Functional near-infrared spectroscopy-based neurofeedback training regulates time-on-task effects and enhances sustained cognitive performance.

Time-on-task effect is a common consequence of long-term cognitive demand work, which reflects reduced behavioral performance and increases the risk of accidents. Neurofeedback is a neuromodulation method that can guide individuals to regulate their brain activity and manifest as changes in related symptoms and cognitive behaviors. This study aimed to examine the effects of functional near-infrared spectroscopy-based neurofeedback training on time-on-task effects and sustained cognitive performance. A randomized, single-blind, sham-controlled study was performed: 17 participants received feedback signals of their own dorsolateral prefrontal cortex activity (neurofeedback group), and 16 participants received feedback signals of dorsolateral prefrontal cortex activity from the neurofeedback group (sham-neurofeedback group). All participants received 5 neurofeedback training sessions and completed 2 sustained cognitive tasks, including a 2-back task and a psychomotor vigilance task, to evaluate behavioral performance changes following neurofeedback training. Results showed that neurofeedback relative to the sham-neurofeedback group exhibited increased dorsolateral prefrontal cortex activation, increased accuracy in the 2-back task, and decreased mean response time in the psychomotor vigilance task after neurofeedback training. In addition, the neurofeedback group showed slower decline performance during the sustained 2-back task after neurofeedback training compared with sham-neurofeedback group. These findings demonstrate that neurofeedback training could regulate time-on-task effects on difficult task and enhance performance on sustained cognitive tasks by increasing dorsolateral prefrontal cortex activity.

The first-in-human preclinical evaluation of the new probe [123I]I-PSMA-7 for real-time intraoperative targeted biopsy and SPECT/CT imaging in prostate cancer.

PURPOSE: PSMA/PET has been increasingly used to detect PCa, and PSMA/PET-guided biopsy has shown promising results. However, it cannot be confirmed immediately whether the tissues are the targeted area. In this study, we aimed to develop a novel probe, [123I]I-PSMA-7. First, we hope that [123I]I-PSMA-7 can provide instant confirmation for prostate biopsy. Second, we hope it will help detect PCa. METHODS: We synthesized a high-affinity probe, [123I]I-PSMA-7, and evaluated its properties. We included ten patients with suspected PCa and divided them into two groups. The injection and biopsy were approximately 24 h apart. The activity in biopsy lesions was measured as the cpm by a γ-counter. Moreover, we enrolled 3 patients to evaluate the potential of [123I]I-PSMA-7 for detecting PCa. RESULTS: Animal experiments verified the safety, targeting and effectiveness of [123I]I-PSMA-7, and the tumor-to-muscle ratio was greatest at 24 h, which confirmed the results of this study in humans. After injection of 185MBq [123I]I-PSMA-7, 18/55 cores were positive, and the cpm was significantly greater (4345 ± 3547 vs. 714 ± 547, P < 0.001), with an AUC of 0.97 and a cutoff of 1312 (sens/spec of 94.40%/91.90%). At a lower dose, 10/55 biopsy cores were cancerous, and the cpm was 2446 ± 1622 vs. 153 ± 112 (P < 0.001). The AUC was 1, with a cutoff value of 490 (sens/spec of 100%). When the radiopharmaceuticals were added to 370 MBq, we achieved better SPECT/CT imaging. CONCLUSION: With the aid of [123I]I-PSMA-7 and via cpm-based biopsy, we can reduce the number of biopsies to a minimum operation. [123I]I-PSMA-7 PSMA SPECT/CT can also provide good imaging results. TRIAL REGISTRATION: Chinese Clinical trial registry ChiCTR2300069745, Registered 24 March 2023.

Neuroprotection of Human Umbilical Cord-Derived Mesenchymal Stem Cells (hUC-MSCs) in Alleviating Ischemic Stroke-Induced Brain Injury by Regulating Inflammation and Oxidative Stress.

