OBJECTIVE:The main clinical manifestations of knee osteoarthritis are pain,swelling,stiffness,and limited activity,which have a serious impact on the life of patients.Exercise therapy can effectively improve the related symptoms of patients with knee osteoarthritis.This paper uses the method of network meta-analysis to compare the efficacy of different exercise types in the treatment of knee osteoarthritis. METHODS:CNKI,WanFang,PubMed,Embase,Cochrane Library,Web of Science,Scopus,Ebsco,SinoMed,and UpToDate were searched with Chinese search terms"knee osteoarthritis,exercise therapy"and English search terms"knee osteoarthritis,exercise".Randomized controlled trials on the application of different exercise types in patients with knee osteoarthritis from October 2013 to October 2023 were collected.The outcome measures included visual analog scale,Western Ontario and McMaster Universities Osteoarthritis Index score,Timed Up and Go test,and 36-item short form health survey.Literature quality analysis was performed using the Cochrane Manual recommended tool for risk assessment of bias in randomized controlled trials.Two researchers independently completed the data collection,collation,extraction and analysis.RevMan 5.4 and Stata 18.0 software were used to analyze and plot the obtained data. RESULTS:A total of 29 articles with acceptable quality were included,involving 1 633 patients with knee osteoarthritis.The studies involved four types of exercise:aerobic training,strength training,flexibility/skill training,and mindfulness relaxation training.(1)The results of network meta-analysis showed that compared with routine care/health education,aerobic training could significantly improve pain symptoms(SMD=-3.26,95%CI:-6.33 to-0.19,P<0.05);strength training(SMD=-0.79,95%CI:-1.34 to-0.23,P<0.05)and mindfulness relaxation training(SMD=-0.79,95%CI:-1.23 to-0.34,P<0.05)could significantly improve the function of patients.Aerobic training(SMD=-1.37,95%CI:-2.24 to-0.51,P<0.05)and mindfulness relaxation training(SMD=-0.41,95%CI:-0.80 to-0.02,P<0.05)could significantly improve the functional mobility of patients.Mindfulness relaxation training(SMD=0.70,95%CI:0.21-1.18,P<0.05)and strength training(SMD=0.42,95%CI:0.03-0.81,P<0.05)could significantly improve the quality of life of patients.(2)The cumulative probability ranking results were as follows:pain:aerobic training(86.6%)>flexibility/skill training(60.1%)>strength training(56.8%)>mindfulness relaxation training(34.7%)>routine care/health education(11.7%);Knee function:strength training(73.7%)>mindfulness relaxation training(73.1%)>flexibility/skill training(56.1%)>aerobic training(39.9%)>usual care/health education(7.6%);Functional mobility:aerobic training(94.7%)>mindfulness relaxation training(65.5%)>strength training(45.1%)>flexibility/skill training(41.6%)>routine care/health education(3.2%);Quality of life:mindfulness relaxation training(91.3%)>strength training(68.0%)>flexibility/skill training(44.3%)>aerobic training(34.0%)>usual care/health education(12.3%). CONCLUSION:(1)Exercise therapy is effective in the treatment of knee osteoarthritis,among which aerobic training has the best effect on relieving pain and improving functional mobility.Strength training and mindfulness relaxation training has the best effect on improving patients'function.Mindfulness relaxation training has the best effect on improving the quality of life of patients.(2)Limited by the quality and quantity of the included literature,more high-quality studies are needed to verify it.

