Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

ObjectiveTo carry out a health technology assessment （HTA） of acupuncture for secondary dysmenorrhea （SD） caused by adenomyosis and endometriosis， in order to provide a reference for relevant medical decision-making. MethodsFrom the perspective of the health system， the assessment covers seven areas， including the technical characteristics， safety， effectiveness， economics， ethical fairness， organizational adaptability， and impact on patients and society. The results are reported accordingly. ResultsThe operational specifications of acupuncture are standardized， and the conditions for its use are clearly defined. Acupuncture has a lower overall incidence of adverse events. The main adverse events are localized pain， subcutaneous bleeding， and dizziness， with most symptoms being mild， all of which have corresponding standard treatments. No reports on occupational or environmental safety were found， and the safety operation specifications are available for reference. Compared with conventional Western medicine， acupuncture demonstrates higher effectiveness. Acupuncture may improve the quality of life scores of patients， though no significant difference was observed. The cost of acupuncture is higher than that of conventional Western medicine， but its overall economic value is greater. The informed consent information is relatively comprehensive. Most patients are aware of the potential benefits and risks of acupuncture and voluntarily opt for it. The treatment process fully respects patient privacy and human rights. The clinical application of acupuncture follows the current acupuncture medical service model， with no special requirements for the level of medical institutions. Patient accessibility and affordability are suitable. Patient satisfaction is high. Most patients indicated they would choose acupuncture again for SD. The main barriers to choosing acupuncture are psychological factors （such as fear of acupuncture）， cost， and transportation issues. Nearly 70% of patients receiving acupuncture treatment benefit from medical insurance reimbursement， with reimbursement rates generally above 50%， indicating strong social security support. ConclusionThe implementation of HTA for acupuncture in the treatment of SD， using the standards for traditional Chinese medicine （TCM）， is feasible. The implementation steps are clear， the data sources for each evaluation domain are adequate， the analysis methods are practical， and the evaluation results are comprehensive. Experts recommend that the findings be used as a reference for relevant medical decision-making.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Based on the theory of toxin in The Inner Canon of Yellow Emperor （《黄帝内经》）， this paper explores the concept and connotation of toxin from several aspects， including medicinal toxicity， pathogenic toxicity， pathoge-nesis and treatment of toxin pathogen. It explores the mechanism and significance of using toxin substances in curing and inducing diseases， sorts out the etiological and pathological evolution of toxic pathogens， clarifies the derivation and differentiation process from external toxins to internal toxins， and elucidates the interactions between toxin and other pathogenic factors such as phlegm， stasis， dampness， and fire. It further distinguishes the logical hierarchy of toxin caused by metabolic disorders such as sugar， fat， and drowning， clarifies that the essence of the etiology of "hidden toxin"， and determines the corresponding treatment principles and methods for toxic pathogens. It establishes a theoretical framework of traditional Chinese medicine toxic pathogen theory， providing theoretical basis for the clinical treatment of many diseases.

Objective:To investigate the indications and effects of arthroscopic all-inside reconstruction in the treatment of isolated posterior cruciate ligament (PCL) injury.Methods:A retrospective analysis was performed on 47 patients with isolated PCL injury, who underwent arthroscopic all-inside reconstruction in the Third Medical Center of the PLA General Hospital from January 2016 to January 2020. There were 39 males and 8 females, aged 27.14±7.70 years old (range 16-40 years old). The preoperative kneeling-position stress X-ray showed that the degree of tibial posterior displacement was 8-10 mm, which was a complete and isolated Grade II PCL injury. The tibial and femoral tunnels were created through posterior-medial, anteromedial, and anterolateral portals, while the lateral portal to the medial femoral condyle was enlarged to position the tibial tunnel and protect the anterior cruciate ligament. The autologous graft tendon was pulled through the femoral and tibial tunnels secured with an adjustable loop plate. The efficacy was evaluated by evaluating and comparing preoperative and postoperative Lachman test, posterior drawer test, knee range of motion and relaxation, pain visual analogue scale (VAS) and Lysholm score.Results:43 patients were followed up for 35.21±3.88 months (range 12-40 months). The symptoms of knee instability all improved after surgery. At the follow-up of 1 year after surgery, 41 (95%) and 40 (93%) patients showed normal or I-degree laxity in Lachman test and posterior drawer test, respectively. The active range of motion and passive flexion of the knee joint were increased to 90°-110° and 110°-130°, respectively. The Lysholm score was 86.44±4.08 at the first year of follow-up and 90.12±3.33 at the last follow-up with significant difference compared with pre-operations ( P<0.05). The VAS score was 2.07±0.94 at the first year of follow-up and 1.28±0.83 at the last follow-up with significant difference compared with pre-operations ( P<0.05). The Lysholm score and VAS were 90.12±3.33 and 1.28±0.83, which were significantly improved compared to 1-year-follow-up ( P<0.05). Conclusion:Routine kneeling stress X-rays can evaluate the degree of tibial posterior displacement in isolated PCL injuries. With tibial posterior displacement equal to or greater than 10 mm, surgical reconstruction was required. All-inside reconstruction of isolated PCL injury was a safe and minimally invasive surgery to improve symptoms and restore knee functions.

