BACKGROUND:Ankylosing spondylitis is closely related to the occurrence and development of psoriasis,but the key genes and regulatory mechanisms are still unclear.OBJECTIVE:To establish an artificial neural network model of genes shared by ankylosing spondylitis and psoriasis based on the GEO database and evaluate its effect,and also to determine whether there is a causal relationship between the expression of key genes and the two diseases using Mendelian randomization.METHODS:Datasets GSE25101(816 ankylosing spondylitis samples and 816 healthy control samples),GSE30999(85 psoriasis samples and 85 healthy control samples),GSE73754(52 ankylosing spondylitis samples and 20 healthy control samples),and GSE14905(33 psoriasis samples and 49 healthy control samples)were downloaded from the GEO database.GSE25101 and GSE30999 were used as the training datasets of ankylosing spondylitis and psoriasis,respectively,and their respective differentially expressed genes were identified through difference analysis to obtain the common driver genes of the two diseases,and the key core genes were further screened out based on Mendelian randomization.The key core genes were further screened out,and artificial neural network models were constructed based on the key core genes and validated in external datasets GSE73754 and GSE14905,followed by the construction of the corresponding nomogram to predict the incidence rates of the diseases.Also,the results of immune infiltration in ankylosing spondylitis and psoriasis were analyzed.Finally,Mendelian randomization was used to assess causal relationships between key genes and diseases,and drug-gene interactions were analyzed using the Dgidb database to predict drug targets.RESULTS AND CONCLUSION:(1)A total of 61 differential genes were obtained in ankylosing spondylitis and 4 309 differential genes were obtained in psoriasis.Eight shared differential genes were obtained after intersection,and five key genes(DNMT1,GNG11,CDC25B,S100A8,and S100A12)were further screened by machine learning.The key genes were utilized to build artificial neural network models of ankylosing spondylitis and psoriasis,with the area under curve values of 0.979 and 0.989 in the training sets GSE25101 and GSE30999,respectively,and 0.818 and 0.874 in the external validation datasets GSE73754 and GSE14905,respectively.(2)Nomogram was constructed based on the five core genes,and the calibration curves showed that the predicted probabilities of the nomogram models were almost the same as that of the ideal model.Immune cell infiltration showed that the key genes were associated with activated B cells,natural killer cells,γδ T cells,follicular helper T cells,monocytes,plasma cell-like dendritic cells,and neutrophils.Mendelian randomization showed that S100A8 was a risk factor for the occurrence of ankylosing spondylitis and psoriasis.Finally,DGldb screening was utilized to obtain 81 targeted drugs,only 16 of which,including methotrexate,atogepant,ubrogepant,rimegepant,eptinezumab,azacitidine,selenium,hydroxyurea,ifosfamide,floxuridine,curcumin,mitoxantrone,cisplatin,arsenic trioxide,diethylstilbestrol,and decitabine,were approved by the U.S.Food and Drug Administration.(3)A large number of successful cases have been accumulated in international databases,research results and data analysis of European groups,especially in genomics and disease phenotyping studies.These experiences provide valuable references for the epidemiological characterization of diseases in China,genetic diversity and their response to the environment and lifestyle.(4)An artificial neural network model of the common driver genes of ankylosing spondylitis and psoriasis was constructed and validated,the causal relationship between the key genes and the pathogenesis of the two diseases was discovered,and the targeted drugs for potential treatments were predicted,which hopefully provides a new perspective for exploring their pathogenesis and therapeutic directions.

