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Introduction: Hepatic cystic echinococcosis (HCE) is a widely seen parasitic infection. Biological activity is crucial for treatment planning. This work aims to explore the potential applications of a deep learning radiomics (DLR) model, based on CT images, in predicting the biological activity grading of hepatic cystic echinococcosis.Methods: A retrospective analysis of 160 patients with hepatic echinococcosis was performed (127 and 33 in training and validation sets). Volume of interests (VOIs) were drawn, and radiomics features and deep neural network features were extracted. Feature selection was performed on the training set, and radiomics score (Rad Score) and deep learning score (Deep Score) were calculated. Seven diagnostics models (based on logistic regression algorithm) for the biological activity grading were constructed using the selected radiomics features and two deep model features respectively. All models were evaluated using the receiver operating characteristic curve, and the area under the curve (AUC) was calculated. A nomogram was constructed using the combined model, and its calibration, discriminatory ability, and clinical utility were assessed.Results: 12, 6 and 10 optimal radiomics features, deep learning features were selected from two deep learning network (DLN) features, respectively. For biological activity grading of hepatic cystic echinococcosis, the combined model demonstrated strong diagnostic performance, with an AUC value of 0.888 (95% CI: 0.837–0.936) in the training set and 0.876 (0.761–0.964) in the validation set. The clinical decision analysis curve indicated promising results, while the calibration curve revealed that the nomogram’s prediction result was highly compatible with the actual result.Conclusion: The DLR model can be used for predicting the biological activity grading of hepatic echinococcosis.

Abstract Objective We aimed to investigate the association of lipid parameters with parenchymal hemorrhage (PH) and early neurological improvement (ENI) after mechanical thrombectomy (MT) in stroke patients. Methods We retrospectively analyzed consecutive patients who underwent MT between January 2019 and February 2022 at a tertiary stroke center. PH was diagnosed and classified as PH‐1 and PH‐2 according to the European Cooperative Acute Stroke Study definition. ENI was defined as a decrease in the National Institutes of Health Stroke Scale (NIHSS) score by ≥8 or an NIHSS score of ≤1 at 24 h after MT. Results Among 155 patients, PH occurred in 41 (26.5%) patients, and 34 (21.9%) patients achieved ENI. In multivariate analysis, lower triglyceride to high‐density lipoprotein cholesterol ratio (TG/HDL‐C) value (OR = 0.51; 95% CI 0.30–0.89; p = 0.017) and higher HDL‐C level (OR = 5.83; 95% CI 1.26–26.99; p = 0.024) were independently associated with PH. The combination of TG

Objective: To determine the predictors and the long-term outcomes of patients with seizures following surgery for dysembryoplastic neuroepithelial tumors (DNTs); Methods: Clinical data were collected from medical records of consecutive patients of the Department of Neurosurgery of Sanbo Brain Hospital of Capital Medical University with a pathological diagnosis of DNT and who underwent surgery from January 2008 to July 2021. All patients were followed up after surgery for at least one year. We estimated the cumulative rate of seizure recurrence-free and generated survival curves. A log-rank (Mantel–Cox) test and a Cox proportional hazard model were performed for univariate and multivariate analysis to analyze influential predictors; Results: 63 patients (33 males and 30 females) were included in this study. At the final follow-up, 49 patients (77.8%) were seizure-free. The cumulative rate of seizure recurrence-free was 82.5% (95% confidence interval (CI) 71.8–91.3%), 79.0% (95% CI 67.8–88.6%) and 76.5% (95% CI 64.8–87.0%) at 2, 5, and 10 years, respectively. The mean time for seizure recurrence-free was 6.892 ± 0.501 years (95% CI 5.91–7.87). Gross total removal of the tumor and a short epilepsy duration were significant predictors of seizure freedom. Younger age of seizure onset, bilateral interictal epileptiform discharges, and MRI type 3 tumors were risk factors for poor prognosis; Conclusions: A favorable long-term seizure outcome was observed for patients with DNT after surgical resection. Predictor analysis could effectively guide the clinical work and evaluate the prognosis of patients with DNT associated with epilepsy.

