Objective: To provide evidence for improving emergency blood supply protocols by analyzing the clinical characteristics and disease distribution of emergency transfusion patients, especially those receiving≥10 units of red blood cells (RBCs). Methods: The data of 4 157 patients who urgently applied for large-volume blood transfusion in various hospitals in Shanghai from May 2024 to April 2025 were selected and analyzed statistically. Results: Tertiary gradeA hospitals accounted for the largest proportion of total transfusion volume (U) (48.79%, 8 420/17 256.5), with no statistically significant differences in RBC transfusion volumes among hospitals of different grades (P>0.05). All blood products are most widely used in tertiary hospitals. Obstetric blood transfusion (U)(19.07%, 3 277.5/17 190.5) was the most frequent. A-mong the hospitals of patients who received emergency blood transfusion with red blood cell suspension≥10 U, tertiary gradeA hospitals also had the largest transfusion volume (U)(47.19%, 1 107/2 346). In terms of disease types, the top three diseases in terms of blood transfusion volume (U) were obstetric transfusion (24.59%, 572/2 326), digestive diseases (14.53%, 338/2 326) and tumors (14.19%, 330/2 326). Conclusion: Tertiary grade A hospitals are the main demand units for emergency blood transfusion, with pregnant women and cancer patients being the core blood-using groups. It is suggested that the safety, timeliness and sufficiency of emergency blood transfusion be guaranteed by establishing a hierarchical blood supply mechanism, formulating single-disease blood transfusion plans and promoting precise blood transfusion guided by thromboelastography.

Objective: To discuss the epidemiological characteristics of hand foot mouth disease (HFMD) among children in Jiujiang City, and its correlation with meteorological factors, so as to provide scientific evidence for developing targeted HFMD prevention and control measures. Methods: HFMD incidence data among children and meteorological factor records from Jiujiang City during 2019-2023 were collected. Pearson correlation analysis and Quasi-Poisson regression analysis of generalized additive model were used to analyze the relationship between the number of cases and meteorological factors, calculating correlation coefficients (r) and excess risk (ER). Results: The annual reported children HFMD cases in Jiujiang City during 2019-2023 were 4 299, 4 671, 2 560, 3 230, and 3 584, respectively. Except for a peak in autumn-winter in 2020, outbreaks occurred mainly in spring and summer in other years. The majority of cases involved scattered children (71.11%) and children in daycare centers (26.64%). Pearson correlation analysis showed that total case counts, cases among scattered children, and cases among children in daycare centers were positively correlated with average temperature ( r =0.36, 0.39, 0.23), maximum temperature ( r =0.32, 0.36, 0.20), minimum temperature ( r =0.37, 0.41, 0.24), and average relative humidity ( r =0.19, 0.20, 0.15) (all P <0.05). Quasi-Poisson regression analysis of generalized additive model revealed that total cases, cases among scattered children, and cases among daycare children were positively associated with average temperature ( r =0.05, 0.06, 0.03) and average relative humidity ( r =0.03, 0.02, 0.02) (all P <0.01). Excess incidence risk analysis indicated that for every 10 ℃ increase in average temperature, the ER (95% CI ) values were 72.16 (45.91-103.14), 79.76 (52.99- 111.23 ) and 39.30 (14.45-69.54) among total children, scattered children and daycare children, respectively; for every 10% increase in average relative humidity, the ER (95% CI ) values were 28.69 (12.22-47.56), 27.81 (12.01-45.84) and 24.42 (5.56-46.65), respectively. Conclusions The incidence level of HFMD among children in Jiujiang City is positively correlated with the average temperature and average relative humidity. Higher temperature and humidity are associated with an increased risk of excess HFMD incidence in scattered children compared to children in daycare centers.

Objective: To evaluate the effect of community comprehensive management model intervention among patients with dyslipidemia, so as to provide the reference for optimizing community management strategies and improving the target achievement rate for blood lipids among this population. Methods: From May to June 2023, a multi-stage stratified random sampling method was employed to select patients with dyslipidemia from primary healthcare institutions in Jiaxing City, Zhejiang Province. Eligible participants were randomly assigned to either a control group or an intervention group. The control group received routine management, while the intervention group was subjected to a community comprehensive management model in addition to the routine care. Both groups were followed up for 24 months. Data on demographic characteristics, lifestyle behaviors, physical examination indices, and blood biochemical indicators were collected at baseline and after the intervention through questionnaires, physical examinations, and laboratory tests. Changes in obesity rate, central obesity rate, target achievement rates for blood lipids, blood pressure, and blood glucose, as well as lifestyle modifications, were analyzed. Differences between the two groups before and after the intervention were assessed using generalized estimating equations (GEE). Results: The control group consisted of 560 patients, including 303 females (54.11%) and 430 individuals aged ≥65 years (76.79%). The intervention group also included 560 patients, with 300 females (53.57%) and 431 individuals aged ≥65 years (76.96%). Before the intervention, no statistically significant differences were observed between the two groups in terms of gender, age, educational level, history of chronic diseases, and atherosclerotic cardiovascular disease risk stratification (all P>0.05). After 24 months of intervention, interaction effects between group and time were observed for obesity rate, central obesity rate, target achievement rate for blood lipids, target achievement rate for blood glucose, composite target achievement rate, physical activity rate, and medication adherence (all P<0.05). Specifically, the intervention group demonstrated lower rates of obesity and central obesity, and higher target achievement rate of blood lipids, target achievement rate of blood glucose, composite target achievement rate, physical activity rate, and medication adherence compared to the control group. Conclusion The community comprehensive management model contributed to improvements in multiple metabolic parameters (including body weight, waist circumference, blood lipids, and blood glucose) among patients with dyslipidemia, and was associated with increased physical activity rate and medication adherence.

