Objective: To investigate the epidemiological characteristics and spatial-temporal clustering of severe fever with thrombocytopenia syndrome (SFTS) in Huai'an City, Jiangsu Province from 2011 to 2024, so as to provide a basis for optimizing local SFTS prevention and control strategies, and identifying high-risk areas and key populations. Methods: Data on SFTS incidence and deaths in Huai'an City from 2011 to 2024 were collected from the Infectious Disease Reporting Information System of the Chinese Disease Prevention and Control Information System. The reported incidence, mortality, and fatality rates were calculated. Descriptive analysis was performed on temporal, population, and regional distribution. The average annual percent change (AAPC) was used to analyze the trend in the reported incidence of SFTS. Global and local spatial autocorrelation analyses were employed to examine the spatial distribution patterns and spatial association patterns of SFTS incidence while spatio-temporal scanning analyses was used to assess the spatial-temporal clustering of SFTS. Results: A total of 337 SFTS cases were reported in Huai'an City from 2011 to 2024, with the reported incidence rising from 0.17/100 000 to 1.88/100 000. There were 20 deaths, with an average annual mortality of 0.03/100 000, and a fatality rate of 5.93%. The incidence showed obvious seasonality, with a peak in May and June (148 cases, accounting for 43.92%). Spring and summer accounted for 107 cases (31.75%) and 159 cases (47.18%), respectively. The reported SFTS cases were mainly male, farmers, and individuals aged ≥41 years, accounting for 56.38%, 79.23%, and 96.74%, respectively. The population distribution of death cases was basically consistent with that of incident cases. Xuyi County was a high-incidence area, with a total of 332 reported cases, accounting for 98.52%. All death cases were reported in this county. Spatial autocorrelation analyses revealed a positive spatial correlation in SFTS incidence from 2019 to 2024, with Moran's I values ranging from 0.214 to 0.336 (all P<0.05). Heqiao Town, Tianquanhu Town, and Guiwu Town in Xuyi County were identified as high-high clustering areas. Spatio-temporal scanning analyses showed that cluster 1 was consistent with the high-high clustering areas, with an aggregation time from the second quarter of 2019 to the second quarter of 2022. Conclusions From 2011 to 2024, the reported incidence of SFTS in Huai'an City showed an upward trend, with a high incidence in spring and summer. Males, farmers, and the middle-aged and elderly population were the key populations for prevention and control. Xuyi County was the key area for prevention and control.

Objective To analyze the epidemiological characteristics of hepatitis E (HE) in Huai'an City from 2015 to 2024, and construct and validate the prediction effect of the Seasonal Autoregressive Integrated Moving Average (SARIMA) model, and to provide a scientific basis for HE prevention and control. Methods Data of reported HE cases in Huai'an City from January 2015 to December 2024 were extracted from the National Disease Control and Prevention Information System. Descriptive epidemiological methods were used to analyze the temporal, regional and population distribution characteristics of HE incidence. After data preprocessing, stationarity test and randomness test, the SARIMA model was constructed. The optimal model was selected by minimizing the Akaike Information Criterion (AIC). The model performance was evaluated by adjusted R-squared (Adj R²) and root mean square error (RMSE). The monthly incidence rate of HE in Huai'an City in 2025 was predicted and compared with the actual incidence data to validate the model. Results A total of 1 713 HE cases were reported in Huai'an City from 2015 to 2024, showing a fluctuating upward trend. Huaiyin District (339 cases) and Lianshui County (334 cases) were high-incidence areas. The cases were mainly concentrated in people aged 45 and above (83.3%), males (gender ratio 2.37:1) and farmers (70.8%). The optimal model was SARIMA (1,1,1)×(2,0,1)₁₂, with residual as white noise sequence. There was no statistical difference between the actual incidence and predicted value from January to August 2025 (P>0.05). Conclusion HE incidence in Huai'an has obvious aggregation and temporal fluctuation characteristics. The SARIMA model has a good prediction effect, which can provide reference for formulating targeted prevention and control strategies.

