Ulcerative colitis （UC）， a chronic nonspecific inflammatory bowel disease characterized by unclear etiology， complex contributing factors， and a refractory course with malignant transformation potential， imposes a substantial burden on both individual patients and healthcare systems. There is an urgent need to explore effective therapeutic strategies and pharmacological interventions. Professor LIU Zhen， based on years of clinical practice， proposed a dynamic pathogenesis chain of UC： Spleen deficiency with dampness excess as the foundation， dampness obstruction as the nexus， stasis-toxin interaction as the key， and stasis-toxin damaging intestinal collaterals as the terminal outcome. The treatment， following the progression of deficiency （depression）-dampness-toxin-stasis （toxin）， should focus on invigorating the spleen and resolving dampness. A stage-specific treatment approach is emphasized. During the susceptible stage， prevention is recommended， which relies on regulating the diet， maintaining a positive mental state， and adjusting daily routines to invigorate the spleen and replenish Qi. During the acute attack and remission stages， the treatment should be tailored according to clinical typing and disease severity， flexibly employing therapeutic strategies such as tonifying deficiency， resolving depression， eliminating dampness， clearing heat， detoxifying， arresting bleeding， and resolving stasis in order to interrupt disease progression. In the recovery stage， latent pathogenic factors should be addressed while the postnatal constitutional foundation be preserved to prevent recurrence. According to the TCM principle of treating disease before its onset， a whole-course management path of early protection-interception-stratified care-consolidation has been developed， covering all stages of UC， to inform its clinical prevention and treatment.

Objectives:To explore whether short-course radiotherapy (SCRT)-based total neoadjuvant therapy (TNT) combined with PD-1 inhibitors could further promote tumor regression and improve the prognosis.Methods:This is a prospective, multicenter, two-arm randomized controlled, seamless phase Ⅱ/Ⅲ trial for proficient mismatch repair or microsatellite stable (pMMR/MSS) locally advanced rectal cancer (LARC). Eligible patients were randomly assigned to the iTNT (TNT+PD-1) group or the TNT group. Patients in the TNT group received SCRT (5 Gy×5) followed by 4 cycles of CAPOX or 6 cycles of mFOLFOX chemotherapy, with the iTNT group receiving SCRT followed by the same regime in combination with 4 cycles of Sintilimab. Total mesorectal excision (TME) surgery or watch and wait (W&W) was performed after neoadjuvant therapy and then 2 cycles of same regimen as before were recommended. The primary endpoints are the complete response (CR) rate for phase Ⅱ trial and 3-year disease-free survival (DFS) for phase Ⅲ trial. A total of 588 patients will be enrolled for the phase Ⅱ/Ⅲ trial. Short-term efficacy and safety data from the initial 100 treated patients were analyzed as planned.Results:From 2022-8-31 to 2023-5-24 the initial 100 patients were enrolled from 10 hospitals in China, 76.0%(76/100) patients were male, and the median age was 61 years (21-74 years). More patients had tumors located in the lower rectum (78.0%, 78/100), staged T3-4 (97.0%, 97/100) and N1-2 (93.0%, 93/100), and about half of the tumors invaded the mesorectal fascia (52.0%, 52/100) and with extramural vascular invasion (51.0%, 51/100). Analyses were performed according to the per-protocal (PP) set. All patients in the iTNT group ( n=52) and the TNT group ( n=48) completed SCRT; The 4-cycle chemotherapy±Sintilimab completion rates were 86.5% and 100.0% in the iTNT and TNT groups, respectively. In the iTNT group, 82.7% (43/52), 11.5% (6/52), and 5.8% (3/52) of the patients received 4, 3, and 2 cycles of PD-1 inhibitor. After TNT, 68 patients underwent radical surgery and 15 patients achieved cCR and adopted W&W. The pathological complete response (pCR) rates were 48.5% (16/33) and 17.1% (6/35) in the iTNT and TNT groups, with CR rates of 50.0% (25/50) and 26.1% (12/46), respectively. The incidence of treatment-related grade 3-4 adverse events was 26.9% (14/52, iTNT group) and 18.8% (9/48, TNT group), with thrombocytopenia and leukopenia being the most common. Among patients receiving immunotherapy, grade 3 immunotherapy-related adverse events occurred in 2 (3.8%, 2/52) patients: one case was pancreatitis, another case was hepatitis combined with myositis and myocarditis. Conclusion:The preliminary results show that SCRT-based TNT combined with PD-1 inhibitors could further improve the CR rate for LARC without unexpected serious adverse events.

