Colorectal cancer(CRC) is one of the most common malignant tumors worldwide, primarily originating from recurrent inflammatory bowel disease(IBD). Therefore, blocking the inflammation-cancer transformation in the colon has become a focus in the early prevention and treatment of CRC. The inflammation-cancer transformation in the colon involves multiple types of cells and complex pathological processes, including inflammatory responses and tumorigenesis. In this complex pathological process, immune cells(including non-specific and specific immune cells) and non-immune cells(such as tumor cells and fibroblasts) interact with each other, collectively promoting the progression of the disease. In traditional Chinese medicine(TCM), inflammation-cancer transformation in the colon belongs to the categories of dysentery and diarrhea, with the main pathogenesis being cold and heat in complexity. This paper first elaborates on the complex molecular mechanisms involved in the inflammation-cancer transformation process in the colon from the perspectives of inflammation, cancer, and their mutual influences. Subsequently, by comparing the pathogenic characteristics and clinical manifestations between inflammation-cancer transformation and the TCM pathogenesis of cold and heat in complexity, this paper explores the intrinsic connections between the two. Furthermore, based on the correlation between inflammation-cancer transformation in the colon and the TCM pathogenesis, this paper delves into the importance of the interaction between inflammation and cancer. Finally, it summarizes and discusses the clinical and basic research progress in the TCM intervention in the inflammation-cancer transformation process, providing a theoretical basis and treatment strategy for the treatment of CRC with integrated traditional Chinese and Western medicine.
Humans ; Colon/pathology* ; Integrative Medicine ; Animals ; Cold Temperature ; Cell Transformation, Neoplastic/drug effects* ; Medicine, Chinese Traditional ; Hot Temperature ; Inflammation ; Drugs, Chinese Herbal/therapeutic use* ; Colonic Neoplasms/drug therapy*

Objective:Analysis of the composition of pathogen spectrum and prevalence characteristics in throat swabs of patients with acute respiratory infections (ARI) in Yucheng city, Henan province, from March to June 2023.Methods:After 1 153 throat swabs were collected from ARI patients in Yucheng, 18 respiratory pathogens were tested using a real-time fluorescence quantitative polymerase chain reaction (qPCR) method. The characterization of pathogens spectrum was analyzed.Results:A total of 1 153 throat swabs from ARI patients were collected from March to June 2023 in Yucheng, including 171 outpatients and 982 hospitalized patients. A total of 244 positive samples for common respiratory pathogens were detected (at least one pathogen per sample was detected). The total detection rate of respiratory pathogens was 21.16%, and the top three detection rates were, in descending order, human bocavirus (HBoV), enterovirus (EV), and human parainfluenza virus (HPIV). The main detection month for pathogens was May, with a detection rate of 42.3% (60/142). The main respiratory pathogens detected are HBoV, EV, and HPIV. The detection rate of the age group under 1 year old was the highest, at 25.1% (49/195), mainly consisting of HBoV, respiratory syncytial virus (RSV), and HPIV. The main clinical manifestations of respiratory pathogen-positive patients were fever and cough, and the clinical diagnosis was mainly lower respiratory tract infection, all of which were hospitalized patients.Conclusions:The respiratory pathogens in ARI patients were mainly HBoV, EV, and HPIV from March to June, 2023 in Yucheng. The peak of the epidemic was in May, mainly infecting children under 5 years of age.