BACKGROUND:Ankylosing spondylitis is closely related to the occurrence and development of psoriasis,but the key genes and regulatory mechanisms are still unclear.OBJECTIVE:To establish an artificial neural network model of genes shared by ankylosing spondylitis and psoriasis based on the GEO database and evaluate its effect,and also to determine whether there is a causal relationship between the expression of key genes and the two diseases using Mendelian randomization.METHODS:Datasets GSE25101(816 ankylosing spondylitis samples and 816 healthy control samples),GSE30999(85 psoriasis samples and 85 healthy control samples),GSE73754(52 ankylosing spondylitis samples and 20 healthy control samples),and GSE14905(33 psoriasis samples and 49 healthy control samples)were downloaded from the GEO database.GSE25101 and GSE30999 were used as the training datasets of ankylosing spondylitis and psoriasis,respectively,and their respective differentially expressed genes were identified through difference analysis to obtain the common driver genes of the two diseases,and the key core genes were further screened out based on Mendelian randomization.The key core genes were further screened out,and artificial neural network models were constructed based on the key core genes and validated in external datasets GSE73754 and GSE14905,followed by the construction of the corresponding nomogram to predict the incidence rates of the diseases.Also,the results of immune infiltration in ankylosing spondylitis and psoriasis were analyzed.Finally,Mendelian randomization was used to assess causal relationships between key genes and diseases,and drug-gene interactions were analyzed using the Dgidb database to predict drug targets.RESULTS AND CONCLUSION:(1)A total of 61 differential genes were obtained in ankylosing spondylitis and 4 309 differential genes were obtained in psoriasis.Eight shared differential genes were obtained after intersection,and five key genes(DNMT1,GNG11,CDC25B,S100A8,and S100A12)were further screened by machine learning.The key genes were utilized to build artificial neural network models of ankylosing spondylitis and psoriasis,with the area under curve values of 0.979 and 0.989 in the training sets GSE25101 and GSE30999,respectively,and 0.818 and 0.874 in the external validation datasets GSE73754 and GSE14905,respectively.(2)Nomogram was constructed based on the five core genes,and the calibration curves showed that the predicted probabilities of the nomogram models were almost the same as that of the ideal model.Immune cell infiltration showed that the key genes were associated with activated B cells,natural killer cells,γδ T cells,follicular helper T cells,monocytes,plasma cell-like dendritic cells,and neutrophils.Mendelian randomization showed that S100A8 was a risk factor for the occurrence of ankylosing spondylitis and psoriasis.Finally,DGldb screening was utilized to obtain 81 targeted drugs,only 16 of which,including methotrexate,atogepant,ubrogepant,rimegepant,eptinezumab,azacitidine,selenium,hydroxyurea,ifosfamide,floxuridine,curcumin,mitoxantrone,cisplatin,arsenic trioxide,diethylstilbestrol,and decitabine,were approved by the U.S.Food and Drug Administration.(3)A large number of successful cases have been accumulated in international databases,research results and data analysis of European groups,especially in genomics and disease phenotyping studies.These experiences provide valuable references for the epidemiological characterization of diseases in China,genetic diversity and their response to the environment and lifestyle.(4)An artificial neural network model of the common driver genes of ankylosing spondylitis and psoriasis was constructed and validated,the causal relationship between the key genes and the pathogenesis of the two diseases was discovered,and the targeted drugs for potential treatments were predicted,which hopefully provides a new perspective for exploring their pathogenesis and therapeutic directions.

OBJECTIVE: To observe the clinical efficacy of acupuncture based on "status-target coherence" theory combined with Kegel exercises for vaginal laxity syndrome (VLS). METHODS: Sixty-six patients with VLS were randomized into an observation group (33 cases, 2 cases dropped out, 1 case was discontinued) and a control group (33 cases, 5 cases dropped out). The observation group was treated with acupuncture combined with Kegel exercises, acupuncture was applied to bilateral Ciliao (BL32), Zhongliao (BL33), Sanyinjiao (SP6), etc. The control group was treated with Kegel exercises. Both acupuncture and Kegel exercises were performed once every other day, three times a week for 12 weeks. Before and after treatment, the vaginal laxity questionnaire (VLQ) score, pelvic floor muscle strength (vaginal resting pressure, vaginal systolic pressure, vaginal contraction duration), degree of vaginal laxity and sexual satisfaction questionnaire (SSQ) grade were observed in both groups. RESULTS: After treatment, the VLQ score, vaginal resting pressure, vaginal systolic pressure, vaginal contraction duration in the observation group were elevated compared with those before treatment (P<0.05), and SSQ grade was improved (P<0.05); and the above indexes in the observation group were better than those in the control group (P<0.05). There were no significant difference before and after treatment in the degree of vaginal laxity in the two groups (P>0.05). CONCLUSION Acupuncture based on "status-target coherence" theory combined with Kegel exercises can effectively enhance the strength of pelvic floor muscles, improve the symptoms of vaginal laxity, and improve the satisfaction of sexual life, and its therapeutic effect is better than Kegel exercises alone.
Humans ; Female ; Adult ; Vagina/physiopathology* ; Acupuncture Therapy ; Exercise Therapy ; Young Adult ; Middle Aged ; Treatment Outcome ; Acupuncture Points ; Combined Modality Therapy ; Vaginal Diseases/therapy*