Brain injury caused by stroke has a high rate of mortality and remains a major medical challenge worldwide. In recent years, there has been significant attention given to the use of human Umbilical cord-derived Mesenchymal Stem Cells (hUC-MSCs) for the treatment of stroke in different adult and neonate animal models of stroke. However, using hUC-MSCs by systemic administration to treat ischemic stroke has not been investigated sufficiently. In this study, we conducted various experiments to explore the neuroprotection of hUC-MSCs in rats. Our findings demonstrate that an intravenous injection of a high dose of hUC-MSCs at 2 × 10^7 cells/kg markedly ameliorated brain injury resulting from ischemic stroke. This improvement was observed one day after inducing transient middle cerebral artery occlusion (MCAO) and subsequent reperfusion in rats. Notably, the efficacy of this single administration of hUC-MSCs surpassed that of edaravone, even when the latter was used continuously over three days. Mechanistically, secretory factors derived from hUC-MSCs, such as HGF, BDNF, and TNFR1, ameliorated the levels of MDA and T-SOD to regulate oxidative stress. In particular, TNFR1 also improved the expression of NQO-1 and HO-1, important proteins associated with oxidative stress. More importantly, TNFR1 played a significant role in reducing inflammation by modulating IL-6 levels in the blood. Furthermore, TNFR1 was observed to influence the permeability of the blood-brain barrier (BBB) as demonstrated in the evan's blue experiment and protein expression of ZO-1. This study represented a breakthrough in traditional methods and provided a novel strategy for clinical medication and trials.

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.

The influence of lymphadenectomy on the prognosis of small intestinal stromal tumors: a study based on the SEER database.

BACKGROUND: Small intestinal stromal tumors (SISTs) typically require surgical treatment. However, the impact of lymphadenectomy (LA) on long-term prognosis in patients remains unclear. Therefore, we plan to analyze the effect of LA on the prognosis of patients with SISTs using the Surveillance, Epidemiology, and End Results (SEER) database. METHODS: Data on SISTs patients between 2000 and 2019 were obtained from the SEER database. Multiple imputation (MI) was employed to handle missing data, while propensity score matching (PSM) was conducted to mitigate selection bias in the comparative assessments between the LA group and the No-LA group. Kaplan-Meier analyses and multivariate Cox proportional hazards models were utilized to evaluate both overall survival (OS) and cancer-specific survival (CSS). RESULTS: A total of 2412 patients diagnosed with SISTs were included in the study, with 879 undergoing LA and 1533 not undergoing LA. There were no significant differences observed between the two cohorts concerning long-term OS (hazard ratio [HR] 0.97, 95% confidence interval [CI] 0.84-1.13, P = 0.720) and CSS (HR 1.05, 95% CI 0.86-1.29, P = 0.622). After PSM, 1596 patients (798 in the LA group and 789 in the No-LA group) were matched for comparison. There was also no difference in long-term OS and CSS between the two groups. Subgroup analysis revealed that in the age group > 60 years, the CSS in the No-LA group was superior to that in the LA group. Multivariate Cox regression analysis revealed that age, M stage, marital status, and mitotic rate are significant risk factors influencing OS and CSS. CONCLUSIONS: Conducting LA in patients with SISTs does not enhance long-term prognosis. For patients aged over 60 years, it may be more advisable to refrain from performing LA.

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.

Clinical efficacy and pain follow-up after arthroscopic discoid meniscoplasty of the knee: a retrospective study.

BACKGROUND: To assess the viability and efficiency of performing arthroscopic meniscoplasty in treating discoid meniscus (DM) in the knee joint. METHODS: A total of 29 patients diagnosed with symptomatic lateral DM between October 2014 and December 2019 were included in the study. Among them, 7 patients with intact DM underwent arthroscopic discoid meniscoplasty (group A), while 22 patients with torn DM received arthroscopic DM plasty along with repair and suturing (group B). Both Visual Analog Scale (VAS) score and Lysholm score assessments were conducted preoperatively and postoperatively. RESULT: The favorable and acceptable outcome rate was 85.71% in group A and 95.45% in group B (P > 0.05). The VAS scores post-operatively at each follow-up time point were consistently lower compared to pre-operative values, while the Lysholm knee function scores showed improvement. There were no significant differences in VAS score and Lysholm score between group A and group B at different stages (P > 0.05). Both surgical techniques (discoid meniscoplasty and discoid meniscoplasty combined with repair and suture) showed significant improvement in postoperative VAS score and Lysholm score, but there was no difference in outcomes between the two groups. CONCLUSION: Overall, the two surgical techniques studied in this study (discoid meniscoplasty and discoid meniscoplasty combined with repair and suture) produced similar results in terms of pain reduction and improved knee function.

