Prognostic factors for liver metastasis in patients with small intestinal stromal tumor: A retrospective analysis of surveillance, epidemiology, and end results.

BACKGROUND: Liver metastasis (LIM) is the most common distant site of metastasis in small intestinal stromal tumors (SISTs). The aim of this study was to determine the risk and prognostic factors associated with LIM in patients with SISTs. METHODS: Patients diagnosed with gastrointestinal stromal tumors between 2010 and 2019 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate logistic regression models, as well as a Cox regression model were used to explore the risk factors associated with the development and prognosis of LIM. Additionally, the overall survival (OS) of patients with LIM was analyzed using the Kaplan-Meier method. Furthermore, a predictive nomogram was constructed, and the model's performance was evaluated using receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis (DCA). RESULTS: A total of 1582 eligible patients with SISTs were included, among whom 146 (9.2%) were diagnosed with LIM. Poor tumor grade, absence of surgery, later T-stage, and no chemotherapy were associated with an increased risk of developing LIM. The nomogram prediction model achieved an AUC of 0.810, 95% Confidence Interval (CI) 0.773-0.846, indicating good performance, and the calibration curve showed excellent accuracy in predicting LIM. The OS rate of patients with LIM was significantly lower than that of patients without LIM (p < 0.001). CONCLUSIONS: Patients with SISTs who are at high risk of developing LIM deserve more attention during follow-up, as LIM can significantly affect patient prognosis. The nomogram demonstrated good calibration and discrimination for predicting LIM.

Automated machine learning for early prediction of acute kidney injury in acute pancreatitis.

BACKGROUND: Acute kidney injury (AKI) represents a frequent and grave complication associated with acute pancreatitis (AP), substantially elevating both mortality rates and the financial burden of hospitalization. The aim of our study is to construct a predictive model utilizing automated machine learning (AutoML) algorithms for the early prediction of AKI in patients with AP. METHODS: We retrospectively analyzed patients who were diagnosed with AP in our hospital from January 2017 to December 2021. These patients were randomly allocated into a training set and a validation set at a ratio of 7:3. To develop predictive models for each set, we employed the least absolute shrinkage and selection operator (LASSO) algorithm along with AutoML. A nomogram was developed based on multivariate logistic regression analysis outcomes. The model's efficacy was assessed using receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA). Additionally, the performance of the model constructed via AutoML was evaluated using decision curve analysis (DCA), feature importance, SHapley Additive exPlanations (SHAP) plots, and locally interpretable model-agnostic explanations (LIME). RESULTS: This study incorporated a total of 437 patients who met the inclusion criteria. Out of these, 313 were assigned to the training cohort and 124 to the validation cohort. In the training and validation cohorts, AKI occurred in 68 (21.7%) and 29(23.4%) patients, respectively. Comparative analysis revealed that the AutoML models exhibited enhanced performance over traditional logistic regression (LR). Furthermore, the deep learning (DL) model demonstrated superior predictive accuracy, evidenced by an area under the ROC curve of 0.963 in the training set and 0.830 in the validation set, surpassing other comparative models. The key variables identified as significant in the DL model within the training dataset included creatinine (Cr), urea (Urea), international normalized ratio (INR), etiology, smoking, alanine aminotransferase (ALT), hypertension, prothrombin time (PT), lactate dehydrogenase (LDH), and diabetes. CONCLUSION: The AutoML model, utilizing DL algorithm, offers considerable clinical significance in the early detection of AKI among patients with AP.

Development and validation of a multimodal model in predicting severe acute pancreatitis based on radiomics and deep learning.

