Objective: To analyze the epidemiological characteristics and influencing factors of severe fever with thrombocytopenia syndrome (SFTS) in Zhejiang Province from 2019 to 2023, so as to provide the reference for strengthening SFTS prevention and control. Methods: Data on laboratory-confirmed SFTS cases in Zhejiang Province from 2019 to 2023 were collected through the Infectious Disease Reporting Information System of Chinese Disease Prevention and Control Information System. Meteorological data, geographic environment and socioeconomic factors during the same period were collected from the fifth-generation European Centre for Medium-Range Weather Forecasts, Geospatial Data Cloud, and Zhejiang Statistical Yearbook, respectively. Descriptive epidemiological methods were used to analyze the epidemiological characteristics of SFTS from 2019 to 2023, and a Bayesian spatio-temporal model was constructed to analyze the influencing factors of SFTS incidence. Results: A total of 578 SFTS cases were reported in Zhejiang Province from 2019 to 2023, with an annual average incidence of 0.23/105. The peak period was from May to July, accounting for 52.60%. There were 309 males and 269 females, with a male-to-female ratio of 1.15∶1. The cases were mainly aged 50-<80 years, farmers, and in rural areas, accounting for 82.53%, 77.34%, and 75.43%, respectively. Taizhou City and Shaoxing City reported more SFTS cases, while Shaoxing City and Zhoushan City had higher annual average incidences of SFTS. The Bayesian spatio-temporal interaction model showed good goodness of fit. The results showed that mean temperature (RR=1.626, 95%CI: 1.111-2.378) and mean wind speed (RR=1.814, 95%CI: 1.321-2.492) were positively correlated with SFTS risk, while altitude (RR=0.432, 95%CI: 0.230-0.829) and population density (RR=0.443, 95%CI: 0.207-0.964) were negatively correlated with SFTS risk. Conclusions SFTS in Zhejiang Province peaks from May to July. Middle-aged and elderly people and farmers are high-risk populations. Taizhou City, Shaoxing City, and Zhoushan City are high-incidence areas. Mean temperature, mean wind speed, altitude, and population density can all affect the risk of SFTS incidence.

Background Nano-alumina (nano-Al₂O₃) is a widely utilized nanomaterial. Its impacts on the environment and biological systems have garnered significant attention. Zebrafish serves as a common model organism in scientific research due to its high homology with the human genome and is extensively used in toxicity studies. Objective To investigate the developmental toxicity and neurotoxicity of nano-Al₂O₃ exposure in zebrafish and the corresponding mechanisms of action. Method Zebrafish embryos at 6 h post-fertilization (hpf) were randomly assigned to a control group and five dose groups exposed to nano-Al₂O₃ at concentrations of 200, 400, 600, 800, and 1000 μg·mL⁻¹, respectively. Thirty embryos were included in each group, and the culture medium was replaced every 24 h until 144 hpf. The hatching rates at 48 and 72 hpf and the cumulative malformation rates up to 144 hpf were calculated. At 144 hpf, a zebrafish behavior analyzer was used to record the movement trajectories of the zebrafish, and the total distance traveled and average speed were analyzed for each group. At 144 hpf, the development of dopaminergic neurons in transgenic zebrafish expressing vmat2: GFP, brain vessels in those expressing vegf: GFP, and central nervous system neurons in those expressing elavl3: EGFP were observed under a fluorescence microscope, and statistical analysis was conducted using Image Pro Plus. Real-time quantitative PCR was employed to detect the expression levels of neuron development-related genes (syn2α, gap43, dat), Lewy body formation-related gene (α-syn), and autophagy-related genes (pink1, parkin) at 144 hpf. Results Compared to the control group, the nano-Al₂O₃ exposed groups exhibited reduced hatching rates at 48 hpf and increased cumulative malformation rates (P<0.05), with phenomena such as delayed development, absence of the swim bladder, and body curvature. The autonomous behavioral tests revealed that the nano-Al₂O₃ exposed zebrafish showed a decrease in the total distance swum (P<0.001) and a significant reduction in average speed compared to the control group. The fluorescence observations indicated that the length of dopaminergic neurons in vmat2: GFP transgenic zebrafish was reduced in the nano-Al₂O₃ exposed groups (P<0.001). Additionally, vegf: GFP transgenic zebrafish exhibited a significant absence of brain vessels, while elavl3: EGFP transgenic zebrafish showed a weakened fluorescence intensity of central nervous system neurons (P<0.001) and a decreased length of these neurons (P<0.01). The real-time quantitative PCR analysis revealed that compared to the control group, the gene expression levels of α-syn, syn2α, dat, and gap43 were upregulated in the zebrafish exposed to nano-Al₂O₃ (except for the 400 μg·mL⁻¹ exposure group) (P<0.01), while the expression levels of parkin were downregulated in the 600 and 800 μg·mL⁻¹ nano-Al₂O₃ exposed groups, and the expression levels of pink1 were downregulated in all exposure groups except for the 200 μg·mL⁻¹ group (P<0.05). Conclusion Exposure to nano-Al₂O₃ exhibits developmental toxicity in zebrafish larvae and induces Parkinsonism-like symptoms in zebrafish. The preliminary speculation of the mechanism suggests that it may be related to nano-Al₂O₃-induced mitochondrial autophagy impairment.

