ObjectiveTo investigate the awareness and clinical practice of guidelines for the prevention and treatment of chronic hepatitis B （2022 edition） among clinicians. MethodsFrom July 19 to December 31， 2024， a self-designed electronic questionnaire was distributed via the WeChat mini program to collect related data from 1 588 clinicians nationwide， including their awareness and practice based on 18 questions regarding testing and referral， diagnosis and treatment， and follow-up. ResultsAmong all respondents， only 350 clinicians correctly understood all the updated key points of antiviral indications and treatment for special populations in the 2022 edition of guidelines for the prevention and treatment of chronic hepatitis B， with an overall awareness rate of 22.0%. Only 20% ‍—‍ ‍40% of the patients with positive HBV DNA and an age of >30 years receive antiviral therapy， while 80% ‍—‍ ‍100% of the patients with positive HBV DNA and a family history of hepatitis B cirrhosis or hepatocellular carcinoma receive antiviral therapy. The median follow-up rates at 1 year， 3 years， and 5 years were 67.5% 57.5% and 47.5%，respectively， showing a trend of gradual reduction， which might be associated with the influencing factors such as insufficient time for follow-up management by clinicians， insufficient awareness of the disease among patients， and poor adherence to follow-up. ConclusionThere is a gap between the awareness and practice of guidelines for the prevention and treatment of chronic hepatitis B （2022 edition） among clinicians. It is recommended to further strengthen training and focus on the whole process of “detection， diagnosis， treatment， and management” for patients with chronic hepatitis B in healthcare institutions， in order to promote the implementation of the guidelines.

Objective To analyze the metabolomics characteristics of chronic atrophic gastritis(CAG)patients with liver-stomach qi stagnation and spleen-stomach weakness syndromes based on non-targeted metabolomics technology,and to identify the serum differentiated metabolites related to traditional Chinese medicine(TCM)syndrome of CAG patients,so as to provide a reference for the objectification of syndrome differentiation.Methods Sixty patients with CAG were included,including 30 cases of liver-stomach qi stagnation syndrome and 30 cases of spleen-stomach weakness syndrome.Fasting blood of 5 mL was collected from the cubital vein of patients in the two groups,and the serum levels of metabolites were detected by ultra-high-performance liquid chromatography-mass spectrometry(UPLC-MS)methods.The principal component analysis(PCA),orthogonal partial least squares-discriminant analysis(OPLS-DA),and cluster analysis were used to screen the differentiated metabolites of CAG patients with liver-stomach qi stagnation syndrome and spleen-stomach weakness syndrome.Finally,metabolite pathway analysis was performed for the obtained differentiated metabolites using the KEGG database.Results The results for the screening of differentiated metabolites showed that significant differences of amino acid derivatives and small peptide metabolites were presented between CAG patients with liver-stomach qi stagnation syndrome and CAG patients with spleen-stomach weakness syndrome.The amino acid derivatives consisted of N-acetylglycine,histamine,O-phosphoserine,selenomethylselenocysteine,and methyl-tyrosine.And the small peptide metabolites consisted of tyrosine-leucine-phenylalanine,histidine-alanine-glutamate-lysine,L-asparagine-L-proline-L-serine,and L-isoleucine-L-isoleucine.Conclusion Differences in amino acid metabolism exist between CAG patients with liver-stomach qi stagnation syndrome and those with spleen-stomach weakness syndrome,and metabolites such as N-acetylglycine,intermethyltyrosine,and O-phosphoserine may be the potential biomarkers for distinguishing liver-stomach qi stagnation syndrome from spleen-stomach weakness syndrome in CAG patients.

