Potential markers of cancer stem-like cells in ESCC: a review of the current knowledge.

In patients with esophageal squamous cell carcinoma (ESCC), the incidence and mortality rate of ESCC in our country are also higher than those in the rest of the world. Despite advances in the treatment department method, patient survival rates have not obviously improved, which often leads to treatment obstruction and cancer repeat. ESCC has special cells called cancer stem-like cells (CSLCs) with self-renewal and differentiation ability, which reflect the development process and prognosis of cancer. In this review, we evaluated CSLCs, which are identified from the expression of cell surface markers in ESCC. By inciting EMTs to participate in tumor migration and invasion, stem cells promote tumor redifferentiation. Some factors can inhibit the migration and invasion of ESCC via the EMT-related pathway. We here summarize the research progress on the surface markers of CSLCs, EMT pathway, and the microenvironment in the process of tumor growth. Thus, these data may be more valuable for clinical applications.

Ex Situ Reconstruction-Shaped Ir/CoO/Perovskite Heterojunction for Boosted Water Oxidation Reaction.

The oxygen evolution reaction (OER) is the performance-limiting step in the process of water splitting. In situ electrochemical conditioning could induce surface reconstruction of various OER electrocatalysts, forming reactive sites dynamically but at the expense of fast cation leaching. Therefore, achieving simultaneous improvement in catalytic activity and stability remains a significant challenge. Herein, we used a scalable cation deficiency-driven exsolution approach to ex situ reconstruct a homogeneous-doped cobaltate precursor into an Ir/CoO/perovskite heterojunction (SCI-350), which served as an active and stable OER electrode. The SCI-350 catalyst exhibited a low overpotential of 240 mV at 10 mA cm-2 in 1 M KOH and superior durability in practical electrolysis for over 150 h. The outstanding activity is preliminarily attributed to the exponentially enlarged electrochemical surface area for charge accumulation, increasing from 3.3 to 175.5 mF cm-2. Moreover, density functional theory calculations combined with advanced spectroscopy and 18O isotope-labeling experiments evidenced the tripled oxygen exchange kinetics, strengthened metal-oxygen hybridization, and engaged lattice oxygen oxidation for O-O coupling on SCI-350. This work presents a promising and feasible strategy for constructing highly active oxide OER electrocatalysts without sacrificing durability.

A Radiomics Nomogram for Non-Invasive Prediction of Progression-Free Survival in Esophageal Squamous Cell Carcinoma.

To construct a prognostic model for preoperative prediction on computed tomography (CT) images of esophageal squamous cell carcinoma (ESCC), we created radiomics signature with high throughput radiomics features extracted from CT images of 272 patients (204 in training and 68 in validation cohort). Multivariable logistic regression was applied to build the radiomics signature and the predictive nomogram model, which was composed of radiomics signature, traditional TNM stage, and clinical features. A total of 21 radiomics features were selected from 954 to build a radiomics signature which was significantly associated with progression-free survival (p < 0.001). The area under the curve of performance was 0.878 (95% CI: 0.831-0.924) for the training cohort and 0.857 (95% CI: 0.767-0.947) for the validation cohort. The radscore of signatures' combination showed significant discrimination for survival status. Radiomics nomogram combined radscore with TNM staging and showed considerable improvement over TNM staging alone in the training cohort (C-index, 0.770 vs. 0.603; p < 0.05), and it is the same with clinical data (C-index, 0.792 vs. 0.680; p < 0.05), which were confirmed in the validation cohort. Decision curve analysis showed that the model would receive a benefit when the threshold probability was between 0 and 0.9. Collectively, multiparametric CT-based radiomics nomograms provided improved prognostic ability in ESCC.

Survival prediction for patients with glioblastoma multiforme using a Cox proportional hazards denoising autoencoder network.

