Real-world study (RWS), based on multi-source data from real medical environments, is gradually becoming an important supplement to traditional randomized controlled trials, and its application in the field of transfusion medicine is becoming increasingly widespread. This article systematically reviews the definition and methodological system of RWS, examines its application cases in clinical blood transfusion research, and discusses the advantages, limitations, and future research directions of RWS, aiming to provide a reference for evidence-based research in blood transfusion medicine.

Real-world study (RWS), based on multi-source data from real medical environments, is gradually becoming an important supplement to traditional randomized controlled trials, and its application in the field of transfusion medicine is becoming increasingly widespread. This article systematically reviews the definition and methodological system of RWS, examines its application cases in clinical blood transfusion research, and discusses the advantages, limitations, and future research directions of RWS, aiming to provide a reference for evidence-based research in blood transfusion medicine.

Objective: Through analyzing the current handling capabilities for complex cases in blood transfusion compatibility detection and the application status of artificial intelligence-assisted (AI-assisted) technologies, this study explores the establishment of an effective AI-augmented protocol for managing challenging blood transfusion compatibility detection. Methods: This research systematically analyzes, designs, and explores an AI-augmented operational workflow for resolving challenging blood transfusion compatibility detection cases. Through three representative case studies, we evaluate its effectiveness, accuracy, and efficiency in addressing real-world diagnostic challenges. Results: The AI-augmented operational model demonstrates significant efficacy in resolving complex blood transfusion compatibility challenges, including complex blood typing, antibody specificity identification, challenging cross-matching, and transfusion strategy formulation. Conclusion: AI-augmented technologies demonstrate immense potential in resolving complex blood transfusion compatibility detections. By enabling intelligent, automated, precise, and standardized solutions, they significantly enhance diagnostic accuracy and operational efficiency, which is critical for ensuring transfusion safety and advancing personalized transfusion medicine. This study delineates both the advantages and existing limitations of AI implementation, explores future developmental trajectories, and provides a theoretical framework and practical implementation pathways for deeper integration of AI in transfusion medicine.

Objective:To examine the validity and reliability of the Chinese version of the Body Acceptance by Others Scale-2(BAOS-2)in adults.Methods:Totally 616 adults(aged 18-56 years)were selected to test the structural validity,and internal consistency reliability of the scale.The Body Appreciation Scale-2(BAS-2),Func-tionality Appreciation Scale(FAS),Self-Compassion Scale(SCS),Self-Esteem Scale(SES)and Satisfaction with Life Scale(SWLS)were used as criteria to test criterion validity.A sample of 55 adults was retested 2 weeks later for the test-retest reliability.Results:The exploratory factor analysis extracted one factor,and the factor loading range of each item was 0.59-0.76.The confirmatory factor analysis showed that the factor model fit indices were acceptable(x2/df=2.99,CFI=0.91,GFI=0.90,TLI=0.89,RMR=0.04,RMSEA=0.08).The scores of the Chinese version of BAOS-2 were positively correlated with the scores of BAS-2,FAS,SCS,SES and SWLS(r=0.43-0.66,Ps＜0.001).The Cronbach a of the Chinese version of BAOS-2 was 0.90,and the test-retest reliabili-ty(ICC)was 0.65.Conclusion:The Chinese version of the Body Acceptance by Others Scale-2(BAOS-2)has i-deal validity and reliability.

Background/Aims: Metabolic syndrome is common in patients with acute pancreatitis and its components have been reported to be associated with infectious complications. In this post hoc analysis, we aimed to evaluate whether metabolic abnormalities impact the effect of immuneenhancing thymosin alpha-1 (Tα1) therapy in acute necrotizing pancreatitis (ANP) patients. Methods: All data were obtained from the database for a multicenter randomized clinical trial that evaluated the efficacy of Tα1 in ANP patients. Patients who discontinued the Tα1 treatment prematurely were excluded. The primary outcome was 90-day infected pancreatic necrosis (IPN) after randomization. Three post hoc subgroups were defined based on the presence of hyperglycemia, hypertriglyceridemia, or both at the time of randomization. In each subgroup, the correlation between Tα1 and 90-day IPN was assessed using the Cox proportional-hazards regression model. Multivariable propensity-score methods were used to control potential bias. Results: Overall, 502 participants were included in this post hoc analysis (248 received Tα1 treatment and 254 received matching placebo treatment). Among them, 271 (54.0%) had hyperglycemia, 371 (73.9%) had hypertriglyceridemia and 229 (45.6%) had both. Tα1 therapy was associated with reduced incidence of IPN among patients with hyperglycemia (18.8% vs 29.7%: hazard ratio, 0.80; 95% confidence interval, 0.37 to 0.97; p=0.03), but not in the other subgroups. Additional multivariate regression models using three propensity-score methods yielded similar results. Conclusions Among ANP patients with hyperglycemia, immune-enhancing Tα1 treatment was associated with a reduced risk of IPN (ClinicalTrials.gov, Registry number: NCT02473406).

