Yttrium-90 microsphere selective internal radiation therapy (SIRT), also known as transarterial radioembolization, has become one of the pivotal treatments for liver cancer, particularly for selected advantageous patient groups. This review summarizes the characteristics of different patients with liver cancer that could obtain maximum benefit from SIRT and discusses key factors affecting efficacy and safety, including tumor characteristics, liver function, patient performance status, and treatment intent. In evaluating appropriate candidates, mapping serves as a crucial simulation procedure to assess tumor vascular anatomy, predict lung shunting, and guide catheter positioning and dose planning. This procedure substantially enhances therapeutic precision while minimizing the risk of nontarget radiation-related adverse events, such as radiation-induced pneumonitis and gastrointestinal toxicity. Several studies have suggested that SIRT is not only suitable for patients with early or limited hepatocellular carcinoma but can also be used as a bridging therapy for liver transplantation and conversion therapy for unresectable liver cancers. In combination with systemic treatments, SIRT has demonstrated survival benefits in patients with unresectable liver cancer. This review also highlights the importance of further optimizing patient screening through personalized dosimetry and mapping to ensure the precision and safety of treatment. A thorough review of relevant literature and clinical practice offers clinicians comprehensive suggestions on patient screening and clarifies the promise of SIRT in the liver cancer population.

Objective Based on the SWOT analysis method,the temporary medical order dispensing service model of pharmacy intravenous admixture service(PIVAS)of M Hospital was constructed and its implementation effect was evaluated,so as to provide reference for other medical institutions to carry out PIVAS temporary dispensing services.Methods SWOT analysis was used to analyze the advantages,disadvantages,opportunities and threats of PIVAS in M Hospital,and targeted operation strategies and practices were proposed.The safety of intravenous medication,the level of pharmacy service and the cost-effectiveness of the department were used to evaluate the implementation effect of PIVAS temporary medical order dispensing service.Results After the operation strategy of PIVAS temporary medical order dispensing service was constructed and implemented based on SWOT analysis,the time of a single medical order for PIVAS labeling in M Hospital was significantly decreased from(7.19±0.06)s/bag to(6.06±0.09)s/bag(P＜0.05);and the number of errors was significantly reduced from(32.50±2.54)pieces/quarter to(19.75±0.59)pieces/quarter(P＜0.05);The qualified rate of temporary prescription increased from(60.52±1.17)％to(90.63±1.72)％(P＜0.05);The qualified rate of finished infusion delivery time increased from(80.63±1.66)％to(90.80±2.98)％(P＜0.05);The satisfaction rate of PIVAS service in the ward increased from 50％to 90％(P＜0.05);the cost of blending decreased from(3.50±0.05)yuan/bag to(3.00±0.12)yuan/bag(P＜0.05).Conclusion The operation strategy of PIVAS temporary medical order dispensing service of M Hospital based on SWOT analysis gives full play to its own advantages,provides more comprehensive and high-quality services for clinicians and patients,ensures the safety and timeliness of patients' medication,and improves the economic efficiency of the department,which is worthy of reference and promotion.

Objective To explore the factors influencing blood drug concentrations of first-line anti-tuberculosis drugs in fixed-dose combinations by analyzing therapeutic drug monitoring data from tuberculosis patients receiving these regimens.Methods This retrospective study enrolled 224 patients who received treatment at Guangzhou Chest Hospital between January 2020 and December 2024.All participants underwent standardized therapy during the intensive phase,with therapeutic drug monitoring of first-line anti-tuberculosis drugs(ANTDs),including isoniazid(INH)and rifampicin(RFP).Data collection was completed in January 2025,at which time clinical records and measured INH and RFP plasma concentrations were updated.Data analysis was conducted from January to February 2025.Eight baseline variables—gender,age,hypoproteinemia(serum albumin<35 g/L),glomerular filtration rate(GFR),and others—were collected.Univariate chi-square tests and multivariate logistic regression analyses were performed to identify independent risk factors associated with subtherapeutic INH and RFP plasma concentrations.Results Among the study participants,71.43%(160/224)exhibited blood drug concentrations below the reference range for INH,compared to 41.07%(92/224)for RFP.The mean blood concentrations(mg/L,±SD)were 2.532±1.371 for INH and 9.428±4.317 for RFP,respectively.One-way analysis indicated significant associations between male gender,positive etiological test results,and subtherapeutic RFP concentrations(P<0.05),suggesting statistically significant differences.Multivariate regression analysis further revealed that male gender(OR=1.992,95%CI:1.094～3.628)and positive etiological tests(OR=1.929,95%CI:1.058～3.517)were independent risk factors for low RFP levels.Conclusions This study demonstrates that therapeutic drug monitoring(TDM)frequently identifies subtherapeutic RFP concentrations in tuberculosis patients undergoing treatment.Multivariate analysis reveals that male sex and positive pathogen test results are independent risk factors associated with low RFP plasma levels.Consequently,clinicians should exercise heightened vigilance in patients exhibiting these characteristics,promptly implementing TDM to guide individualized dose adjustments.Such an approach is crucial for optimizing treatment efficacy and minimizing the risk of drug resistance development.

