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Tire and Road Wear Particles (TRWP) are pervasive environmental contaminants, yet the molecular mechanisms linking their toxic derivative, 6PPD-quinone (6PPD-Q), to bladder cancer (BLCA) progression remain obscure. This ...

Phthalate plasticizers, especially diethyl phthalate (DEP), are linked to metabolic disorders, while their precise role and mechanism in diabetic nephropathy (DN) pathogenesis remain unclear. Here, we integrated transcri...

Lung diseases such as pneumonia, tuberculosis, COVID-19, and lung cancer remain significant global health challenges that demand rapid and accurate diagnosis to improve patient outcomes. This study proposes NASNet-ViT, a...

Dynamic gesture recognition is a core technology for human–computer interaction, yet existing methods face prominent limitations in hand spatial topology modeling, long–short-term temporal feature fusion, and general...

Global food security relies heavily on rice production, which is continuously threatened by crop diseases. Although deep learning (DL) models have demonstrated strong diagnostic performance, their high computational and ...

Objectives: Deep learning networks have achieved significant progress in caries diagnosis, but automated localization and numbering of carious teeth in cone-beam computed tomography (CBCT) images remain underexplored. Th...

Cadmium poses severe threats to ecosystems and human health due to its high toxicity and bioaccumulative nature. The global regulatory limits for Cd are often low at 0.1-0.6 mg kg−1, which is 1 to 2 orders of magnitude...

Surabaya City is one of the urban areas in Indonesia with a high incidence of breast cancer. Multiple factors, including genetic predisposition, lifestyle patterns, and environmental exposures, influence this condition. ...

To overcome the limitations of traditional models to simulate discrete environmental variables, this study introduces a novel, integrated simulation framework: the Spatio-Temporal Integrated Geographic Generative Adversa...

Introduction: The advancement of AI-assisted oral disease diagnosis critically relies on the availability of annotated, high-quality datasets and resilient deep learning architectures. Nevertheless, progress in this doma...