Objective:To establish 30-day of age transcutaneous bilirubin (TcB) reference curves for healthy neonates, and to investigate regional variations in bilirubin dynamics.Methods:A multicenter retrospective cohort study was conducted. A total of 220 950 healthy neonates born at a gestational age of 35-<42 weeks, with a birth weight ≥2 000 g, who did not receive phototherapy within 60 h after birth were recruited. All of them underwent remote TcB monitoring using the Bilibaby remote jaundice monitoring system between August 1 st, 2020 and December 31 st, 2024 in 426 hospitals. TcB data were collected within the period from birth to 30-day of age. The P40, P75, and P95 of TcB values were calculated, and dynamic TcB curves for 30-day of age were constructed. Patterns of bilirubin change, rates of change, and transition outcomes were described. Regional comparisons between South and North were conducted using linear mixed-effects models for TcB trajectories and Pearson′s chi-square test for outcome differences. Results:A total of 220 950 neonates were included, of whom 101 711 (46.03%) were female. Gestational age at birth was (38.75±1.12) weeks, and birth weight was (3 272±417) g. TcB levels increased rapidly within 3-day of age, peaked at 4-6-day of age, with peak values at P40, P75, and P95 of 200.6, 239.7 and 275.4 μmol/L (11.8, 14.1 and 16.2 mg/dl), respectively. TcB levels gradually declined thereafter and stabilized after 13-day of age, with values at P40, P75, and P95 fluctuating between 147.9-159.8, 190.4-200.6, and 231.2-239.7 μmol/L (8.7-9.4, 11.2-11.8, 13.6-14.1 mg/dl), respectively. Notably, among neonates categorized as low-or low-intermediate-risk within 3-day of age, 6 700 (12.76%) progressed to intermediate-high or high risk between 4 and 30 days of age. Before 13-day of age, TcB levels in the southern regions were consistently higher than those in the northern regions ( P=0.039); from 14 to 30 days of age, the overall TcB levels had no statistically difference, but the temporal changes in TcB still showed regional differences (degrees of freedom=3, all interaction P<0.05). Among neonates classified as low-or low-intermediate risk within 3-day of age, 25 326 were from southern regions, of whom 4 254 (16.80%) progressed to intermediate-high or high risk between 4 and 30 days of age. In northern regions, 27 193 neonates were classified as low-or low-intermediate risk within 3-day of age, among whom 2 446 (8.99%) progressed to intermediate-high or high risk. The risk progression between the 2 regions had statistically difference ( χ2=716.49, P<0.001). Conclusions:A TcB percentile curve for neonates within 30-day of age was established, revealing that both the overall TcB level and its temporal trend were higher in southern than in northern newborns. These findings provide baseline data to support continuous management of neonatal jaundice.

Aim To investigate the regulatory mecha-nisms of donepezil on the expression and enzymatic ac-tivity of cytochrome P450 3A4(CYP3A4),elucidate the synergistic impact of hypoxia on CYP3A4 function,and reveal its potential association with drug-induced cardiotoxicity,particularly QT interval prolongation.Methods Western blot,co-immunoprecipitation,and gene knockdown techniques were employed to evaluate the effects of donepezil and hypoxia on CYP3A4 pro-tein expression.CYP3A4 enzymatic activity was as-sessed using an in vitro incubation system with rat liver microsomes combined with high-performance liquid chromatography(HPLC),and the half-maximal inhib-itory concentration(IC50)was determined.Results Donepezil(10 μmol·L-1)and hypoxia reduced CYP3A4 protein expression to 31.75％and 45.90％of the control levels,respectively.Both interventions activated the gp78-mediated ubiquitin-proteasome path-way,significantly increasing CYP3A4 ubiquitination levels by 2.1-fold compared to the control group,thereby promoting proteasomal degradation.Donepezil inhibited CYP3A4 enzyme activity with an IC50 of 83.4μmol·L-1,and hypoxia synergistically enhanced this inhibitory effect,reducing the IC50 to 20.79 μmol·L-1.Conclusion Donepezil downregulates CYP3A4 function through dual mechanisms involving ubiquitin-mediated proteasomal degradation and direct enzymatic inhibition.Hypoxia potentiates this effect,leading to impaired metabolism of CYP3A4 substrate drugs,ele-vated plasma drug concentrations(1.6-2.3-fold in-crease compared to normal metabolic conditions),and an increased risk of QT interval prolongation and other forms of cardiotoxicity.