Background and Purpose:Previous studies have investigated the prognostic significance of skeletal muscle and adipose tissue composition and distribution in colorectal cancer patients,yet most have not differentiated between rectal and colon cancer patient cohorts.This study aimed to explore the relationship between body composition and long-term prognosis,and to develop a postoperative predictive model.Methods:Clinical data of rectal cancer patients who underwent surgical treatment at Qingdao University Affiliated Hospital from January 2018 to December 2021 were retrospectively collected.Inclusion criteria:①Age＞18 years;② Preoperative colonoscopy and pathological diagnosis of colorectal cancer;③ Complete surgical resection;④Abdominal computed tomography(CT)scan 1 month before surgery.Exclusion criteria:① Clinical data is missing;② Multiple metastases of tumors;③ Tumor T stage 0 or carcinoma in situ;④ Severe artifacts lead to poor quality CT imaging,making it difficult to distinguish between fat and muscle;⑤ Inability to obtain follow-up results.This study has been approved by the Medical Ethics Committee of the Affiliated Hospital of Qingdao University(approval number:QYFYWZLL30313),and informed consent has been waived in the ethical approval process.The skeletal muscle index(SMI)and subcutaneous adipose tissue index(SATI)were calculated by dividing the areas of skeletal muscle and subcutaneous fat observed on CT scans by the square of the patient's height.Univariate and multivariate COX regression analyses were conducted to identify risk factors influencing recurrence-free survival(RFS)and overall survival(OS)in rectal cancer patients.Based on the results of the multivariate analysis,a nomogram prediction model was developed,its predictive power and accuracy were assessed using the receiver operating characteristic(ROC)curve,calibration plots and decision curve analysis(DCA),and internal validation was conducted.Results:A total of 696 patients were included in this study,with 96(13.8%)patients experiencing postoperative recurrence and 89(12.8%)patients dying.Multivariate COX regression analysis showed that SMI,SATI,tumor T stage and N stage were independent factors affecting the postoperative RFS and OS of patients.Nomogram prediction models for RFS and OS in rectal cancer patients were constructed based on the above independent predictors.The area under ROC curve(AUC)for 3-,4-and 5-year RFS was 0.862,0.846 and 0.824,respectively;the AUC for 3-,4-and 5-year OS was 0.886,0.898 and 0.875,respectively.The models were evaluated using calibration curves and decision curves,and internal validation was performed,which showed that the prediction accuracy of the models was good.Conclusion:CT body composition is an independent predictor of RFS and OS in rectal cancer patients,and the nomogram model developed based on these factors demonstrates good predictive value for patient prognosis.

Objective:To explore the interrelationship between brain functional networks and features in functional magnetic resonance imaging(fMRI)of patients with Alzheimer's disease(AD),and to construct mixed-function networks(MFN),and apply them in machine learning classification models to improve the accuracy of AD classification.Methods:102 AD patients and 227 healthy subjects in the Alzheimer's Neuroimaging Initiative(ADNI)dataset were retrospectively analyzed.The partial correlation brain network of the blood oxygen level dependent(BOLD)signal was calculated and fused with low-frequency wave amplitude(ALFF),fractional low-frequency wave amplitude(fALFF)and local consistency(ReHo)features to construct MFN.Network topology parameters were extracted,and a variety of machine learning classification models were constructed based on MFN topological parameters,accuracy,precision,recall and area under the curve(AUC)were used to evaluate the predictive efficiency of the models.Results:By constructed MFN and calculated intra group to inter group ratio(IIGR),35 features could be obtained from ALFF,fALFF and ReHo feature topological parameter analysis,after rank sum test and FDR correction,there were statistical differences among 28 features(P＜0.05).The classification results show that,all the five classifiers have high classification performance on the test data set.The accuracy,precision and recall rates of random forest(RF),adaptive lifting algorithm(AdaBoost),guided aggregation algorithm(Bagging)and support vector machine(SVM)were all 99.7％,and the AUC values were up to 100％,99.5％,99.1％and 99.5％,respectively.The accuracy(98.5％),precision(98.5％),recall(98.5％),and AUC(99.1％)of the multi-layer perceptron(MLP)were slightly lower than other models,but remained excellent.It was worth noting that RF has the highest AUC value of all models at 100.0％,while Bagging has the lowest AUC value(99.1％)in the integrated approach.The results of performance comparison show that,MFN classification model can significantly improve the recognition and classification of AD disease,and greatly improve the performance of various indicators of the classifier.The results showed that,MFN classification model was superior to intelligent classification based fusion,DBN-based multitask learning,PVT-TSVM,unsupervised learning and clustering,SVM and SVM of degree 3 polynomial kernel function in key indicators such as accuracy(99.13％),AUC(99.42％),recall rate(99.46％)and specificity(99.42％)with plasma proteins,machine learning algorithms.It was further proved that MFN classification model has good generalization ability and robustness in AD disease classification.Conclusion:The AD classification model constructed based on brain mixed function network topology parameters and machine learning can improve the accuracy of AD classification.