OBJECTIVE: Aim to establish a multimodal model for predicting severe acute pancreatitis (SAP) using machine learning (ML) and deep learning (DL). METHODS: In this multicentre retrospective study, patients diagnosed with acute pancreatitis at admission were enrolled from January 2017 to December 2021. Clinical information within 24 h and CT scans within 72 h of admission were collected. First, we trained Model α based on clinical features selected by least absolute shrinkage and selection operator analysis. Second, radiomics features were extracted from 3D-CT scans and Model ß was developed on the features after dimensionality reduction using principal component analysis. Third, Model γ was trained on 2D-CT images. Lastly, a multimodal model, namely PrismSAP, was constructed based on aforementioned features in the training set. The predictive accuracy of PrismSAP was verified in the validation and internal test sets and further validated in the external test set. Model performance was evaluated using area under the curve (AUC), accuracy, sensitivity, specificity, recall, precision and F1-score. RESULTS: A total of 1,221 eligible patients were randomly split into a training set (n = 864), a validation set (n = 209) and an internal test set (n = 148). Data of 266 patients were for external testing. In the external test set, PrismSAP performed best with the highest AUC of 0.916 (0.873-0.960) among all models [Model α: 0.709 (0.618-0.800); Model ß: 0.749 (0.675-0.824); Model γ: 0.687 (0.592-0.782); MCTSI: 0.778 (0.698-0.857); RANSON: 0.642 (0.559-0.725); BISAP: 0.751 (0.668-0.833); SABP: 0.710 (0.621-0.798)]. CONCLUSION: The proposed multimodal model outperformed any single-modality models and traditional scoring systems.

RUNX2 prompts triple negative breast cancer drug resistance through TGF-ß pathway regulating breast cancer stem cells.

Triple-negative breast cancer (TNBC) stands out as the most aggressive subtype within the spectrum of breast cancer. The current clinical guidelines propose treatment strategies involving cytotoxic agents like epirubicin or paclitaxel. However, the emergence of acquired resistance frequently precipitates secondary tumor recurrence or the spread of metastasis. In recent times, significant attention has been directed toward the transcription factor RUNX2, due to its pivotal role in both tumorigenesis and the progression of cancer. Previous researches suggest that RUNX2 might be intricately linked to the development of resistance against chemotherapy, with its mechanism of action possibly intertwined with the signaling of TGF-ß. Nevertheless, the precise interplay between their effects and the exact molecular mechanisms underpinning chemoresistance in TNBC remain elusive. Therefore, we have taken a multifaceted approach from in vitro and in vivo experiments to validate the relationship between RUNX2 and TGF-ß and to search for their pathogenic mechanisms in chemoresistance. In conclusion, we found that RUNX2 affects chemoresistance by regulating cancer cell stemness through direct binding to TGF-ß, and that TGF-ß dually regulates RUNX2 expression. The important finding will provide a new reference for clinical reversal of the development of chemoresistance in breast cancer.

The mechanisms of ferroptosis and its role in atherosclerosis.

Ferroptosis is a newly identified form of non-apoptotic programmed cell death, characterized by the iron-dependent accumulation of lethal lipid reactive oxygen species (ROS) and peroxidation of membrane polyunsaturated fatty acid phospholipids (PUFA-PLs). Ferroptosis is unique among other cell death modalities in many aspects. It is initiated by excessive oxidative damage due to iron overload and lipid peroxidation and compromised antioxidant defense systems, including the system Xc-/ glutathione (GSH)/glutathione peroxidase 4 (GPX4) pathway and the GPX4-independent pathways. In the past ten years, ferroptosis was reported to play a critical role in the pathogenesis of various cardiovascular diseases, e.g., atherosclerosis (AS), arrhythmia, heart failure, diabetic cardiomyopathy, and myocardial ischemia-reperfusion injury. Studies have identified dysfunctional iron metabolism and abnormal expression profiles of ferroptosis-related factors, including iron, GSH, GPX4, ferroportin (FPN), and SLC7A11 (xCT), as critical indicators for atherogenesis. Moreover, ferroptosis in plaque cells, i.e., vascular endothelial cell (VEC), macrophage, and vascular smooth muscle cell (VSMC), positively correlate with atherosclerotic plaque development. Many macromolecules, drugs, Chinese herbs, and food extracts can inhibit the atherogenic process by suppressing the ferroptosis of plaque cells. In contrast, some ferroptosis inducers have significant pro-atherogenic effects. However, the mechanisms through which ferroptosis affects the progression of AS still need to be well-known. This review summarizes the molecular mechanisms of ferroptosis and their emerging role in AS, aimed at providing novel, promising druggable targets for anti-AS therapy.