Objective·To develop an early diagnostic model for small cell lung cancer(SCLC)based on differences in serum metabolite expression profiles between patients with SCLC and those with benign pulmonary diseases,using machine learning algorithms.Methods·Serum samples were collected from 29 SCLC patients and 67 patients with benign lung diseases at Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine,as the training cohort.An independent external validation cohort included 20 SCLC patients and 40 patients with benign lung diseases from Gansu Provincial Cancer Hospital.A total of 69 serum metabolites were quantitatively analyzed using liquid chromatography-tandem mass spectrometry(LC-MS/MS).The XGBoost Classifier was employed to rank metabolite importance,and a forward feature selection strategy based on XGBoost was used to identify a subset of key metabolites.Diagnostic models were constructed using AdaBoost,random forest(RF),and light gradient boosting machine(LGBM)algorithms.Model performance was assessed using receiver operating characteristic(ROC)curves and the area under the curve(AUC),and validated on the external test cohort.Results·Principal component analysis(PCA)and orthogonal projections to latent structures-discriminant analysis(OPLS-DA)of the training cohort revealed distinct metabolic profiles between SCLC and benign lung disease patients.Based on feature importance rankings,six key metabolites were selected to construct the MTB-6 diagnostic model.Among the models,AdaBoost achieved the best performance,with an AUC of 0.943,sensitivity of 75.0%,and specificity of 90.9%in the training cohort.In the external test cohort,the model demonstrated robust performance with an AUC of 0.921,sensitivity of 80.0%,and specificity of 87.5%.Conclusion·The MTB-6 model,based on six serum metabolites and the AdaBoost algorithm,exhibits excellent diagnostic performance and holds potential for the differential diagnosis of SCLC and benign pulmonary diseases.

Objective·To develop an early diagnostic model for small cell lung cancer(SCLC)based on differences in serum metabolite expression profiles between patients with SCLC and those with benign pulmonary diseases,using machine learning algorithms.Methods·Serum samples were collected from 29 SCLC patients and 67 patients with benign lung diseases at Shanghai General Hospital,Shanghai Jiao Tong University School of Medicine,as the training cohort.An independent external validation cohort included 20 SCLC patients and 40 patients with benign lung diseases from Gansu Provincial Cancer Hospital.A total of 69 serum metabolites were quantitatively analyzed using liquid chromatography-tandem mass spectrometry(LC-MS/MS).The XGBoost Classifier was employed to rank metabolite importance,and a forward feature selection strategy based on XGBoost was used to identify a subset of key metabolites.Diagnostic models were constructed using AdaBoost,random forest(RF),and light gradient boosting machine(LGBM)algorithms.Model performance was assessed using receiver operating characteristic(ROC)curves and the area under the curve(AUC),and validated on the external test cohort.Results·Principal component analysis(PCA)and orthogonal projections to latent structures-discriminant analysis(OPLS-DA)of the training cohort revealed distinct metabolic profiles between SCLC and benign lung disease patients.Based on feature importance rankings,six key metabolites were selected to construct the MTB-6 diagnostic model.Among the models,AdaBoost achieved the best performance,with an AUC of 0.943,sensitivity of 75.0%,and specificity of 90.9%in the training cohort.In the external test cohort,the model demonstrated robust performance with an AUC of 0.921,sensitivity of 80.0%,and specificity of 87.5%.Conclusion·The MTB-6 model,based on six serum metabolites and the AdaBoost algorithm,exhibits excellent diagnostic performance and holds potential for the differential diagnosis of SCLC and benign pulmonary diseases.