Exposure to ionizing radiation intervenes in genomic stability and gene expression,resulting in the disruption of normal metabolic processes in cells and organs by causing complex biolog-ical responses.Altered genomic variations,gene expression and metabolite concentrations in blood or tissue samples reflect systemic radiation damage.With the application of new techniques and exten-sive study on the mechanisms for ionizing radiation damage,related indicators such as chromosomal variation,gene expression,lipid and metabolism are being recognized and promise to be the markers for early diagnosis and prognosis of radiation exposure.Therefore,this article reviews recent progress in and potential applications of biomarkers related to ionizing radiation injury.

Objective:To study the protective effect of Mongolian medicine Bateri-7 on radiation-induced intestinal injury in mice.Methods:C57BL/6J male mice were randomly divided into control group, irradiation group and irradiation plus drug administration group, with 10 or 15 mice in each group. For irradiation group, the mice were given a single dose of 12 Gy 60Co γ-rays with total body irradiation. For drug treatment, the mice were gavaged with Bateri-7 (530 mg/kg) 7 d before irradiation until 3 d after IR. At 6 h and 24 h after irradiation, the Tunel positive cells in intestine were detected immunohistochemically. At 3.5 d after irradiation, the structure of intestinal villi was observed by HE staining, and the BrdU and Ki67 positive cells were detected immunohistochemically. The expression levels of IL-6, TNF-α and Cxcl-5 were detected by qPCR. The FITC-dextran in peripheral blood was also determined. Results:The survival of irradiated mice was significantly increased by Bateri-7 ( χ2= 5.84, P < 0.05), but there was no significant difference in weight between two groups ( P > 0.05). The villi length of small intestine in the irradiation plus drug group was significantly longer than that in the irradiation group ( t = 20.24, P < 0.05), and there was no significant difference in the depth of intestinal crypt between two groups ( P > 0.05). At 6 and 24 h after irradiation, the number of Tunel positive cells in intestinal crypts in the irradiation plus drug group was significantly reduced in comparison with the irradiation group ( t = 3.52, 2.90, P < 0.05). At 3.5 d after irradiation, the level of FITC-dextran in serum and the expressions of IL-6, TNF-α and Cxcl-5 in small intestine of mice in the irradiation plus drug group were significantly lower than those in the irradiation group, respectively( t = 6.92, 7.01, 7.18, 13.16, P < 0.05). The number of BrdU and Ki67 positive cells in the crypt of mice in the irradiation plus drug group was higher than that of the irradiation group ( t = 3.91, 2.57, P < 0.05). Conclusions:Mongolian medicine Bateri-7 can effectively alleviate irradiation-induced intestinal injury of mice, which may have a good preventive and therapeutic effect on radiation enteritis.