BACKGROUND:MRI is important for the diagnosis of early knee osteoarthritis.MRI image recognition and intelligent segmentation of knee osteoarthritis using deep learning method is a hot topic in image diagnosis of artificial intelligence. OBJECTIVE:Through deep learning of MRI images of knee osteoarthritis,the segmentation of femur,tibia,patella,cartilage,meniscus,ligaments,muscles and effusion of knee can be automatically divided,and then volume of knee fluid and muscle content were measured. METHODS:100 normal knee joints and 100 knee osteoarthritis patients were selected and randomly divided into training dataset(n=160),validation dataset(n=20),and test dataset(n=20)according to the ratio of 8:1:1.The Coarse-to-Fine sequential training method was used to train the 3D-UNET network deep learning model.A Coarse MRI segmentation model of the knee sagittal plane was trained first,and the rough segmentation results were used as a mask,and then the fine segmentation model was trained.The T1WI and T2WI images of the sagittal surface of the knee joint and the marking files of each structure were input,and DeepLab v3 was used to segment bone,cartilage,ligament,meniscus,muscle,and effusion of knee,and 3D reconstruction was finally displayed and automatic measurement results(muscle content and volume of knee fluid)were displayed to complete the deep learning application program.The MRI data of 26 normal subjects and 38 patients with knee osteoarthritis were screened for validation. RESULTS AND CONCLUSION:(1)The 26 normal subjects were selected,including 13 females and 13 males,with a mean age of(34.88±11.75)years old.The mean muscle content of the knee joint was(1 051 322.94±2 007 249.00)mL,the mean median was 631 165.21 mL,and the mean volume of effusion was(291.85±559.59)mL.The mean median was 0 mL.(2)There were 38 patients with knee osteoarthritis,including 30 females and 8 males.The mean age was(68.53±9.87)years old.The mean muscle content was(782 409.18±331 392.56)mL,the mean median was 689 105.66 mL,and the mean volume of effusion was(1 625.23±5 014.03)mL.The mean median was 178.72 mL.(3)There was no significant difference in muscle content between normal people and knee osteoarthritis patients.The volume of effusion in patients with knee osteoarthritis was higher than that in normal subjects,and the difference was significant(P<0.05).(4)It is indicated that the intelligent segmentation of MRI images by deep learning can discard the defects of manual segmentation in the past.The more accuracy evaluation of knee osteoarthritis was necessary,and the image segmentation was processed more precisely in the future to improve the accuracy of the results.

Objective To evaluate the efficacy and safety of brexpiprazole in treating acute schizophrenia.Methods Patients with schizophrenia were randomly divided into treatment group and control group.The treatment group was given brexpiprozole 2-4 mg·d-1 orally and the control group was given aripiprazole 10-20 mg·d-1orally,both were treated for 6 weeks.Clinical efficacy of the two groups,the response rate at endpoint,the changes from baseline to endpoint of Positive and Negative Syndrome Scale(PANSS),Clinical Global Impression-Improvement(CGI-S),Personal and Social Performance scale(PSP),PANSS Positive syndrome subscale,PANSS negative syndrome subscale were compared.The incidence of treatment-related adverse events in two groups were compared.Results There were 184 patients in treatment group and 186 patients in control group.After treatment,the response rates of treatment group and control group were 79.50％(140 cases/184 cases)and 82.40％(150 cases/186 cases),the scores of CGI-I of treatment group and control group were(2.00±1.20)and(1.90±1.01),with no significant difference(all P＞0.05).From baseline to Week 6,the mean change of PANSS total score wese(-30.70±16.96)points in treatment group and(-32.20±17.00)points in control group,with no significant difference(P＞0.05).The changes of CGI-S scores in treatment group and control group were(-2.00±1.27)and(-1.90±1.22)points,PSP scores were(18.80±14.77)and(19.20±14.55)points,PANSS positive syndrome scores were(-10.30±5.93)and(-10.80±5.81)points,PANSS negative syndrome scores were(-6.80±5.98)and(-7.30±5.15)points,with no significant difference(P＞0.05).There was no significant difference in the incidence of treatment-related adverse events between the two group(69.00％vs.64.50％,P＞0.05).Conclusion The non-inferiority of Brexpiprazole to aripiprazole was established,with comparable efficacy and acceptability.