Silver nanoparticles(AgNPs)is widely used in biomedicine,daily chemicals,food industry and other fields,and the possible negative health effects of its exposure have attracted widespread attention.Accurate analysis of AgNPs in biological matrices is the basis for biosafety studies of AgNPs.Among the existing analytical techniques,single particle-inductively coupled plasma-mass spectrometry(sp-ICP-MS)has significant advantages such as high sensitivity and simultaneous detection of different forms of silver.However,AgNPs in biological matrices is uniquely highly dynamic and low in content,and the matrix interference is severe,which increases the complexity of the analysis.Although some scholars have reviewed the application of this method for detection of metal nanoparticles in different scenarios,there is a lack of a summary of the quality control and optimization of the whole process from the perspective of AgNPs detection.There is still a lack of reference standards for the sp-ICP-MS analysis of AgNPs in biological matrices,and the existing methods need to be summarized and further optimized to achieve accurate quantification.Therefore,this paper reviewed the recent studies on the analysis of silver-containing nanoparticles in biological matrices based on sp-ICP-MS,mainly included the principles of the technique,the extraction methods of the particles,and the process of data processing,which focused on elaborating and comparing different pre-treatment methods,and explored issues of the current application of sp-ICP-MS for detection of AgNPs in biological tissues and the development of future optimization trends.The current problems of sp-ICP-MS for detection of AgNPs in biological tissues and the future development trend were also discussed.

Objective To compare the pharmacokinetic profiles of the two teriflunomide tablets in healthy Chinese subjects under fasting and fed conditions and to evaluate their bioequivalence and safety.Methods A randomized,open,single-dose,parallel trial design was used to enroll 31 and 32 healthy Chinese male subjects in the fasting and fed groups,who were randomized to a single oral dose of 14 mg of either reference or test preparation of teriflunomide tablets.The plasma concentrations of teriflunomide were determined using liquid chromatography-tandem mass spectrometry method,and Phoenix WinNonlin 8.1 software was used to calculate pharmacokinetic parameters and perform bioequivalence analysis.Results Subjects received a single oral dose of the reference and test formulations of teriflunomide.The main pharmacokinetic parameters of teriflunomide in the fasting group were as follows:Cmax were(2.14±0.27)and(2.27±0.33)μg·mL-1,AUC0-72h were(105.70±11.20)and(107.72±11.77)μg·mL-1·h,tmax was 1.49 and 0.99 h;the main pharmacokinetic parameters of teriflunomide in the fed group were as follows:Cmaxwere(1.83±0.17)and(1.75±0.22)μg·mL-1,AUC0-72h were(102.66±9.18)and(101.57±13.01)μg·mL-1·h,tmax was 4.01 and 4.99 h.The 90％confidence intervals for the geometric means of Cmax and AUC0-72h for reference and test preparations in the fasting and fed groups were in the range of 80％to 125％.Conclusion The pharmacokinetic characteristics of the 2 formulations were similar under fasting and fed administration conditions,with good bioequivalence and safety;Postprandial administration may delay the time to peak of the drug.

Temporomandibular joint (TMJ) diseases are common clinical conditions. The number of patients with TMJ diseases is large, and the etiology, epidemiology, disease spectrum, and treatment of the disease remain controversial and unknown. To understand and master the current situation of the occurrence, development and prevention of TMJ diseases, as well as to identify the patterns in etiology, incidence, drug sensitivity, and prognosis is crucial for alleviating patients′suffering.This will facilitate in-depth medical research, effective disease prevention measures, and the formulation of corresponding health policies. Cohort construction and research has an irreplaceable role in precise disease prevention and significant improvement in diagnosis and treatment levels. Large-scale cohort studies are needed to explore the relationship between potential risk factors and outcomes of TMJ diseases, and to observe disease prognoses through long-term follw-ups. The consensus aims to establish a standard conceptual frame work for a cohort study on patients with TMJ disease while providing ideas for cohort data standards to this condition. TMJ disease cohort data consists of both common data standards applicable to all specific disease cohorts as well as disease-specific data standards. Common data were available for each specific disease cohort. By integrating different cohort research resources, standard problems or study variables can be unified. Long-term follow-up can be performed using consistent definitions and criteria across different projects for better core data collection. It is hoped that this consensus will be facilitate the development cohort studies of TMJ diseases.

Objective The leptin receptor,encoded by the LEPR gene,is involved in tumorigenesis.A potential functional variant of LEPR,rs1137101(Gln223Arg),has been extensively investigated for its contribution to the risk of digestive system(DS)cancers,but results remain conflicting rather than conclusive.Here,we performed a case-control study and subsequent meta-analysis to examine the association between rs1137101 and DS cancer risk. Methods A total of 1,727 patients with cancer(gastric/liver/colorectal:460/480/787)and 800 healthy controls were recruited.Genotyping of rs1137101 was conducted using a polymerase chain reaction-restriction fragment length polymorphism(PCR-RFLP)assay and confirmed using Sanger sequencing.Twenty-four eligible studies were included in the meta-analysis. Results After Bonferroni correction,the case-control study revealed that rs1137101 was significantly associated with the risk of liver cancer in the Hubei Chinese population.The meta-analysis suggested that rs1137101 is significantly associated with the risk of overall DS,gastric,and liver cancer in the Chinese population. Conclusion The LEPR rs1137101 variant may be a genetic biomarker for susceptibility to DS cancers(especially liver and gastric cancer)in the Chinese population.