ObjectiveTo analyze the epidemiological characteristics of 8 major respiratory pathogens in influenza-like illness (ILI) cases with acute respiratory infections at fever clinics in Huangpu District, Shanghai from 2015 to 2024, and to provide a scientific basis for the prevention and treatment of respiratory diseases. MethodsA retrospective study was conducted in Huangpu District. Individuals meeting the case definition of ILI from 2015 to 2024 was registered. Their nasopharyngeal swabs were collected for pathogen detection. A total of 8 respiratory viruses were tested, including Influenza A virus (Flu A), Influenza B virus (Flu B), adenovirus (ADV), enterovirus/human rhinovirus (EV/HRV), human parainfluenza virus (HPIV), human coronavirus (HCoV), respiratory syncytial virus (RSV), and human metapneumovirus (HMPV). ResultsFrom 2015 to 2019, a total of 344 ILI cases were tested, of which 192 out of 344 cases (55.81%) were tested positive for single respiratory pathogen. From 2023 to 2024, 1 557 ILI cases were tested, with 572 out of 1 557 cases (36.74%) being positive for single pathogen. From 2023 to 2024, the positive rate of single pathogen in ILI cases was significantly lower than that in 2015‒2019 (χ²=42.66, P<0.001). Specifically, the positive rate of Flu A (χ²=74.43, P<0.001) decreased, while that of HPIV (χ²=8.66, P=0.003) increased, both with statistically significant differences. According to the seasonal pattern, the epidemic intensity of Flu A decreased in summer, while that of HPIV increased in summer and autumn. Demographic results showed statistically significant differences in the positive rates of EV/HRV between genders (χ²=22.38, P<0.001), with males exhibiting a higher positive rate than females. No statistically significant differences were identified in the positive rates of single pathogen among different age groups (χ²=4.42, P=0.110). Nevertheless, statistically significant differences were noted when comparing the positive rates of EV/HRV, Flu A, Flu B and HPIV across different age groups (P<0.05). EV/HRV was more commonly detected in the 15‒<25 age group (10.93%), while Flu A and HPIV had the highest positive rates in the ≥60 age group (21.24% and 4.77%). Flu B had the highest positive rate in the 25‒<60 age group (11.26%). 52.63% of cases with co-infections occurred during winter, with the primary pathogens involved being EV/HRV (9 cases) and HCoV (6 cases). The most prevalent combination of co-infection was Flu A with EV/HRV. ConclusionThe prevalence of respiratory pathogens among ILI cases from 2023 to 2024 exhibited notable fluctuations compared to that from 2015 to 2019. Therefore, influenza surveillance should be strengthened, and attention should also be paid to the prevalence of respiratory pathogens such as HPIV. These findings have profound implications for future research, surveillance, vaccine planning, and public health policy making.

BackgroundAddictive non-suicidal self-injury （NSSI） behaviors among adolescents have become increasingly prominent， although previous studies have identified multiple related risk factors and have examined the association between screen time and NSSI behaviors， the impact of screen time on NSSI behaviors addiction， as well as the mediating role of family dysfunction in this relationship， remain to be further clarified. ObjectiveTo investigate the mediating role of family dysfunction in the relationship between screen time and NSSI behaviors addiction among adolescent female patients with depression disorder， with the aim of providing references for reducing NSSI behaviors addiction. MethodsFrom September 2024 to November 2025， a total of 652 adolescent female patients with depression disorder were enrolled from both outpatient and inpatient departments of Xiamen Xian-yue Hospital， all of whom met the diagnostic criteria for depressive episode （F32） or recurrent depressive disorder （F33） according to the International Classification of Diseases， tenth edition （ICD-10）. Assessments included a self-developed demographic questionnaire， screen use questionnaire， Chinese Family Assessment Instrument （C-FAI）， and Ottawa Self-injury Inventory Chinese Revised version （OSIC）. Among participants with NSSI behaviors， Spearman correlation analysis was used to examine the correlation between screen time and scale scores. Model 4 of the Process 4.1 for SPSS 26.0 was then applied to test the mediating role， and Bootstrapping procedure involving 5 000 replicates was employed to confirm the statistical significance. ResultsAmong the 652 patients， 569 （87.27%） exhibited NSSI behaviors. Among them， 398 cases （69.95%） belonged to the addictive NSSI group， and 171 cases （30.05%） belonged to the non-addictive NSSI group. The OSIC addiction dimension score was positively correlated with screen time and C-FAI scores （r_s=0.114， 0.224， P<0.01）. Family dysfunction mediated the relationship between screen time and NSSI addiction， with an indirect effect value of 0.036 （95% CI： 0.016–0.062）， accounting for 35.88% of the total effect. ConclusionScreen time may affect the NSSI behaviors addiction in adolescent female patients with depression disorder through family dysfunction. ［Funded by Joint Funds for the Innovation of Science and Technology， Fujian Province （number， 2025Y9762）］