Metabolic parameters of pretreatment 2-[18F]fluoro-D-glucose positron emission tomography for prognosis in patients with gallbladder adenocarcinoma: a cohort study.

Background: The incidence of gallbladder adenocarcinoma (GBA) is relatively low, yet it exhibits a high degree of malignancy and a significantly low 5-year survival rate. The aim of this study was to investigate the prognostic value of pretreatment 2-[18F]fluoro-D-glucose positron emission tomography {2-[18F]FDG PET} parameters in predicting outcomes for patients with GBA. Methods: In total, 67 patients with GBA who underwent 2-[18F]FDG PET/computed tomography (CT) before treatment were retrospectively analyzed at Chinese PLA General Hospital from January 2012 to June 2022. All patients were diagnosed by pathology, and their baseline characteristics and clinical data were collected. The metabolic PET parameters of the primary and metastatic lesions were measured, including the maximum and average standardized uptake values (SUVs), metabolic tumor volume (MTV), and total lesion glycolysis (TLG). The prognostic significance of metabolic parameters and other clinical variables was assessed using Cox proportional hazards regression models. Differences in progression-free survival (PFS) and overall survival (OS) in relation to metabolic parameters were examined using the Kaplan-Meier method. Results: During a median follow-up period of 14.2 months, 43 patients (64.2%) experienced tumor recurrence or progression, and 38 patients (56.7%) died of cancer. In the univariate Cox regression analysis, liver parenchymal invasion (P=0.001), lymph node metastasis (P=0.007), distant metastases (P=0.049), tumor differentiation (P=0.028), surgery (P=0.014), carcinoembryonic antigen (CEA) level (P=0.030), carbohydrate antigen 19-9 (CA19-9) level (P=0.003), TLG (P=0.005), MTV (P<0.001), sum of the TLGs of the primary and metastatic lesions (total TLG, tTLG) (P=0.001), and sum of the MTVs of the primary and metastatic lesions (total MTV, tMTV) (P<0.001) were significant predictors of PFS. In multivariate analysis, MTV was an independent predictor of PFS [hazard ratio (HR) =2.785; 95% confidence interval (CI): 1.204-6.441; P=0.017]. In the univariate Cox regression analysis, liver parenchymal invasion (P=0.001), lymph node metastasis (P=0.027), distant metastases (P=0.036), tumor differentiation (P=0.047), surgery (P=0.002), neutrophil-to-lymphocyte ratio (NLR) (P=0.011), CEA level (P=0.036), CA19-9 level (P<0.001), TLG (P=0.007), MTV (P<0.001), tTLG (P=0.003), and tMTV (P<0.001) were significant predictors of OS. In the multivariate analysis, higher CA19-9 levels >37 U/mL and a greater tMTV (HR =2.961; 95% CI: 1.092-8.024; P=0.033) were predictive of OS. Conclusions: Our study results suggest that pretreatment 2-[18F]FDG PET parameters can not only assist in the diagnosis of patients with GBA but may also serve as predictive factors for the prognosis of these patients and should thus be applied in their treatment.

Clinical characteristics and prognosis of early-onset cholangiocarcinoma: a population-based study.

BACKGROUND: Little is known about the disease of early-onset cholangiocarcinoma (EOC). The primary objective of this study was to compare EOC with later-onset cholangiocarcinoma (LOC) concerning clinical features and survival prognosis. METHODS: 19325 cholangiocarcinoma patients were extracted from 1975 to 2020 in the SEER database. Cox regression analysis and Kaplan-Meier survival curves were used for the evaluation of cause-specific survival (CSS) and overall survival (OS). To reduce confounding, we compared survival differences between the EOC and LOC groups using propensity score matching (PSM). RESULTS: 4037 cholangiocarcinoma patients were included in the study, of which 274 were EOC and 3763 were LOC. Early-onset patients were more likely to be non-white, and intrahepatic cholangiocarcinoma. At diagnosis, patients had advanced AJCC stage, lymph node metastase and distant metastase. The EOC patients were more likely to receive surgery, radiotherapy, and chemotherapy than later-onset patients. Multifactorial COX analysis indicated that EOC patients had lower mortality risk than later-onset patients, and similar results were obtained after PSM; Kaplan-Meier survival curves corroborated that early-onset patients exhibited better OS than later-onset patients, and this survival advantage persisted after PSM. Further subgroup analysis following matching demonstrated that early-onset patients had better OS than later-onset patients in the surgical subgroup, while there were no statistically significant differences in the radiotherapy and chemotherapy subgroups. CONCLUSION: The EOC patients typically exhibit an intrahepatic presentation and generally experience a more favorable prognosis. Surgery emerged as a critical treatment modality significantly influencing the overall prognosis of EOC.

