Discussion on the mechanism of HER2 resistance in esophagogastric junction and gastric cancer in the era of immunotherapy.

Human epidermal growth factor receptor 2 (HER2) is a critical biomarker and therapeutic target in gastric/gastroesophageal junction (G/GEJ) cancers, despite the initial success of HER2-targeted therapies, such as trastuzumab, resistance to these drugs has emerged as a major impediment to effective long-term treatment. This review examines the mechanisms of drug resistance in HER2-positive G/GEJ cancer, the primary mechanisms of resistance explored include alterations in the HER2 receptor itself, such as mutations and changes in expression levels, as well as downstream signaling pathways, and interactions with the tumor microenvironment (TME). Furthermore, the review discusses the Novel therapeutic approaches, including the use of antibody-drug conjugates (ADCs) and combination therapies are assessed for their potential to enhance outcomes.

Unveiling an innovative sustainable blue resource-ecofriendly extraction technique towards a circular economy: Optimization of natural deep eutectic solvent and ultrasonication synergistic pathways for type-I collagen refined recovery from discarded fish scales.

A vast sum of fish waste is being annually discarded by marine fishing industries imposing serious environmental pollution concerns. However, these aquatic discarded matters are captivating sources of collagen, a fibrous protein with eminent social and economic relevance. Collagen is conventionally recovered using outdated complex processes requiring many reagents, multiple steps, and extended periods.

High-throughput markerless pose estimation and home-cage activity analysis of tree shrew using deep learning.

Background: Quantifying the rich home-cage activities of tree shrews provides a reliable basis for understanding their daily routines and building disease models. However, due to the lack of effective behavioral methods, most efforts on tree shrew behavior are limited to simple measures, resulting in the loss of much behavioral information.

Methods: To address this issue, we present a deep learning (DL) approach to achieve markerless pose estimation and recognize multiple spontaneous behaviors of tree shrews, including drinking, eating, resting, and staying in the dark house, etc.

Weakening Coulomb interactions in ionic liquid via hydrogen bonds enables ultrafast supercapacitors.

The application of ionic liquid electrolytes in ultrafast supercapacitors to achieve wide electrochemical operating windows and high electrochemical stability is highly applauded. However, the strong Coulomb interaction between ions leads to the overscreening effect and slow establishment process of the electrical double layer (EDL), which deteriorates the rate performance of supercapacitors. Herein, inspired by Coulomb's law and EDL transient dynamics, we introduce competitive hydrogen bond interactions into typical ionic-liquid electrolytes to weaken the Coulomb interaction between ions.