Objective To elucidate the changes in the gut microbiota and molecular mechanism of huaier in enhancing the efficacy of oxaliplatin (OXA) chemotherapy in gastric cancer (GC). Methods The effects of huaier on the gut microbiota structure and intestinal barrier function in MKN45-bearing mice were analyzed by using 16S rRNA sequencing, RT-qPCR, and IHC. UPLC-MS and network pharmacology, as well as in vivo experimental approaches, were employed to investigate the key bioactive constituents of huaier systematically and elucidate the underlying mechanisms by which huaier exerts therapeutic effects against GC. The expression of the PI3K/AKT/SREBP pathway was detected in cancer cells and tissues via Western blot analysis. The safety profile of huaier combined with OXA was verified through serum biochemistry and HE-stained tissue section analyses. Results Huaier inhibited the PI3K/AKT/SREBP pathway by increasing the abundance of Akkermansia muciniphila, reduced lipid droplet deposition, and ultimately enhanced the sensitivity to OXA in the treatment of GC. Conclusion This study demonstrates the value of huaier in gastric cancer treatment by enhancing chemosensitivity and provides novel insights into its systemic therapeutic effects through molecular mechanisms and gut microbiota modulation.

ObjectiveTo develop a community-family management model for older adults with mild cognitive impairment (MCI) and to formulate detailed application specifications, and to fully leverage the initiative of communities and families under limited resource conditions, for achieving community-based early detection and early intervention for older adults with MCI. MethodsA systematic literature review was conducted to identify pertinent publications. Corpus-based research methodologies were employed to extract, refine, integrate and synthesize management elements, thereby establishing the specific content and service processes for each stage of the management model. Utilizing the 5W2H analytical framework, essential elements such as management stakeholders, target populations, content and methods for each stage were delineated. The model and its application guidelines were finalized through expert consultation and demonstration. ResultsAn expert evaluation of the management model yielded mean scores of 4.84, 4.32 and 4.84 for acceptability, feasibility and systematicity, respectively. By integrating the identified core elements with expert ratings and feedback, the final iteration of the community-family management model for older adults with MCI was formulated. This model comprised of five stages: screening and identification, comprehensive assessment, intervention planning, monitoring and referral pathways to ensure implementation, and enhanced support for communities, family members and caregivers. Additionally, it included 18 specific application guidelines. ConclusionThe proposed management model may theoretically help delay cognitive decline, improve cognitive function and potentially promote reversal from MCI to normal cognition. It may also enhance the awareness and coping capacity of older adults and their families, strengthen community healthcare professionals' ability to early identify and manage MCI.

Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.

BACKGROUND:Psoralen has a strong anti-osteoporotic activity and may have a restorative effect on chemotherapy-induced osteoporosis. OBJECTIVE:To explore the restorative effect of psoralen on the osteogenic differentiation of bone marrow mesenchymal stem cells in mice inhibited by cyclophosphamide and its mechanism. METHODS:C57BL/6 mouse bone marrow mesenchymal stem cells were isolated and cultured.Effect of psoralen on viability of bone marrow mesenchymal stem cells was detected by MTT assay.Osteogenic induction combined with alkaline phosphatase staining was used to determine the optimal dose of psoralen to restore the osteogenic differentiation of bone marrow mesenchymal stem cells inhibited by cyclophosphamide.The mRNA expression levels of Runx2,alkaline phosphatase,Osteocalcin,osteoprotegerin,and Wnt/β-catenin signaling pathway-related genes Wnt1,Wnt4,Wnt10b,β-catenin,and c-MYC were measured by RT-qPCR at different time points under the intervention with psoralen.The protein expression of osteogenic specific transcription factor Runx2 and Wnt/β-catenin signaling pathway related genes Active β-catenin,DKK1,c-MYC,and Cyclin D1 was determined by western blot assay at different time points under the intervention with psoralen. RESULTS AND CONCLUSION:(1)There was no significant effect of different concentrations of psoralen on the viability of bone marrow mesenchymal stem cells.The best recovery of the inhibition of osteogenic differentiation of bone marrow mesenchymal stem cells caused by cyclophosphamide was under the intervention of psoralen at a concentration of 200 μmol/L.(2)Psoralen reversed the reduction in osteogenic differentiation marker genes Runx2,alkaline phosphatase,Osteocalcin and osteoprotegerin mRNA expression and Runx2 protein expression in bone marrow mesenchymal stem cells caused by cyclophosphamide conditioned medium.(3)Psoralen reversed the decrease in Wnt/β-catenin pathway-related genes Wnt4,β-catenin,c-MYC mRNA and Active β-catenin,c-MYC,and Cyclin D1 protein expression and the increase in DKK1 protein expression in bone marrow mesenchymal stem cells caused by cyclophosphamide conditioned medium.(4)The results showed that cyclophosphamide inhibited osteogenic differentiation of bone marrow mesenchymal stem cells in mice,and psoralen had a restorative effect on it.The best intervention effect was achieved at a concentration of 200 μmol/L psoralen,and this protective effect might be related to the activation of Wnt4/β-catenin signaling pathway by psoralen.

