Development of a prognostic nomogram and risk stratification system for elderly patients with esophageal squamous cell carcinoma undergoing definitive radiotherapy: a multicenter retrospective analysis (3JECROG R-03 A).

Background: Our goal is to develop a nomogram model to predict overall survival (OS) for elderly esophageal squamous cell carcinoma (ESCC) patients receiving definitive radiotherapy (RT) or concurrent chemoradiotherapy (CRT), aiding clinicians in personalized treatment planning with a risk stratification system.

Methods: A retrospective study was conducted on 718 elderly ESCC patients treated with RT or CRT at 10 medical centers (3JECROG) from January 2004 to November 2016. We identified independent prognostic factors using univariate and multifactorial Cox regression to construct a nomogram model.

Rapid High-Sensitivity Analysis of Methane Clumped Isotopes (ΔCHD and ΔCHD) Using Mid-Infrared Laser Spectroscopy.

Mid-infrared laser absorption spectroscopy enables rapid and nondestructive analysis of methane clumped isotopes. However, current analytical methods require a sample size of 20 mL STP (0.82 mmol) of pure CH gas, which significantly limits its application to natural samples.

Effects of lifestyle interventions on the prevention of type 2 diabetes and reversion to normoglycemia by prediabetes phenotype: A systematic review and meta-analysis of randomized controlled trials.

Objective: To explore the effects of lifestyle interventions on the prevention of type 2 diabetes (T2D) and reversion to normoglycemia by prediabetes phenotype.

Methods: We searched MEDLINE, Embase, and the Cochrane Library for randomized controlled trials (RCTs) that evaluated the effects of lifestyle interventions in adults with prediabetes for a minimum duration of one year. Two reviewers independently screened articles, extracted data, and performed quality assessment.

Engineered cell membrane vesicles loaded with lysosomophilic drug for acute myeloid leukemia therapy via organ-cell-organelle cascade-targeting.

Acute myeloid leukemia (AML) presents significant treatment challenges due to the severe toxicities and limited efficacy of conventional therapies, highlighting the urgency for innovative approaches. Organelle-targeting therapies offer a promising avenue to enhance therapeutic outcomes while minimizing adverse effects. Herein, inspired that primary AML cells are enriched with lysosomes and sensitive to lysosomophilic drugs (e.

An Intelligent System for Classifying Patient Complaints Using Machine Learning and Natural Language Processing: Development and Validation Study.

Background: Accurate classification of patient complaints is crucial for enhancing patient satisfaction management in health care settings. Traditional manual methods for categorizing complaints often lack efficiency and precision. Thus, there is a growing demand for advanced and automated approaches to streamline the classification process.