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 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.

Objective To investigate the effect of Ilizarov technique combined with rotational center dome-shaped osteoto-my in the treatment of juvenile distal femoral valgus deformity.Methods A retrospective study was conducted to analyze the clinical data of 11 patients with valgus deformity of the distal femur who had been admitted and followed up completely from January 2016 to October 2020.There were 7 males and 4 females.The 6 patients were on the right side and 5 patients were on the left side.The age ranged from 10 to 14 years old.The center of roration of angulation(CORA)was identified at the distal femur deformity,and dome-shaped osteotomy was performed with the CORA as the midpoint.The annular external fixator was installed according to the needle threading principle of Ilizarov external fixation,and the distal femur was cut off.The valgus deformity under visual inspection of the distal femur was corrected immediately,and the external fixator was fixed and main-tained.The residual deformity and shortening were corrected according to the force line and length of the lower limbs suggested by the weight-bearing full-length anteroposterior and lateral X-rays of both lower limbs.Results All 11 patients were followed up for 13 to 25 months.The time of wearing external fixator was 12 to 17 weeks.In the last follow-up,both lower limbs were measured by the weight-bearing full-length anteroposterior and lateral X-rays,and the length of both lower limbs of 11 patients were equal,and the deformities were corrected.The score of hospital for special surgery(HSS)was used to evaluate the knee function,all of which were excellent.Conclusion The Ilizarov technique was applied in the treatment of distal femoral valgus deformity in adolescents using a rotating central dome-shaped osteotomy.Visual femoral valgus deformity was corrected imme-diately during the operation.After the operation,residual deformities and shortening were dynamically adjusted and corrected according to the force line and shortening degree of lower extremities indicated by the weight-bearing anteroposterior and lateral radiographs of both lower limbs,with minimal damage and fast recovery.

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 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 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.

Patients with severe trauma require an extremely timely treatment and transfusion plays an irreplaceable role in the emergency treatment of such patients. An increasing number of evidence-based medicinal evidences and clinical practices suggest that patients with severe traumatic bleeding benefit from early transfusion of low-titer group O whole blood or hemostatic resuscitation with red blood cells, plasma and platelet of a balanced ratio. However, the current domestic mode of blood supply cannot fully meet the requirements of timely and effective blood transfusion for emergency treatment of patients with severe trauma in clinical practice. In order to solve the key problems in blood supply and blood transfusion strategies for emergency treatment of severe trauma, Branch of Clinical Transfusion Medicine of Chinese Medical Association, Group for Trauma Emergency Care and Multiple Injuries of Trauma Branch of Chinese Medical Association, Young Scholar Group of Disaster Medicine Branch of Chinese Medical Association organized domestic experts of blood transfusion medicine and trauma treatment to jointly formulate Chinese expert consensus on blood support mode and blood transfusion strategies for emergency treatment of severe trauma patients ( version 2024). Based on the evidence-based medical evidence and Delphi method of expert consultation and voting, 10 recommendations were put forward from two aspects of blood support mode and transfusion strategies, aiming to provide a reference for transfusion resuscitation in the emergency treatment of severe trauma and further improve the success rate of treatment of patients with severe trauma.