Objective:To investigate the correlation between triglyceride-glucose-body mass index (TyG-BMI index) and the outcome of young patients with acute ischemic stroke (AIS).Methods:Consecutive young patients with first-ever AIS (aged 18-45 years) admitted to Pingyi County People's Hospital and Qingdao Municipal Hospital from January 2020 to December 2023 were included retrospectively. The demographic data, vascular risk factors, baseline blood pressure, baseline laboratory tests, classification of stroke etiology, baseline National Institutes of Health Stroke Scale (NIHSS) scores, and main treatment methods were collected. At 3 months after the onset of stroke, the modified Rankin Scale was used for outcome evaluation. A score of 0-2 was defined as good outcome and >2 were defined as poor outcome. Multivariate logistic regression analysis was used to identify independent factors associated with poor outcome in young patients with AIS. Results:A total of 253 young patients with AIS were enrolled, including 196 males (77.5%), aged 38.65±5.34 years; baseline NIHSS score 3.03±2.88. At 90 days after onset, 206 patients (81.4%) had good outcome, while 47 (18.6%) had poor outcome. The poor outcome group had significantly higher systolic blood pressure, triglycerides, fasting blood glucose, triglyceride glucose (TyG) index, body mass index (BMI), TyG-BMI index, and baseline NIHSS score than those of the good outcome group (all P<0.05). Multivariate logistic regression analysis showed that after adjusting for gender, systolic blood pressure, baseline NIHSS score, and antiplatelet drug use, the TyG-BMI index was significantly independently associated with the poor outcome in young patients with AIS (odds ratio 1.039, 95% confidence interval 1.021-1.057; P<0.001). Conclusion:A higher baseline TyG-BMI index is independently associated with the poor outcome in young patients with AIS.

Purpose: This study examined the diagnostic value of high-frequency ultrasound (HFUS) features in differentiating between benign and malignant skin lesions. Methods: A total of 1,392 patients with 1,422 skin lesions who underwent HFUS examinations were included in an initial dataset (cohort 1) to identify features indicative of malignancy. Qualitative clinical and HFUS characteristics were recorded for all lesions. To determine which HFUS and clinical features were suggestive of malignancy, univariable and multivariable logistic regression analyses were employed. The diagnostic performance of HFUS features combined with clinical information was evaluated. This assessment was validated using internal data (cohort 2) and multicenter external data (cohort 3). Results: Features significantly associated with malignancy included age above 60 years; lesion location in the head, face, and neck or genital regions; changes in macroscopic appearance; crawling or irregular growth pattern; convex or irregular base; punctate hyperechogenicity; blood flow signals; and feeding arteries. The area under the receiver operating characteristic curve, sensitivity, and specificity of HFUS features combined with clinical information were 0.946, 92.5%, and 86.9% in cohort 1; 0.870, 93.1%, and 80.8% in cohort 2 (610 lesions); and 0.864, 86.2%, and 86.6% in cohort 3 (170 lesions), respectively. However, HFUS is not suitable for evaluating lesions less than 0.1 mm in thickness or lesions exhibiting surface hyperkeratosis. Conclusion In a clinical setting, the integration of HFUS with clinical information exhibited good diagnostic performance in differentiating malignant and benign skin lesions. However, its utility was limited in evaluating extremely thin lesions and those exhibiting hyperkeratosis.