Reciprocal Links Between Friendship Quality and Peer Victimization Among Middle Adolescents.

There is a robust association between friendship quality and victimization in adolescence; yet, it remains unclear whether friendship quality may be linked causally with different forms of victimization in middle adolescence. To fill this gap, this study examines the bidirectional associations of friendship quality and relational/verbal victimization with data collected at two time points, 6 months apart, in a sample of 671 middle Chinese adolescents (Mage = 15.63, SDage = 0.73, 49% males). Cross-lagged panel analyses revealed a two-way relationship between friendship quality and victimization, which existed in both verbal and relational victimization. Multi-group panel analyses observed that the cross-lagged associations between friendship quality and relational/verbal victimization were only found for males, but not for females. This result suggests that adolescent males' victimization is both affected by and a predictor of friendship quality, with implications for youth prevention programs.

Diagnostic and prognostic value of the gut microbiota and its metabolite butyrate in children with biliary atresia.

PURPOSE: To determine the prevalent microbiological profile of biliary atresia (BA) patients at the time of its occurrence by studying their intestinal flora. METHODS: A total of 118 gut microbiota samples from three groups of 43 BA patients, 33 disease controls (DC) with other cholestatic diseases and 42 healthy controls (HC), were analyzed by deep mining of public data. Subsequently, a total of 23 fecal samples from three groups of clinically collected patients (11 BA, 6 DC and 6 HC) were sequenced for 16S rRNA gene amplification and analyzed for serum butyrate (BU) level by liquid chromatography. RESULTS: Taxonomic analysis revealed significant differences in the composition of the intestinal microbiota between BA patients and controls, with a reduction in diversity and a higher abundance of Proteobacteria, Streptococcus and Lactobacillus in the BA group. Database and clinical data analyses concluded that Streptococcus/Bacteroides (AUC = 0.9035, 95% CI 0.8347-0.9722, P < 0.0001) or Streptococcus/Eggerthella (AUC = 0.8333, 95% CI 0.6340-1.000, P = 0.027) was the best microbiota to differentiate between BA and DC. Serum butyrate levels were low in the BA and DC groups and differed from the HC group (P = 0.01, P = 0.04). Butyrate levels in BA were negatively correlated with jaundice clearance and cholangitis, but not statistically significant. CONCLUSIONS: Our study reveals changes in the composition of the gut microbiota in BA, especially the butyrate-producing microbiota, and suggests the potential for using gut microbiota as a noninvasive diagnostic benefit for BA. Low levels of serum butyrate in BA may indicate a poor prognosis.

Radiomic analysis will add differential diagnostic value of benign and malignant pulmonary nodules: a hybrid imaging study based on [18F]FDG and [18F]FLT PET/CT.

