The Proctor's reporting guideline for implementation strategies represents a landmark framework in the field of implementation science, aiming to address the issue of inconsistent reporting in implementation research by standardizing the naming, definition, and operationalization of implementation strategies, thereby enhancing the credibility and utility of research findings. This paper provides an in-depth interpretation of the core connotations of this reporting guideline and illustrates its application in developing interview outlines and specifying implementation strategies, using a brief smoking cessation intervention project as a case study. Through this reporting guideline, abstract recommendations for implementation are systematically transformed into clear, multidimensional operational guides, significantly improving the transparency of strategy connotations and the replicability of actual execution. Meanwhile, the case study highlights the flexibility of the guideline, which allows researchers to adapt the content and format of strategies based on local resources and cultural contexts, thus enhancing practical adaptability while maintaining scientific rigor. However, the application of Proctor's reporting guideline still faces challenges, primarily manifested in the potential confusion surrounding the constructs of temporality and dose in practice, as well as the challenges that the inherent flexibility of the guideline may pose to the assessment of fidelity and effectiveness. Despite these limitations, the reporting guideline remains a vital tool for implementation research; future efforts should focus on optimizing its application—through refining operational guidelines, standardizing flexible adaptations, and involving stakeholders—to better guide implementation studies and continuously promote high-quality development in the field.

Objective: To review the current development of artificial intelligence (AI) technology in the field of transfusion medicine. Methods: A systematic search was conducted in the Clarivate Web of Science Database from inception to December 2024 for literature related to AI and transfusion. A total of 4 775 publications were identified. Based on inclusion and exclusion criteria, 133 original studies were ultimately included and analyzed using a narrative synthesis approach. Results: Research on AI in transfusion has surged since 2020 (accounting for 77% of all publications), with China ranking second globally in publication volume. Among the included studies, 69.2% focused on predicting individual transfusion needs, followed by inventory management (8.3%), diagnosis and prediction of adverse transfusion reactions (6.0%), factors influencing transfusion outcomes (5.3%), blood group identification (5.3%), blood quality testing (4.5%), and precise blood volume measurement (1.5%). Additionally, 4.5% of the studies were published in journals with an impact factor greater than 10; 19.5% developed software or applications; 31.5% were multi-center studies; 48.1% utilized decision tree methods, while 31.5% employed neural network approaches; and 14.2% conducted external validation of the algorithms. Conclusion: AI demonstrates significant potential in transfusion risk prediction, decision support, and blood management. However, challenges remain, including limited model generalizability, insufficient algorithm interpretability, and barriers to clinical translation. The deep integration of AI with transfusion medicine will accelerate the advent of precision transfusion era, maximizing blood resource utilization, reducing waste, and ensuring transfusion safety.

Objective To investigate the prognostic value of optic nerve sheath diameter(ONSD)measured by critical care ultrasound combined with serum biomarkers[S100 calcium-binding protein β(S100β)and neuron-specific enolase(NSE)]in patients with severe traumatic brain injury.Methods A total of 103 adult severe traumatic brain injury patients admitted to the intensive care unit of this hospital from A-pril 1,2023,to April 1,2024 were enrolled.All patients underwent invasive intracranial pressure monitoring after admission,alongside bedside critical care ultrasound measurement of ONSD at 3 mm behind the globe and serum biomarker testing.Baseline data and Glasgow outcome scale(GOS)scores at 90 days after dis-charge were recorded.Patients were divided into the survival and the non-survival groups based on GOS scores.Receiver operating characteristic(ROC)curve analysis and area under the curve(AUC)were used to evaluate the predictive performance of ONSD and serum biomarkers for poor prognosis in severe traumatic brain injury patients.Results Ninety-six patients were ultimately included,with 52(54.1％)in the survival group and 44(45.9％)in the non-survival group.Significant differences were observed in blood glucose,Glas-gow coma scale(GCS)score,acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score,ONSD,NSE,and S100β levels(P＜0.05)between the two groups.Multivariate analysis identified ONSD(OR=4.962,95％CI:3.473-6.254),NSE(OR=2.704,95％CI:1.987-3.033),S100β(OR=2.983,95％CI:1.843-4.571),and APACHE Ⅱ score(OR=3.726,95％CI:2.837-4.592)as independent predictors of mortality in severe traumatic brain injury patients(P＜0.05).The combination of ONSD,NSE,and S100β yielded an AUC of 0.840 for predicting poor prognosis,with a specificity of 88.3％and sensitivity of 98.6％.Conclusion ONSD and serum brain injury biomarkers(NSE,S100β)are associated with in-hospital prognosis in severe traumatic brain injury patients.Their combined detection can effectively predict a poor outcome.