Metabolic-bariatric surgery(MBS)has become an important treatment for pathological obesity and metabolic diseases.However,common postoperative nutritional complications—such as protein-energy malnutrition,iron deficiency anemia,and vitamin B12 deficiency—significantly affect patients' long-term prognosis.Traditional nutritional management models rely on static monitoring and standardized supplementation,which are insufficient to address individual variability and dynamic postoperative changes.Artificial intelligence(AI),through integrating multimodal data(such as biochemical indicators,imaging information,and wearable device monitoring)and intelligent modeling,offers new approaches for dynamic monitoring,risk prediction,and personalized intervention.Based on literature from 2017 to 2025,this article systematically evaluates the application of AI in perioperative nutritional management for MBS,covering key technologies including machine learning,deep learning,and natural language processing.It also analyzes current challenges in clinical translation,such as data fragmentation,lack of model interpretability,and limited long-term validation.In the future,enhanced multi-center collaboration,the development of standardized databases,and explainable models will be essential to advancing nutritional management in MBS from empirical practice to precision medicine.

Metabolic-bariatric surgery(MBS)has become an important treatment for pathological obesity and metabolic diseases.However,common postoperative nutritional complications—such as protein-energy malnutrition,iron deficiency anemia,and vitamin B12 deficiency—significantly affect patients' long-term prognosis.Traditional nutritional management models rely on static monitoring and standardized supplementation,which are insufficient to address individual variability and dynamic postoperative changes.Artificial intelligence(AI),through integrating multimodal data(such as biochemical indicators,imaging information,and wearable device monitoring)and intelligent modeling,offers new approaches for dynamic monitoring,risk prediction,and personalized intervention.Based on literature from 2017 to 2025,this article systematically evaluates the application of AI in perioperative nutritional management for MBS,covering key technologies including machine learning,deep learning,and natural language processing.It also analyzes current challenges in clinical translation,such as data fragmentation,lack of model interpretability,and limited long-term validation.In the future,enhanced multi-center collaboration,the development of standardized databases,and explainable models will be essential to advancing nutritional management in MBS from empirical practice to precision medicine.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective:To analyze the efficacy of phantom-less quantitative computer tomography (PL-QCT) for the diagnosis of osteoporosis in patients with lumbar degenerative diseases.Methods:From October 2021 to October 2023, a total of 1 248 patients with lumbar degenerative disease who did not receive anti-osteoporosis treatment in the Department of Spine Surgery, Tianjin Hospital were retrospectively analyzed. There were 520 males and 728 females, aged 62.31±9.37 years (range, 40-87 years), height 1.66±0.08 m (range, 1.43-1.89 m), weight 69.04±8.27 kg (range, 49-93 kg). The mean body mass index was 26.11±3.67 kg/m 2 (range, 14.40-37.11 kg/m 2). Dual-energy X-ray absorptiometry (DXA) and PL-QCT were used to diagnose osteoporosis, and the detection rates of the two diagnostic methods were compared. The receiver operating characteristic (ROC) curve of PL-QCT for the diagnosis of osteoporosis was drawn, the area under the curve (AUC) and 95% confidence interval (CI), sensitivity and specificity were calculated. Results:Among 1 248 patients with lumbar degenerative diseases, 626 (50.2%) were diagnosed as osteoporosis by PL-QCT, 423(33.9%) were diagnosed by spine DXA, 488(39.1%) were diagnosed by hip DXA and 539 patients(43.2%) were diagnosed by dual-site DXA. The detection rate of osteoporosis of PL-QCT was higher than that of spine DXA (χ 2=193.557, P<0.001), hip DXA (χ 2=322.201, P<0.001) and dual-site DXA (χ 2=94.683, P<0.001), and the difference was statistically significant. Taking the diagnostic results of spinal DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 79%, a specificity of 81%, and an AUC and 95% CI of 0.82(0.79, 0.85). Taking the diagnostic results of hip DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 85%, a specificity of 55%, and an AUC and 95% CI of 0.75(0.71, 0.78). Taking the diagnostic results of two-site DXA for osteoporosis as a reference, the ROC curve of PL-QCT for the diagnosis of osteoporosis showed a sensitivity of 72%, a specificity of 75%, and an AUC and 95% CI of 0.81(0.78, 0.83). Conclusion:Compared with DXA, PL-QCT has a higher detection rate of osteoporosis in patients with degenerative lumbar spine disease and good diagnostic efficacy.