OBJECTIVE To construct a closed-loop management model for externally dispensed intravenous prescriptions， and to provide reference for standardized management of externally dispensed intravenous prescriptions. METHODS Based on the Expert Consensus on Closed-loop Management of Externally Dispensed Intravenous Prescriptions in Guangxi Zhuang Autonomous Region previously formulated by our hospital， risk points during the entire process were systematically identified through multidisciplinary team brainstorming and a fishbone diagram. A series of strategies were subsequently formulated and implemented， including qualifying designated external dispensing pharmacies and the drug catalogs， operating and maintaining the hospital information system and the Pharmacy Intravenous Admixture Service （PIVAS） intelligent management platform， and strengthening differentiated training for staff in the whole workflow. A whole-process closed-loop management system was constructed with PIVAS as the co re hub and the daytime chemotherapy center as the safety terminal. RESULTS A total of 3 cooperating pharmacies and an initial drug list comprising 35 product specifications were selected. A closed‑loop management process encompassing hospital outpatient prescribing， patient drug purchase in designated pharmacies， PIVAS drug dispensing， and medication use in daytime chemotherapy center was successfully established. This system enabled the mandatory grouping and association of externally dispensed intravenous prescriptions with in-hospital diluents， full-process verification based on drug traceability codes， intelligent monitoring of infusion parameters， and whole-process data traceability. CONCLUSIONS The constructed model effectively resolves the coordination and safety oversight during the use of externally dispensed intravenous drugs from out-of-hospital circulation to in-hospital use， and has preliminarily enabled procedural standardization， whole-process information traceability， and proactive control of medication risks.

ObjectiveTo investigate the effects of zinc finger E-box binding homeobox 1 （ZEB1） on the proliferation， migration， and invasion of lung adenocarcinoma H322 cells， as well as its underlying molecular mechanisms. MethodsThe gene expression characteristics of the transcription factor ZEB1 in lung adenocarcinoma were analyzed using data from the GEO and TCGA public databases. RT-qPCR and Western blot were employed to measure mRNA and protein expression levels of ZEB1 in lung adenocarcinoma cell lines （H322， A549， 95-D） and normal human bronchial epithelial cells （BEAS-2B）. Lentiviral transduction was utilized to establish stable ZEB1-overexpressing （Oe-ZEB1） and vector control （Oe-NC） H322 cell lines. Cell proliferation was assessed using CCK-8， colony formation， and EdU assays， while apoptosis was evaluated by Hoechst33258/PI double staining. Wound healing and Transwell assays were performed to examine cell migration and invasion capabilities. Cell cycle distribution was determined by flow cytometry， and Western blot was used to analyze protein expression changes in relevant signaling pathways. ResultsThe findings from GEO and TCGA indicated that ZEB1 expression in lung adenocarcinoma varied with tumor malignancy grade. RT-qPCR and Western blot analyses revealed significantly higher ZEB1 expression in lung adenocarcinoma cell lines compared to BEAS-2B cells （P0.05）. Results from the CCK-8， colony formation， EdU， wound healing， and Transwell assays demonstrated that， compared with the un-transfected control （Control） group， Oe-ZEB1 H322 cells exhibited enhanced proliferation， migration， and invasion capabilities （P0.05）. Hoechst33258/PI double staining and flow cytometry analyses showed that， relative to the Control group， apoptosis was reduced in Oe-ZEB1 H322 cells （P0.05）. Additionally， a decreased proportion of cells in the G₁ phase and an increased proportion in the S phase were observed in Oe-ZEB1 cells， indicating accelerated cell cycle progression. Western blot analysis further revealed that， compared with the Control group， Oe-ZEB1 H322 cells exhibited upregulated expression of N-cadherin， mutant p53 （mutp53）， and Cyclin D1 （P0.05）， while expression levels of E-cadherin， murine double minute 2 （MDM2）， and p21 were downregulated （P0.05）. ConclusionOverexpression of ZEB1 promotes the proliferation， migration， and invasion of lung adenocarcinoma H322 cells and may facilitate cell cycle progression by modulating the MDM2/mutp53/p21 signaling pathway， thereby promoting the transition of cells from the G₀/G₁ phase to the S phase.