GPR126, also known as ADGRG6, is one of the most deeply studied aGPCRs. Initially, GPR126 was thought to be a receptor associated with muscle development and was primarily expressed in the muscular and skeletal systems. With the deepening of research, it was found that GPR126 is expressed in multiple mammalian tissues and organs, and is involved in many biological processes such as embryonic development, nervous system development, and extracellular matrix interactions. Compared with other aGPCRs proteins, GPR126 has a longer N-terminal domain, which can bind to ligands one-to-one and one-to-many. Its N-terminus contains five domains, a CUB (complement C1r/C1s, Uegf, Bmp1) domain, a PTX (Pentraxin) domain, a SEA (Sperm protein, Enterokinase, and Agrin) domain, a hormone binding (HormR) domain, and a conserved GAIN domain. The GAIN domain has a self-shearing function, which is essential for the maturation, stability, transport and function of aGPCRs. Different SEA domains constitute different GPR126 isomers, which can regulate the activation and closure of downstream signaling pathways through conformational changes. GPR126 has a typical aGPCRs seven-transmembrane helical structure, which can be coupled to Gs and Gi, causing cAMP to up- or down-regulation, mediating transmembrane signaling and participating in the regulation of cell proliferation, differentiation and migration. GPR126 is activated in a tethered-stalk peptide agonism or orthosteric agonism, which is mainly manifested by self-proteolysis or conformational changes in the GAIN domain, which mediates the rapid activation or closure of downstream pathways by tethered agonists. In addition to the tethered short stem peptide activation mode, GPR126 also has another allosteric agonism or tunable agonism mode, which is specifically expressed as the GAIN domain does not have self-shearing function in the physiological state, NTF and CTF always maintain the binding state, and the NTF binds to the ligand to cause conformational changes of the receptor, which somehow transmits signals to the GAIN domain in a spatial structure. The GAIN domain can cause the 7TM domain to produce an activated or inhibited signal for signal transduction, For example, type IV collagen interacts with the CUB and PTX domains of GPR126 to activate GPR126 downstream signal transduction. GPR126 has homology of 51.6%-86.9% among different species, with 10 conserved regions between different species, which can be traced back to the oldest metazoans as well as unicellular animals.In terms of diseases, GPR126 dysfunction involves the pathological process of bone, myelin, embryo and other related diseases, and is also closely related to the occurrence and development of malignant tumors such as breast cancer and colon cancer. However, the biological function of GPR126 in various diseases and its potential as a therapeutic target still needs further research. This paper focuses on the structure, interspecies differences and conservatism, signal transduction and biological functions of GPR126, which provides ideas and references for future research on GPR126.

Tumors are the second leading cause of death worldwide. Exosomes are a type of extracellular vesicle secreted from multivesicular bodies, with particle sizes ranging from 40 to 160 nm. They regulate the tumor microenvironment, proliferation, and progression by transporting proteins, nucleic acids, and other biomolecules. Compared with other drug delivery systems, exosomes derived from different cells possess unique cellular tropism, enabling them to selectively target specific tissues and organs. This homing ability allows them to cross biological barriers that are otherwise difficult for conventional drug delivery systems to penetrate. Due to their biocompatibility and unique biological properties, exosomes can serve as drug delivery systems capable of loading various anti-tumor drugs. They can traverse biological barriers, evade immune responses, and specifically target tumor tissues, making them ideal carriers for anti-tumor therapeutics. This article systematically summarizes the methods for exosome isolation, including ultracentrifugation, ultrafiltration, size-exclusion chromatography (SEC), immunoaffinity capture, and microfluidics. However, these methods have certain limitations. A combination of multiple isolation techniques can improve isolation efficiency. For instance, combining ultrafiltration with SEC can achieve both high purity and high yield while reducing processing time. Exosome drug loading methods can be classified into post-loading and pre-loading approaches. Pre-loading is further categorized into active and passive loading. Active loading methods, including electroporation, sonication, extrusion, and freeze-thaw cycles, involve physical or chemical disruption of the exosome membrane to facilitate drug encapsulation. Passive loading relies on drug concentration gradients or hydrophobic interactions between drugs and exosomes for encapsulation. Pre-loading strategies also include genetic engineering and co-incubation methods. Additionally, we review approaches to enhance the targeting, retention, and permeability of exosomes. Genetic engineering and chemical modifications can improve their tumor-targeting capabilities. Magnetic fields can also be employed to promote the accumulation of exosomes at tumor sites. Retention time can be prolonged by inhibiting monocyte-mediated clearance or by combining exosomes with hydrogels. Engineered exosomes can also reshape the tumor microenvironment to enhance permeability. This review further discusses the current applications of exosomes in delivering various anti-tumor drugs. Specifically, exosomes can encapsulate chemotherapeutic agents such as paclitaxel to reduce side effects and increase drug concentration within tumor tissues. For instance, exosomes loaded with doxorubicin can mitigate cardiotoxicity and minimize adverse effects on healthy tissues. Furthermore, exosomes can encapsulate proteins to enhance protein stability and bioavailability or carry immunogenic cell death inducers for tumor vaccines. In addition to these applications, exosomes can deliver nucleic acids such as siRNA and miRNA to regulate gene expression, inhibit tumor proliferation, and suppress invasion. Beyond their therapeutic applications, exosomes also serve as tumor biomarkers for early cancer diagnosis. The detection of exosomal miRNA can improve the sensitivity and specificity of diagnosing prostate and pancreatic cancers. Despite their promising potential as drug delivery systems, challenges remain in the standardization and large-scale production of exosomes. This article explores the future development of engineered exosomes for targeted tumor therapy. Plant-derived exosomes hold potential due to their superior biocompatibility, lower toxicity, and abundant availability. Furthermore, the integration of exosomes with artificial intelligence may offer novel applications in diagnostics, therapeutics, and personalized medicine.