Objective:To investigate the clinical efficacy of lumbar lateral interbody fusion (LLIF) versus posterior lumbar interbody fusion (PLIF) in the treatment of severe lumbar spinal stenosis.Methods:The data of patients with severe lumbar spinal stenosis who underwent LLIF or PLIF from February 2019 to December 2023 were retrospectively analyzed. There were 30 patients in the LLIF group, 10 males and 20 females, aged 62.7±5.6 years (range, 53-74 years), including 21 cases of single segment and 9 cases of double segment. There were 46 patients in the PLIF group, including 20 males and 26 females, aged 63.2±8.4 years (range, 43-75 years), 40 cases of single segment and 6 cases of double segment. The visual analogue scale (VAS), Oswestry disability index (ODI), intervertebral space height, intervertebral foramen height and postoperative complications were compared between the two groups.Results:All patients were followed up for an average of 21.3±6.4 months (range, 12-32 months). The intraoperative blood loss in the LLIF group was 112.2±76.9 ml, which was significantly lower than 193.9±88.2 ml in the PLIF group ( P<0.05). The VAS scores of back pain and leg pain after operation were significantly lower than those before operation in the two groups ( P<0.05). There was no statistically significant difference between groups in back pain VAS scores at preoperative, 6 months postoperative, and final follow-up ( P>0.05); the back pain VAS score at 1 month postoperatively in the LLIF group was 1.6±1.2, which was less than 2.8±0.7 in the PLIF group ( P<0.05). There was no statistically significant difference between groups in leg pain VAS scores at preoperative, 1 month postoperative, and 6 months postoperative ( P>0.05); the leg pain VAS score at the final follow-up in the LLIF group was 1.2±1.5, which was smaller than 1.8±1.0 in the PLIF group ( P<0.05). The postoperative ODI was smaller than the preoperative one in both groups, and the difference was statistically significant ( P<0.05); the preoperative, 1-month postoperative, 6-month postoperative, and final follow-up ODIs in the LLIF group were 45.7%±16.0%, 17.9%±12.0%, 16.2%±11.6%, and 15.7%±11.7%, and those in the PLIF group were 47.9%±15.4%, 20.1%±9.3%, 16.9%±10.6%, and 14.6%±11.0% in the PLIF group, and the difference between the groups was not statistically significant ( P>0.05). The preoperative intervertebral space height in the LLIF group was 10.6±2.0 mm, which was smaller than that in the PLIF group 11.8±2.2 mm ( P<0.05). The intervertebral space heights in the immediate postoperative period and at the final follow-up were 13.3±2.3 mm and 12.3±2.2 mm in the LLIF group and 13.7±1.7 mm and 13.0±1.9 mm in the PLIF group ( P>0.05). The preoperative intervertebral foraminal height in the LLIF group was 18.0±3.2 mm, which was smaller than that of 19.7±2.4 mm in the PLIF group ( P<0.05); the intervertebral foraminal heights in the immediate postoperative period and at the final follow-up were 21.4±2.5 mm and 20.2±2.4 mm in the LLIF group, and in the PLIF group were 20.7±2.4 mm and 19.7±2.6 mm in the PLIF group ( P>0.05). In the LLIF group, 2 cases had femoral nerve injury and 2 cases had transient back pain after operation. There were 2 cases of cerebrospinal fluid leakage, 1 case of screw loosening, and 2 cases of deep vein thrombosis in the PLIF group. In the PLIF group, 2 patients underwent revision, including 1 case due to cage displacement and 1 case due to screw malposition. The fusion settling rate was 21% (8/39) in the LLIF group and 12% (6/52) in the PLIF group ( P>0.05). Conclusion:Both LLIF and PLIF can effectively restore the intervertebral height, improve the lumbar function and the symptoms of back and leg pain in the treatment of severe lumbar spinal stenosis.

Objective:To investigate the risk factors for complications following lateral lumbar interbody fusion (LLIF) surgery.Methods:A retrospective analysis was conducted on 196 patients who underwent LLIF surgery via the psoas major muscle approach in the Department of Spinal Surgery, Tianjin Hospital, Tianjin University, from October 2018 to July 2024. The age, gender, body mass index (BMI), presence of hypertension, type 2 diabetes, heart disease, osteoporosis, history of lumbar surgery, history of abdominal surgery, history of abdominal inflammation, smoking status, operative time, surgical segments (whether the surgery was single-segment or multi-segments), and use of internal fixation or not were compared between patients with and without postoperative complications, the indicators with P<0.10 were included in the binary variable logistic regression analysis, and determine the independent risk factors for complications after LLIF surgery. Complications included anterior thigh symptoms (pain, numbness, weakness), cage subsidence, surgery-related complications (nerve injury, surgical site infection, postoperative buttock pain, urinary and fecal incontinence, etc.), and medical complications (cerebrovascular accident, deep vein thrombosis, urinary tract infection, etc.). Results:All 196 patients were followed up for 27.02 (12.6, 40.69) months. Postoperative complications occurred in 71 cases (96 times), and no complications occurred in 125 cases. In the complication group, there were 15 males and 56 females with a mean age of 61.82±7.57 years; in the non-complication group, there were 43 males and 82 females with a mean age of 62.00± 8.39 years. In the complication group, there were 43 cases of anterior thigh symptoms, 38 cases of cage subsidence, 11 cases of surgical operation-related complications, and 4 cases of medical complications. There were statistically significant differences in gender (χ 2=3.829, P=0.051), operation time ( t=2.391, P=0.018), and surgical segment (χ 2=4.245, P=0.039) between the complication group and the non-complication group. No statistically significant differences were found in age, gender, BMI, presence of hypertension, type 2 diabetes, heart disease, osteoporosis, history of lumbar surgery, history of abdominal surgery, history of abdominal inflammation, smoking status, or use of internal fixation ( P>0.10). Binary variable logistic regression analysis indicated that prolonged operative time [ OR=1.007, 95% CI(1.001, 1.013), P=0.019] and multilevel surgery [ OR=2.099, 95% CI(1.095, 4.025), P=0.026] were independent risk factors for complications following LLIF. Conclusion:Prolonged operative time and multi-segments surgery are independent risk factors for complications following LLIF.