ObjectiveTo analyze the epidemiological characteristics of influenza virus in severe acute respiratory tract infection (SARI) cases in Jingzhou City, so as to provide a scientific basis for the formulation of influenza prevention and control policies in Jingzhou City. MethodsSARI surveillance was carried out in two sentinel hospitals in Jingzhou City from 2018 to 2023. Respiratory tract samples were collected from cases and influenza virus nucleic acid was measured using real-time fluorescent polymerase chain reaction (RT-PCR). ResultsA total of 2 603 SARI samples were tested from 2018 to 2023, and 338 samples were positive for influenza virus nucleic acid, with a detection rate of 12.99%. The highest positive detection rate was 20.22% in 2019, followed by 14.29% in 2022, and the lowest detection rate was 7.75% in 2020. There were significant differences for the positive detection rates of influenza in each monitoring year (χ²=30.386, P<0.001). There were epidemic peaks in the five surveillance years from 2018 to 2023 except 2020. There were winter epidemic peaks during 2018‒2019 and 2021‒2022, and an obvious summer epidemic peak was also observed from 2019 to 2022. H1N1, H3N2, B-Victoria and B-Yamagata were alternately prevalent in the six surveillance years. In 2019, H1N1, H3N2 and B-Victoria were alternately prevalent with time progress, in 2021 only B-Victoria was prevalent, and in 2022 H3N2 and B-Victoria were prevalent. There was no statistically significant difference for the positive detection rates of influenza virus between different genders (χ²=0.178, P=0.673). Among the four age groups, the positive rate of influenza virus in the age group of 15‒<25 years old was the highest (40.91%), followed by the age group of 25‒<60 years old (21.31%). There were statistically significant differences for the positive rates of influenza virus among different age groups (χ²=24.496, P<0.001). ConclusionThe surveillance of SARI cases in Jingzhou City could serve as an effective supplement to the surveillance of ILI in sentinel hospitals. It is suggested to expand the surveillance scope, strengthen public education and outreach on the prevention and control of respiratory diseases, thereby providing a scientific basis for influenza prevention and control.

