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 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.

Ethanol (EtOH) is a common trigger for gastric mucosal diseases, and mitigating oxidative stress is essential for attenuating gastric mucosal damage. Capsaicin (CAP) has been identified as a potential agent to counteract oxidative damage in the gastric mucosa; however, its precise mechanism remains unclear. This study demonstrates that CAP alleviates EtOH-induced gastric mucosal injuries through two primary pathways: by suppressing the chemokine receptor 4 (CCR4)/Src/p47phox axis, thereby reducing oxidative stress, and by inhibiting the phosphorylation and nuclear translocation of nuclear factor-κB p65 (NF-κB) p65, resulting in diminished inflammatory responses. These findings elucidate the mechanistic pathways of CAP and provide a theoretical foundation for its potential therapeutic application in the treatment of gastric mucosal injuries.
Ethanol/toxicity* ; Animals ; Gastric Mucosa/metabolism* ; Signal Transduction/drug effects* ; Oxidative Stress/drug effects* ; Capsaicin/pharmacology* ; Male ; NADPH Oxidases/genetics* ; Mice ; Humans ; src-Family Kinases/genetics*

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.

Objective:To investigate the clinical value of the Nomogram model based on two-dimensional shear wave elastography(2D-SWE)combined with biochemical indicators in the diagnosis of moderate and severe metabolic-associated fatty liver disease(MAFLD).Methods:A total of 170 patients with MAFLD diagnosed by ultrosound image in the health management center of the Second People's Hospital of Wuhu from Jan 2023 to Dec 2023 were divided into mild,moderate and severe groups according to two-dimensional ultrasound images,and 111 healthy volunteers were recruited as control group in the same period.Multivariate logistic regression analysis was used to screen independent risk factors for moderate and severe MAFLD and construct a predictive model.The diagnostic efficacy of the ROC model was plotted,and the Nomogram model was used to conduct internal verification.Results:Multivariate logistic regression analysis showed that liver stiffness measurement(LSM),platelet count(PLT)and hepatic steatosis index(HSI)were the independent risk factors for the diagnosis of moderate and severe MAFLD.The area under the curve(AUC)of LSM,PLT and HSI was 0.940(95%CI:0.911-0.969),with a sensitivity was 87.5%and a specificity was 88.1%.The internal validation showed that the model had high accuracy and stability.Conclusion:The Nomogram model based on LSM combined with PLT and HSI can effectively diagnose moderate and severe MAFLD,providing a reliable evidence for early clinical intervention and adjustment of therapeutic measures.

Objective:To investigate the clinical efficacy of pancreatic cancer surgery with arterial resection.Methods:The clinicopathological and follow-up data of 135 patients undergoing pancreatectomies with arterial resection in Pancreas Center, the First Affiliated Hospital of Nanjing Medical University from Sep 2013 to Dec 2023 were retrospectively analyzed.Results:There were 77 males and 58 females, with age [ M( IQR)] of 63 (14) years old. Among the 135 patients, 122 (90.4%) were distal pancreatectomies, 8 (5.9%) were pancreaticoduodenectomies, 4 (3.0%) were total pancreatectomies and 1 (0.7%) was resection for local recurrence after distal pancreatectomy. There were 120 (88.9%) celiac axis resections, 11 (8.1%) hepatic artery resections, 1 (0.7%) superior mesenteric artery resection and 3 (2.2%) other artery resections. Simultaneous portal vein-superior mesenteric vein or organ resection accounted for 26.7% (36/135) and 29.6% (40/135),respectively. The median blood loss was 300 (300) ml and the median operation time was 275 (105) minutes. The 90-day mortality rate was 7.4% (10/135). The overall morbidity rate was 70.4% (95/135) while the major morbidity rate was 18.5% (25/135). Postoperative hemorrhage occurred in 8.9% (12/135), clinically relevant postoperative pancreatic fistula in 57.0% (77/135), bile leak in 0.74% (1/135), delayed gastric emptying in 9.6% (13/135), liver failure in 3.7% (5/135) and transient liver enzyme elevation in 44.4% (60/135). All of the 135 cases were confirmed as pancreatic cancer histologically, including 54.6% (71/130) moderately differentiated, 45.4% (59/130) poorly differentiated and no for well differentiated. The median tumor size was 4.5 (2.3) cm. The median number of harvested lymph nodes was 14 (13) and the percentage of N0, N1 and N2 according to AJCC 8th staging system was 27.1% (36/133), 52.6% (70/133) and 20.3% (27/133), respectively. The R 0 resection was achieved in 40 of 123 cases (32.5%), whose margins of specimens were assessed circumferentially based on the 1mm rule. The median overall survival time (MST) after surgery was 22.5 months, and the median progress-free survival time was 16.1 months. The overall survival rate at 1-, 2- and 5-year was 71.5%, 45.1% and 11.3%, respectively. The MST of patients who received no adjuvant therapy, chemotherapy after surgery was 8.4 months, 25.3 months, respectively. Conclusions:Pancreatectomy with arterial resection is generally safe and feasible. Survival outcome improves significantly when combined with adjuvant chemotherapy.

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.

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.