Breast cancer prevention and treatment have become major issues that urgently need to be addressed in the field of global public health. As a key pathological transitional stage in the progression of breast cancer， preneoplastic breast cancer （PBC） carries a significant risk of clinical transformation. Effective intervention in the progression of PBC is of great clinical significance in preventing the occurrence of breast cancer. Pathological studies have shown that abnormal angiogenesis is a key mechanism driving the transformation of PBC into breast cancer. Vascular endothelial growth factor （VEGF）， as a core regulatory molecule that promotes angiogenesis， plays a pivotal role in this process. The malignant transformation of PBC is closely associated with the abnormal activation of the VEGF-mediated pro-angiogenic network. Although modern medicine has achieved certain therapeutic effects through surgery and endocrine therapy， clinical limitations such as invasiveness， drug resistance， and adverse reactions still exist. Recent studies have demonstrated that the VEGF signaling system mediates the phosphatidylinositol 3-kinase-protein kinase B （PI3K/Akt） signaling pathway and the mitogen-activated protein kinase （MAPK） pathway. In addition， the hypoxia-inducible factor-1α （HIF-1α）/VEGF signaling pathway and the delta-like ligand 4 （DLL4）/Notch receptor 1 （Notch1） signaling pathway， together with other pathways， form a complex regulatory network that plays a central role in angiogenesis during PBC. Traditional Chinese medicine （TCM）， characterized by multi-component synergy， multi-pathway regulation， and high safety， demonstrates significant advantages in inhibiting pathological angiogenesis and blocking PBC progression by targeting the VEGF signaling pathway. From the perspective of VEGF pathway regulation， this paper systematically reviews the latest research progress on TCM in inhibiting angiogenesis and intervening in PBC， and discusses its mechanisms and application value in the early prevention and treatment of PBC， with the aim of providing references for optimizing clinical intervention strategies for PBC.

Background Diesel engines are widely used in transportation, agriculture, construction, industry, and other fields. Diesel exhaust, classified as a Group 1 carcinogen, emits particles (DEP) that can penetrate deep into the respiratory tract, posing significant health risks. DEP pollution is particularly severe in confined environments, necessitating effective control measures. Objective Under laboratory simulation conditions, to explore the spatiotemporal distribution characteristics of the mass and number concentrations of DEP as it diffuses indoors and to reveal the effects of ventilation and additional airflow on indoor DEP pollution levels. Methods A diesel engine was placed in a laboratory (length 3.39 m × width 2.85 m × height 2.4 m) with its exhaust emitted from east to west. An air purifier was installed 1 m south of the engine. Eight measurement points (1 m horizontal distance from the exhaust outlet, height: 1 m/1.5 m) were setup to monitor DEP concentrations using portable laser particle sizers. The effects of engine power (4.05 kW vs. 5.15 kW), ventilation (maximum airflow: 600 m³·h⁻¹), additional airflow intensity (low and high), and direction (forward/reverse) on DEP pollution were analyzed. DEP levels of 5 diesel vehicle models were also compared. Results The mass and number concentrations of DEP indoors increased immediately after the diesel engine started. The peak mass concentration time at the eastern measurement point (−1, 0) m opposite to the exhaust direction (17.70 min) was significantly longer than that at the western (1, 0) m (16.20 min), southern (0, -1) m (14.45 min), and northern (0, 1) m (12.70 min) points (P<0.05), with no significant differences between the other points (western, southern, and northern) (P>0.05). The northern point (0, 1) m exhibited the highest DEP mass and number concentration peaks (174.62 μg·m⁻³, 1319.85 p·cm⁻³), significantly exceeding those at the southern (0, −1) m (129.89 μg·m⁻³, 1175.24 p·cm⁻³), eastern (−1, 0) m (140.12 μg·m⁻³, 1120.53 p·cm⁻³), and western (1, 0) m (147.60 μg·m⁻³, 818.62 p·cm⁻³) points (P<0.05), and no significant differences were observed among other points (P>0.05). There were no significant differences in peak DEP mass and number concentrations by measurement heights (P>0.05). Diesel engine power, ventilation, airflow intensity, and airflow direction had no significant effect on the time of peak DEP concentration (P>0.05). However, higher engine power (5.15 kW) produced greater DEP peaks [(186.66±19.29) μg·m⁻³, (1382.79±122.56) p·cm⁻³] than the 4.05 kW engine power [(168.41±12.65) μg·m⁻³, (1284.45±71.30) p·cm⁻³] (P<0.05). The peak mass concentration [(342.04±35.03) μg·m⁻³] and number concentration [(1886.87±57.91) p·cm⁻³] of DEP in the non-ventilated group were significantly higher than those in the ventilated group [(186.66±19.29) μg·m⁻³, (1382.79±122.56) p·cm⁻³] (P<0.001). Forward airflow elevated DEP mass concentrations compared to reverse airflow (287.71 μg·m⁻³ vs. 243.74 μg·m⁻³, t=−2.592, P=0.009), but no effects on DEP number concentration (P>0.05). Significant differences in mass concentration were observed among selected 5 vehicle models (Z=38.109, P<0.001). Conclusion The operation of diesel engines will emit a large amount of particulate matter, causing pollution in enclosed spaces. Diesel engines with greater power have higher levels of DEP pollution emissions. Based on the spatiotemporal distribution characteristics, it is recommended to set the operation position in the reverse direction of exhaust emissions and close to air purifiers, while avoiding the use of additional air flow equipment.