PURPOSE: To investigate the clinical value of radiomic analysis on [18F]FDG and [18F]FLT PET on the differentiation of [18F]FDG-avid benign and malignant pulmonary nodules (PNs). METHODS: Data of 113 patients with inconclusive PNs based on preoperative [18F]FDG PET/CT who underwent additional [18F]FLT PET/CT scans within a week were retrospectively analyzed in the present study. Three methods of analysis including visual analysis, radiomic analysis based on [18F]FDG PET/CT images alone, and radiomic analysis based on dual-tracer PET/CT images were evaluated for differential diagnostic value of benign and malignant PNs. RESULTS: A total of 678 radiomic features were extracted from volumes of interest (VOIs) of 123 PNs. Fourteen valuable features were thereafter selected. Based on a visual analysis of [18F]FDG PET/CT images, the diagnostic accuracy, sensitivity, and specificity were 61.6%, 90%, and 28.8%, respectively. For the test set, the area under the curve (AUC), sensitivity, and specificity of the radiomic models based on [18F]FDG PET/CT plus [18F]FLT signature were equal or better than radiomics based on [18F]FDG PET/CT only (0.838 vs 0.810, 0.778 vs 0.778, 0.750 vs 0.688, respectively). CONCLUSION: Radiomic analysis based on dual-tracer PET/CT images is clinically promising and feasible for the differentiation between benign and malignant PNs. CLINICAL RELEVANCE STATEMENT: Radiomic analysis will add differential diagnostic value of benign and malignant pulmonary nodules: a hybrid imaging study based on [18F]FDG and [18F]FLT PET/CT. KEY POINTS: • Radiomics brings new insights into the differentiation of benign and malignant pulmonary nodules beyond the naked eyes. • Dual-tracer imaging shows the biological behaviors of cancerous cells from different aspects. • Radiomics helps us get to the histological view in a non-invasive approach.

Development and post-Kasai procedure prognostic relevance of histological features for biliary atresia.

OBJECTIVES: To validate an appropriate evaluation method of liver fibrosis assessment based on the unique pathological features of biliary atresia (BA) that could well predict its prognosis. METHODS: A total of 68 patients with BA who underwent Kasai procedure (KP) and an intraoperative liver biopsy, followed up from January 2019 to December 2021, were recruited in a retrospective analysis. Ishak, Metavir, and BA-specific staging systems in relation to outcomes were analyzed using logistic regression, COX proportional hazard regression, Kaplan-Meier analysis, etc. RESULTS: Kaplan-Meier analysis determined a significant difference in native liver survival according to the BA-specific stage (p = 0.002). The ROC curve analysis for predicting prognosis showed that the AUC of BA-specific staging combined with iBALF and severe bile duct proliferation (BDP) (0.811, 95% CI: 0.710-0.913, p < 0.0001) was higher than BA-specific staging alone (0.755, 95% CI: 0.639-0.872, p < 0.001). CONCLUSIONS: The BA-specific staging system reflects the condition of the liver fibrosis, and its combination with iBALF and severe BDP helps to better evaluate the prognosis of patients with BA.

Research trends and hotspots of exercise therapy in Panvascular disease: A bibliometric analysis.

Panvascular diseases are a group of vascular system diseases, mainly including the heart, brain, neck, and other parts of the vascular lesions. As a non-pharmacological intervention, exercise therapy could prevent and treat Panvascular diseases. However, few bibliometric analyses of exercise therapy in Panvascular disease exist. This study aimed to analyze the trends and hotspots over the past decade and provide insights into the latest state of the art in global research, thereby contributing to further research in the field. We systematically searched the Web of Science Core Collection (WOSCC) for articles on exercise therapy and Panvascular disease. The acquired information from the reports was analyzed using CiteSpace and VOSviewer software to assess and forecast this field hottest areas and trends. The final analysis included 294 articles by our specified inclusion criteria. The number of publications has gradually increased over the past decade. Stroke was one of the most studied Panvascular diseases. China and the University of Sao Paulo were the country es and institutions that contributed the most to the field. Mary M. McDermott was the most prolific researcher, and the Journal of Vascular Surgery published the most articles. The 6-minute walk test, skeletal muscle, oxidative stress, and supervised exercise therapy were hot topics from 2019 to 2023. In conclusion, exploring exercise therapy programs and exercise mechanisms for Panvascular diseases has been ongoing. This study revealed the current status and trends of research in the field and identified hot topics. It was helpful for scholars to understand exercise therapy critical role in treating and preventing Panvascular diseases and provided a reference for clinical decision-making and further research.

Electrical stimulation induces anti-tumor immunomodulation via a flexible microneedle-array-integrated interdigital electrode.