Objective:To analyze the predictive role of WT1 expression levels pre-and early post-transplantation on relapse and overall survival(OS)in patients with acute myeloid leukemia(AML)undergoing allogeneic hematopoietic stem cell transplantation(allo-HSCT)during their first complete remission(CR1).Methods:A retrospective analysis was conducted on the clinical data of 107 adult AML patients who underwent allo-HSCT during their CR1 at our center between May 2012 and December 2021.The predictive role of bone marrow WT1 expression levels before transplantation and at 3 and 6 months post-transplantation on relapse and OS was explored in combination with relevant clinical factors.Results:The median follow-up time for the 107 patients was 70(range:11-117)months.Among the patients,15 cases died.Kaplan-Meier survial analysis showed that the 3-year overall survival(OS)rate was 85.0％.20 patients experienced relapse,with a median time to relapse of 8(range:0.5-44)months and a l-year cumulative relapse rate of 13.1％.The overall median value of WT1 before transplantation,3 months after transplantation,and 6 months after transplantation was 0.26％(range:0％-23.64％),with an upper quartile value of 0.74％.No statistically significant differences in WT1 expression levels were observed among the pre-transplantation,3-month post-transplantation,and 6-month post-transplantation time points(P=0.227).Univariate analysis showed that patients with WT1 levels＞0.74％at 3 months post-transplantation had a higher 1-year relapse rate(P=0.029)and lower 3-year OS rate(P＜0.001)compared to patients with WT1 levels ≤0.74％.Other significant factors affecting 1-year relapse included stem cell source(P=0.041)and chronic graft-versus-host disease(cGVHD)(P=0.013).For 3-year OS,additional influencing factors were genetic high risk(P=0.048)and stem cell source(P=0.016).Multivariate analysis revealed that WT1 level＞0.74％at 3 months post-transplantation had a trend to affect 1-year relapse rate(HR=3.309,95％CI:0.958-11.431,P=0.058),while the absence of cGVHD was an independent risk factor for 1-year relapse(HR=3.473,95％CI:0.749-16.100,P=0.037).Only WT1 level＞0.74％at 3 months post-transplantation was an independent risk factor for 3-year OS(HR=6.886,95％CI:2.402-19.738,P＜0.001).Conclusion:High WT1 expression level at 3 months post-transplantation in AML patients undergoing allo-HSCT during CR1 affects the 1-year relapse rate and 3-year OS,and is an independent risk factor affecting 3-year OS.These findings suggest that dynamic monitoring of WT1 expression levels has certain value in prognostic assessment of AML patients who received allo-HSCT during CR1.

Objective To develop a predictive model for postoperative mortality risk in patients with acute aortic dissection(AAD)using the Extreme Gradient Boosting(XGBoost)algorithm combined with Shapley Additive Explanation(SHAP),and to establish a prediction website to serve as a diagnostic and therapeutic support platform for clinicians and patients.Methods A retrospective cohort study design was adopted.Data from 782 AAD patients who underwent surgical treatment at the Fourth Hospital of Hebei Medical University from January 2013 to December 2023 were collected,including basic information and initial serum biomarker test results.Patients were randomly divided into training and test sets at a 7:3 ratio.An external validation set consisting of 313 AAD patients admitted to the Second Hospital of Hebei Medical University from January 2020 to December 2023 was also established for further model validation.Variables were screened using LASSO regression,and an XGBoost machine learning model was constructed and interpreted using SHAP.The predictive performance of the model was evaluated using receiver operating characteristic(ROC)curve analysis.Using the Shiny package,the XGBoost model was deployed to shinyapps.io to create a prediction website for postoperative mortality risk in AAD patients.One patient was selected by simple random sampling from the test set and the external validation set respectively for the prediction example on the Shiny webpage.Results The XGBoost model demonstrated high predictive performance for postoperative mortality in AAD patients,with area under the ROC curve(AUC)values of 0.928(95%CI 0.901-0.956)in the training set,0.919(95%CI 0.891-0.949)in the test set,and 0.941(95%CI 0.915-0.967)in the external validation set.SHAP values indicated the following order of variable importance in the model(from highest to lowest):"lactate dehydrogenase""blood chlorine""multiple organ injury""carbon dioxide combining power""prothrombin time""α-hydroxybutyric acid""creatine kinase isoenzyme""Stanford classification""combined use of bedside blood purification""gender""acute kidney injury""gastrointestinal bleeding""brain injury"and"shock".A risk prediction website for adverse postoperative outcomes in AAD patients was developed using XGBoost-SHAP method(https://dun-dunxiaolu.shinyapps.io/document/)and validated with examples.One randomly selected patient from each of the test and external validation sets was applied:the predicted mortality risk value for patient 1(who died postoperatively)was 0.9539,and that for patient 2(who survived postoperatively)was 0.0206.Conclusions The XGBoost-SHAP model demonstrates high accuracy in predicting postoperative mortality risk for AAD patients.The online prediction tool established based on this model enhances the identification efficiency of high-risk postoperative mortality patients.