Objective: To investigate the clinical characteristics, the types of unexpected antibodies, and their impacts on immunological risks among patients with different frequencies of cross-matching incompatibility, so as to propose corresponding solutions. Methods: Data of cross-matching incompatibility samples from 92 medical institutions during 2022 to 2024 were collected and divided into three groups based on the frequency of cross-matching. Statistical analysis was performed on disease types, distribution of hematologic diseases, alloantibody detection rates, and proportions of alloantibody types. Results: The 858 patients were divided into three groups based on the frequency of blood cross-matching incompatibility: ≥5 times (8.28%, 71/858), 2 to 4 times (28.21%, 242/858); 1 time (63.52%, 545/858). There was a clustered distribution of disease types in the ≥5 cross-matchings group, with 71.83% (51/71) of patients having tumors or hematologic and hematopoietic diseases. In contrast, the disease types in the 2 to 4 cross-matchings and 1 cross-matching groups were more diverse. An analysis of 249 patients with hematologic diseases found that multiple myeloma was the most common disease in all three groups, accounting for 31.43% (11/35), 35.37% (29/82), and 37.88% (50/132) respectively. In the ≥5 cross-matchings group, myelodysplastic syndrome (14.29%, 5/35) and thalassemia (14.29%, 5/35) were the second most common diseases. In contrast, in the 2 to 4 cross-matchings group and 1 cross-matching group, autoimmune hemolytic anemia was the second most common disease, with prevalence rates of 20.73% (17/82) and 24.24% (32/132), respectively. Alloantibodies were detected in 54.66% of the patients, with antibodies against Rh blood group being most frequent (>50%) in all three groups. The detection rates of alloantibodies/alloantibodies with coexisting autoantibodies decreased across groups: the ≥5 cross-matchings group (70.42%, 50/71) > the 2 to 4 cross-matchings group (54.96%, 133/242) > the 1 cross-matching group (52.48%, 286/545). Conclusion: The risk of alloantibody production increases in patients with multiple cross-matching incompatibilities, especially in those with tumors or hematologic diseases. For handling of cross-matching incompatibility cases, it is recommended to optimize the cross-matching process, implement individualized transfusion plans, and enhance the technical capabilities of clinical transfusion departments and blood group reference laboratories to ensure the safety and effectiveness of transfusions.

