to extract 105 radiomics features. Least absolute shrinkage and selection operator (LASSO) algorithm with 5-fold cross-validation was used to build the logistic regression model. And radiomic scores (RS) of each lesion were calculated according to their weighted coefficients. The area under the receiver operating characteristic (ROC) curve was used for evaluating the predictive efficacy for IDH1 prediction. The predictive efficacies of radiomics model and traditional semi-quantitative parameters including tumor-to-background ratio (TBR; maximum TBR (TBR max), mean TBR (TBR mean), peak TBR (TBR peak)), metabolic tumor volume (MTV) and total lesion tracer uptake (TLU), were compared by Delong test. Results:Seven radiomics features including maximum 2-dimensional (2D) diameter slice, first order_maximum, first order_range, gray level co-occurrence matrix (GLCM)_joint energy, GLCM_inverse variance, gray level dependence matrix (GLDM)_dependence entropy and GLDM_large dependence low gray level emphasis were selected for the LASSO regression model building and RS calculation. ROC analysis results showed that the predictive accuracy of RS for IDH1 genotyping (mutation, n=20; wild-type, n=38) was 81.0%(47/58), with sensitivity of 65.0%(13/20), specificity of 89.5%(34/38), and area under curve (AUC) of 0.842, respectively. The traditional 18F-FET semi-quantitative parameter TLU ranked the second regarding the diagnostic performance, with accuracy of 60.3%(35/58), sensitivity of 85.0%(17/20), specificity of 47.4%(18/38), and AUC of 0.661( z=3.426, P<0.01). Conclusion:Radiomics analysis based on 18F-FET PET images can improve the predictive efficacy for IDH1 genotyping in untreated adult glioma patients.