Retrospective analysis of disease characteristics and treatment patterns among patients with esophageal cancer across 14 surgically represented centers.

Objective: Esophageal cancer (EC) ranks eighth among cancers in cancer-related deaths globally, and ~44% of new cases occur in China. We sought to describe the clinical characteristics and treatment landscape of EC in China before the approval of immunotherapy in 2020.

Methods: CHANNEL was a large, retrospective study using patient-level data from 14 hospitals/cancer centers across China, including adults initiating therapy for newly diagnosed EC (January to December 2018).

Whole-genome sequencing and secondary metabolite exploration of the novel BN with broad-spectrum antagonistic activity against fungal plant pathogens.

The utilization of chemical pesticides recovers 30%-40% of food losses. However, their application has also triggered a series of problems, including food safety, environmental pollution, pesticide resistance, and incidents of poisoning. Consequently, green pesticides are increasingly seen as viable alternatives to their chemical counterparts.

Quantitative analysis and identification of magnesium alloys using fs-LA-SIBS combined with machine learning methods.

This work employs the femtosecond laser-ablation spark-induced breakdown spectroscopy (fs-LA-SIBS) technique for the quantitative analysis of magnesium alloy samples. It integrates four machine learning models: Random Forest (RF), Support Vector Machine (SVM), Partial Least Squares (PLS), and -Nearest Neighbors (KNN) to evaluate their classification performance in identifying magnesium alloys. In regression tasks, the models aim to predict the content of four elements: manganese (Mn), aluminum (Al), zinc (Zn), and nickel (Ni) in the samples.

Radiomicsmetabolic signature profiles for advanced non-small cell lung cancer with chemoimmunotherapy by reflecting biological function and survival.

Background: Resistance to chemoimmunotherapy in patients with advanced non-small cell lung cancer (NSCLC) necessitates effective prognostic biomarkers. Although F-fluorodeoxyglucose (FDG) positron emission tomography (PET)/computed tomography (CT) has shown potential for efficacy assessment, it has been mainly evaluated in immuno-monotherapy setting, lacking elaborations in the scenarios of immunotherapy combined with chemotherapy. To tackle this dilemma, we aimed to build a non-invasive PET/CT-based model for stratifying tumor heterogeneity and predicting survival in advanced NSCLC patients undergoing chemoimmunotherapy.

Challenges and opportunities in 2D materials for high-performance aqueous ammonium ion batteries.

Aqueous ammonium ion batteries (AAIBs) have attracted considerable attention due to their high safety and rapid diffusion kinetics. Unlike spherical metal ions, NH forms hydrogen bonds with host materials, leading to a unique storage mechanism. A variety of electrode materials have been proposed for AAIBs, but their performance often falls short in terms of future energy storage needs.