Purpose: This study examined the diagnostic value of high-frequency ultrasound (HFUS) features in differentiating between benign and malignant skin lesions. Methods: A total of 1,392 patients with 1,422 skin lesions who underwent HFUS examinations were included in an initial dataset (cohort 1) to identify features indicative of malignancy. Qualitative clinical and HFUS characteristics were recorded for all lesions. To determine which HFUS and clinical features were suggestive of malignancy, univariable and multivariable logistic regression analyses were employed. The diagnostic performance of HFUS features combined with clinical information was evaluated. This assessment was validated using internal data (cohort 2) and multicenter external data (cohort 3). Results: Features significantly associated with malignancy included age above 60 years; lesion location in the head, face, and neck or genital regions; changes in macroscopic appearance; crawling or irregular growth pattern; convex or irregular base; punctate hyperechogenicity; blood flow signals; and feeding arteries. The area under the receiver operating characteristic curve, sensitivity, and specificity of HFUS features combined with clinical information were 0.946, 92.5%, and 86.9% in cohort 1; 0.870, 93.1%, and 80.8% in cohort 2 (610 lesions); and 0.864, 86.2%, and 86.6% in cohort 3 (170 lesions), respectively. However, HFUS is not suitable for evaluating lesions less than 0.1 mm in thickness or lesions exhibiting surface hyperkeratosis. Conclusion In a clinical setting, the integration of HFUS with clinical information exhibited good diagnostic performance in differentiating malignant and benign skin lesions. However, its utility was limited in evaluating extremely thin lesions and those exhibiting hyperkeratosis.

Purpose: This study examined the diagnostic value of high-frequency ultrasound (HFUS) features in differentiating between benign and malignant skin lesions. Methods: A total of 1,392 patients with 1,422 skin lesions who underwent HFUS examinations were included in an initial dataset (cohort 1) to identify features indicative of malignancy. Qualitative clinical and HFUS characteristics were recorded for all lesions. To determine which HFUS and clinical features were suggestive of malignancy, univariable and multivariable logistic regression analyses were employed. The diagnostic performance of HFUS features combined with clinical information was evaluated. This assessment was validated using internal data (cohort 2) and multicenter external data (cohort 3). Results: Features significantly associated with malignancy included age above 60 years; lesion location in the head, face, and neck or genital regions; changes in macroscopic appearance; crawling or irregular growth pattern; convex or irregular base; punctate hyperechogenicity; blood flow signals; and feeding arteries. The area under the receiver operating characteristic curve, sensitivity, and specificity of HFUS features combined with clinical information were 0.946, 92.5%, and 86.9% in cohort 1; 0.870, 93.1%, and 80.8% in cohort 2 (610 lesions); and 0.864, 86.2%, and 86.6% in cohort 3 (170 lesions), respectively. However, HFUS is not suitable for evaluating lesions less than 0.1 mm in thickness or lesions exhibiting surface hyperkeratosis. Conclusion In a clinical setting, the integration of HFUS with clinical information exhibited good diagnostic performance in differentiating malignant and benign skin lesions. However, its utility was limited in evaluating extremely thin lesions and those exhibiting hyperkeratosis.

Clinical trials play a crucial role in advancing the field of human health care. The registration of clinical trials can effectively identify potential publication bias and prevent unnecessary duplication of research efforts, serving as a source of transparent data for health care professionals and researchers, enhancing the quality of clinical research, and presenting more transparent, standardized, authentic, and useful clinical trials. To enhance the capacity for evidence production in traditional medicine from the source, the International Traditional Medicine Clinical Trial Registry (ITMCTR), a cross-regional registry focusing on the theme of traditional medicine, was established. Under the current registration background, this study aims to introduce the problems and current status related to clinical trial registration, as well as the features and functions of the ITMCTR. The results of this study illustrate the necessity of establishing a specialized registration platform for traditional medicine to assist researchers in understanding the basic background of registration and relevant information regarding registration platforms, regardless of whether their research is related to traditional medicine or not. Ultimately, the results of this work will help researchers choose the appropriate platform for more efficient and transparent registration.