Objective To explore the clinical value of artificial intelligence (AI) quantitative parameters in distinguishing pathological grades of stageⅠ invasive adenocarcinoma (IAC). Methods Clinical data of patients with clinical stageⅠ IAC admitted to Yantaishan Hospital Affiliated to Binzhou Medical University from October 2018 to May 2023 were retrospectively analyzed. Based on the 2021 WHO pathological grading criteria for lung adenocarcinoma, IAC was divided into gradeⅠ, grade Ⅱ, and grade Ⅲ. The differences in parameters among the groups were compared, and logistic regression analysis was used to evaluate the predictive efficacy of AI quantitative parameters for grade Ⅲ IAC patients. Parameters were screened using least absolute shrinkage and selection operator (LASSO) regression analysis. Three machine learning models were constructed based on these parameters to predict grade Ⅲ IAC and were internally validated to assess their efficacy. Nomograms were used for visualization. Results A total of 261 IAC patients were included, including 101 males and 160 females, with an average age of 27-88 (61.96±9.17) years. Six patients had dual primary lesions, and different lesions from the same patient were analyzed as independent samples. There were 48 patients of gradeⅠ IAC, 89 patients of grade Ⅱ IAC, and 130 patients of grade Ⅲ IAC. There were statitical differences in the AI quantitive parameters such as consolidation/tumor ratio (CTR), ect among the three goups. (P<0.05). Univariate analysis showed that the differences in all variables except age were statistically significant (P<0.05) between the group gradeⅠ+grade Ⅱand the group grade Ⅲ . Multivariate analysis suggested that CTR and CT standard deviation were independent risk factors for identifying grade Ⅲ IAC, and the two were negatively correlated. Grade Ⅲ IAC exhibited advanced TNM staging, more pathological high-risk factors, higher lymph node metastasis rate, and higher proportion of advanced structure. CTR was positively correlated with the proportion of advanced structures in all patients. This correlation was also observed in grade Ⅲ but not in gradeⅠand grade ⅡIAC. CTR and CT median value were selected by using LASSO regression. Logistic regression, random forest, and XGBoost models were constructed and validated, among which, the XGBoost model demonstrated the best predictive performance. Conclusion Cautious consideration should be given to grade Ⅲ IAC when CTR is higher than 39.48% and CT standard deviation is less than 122.75 HU. The XGBoost model based on combined CTR and CT median value has good predictive efficacy for grade Ⅲ IAC, aiding clinicians in making personalized clinical decisions.

Jiegeng decoction is a classic prescription composed of two Chinese medicinal herbs： Platycodon grandiflorum and Glycyrrhiza uralensis. It has the efficacy of diffusing lung qi， resolving phlegm， relieving sore throat and discharging pus， and is commonly used in the treatment of respiratory diseases such as cough and pharyngodynia. This article reviews the chemical components， pharmacological mechanisms and clinical applications of Jiegeng decoction. It was found that Jiegeng decoction contains triterpenoid saponins， flavonoids， glycosides， acids， and other components， with platycodin D， platycodin D2， glycyrrhizic acid， glycyrrhetinic acid， liquiritin， etc.， serving as the main active pharmaceutical ingredients. Jiegeng decoction and its chemical constituents exert anti-inflammatory effects by inhibiting signaling pathways such as nuclear factor-κB and mitogen- activated protein kinases， and demonstrate anti-tumor activities through mechanisms like modulating the tumor immune microenvironment and promoting cancer cell apoptosis. Additionally， it exhibits various pharmacological actions including antibacterial， antiviral， and antioxidant effects. Clinically， Jiegeng decoction， its modified prescription and compound combinations are widely used in the treatment of respiratory diseases such as cough， pneumonia， and pharyngitis， as well as digestive system disorders like constipation.

Gastric cancer has high incidence and mortality rate. Chemotherapy is the first-line treatment for gastric cancer and has achieved considerable success. However, due to genetic variations and tumor heterogeneity, the effectiveness of chemothrapy drugs varies among different patients. Therefore, accurate assessment of patient’s sensitivity to chemotherapy drugs is crucial for personalized treatment. Gastric cancer organoids serve as effective tools for predicting patient’s sensitivity to chemotherapy drugs. This review summarizes the applications and related research progress of gastric cancer organoids in determining chemotherapy drug sensitivity, discusses the strengths and limitations of organoid models, and proposes outlooks for future research directions, hoping that organoids can provide more effective personalized treatment options and a greater range of drug choices for gastric cancer treatment.