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.

Systematic review of the mechanism and assessment of liver fibrosis in biliary atresia.

PURPOSE: This study systematically reviewed our team's research on the mechanism and assessment of liver fibrosis in BA, summarized our experience, and discussed the future development direction. METHODS: In this study, Pubmed and Wanfang databases were searched to collect the literature published by our team on the mechanisms of liver fibrosis in BA and the assessment of liver fibrosis in BA, and the above research results were systematically reviewed. RESULTS: A total of 58 articles were retrieved. Among the included articles, 25 articles related to the mechanism of liver fibrosis in BA, and five articles evaluated liver fibrosis in BA. This article introduces the key pathways and molecules of liver fibrosis in BA and proposes a new grading system for liver fibrosis in BA. CONCLUSIONS: The new BA liver fibrosis grading method is expected to assess children's conditions, guide treatment, and improve prognosis more accurately. In addition, we believe that the TGF-ß1 signaling pathway is the most important in the study of liver fibrosis in BA, and at the same time, the study of EMT occurrence in BA should also be deepened to resolve the controversy on this issue.

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.

Profiles of Family and School Experiences and Adjustment of Adolescents During the Transition to High School.

Although family and school experiences play an important role in adolescents' adjustment during the transition to high school, most prior studies investigated the effects of these experiences in isolation; their joint implications for both adolescents' concurrent and long-term adjustment outcomes are less clear, and the potential role of individual characteristics within such associations remains understudied. Based on 525 10th graders (Mage = 15.48, SDage = 0.71, 43.6% boys) who participated in a longitudinal study, the present research aimed to identify distinct family and school experience profiles among first-year high school students and examine their associations with adolescents' internalizing problems and externalizing problems, both concurrently and 18 months later. Latent profile analysis revealed four distinctive profiles: thriving, low resources-moderate family risk, developmental stress-high parental conflicts, and developmental stress-high peer victimization profiles. The other three profiles (vs. the thriving profile) reported significantly higher levels of concurrent internalizing problems; while these differences diminished after 18 months. However, the enduring impacts of these profiles on internalizing problems persisted among adolescents with higher levels of environmental sensitivity. Additionally, adolescents characterized by two developmental stress profiles (vs. the thriving profile) exhibited significantly higher levels of externalizing problems both currently and longitudinally. Findings underscore the importance of identifying at-risk populations among adolescents during the transition to high school by including both family and school experiences when examining environmental influence on their adjustment, as well as the necessity to take individual environmental sensitivity into account when examining these associations.

Highly Sensitive Imaging of Tumor Metastasis Based on the Targeting and Polarization of M2-like Macrophages.

Tumor-associated macrophages, especially M2-like macrophages, are extensively involved in tumor growth and metastasis, suppressing the innate immunity to help tumor cells escape and reshaping the microenvironment to help metastatic cells grow. However, in vivo, real-time visualized migration of M2-like macrophages has never been explored to monitor the tumor metastasis process. Herein, we prepared an M2-like macrophage-targeting nitric oxide (NO)-responsive nanoprobe (NRP@M-PHCQ) consisting of an amphiphilic block copolymer with mannose and hydroxychloroquine (HCQ) moieties (denoted as M-PHCQ) and a NO-responsive NIR-II probe (denoted as NRP). The mannose moieties provided M2-like macrophage-targeting capacity, and the HCQ moieties polarized M2-like macrophages to M1-like ones with enhanced NO secretion. Consequently, NRP@M-PHCQ was lit up by the secreted NO to visualize the migration and polarization of M2-like macrophages in real time. In vivo metastasis imaging with NRP@M-PHCQ successfully tracked early tumor metastasis in the lymph nodes and the lungs with high sensitivity, even superior to Luci-labeled bioluminescence imaging, suggesting the extensive distribution and critical role of M2-like macrophages in tumor metastasis. In general, this work provided a new strategy to sensitively image metastatic tumors by tracking the polarization of M2-like macrophages and visually disclosed the critical role of M2-like macrophages in early tumor metastasis.

