CD44-Mediated Metabolic Rewiring is A Targetable Dependency of IDH-Mutant Leukemia.

Recurrent IDH mutations catalyze NADPH-dependent production of oncometabolite R-2HG for tumorigenesis. IDH inhibition provides clinical response in a subset of acute myeloid leukemia (AML) cases; however, most patients develop resistance, highlighting the need for more effective IDH-targeting therapies. By comparing transcriptomic alterations in isogenic leukemia cells harboring CRISPR base-edited IDH mutations, we identify the activation of adhesion molecules including CD44, a transmembrane glycoprotein, as a shared feature of IDH-mutant leukemia, consistent with elevated CD44 expression in IDH-mutant AML patients.

AggNet: Advancing protein aggregation analysis through deep learning and protein language model.

Protein aggregation is critical to various biological and pathological processes. Besides, it is also an important property in biotherapeutic development. However, experimental methods to profile protein aggregation are costly and labor-intensive, driving the need for more efficient computational alternatives.

An oral microbiota-based deep neural network model for risk stratification and prognosis prediction in gastric cancer.

Background: This study aims to develop an oral microbiota-based model for gastric cancer (GC) risk stratification and prognosis prediction.

Methods: Oral microbial markers for GC prognosis and risk stratification were identified from 99 GC patients, and their predictive potential was validated on an external dataset of 111 GC patients. The identified bacterial markers were used to construct a Deep Neural Network (DNN) model, a Random Forest (RF) model, and a Support Vector Machine (SVM) model for predicting GC prognosis.

Risk factors analysis of hypokalemia after radical resection of esophageal cancer and establishment of a nomogram risk prediction model.

Objective: This study aimed to explore the risk factors of hypokalemia after radical resection of esophageal cancer (EC) and establish a nomogram risk prediction model to evaluate hypokalemia risk after esophagectomy. Thus, this study provides a reference for the clinical development of intervention measures.

Methods: Clinical data of EC patients who underwent radical surgery from January 2020 to November 2022 in the First Affiliated Hospital of Guangxi Medical University were retrospectively collected.

The role of metagenomic next-generation sequencing in diagnosing and managing post-kidney transplantation infections.

Kidney transplantation (KT) is a life-saving treatment for patients with end-stage renal disease, but post-transplant infections remain one of the most significant challenges. These infections, caused by a variety of pathogens, can lead to prolonged hospitalization, graft dysfunction, and even mortality, particularly in immunocompromised patients. Traditional diagnostic methods often fail to identify the causative organisms in a timely manner, leading to delays in treatment and poorer patient outcomes.