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.

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.

OBJECTIVE To evaluate the quality of diagnosis and treatment guidelines and expert consensuses on childhood immune thrombocytopenic purpura （ITP） published domestically and internationally， in order to provide reference for clinical practice and future guideline/expert consensus development and improvement. METHODS A systematic search was conducted across multiple databases， including PubMed， Cochrane Library， Embase， CNKI， Wanfang data， VIP， CBM； additionally， supplementary searches were carried out on websites such as Medlive， the Chinese Medical Association’s official website， and National Institute for Health and Clinical Excellence in the UK. The retrieval time ranged from the inception to September 2， 2024. Researchers who had undergone systematic training independently evaluated the methodology and report quality included in the guideline/consensus using the Appraisal of Guidelines Research and Evaluation Ⅱ （AGREE Ⅱ） and the Reporting Items for Practice Guidelines in Healthcare （RIGHT）. RESULTS A total of 11 guidelines/consensuses were included. The average scores for the six domains of AGREE Ⅱ tool respectively were “range and purpose” （[ 66.67±17.98）% ]， “participants” [58.33% （13.89%，73.61%）]， “rigor” （[ 41.81±23.85）% ]， “clarity”（[ 69.57±19.35）%]， “applicability” （[ 35.98±17.83）%]， and “independence” [27.08% （0，75.00%）]； out of 11 articles， 9 had a recommendation level of B， 2 had a recommendation level of C， and there were no A-level articles. The average reporting rates of the 7 areas in the RIGHT tool were “basic information” （[ 72.35±12.95）% ]， “background” （[ 54.55±15.40）%]，“ evidence” （[ 36.36±24.81）%]，“ recommended opinions” （[ 53.25±19.20）%]，“ review and quality assurance” [0 （0， 25.00%）]， “funding and conflict of interest statement and management” [12.50%（0，25.00%）]， and other aspects [8.33%（0， 50.00%）]. In addition， there was no statistically significant difference in the AGREE Ⅱ and RIGHT scores between the guidelines and consensuses （P＞0.05）. CONCLUSIONS The overall quality of the guidelines and consensuses included in this study is not high， with a recommended level of B or C. It is recommended that clinical decision-making prioritize referring to the relatively high-quality guideline/consensus among them. The quality of evidence in the existing traditional Chinese medicine guidelines for children with ITP needs to be improved， and there is no integrated guideline/consensus for traditional Chinese and Western medicine. It is recommended to revise or write relevant guideline/consensus according to the requirements of AGREE Ⅱ and RIGHT in various fields to guide clinical practice.