Objective To investigate the effects of Astragalus polysaccharides(HPS)on farnitol X receptor(FXR)-small heterodimer chaperone receptor(SHP)signaling pathway and key proteins of glucose and lipid metabolism in diabetic rats.Methods Twelve male Wistar rats were randomly selected as blank group,and the remaining 60 rats were fed with a one-time intrabitoneal injection of streptozotocin(STZ,50 mg·kg-1)combined with a high-sugar and high-fat diet to replicate the diabetic rat model.The model rats were randomly divided into model group,positive control group(400 mg·kg-1·d-1 Bifidobacterium quadruple viable bacterial tablet suspension),experimental-H,-M,-L groups(200,100 and 50 mg·kg-1·d-1 HPS suspension),respectively.Blank group and model group were given equal volume of pure water once a day for 8 weeks.Blood glucose(Glu)was measured before and after gavage.Real-time fluorescent polymerase chain reaction(RT-PCR),Western blot were used to detect the mRNA and protein expression level of FXR,SHP,antiperoxisomal proliferator-activated receptor α(PPARα),antiphosphoenolpyruvate carboxylkinase(PEPCK),sterol regulatory receptor binding protein-1c(SREBP-1c),glucose 6 phosphatase(G6Pase).Results Glu levels in normal group,model group,positive control group and experimental-H group after treatment were(7.66±0.61),(29.25±1.64),(23.31±3.02),(19.31±5.13)mmol·L-1,respectively;the relative expression levels of FXR mRNA in liver tissues were 1.00±0.04,0.44±0.03,0.61±0.06,0.87±0.03,respectively;the relative expression levels of SHP mRNA were 1.00±0.04,0.40±0.01,0.67±0.01,0.67±0.02;the relative expression levels of G6Pase mRNA in liver tissues were 1.00±0.06,3.00±0.08,1.87±0.03,1.44±0.05,respectively;the relative expression levels of PEPCK mRNA in liver tissues were 1.00±0.04,1.88±0.03,1.31±0.02,1.23±0.04,respectively;the relative expression levels of SREBP-1c mRNA in liver tissues were 1.00±0.04,1.90±0.01,1.26±0.03,1.06±0.04;the relative expression levels of PPARα mRNA in liver tissues were 1.00±0.02,0.16±0.01,0.45±0.01,0.96±0.03,respectively.Compared with blank group,positive control group and experimental-H group,there were statistically significant differences in the above indexes between model group and blank group(all P＜0.01).The protein expression trend of FXR,SHP,G6Pase,PEPCK,SREBP-1c,PPARα was consistent with mRNA expression.Conclusion HPS may regulate FXR-SHP signaling pathway in liver tissue,inhibit the expression of key proteins of glucose and lipid metabolism,promote lipid oxidation,improve Glu and protect liver tissue in diabetic rats.

Objective Viral encephalitis is an infectious disease severely affecting human health.It is caused by a wide variety of viral pathogens,including herpes viruses,flaviviruses,enteroviruses,and other viruses.The laboratory diagnosis of viral encephalitis is a worldwide challenge.Recently,high-throughput sequencing technology has provided new tools for diagnosing central nervous system infections.Thus,In this study,we established a multipathogen detection platform for viral encephalitis based on amplicon sequencing. Methods We designed nine pairs of specific polymerase chain reaction(PCR)primers for the 12 viruses by reviewing the relevant literature.The detection ability of the primers was verified by software simulation and the detection of known positive samples.Amplicon sequencing was used to validate the samples,and consistency was compared with Sanger sequencing. Results The results showed that the target sequences of various pathogens were obtained at a coverage depth level greater than 20×,and the sequence lengths were consistent with the sizes of the predicted amplicons.The sequences were verified using the National Center for Biotechnology Information BLAST,and all results were consistent with the results of Sanger sequencing. Conclusion Amplicon-based high-throughput sequencing technology is feasible as a supplementary method for the pathogenic detection of viral encephalitis.It is also a useful tool for the high-volume screening of clinical samples.