Despite recent studies, relatively few are known about the diversity of fungal communities in the deep Atlantic Ocean. In this study, we investigated the diversity of fungal communities in 15 different deep-sea sediments from the South Atlantic Ocean with a culturedependent approach followed by phylogenetic analysis of ITS sequences. A total of 29fungal strains were isolated from the 15 deep-sea sediments. These strains belong to four fungal genera, including Aspergillus, Cladosporium, Penicillium, and Alternaria. Penicillium, accounting for 44.8% of the total fungal isolates, was a dominant genus. The antiaflatoxigenic activity of these deep-sea fungal isolates was studied. Surprisingly, most of the strains showed moderate to strong antiaflatoxigenic activity. Four isolates, belonging to species of Penicillium polonicum, Penicillium chrysogenum, Aspergillus versicolor, and Cladosporium cladosporioides, could completely inhibit not only the mycelial growth of Aspergillus parasiticus mutant strain NFRI-95, but also the aflatoxin production. To our knowledge, this is the first report to investigate the antiaflatoxigenic activity of culturable deep-sea fungi. Our results provide new insights into the community composition of fungi in the deep South Atlantic Ocean. The high proportion of strains that displayed antiaflatoxigenic activity demonstrates that deep-sea fungi from the Atlantic Ocean are valuable resources for mining bioactive compounds.

Despite recent studies, relatively few are known about the diversity of fungal communities in the deep Atlantic Ocean. In this study, we investigated the diversity of fungal communities in 15 different deep-sea sediments from the South Atlantic Ocean with a culturedependent approach followed by phylogenetic analysis of ITS sequences. A total of 29fungal strains were isolated from the 15 deep-sea sediments. These strains belong to four fungal genera, including Aspergillus, Cladosporium, Penicillium, and Alternaria. Penicillium, accounting for 44.8% of the total fungal isolates, was a dominant genus. The antiaflatoxigenic activity of these deep-sea fungal isolates was studied. Surprisingly, most of the strains showed moderate to strong antiaflatoxigenic activity. Four isolates, belonging to species of Penicillium polonicum, Penicillium chrysogenum, Aspergillus versicolor, and Cladosporium cladosporioides, could completely inhibit not only the mycelial growth of Aspergillus parasiticus mutant strain NFRI-95, but also the aflatoxin production. To our knowledge, this is the first report to investigate the antiaflatoxigenic activity of culturable deep-sea fungi. Our results provide new insights into the community composition of fungi in the deep South Atlantic Ocean. The high proportion of strains that displayed antiaflatoxigenic activity demonstrates that deep-sea fungi from the Atlantic Ocean are valuable resources for mining bioactive compounds.

OBJECTIVE: To explore the integration method and technical realization of artificial intelligence bone age assessment system with the hospital RIS-PACS network and workflow. METHODS: Two sets of artificial intelligence based on bone age assessment systems (CHBoneAI 1.0/2.0) were developed. The intelligent system was further integrated with RIS-PACS based on the http protocol in Python flask web framework. RESULTS: The two sets of systems were successfully integrated into the local network and RIS-PACS in hospital. The deployment has been smoothly running for nearly 3 years. Within the current network setting, it takes less than 3 s to complete bone age assessment for a single patient. CONCLUSIONS The artificial intelligence based bone age assessment system has been deployed in clinical RIS-PACS platform and the "running in parallel", which is marking a success of Stage-I and paving the way to Stage-II where the intelligent systems can evolve to become more powerful in particular of the system self-evolution and the "running alternatively".
Age Determination by Skeleton ; Artificial Intelligence ; Bone and Bones ; Hospital Information Systems ; Hospitals ; Humans ; Radiology Information Systems ; Systems Integration

