ObjectiveThis paper aims to investigate the efficacy and related actions of Guizhi Fulingwan in intervening in the mice with colitis-associated colon cancer （CAC） based on the immunosuppressive microenvironment associated with myeloid-derived suppressor cells （MDSCs）. MethodsSixty male C57BL/6 mice were randomly assigned to a blank group， a model group， an aspirin group （0.04 g·kg^-1）， and low-， medium-， and high-dose Guizhi Fulingwan groups （4.87， 9.75， and 19.50 g·kg^-1）， with ten mice per group. The CAC mouse model was established via combined induction of azoxymethane （AOM）/dextran sulphate sodium （DSS）. Drug intervention commenced in week five， with continuous intragastric administration for nine weeks. The food intake， body weight， fecal characteristics， and haematochezia were observed and recorded， and disease activity index （DAI） scores were calculated according to scoring criteria. Hematoxylin and eosin （HE） staining was used to observe the histopathological changes in the colon tissues of the mice. Immunohistochemistry was used to determine proliferating cell nuclear antigen-67 （Ki67） expression in the colon tissues， and enzyme-linked immunosorbent assay （ELISA） was used to detect the contents of interleukin-6 （IL-6）， IL-1β， and tumor necrosis factor-α （TNF-α） in the serum of the mice. Flow cytometry was employed to determine the proportion levels of MDSCs， CD4⁺ T cells， and CD8⁺ T cells in the spleen tissues of the mice. The mRNA expressions of MDSC-associated effector molecules， including arginase 1 （Arg1） and inducible nitric oxide synthase （iNOS）， were detected by real-time quantitative polymerase chain reaction （Real-time PCR）. After that， an in vitro co-culture model of MDSCs and CD8⁺ T cells was established， and drug-containing serum of Guizhi Fulingwan was used for intervention. The Flow cytometry was employed to assess the effects of drug-containing serum of Guizhi Fulingwan with different concentrations on the levels of reactive oxygen species （ROS） and iNOS in MDSCs and the proliferation of CD8⁺ T cells. The levels of granzyme B （GZMB） and interferon-γ （IFN-γ） in cell supernatant were detected by ELISA. ResultsCompared with those in the control group， the mice in the model group exhibited significantly reduced body weight， elevated DAI scores， shortened colon length （P<0.01）， increased number of tumors and Ki67 expression （P<0.01）， and significantly elevated contents of IL-6， IL-1β， and TNF-α in the serum （P<0.01）. Significant increases in the number of MDSCs were observed in mouse spleens， alongside marked reductions in the levels of CD4⁺ T and CD8⁺ T cells （P<0.01）. Furthermore， the mRNA expressions of MDSC function-associated effector molecules Arg1 and iNOS were significantly upregulated （P<0.01）. Compared with those in the model group， the mice in the middle-dose Guizhi Fulingwan group exhibited increased body weight and significantly decreased DAI scores （P<0.05， P<0.01）. The mice in the middle- and high-dose Guizhi Fulingwan groups exhibited significantly improved colon shortening， significantly decreased number of tumors and Ki67 expression （P<0.05， P<0.01）， and significantly decreased contents of IL-6， IL-1β， and TNF-α in the serum （P<0.05， P<0.01）. Furthermore， administration of Guizhi Fulingwan markedly reduced MDSC infiltration in the spleen of the mice， with different degrees of increase in the levels of both CD4⁺ T and CD8⁺ T cells （P<0.05， P<0.01）， alongside significant decreases in the mRNA expressions of Arg1 and iNOS （P<0.05， P<0.01）. In vitro cell co-culture shows that administration of drug-containing serum of Guizhi Fulingwan significantly decreases the activity levels of ROS and iNOS in MDSCs and promotes the proliferation of CD8⁺ T cells and the secretion of GZMB and IFN-γ （P<0.05， P<0.01）. ConclusionGuizhi Fulingwan can reduce pro-inflammatory cytokine secretion and inhibit tumor proliferation in the colon tissues of CAC mice. Its potential mechanism may involve reducing MDSC infiltration， enhancing effector T cells， particularly CD8⁺ T cell response， and improving the tumor immunosuppressive microenvironment.

With the rapid development of generative artificial intelligence(GAI)technologies,their widespread application in academic research and writing is continuously expanding the boundaries of sci-entific inquiry.However,this trend has also raised a series of ethical and regulatory challenges,inclu-ding issues related to authorship,content authenticity,citation accuracy,and accountability.In light of the growing involvement of AI in generating academic content,establishing an open,controllable,and trustworthy ethical governance framework has become a key task for safeguarding research integrity and maintaining trust within the academic community.This expert consensus outlines ethical requirements across key stages of AI-assisted academic writing-including topic selection,data management,citation practices,and authorship attribution.It aims to clarify the boundaries and ethical obligations surrounding AI use in academic writing,ensuring that technological tools enhance efficiency without compromising in-tegrity.The goal is to provide guidance and institutional support for building a responsible and sustainable research ecosystem.

