Objective: To compare the predictive performance of the seasonal autoregressive integrated moving average (SARIMA) model, the Prophet model, and the Bayesian structural time series (BSTS) model in forecasting the incidence of hand, foot, and mouth disease (HFMD) , so as to provide a basis for optimizing the early warning system of this disease. Methods: Weekly incidence data of HFMD in Longgang District, Shenzhen City from 2014 to 2024 were collected. The HFMD incidence data from 2014-2019 and 2023 were used as the training set to construct SARIMA, Prophet, and BSTS models, while the data from 2024 were used as the test set to compare and evaluate the predictive performance of the three models. The technique for order preference by similarity to ideal solution (TOPSIS) method was employed to calculate the C-value. This approach integrates multiple evaluation metrics, such as the mean absolute error (MAE), mean squared error (MSE), root mean squared error (RMSE), and symmetric mean absolute percentage error (SMAPE), to comprehensively assess model performance. Results: A total of 150 111 cases of HFMD were reported in Longgang District from 2014 to 2024, with an average annual incidence of 400.72/105. The weekly incidence fluctuated between 0 and 63.78/105, exhibiting a bimodal seasonal pattern characterized by a primary peak from May to July and a secondary peak from September to October. In the training set, all three models demonstrated a good fit to the bimodal epidemic trend of HFMD, with the BSTS model achieving the best fit. The BSTS model yielded performance metrics as follows: MAE=0.124, MSE=0.050, RMSE=0.223, SMAPE=0.021, and a C-value of 1.000. In the test set, all three models, including SARIMA, Prophet, and BSTS, performed well for short-term predictions (≤16 weeks), with the Prophet model showing relatively superior predictive performance. However, the prediction accuracy of all models declined as the forecast horizon extended. During the primary peak period (May-July), the Prophet model exhibited better predictive performance, whereas the BSTS model performed relatively better during the secondary peak period (September-October). Conclusions For the short-term forecasting of weekly HFMD incidence, the Prophet model outperformed both the SARIMA and BSTS models. During the primary peak period, the Prophet model demonstrated superior predictive performance, whereas the BSTS model exhibited better accuracy in forecasting the secondary peak period.

Autoimmune hepatitis （AIH） is a chronic inflammatory liver disease. The pathogenesis of AIH remains unclear， but it is mainly autoimmune injury caused by the breakdown of autoimmune tolerance due to the abnormal activation of the immune system， while the specific molecular mechanism remains unknown. Recent studies have shown that abnormal amino acid metabolism plays an important role in the development and progression of AIH. This article reviews the research advances in amino acid metabolic reprogramming in AIH， in order to provide a theoretical basis for amino acid metabolism as a new target for the clinical diagnosis and treatment of AIH.

The production of high-quality oocytes requires precisely orchestrated intercellular communication. Extracellular vesicles (EVs) are cell-derived nanoparticles that play a vital role in the transfer of bioactive molecules, which has gained much attention in the field of diagnosis and treatment. Over the past ten years, the participation of EVs in the reproductive processes of oocytes has been broadly studied and has shown great potential for elucidating the intricacies of female reproductive health. This review provides an extensive discussion of the influence of EVs on oocytes, emphasizing their involvement in normal physiology and altered cargo under pathological conditions. In addition, the positive impact of therapeutic EVs on oocyte quality and their role in alleviating ovarian pathological conditions are summarized.
Humans ; Extracellular Vesicles/physiology* ; Oocytes/cytology* ; Female ; Animals ; Cell Communication/physiology*

Musculoskeletal disorders (MSDs) are characterized by extensive pathological involvement and high prevalence and cause a significant disease burden. Long-term drug administration often causes by adverse effects with poor therapeutic efficacy. Low-intensity pulsed ultrasound (LIPUS), as a specialized therapeutic modality, delivers acoustic energy at a low intensity in a pulsed wave mode, thus ensuring stable energy transmission to the target tissues while minimizing thermal effects. This non-invasive approach has demonstrated significant potential for MSD treatment by delivering effective physical stimulations. Extensive animal and clinical studies have demonstrated the efficacy of LIPUS for accelerating the healing process of fresh fractures and nonunions, promoting soft tissue regeneration and suppressing inflammatory responses. Emerging evidence suggests promising applications of LIPUS in skeletal muscle injury treatment and promoting tissue regeneration and repair. This review outlines the recent advancements and mechanistic studies of LIPUS for treatment of common MSDs including fractures, nonunions, muscle injuries, and osteoarthritis, addressing also the technical parameters of commercially available LIPUS devices, current therapeutic approaches, the existing challenges, and future research directions.
Humans ; Ultrasonic Therapy/methods* ; Musculoskeletal Diseases/therapy* ; Ultrasonic Waves ; Osteoarthritis/therapy* ; Muscle, Skeletal/injuries*