Objective This study explores the clinical correlation between different low-density lipoprotein cholesterol(LDL-C)levels and prognosis,providing evidence-based guidance for the development of personalized lipid-lowering goals.Methods Patients who underwent elective percutaneous coronary intervention(PCI)treatment at Beijing Anzhen Hospital from January 2020 to June 2023 and received lipid-lowering therapy with the addition of Evolocumab were selected.Based on the results of blood lipid rechecks 3 to 6 months after surgery,the patients were divided into five groups:low-density lipoprotein＜0.5 mmol/L,0.5 to＜1.0 mmol/L,1.0 to＜1.4 mmol/L,1.4 to＜1.8 mmol/L,and above 1.8 mmol/L.All patients were followed up for more than one year,and clinical conditions and major adverse cardiovascular events(MACE)were recorded.Results A total of 1 106 patients undergoing PCI were enrolled;after propensity score matching and exclusion of patients lost to follow up,550 remained(110 per group).During 12 months of follow-up,58 patients(10.5％)experienced a MACE,with incidence rising step-wise across LDL-C categories.In multivariable Cox models adjusted for age,sex,diabetes,hypertension,baseline LDL-C,follow-up LDL-C,estimated glomerular filtration rate(eGFR),and left ventricular ejection fraction,the hazard ratios[HR(95％CI)]for MACE,relative to the＜0.5 mmol/L group,were 1.810(0.507-6.454,P=0.361),3.036(0.945-9.749,P=0.062),5.228(1.737-15.735,P=0.003),7.708(2.633-22.565,P＜0.001)for LDL-C levels of 0.5 to＜1.0,1.0 to＜1.4,1.4 to＜1.8 and≥ 1.8 mmol/L,respectively.A restricted cubic spline model demonstrated a significant non-linear positive association between LDL-C and MACE(P-overall≤0.001;P-non-linear=0.008).Stratified analyses by age,sex,hypertension and diabetes showed consistent HR with no significant interactions(all P＞0.05).There were no statistically significant differences among the groups in the incidence of bleeding events,elevated creatinine levels,or abnormal liver function(all P＞0.05).Conclusions In patients using PCSK9 after PCI,there is a significant positive correlation between LDL-C levels and the risk of MACE,and no correlation was observed between different LDL-C levels and the risk of adverse events such as bleeding.

Alzheimer's disease(AD),a neurodegenerative disorder,manifests pathological changes in the brain even during the asymptomatic stage.As the pathological burden intensifies,patients experience functional decline in multiple cognitive domains,including memory,language,spatial perception,executive function,and calculation,and may also exhibit emotional abnormalities.Once AD progresses,treatment becomes extremely chal-lenging.Therefore,early diagnosis and accurate prediction of disease conversion are core tasks in the prevention and treatment of AD,and they are also urgent scientific research challenges to be overcome.Deep learning(DL)models demonstrate considerable advantages in the diagnosis,prediction,classification,and feature extraction of AD,offering new hope for solving this challenging problem.This research commences with a concise introduction to the outcomes of AD and the fundamental knowledge of deep learning.Subsequently,it offers an overview of the imaging studies on the utilization of deep learning for predicting disease transformation from two perspectives.Firstly,it systematically summarizes the existing DL models that have demonstrated innovation in the classification and prediction performance of AD.Secondly,it provides a comprehensive outline of the DL fusion models applied to the diagnosis,classification,and prediction of AD.Finally,this paper expounds upon the impending challenges in the research of this domain.This article demonstrates that deep learning models is cutting-edge trends in the ex-ploration of AD research.