Objective:To establish HPLC fingerprint and methods for determining the contents of four iridoid glycosides of Gentiana rigescens; To evaluate the quality of Gentiana rigescens from different origins; To improve the quality control level of Gentiana rigescens medicinal materials.Methods:Using 15 batches of Gentiana rigescens from the main production areas and authentic production areas as raw materials, the common mode of HPLC fingerprints of Gentiana rigescens was established, and the chemical components of the common peaks were identified. Referring to the common mode of fingerprints, similarity analysis was conducted on the fingerprints of Gentiana rigescens from different origins. Using chemometric methods, cluster analysis (HCA), principal component analysis (HCA), and orthogonal partial least squares discriminant analysis (OPLS-DA) were performed on 15 batches of Gentiana rigescens, with the common peak area of fingerprint as the variable. The contents of four types of iridoid glycosides in Gentiana rigescens were determined. Combined with the fingerprints and the content results of four types of iridoid glycosides, the quality of Gentiana rigescens from different origins was evaluated.Results:The fingerprints of Gentiana rigescens contained 9 common peaks, with 4 identified iridoid glycosides. The similarity of the fingerprints of 15 batches of Gentiana rigescens ranged from 0.962 to 0.999. HCA and PCA divided the 15 batches of Gentiana rigescens into two categories. OPLS-DA analyzed 3 significantly different components, namely gentiopicroside, peak 7, and loganic acid. The content determination results showed that the average contents of loganic acid, swertiamarin, and gentiopicroside in Gentiana rigescens from Dali Bai Autonomous Prefecture and Yunnan Province were the highest, and the total amount of four iridoid glycosides was also significantly higher than that from other regions, indicating that the overall quality of Gentiana rigescens from Dali Bai Autonomous Prefecture and Yunnan Province was relatively good.Conclusion:This method is simple, fast, accurate, and can provide reference for improving the quality standards of Gentiana rigescens.

Objective:To establish a mass spectrometry method for the determination of characteristic peptides of Galli Gigerii Endothelium Corneum that can identify the authenticity of Galli Gigerii Endothelium Corneum as well as its preparations; To evaluate their quality.Methods:Ultra performance chromatography-electrospray tandem mass spectrometry (UPLC-MS/MS) with the mode of multiple reaction monitoring quantification (MRM) was employed to monitor the ion pairs of m/z 379.21(charge: +2)→571.36, m/z 379.21(charge: +2)→385.26, m/z 785.41(charge: +2)→941.51 and m/z 785.41(charge: +2)→245.08, in order to detect the Galli Gigerii Endothelium Corneum crude drug and its preparations. Results:Chicken specific peptide I and chicken specific peptide Ⅱ could be detected in the 18 batches of Galli Gigerii Endothelium Corneum from different regions, their corresponding extractions and 4 batches of prescription preparations, while the chicken specific peptides were not detected in the 8 batches of endothelium corneums from ducks, geese and pigeons.Conclusions:The method established in this study can effectively supplement the deficiencies in standards of Galli Gigerii Endothelium Corneum and its decoction pieces, improve the quality control standard, and provide a reference for the safety and effectiveness of Galli Gigerii Endothelium Corneum in clinical medication.