Objective To investigate the clinical and practical value of transvaginal endoscopic technology by using traditional hysteroscope in the diagnosis and treatment of intrauterine lesions in asexual women of childbearing age.Methods A retrospective analysis was conducted on 98 cases of hysteroscopic surgery in asexual women of childbearing age admitted from January 2005 to May 2024.Transvaginal endoscopic technology was applied for hysteroscopic examination and/or treatment by using traditional hysteroscope.Results A total of 62 cases underwent electrocautery after cervical dilation with a dilation rod,including 43 cases of endometrial polyps,15 cases of submucosal fibroids,and 4 cases of cervical polyps.The remaining 36 cases underwent endometrial biopsy or curettage by using a microscope,and all obtained endometrial biopsy pathology.One case of hymen laceration about 0.3 cm in length was sutured with 5-0 absorbable suture for one stitch.For the remaining cases,the hymen remained intact.Conclusion Using transvaginal endoscopic technology with traditional hysteroscope can complete hysteroscopic examination or surgical treatment without damaging the hymen,which is suitable for asexual women of childbearing age.

Objective:To construct a risk assessment model based on hesitant probabilistic fuzzy set(HPFS)and to explore its application value in the risk control and management of safe operation of anesthesia equipment.Methods:Taking the whole life cycle safety and management safety as the important risk assessment dimensions,the risk index system of safe operation of anesthesia equipment was constructed,HPFS and hierarchical-superior-inferior solution distance method were used to realize the quantitative analysis of risks,and the safety self-inspection and risk control treatment strategies were formulated.A total of 150 surgical patients and 16 anesthesia equipment used in surgery used in the operation were selected from July 2020 to June 2023 in Tongzhou District Maternal and Child Health Hospital,and into control group and observation group according to different management modes of anesthetic equipment,with 75 cases in each group.The 10 anesthesia machines used during the surgical treatment of the control group adopted the conventional risk control mode,and the 12 anesthesia machines used in the observation group(including 6 in the control group and the 6 newly added ones)adopted the risk assessment control mode.The incidence of perioperative anesthesia equipment-related risk events,the awareness rate of anesthesia medical staff about potential safety risks,and the failure rate of anesthesia equipment were compared between the two groups.Results:The number of perioperative risk events of improper operation of anesthesia equipment,unreasonable dosage of anesthesia,associated infection and missing records in the observation group were 4 cases(5.3%),0 cases(0%),1 case(1.3%)and 1 case(1.3%),respectively,which was lower than that in the control group,the difference was statistically significant(x2=4.478,4.110,6.857,4.754;P<0.05).The average scores of theoretical knowledge of safety management,safe use,management awareness and fault judgment ability of medical staff operating anesthesia equipment in the observation group were(96.27±3.93)points,(94.31±2.69)points,(91.82±1.94)points and(84.97±4.36)points,respectively,which were higher than those in the control group,the difference was statistically significant(t=5.176,5.322,5.541,5.942;P<0.05).The total number of equipment operation setting,anesthetic gas path,anesthesia depth monitoring,threshold alarm and other faults in the two groups were 90,37,25,316 and 125,respectively,and the failure incidence rates in the observation group were 30%(27/90),35%(13/37),28%(7/25),22%(69/316)and 39%(49/125),respectively,which were lower than those in the control group,the difference was statistically significant(x2=28.800,6.541,9.680,200.532,11.664;P<0.05). Conclusion:The risk assessment model based on HPFS can reduce the incidence of risk events related to anesthesia equipment,enhance the awareness of safety risk control of anesthesia medical staff,and improve the quality of clinical operation of anesthesia equipment.