Objective: To evaluate the efficacy and safety of ruxolitinib combined with low-dose hormone for patients with acute graft-versus-host disease (aGVHD) after allogeneic hematopoietic stem cell transplantation (allo-HSCT). Methods: Thirty patients with aGVHD after allo-HSCT admitted to the Department of Hematology of the General Hospital of Western Theater Command from November 2021 to November 2024 were retrospectively analyzed. All patients were treated with low-dose hormone (methylprednisolone 0.3-1 mg kg -d ) combined with ruxolitinib 5-10 mg d . The efficacy and adverse reactions were observed during the follow-up period to analyze the survival outcomes of the patients. Results: A total of 30 patients with aGVHD after allo-HSCT were included in this study, consisting of 15 (50%) males and 15 (50%) females with a median age of 34 year-old (ranging from 14 to 62). Classification by disease type: there were 18 cases of acute myeloid leukemia, 4 cases of acute lymphoblastic leukemia, 4 cases of aplastic anemia, and 4 cases of myelodysplastic syndrome. Classification by aGVHD severity: there were 27 cases (90%) of Ⅱ-Ⅳ degree aGVHD and 11 cases (36.7%) of Ⅲ-Ⅳ degree aGVHD. Ruxolitinib in combination with low-dose glucocorticoid treatment yield responses in 28 (93.3%) patients, of which 27 (90%) achieved complete remission (CR), while 1 (3.3%) showed partial remission (PR). One patient (3.3%) had no response (NR), and 1 patient (3.3%) exhibited progressed disease (PD). Overall survival (OS) at 1 year of transplantation was 73.9% (95%CI 49.5% to 87.7%), progression-free survival (PFS) was 93.3% (95%CI 75.9% to 98.3%), non-relapse mortality (NRM) was 20.6% (95%CI 7.9% to 47.4%), and median survival time was 27.6 months. Conclusion: Ruxolitinib combined with low-dose hormones is safe and effective in the treatment of aGVHD after allo-HSCT.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective This study aimed to investigate the antimicrobial resistance profiles of bacterial strains isolated from pediatric intensive care units(PICU)in China for better antimicrobial therapy.Methods Clinical isolates were collected from 17 institutions,including tertiary care children's hospitals and pediatric department of tertiary general hospitals in China from January 1,2020 to December 31,2022.Antimicrobial susceptibility testing was carried out according to a unified protocol using Kirby-Bauer method or automated systems.Results were interpreted according to the breakpoints released by the Clinical and Laboratory Standards Institute(CLSI)in 2020.Results A total of 10 688 isolates were collected,including gram-positive organisms(39.2％)and gram-negative organisms(60.8％).The top three organisms were S.aureus(13.6％,1 453/10 688),A.baumannii(10.0％,1 067/10 688),and coagulase-negative Staphylococcus(9.9％,1 058/10 688).Multi-drug resistant organisms(MDROs)were very common in children.The prevalence of methicillin-resistant Staphylococcus aureus(MRSA),carbapenem-resistant Enterobacterales(CRE),carbapenem-resistant E.coli,carbapenem-resistant K.pneumoniae(CRKP),carbapenem-resistant A.baumannii(CRAB),and carbapenem-resistant P.aeruginosa(CRPA)was 41.1％,19.4％,8.8％,30.9％,67.4％,and 28.8％,respectively.Overall,more than 50％of Enterobacteriales isolates were resistant to cephalosporins,while nearly 25％of Enterobacteriales isolates were resistant to carbapenems.MDROs were highly resistant to commonly used antibiotics.More than 80％of CRE and CRAB strains were resistant to all beta-lactam antibiotics.CRE and CRAB showed low resistance rates to tigecycline and polymyxin.CRPA showed lower resistance rates to piperacillin,beta-lactamase inhibitor combinations than the resistance rates to third and fourth generation cephalosporins.All of the Staphylococcus and Enterococcus isolates were susceptible to vancomycin and tigecycline.None of PRSP strains isolated from meningitis and nonmeningitis samples were resistant to rifampicin,vancomycin,or linezolid.The prevalence of β-lactamase-negative ampicillin-resistant(BLNAR)strains was 43.3％in Haemophilus influenzae.Conclusions MDROs were prevalent in PICU.It is necessary to establish an effective multidisciplinary team(MDT)to control the antimicrobial resistance.