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.

Multiparameter diagnostic model based on 18F-FDG PET metabolic parameters and clinical variables can differentiate nonmetastatic gallbladder cancer and cholecystitis.

OBJECTIVE: To evaluate the diagnostic value of a multiparameter model based on 18F-fluorodeoxyglucose positron emission tomography (18F-FDG PET) metabolic parameters and clinical variables in differentiating nonmetastatic gallbladder cancer (GBC) from cholecystitis. PATIENTS AND METHODS: In total, 122 patients (88 GBC nonmetastatic patients and 34 cholecystitis patients) with gallbladder space-occupying lesions who underwent 18F-FDG PET/CT were included. All patients received surgery and pathology, and baseline characteristics and clinical data were also collected. The metabolic parameters of 18F-FDG PET, including SUVmax (maximum standard uptake value), SUVmean (mean standard uptake value), SUVpeak (peak standard uptake value), MTV (metabolic tumour volume), TLG (total lesion glycolysis) and SUVR (tumour-to-normal liver standard uptake value ratio), were evaluated. The differential diagnostic efficacy of each independent parameter and multiparameter combination model was evaluated using the receiver operating characteristic (ROC) curve. The improvement in diagnostic efficacy using a combination of the above multiple parameters was evaluated by integrated discriminatory improvement (IDI), net reclassification improvement (NRI) and bootstrap test. Decision curve analysis (DCA) was used to evaluate clinical efficacy. RESULTS: The ROC curve showed that SUVR had the highest diagnostic ability among the 18F-FDG PET metabolic parameters (area under the curve [AUC] = 0.698; sensitivity = 0.341; specificity = 0.971; positive predictive value [PPV] = 0.968; negative predictive value [NPV] = 0.363). The combined diagnostic model of cholecystolithiasis, fever, CEA > 5 ng/ml and SUVR showed an AUC of 0.899 (sensitivity = 0.909, specificity = 0.735, PPV = 0.899, NPV = 0.758). The diagnostic efficiency of the model was improved significantly compared with SUVR. The clinical efficacy of the model was confirmed by DCA. CONCLUSIONS: The multiparameter diagnostic model composed of 18F-FDG PET metabolic parameters (SUVR) and clinical variables, including patient signs (fever), medical history (cholecystolithiasis) and laboratory examination (CEA > 5 ng/ml), has good diagnostic efficacy in the differential diagnosis of nonmetastatic GBC and cholecystitis.

Application Value of the Automated Machine Learning Model Based on Modified Computed Tomography Severity Index Combined With Serological Indicators in the Early Prediction of Severe Acute Pancreatitis.

BACKGROUND AND AIMS: Machine learning (ML) algorithms are widely applied in building models of medicine due to their powerful studying and generalizing ability. To assess the value of the Modified Computed Tomography Severity Index (MCTSI) combined with serological indicators for early prediction of severe acute pancreatitis (SAP) by automated ML (AutoML). PATIENTS AND METHODS: The clinical data, of the patients with acute pancreatitis (AP) hospitalized in Hospital 1 and hospital 2 from January 2017 to December 2021, were retrospectively analyzed. Serological indicators within 24 hours of admission were collected. MCTSI score was completed by noncontrast computed tomography within 24 hours of admission. Data from the hospital 1 were adopted for training, and data from the hospital 2 were adopted for external validation. The diagnosis of AP and SAP was based on the 2012 revised Atlanta classification of AP. Models were built using traditional logistic regression and AutoML analysis with 4 types of algorithms. The performance of models was evaluated by the receiver operating characteristic curve, the calibration curve, and the decision curve analysis based on logistic regression and decision curve analysis, feature importance, SHapley Additive exPlanation Plot, and Local Interpretable Model Agnostic Explanation based on AutoML. RESULTS: A total of 499 patients were used to develop the models in the training data set. An independent data set of 201 patients was used to test the models. The model developed by the Deep Neural Net (DL) outperformed other models with an area under the receiver operating characteristic curve (areas under the curve) of 0.907 in the test set. Furthermore, among these AutoML models, the DL and gradient boosting machine models achieved the highest sensitivity values, both exceeding 0.800. CONCLUSION: The AutoML model based on the MCTSI score combined with serological indicators has good predictive value for SAP in the early stage.