Immunotherapy has revolutionized cancer therapy, using chemical or biological agents to reinvigorate the immune system. However, most of these agents have poor tumor penetration and inevitable side effects that complicate therapeutic outcomes. Electrical stimulation (ES) is a promising alternative therapy against cancers that does not involve chemical or biological agents but is limited in the fabrication and operation of complex micrometer-scale ES devices. Here, we present an optically microprinted flexible interdigital electrode with a gold-plated polymer microneedle array to generate alternating electric fields for cancer treatment. A flexible microneedle-array-integrated interdigital electrode (FMIE) was fabricated by combining optical 3D microprinting and electroless plating processes. FMIE-mediated ES of cancer cells induced necrotic cell death through mitochondrial Ca2+ overload and increased intracellular reactive oxygen species (ROS) production. This led to the release of damage-associated molecular patterns that activated the immune response and potentiated immunogenic cell death (ICD). FMIE-based ES has an excellent safety profile and systemic anti-tumor effects, inhibiting the growth of primary and distant tumors as well as melanoma lung metastasis. FMIE-based ES-driven cancer immunomodulation provides a new pathway for drug-free cancer therapy.

Urinary exosomes: a promising biomarker of drug-induced nephrotoxicity.

Drug-induced nephrotoxicity (DIN) is a big concern for clinical medication, but the clinical use of certain nephrotoxic drugs is still inevitable. Current testing methods make it hard to detect early renal injury accurately. In addition to understanding the pathogenesis and risk factors of drug-induced nephrotoxicity, it is crucial to identify specific renal injury biomarkers for early detection of DIN. Urine is an ideal sample source for biomarkers related to kidney disease, and urinary exosomes have great potential as biomarkers for predicting DIN, which has attracted the attention of many scholars. In the present paper, we will first introduce the mechanism of DIN and the biogenesis of urinary exosomes. Finally, we will discuss the changes in urinary exosomes in DIN and compare them with other predictive indicators to enrich and boost the development of biomarkers of DIN.

Multiparameter diagnostic model based on 18F-FDG positron emission tomography and serological examination for differentiating focal autoimmune pancreatitis from pancreatic ductal adenocarcinoma.

Background: 18F-fluorodeoxyglucose positron emission tomography-computerized tomography (18F-FDG PET-CT) has demonstrated high sensitivity in the diagnosis of autoimmune pancreatitis (AIP) and pancreatic ductal adenocarcinoma (PDAC), while also exhibiting the ability to distinguish AIP from PDAC lesions. The objective of this investigation was to assess the efficacy of multiparametric 18F-FDG PET with serological examination for distinguishing focal AIP (f-AIP) from PDAC. Methods: A total of 127 patients (43 with f-AIP and 84 with PDAC) who received 18F-FDG PET-CT before treatment were retrospectively included in the cohort study conducted at two centers, Beijing Friendship Hospital and Chinese PLA General Hospital, from January 2015 to December 2021. The baseline characteristics and clinical data were collected. The metabolism parameters of 18F-FDG PET, including maximum standardized uptake value (SUVmax), tumor-to-normal liver SUV ratio (SUVR), mean SUV (SUVmean), total lesion glycolysis (TLG), and metabolic tumor volume (MTV) were evaluated. The area under the receiver operating characteristic (ROC) curve was used to evaluate the differential diagnostic efficacy. The diagnostic efficacy improvement was assessed through the integrated discriminatory improvement (IDI), net reclassification improvement (NRI), and DeLong test. Results: Serum immunoglobulin G4 (IgG4) >280 mg/dL, carbohydrate antigen 19-9 (CA19-9) <85 U/mL, and metabolic parameters differed significantly between patients with f-AID and PDAC. The ROC curve analysis of MTV showed the highest differentiating diagnostic value [sensitivity =0.814, 95% confidence interval (CI): 0.661-0.911; specificity =0.893, 95% CI: 0.802-0.947; area under the curve (AUC) =0.890, 95% CI: 0.820-0.957]. The combined diagnostics model of serum IgG4 >280 mg/dL, CA19-9 <85 U/mL, and MTV resulted in the highest AUC of 0.991 (95% CI: 0.978-1.000; sensitivity =0.953, 95% CI: 0.829-0.992; specificity =0.964, 95% CI: 0.892-0.991). Conclusions: The multiparameter diagnostic model based on 18F-FDG PET and serological examination has excellent clinical value in the differential diagnosis of f-AID and PDAC.

