Stem Cell Research

Photobiomodulation therapy (PBMT) in skeletal muscle regeneration: A comprehensive review of mechanisms, clinical applications, and future directions.

Photobiomodulation therapy (PBMT) emerged as a significant non-invasive method of stimulating regeneration of the skeletal muscle tissue. This review considers the pathophysiologic and molecular mechanisms of muscle repair, with a focus on the imperative of inflammation resolution, activation of satellite cells, mitochondrial ATP generation, and angiogenesis, with consideration of the role of PBMT...

Ultra-Sparse-View Cone-Beam CT Reconstruction-Based Strictly Structure-Preserved Deep Neural Network in Image-Guided Radiation Therapy.

Radiation therapy is regarded as the mainstay treatment for cancer in clinic. Kilovoltage cone-beam CT (CBCT) images have been acquired for most treatment sites as the clinical routine for image-guided radiation therapy (IGRT). However, repeated CBCT scanning brings extra irradiation dose to the patients and decreases clinical efficiency. Sparse CBCT scanning is a possible solution to the problems...

Machine Learning-Assisted Analysis of the Oral Cancer Immune Microenvironment: From Single-Cell Level to Prognostic Model Construction.

Oral cancer is among the most prevalent malignant tumours worldwide; prognosis can be affected by several factors, including molecular subtypes, immun...

Evolving Therapeutic Landscape of Intracerebral Hemorrhage: Emerging Cutting-Edge Advancements in Surgical Robots, Regenerative Medicine, and Neurorehabilitation Techniques.

Intracerebral hemorrhage (ICH) is the most serious form of stroke and has limited available therapeutic options. As knowledge on ICH rapidly develops,...

Spotlights on novel strategic innovations on the artificial intelligence and deep learning driven quality control focuses in transfusion medicine, to optimize blood component safety and efficacy and minimize the potential pitfalls.

Artificial intelligence (AI) combined with human intelligent, and machine learning (ML) are transforming quality control (QC) in transfusion medicine,...

Comparing Retrieval Strategies to Capture Interdisciplinary Scientific Research: A Bibliometric Evaluation of the Integration of Neuroscience and Computer Science

Interdisciplinary scientific research is increasingly important in knowledge production, funding policies, and academic discussions on scholarly com...

Harnessing artificial intelligence to address immune response heterogeneity in low-dose radiation therapy.

Low-dose radiation therapy has emerged as a promising modality for cancer treatment because of its ability to stimulate antitumor immune responses whi...

Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models

Inverse problems (IPs) involve reconstructing signals from noisy observations. Recently, diffusion models (DMs) have emerged as a powerful framework...

Integrating Intermediate Layer Optimization and Projected Gradient Descent for Solving Inverse Problems with Diffusion Models

Inverse problems (IPs) involve reconstructing signals from noisy observations. Traditional approaches often rely on handcrafted priors, which can fa...

Ctrl-DNA: Controllable Cell-Type-Specific Regulatory DNA Design via Constrained RL

Designing regulatory DNA sequences that achieve precise cell-type-specific gene expression is crucial for advancements in synthetic biology, gene th...

Artificial intelligence and the impact of multiomics on the reporting of case reports.

The integration of artificial intelligence (AI) and multiomics has transformed clinical and life sciences, enabling precision medicine and redefining ...

SCIG: Machine learning uncovers cell identity genes in single cells by genetic sequence codes.

Deciphering cell identity genes is pivotal to understanding cell differentiation, development, and cell identity dysregulation involving diseases. Her...

Deep learning classification integrating embryo images with associated clinical information from ART cycles.

An advanced Artificial Intelligence (AI) model that leverages cutting-edge computer vision techniques to analyse embryo images and clinical data, enab...

Kaleidoscope Gallery: Exploring Ethics and Generative AI Through Art

Ethical theories and Generative AI (GenAI) models are dynamic concepts subject to continuous evolution. This paper investigates the visualization of...

A cost-effective approach using generative AI and gamification to enhance biomedical treatment and real-time biosensor monitoring.

Biosensors are crucial to the diagnosis process since they are designed to detect a specific biological analyte by changing from a biological entity i...

Machine learning and single-cell analysis uncover distinctive characteristics of CD300LG within the TNBC immune microenvironment: experimental validation.

Investigating the essential function of CD300LG within the tumor microenvironment in triple-negative breast cancer (TNBC). Transcriptomic and single-c...

HumaniBench: A Human-Centric Framework for Large Multimodal Models Evaluation

Large multimodal models (LMMs) now excel on many vision language benchmarks, however, they still struggle with human centered criteria such as fairn...

Near-critical gene expression in embryonic boundary precision

Embryonic development relies on the formation of sharp, precise gene expression boundaries. In the fruit fly Drosophila melanogaster, boundary forma...

Deep learning progressive distill for predicting clinical response to conversion therapy from preoperative CT images of advanced gastric cancer patients.

Identifying patients suitable for conversion therapy through early non-invasive screening is crucial for tailoring treatment in advanced gastric cance...

An AI-based automatic leukemia classification system utilizing dimensional Archimedes optimization.

Leukemia is a common type of blood cancer marked by the abnormal and uncontrolled proliferation and expansion of white blood cells. This anomaly impac...