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.

Development and validation of a preoperative difficulty scoring system for endoscopic resection of gastric gastrointestinal stromal tumor: a multi-center study.

BACKGROUND: Endoscopic resection (ER) is a promising technique for resecting gastric gastrointestinal stromal tumors (gGISTs); however, ER is technically challenging. This study aimed to develop and validate a difficulty scoring system (DSS) to determine the difficulty for ER of a gGIST. METHODS: This retrospective study enrolled 555 patients with gGISTs in multi-centers from December 2010 to December 2022. Data on patients, lesions, and outcomes of ER were collected and analyzed. A difficult case was defined as an operative time ≥ 90 min, or the occurrence of severe intraoperative bleeding, or conversion to laparoscopic resection. The DSS was developed in the training cohort (TC) and validated in the internal validation cohort (IVC) and external validation cohort (EVC). RESULTS: The difficulty occurred in 97 cases (17.5%). The DSS comprised the following: tumor size ≥ 3.0 cm (3 points) or 2.0-3.0 cm (1 point); location in the upper third of the stomach (2 points); invasion depth beyond the muscularis propria (2 points); lack of experience (1 point). The area under the curve (AUC) of DSS in IVC and EVC was 0.838 and 0.864, respectively, and the negative predictive value (NPV) was 0.923 and 0.972, respectively. The proportions of difficult operation in easy (score 0-3), intermediate (score 4-5), and difficult (score 6-8) categories were 6.5%, 29.4%, and 88.2% in the TC, 7.7%, 45.8%, and 85.7% in the IVC, and 7.0%, 29.4%, and 85.7% in the EVC, respectively. CONCLUSIONS: We developed and validated a preoperative DSS for ER of gGISTs based on tumor size, location, invasion depth, and endoscopists' experience. This DSS can be used to grade the technical difficulty before surgery.

Risk factors for postoperative complications in endoscopic resection of gastric gastrointestinal stromal tumors: a multi-center analysis.

BACKGROUND: Endoscopic resection (ER) is widely used in treating gastric gastrointestinal stromal tumors (gGISTs); however, complications occur frequently after resection. We aimed to determine factors associated with postoperative complications for ER of gGISTs. METHODS: This was a retrospective, multi-center, observational study. Consecutive patients who underwent ER of gGISTs at five institutes from January 2013 to December 2022 were analyzed. The risk factors for delayed bleeding and postoperative infection were assessed. RESULTS: A total of 513 cases were finally analyzed. Of 513 patients, 27 (5.3%) had delayed bleeding and 69 (13.4%) had a postoperative infection. Multivariate analysis indicated that risk factors for delayed bleeding were long operative time (OR = 50.655; 95% CI, 13.777-186.252; P < 0.001) and severe intraoperative bleeding (OR = 4.731, 95% CI, 1.139-19.658; P = 0.032), and risk factors for postoperative infection were long operative time (OR = 13.749, 95% CI, 6.884-27.461; P < 0.001) and perforation (OR = 4.339, 95% CI, 2.178-8.644; P < 0.001). CONCLUSIONS: Our study indicated the risk factors for postoperative complications in ER of gGISTs. Long operation time is a common risk factor for delayed bleeding and postoperative infection. Patients with these risk factors should be given careful observation postoperatively.

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.

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.