Survival analysis of extragastrointestinal stromal tumors based on the SEER database: a population-based study.

BACKGROUND: Extragastrointestinal stromal tumors (EGISTs) are rare mesenchymal neoplasms that originate outside the gastrointestinal tract. However, the population-level survival analysis of EGIST remains poorly grasped. Therefore, we aimed to analyze the survival of EGIST patients using the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: All patients diagnosed with GIST and EGIST between 2000 and 2019 were identified through utilization of the SEER database. Missing data were handled using multiple imputation methodology. Kaplan-Meier analyses and Cox proportional hazard models were employed to assess the influence of demographic and clinical characteristics on both overall survival (OS) and cancer-specific survival (CSS). RESULTS: A total of 13,330 patients were enrolled in the study, comprising 12,627 diagnosed with GIST and 703 with EGIST. EGIST patients demonstrated significantly poorer OS [hazard ratio (HR) 1.732, 95% confidence interval (CI) 1.522-1.970, P < 0.001] and CSS (HR 2.167, 95% CI 1.821-2.577, P < 0.001) compared to GIST patients. The mean 1-year, 3-year, 5-year, and 10-year OS rates for EGIST patients were 78.3%, 61.9%, 50.5%, and 32.5%, respectively, with corresponding mean CSS rates of 84.3%, 70.8%, 61.3%, and 46.5%. Multivariate Cox regression analysis identified age, race, sex, grade, size, and surgical type as independent risk factors for OS in EGIST patients, while age, sex, year of diagnosis, grade, surgical type, and radiation therapy were identified as independent risk factors for CSS. Patients with EGIST who underwent surgical treatment exhibited significantly higher 5-year OS rates (49.0% vs. 39.9%, P = 0.035) and CSS rates (63.9% vs. 53.0%, P = 0.028) compared to those who did not undergo surgery. CONCLUSIONS: EGIST patients have a poorer prognosis compared to GIST patients; however, surgical treatment has been shown to improve the prognosis.

Multifunctional Nanoassembly for MRI-Trackable Dendritic Cell Dependent and Independent Photoimmunotherapy.

Immunotherapy has emerged as a triumph in the treatment of malignant cancers. Nevertheless, current immunotherapeutics are insufficient in addressing tumors characterized by tumor cells' inadequate antigenicity and the tumor microenvironment's low immunogenicity (TME). Herein, we developed a novel multifunctional nanoassembly termed FMMC through the self-assembly of indoleamine 2,3-dioxygenase 1 (IDO-1) inhibitor 1-methyl-tryptophan prodrug (FM), Ce6, and ionic manganese (Mn2+) via noncovalent interactions. The laser-ignited FMMC treatment could induce effective immunogenic cell death and activate the STING/MHC-I signaling pathway, thus deeply sculpting the tumor-intrinsic antigenicity to achieve dendritic cell (DC)-dependent and -independent T cell responses against tumors. Meanwhile, by inhibiting IDO-1, FMMC could lead to immunosuppressive TME reversion to an immunoactivated one. FMMC-based phototherapy led to the up-regulation of programmed death-ligand 1 (PD-L1), enhancing the sensitivity of tumors to anti-PD-1 therapy. Furthermore, the incorporation of Mn2+ into FMMC resulted in an augmented longitudinal relaxivity and enhanced the MRI for monitoring the growth of primary tumors and lung metastases. Collectively, the superior reprogramming performance of immunosuppressive tumor cells and TME, combined with excellent anticancer efficacy and MRI capability, made FMMC a promising immune nanosculptor for cancer theranostics.

Linc00657 promoted pyroptosis in THP-1-derived macrophages and exacerbated atherosclerosis via the miR-106b-5p/TXNIP/NLRP3 axis.