Essential oils (EOs) are natural, volatile substances derived from aromatic plants. They exhibit multiple pharmacological effects, including antibacterial, anticancer, anti-inflammatory, and antioxidant properties, with broad application prospects in health care, food, and agriculture. However, the instability of volatile components, which are susceptible to deterioration under light, heat, and oxygen exposure, as well as limited water solubility, have significantly impeded the development and application of EOs. Porous nanoclays are natural clay minerals with a layered structure. They possess unique structural characteristics such as large pore size, regular distribution, and tunable particle size, which are extensively utilized in drug delivery, adsorption separation, reaction catalysis, and other fields. Natural-derived porous nanoclays have garnered considerable attention for the encapsulation and delivery of EOs. This review comprehensively summarizes the structure, types, and properties of natural-derived porous nanoclays, focusing on the structural characteristics of porous nanoclays such as montmorillonite, palygorskite, halloysite, kaolinite, vermiculite, and natural zeolite. It also examines research advances in their delivery of EOs and explores engineering strategies to enhance the delivery of EOs by natural-derived porous nanoclays. Finally, various applications of natural-derived porous nanoclays for EOs in antibacterial, food preservation, repellent, and insecticide aspects are presented, providing a reference for the development and application of EOs.
Humans ; Nanoparticles/chemistry* ; Oils, Volatile/administration & dosage* ; Porosity ; Nanoparticle Drug Delivery System/chemistry*

Phage-microbe interactions are appealing systems to study coevolution,and have also been increasingly emphasized due to their roles in human health,disease,and the development of novel therapeutics.Phage-microbe interactions leave diverse signals in bacterial and phage geno-mic sequences,defined as phage-host interaction signals(PHISs),which include clustered regularly interspaced short palindromic repeats(CRISPR)targeting,prophage,and protein-protein interac-tion signals.In the present study,we developed a novel tool phage-host interaction signal detector(PHISDetector)to predict phage-host interactions by detecting and integrating diverse in silico PHISs,and scoring the probability of phage-host interactions using machine learning models based on PHIS features.We evaluated the performance of PHISDetector on multiple benchmark datasets and application cases.When tested on a dataset of 758 annotated phage-host pairs,PHISDetector yields the prediction accuracies of 0.51 and 0.73 at the species and genus levels,respectively,outper-forming other phage-host prediction tools.When applied to 125,842 metagenomic viral contigs(mVCs)derived from 3042 geographically diverse samples,a detection rate of 54.54％could be achieved.Furthermore,PHISDetector could predict infecting phages for 85.6％of 368 multidrug-resistant(MDR)bacteria and 30％of 454 human gut bacteria obtained from the National Institutes of Health(NIH)Human Microbiome Project(HMP).

Objective:To evaluate the effect of invasive arterial blood pressure (IBP) monitoring on the prognosis of patients with sepsis.Methods:Patients with sepsis from the MIMIC-Ⅳ database were collected and divided into IBP and non-invasive blood pressure monitoring (NIBP) groups according to whether IBP monitoring was performed. Baseline variables that were considered clinically relevant or showed a univariate relationship with the outcome were entered into a multivariate logistic regression model as covariates.Propensity score matching(PSM) and inverse probability of treatment weighing(IPTW) were used to adjust confounders to ensure the robustness of findings.Subgroup analysis were conducted to evaluate the effect of differences in IBP onset and duration on outcome.Results:The 28-day mortality is lower in IBP group compared with NIBP group( OR=0.54, 95% CI 0.46-0.62, P<0.001), the conclusion maintain robust after PSM and IPTW.Then we conducted a series of logistic regression regarding to different initial IBP time(<24 h,24 h-48 h,>48 h) and the initial IBP time within 24 h showed the same results compared to primary outcoms( OR=0.42, 95% CI: 0.36-0.49, P<0.001). IBP duration varied (≤1day, ≤2days, ≤3days, ≤4days, >4days) all showed a statistically significant association with decreased 28-day mortality in the IBP group. Conclusions:IBP is associated with decreased 28-day mortality in patients with sepsis, and the optimal time of IBP is within 24 hours.