Objective:To identify the components of Prunus mume f. viridicalyx based on ultra performance liquid chromatography-QE-Orbitrap mass spectrometry (UPLC-QE-Orbitrap-MS); To predict and analyze its substances and mechanisms to exert anti-depression effects combined with network pharmacology.Methods:UPLC-QE Orbitrap MS technology was used to analyze the chemical components of Prunus mume f. viridicalyx. Based on ChemSpider, mzCloud online platform, orbitrap TCM library and existing literature research, the secondary mass spectra of target compounds were compared and confirmed to identify the chemical composition of Prunus mume f. viridicalyx. The active components of the Prunus mume f. viridicalyx were screened. The Swiss Target Prediction database was used to predict targets with high correlation to active components in Prunus mume f. viridicalyx, and obtaining depression related disease targets from GeneCards and DisGeNET databases. The intersection targets of constituents and diseases were obtained using Venny platform. Protein-protein interaction network (PPI) was constructed by using String database, and the core targets were screened. Gene ontology function and Kyoto encyclopedia of genes and genomes pathway enrichment analysis of potential core targets were performed by using David database, and "active component-core target-signal pathway" network was constructed. PyMOL software was used to perform molecular docking between active components and key targets.Results:A total of 54 components, including organic acids, flavonoids and their glycosides, alkaloid, amino acids and other compounds were identified from Prunus mume f. viridicalyx. A total of 22 active components were screened and 92 active components and disease intersection targets were identified. A total of 13 core targets were screened through PPI network, including tumor necrosis factor, albumin, amyloid beta-protein precursor, AKT serine/threonine kinase 1 and so on. Enrichment analysis showed that Prunus mume f. viridicalyx mainly participated in transcription from RNA polymerase Ⅱ promoter, gene expression, protein binding and other functions, and presented the effects of anti-depression through MAPK, Toll-like receptor signaling pathway and other pathways. 12 key targets and 7 key active components were further obtained through the analysis of the "active component-core target-signal pathway" network, three of them were confirmed as kaempferol, quercetin, and isorhamnetin by reference substance. Molecular docking showed that 3 compounds could bind to the target proteins of depression well.Conclusion:Prunus mume f. viridicalyx exerts antidepressant effects through multiple components, targets, and pathways, mainly through the MAPK signaling pathway.

Objective:To establish fingerprints of Faeces Bombycis and simultaneously determine the content of four amino acids; To evaluate the quality of Faeces Bombycis from different regions. The fingerprint of Faeces Bombycis was established and the contents of 4 amino acids were determined.Methods:Kromasil 100-5 C18 (4.6 mm×250 mm, 5 μm) column was used for phenyl isothiocyanate (PITC) pre-column derivation-high performance liquid chromatography with acetonitrile-0.1 mol/L sodium acetate solution (pH adjusted to 6.5 with acetic acid) (7:93) mixed solution, and acetonitrile-water (4:1) mixed solution were mobile phase for gradient elution. The flow rate was 1.0 ml/min; the column temperature was 35 ℃; the detection wavelength was 254 nm; the injection amount was 5 μl. The fingerprints of 17 batches of Faeces Bombycis were established, the common peaks were identified by comparison of reference materials, and the similarity evaluation and principal component analysis (PCA) were carried out. The contents of glycine, alanine, proline and phenylalanine were determined simultaneously.Results:A total of 12 common peaks were identified from the fingerprints of Faeces Bombycis, and 12 amino acids were identified. The similarity of 17 batches of samples was greater than 0.95. PCA analysis showed that the regional difference of the quality of Faeces Bombycis was not significant. Faeces Bombycis produced in Qujing city in Yunnan Province had the highest total contents of 4 amino acids.Conclusion:The method has good repeatability and can provide reference for the quality evaluation and standard improvement of Faeces Bombycis.

