Results 101 to 110 of about 142,324 (226)
In recent years, deep learning models have exhibited exceptional performance across several tasks. However, the substantial computational and storage demands impede implementation on edge devices with constrained resources. Online Knowledge Distillation (
Jincheng Xia +3 more
doaj +1 more source
The 10B‐enriched monocarbonyl analog of curcumin (BMAC) 10B‐9 enables site‐specific Boron Neutron Capture Therapy (BNCT) on amyloid‐β (Aβ) fibrils. Neutron irradiation induces histidine oxidation and fibril destabilization, as revealed by 1H‐NMR and FESEM analyses.
Sebastiano Micocci +13 more
wiley +1 more source
Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy
Cancer immunotherapy faces challenges in predicting treatment responses and understanding resistance mechanisms. Artificial intelligence (AI) and machine learning (ML) offer powerful solutions for cancer immunotherapy in patient stratification, biomarker discovery, treatment strategy optimization, and foundation model development.
Xinchao Wu +4 more
wiley +1 more source
Recently, knowledge distillation-based methods have achieved low parameter volume and high accuracy in remote sensing (RS) image scene classification tasks, leading to their widespread application. However, existing knowledge distillation methods fail to
Xiaoning Chen +5 more
doaj +1 more source
This study utilizes programmable mechanical pressure as a therapeutic enhancer to establish a mechano‐chemotherapy strategy. Controlled pressure activates the mechanosensitive ion channel Piezo1 in bladder cancer, triggering a calcium ion cascade that transiently and reversibly amplifies membrane permeability to chemotherapeutics.
Minghai Ma +16 more
wiley +1 more source
This study outlines the developmental pipeline of a multiplexed nanozyme‐based lateral flow immunoassay for the purpose of ovarian germ cell tumor detection. It demonstrates the application of a design of experiments optimization approach for nanozyme probe conjugate development.
Aida Abdelwahed +10 more
wiley +1 more source
This study explores the opposing effects of the mGluR2 and mGluR3 receptors on amyloid precursor protein processing. mGluR2 promotes amyloidogenic cleavage, while mGluR3 favors non‐amyloidogenic pathways. Using a brain‐penetrant nanobody as a mGluR2 positive allosteric modulator, the study uncovers how its chronic activation aggravates amyloid‐β burden
Pierre‐André Lafon +21 more
wiley +1 more source
ML Workflows for Screening Degradation‐Relevant Properties of Forever Chemicals
The environmental persistence of per‐ and polyfluoroalkyl substances (PFAS) necessitates efficient remediation strategies. This study presents physics‐informed machine learning workflows that accurately predict critical degradation properties, including bond dissociation energies and polarizability.
Pranoy Ray +3 more
wiley +1 more source
Adversarial training suffers from poor effectiveness due to the challenging optimisation of loss with hard labels. To address this issue, adversarial distillation has emerged as a potential solution, encouraging target models to mimic the output of the ...
Shuyi Li +3 more
doaj +1 more source
A mitochondria‐targeted copper depletion nanoplatform (CYN‐CDA@Alb) was developed to selectively disrupt tumor mitochondria copper, which then reprogrammed the tumor immune microenvironment by depressing PD‐L1 and CD47 expression simultaneously. By doing this, CYN‐CDA@Alb reversed radiotherapy‐induced immune tolerance, showing the potential usage of ...
Zaigang Zhou +10 more
wiley +1 more source