Objective To explore the effects of robot assisted training (RAT) combined with neural mobi-lization (NM) training on the recovery of upper limb functions in stroke patients. Methods A total of 110 stroke patients who met the inclusion criteria were selected as the subjects and randomly divided into a control group (n=28),RAT group (n=27),NM group (n=28),and combination group (n=27). All patients underwent routine upper limb occupational therapy. Additionally,the patients in the RAT group were treated with upper limb rehabilitation robots,those in the NM group underwent neural mobilization for treatment,those in the combination group were managed with robot-assisted training for upper limb rehabilitation and neural mobilization. Before treat-ment and 4 weeks after treatment,the modified Ashworth scale (MAS),Fugl-Meyer assessment upper extremity (FMA-UE),functional test for the hemiplegic upper extremity Hong Kong version (FTHUE-HK),and modified Barthel index (MBI) were used to assess the effects. The surface electromyographic signals of the biceps and triceps at the maximum isometric voluntary contraction (MIVC) position during elbow flexion and extension were measured,the integrated electromyographic values (iEMG) were recorded and the synergistic contraction rate (CR) was calculated. Results There was no statistically significant difference (P>0.05) between the four groups in the general information and pre-treatment assessments of MAS,FMA-UE,FTHUE-HK,MBI,iEMG,and CR. After 4 weeks,significant improvements were observed in all indicators compared to the pre-treatment assessments (P<0.05),with the exception of the triceps brachii CR,biceps brachii CR,and elbow extension MIVC biceps brachii iEMG in the control group.Among the group comparisons,all indicators showed statistically significant differences in mean or distribution (P<0.05),except for MAS and triceps brachii CR. The RAT group,NM group,and combination group all demonstrated significant improvements compared to the control group (P<0.05). Nota-bly,the combination group exhibited a greater degree of improvement than the RAT and NM groups. Conclusion RATcombined with NM can reduce upper limb muscle tone in stroke patients. This approacheffectively promotes the establishment of normal movement patterns,improve upper limb motor function,and enhance activities of daily living. This combination is effective and worthy of further clinical promotion and application.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Adenoid cystic carcinoma(ACC)of the cervix is a rare and highly aggressive subtype of cervical cancer,accounting for less than 1%of all cervical cancer cases.ACC predominantly affects postmenopausal women over the age of 60,with postmenopausal vaginal bleeding being the most common symptom.Diagnosis of ACC primarily relies on histopathological examination and immunohistochemical analysis.Although there is currently no standard treatment protocol,surgical resection combined with radiotherapy or concurrent chemoradiotherapy is considered to be an effective approach.However,the effectiveness is limited,particularly in advanced cases,which generally have a poor prognosis.The treatment and prognosis of ACC are closely related to tumor staging,perineural invasion,and margin status.This paper discusses the clinical data and follow-up of six ACC patients treated at our institution,and goes through a literature review,examines its clinical features and treatment outcomes,underscores the critical importance of early diagnosis and individualized treatment.

Depression is a highly heterogeneous psychiatric disorder with complex pathogenesis influenced by the interplay of biological,psychological,and social-environmental factors.Based on the 2021 edition of the Chinese Guidelines for the Prevention and Treatment of Depressive Disorders,which explicitly identify gender as a significant risk factor for depression onset,this paper systematically reviews the gender-differentiated pathogenesis and therapeutic advances in depression from both traditional Chinese medicine(TCM)and Western medical perspectives.In Western medicine,a large number of studies have demonstrated the sex-specific mechanism of estrogen/testosterone fluctuations and monoamine transmitter system regulation.While in TCM,although the constitution theory proposes that there are significant gender differences in congenital constitution and that qi depression and qi deficiency are associated with susceptibility to depression,current evidence primarily relies on cross-sectional surveys and lacks validation through high-quality RCTs.Compared with Western medicine,the direct research on gender-differentiated antidepressant effects in TCM remains relatively underdeveloped.In future study,it may be possible to deepen and improve the research on anti-depression in TCM from the biological markers of particular constitutions in the gender dimension.This paper advocates establishing a bio-psycho-social integrated intervention model,advancing mechanistic exploration through prospective cohort studies and multi-omics technologies,and promoting precision diagnosis and treatment systems based on gender differences,and to form a three-dimensional diagnosis and treatment and research system that covers biomarkers,social role assessment,and TCM constitution identification,in order to provide a new theoretical framework and a practical pathway for the precise medical treatment of depression.