Objective To compare the predictive performance of the deep forest ensemble model,deep forest,and random forest in medical classification.Methods This study proposed a deep forest ensemble model that integrated Sobol-MDA(Sobol-mean decrease accuracy)with the cascading structure of deep forest and feature extraction capabilities of random forest.The model was applied to both simulation and real medical data analysis.The simulation experiments covered scenarios such as unbalanced outcome variables,nonlinear relationships,noise variables,multicollinearity,and interactions.The real data analysis was conducted on parotid MRI data to compare the performance of the models in terms of area under curve(AUC)and other metrics.Results In both the simulation and real data analysis,the deep forest ensemble model demonstrated superiority,especially in complex interaction scenarios,where its predictive performance significantly outperformed deep forest and random forest models.Conclusion Deep forest ensemble model shows significant advantages in addressing complex medical classification tasks.Its predictive performance outperforms traditional models.

Objective:To analyze the development trend of medical institution bed allocation in OECD countries and provide insights for optimizing bed resources allocation in China.Methods:Data on indicators of bed allocation and related factors from 1991 to 2022 were collected from the OECD online database.Bed allocation impact dimensions were identified based on health needs and demand theories.The random effect model and correlation analysis were used to explore influencing pathways of bed allocation.Results:The number of beds per 1 000 population and average life expectancy showed a significant positive correlation in countries below the average bed level,while an inverse trend was observed in countries above the average level.The number of long-term care beds per 1000 population showed positive correlation with average life expectancy.Multidimensional factors such as the disease spectrum and bed utilization efficiency were significant correlated with the bed allocation levels.The greater the gap in inpatient and outpatient reimbursement rations,the higher the demand for hospitalization among patients with chronic disease.Conclusions:An optimal number of beds is essential for achieving higher health outcomes.The bed classification planning system should be designed to adapt to demographic changes and strengthen the medical security support system.

In recent years,the incidence of heat-related diseases has been on a steady upward trend,which is closely associated with environmental factors such as climate change and air pollution.Exposure to a hot environment and/or strenuous physical activities can progress to heat stroke(HS),an acute disease that can lead to death.Current research indicates that gut injury occupies the most crucial initiating position in the pathophysiological changes and pathogenesis of HS.Probiotics can reduce the incidence and mortality of HS through maintaining the health of the gut microbiota,regulating the intestinal immune system,and other effects.In addition,the gut microbiota can construct axis systems to interact with multiple organs such as the liver,lungs,and brain,which is of great significance for alleviating the damage to distant organs caused by HS.This paper reviews the regulation of the gut microbiota by probiotics to improve the intestinal heat tolerance ability and barrier function,aiming to provide references for the prevention and treatment of heat stroke in clinical practice.

Objective To construct an intelligent segmentation and T-stage diagnostic model for esophageal cancer based on the DAEUnet and ConvNeXt networks using transfer learning.Methods Dicom raw data from 126 patients diagnosed with esophageal cancer between January 2018 and April 2022 were collected,including 100 cases from Department of Thoracic Surgery at the First Affiliated Hospital of Army Medical University and 26 cases from the Department of Thoracic Surgery at Shanxi Cancer Hospital.After data augmentation,a total of 60 275 images were obtained.The DAEUnet esophageal cancer intelligent segmentation network was built,and on this basis,3 classification networks,ConvNeXt,Swin Transformer,and ResNet were constructed for T-stage diagnosis of esophageal cancer.Results The Dice similarity coefficient(DSC)for esophageal cancer intelligent segmentation using the DAEUnet network was 0.82,and the DSC value of the esophagus,aorta,normal esophagus,mediastinal lymph nodes,and heart was 72.4％,87.5％,79.3％,60.5％ and 96.8％,respectively.Among the 3 T-stage diagnosis models for esophageal cancer,the ConvNeXt model performed the best,with a precision value for T1～T4 stages of 0.65,0.727,0.889 and 0.92,respectively,and an AUC value of 0.892,which were superior to the ResNet and Swin Transformer networks.Conclusion The proposed DAEUnet and ConvNeXt-based intelligent segmentation and T-stage diagnosis model for esophageal cancer improves T-stage accuracy and treatment efficiency.