Objective:To establish the UPLC fingerprint evaluation system of Viticis Fructus; To comprehensively evaluate the quality of Viticis Fructus and its processed products combining with multivariate statistical methods and compositional variance analysis.Methods:19 batches of Viticis Fructus from different regions were collected and processed by frying process into decoction pieces. The separation was operated on Waters CORTECS T3 C18 chromatographic column (100 mm × 2.1 mm, 1.6 μm). Acetonitrile and 0.1% phosphoric acid water were used as mobile phases for gradient elution, to establish the UPLC fingerprints of Viticis Fructus. The UPLC fingerprints of Viticis Fructus were analyzed using similarity evaluation, principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA). The contents of seven active components in the samples of Viticis Fructus and fried Viticis Fructus were determined.Results:A total of 26 common peaks were identified in the fingerprints of 38 batches of samples, and 7 components were identified. Similarity evaluation results demonstrated that the chemical components of Viticis Fructus from Jingdezhen City, Jiangxi Province, were significantly different from those of other regions. The results of PCA and PLS-DA analysis showed that the chemical components of Viticis Fructus and fried Viticis Fructus could be clearly distinguished, and the processing process had an impact on the components. The results of content determination showed that the contents of some components increased or decreased after frying. The analysis results of grey correlation method and TOPSIS method show that the medicinal materials in Jiujiang City, Jiangxi Province have a high score ranking and stable quality.Conclusion:This study successfully establishes the fingerprints of Viticis Fructus and its processed products, grey correlation method and TOPSIS method analysis revealed the quality differences of samples from different origins, which providing a scientific basis for the quality control and evaluation of Viticis Fructus and its processed products.

Objective:To determine the contents of four flavonoids by establishing HPLC specific chromatogram for Alpiniae Katsumadai Semen; To evaluate the differences of Alpiniae Katsumadai Semen from different producing areas.Methods:The specific chromatogram was developed on a column of Thermo Acclaim C18 with acetonitrile-0.1% phosphoric acid solution as the mobile phase by gradient elution at a flow rate of 1.0 ml/min. The detective wavelength was 260 nm, and the column temperature was 30 ℃. Similarity evaluation, PCA analysis, and OPLS-DA analysis were conducted. The contents of Alpinetin, Pinocembrin, Cardamonin, Alnustone in 16 batches of Alpiniae Katsumadai Semen.Results:There were 9 characteristic peaks in the specific chromatogram of Alpiniae Katsumadai Semen. Except the sample of S2 (Hainan producing area), the similarity of Alpiniae Katsumadai Semen in different producing areas was greater than 0.90; PCA analysis divided 16 batches of Alpiniae Katsumadai Semen into 2 categories, and OPLS-DA analysis identified 4 differential biomarkers, with the order of impact being peak 3>peak 5>Alpinetin>Cardamonin. Among them, the quality of Alpiniae Katsumadai Semen from Guangdong producing area was generally stable. Moreover, there were significant differences in the contents of Alpinetin and Cardamonin among the indicator components of Alpiniae Katsumadai Semen from different producing areas.Conclusion:This method can effectively analyze the differences in the quality of Alpiniae Katsumadai Semen from different producing areas, providing reference for the quality evaluation of Alpiniae Katsumadai Semen.

Objective:To establish a quality control method for Aiye standard decoction.Methods:The ultra performance liquid chromatogrphy (UPLC) column Waters ACQUITY HSS T3 C18 (2.1 mm×150 mm,1.8 μm) was used to gradient elution by acetonitrile and 0.1% formic acid in water. 16 batches of Aiye standard decoction fingerprints were established by UPLC and the common peaks were determined in the fingerprints. The contents of 12 components were determined. The 16 batches of Aiye standard decoction were analyzed by similarity calculation, hierarchical cluster analysis (HCA), principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) for analysis of differential components of Artemisiae Argyi Folium from different origins.Results:A total of 13 common peaks were marked in the fingerprints of 16 batches of Aiye standard decoction, 12 of which were identified by comparison with reference substance, including chlorogenic acid, sochlorogenic acid A, neochlorogenic acid, cryptochlorogenic acid, caffeic acid,1,3-O-Dicaffeoylquinic acid, schaftoside, isochlorogenic acid B,1,5-O-Dicaffeoylquinic acid, isochlorogenic acid C, jaceosidin and eupatilin. Similarity evaluation, PCA and HCA all classified the 16 batches of Aiye standard decoction into 2 categories. Orthogonal partial least squares discriminant analysis screened 5 differential biomarkers from 13 common peaks. The content determination results showed that the phenolic compounds and flavonoids in samples from Hubei were significantly higher than that in samples from other areas.Conclusion:This method can effectively analyze the differences in the quality of Aiye standard decoction from different origins, and provide reference for the formulation of quality standards for Aiye standard decoction and related preparations.