Objective Based on the SWOT analysis method,the temporary medical order dispensing service model of pharmacy intravenous admixture service(PIVAS)of M Hospital was constructed and its implementation effect was evaluated,so as to provide reference for other medical institutions to carry out PIVAS temporary dispensing services.Methods SWOT analysis was used to analyze the advantages,disadvantages,opportunities and threats of PIVAS in M Hospital,and targeted operation strategies and practices were proposed.The safety of intravenous medication,the level of pharmacy service and the cost-effectiveness of the department were used to evaluate the implementation effect of PIVAS temporary medical order dispensing service.Results After the operation strategy of PIVAS temporary medical order dispensing service was constructed and implemented based on SWOT analysis,the time of a single medical order for PIVAS labeling in M Hospital was significantly decreased from(7.19±0.06)s/bag to(6.06±0.09)s/bag(P＜0.05);and the number of errors was significantly reduced from(32.50±2.54)pieces/quarter to(19.75±0.59)pieces/quarter(P＜0.05);The qualified rate of temporary prescription increased from(60.52±1.17)％to(90.63±1.72)％(P＜0.05);The qualified rate of finished infusion delivery time increased from(80.63±1.66)％to(90.80±2.98)％(P＜0.05);The satisfaction rate of PIVAS service in the ward increased from 50％to 90％(P＜0.05);the cost of blending decreased from(3.50±0.05)yuan/bag to(3.00±0.12)yuan/bag(P＜0.05).Conclusion The operation strategy of PIVAS temporary medical order dispensing service of M Hospital based on SWOT analysis gives full play to its own advantages,provides more comprehensive and high-quality services for clinicians and patients,ensures the safety and timeliness of patients' medication,and improves the economic efficiency of the department,which is worthy of reference and promotion.

Objective:The Social Isolation Scale for people with type 2 diabetes mellitus (T2DM) was developed and tested for reliability and validity, which provided an effective tool for measuring the social isolation level of patients with T2DM.Methods:The initial scale was developed through literature review, qualitative interviews, and expert consultation. Convenience sampling method was used to select T2DM patients who met the inclusion and exclusion criteria for questionnaire survey. The item analysis method was used to select the items of the scale. Exploratory and confirmatory factor analyses were used to evaluate construct validity. The content validity of the scale was evaluated by the scale-level content validity index and the item-level content validity index. The criterion validity was verified by using the Lubben Social Network Scale-6 and the De Jong Gierveld Loneliness Scale. Reliability was tested through internal consistency and test-retest reliability.Results:Through literature review and qualitative interviews, 30 items of the scale were selected to form the first version scale. After two rounds of inquiries from 16 experts (expert authority coefficient = 0.897), the second version of the scale was formed. A total of 407 questionnaires were distributed in two stages using the second version scale. Among the 407 patients, there were 214 males and 193 females. Exploratory factor analysis extracted 4 common factors, with a cumulative variance contribution rate of 61.338%. The final scale was determined to include 4 dimensions and 16 items, with the dimensions being "social support network", "frequency of social participation", "satisfaction with interpersonal relationships", and "diabetes-related sense of isolation".The average content validity index at the scale level was 0.929, the content validity index at the item level was 0.830 - 1.000, and the criterion validity was - 0.647 and 0.681. The Cronbach′s α coefficient of the total scale was 0.822, and the test-retest reliability was 0.858.Conclusions:The Social Isolation Scale for people with T2DM has good reliability and validity. It is a reliable and valid tool for assessing social isolation in T2DM patients.

Non-human primate animal models are core tools for the study of highly pathogenic microorganisms and are irreplaceable in the fields of pathology and drug discovery.However,anatomical sampling of non-human primate infection models in high-level biosafety laboratories carries potential risk and related risk assessment and control measures require clarification.Based on biosafety regulations and practical experience,we systematically discuss the risk control strategies of anatomical operations with respect to personal protection,instrument selection,anatomical specifications,documentation,and personnel training.Our review will help to improve the management of high-level biosafety laboratories,reduce the risk of pathogen escape and human infection,and provide support for the safe research of highly pathogenic microorganisms.