Objective:To evaluate the value of ultrasound radiomics combined with machine learning for early diagnosis of seronegative Hashimoto’s thyroiditis (SN-HT) .Methods:This retrospective study included 164 patients from Liaoning Provincial People’s Hospital , Lixin County People’s Hospital, Linghai Dalinghe Hospital, Fengcheng Phoenix Hospital, who underwent thyroidectomy for solitary nodules with normal thyroid function between Nov. 2016 and Jan. 2024. Postoperative pathology confirmed Hashimoto’s thyroiditis (HT) in some cases, who were further categorized into antibody-positive and antibody-negative groups based on serum antibody status. Patients without Hashimoto’s thyroiditis served as the control group. A total of 298 ultrasound images were analyzed. Radiomics features were extracted from hypoechoic non-nodular areas within 0.5 cm surrounding the tumor. Two senior pathologists and two senior ultrasound physicians independently assessed lymphocytic infiltration, eosinophilic changes of follicular epithelium, and the proportion of hypoechoic areas in pathology and ultrasound images, respectively. A machine learning model, CCH-NET, was developed using linear regression and t-distributed stochastic neighbor embedding (t-SNE) techniques. The dataset was divided into a training set (80%) and a validation set (20%) to compare the diagnostic accuracy of CCH-NET with that of senior ultrasound physicians. Results:In internal validation, CCH-NET achieved a diagnostic accuracy of 88.89% for both antibody-positive and antibody-negative groups, significantly higher than the 66.67% accuracy of senior ultrasound physicians ( P<0.01). In external validation, CCH-NET achieved 75.00% and 66.67% accuracy for the two groups, compared to 50.00% by senior ultrasound physicians. For the control group, both methods achieved 93.33% accuracy. The AUC of CCH-NET was 0.848, outperforming senior ultrasound physicians (0.681) ,demonstrating superior diagnostic performance. Conclusion:The radiomics-based CCH-NET model, using non-nodular hypoechoic areas as a specific indicator, can accurately identify early SN-HT in euthyroid patients. It significantly outperforms senior ultrasound physicians, improving diagnostic accuracy and reducing missed diagnoses.

Objective:To evaluate the feasibility and preventive efficacy of a fascia- locking circular continuous suture ostomy technique in reducing parastomal hernia incidence.Methods:This technique was applied to patients undergoing permanent colostomy following radical rectal cancer resection. Surgical steps included: (1) A circular incision was made 1-2 cm medial to the intersection of the lateral margin of the rectus abdominis muscle and the line connecting the umbilicus to the left anterior superior iliac spine. Subcutaneous tissues were dissected vertically to expose the anterior rectus sheath, followed by blunt separation of the rectus abdominis after longitudinal incision of the sheath. The posterior rectus sheath and peritoneum were similarly incised. (2) Eight equidistant interrupted sutures (anchoring knots) were placed through the anterior rectus sheath, partial rectus abdominis, posterior rectus sheath, and peritoneum. (3) The terminal colon was exteriorized, and continuous sutures were applied to secure the anchoring knots and seromuscular layers of the bowel between knots, forming a circular locking mechanism by tying the terminal suture to the initial knot's tail. (3) The skin and seromuscular layers of the bowel margin were intermittently sutured (8-12 stitches) to achieve mucosal eversion.Results:From February to October 2023, 13 patients (11 males, 2 females; age: 67 ± 10 years; BMI: 23.8 ± 4.0 kg/m2) underwent this technique at the Second Affiliated Hospital of Army Medical University. Mean stoma creation time was 15.7 ± 3.0 minutes. During a follow-up of 14.6 ± 3.1 months, physical examinations and abdominal CT scans identified parastomal hernias in 2 male patients at 10 and 7 months postoperatively. Only one patient experienced a Clavien-Dindo grade ≥Ⅲ complication, which resolved with treatment. No stoma-related complications (e.g., infection, stenosis, or prolapse) occurred in any patient.Conclusion:The fascia-locking circular continuous suture ostomy technique is safe and feasible, demonstrating potential efficacy in preventing parastomal hernia following colostomy.

Objective To observe the value of changes of neutrophil-to-lymphocyte ratio(NLR)before and after the first interventional treatment of hepatocellular carcinoma(HCC)for predicting patient's overall survival(OS).Methods Totally 92 HCC patients who underwent the first time TACE or TACE+hepatic artery infusion chemotherapy(HAIC)were retrospectively enrolled.The patients were divided into NLR ratio(NLRR)＜1.29 group(n=54)and≥1.29 group(n=38)based on the ratio of NLR after to before treatment,also ΔNLR＜0.87 group(n=60)and≥0.87 group(n=32)based on the difference of NLR after and before treatment.Clinical data were compared between groups,survival analysis was performed,and the value of NLRR and ΔNLR for predicting OS were analyzed.Results No significant difference of clinical data was found between NLRR＜1.29 and≥1.29 groups,nor between ΔNLR＜0.87 and≥0.87 groups(all P＞0.05).The median OS of 92 patients was 30.90 months,which in NLRR＜1.29 group(55.10 months)was longer than that in NLRR≥1.29 group(22.30 months,P=0.005),while in ΔNLR＜0.87 group(55.10 months)was longer than that in ΔNLR≥0.87 group(14.20 months,P=0.003).Cox regression analysis showed that the maximum diameter of tumor≥5 cm,distant metastasis,ascites,NLRR≥1.29 and ΔNLR≥0.87 were all independent risk factors of OS(all P＜0.05).Taken 1.29 and 0.87 as the best cut-off value,respectively,the area under the curve of NLRR and ΔNLR for predicting OS was 0.620 and 0.610,respectively.Conclusion NLRR and ΔNLR were helpful for predicting OS of HCC patient after the first interventional treatment.