Objective:To analyze the epidemic characteristics of human brucellosis in Tangshan City, Hebei Province from 2016 to 2024, and to establish a prediction model for forecasting incidence of human brucellosis in Tangshan City from 2025 to 2028, so that to provide evidence for prevention and control strategies.Methods:The incidence data of human brucellosis in Tangshan City from 2016 to 2024 were collected. Brucella strains isolated from blood cultures of patients with acute brucellosis were identified.The onset time and demographic distributions of brucellosis were analyzed using descriptive epidemiological methods. Chi-square test was used for statistical analysis. Python software was used to establish a seasonal autoregressive integrated moving average model (SARIMA model) and predict the incidence of brucellosis in Tangshan City from 2025 to 2028. Results:From 2016 to 2024, a total of 2 446 cases of human brucellosis in Tangshan City were reported, with the highest incidence in 2016 (378 cases) and the lowest in 2022 (277 cases).Seasonal variation was observed, with 54.87%(1 342/2 446) occurring in spring and summer (March to July). The incidence rate of male was 5.28/100 000, which was significantly higher than that of female (1.94/100 000) ( χ2=554.96, P<0.001). The cases spanned all age groups, with the highest incidence among those aged 50 to 59 (30.25%(740/2 446)). Farmers engaged in cattle/sheep breeding accounting for 85.73% (2 097/2 446) of cases. A total of 236 blood samples were collected from patients with acute brucellosis, and 12 Brucella strains were isolated and identified as sheep type Ⅲ Brucella. The optimal model constructed was SARIMA (1, 0, 0) (1, 0, 1) 12, which was used to predict the incidence of human brucellosis in Tangshan City from 2025 to 2028. The results showed that the overall incidence was relatively stable, retaining the characteristic single annual peak. Conclusions:Human brucellosis in Tangshan City peaks in spring/summer and predominantly affects cattle/sheep farmers. The SARIMA (1, 0, 0) (1, 0, 1) 12 model effectively fits the epidemiological data of human brucellosis in Tangshan City well and enables reliable future trend predictions, supporting scientific and effective prevention and control work.

AIM To establish a UPLC-ESI-MS/MS method for analyzing the toxic material basis of 95％ethanol cold soaked ultrasonic extract(EC),95％ethanol heated reflux extract(EH)and water decoction extract(WD)from Dryopteris crassirhizoma Nakai.METHODS The analysis was performed on a 25 ℃ thermostatic agilent ZORBAX RRHD StableBond C18 column(2.1 mm×150 mm,1.8 μm),with the mobile phase comprising of methanol-0.2％formic acid flowing at 0.30 mL/min,and heated electrospray ion source was adopted in positive and negative ion scanning.Compounds were identified by Compound Discover 3.3 software combined with the database and related literature,and the main differential components were screened by Heatmap cluster analysis and partial least squares discriminant analysis.RESULTS 72 compounds were identified(22 phloroglucinols,19 flavonoids,8 phenylpropanoids,6 terpenoids and 17 other components).The main toxic differential components were phloroglucinols such as flavaspidic acid AB,didemethylpseudoaspidin AA and filixic acid PBP,flavonoids such as(-)-epicatechin,(-)-epigallocatechin,cianidanol,and other compounds such as indole-3-carboxaldehyde.CONCLUSION This method can rapidly,effectively and comprehensively characterize the main chemical composition of D.crassirhizoma,and provide a reference for the study of its pharmacological mechanism.

Diabetic kidney disease(DKD)with increasing global prevalence lacks effective therapeutic targets to halt or reverse its progression.Therapeutic targets supported by causal genetic evidence are more likely to succeed in randomized clinical trials.In this study,we integrated large-scale plasma proteomics,genetic-driven causal inference,and experimental validation to identify prioritized targets for DKD using the UK Biobank(UKB)and FinnGen cohorts.Among 2844 diabetic patients(528 with DKD),we identified 37 targets significantly associated with incident DKD,supported by both observational and causal evi-dence.Of these,22％(8/37)of the potential targets are currently under investigation for DKD or other diseases.Our prospective study confirmed that higher levels of three prioritized targets-insulin-like growth factor binding protein 4(IGFBP4),family with sequence similarity 3 member C(FAM3C),and prostaglandin D2 synthase(PTGDS)—were associated with a 4.35,3.51,and 3.57-fold increased likeli-hood of developing DKD,respectively.In addition,population-level protein-altering variants(PAVs)analysis and in vitro experiments cross-validated FAM3C and IGFBP4 as potential new target candidates for DKD,through the classic NLR family pyrin domain containing 3(NLRP3)-caspase-1-gasdermin D(GSDMD)apoptotic axis.Our results demonstrate that integrating omics data mining with causal inference may be a promising strategy for prioritizing therapeutic targets.