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.

Background and Purpose:Previous studies have investigated the prognostic significance of skeletal muscle and adipose tissue composition and distribution in colorectal cancer patients,yet most have not differentiated between rectal and colon cancer patient cohorts.This study aimed to explore the relationship between body composition and long-term prognosis,and to develop a postoperative predictive model.Methods:Clinical data of rectal cancer patients who underwent surgical treatment at Qingdao University Affiliated Hospital from January 2018 to December 2021 were retrospectively collected.Inclusion criteria:①Age＞18 years;② Preoperative colonoscopy and pathological diagnosis of colorectal cancer;③ Complete surgical resection;④Abdominal computed tomography(CT)scan 1 month before surgery.Exclusion criteria:① Clinical data is missing;② Multiple metastases of tumors;③ Tumor T stage 0 or carcinoma in situ;④ Severe artifacts lead to poor quality CT imaging,making it difficult to distinguish between fat and muscle;⑤ Inability to obtain follow-up results.This study has been approved by the Medical Ethics Committee of the Affiliated Hospital of Qingdao University(approval number:QYFYWZLL30313),and informed consent has been waived in the ethical approval process.The skeletal muscle index(SMI)and subcutaneous adipose tissue index(SATI)were calculated by dividing the areas of skeletal muscle and subcutaneous fat observed on CT scans by the square of the patient's height.Univariate and multivariate COX regression analyses were conducted to identify risk factors influencing recurrence-free survival(RFS)and overall survival(OS)in rectal cancer patients.Based on the results of the multivariate analysis,a nomogram prediction model was developed,its predictive power and accuracy were assessed using the receiver operating characteristic(ROC)curve,calibration plots and decision curve analysis(DCA),and internal validation was conducted.Results:A total of 696 patients were included in this study,with 96(13.8%)patients experiencing postoperative recurrence and 89(12.8%)patients dying.Multivariate COX regression analysis showed that SMI,SATI,tumor T stage and N stage were independent factors affecting the postoperative RFS and OS of patients.Nomogram prediction models for RFS and OS in rectal cancer patients were constructed based on the above independent predictors.The area under ROC curve(AUC)for 3-,4-and 5-year RFS was 0.862,0.846 and 0.824,respectively;the AUC for 3-,4-and 5-year OS was 0.886,0.898 and 0.875,respectively.The models were evaluated using calibration curves and decision curves,and internal validation was performed,which showed that the prediction accuracy of the models was good.Conclusion:CT body composition is an independent predictor of RFS and OS in rectal cancer patients,and the nomogram model developed based on these factors demonstrates good predictive value for patient prognosis.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Objective:To analyze the molecular characteristics of prevalent Bordetella pertussis (Bp) isolates in Liaocheng City, Shandong Province in 2024. Methods:From March to August 2024, oropharyngeal swabs were collected from suspected pertussis cases at Liaocheng People′s Hospital in Shandong Province for Bp isolation. A total of 99 Bp isolates were obtained. Whole-genome sequencing was performed on all isolates, followed by Multilocus Sequence Typing (MLST), vaccine antigen-related gene typing (including ptxP, ptxA, ptxB, ptxC, ptxD, ptxE, fhaB, fim2, fim3, and prn), 23S rRNA gene typing, and phylogenetic analysis. To capture the differences between Bp isolates and vaccine strains in Liaocheng City, the international vaccine strain Tohama I and the Chinese vaccine strain CS were included in the analysis. Antimicrobial resistance testing against 11 agents was performed on 52 isolates. Results:The throat swabs of 99 Bp isolates were collected from patients aged 44 days to 42 years, and the median age of the patients was 7 (5, 8) years. All isolates ptxP were ptxP3 type. 74 isolates (74.75%) carried the prn150, while 21 isolates (21.21%) were prn-deficient. The predominant antigenic profile was ptxP3/ ptxA1/ ptxB1/ ptxC4/ ptxD1/ ptxE4/ fhaB1/ fim2-1/ fim3-1/ prn150, found in 72 isolates (72.73%). All 99 isolates carried the A2047G mutation in the 23S rRNA gene. Antimicrobial susceptibility testing showed that the MICs of macrolides and clindamycin for all 52 Bp isolates were all >256 mg/L. However, the isolates showed low MIC for seven other antimicrobials tested, including trimethoprim-sulfamethoxazole, amoxicillin, and levofloxacin. MLST typing revealed that 94 isolates (94.95%) were identified as ST-2, while 5 isolates (5.05%) belonged to a novel sequence type (ST-118). Phylogenetic analysis demonstrated that all 99 Bp isolates were highly homologous but clustered in evolutionary branches distinct from vaccine strains. Conclusion:In 2024, Bordetella pertussis isolates in Liaocheng City exhibit distinct clonal epidemic characteristics, with the predominant antigenic genotype being ptxP3/ ptxA1/ ptxB1/ ptxC4/ ptxD1/ ptxE4/ fhaB1/ fim2-1/ fim3-1/ prn150. All isolates are resistant to macrolide antibiotics.