AIM To establish the quantitative models for gallic acid,mononucleoside,loganin,resveratrol,and rhein in Yishen Xiezhuo Mixture.METHODS HPLC was adopted in the content determination of various effective components,after which the near-infrared spectroscopy(NIRS)data were collected in 128 batches of samples and pretreatment was conducted,competitive adaptive reweighting sampling(CARS)algorithm was used for screening wavelength,partial least square method(PLS)regression analysis was performed.RESULTS There were no significant differences between the predicted values obtained by PLS models and measured values obtained by HPLC for various effective components(P＞0.05).CONCLUSION The quantitative models established by NIRS combined with chemometrics display good predictive performance,which can be used for the rapid determination of effective components in Yishen Xiezhuo Mixture,and provide a reference for the rapid monitoring of other traditional Chinese medicine preparations in production processes.

Objective To investigate the value of ultrasound for differentiating pancreatoblastoma(PB)and solid pseudopapillary tumor of pancreas(SPT)in children.Methods Data of 7 children with PB(PB group)and 22 with SPT(SPT group)were retrospectively analyzed.The clinical data and lesion's ultrasonic manifestations were compared between groups.Receiver operating characteristic(ROC)curves of clinical and ultrasound related parameters being significantly different between groups showed by univariate analysis were draw,and the area under the curve(AUC)were calculated to evaluate their efficacy for differentiating PB and SPT.Ultrasound parameters with P＜0.05 in univariate analysis were incorporated into binary logistic analysis,and a ultrasound regression model was constructed to distinguish PB and SPT,and its diagnostic efficacy was evaluated.Results Significant differences of children'age,gender,serum alpha fetoprotein level,and the shape,maximum diameter,texture,calcification and local invasion of lesions were found between groups(all P＜0.05).AUC of single serum alpha fetoprotein level,the shape,maximum diameter,texture,calcification and local invasion of lesion for differentiating PB and SPT was 1.000,0.766,0.854,0.776,0.789 and 0.714,respectively(all P＜0.05).The shape(OR=8.704,P=0.075)and maximum diameter of lesions(OR=1.695,P=0.042)showed with ultrasound were both important differentiating factors for PB and SPT,and AUC of the ultrasound regression model constructed based on them was 0.886.Conclusion Ultrasound could effectively differentiate PB and SPT in children.

Objective:To evaluate the effectiveness and safety of belumosudil for the treatment of chronic graft-versus-host disease (cGVHD) .Methods:We retrospectively collected data on patients with cGVHD who received belumosudil at Ruijin Hospital Affiliated to Shanghai Jiaotong University School of Medicine from May 2023 to March 2024. The study endpoints were overall response rate (ORR), organ-specific response rates, time to response (TTR), changes in Lee Symptom Scale (LSS) scores, tapering or discontinuation of corticosteroid treatment, failure-free survival (FFS), and adverse events.Results:The study included 20 patients with cGVHD who received belumosudil, of whom 15 were men and 5 women. The median age was 34.5 (12-67) years, and three patients were under 18 years old. The median follow-up duration was 5.0 (1.4 - 9.8) months. All patients had severe cGVHD, and 18 (90.0%) showed involvement of at least four organs. The median number of prior treatment lines was 4, and 15 patients (75%) had previously received ruxolitinib. All patients received 200 mg of belumosudil once daily in combination with other cGVHD systemic therapies. The ORR was 90.0% (95% CI: 68.3%-98.8%), and all responses were partial responses. The median TTR was 1.6 (0.9 - 8.4) months. The LSS scores improved in a clinically meaningful way in 80.0% (16/20) of the patients within 3 months. The corticosteroid dose was reduced in 42.6% (6/14) of the patients. The 3-month FFS was 79.6% (95% CI: 61.4%-100.0%). Most adverse events were grade 1 or grade 2, and two patients (10.0%) experienced grade 3 or higher-grade adverse events. Conclusions:In the real-world setting, belumosudil demonstrated good effectiveness and safety in patients with cGVHD with a history of severe disease and multiorgan involvement.

Based on the concept of"two-stage,four-phase,and three-phase treatments"of in vitro fertilization and embryo transfer(IVF-ET)assisted the whole-course management of TCM by national TCM master You Zhaoling,this article analyzed the treatment strategy assisted by acupuncture in five aspects:principle,method,prescription,acupoint,and technique.Principle:syndrome differentiation and treatment follow different cases;method establish guiding methods based on principles,while following stage diagnoses and treatments;prescription:determine the prescriptions based on therapeutic principles within the context of overall regulation;acupoint:precise acupoint taking and rational acupoint matching;technique:the primary method is acupuncture,supported by various therapeutic modalities,providing a comprehensive framework and evidence-based support for the clinical application of acupuncture and moxibustion in IVF-ET.