Objective:To explore the clinical characteristics and outcomes of type 2 autoimmune pancreatitis (AIP) and compare with type 1 AIP.Methods:Clinical data of the patients diagnosed with type 2 AIP by the International Consensus on diagnostic criteria of AIP at Peking Union Medical College Hospital from January 2001 to December 2022 were retrospectively analyzed, and type 1 AIP patients diagnosed in Peking Union Medical College Hospital from January 1985 to December 2016 were collected as controls. The clinical symptoms, treatments and follow-ups were analyzed.Results:A total of 25 patients with type 2 AIP were included, of which 16 cases (64.0%) were pathologically confirmed cases (13 cases by endoscopic ultrasound puncture, 2 cases by surgery, and 1 case by interventional puncture), and 9 cases (36.0%) were suspected. The average age of onset was 40 years old. Most patients ( n=23, 92.0%) had abdominal pain along with emaciation to a various degree. Among them, 3 cases primarily presented as acute pancreatitis. Two cases were diagnosed after surgery for pancreatic masses. Eighteen cases were complicated with inflammatory bowel disease, including 16 cases with ulcerative colitis, one case with Crohn's disease, and one case with indeterminate colitis. All patients had typical imaging manifestations, including 13 cases (52.0%) with diffuse pancreatic enlargement, 12 cases (48.0%) with focal or multifocal pancreatic lesions, and 5 cases (20.0%) with simultaneous focal pancreatic masses and diffuse enlargement. All patients had normal serum IgG4 levels, anti-neutropil cytoplasmic antibodies (ANCA) positivity rate was 35.3% (6/17), and anti-nuclear antibody (ANA) positivity rate was 29.2% (7/24). Two surgical patients recovered well after surgery, and the other patients all achieved clinical and imaging relief after hormone therapy, and no recurrence was seen during follow-up. Compared with type 1 AIP, type 2 AIP had younger onset age, main manifestation as abdominal pain without jaundice, rare involvement with extra-pancreatic organs, the lesions mainly located in the intestine and normal IgG4 level with statistically significant differences. The recurrence rate of type 2 AIP was lower than that of type 1 AIP (0 vs 16%). Conclusions:Type 2 AIP has different clinical characteristics from type 1 AIP. Due to the lack of specific serum markers, the diagnosis is more difficult. It responds well to glucocorticoids and has a low recurrence rate.

The breakthrough progress of implantable brain-computer interfaces (iBCIs) technology in the field of clinical trials has attracted widespread attention from both academia and industry. The development and advancement of this technology have provided new solutions for the rehabilitation of patients with movement disorders. However, challenges from many aspects make it difficult for iBCIs to further implement and transform technologies. This paper illustrates the key challenges restricting the large-scale development of iBCIs from the perspective of system implementation, then discusses the latest clinical application progress in depth, aiming to provide new ideas for researchers. For the system implementation part, we have elaborated the front-end signal collector, signal processing and decoder, then the effector. The most important part of the front-end module is the neural electrode, which can be divided into two types: piercing and attached. These two types of electrodes are newly classified and described. In the signal processing and decoder section, we have discussed the experimental paradigm together with signal processing and decoder for the first time and believed that the experimental paradigm acts as a learning benchmark for decoders that play a pivotal role in iBCIs systems. In addition, the characteristics and roles of the effectors commonly used in iBCIs systems, including cursors and robotic arms, are analyzed in detail. In the clinical progress section, we have divided the latest clinical progress into two categories: functional rehabilitation and functional replacement from the perspective of the application scenarios of iBCIs. Functional rehabilitation and functional replacement are two different types of application, though the boundary between the two is not absolute. To this end, we have first introduced the corresponding clinical trial progress from the three levels: application field, research team, and clinical timeline, and then conducted an in-depth discussion and analysis of their functional boundaries, in order to provide guidance for future research. Finally, this paper mentions that the key technical challenges in the development of iBCIs technology come from multiple aspects. First of all, from the signal acquisition level, high-throughput and highly bio-compatible neural interface designing is essential to ensure long-term stable signal acquisition. The electrode surface modification method and electrode packaging were discussed. Secondly, in terms of decoding performance, real-time, accurate, and robust algorithms have a decisive impact on improving the reliability of iBCIs systems. The third key technology is from the perspective of practicality, we believe that the signal transmission mode of wireless communication is the trend of the future, but it still needs to overcome challenges such as data transmission rate and battery life. Finally, we believe that issues such as ethics, privacy, and security need to be addressed through legal, policy, and technological innovation. In summary, the development of iBCIs technology requires not only the unremitting efforts of scientific researchers, but also the participation and support of policymakers, medical professionals, technology developers, and all sectors of society. Through interdisciplinary collaboration and innovation, iBCIs technology will achieve wider clinical applications in the future and make important contributions to improving the quality of life of patients.