Objective:To construct a machine learning model based on localization CT-based radiomics, dosiomics and clinical features for predicting radiotherapy response in non-small cell lung cancer (NSCLC) and validate its application value.Methods:A retrospective case series study was conducted. A total of 138 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022 were selected. The efficacy was evaluated according to the Response Evaluation Criteria in Solid Tumors (RECIST) 1.1, and the patients were stratified according to the objective remission (complete remission+partial remission). Random stratified sampling was used to divide the 138 patients into a training group (96 cases) and an internal validation group (42 cases) at a ratio of 7∶3. Additionally, 33 patients who received radiotherapy at Jining Cancer Hospital from January 2019 to December 2022 were included as the external validation group. Based on the pre-radiotherapy data of the radiotherapy planning system, PyRadiomics software package was used to extract 107 radiomics features and 107 dosiomics features for each patient. Pearson correlation analysis and LASSO regression analysis were used for dimensionality reduction screening; the final selected features were weighted and integrated to generate radiomics-dosiomics scores (RDS), which were then input into logistic regression (LR), support vector machine (SVM), extremely randomized forest (Extra Trees), K-nearest neighbor algorithm (KNN), lightweight gradient boosting machine (Light GBM), and multi-layer perceptron (MLP) machine learning algorithms to construct 6 radiomics-dosiomics models (RDM) for predicting the objective remission. RECIST 1.1 standard was used to evaluate objective remission as the gold standard, receiver operating characteristic (ROC) curve of 6 RDM for predicting objective remission was plotted, and the optimal algorithm for RDM was selected. Univariate and multivariate logistic regression were performed on demographic characteristics, hematological indicators and radiotherapy parameters of the training group to screen independent risk factors for NSCLC patients who received radiotherapy but did not achieve objective remission. These factors were input into the optimal machine learning algorithm to construct a clinical model (CM). Combined with features from RDS and CM, the clinical feature-radiomics-dosiomics combined model (CRDM) was established, and the nomogram of the model for predicting objective remission in NSCLC patients with radiotherapy was drawn. ROC curves were used to evaluate the efficacy of CM, RDM and CRDM in predicting the objective remission in NSCLC patients with radiotherapy in the training group, internal validation group and external validation group.Results:Four radiomics features (including grayscale variance, low grayscale long-range operation emphasis, low grayscale area emphasis, and small area low grayscale area emphasis, all of which were texture features) and 6 dosiomics features [including 1 first-order feature (robust mean absolute deviation), 4 texture features (grayscale non-uniformity, large area emphasis, large area high grayscale emphasis, contrast) and 1 shape feature (shortest axis length)] were selected. ROC curve analysis showed that the area under the curve (AUC) of the RDM constructed using SVM algorithm for judging the objective remission in the training group and the internal validation group was 0.907 (95% CI: 0.836-0.977) and 0.822 (95% CI: 0.685-0.959), which were higher than RDM constructed using other algorithms, and the sensitivity (96.2% and 91.7%), specificity (78.6% and 76.7%) and accuracy (83.3% and 81.0%) at the optimal cut-off values were all higher. Considering the stability and generalization ability of the model, SVM algorithm was ultimately used to construct RDM, CM and CRDM uniformly. Based on training group data, univariate and multivariate logistic regression analysis showed that elevated platelet-to-lymphocyte ratio (PLR) ( OR = 1.001, 95% CI: 1.000-1.003, P = 0.035) and increased target volume of radiotherapy plan ( OR = 1.001, 95% CI: 1.000-1.001, P = 0.008) were independent risk factors for failure to achieve objective remission. ROC curve analysis showed that in the training group and the internal validation group, the AUC of CRDM predicting objective remission were 0.914 (95% CI: 0.856-0.972) and 0.864 (95% CI: 0.754-0.974), respectively, which were better than CM [AUC were 0.735 (95% CI: 0.612-0.857) and 0.697 (95% CI: 0.507-0.888)] and RDM, respectively. In the external validation group, the AUC of CRDM, CM and RDM were 0.778 (95% CI: 0.500-1.000), 0.667 (95% CI: 0.434-0.899) and 0.741 (95% CI: 0.463-1.000), respectively. Conclusions:The CRDM constructed by combining radiomics, dosiomics and clinical features can comprehensively and accurately evaluate the radiotherapy response of NSCLC patients, and may have important clinical application value in achieving precision medicine and optimizing treatment strategies.

In the past decade, real-world data (RWD) research has undergone significant transformations due to data aggregation and processing technologies. However, there is still a lack of consensus regarding the scope of RWD applications and the value of real-world evidence (RWE). This study briefly outlined the origins of the concept of RWD study and its early research scope to promote further development in this area. We also reviewed the understanding of RWD applications and research models from the five perspectives of healthcare professionals, medical institutions, decision-making departments, cross-regional cooperation model, and the practice of the One-Health model. Finally, we systematically summarized the renewed understanding of the value of RWE while looking ahead to the challenges and future developments in this field.