As the top-level design for soil environmental protection in China, the 'Action Plan for Soil Pollution Prevention and Control' (abbreviated as the '10-Chapter Soil Pollution Action Plan') encourages enterprises to actively engage in soil pollution prevention and control. Diverging from conventional soil pollution control policies, the '10-Chapter Soil Pollution Action Plan' serves as a protracted working framework for addressing soil pollution in China. Aimed at safeguarding soil environmental quality through institutional means and rigorously curbing new pollution, this plan inherently prioritizes prevention over remediation. This fundamental orientation may yield divergent conclusions in micro-level studies that assess the sustainable remediation effects of the plan. To evaluate the implementation effect of the '10-Chapter Soil Pollution Action Plan,' this study took the A-share enterprises under key soil pollution supervision from 2013 to 2020 as samples and used the difference-in-differences model (DID) to examine the effect and mechanisms of the plan on corporate sustainability. The study found that the '10-Chapter Soil Pollution Action Plan' significantly promoted corporate sustainability, attributable to the risk management principles embedded in these measures. However, this promoting effect could be subject to the reverse adjustment of the regional industrial structure level. In areas where the proportion of the tertiary industry was higher, the promoting effect of the '10-Chapter Soil Pollution Action Plan' on corporate sustainability was more limited. Further research showed that the local government's land finance mechanism and the enterprises' cash defense mechanism were important channels through which the '10-Chapter Soil Pollution Action Plan' played a facilitating role, and this role in promoting corporate sustainability was more significant in state-owned enterprises, large-scale enterprises, and regions under stronger environmental regulations. This study, adopting the perspective of corporate sustainability, serves as a supplement to existing research on the implementation effects of the '10-Chapter Soil Pollution Action Plan.' It highlights the pivotal role of high polluting enterprises in the field of soil pollution prevention and control. The study provides empirical evidence for the formation of a soil pollution prevention and control system that is led by the government and requires corporate responsibility. Additionally, it points out the direction for strengthening corporate responsibility identification and soil pollution control. [ABSTRACT FROM AUTHOR]

Background and Aim: The study aims to develop a hybrid machine learning model for predicting resectability of the pancreatic cancer, which is based on computed tomography (CT) and National Comprehensive Cancer Network (NCCN) guidelines. Method: We retrospectively studied 349 patients. One hundred seventy‐one cases from Center 1 and 92 cases from Center 2 were used as the primary training cohort, and 66 cases from Center 3 and 20 cases from Center 4 were used as the independent test dataset. Semi‐automatic module of ITK‐SNAP software was used to assist CT image segmentation to obtain three‐dimensional (3D) imaging region of interest (ROI). There were 788 handcrafted features extracted for 3D ROI using PyRadiomics. The optimal feature subset consists of three features screened by three feature selection methods as the input of the SVM to construct the conventional radiomics‐based predictive model (cRad). 3D ROI was used to unify the resolution by 3D spline interpolation method for constructing the 3D tumor imaging tensor. Using 3D tumor image tensor as input, 3D kernelled support tensor machine‐based predictive model (KSTM), and 3D ResNet‐based deep learning predictive model (ResNet) were constructed. Multi‐classifier fusion ML model is constructed by fusing cRad, KSTM, and ResNet using multi‐classifier fusion strategy. Two experts with more than 10 years of clinical experience were invited to reevaluate each patient based on their CECT following the NCCN guidelines to obtain resectable, unresectable, and borderline resectable diagnoses. The three results were converted into probability values of 0.25, 0.75, and 0.50, respectively, according to the traditional empirical method. Then it is used as an independent classifier and integrated with multi‐classifier fusion machine learning (ML) model to obtain the human–machine fusion ML model (HMfML). Results: Multi‐classifier fusion ML model's area under receiver operating characteristic curve (AUC; 0.8610), predictive accuracy (ACC: 80.23%), sensitivity (SEN: 78.95%), and specificity (SPE: 80.60%) is better than cRad, KSTM, and ResNet‐based single‐classifier models and their two‐classifier fusion models. This means that three different models have mined complementary CECT feature expression from different perspectives and can be integrated through CFS‐ER, so that the fusion model has better performance. HMfML's AUC (0.8845), ACC (82.56%), SEN (84.21%), SPE (82.09%). This means that ML models might learn extra information from CECT that experts cannot distinguish, thus complementing expert experience and improving the performance of hybrid ML models. Conclusion: HMfML can predict PC resectability with high accuracy. [ABSTRACT FROM AUTHOR]