Objective To observe the therapeutic effect and mechanism of Guhuaisi Kangfu Pills on rats with steroid-induced osteonecrosis of the femoral head(SONFH).Methods Sixty rats were randomly divided into blank group,model group,Xianling Gubao Capsules group and Guhuaisi Kangfu Pills low-,medium-and high-dose groups,10 rats in each group.Except for the blank group,the SONFH model was established by lipopolysaccharide combined with Glucocorticoid induction method in all other groups of rats.At the end of the intervention,for the femoral head,blood vessel radiography was performed to observe the microvascular changes in the bone marrow,and hematoxylin-eosin(HE)staining and calculation of the empty bone trap rate,Micro-CT scanning analysis,and compression experiments were carried out,and the real-time quantitative polymerase chain reaction(RT-qPCR)was used to detect the gene expressions of phosphatidylinositol 3-kinase(PI3K),protein kinase B(Akt)1,vascular endothelial growth factor(VEGF)and platelet endothelial cell adhesion molecule 1(CD31)in whole blood.Results Compared with the blank group,the blood supply in the femoral head medullary cavity of the model group was poor,the empty bone lacuna rate was increased(P＜0.05),the bone mineral density and bone volume fraction were significantly decreased(P＜0.05),the maximum load and elastic modulus of the femoral head were decreased(P＜0.05),and the mRNA expression levels of Akt1,PI3K,VEGF and CD31 in whole blood were decreased(P＜0.05).Compared with the model group,the blood supply in the femoral head medullary cavity was relatively good,the empty bone lacuna rate was decreased(P＜0.05),the bone mineral density,bone volume fraction,trabecular number and trabecular thickness were significantly increased(P＜0.05),the trabecular separation was significantly decreased(P＜0.05),the maximum load and elastic modulus of the femoral head were increased(P＜0.05),and the mRNA expression levels of Akt1,PI3K,VEGF and CD31 in the whole blood were increased(P＜0.05)in the high-dose group of Guhuaisi Kangfu Pills and Xianling Gubao Capsules group.There was no significant difference in the above indexes between the high-dose group of Guhuaisi Kangfu Pills and the Xianling Gubao Capsules group(P＞0.05).Conclusion Guhuaisi Kangfu Pills improves SONFH in rats,and its mechanism is related to the promotion of VEGF/PI3K/Akt pathway gene expression,thereby promoting angiogenesis.

Objective To establish a dynamic prediction model of fatal massive hemorrhage in trauma based on the vital signs time series data and machine learning algorithms.Methods Retrospectively analyze the vital signs time series data of 7522 patients with trauma in the Medical Information Mart for Intensive Care-Ⅳ(MIMIC-Ⅳ)database from 2008 to 2019.According to the occurrence of posttraumatic fatal massive hemorrhage,the patients were divided into two groups:fatal massive hemorrhage group(n=283)and non-fatal massive hemorrhage group(n=7239).Six machine learning algorithms,including logistic regression(LR),support vector machine(SVM),random forests(RF),adaptive boosting(AdaBoost),gated recurrent unit(GRU),and GRU-D were used to develop a dynamic prediction models of fatal massive hemorrhage in trauma.The probability of fatal massive hemorrhage in the following 1,2,and 3 h was dynamically predicted.The performance of the models was evaluated by accuracy,sensitivity,specificity,positive predictive value,negative predictive value,Youden index,and area under receiver operating characteristic curve(AUC).The models were externally validated based on the trauma database of the Chinese PLA General Hospital.Results In the MIMIC-Ⅳ database,the set of dynamic prediction models based on the GRU-D algorithm was the best.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.946±0.029,0.940±0.032,and 0.943±0.034,respectively,and there was no significant difference(P=0.905).In the trauma dataset,GRU-D model achieved the best external validation effect.The AUC for predicting fatal major bleeding in the next 1,2,and 3 h were 0.779±0.013,0.780±0.008,and 0.778±0.009,respectively,and there was no significant difference(P=0.181).This set of models was deployed in a public web calculator and hospital emergency department information system,which is convenient for the public and medical staff to use and validate the model.Conclusion A set of dynamic prediction models has been successfully developed and validated,which is greatly significant for the early diagnosis and dynamic prediction of fatal massive hemorrhage in trauma.