Objective This study explores the clinical correlation between different low-density lipoprotein cholesterol(LDL-C)levels and prognosis,providing evidence-based guidance for the development of personalized lipid-lowering goals.Methods Patients who underwent elective percutaneous coronary intervention(PCI)treatment at Beijing Anzhen Hospital from January 2020 to June 2023 and received lipid-lowering therapy with the addition of Evolocumab were selected.Based on the results of blood lipid rechecks 3 to 6 months after surgery,the patients were divided into five groups:low-density lipoprotein＜0.5 mmol/L,0.5 to＜1.0 mmol/L,1.0 to＜1.4 mmol/L,1.4 to＜1.8 mmol/L,and above 1.8 mmol/L.All patients were followed up for more than one year,and clinical conditions and major adverse cardiovascular events(MACE)were recorded.Results A total of 1 106 patients undergoing PCI were enrolled;after propensity score matching and exclusion of patients lost to follow up,550 remained(110 per group).During 12 months of follow-up,58 patients(10.5％)experienced a MACE,with incidence rising step-wise across LDL-C categories.In multivariable Cox models adjusted for age,sex,diabetes,hypertension,baseline LDL-C,follow-up LDL-C,estimated glomerular filtration rate(eGFR),and left ventricular ejection fraction,the hazard ratios[HR(95％CI)]for MACE,relative to the＜0.5 mmol/L group,were 1.810(0.507-6.454,P=0.361),3.036(0.945-9.749,P=0.062),5.228(1.737-15.735,P=0.003),7.708(2.633-22.565,P＜0.001)for LDL-C levels of 0.5 to＜1.0,1.0 to＜1.4,1.4 to＜1.8 and≥ 1.8 mmol/L,respectively.A restricted cubic spline model demonstrated a significant non-linear positive association between LDL-C and MACE(P-overall≤0.001;P-non-linear=0.008).Stratified analyses by age,sex,hypertension and diabetes showed consistent HR with no significant interactions(all P＞0.05).There were no statistically significant differences among the groups in the incidence of bleeding events,elevated creatinine levels,or abnormal liver function(all P＞0.05).Conclusions In patients using PCSK9 after PCI,there is a significant positive correlation between LDL-C levels and the risk of MACE,and no correlation was observed between different LDL-C levels and the risk of adverse events such as bleeding.

Objective:Analysis of the composition of pathogen spectrum and prevalence characteristics in throat swabs of patients with acute respiratory infections (ARI) in Yucheng city, Henan province, from March to June 2023.Methods:After 1 153 throat swabs were collected from ARI patients in Yucheng, 18 respiratory pathogens were tested using a real-time fluorescence quantitative polymerase chain reaction (qPCR) method. The characterization of pathogens spectrum was analyzed.Results:A total of 1 153 throat swabs from ARI patients were collected from March to June 2023 in Yucheng, including 171 outpatients and 982 hospitalized patients. A total of 244 positive samples for common respiratory pathogens were detected (at least one pathogen per sample was detected). The total detection rate of respiratory pathogens was 21.16%, and the top three detection rates were, in descending order, human bocavirus (HBoV), enterovirus (EV), and human parainfluenza virus (HPIV). The main detection month for pathogens was May, with a detection rate of 42.3% (60/142). The main respiratory pathogens detected are HBoV, EV, and HPIV. The detection rate of the age group under 1 year old was the highest, at 25.1% (49/195), mainly consisting of HBoV, respiratory syncytial virus (RSV), and HPIV. The main clinical manifestations of respiratory pathogen-positive patients were fever and cough, and the clinical diagnosis was mainly lower respiratory tract infection, all of which were hospitalized patients.Conclusions:The respiratory pathogens in ARI patients were mainly HBoV, EV, and HPIV from March to June, 2023 in Yucheng. The peak of the epidemic was in May, mainly infecting children under 5 years of age.