Objective:To analyze the clinical features and risk factors for renal injury in children with antineutrophil cytoplasmic antibody (ANCA)-positive IgA vasculitis (IgAV).Methods:A case-control study was conducted. Seventy-two ANCA-positive IgAV children hospitalized at the Children′s Hospital of Chongqing Medical University from January 2017 to October 2022 were enrolled as the ANCA-positive group. Propensity score matching (1∶4) using the nearest neighbor was performed with age and gender as covariate, and 288 cases ANCA-negative IgAV children were included as the ANCA-negative group. Patients with renal injury were named ANCA-positive IgAV nephritis (IgAVN) group and ANCA-negative IgAVN group, respectively. The ANCA-positive IgAVN group was further divided into myeloperoxidase (MPO) group and proteinase 3 (PR3) group based on the type of ANCA. Clinical data including manifestations, laboratory tests, renal injury, and prognosis were collected. Comparisons between groups were performed using independent sample t-tests, Mann-Whitney U tests, χ2 tests, or Fisher′s exact tests. Kaplan-Meier curves were used to assess differences in the time to renal injury onset, and multivariate logistic regression was performed to identify independent risk factors for renal injury. Results:Among the 72 ANCA-positive IgAV children (41 males, 31 females, age of 7.7 (5.3, 11.2) years), no significant difference in age or gender was observed compared to the ANCA-negative group (both P>0.05). The ANCA-positive group had higher IgM levels, a higher incidence of recurrent rash, and shorter thrombin time (all P<0.05). Among children with renal injury, the ANCA-positive group showed significant differences in the incidence of hematuria, clinical classification, and grade A prognosis compared to the ANCA-negative group (all P<0.05), but no difference was found in the time to renal involvement onest or renal pathology (all P>0.05). The MPO group had higher rates of microscopic hematuria, gross hematuria, acute renal insufficiency, glomerular sclerosis, and grade B prognosis compared to the ANCA-negative IgAVN group (all P<0.05), with a later onset of renal involvement ( P<0.05). Elevated serum creatinine ( OR=1.08, 95% CI 1.03-1.14) and shortened thrombin time ( OR=0.71, 95% CI 0.55-0.92) were independent risk factors for renal injury in ANCA-positive IgAV children (all P<0.05). Conclusions:Children with ANCA-positive IgAV are more likely to experience recurrent rash. MPO-ANCA-positive IgAVN children have higher risks of hematuria, acute kidney injury and glomerular sclerosis, with later-onset but poorer renal prognosis compared to ANCA-negative IgAVN children. Higher serum creatinine levels and shorter thrombin time may be associated with renal injury in children with ANCA-positive IgAV.

Objective:To develop and validate a combined model integrating radiomics, dosiomics, and clinical parameters based on CT simulation and dosimetric images in order to predict the occurrence of radiation pneumonitis (RP) in patients with non-small cell lung cancer (NSCLC).Methods:A retrospective study was conducted on the clinic data of 143 NSCLC patients who received radiotherapy at the Affiliated Hospital of Jining Medical University from January 2016 to December 2022. Patients were randomly stratified into a training group ( n = 100) and an internal validation group ( n = 43) at a 7∶3 ratio. Moreover, clinic data were collected from 34 NSCLC patients who received radiotherapy at the Jining Cancer Hospital between January 2019 and December 2022 as an external validation group. All three groups (the training group, internal validation, and external validation groups) were further categorized into two groups based on the RP severity (i.e., RP ≥ grade 2 and RP < grade 2). Their radiotherapy dose, CT simulation, and 3D dose distribution images were collected. Then, the total lung minus planning target volume (TL-PTV) was defined as the region of interest (ROI) for radiomics and dosiomic feature extraction, followed by feature dimensionality reduction. Consequently, key features associated with RP were determined. Four predictive models were developed using machine learning approaches (especially multilayer perceptron, MLP): a clinical model (CM), a radiomics model (RM), a dosiomics model (DM), and a radiomics and dosiomics nomogram (RDN), with a nomogram subsequently constructed. Ultimately, the performance and clinical feasibility of these models were assessed using receiver operating characteristic (ROC), area under the curve (AUC), and decision curve analysis (DCA). Results:A total of 1 834 radiomic features and 1 834 dosiomic features were extracted. Using the occurrence of RP ≥ grade 2 as the marker variable, 14 radiomic features, 15 dosiomic features, and three clinical features were selected from the training group to construct the prediction models (CM, RM, DM, and RDN). The performance and generalizability of these models were subsequently validated in both the internal validation and external validation groups. Specifically, the RDN exhibited AUCs of 0.915 (95% CI: 0.852-0.978), 0.879 (95% CI: 0.777-0.982), and 0.838 (95% CI: 0.701-0.975) in the three groups, respectively. A nomogram was established for RDN by integrating the radiomics score (R-score), dosiomics score (D-score), mean lung dose (MLD), V20, and V30. This nomogram allowed for individualized risk estimation of RP and facilitated personalized radiotherapy planning. Conclusions:The RDN model that is developed based on CT simulation and 3D dose distribution images and integrates radiomics, dosiomics, and clinical features can effectively predict the RP risk of NSCLC patients. The integration of multidimensional data contributes to the formation of the optimal predictive model, offering guidance for clinicians.