Objective: To explore the clinical effects of superior gluteal artery perforator island flap in repair of sacral pressure ulcer. Methods: From May 2012 to May 2017, 20 patients with sacral pressure ulcers (14 males and 6 females, aged 27 to 67 years) were admitted to our department. According to the consensus staging system of National Pressure Ulcer Advisory Panel in 2016, 6 cases were in 3 stages, 14 cases were in 4 stages, with the area of pressure ulcers ranging from 5.0 cm×4.0 cm to 10.0 cm×8.0 cm. After debridement and vacuum sealing drainage, the superior gluteal artery perforator island flaps were used to repair the pressure wounds, with the area of flaps ranging from 6 cm×5 cm to 13 cm×8 cm. The donor sites were sutured directly. The survival of flaps after operation, the healing of wounds, and the follow-up of patients were observed. Results: After surgery, flaps of 20 patients survived well without reoperation. The length of hospital stay of patients was 20 to 40 days, with an average of 25 days. Eighteen patients were followed up for 6 to 24 months, with an average of 12.2 months. The flaps were in good shape and elastic recovery. There were no complications such as seroma or hematoma in the donor sites. Both the patients and family members expressed satisfaction with the shape and texture of the flap and shape of hip. Conclusions The superior gluteal artery perforator island flap is reliable in blood supply and easy to rotate. The flap can carry a little muscle to increase the anti-infective ability. Moreover, the donor site can be directly sutured with slight damage. Thus, it is one of the good methods for repairing sacral pressure ulcers.

s] Objective To detect the feasibility and efficiency of bone age(BA) artificial intelligence(AI) estimation based on deep learning features from traditional regions of interest(ROI) in hand digital radiographs(DR). Methods BA dataset of left hand DR with 11 858 subjects aged from 0 to 18 years in Children′s Hospital of Shanghai were split to training(80.0%) and validation (20.0%) set in this study. An improved regression convolutional neural networks and extreme gradient boosting decision tree method were utilized for the BA analysis based on traditional ROIs in the images. Another set of BA data with 1 229 subjects also in the hospital was adopted for test. Mean average precision(mAP) and mean absolute error(MAE) were used to assess model accuracy of detection and BA prediction, respectively. Results The mAP of ROIs detection of the model was 0.91,and MAE of all male and female subjects was 0.461 and 0.431 years respectively in validation and test sets. The difference less than 1 year in test accounted for 90.07% between BA assessment of the model and of the peadiatric radiologists, with an accuracy rate of 96.67%.The difference over 1 year was 9.03% (with underestimation of 6.43% and overestimation of 2.60%), in which corresponding age data was of being less in training set or sesamoid nearby adductor pollicis or fusion of epiphysis appeared in test set. Conclusion An AI model based on deep learning of traditional ROIs′features in hand DR images is initially achieved to automatically predict BA rapidly and effectively, yet it still needs further optimization.

Objective: To detect the feasibility and efficiency of bone age(BA) artificial intelligence(AI) estimation based on deep learning features from traditional regions of interest(ROI) in hand digital radiographs(DR). Methods: BA dataset of left hand DR with 11 858 subjects aged from 0 to 18 years in Children′s Hospital of Shanghai were split to training(80.0%) and validation (20.0%) set in this study. An improved regression convolutional neural networks and extreme gradient boosting decision tree method were utilized for the BA analysis based on traditional ROIs in the images. Another set of BA data with 1 229 subjects also in the hospital was adopted for test. Mean average precision(mAP) and mean absolute error(MAE) were used to assess model accuracy of detection and BA prediction, respectively. Results: The mAP of ROIs detection of the model was 0.91,and MAE of all male and female subjects was 0.461 and 0.431 years respectively in validation and test sets. The difference less than 1 year in test accounted for 90.07% between BA assessment of the model and of the peadiatric radiologists, with an accuracy rate of 96.67%.The difference over 1 year was 9.03% (with underestimation of 6.43% and overestimation of 2.60%), in which corresponding age data was of being less in training set or sesamoid nearby adductor pollicis or fusion of epiphysis appeared in test set. Conclusion An AI model based on deep learning of traditional ROIs′ features in hand DR images is initially achieved to automatically predict BA rapidly and effectively, yet it still needs further optimization.