Objective To explore the efficacy of DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy for management of cancer pain and provide reference for its standardized clinical application.Methods and Results Recommendations were formulated based on literature review and expert group discussion,and consensus was reached following expert consultation.The consensus recommendations are comprehensive,covering the entire treatment procedures from preoperative assessment and preparation,surgical operation process,postoperative management and traditional Chinese medicine treatment to individualized treatment planning.The study results showed that the treatment plans combining traditional Chinese with Western medicine effectively alleviated cancer pain,reduced the use of opioid drugs,and significantly improved the quality of life and enhanced immune function of the patients.Postoperative follow-up suggested good treatment tolerance among the patients without serious complications.Conclusion The formulated consensus is comprehensive and can provide reference for clinicians to use DSA-guided intrathecal drug delivery system combined with Zi Wu Liu Zhu Acupoint Therapy.The combined treatment has a high clinical value with a good safety profile for management of cancer pain.

OBJECTIVE: To explore the impact of age on the genetic variant spectrum and prognosis of patients with previously untreated Diffuse large B-cell lymphoma (DLBCL). METHODS: A retrospective analysis was conducted on the clinical data and follow-up information of 254 previously untreated DLBCL patients from 14 hospitals in the Jiangsu Cooperative Lymphoma Group (JCLG) enrolled from July 2018 and July 2023. Following extraction of DNA from tumor tissue samples, next-generation sequencing (NGS) technique was employed to analyze the genetic variant spectrum of the DLBCL patients, with an evaluation of the relationship between age and genetic variants as well as prognosis. This study was approved by the Medical Ethics Committee of the Affiliated Hospital of Nantong University (Ethics No.: 2023-K048-01). RESULTS: The median age of the 254 DLBCL patients was 62 years old, with 55% of patients aged 60 years or above. Clinical evaluation showed that younger (< 60 years) patients had higher complete response (CR) (70% vs. 59%), and objective response rate (ORR) (88% vs. 79%) than older patients, though the difference between the two groups was not statistically. Survival analysis indicated that both the five-year overall survival (OS) (82.7% vs. 71.7%, P = 0.006) and progression-free survival (PFS) (70.6% vs. 50.2%, P < 0.05) rates were significantly higher in younger patients. NGS showed that 99.6% of the patients harbored genetic variants, with PIM1, KMT2D, TP53, MYD88, and CD79B being the most common genes. Age significantly affected the variant frequency of certain genes, with MYC variants serving an adverse prognostic factor for OS in younger patients (P = 0.002), while TP53 (P = 0.024) and BCL2 (P = 0.002) variants significantly impacted OS in older patients. Prognostic analysis identified age ≥ 60 years (HR = 3.439, 95%CI: 1.318~9.874), presence of B symptoms (HR = 2.871, 95%CI = 1.133~7.307), and elevated lactate dehydrogenase (HR = 3.528, 95%CI = 1.231~10.66) as independent adverse prognostic factors. CONCLUSION Age, genetic variants, and clinical factors may significantly affect the prognosis of the DLBCL patients. Younger patients have better survival compared to older patients. Variants of the MYC, BCL2, and TP53 genes are closely associated with poor prognosis.
Humans ; Lymphoma, Large B-Cell, Diffuse/diagnosis* ; Middle Aged ; Female ; Male ; Retrospective Studies ; Aged ; Prognosis ; Adult ; Aged, 80 and over ; High-Throughput Nucleotide Sequencing ; Young Adult ; Adolescent ; Genetic Variation

The traditional Chinese medicine （TCM） myocardial infarction （MI） unit is a standardized， regulated， and continuous integrated care unit guided by TCM theory and built upon existing chest pain centers or emergency care units. This unit emphasizes multidisciplinary collaboration and forms a restructured clinical entity without altering current departmental settings， offering comprehensive diagnostic and therapeutic services with full participation of TCM in the treatment of MI. Its core medical model is patient-centered and disease-focused， providing horizontally integrated TCM-based care across multiple specialties and vertically constructing a full-cycle treatment unit for MI， delivering prevention， treatment， and rehabilitation during the acute， stable， and recovery phases. Additionally， the unit establishes a TCM-featured education and prevention mechanism for MI to guide patients in proactive health management， reduce the incidence of myocardial infarction， and improve quality of life.

Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans ; Diagnostic Imaging/methods* ; Precision Medicine/methods* ; Image Processing, Computer-Assisted/methods*