Objective: To explore the correlation between pulmonary vascular performance and hemodynamics in patients with pulmonary arterial hypertension (PAH), using right heart catheterization (RHC) and intravascular ultrasound (IVUS). Method: A total of 60 patients underwent RHC and IVUS examinations. Of these, 27 patients were diagnosed with PAH associated with connective tissue diseases (PAH-CTD group), 18 patients were diagnosed with other types of PAH (other-types-PAH group), and 15 patients were without PAH (control group). The hemodynamics and morphological parameters of pulmonary vessels in PAH patients were assessed using RHC and IVUS. Results: There were statistically significant differences in right atrial pressure (RAP), pulmonary artery systolic pressure (sPAP), pulmonary artery diastolic pressure (dPAP), mean pulmonary artery pressure (mPAP) and pulmonary vascular resistance (PVR) values between the PAH-CTD group, other-types-PAH group, and the control group (P < .05). No statistically significant difference was noticed in pulmonary artery wedge pressure (PAWP) and cardiac output (CO) values between these three groups (P > .05). The mean wall thickness (MWT), wall thickness percentage (WTP), pulmonary vascular compliance, dilation, elasticity modulus, stiffness index ß, and other indicators were significantly different between these three groups (P < .05). Pairwise comparison showed that the average levels of pulmonary vascular compliance and dilation in PAH-CTD group and other-types-PAH group were lower than those in control group, while the average levels of elastic modulus and stiffness index ß were higher than those in control group. Conclusion: Pulmonary vascular performance deteriorates in PAH patients, and the performance is better in PAH-CTD patients than in other types of PAH. [ABSTRACT FROM AUTHOR]

Acute liver failure (ALF) is a life‐threatening condition. Cell‐based and cell‐free‐based therapies have proven to be effective in treating ALF; however, their clinical application is limited by cell tumorigenicity and extracellular vesicle (EV) isolation in large doses. Here, we explored the effectiveness and mechanism of umbilical cord mesenchymal stem cells (hUCMSCs)‐based bioartificial liver (hUCMSC‐BAL), which is a simple and efficient strategy for ALF. D‐galactosamine‐based pig and mouse ALF models were used to explore the effectiveness of hUCMSC‐BAL and hUCMSC‐sEV therapies. Furthermore, high‐throughput sequencing, miRNA transcriptome analysis, and western blot were performed to clarify whether the miR‐139‐5p/PDE4D axis plays a critical role in the ALF model in vivo and in vitro. hUCMSC‐BAL significantly reduced inflammatory responses and cell apoptosis. hUCMSC‐sEV significantly improved liver function in ALF mice and enhanced the regeneration of liver cells. Furthermore, hUCMSC‐sEV miRNA transcriptome analysis showed that miR‐139‐5p had the highest expression and that PDE4D was one of its main target genes. The sEV miR‐139‐5p/PDE4D axis played a role in the treatment of ALF by inhibiting cell apoptosis. Our data indicate that hUCMSC‐BAL can inhibit cytokine storms and cell apoptosis through the sEV miR‐139‐5p/PDE4D axis. Therefore, we propose hUCMSC‐BAL as a therapeutic strategy for patients with early ALF. [ABSTRACT FROM AUTHOR]

Glioblastoma (GBM), the most common and malignant brain tumor, is classified according to its isocitrate dehydrogenase (IDH) mutation status in the 2016 World Health Organization (WHO) brain tumor classification scheme. The standard treatment for GBM is maximal resection, radiotherapy, and Temozolomide (TMZ). Recently, Bevacizumab (Bev) has been added to basic therapy for newly diagnosed GBM, and monotherapy for recurrent GBM. However, the effect of IDH1 mutation on the combination of Bev and TMZ is unknown. In this study, we performed transcriptomic analysis by RNA sequencing with next generation sequencing (NGS), a newly developed powerful method that enables the quantification of the expression level of genome-wide genes. Extracellular matrix and immune cell migration genes were mainly upregulated whereas cell cycle genes were downregulated in IDH1-mutant U87 cells but not in IDH1-wildtype U87 cells after adding Bev to TMZ. In vitro and in vivo studies were conducted for further investigations to verify these results, and the addition of Bev to TMZ showed a significant antitumor effect only in the IDH1-mutant GBM xenograft model. Further studies of gene expression profiling in IDH1 mutation gliomas using NGS will provide more genetic information and will lead to new treatments for this refractory disease.