Aim To explore the effects of Lycium berry seed oil on Nrf2/ARE pathway and oxidative damage in testis of subacute aging rats. Methods Fifty out of 60 male SD rats, aged 8 weeks, were subcutaneously injected with 125 mg • kg"D-galactosidase in the neck for 8 weeks to establish a subacute senescent rat model. The presence of senescent cells was observed using P-galactosidase ((3-gal), while testicular morphology was examined using HE staining. Serum levels of testosterone (testosterone, T), follicle-stimulating hormone ( follicle stimulating hormone, FSH ) , luteinizing hormone ( luteinizing hormone, LH ) , superoxide dis-mutase ( superoxide dismutase, SOD ) , glutathione ( glutathione, GSH) and malondialdehyde ( malondial-dehyde, MDA) were measured through ELISA, and the expressions of factors related to aging, oxidative damage, and the Nrf2/ARE pathway were assessed via immunohistochemical analysis and Western blotting. Results After successfully identifying the model, the morphology of the testis was improved and the intervention of Lycium seed oil led to a down-regulation in the expression of [3-gal and -yH2AX. The serum levels of SOD, GSH, T, and FSH increased while MDA and LH decreased (P 0. 05) . Additionally, there was an up-regulated expression of Nrf2, GCLC, NQOl, and SOD2 proteins in testicular tissue ( P 0. 05 ) and nuclear expression of Nrf2 in sertoli cells. Conclusion Lycium barbarum seed oil may reduce oxidative damage in testes of subacute senescent rats by activating the Nrf2/ARE signaling pathway.

Aim To analyze the anti-A549 and HI299 lung ade-nocarcinoma activities via using examples of baicalin, astragalo-side, hesperidin and cisplatin based on real time cellular analysis (RTCA) technology, and to build a new strategy for EC50 e-valuation reflecting the time-dimensional characteristic. Methods Using RTCA Software Pro for data analysis and GraphPad Prism and Origin Pro plotting, the in vitro anti-A549 and H1299 lung adenocarcinoma activities of baicalin, astragaloside, hesperidin, and cisplatin were characterized using the endpoint method and time dimension, respectively. Results (X) There were significant differences in EC50 values of A549 and H1299 cells at 24 h and 48 h endpoint methods. (2) The correlation coefficient of the curve fitted with the four-parameter equation was > 0. 9, and the dynamic change of EC50 remained relatively stable (the linear fitting of EC50 at adjacent 4 points I slope 1^1) used to calculate the EC50 value within this time dimension. The EC50 of baicalin, astragaloside, hesperidin and cisplatin on A549 cells was 52. 97 ±1.75 плпо! • L~1(16~48 h) , 62.88 ± 2.91 ijunol • L"1 (32.25 -48 h) , 78.84 ±0.33 плпо1 • L"1 (21.5 -29.75 h), 13.57 ±1.54 плпо1 • L_1(27.5 -48 h), respectively; the EC50 of baicalin, astragaloside, hesperidin and cisplatin on H1299 cells was 43. 71 ± 1. 26 |лто1 • L_1 ( 19. 5 -48 h), 47.23 ±1. 19 |лто1 • L_1(14 -48 h) , 39.45 ±0.24 плпо1 • L"1 (12.75 -46.25 h), 25.97 ±4.76 плпо1 • L"1 (10. 25 -48 h) , respectively. The results showed that the time window for the anti-tumor effect of the test solution/drug was different. Conclusions Based on RTCA technology, it is more accurate and reasonable to select EC50 data that exhibit better fitting, stable changes, and time-dimensional characteristics for the evaluation of anti-tumor activity. In addition, this method of distinguishing different effective time of antitumor drugs can provide a reference for the timing of clinical combination drugs, and this approach will also provide a reference for further related studies.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.