Objective:To investigate the risk factors associated with post-prematurity respiratory disease (PPRD) in very preterm infants.Methods:A prospective cohort study was conducted, enrolling 369 very preterm infants who were admitted to the neonatal intensive care unit of Xinhua Hospital, Shanghai Jiao Tong University School of Medicine, within one week of birth from January 2019 to June 2023. Data on maternal and infant clinical characteristics, neonatal morbidities, and treatments during hospitalization were collected. The very preterm infants were divided into 2 groups based on whether they developed PPRD. Continuous variables were compared using Mann-Whitney U test, while categorical variables were compared using χ2 tests or continuity correction χ2 test. Multivariate Logistic regression analysis was used to identify the independent risk factors for PPRD in very preterm infants. Results:Among the 369 very preterm infants, 217 cases(58.8%) were male, with a gestational age of 30 (28, 31) weeks at birth and a birth weight of 1 320 (1 085, 1 590) g. Of these, 116 cases (31.4%) developed PPRD, while 253 cases (68.6%) did not. The very preterm infants in the PPRD group had a lower gestational age and lower birth weight (both, P<0.001). The PPRD group also had a higher proportion of males, lower Apgar scores at the 1 th minute after birth and the 5 th minutes after birth, a higher rate of born via cesarean delivery, and a higher incidence of bronchopulmonary dysplasia, more pulmonary surfactant treatment, longer durations of mechanical ventilation, longer total oxygen therapy, and lower Z-score for weight at discharge (all P<0.05). Multivariate Logistic regression analysis showed that gestational age ( OR=0.85, 95% CI 0.73-0.99, P=0.037), born via cesarean delivery ( OR=2.23, 95% CI 1.21-4.10, P=0.010), a duration of mechanical ventilation ≥7 days ( OR=2.51, 95% CI 1.43-4.39, P=0.001), and a Z-score for weight at discharge ( OR=0.82, 95% CI 0.67-0.99, P=0.040) were all independent risk factors for PPRD in very preterm infants. Conclusion:Very preterm infants with a small gestational age, born via cesarean section, mechanical ventilation ≥7 days, and a low Z-score for weight at discharge should be closely monitored for PPRD, and provided with standardized respiratory management after discharge.

Objective To explore the factors influencing blood drug concentrations of first-line anti-tuberculosis drugs in fixed-dose combinations by analyzing therapeutic drug monitoring data from tuberculosis patients receiving these regimens.Methods This retrospective study enrolled 224 patients who received treatment at Guangzhou Chest Hospital between January 2020 and December 2024.All participants underwent standardized therapy during the intensive phase,with therapeutic drug monitoring of first-line anti-tuberculosis drugs(ANTDs),including isoniazid(INH)and rifampicin(RFP).Data collection was completed in January 2025,at which time clinical records and measured INH and RFP plasma concentrations were updated.Data analysis was conducted from January to February 2025.Eight baseline variables—gender,age,hypoproteinemia(serum albumin<35 g/L),glomerular filtration rate(GFR),and others—were collected.Univariate chi-square tests and multivariate logistic regression analyses were performed to identify independent risk factors associated with subtherapeutic INH and RFP plasma concentrations.Results Among the study participants,71.43%(160/224)exhibited blood drug concentrations below the reference range for INH,compared to 41.07%(92/224)for RFP.The mean blood concentrations(mg/L,±SD)were 2.532±1.371 for INH and 9.428±4.317 for RFP,respectively.One-way analysis indicated significant associations between male gender,positive etiological test results,and subtherapeutic RFP concentrations(P<0.05),suggesting statistically significant differences.Multivariate regression analysis further revealed that male gender(OR=1.992,95%CI:1.094～3.628)and positive etiological tests(OR=1.929,95%CI:1.058～3.517)were independent risk factors for low RFP levels.Conclusions This study demonstrates that therapeutic drug monitoring(TDM)frequently identifies subtherapeutic RFP concentrations in tuberculosis patients undergoing treatment.Multivariate analysis reveals that male sex and positive pathogen test results are independent risk factors associated with low RFP plasma levels.Consequently,clinicians should exercise heightened vigilance in patients exhibiting these characteristics,promptly implementing TDM to guide individualized dose adjustments.Such an approach is crucial for optimizing treatment efficacy and minimizing the risk of drug resistance development.