Objectives: This study aimed to establish and validate a prognostic model based on magnetic resonance imaging and clinical features to predict the survival time of patients with glioblastoma multiforme (GBM). Methods: In this study, a convolutional denoising autoencoder (DAE) network combined with the loss function of the Cox proportional hazard regression model was used to extract features for survival prediction. In addition, the Kaplan-Meier curve, the Schoenfeld residual analysis, the time-dependent receiver operating characteristic curve, the nomogram, and the calibration curve were performed to assess the survival prediction ability. Results: The concordance index (C-index) of the survival prediction model, which combines the DAE and the Cox proportional hazard regression model, reached 0.78 in the training set, 0.75 in the validation set, and 0.74 in the test set. Patients were divided into high- and low-risk groups based on the median prognostic index (PI). Kaplan-Meier curve was used for survival analysis (p = < 2e-16 in the training set, p = 3e-04 in the validation set, and p = 0.007 in the test set), which showed that the survival probability of different groups was significantly different, and the PI of the network played an influential role in the prediction of survival probability. In the residual verification of the PI, the fitting curve of the scatter plot was roughly parallel to the x-axis, and the p-value of the test was 0.11, proving that the PI and survival time were independent of each other and the survival prediction ability of the PI was less affected than survival time. The areas under the curve of the training set were 0.843, 0.871, 0.903, and 0.941; those of the validation set were 0.687, 0.895, 1.000, and 0.967; and those of the test set were 0.757, 0.852, 0.683, and 0.898. Conclusion: The survival prediction model, which combines the DAE and the Cox proportional hazard regression model, can effectively predict the prognosis of patients with GBM.

Atomic cerium modulated palladium nanoclusters exsolved ferrite catalysts for lean methane conversion.

The active and stable palladium (Pd) based catalysts for CH4 conversion are of great environmental and industrial significance. Herein, we employed N2 as an optimal activation agent to develop a Pd nanocluster exsolved Ce-incorporated perovskite ferrite catalyst toward lean methane oxidation. Replacing the traditional initiator of H2, the N2 was found as an effective driving force to selectively touch off the surface exsolution of Pd nanocluster from perovskite framework without deteriorating the overall material robustness. The catalyst showed an outstanding T50 (temperature of 50% conversion) plummeting down to 350°C, outperforming the pristine and H2-activated counterparts. Further, the combined theoretical and experimental results also deciphered the crucial role that the atomically dispersed Ce ions played in both construction of active sites and CH4 conversion. The isolated Ce located at the A-site of perovskite framework facilitated the thermodynamic and kinetics of the Pd exsolution process, lowering its formation temperature and promoting its quantity. Moreover, the incorporation of Ce lowered the energy barrier for cleavage of C─H bond, and was dedicated to the preservation of highly reactive PdOx moieties during stability measurement. This work successfully ventures uncharted territory of in situ exsolution to provide a new design thinking for a highly performed catalytic interface.

Minimized thermal expansion mismatch of cobalt-based perovskite air electrodes for solid oxide cells.

The mismatch of thermal expansion coefficients (TECs) between cobalt-containing perovskite air electrodes and electrolytes is a great challenge for the development of thermo-mechanically durable solid oxide cells (SOCs). In this work, we propose a facile design principle to directly grow highly dispersed Co reactive sites onto ion-conducting scaffolds and confine the dimension of active centres within nanoscale. As a representative, the Co-socketed BaCe0.7Zr0.2Y0.1O3-δ perovskite (denoted as R-BCZY-Co) was constructed via a consecutive sol-gel and in situ exsolution approach. Combined XRD, H2-TPR, SEM and TEM results confirm the emergence of Co nanoparticles on a BCZY matrix without the segregation of a secondary Co-rich phase. The symmetric half-cell measurement suggests that R-BCZY-Co air electrode with the optimal Co content of 10 mol% exhibits a 7-fold promoted oxygen activation performance with a polarization resistance of ∼0.17 Ω cm2 at 750 °C. The TEC mismatch between fabricated R-BCZY-Co electrodes and BCZY electrolytes is minimized down to only ∼11.4%, which is significantly lower than that of other representative counterparts. Moreover, the detailed XPS result proves that the architecture of exsolved Co on BCZY possesses a higher concentration of surface oxygen vacancy, which further benefits the kinetics of ion diffusion and oxygen absorption.