Objective:To study the diagnostic value of the artificial intelligence (AI) diagnostic system, ACR TI-RADS classification and AI+ ACR TI-RADS combined diagnostic performance in benign and malignant thyroid nodules and its guiding significance for surgical treatment.Methods:From Nov. 1, 2021, to Feb. 26, 2022, 349 patients with 605 thyroid nodules who received surgical treatment in Department of Thyroid (Hernia) Surgery, Department of General Surgery, the First Medical Center of the PLA General Hospital, were selected. There were 95 males and 254 females, male: female=1:2.67, aged 16-78 years, and the nodule diameter was 0.2-5.6 cm. SPSS 26.0 and R studio software were used for data processing. AI diagnostic system, ACR TI-RADS grading and AI+ ACR TI-RADS combined diagnostic efficacy were statistically analyzed, respectively. ROC curve analysis was performed in parallel.Results:The AUC value of AI+ ACR TI-RADS combined diagnosis was 0.900, greater than 0.857 of AI diagnostic system and 0.788 of ACR TI-RADS, and the difference was statistically significant ( Z= 7.631, both P<0.001) . The sensitivity of the combined diagnosis was 95.32%, the specificity was 84.61%, the accuracy was 92.56%, the positive predictive value was 94.69%, the negative predictive value was 86.27%, the missed diagnosis rate was 4.68%, and the misdiagnosis rate was 15.38%, which were better than the other two diagnostic methods. With an excellent coincidence rate with postoperative pathological results ( Kappa=0.804, P<0.001) . The accuracy of combined diagnosis in identifying the maximum diameter of different tumors was 89.58% for d≤0.5 cm, 96.09% for 0.54.0 cm, better than the other two diagnostic methods. Conclusions:The combined application of AI+ACR TI-RADS has a certain primary screening value in evaluating thyroid nodule properties. The combined diagnosis of the two can more effectively determine the benign and malignant thyroid nodules.

Objective:To investigate the urine output threshold of acute kidney injury in patients with acute pancreatitis(AP) and to guide early fluid therapy.Methods:The clinical data of AP patients from Medical Information Mart for Intensive Care Ⅳ (MIMIC-Ⅳ) were collected. The 24-h urine output rate [24-h urine output·kg-1·24-h-1, 24-UR mL/ (kg·h) ] and 48-h urine output rate [48-h urine output·kg-1·48-h-1, 48-UR mL/ (kg·h) ] were calculated, and according to the occurrence of acute kidney injury within 7 days (7-AKI), AP patients were divided into the 7-AKI group and non-7-AKI group. The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of 24-UR and 48-UR on 7-AKI in AP patients. 24-UR and 48-UR were grouped according to the optimal cut-off value obtained from the ROC curve. Logistic regression was used to analyze the risk factors of 7-AKI, and Kaplan-Meier (KM) survival curve was drawn to analyze the effect of 24-UR and 48-UR on in-hospital mortality of AP patients.Results:A total of 713 AP patients were included, ROC curve analysis showed that the area under the ROC curve (AUC) of 24-UR in predicting 7-AKI in AP patients was 0.76. Based on the maximum Youden index, the cut-off value of 24-UR was 0.795 mL/ (kg·h) , and the AUC of 48-UR was 0.78 and the cut-off value of 48-UR was 0.975 mL/ (kg·h) . Logistic regression analysis showed that 24-UR≤0.795 mL/ (kg·h) was an independent risk factor for 7-AKI compared with 24-UR>0.795 mL/ (kg·h) ( OR: 4.22, 95% CI:1.50-11.85, P=0.006). Similarly, compared with 48-UR>0.975 mL/ (kg·h) , 48-UR0.975 mL/ (kg·h) was an independent risk factor for 7-AKI ( OR: 3.75, 95% CI: 1.45-9.72, P=0.007). The KM survival curve showed that the cumulative in-hospital survival rate in the high 24-UR group was higher than that in the low 24-UR group. Conclusions:24-UR can be used to guide early fluid therapy in AP patients.