Objective: To evaluate the application of blood conservation measures in obstetric patients with different red blood cell transfusion volumes and to assess the impact of different transfusion volumes on postpartum outcomes. Methods: A retrospective investigation was conducted on 448 obstetric patients who received blood transfusions at the Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine from January 2016 to December 2022. Patients were divided into four groups (1-2 units group, 3-4 units group, 5-6 units group, and >6 units group) based on the volumes of red blood cells (RBCs) transfused during and within 7 days after delivery. The maternal physiological indicators, pre- and postpartum laboratory test indicators, obstetric complications, application of blood conservation measures, use of blood products, and postpartum outcomes were reviewed. The clinical characteristics, application of blood conservation measures, and their impact on postpartum outcomes were compared among different transfusion groups. Results: There were statistically significant differences in the multivariate logistic analysis of history of previous cesarean section (OR=1.781), eclampsia/pre-eclampsia/(OR=1.972) and postpartum blood loss>1 000 mL（OR=1.699）(P<0.05) among different transfusion groups. In terms of blood conservation measures, the more RBCs transfused, the higher the rate of mothers receiving blood conservation measures such as balloon occlusion, arterial ligation, autologous blood transfusion with a cell saver, and hysterectomy. With the increase in the volume of RBCs transfusion, the demand for fresh frozen plasma（FFP）, cryoprecipitate, and platelet transfusions also increased. The hospitalization days for the four groups of parturients were 6.0 (4.0-9.0), 7.5 (5.0-14.8), 7.0 (4.5-13.0) and 11.0 (9.0-20.5), respectively (P<0.05) and the rates of ICU transfer were 2.0% (5/250), 9.4% (12/128),18.2% (6/33) and 51.4% (19/37), respectively (P<0.05). Both increased significantly with the increase in the volume of RBCs transfusion, and the differences between groups were statistically significant. Conclusion: Parturients who received higher volume of RBCs had multiple risks factors for bleeding before childbirth, had higher postpartum blood loss, and had a higher rate of application of various blood conservation measures. In addition, an increase in the volume of RBCs transfusion may have adverse effects on postpartum recovery.

The scientific interpretation of the theory of medicinal properties of TCM is a research hotspot in the modernization of TCM. It is of great value to clarify the property and degree of cold and heat in Chinese materia medica for guiding clinical precise medication. In recent years, the research on the cold and heat properties of Chinese materia medica has been carried out at the animal, cell and molecular levels. Based on the objective material basis of medicinal properties, from the perspective of biological effects such as thermodynamics and multiomics; with the help of infrared thermal imaging and other technologies for analysis; forming a variety of research models such as "property-structure relationship". Related research has developed from a single material component or index to a new model that tends to integrate multi-source information and multi-dimensional data. However, how to deal with the problems of large sample size, strong redundancy, high heterogeneity, and how to integrate multi-dimensional information are still research difficulties. With its powerful computing and learning ability, machine learning can show good discrimination and prediction ability in the study of cold and hot properties of Chinese materia medica, and play an important role in the study of cold and hot properties of Chinese materia medica. At present, the most widely used algorithms are linear discriminant analysis, Logistic discriminant analysis, support vector machine, decision tree, random forest and so on. The data dimension of the existing research needs to be enriched, the algorithm has room for further optimization, and a more detailed discriminant model of cold and hot properties of Chinese materia medica needs to be established.