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

OBJECTIVE: To investigate the predictive value of sphinor kinase 1 (sphk1), D-lactic acid, and intestinal fatty acid binding protein (I-FABP) for gastrointestinal injury in patients with sepsis. METHODS: A prospective observational study was conducted. Sixty-eight patients with sepsis and gastrointestinal dysfunction admitted to the department of critical care medicine of the First Affiliated Hospital of Baotou Medical College Inner Mongolia University of Science and Technology from May 2024 to March 2025 were enrolled (sepsis group), and they were divided into acute gastrointestinal injury (AGI) I-IV groups according to the definition and grading criteria of AGI proposed by the European Society of Intensive Care Medicine in 2012. Twenty non-sepsis patients without AGI admitted to the intensive care unit during the same period were enrolled as the control group (non-sepsis group). Within 30 minutes of patient enrollment, plasma sphk1, D-lactic acid, and I-FABP levels were determined by enzyme linked immunosorbent assay (ELISA). General data such as gender, age were recorded, and levels of procalcitonin (PCT), high-sensitivity C-reactive protein (hs-CRP), lactic acid (Lac), and acute physiology and chronic health evaluation II (APACHEII), sequential organ failure assessment (SOFA) were measured. Spearman method was used to analyze the correlation between sphk1, I-FABP, D-lactic acid and other indicators. The receiver operator characteristic curve (ROC curve) was used to evaluate the predictive value of sphk1, D-lactic acid, I-FABP, APACHEII score, and SOFA score for gastrointestinal injury in patients with sepsis. RESULTS: Among the 68 sepsis patients, 13 were classified as AGI grade I, 16 as AGI grade II, 23 as AGI grade III, and 16 had AGI grade IV. There were no statistically significant differences in gender, age, and abdominal infection rate among the groups. The SOFA score and APACHEII score of the sepsis group were significantly higher than those of the non-sepsis group; and the APACHEII score of the AGI IV group was significantly higher than that of the AGI I and AGI II groups. The levels of sphk1, D-lactic acid, I-FABP, PCT, Lac and hs-CRP in the sepsis group were significantly higher than those in the non-sepsis group, and each indicator gradually increased with the increase of AGI grade. Correlation analysis showed that plasma sphk1, D-lactic acid, and I-FABP in patients with sepsis-induced gastrointestinal injury were positively correlated with PCT, Lac, APACHEII score, and AGI grade (all P < 0.05), and sphk1 was positively correlated with I-FABP and D-lactic acid (r values were 0.773 and 0.782, respectively, both P < 0.05). ROC curve analysis showed that sphk1, D-lactic acid, I-FABP, APACHEII score, and SOFA score had high predictive value for gastrointestinal injury in patients with sepsis, with area under the curve (AUC) of 0.996, 0.987, 0.976, 0.901, and 0.934 (all P < 0.05). When the optimal cut-off value of sphk1 was 60.46 ng/L, the sensitivity and specificity were 95.6% and 100%, respectively; when the optimal cut-off value of D-lactic acid was 1 454.3 μg/L, the sensitivity and specificity were 95.6% and 100%, respectively; when the optimal cut-off value of I-FABP was 0.91 ng/L, the sensitivity and specificity were 95.6% and 100%, respectively; when the optimal cut-off value of APACHEII score was 14.5, the sensitivity and specificity were 80.9% and 85.0%, respectively; when the optimal cut-off value of SOFA score was 3.5, the sensitivity and specificity were 85.3% and 95.0%, respectively. CONCLUSIONS The levels of plasma sphk1, I-FABP, and D-lactic acid were significantly elevated in patients with sepsis and gastrointestinal injury. These indicators can serve as sensitive and relatively specific serological markers for early prediction of intestinal mucosal damage.
Humans ; Lactic Acid/blood* ; Fatty Acid-Binding Proteins/blood* ; Sepsis/complications* ; Prospective Studies ; Male ; Female ; Middle Aged ; Predictive Value of Tests ; Adult ; Aged ; Gastrointestinal Diseases/blood* ; Prognosis

Advanced gastric cancer(AGC)includes locally unresectable gastric cancer(GC),metastatic GC,and postoperative recurrent GC.Due to delayed diagnosis and lack of effective treatment for AGC,the median survival time of AGC patients is only 6-12 months.At present,the main treatment goal of AGC is to improve symptoms and prolong the survival time of patients receiving sequential chemotherapy.Although the therapeutic effect of systemic therapy on AGC is gradually becoming apparent,the patient's prognosis is far from expected.In addition,targeted therapy and novel immunotherapy have drawbacks such as high incidence of drug resistance,high toxic side effects,and heavy economic burden on patients.Therefore,finding new therapeutic targets and developing anti-tumor drugs is a key issue that urgently needs to be addressed.According to reports,abnormal activation of the hepatocyte growth factor(HGF)/cellular-mesenchymal epithelial transition factor(c-MET)pathway plays a crucial role in the progression of GC and the occurrence of multi-line resistance and may be a potential therapeutic target for GC.In recent years,some HGF/c-MET-targeting small molecule tyrosine kinase inhibitors(TKIs)have been found to show good clinical effects in the treatment of GC.Meanwhile,new HGF/c-MET inhibitors(such as monoclonal antibodies,bispecific antibodies,antibody drug conjugates,etc.)have shown good anti-tumor activity in preclinical studies,but they are all at different stages of clinical research,and their efficacy and safety still need further confirmation.This review elaborates on the latest research progress of HGF/c-MET inhibitors in the treatment of AGC and discusses the main reasons and strategies for drug resistance,aiming to provide better guidance for the treatment of AGC and provide reference for future research.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.