BACKGROUND:How to effectively promote bone regeneration and bone reconstruction after bone injury has always been a key issue in clinical bone repair research.The use of biological and degradable materials loaded with bioactive factors to treat bone defects has excellent application prospects in bone repair. OBJECTIVE:To investigate the effect of polylactic acid-glycolic acid copolymer(PLGA)composite scaffold modified by lysine-grafted graphene oxide nanoparticles(LGA-g-GO)on osteogenic differentiation and new bone formation. METHODS:PLGA was dissolved in dichloromethane and PLGA scaffold was prepared by solvent evaporation method.PLGA/GO composite scaffolds were prepared by dispersing graphene oxide uniformly in PLGA solution.LGA-g-GO nanoparticles were prepared by chemical grafting method,and the PLGA/LGA-g-GO composite scaffolds were constructed by blending LGA-g-GO nanoparticles at different mass ratios(1%,2%,and 3%)with PLGA.The micromorphology,hydrophilicity,and protein adsorption capacity of scaffolds of five groups were characterized.MC3T3 cells were inoculated on the surface of scaffolds of five groups to detect cell proliferation and osteogenic differentiation. RESULTS AND CONCLUSION:(1)The surface of PLGA scaffolds was smooth and flat under scanning electron microscope,while the surface of the other four scaffolds was rough.The surface roughness of the composite scaffolds increased with the increase of the addition of LGA-g-GO nanoparticles.The water contact angle of PLGA/LGA-g-GO(3%)composite scaffolds was lower than that of the other four groups(P<0.05).The protein adsorption capacity of PLGA/LGA-g-GO(1%,2%,and 3%)composite scaffolds was stronger than PLGA and PLGA/GO scaffolds(P<0.05).(2)CCK-8 assay showed that PLGA/LGA-g-GO(2%,3%)composite scaffold could promote the proliferation of MC3T3 cells.Alkaline phosphatase staining and alizarin red staining showed that the cell alkaline phosphatase activity in PLGA/LGA-g-GO(2%,3%)group was higher than that in the other three groups(P<0.05).The calcium deposition in the PLGA/GO and PLGA/LGA-g-GO(1%,2%,and 3%)groups was higher than that in the PLGA group(P<0.05).(3)In summary,PLGA/LGA-g-GO composite scaffold can promote the proliferation and osteogenic differentiation of osteoblasts,and is conducive to bone regeneration and bone reconstruction after bone injury.

Coronary atherosclerotic heart disease is a major cardiovascular condition driven by atherosclerosis, distinguished by chronic inflammation and dysregulated lipid metabolism. The gut microbiota plays an essential role in human health and disease, with research indicating a strong association between gut microbial metabolism and the development and progression of coronary heart disease. This article provides a review of the relationship between gut microbiota and coronary heart disease, as well as the mechanisms by which traditional Chinese medicine regulates digestive tract microbiota to treat coronary heart disease, which systematically explains how the gut microbiota, through metabolic products and immune regulation, contributes to the occurrence and progression of coronary heart disease, and summarizes recent advances in research on traditional Chinese medicine's regulation of gut microbiota for treating coronary heart disease. It aims to provide further reference and insights for exploring the relationship between gut microbiota and coronary heart disease, as well as traditional Chinese medicine approaches for treating coronary heart disease.