AIMC Topic: Disulfides

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Disulfide bond-related gene signature development for bladder cancer prognosis prediction and immune microenvironment characterization.

Scientific reports
Bladder cancer is the fourth most common malignant tumor in men, with limited therapeutic biomarkers and heterogeneous responses to immunotherapy. Disulfide bond-driven cell death has emerged as a critical regulator of tumor progression and immune mi...

Constructing Built-In Electric Field in Hierarchical-Flower Heterostructure for High-Performance Serum Metabolic Assay.

Analytical chemistry
Laser desorption ionization mass spectrometry (LDI-MS) is a critical platform for high-throughput nontargeted metabolomics analysis in clinical diagnosis. However, traditional organic matrices inherently suffer from background interference in the low...

Heterojunction nanofluidic memristors based on peptide chain valves for neuromorphic applications.

Biosensors & bioelectronics
Memristors exhibit significant potential for neuromorphic computing due to their unique properties. This study introduces a heterojunction nanofluidic memristor (HJNFM) and explores its applications in simulating synapses and constructing neural netw...

Involvement of disulfidptosis in the pathophysiology of autism spectrum disorder.

Life sciences
Autism Spectrum Disorder (ASD) is a complex neurodevelopmental disorder, with oxidative stress recognized as a key pathogenic mechanisms. Oxidative stress disrupts intracellular dynamic- thiol/disulfide homeostasis (DTDH), potentially leading to disu...

Machine Learning Assisted Nanofluidic Array for Multiprotein Detection.

ACS nano
Solid-state nanopore and nanochannel biosensors have revolutionized protein detection by offering label-free, highly sensitive analyses. Traditional sensing systems (1st and 2nd stages) primarily focus on inner wall (IW) interactions, facing challeng...

Rapid prediction of key residues for foldability by machine learning model enables the design of highly functional libraries with hyperstable constrained peptide scaffolds.

PLoS computational biology
Peptides are an emerging modality for developing therapeutics that can either agonize or antagonize cellular pathways associated with disease, yet peptides often suffer from poor chemical and physical stability, which limits their potential. However,...

A Machine Learning-Optimized System for Pulsatile, Photo- and Chemotherapeutic Treatment Using Near-Infrared Responsive MoS-Based Microparticles in a Breast Cancer Model.

ACS nano
Multimodal cancer therapies are often required for progressive cancers due to the high persistence and mortality of the disease and the negative systemic side effects of traditional therapeutic methods. Thus, the development of less invasive modaliti...

Artificial intelligence as a tool for predicting the quality attributes of garlic (Allium sativum L.) slices during continuous infrared-assisted hot air drying.

Journal of food science
Effective drying methods are a highly suitable solution for ensuring stable food supply chains, reducing postharvest agricultural losses, and preventing the spoilage of perishable fruits and vegetables. Moreover, machine learning techniques are innov...

Molybdenum Disulfide-Assisted Spontaneous Formation of Multistacked Gold Nanoparticles for Deep Learning-Integrated Surface-Enhanced Raman Scattering.

ACS nano
Several fabrication methods have been developed for label-free detection in various fields. However, fabricating high-density and highly ordered nanoscale architectures by using soluble processes remains a challenge. Herein, we report a biosensing pl...

Optically Modulated HfS-Based Synapses for Artificial Vision Systems.

ACS applied materials & interfaces
The simulation of human brain neurons by synaptic devices could be an effective strategy to break through the notorious "von Neumann Bottleneck" and "Memory Wall". Herein, opto-electronic synapses based on layered hafnium disulfide (HfS) transistors ...