Long intergenic non-coding RNA 00657 (linc00657) is involved in various diseases, whereas its role in atherosclerosis (AS) development remains inconclusive. This study was designed to investigate the effects and underlying mechanisms of linc00657 in atherogenesis. The results showed that ox-LDL treatment significantly induced pyroptosis in human THP-1-derived macrophages. The secretion levels of LDH and pro-inflammatory factors were markedly enhanced, and the integrity of plasma membranes was disrupted in ox-LDL-treated THP-1-derived macrophages. These effects were significantly compensated after transfection with linc00657 siRNA and became more evident by linc00657 overexpression. Moreover, the effects of linc00657 overexpression on pyroptosis of THP-1-derived macrophages can also be robustly reversed by TXNIP knockdown or miR-106b-5p mimics transfection. Mechanistically, linc00657 enhanced TXNIP expression by competitively binding to miR-106b-5p, promoting NLRP3 inflammasome activation. Finally, we found that linc00657 overexpression significantly increased the expression of pyroptosis-related factors and decreased miR-106b-5p level in the aorta of high-fat-diet-fed apoE-/- mice. Furthermore, linc00657 up-regulation enlarged the plaque area, exacerbated plasma lipid profile, and increased pro-inflammatory cytokines levels in the serum, effects that were reversed by injection of miR-106b-5p agomir. This evidence indicated that linc00657 stimulated macrophage pyroptosis and aggravated the progression of AS via the miR-106b-5p/TXNIP/NLRP3 pathway.

Protective role of resilience on the associations between childhood maltreatment and internalising and externalising problems.

Different types of childhood maltreatment have negative effects on individual mental and behavioural outcomes. However, most of previous studies investigated their effects separately. Little is known about the effects of co-occurring maltreatment profiles on adolescents' developmental outcomes and the potential protective factor. The current study sought to identify distinct profiles of childhood maltreatment and examine the effects of profiles of childhood maltreatment on internalising and externalising problems and the protective role of resilience based on two-wave longitudinal data, which was collected from a sample of 670 Chinese adolescents (Mage  = 15.50, SDage  = 0.75, 48.4% boys). Four profiles of childhood maltreatment, that is, No maltreatment (67.9%), High neglect (23.0%), High abuse and neglect/Low sexual abuse (5.0%), and Multi-maltreatment (4.1%), were identified. Adolescents in High neglect, High abuse and neglect/Low sexual abuse, and Multi-maltreatment profiles were more likely to report internalising and externalising problems. Further, significant moderating effects of resilience only emerged for the association between the High neglect profile and internalising problems, such that high levels of resilience may weaken the association between the High neglect profile and internalising problems. Our findings revealed the importance and utility of identifying maltreatment profiles to tailor treatment based on specific maltreatment experiences. Resilience-oriented intervention could be considered for Chinese adolescents who have experienced high neglect.

Lotus Leaf Derived NiS/Carbon Nanofibers/Porous Carbon Heterogeneous Structures for Strong and Broadband Microwave Absorption.

Developing composite materials with the synergistic effects of heterogeneous structures and multiple components is considered as a promising strategy to achieve high-performance electromagnetic wave (EMW) absorbers. To further satisfy the demand of broadband and strong microwave absorption, a novel NiS/carbon nanofibers (CNFs)/porous carbon composite is successfully synthesized by hydrothermal and chemical vapor deposition using lotus leaves as a biomass carbon source. A few carbon nanotubes (CNTs) and uniformly dispersed Ni nanocrystals have also been found in the hybrid. Benefiting from the porous structure derived from lotus leaves, the combination of dielectric NiS, conductive carbon nanomaterials, and magnetic Ni nanoparticles, together with the three-dimensional conductive network of CNFs and CNTs, the remarkable EMW absorption properties with a minimum reflection loss up to -67.65 dB have been achieved at merely 2.32 mm. Besides, the widest effective absorption band can reach 5.9 GHz with a thin thickness of 2.07 mm, covering almost the entire Ku band. In addition, under the incident angle of 31°, the radar cross-section reduction value of LNSF-600 can reach 42.88 dBm2. Therefore, this work provides an efficient and facile method for manufacturing outstanding biomass-derived EMW absorbers.