Stem Cell Research

Discovery of CYP1A1 Inhibitors for Host-Directed Therapy against Sepsis.

Bacterial sepsis remains a leading cause of death globally, exacerbated by the rise of multidrug resistance (MDR). Host-directed therapy (HDT) has emerged as a promising nonantibiotic approach to combat infections; thus, multiple HDT targets have been identified. However, the translation of HDT targets into therapeutic drugs, particularly small-molecule drugs, remains rare. Our study focuses on cy...

Multiscale Organization of Neural Networks in a 3D Bioprinted Matrix.

The efficient establishment of in vitro neural models that accurately mimic the structural and functional connectivity of neural networks is critical in neuroscience research. 3D bioprinting shows great potential for constructing sophisticated in vitro models with high freedom of design. However, mature neurons are delicate and susceptible to manipulation. Here, extrusion-based 3D bioprinting is e...

Machine learning to predict gold nanostar optical properties.

Gold nanostars (AuNS) are nanoparticles with spiky structures and morphology-dependent optical features. These include strong extinction coefficients ...

Optimizing phage therapy with artificial intelligence: a perspective.

Phage therapy is emerging as a promising strategy against the growing threat of antimicrobial resistance, yet phage and bacteria are incredibly divers...

Uncovering codon usage patterns during murine embryogenesis and tissue-specific developmental diseases.

INTRODUCTION: Mouse models share significant genetic similarities with humans and have expanded our understanding of how embryonic tissue-specific gen...

Adaptive Machine Learning Framework enables Unprecedented Yield and Purity of Adeno-Associated Viral Vectors for Gene Therapy.

Adeno-associated viral (AAV) vectors for gene therapy are becoming integral to modern medicine, providing therapeutic options for diseases once deemed...

Cutting-edge assays for mirabegron and tadalafil combo therapy for benign prostatic hyperplasia; insilico kinetics approach; multi trait sustainability assessment.

The combination therapy of mirabegron (MIR) and tadalafil (TAD) has gained significant attention in clinical practice for the treatment of Benign Pros...

Artificial intelligence, machine learning, and digitalization systems in the cell and gene therapy sector: a guidance document from the ISCT industry committees.

As artificial intelligence (AI), machine learning (ML) and other digital tools gain prominence across industries, their application in cell and gene t...

Treatment journey clustering with a novel kernel k-means machine learning algorithm: a retrospective analysis of insurance claims in bipolar I disorder.

In real-world psychiatric practice, patients may experience complex treatment journeys, including various diagnoses and lines of therapy. Insurance cl...

Induced Pluripotent Stem Cells in Cardiomyopathy: Advancing Disease Modeling, Therapeutic Development, and Regenerative Therapy.

Cardiomyopathies are a heterogeneous group of heart muscle diseases that can lead to heart failure, arrhythmias, and sudden cardiac death. Traditional...

Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data.

Synthetic and naturally occurring particles, such as nanoparticles (NPs) and exosomes; a type of extracellular vesicles (EVs), have garnered widesprea...

Deciphering the history of ERK activity from fixed-cell immunofluorescence measurements.

The RAS/ERK pathway plays a central role in diagnosis and therapy for many cancers. ERK activity is highly dynamic within individual cells and drives ...

Advances of oncolytic vaccinia viruses armed with interleukin in tumor therapy.

Oncolytic vaccinia viruses armed with interleukins represent a promising frontier in tumor therapy. Oncolytic vaccinia viruses express IL-2, IL-10, IL...

Stem Cell and Synthetic Embryo Models: Advances, Applications, and Ethical Considerations.

Independent traditional gametes and recent advances in stem cell biology have made it possible to create synthetic embryo models (SEMs), altering our ...

A multi-faceted discovery strategy identifies functional antibodies binding to cysteine-rich domain 1 of hDKK1 for cancer immunotherapy via Wnt non-canonical pathway.

Wnt signaling is important in embryonic development and tumorigenesis. These biological effects can be exerted by the activation of the β-catenin-depe...

The Impact of Language Variability on Artificial Intelligence Performance in Regenerative Endodontics.

BACKGROUND: Regenerative endodontic procedures (REPs) are promising treatments for immature teeth with necrotic pulp. Artificial intelligence (AI) is ...

Machine Learning-based Dose Prediction in [Lu]Lu-PSMA-617 Therapy by Integrating Biomarkers and Radiomic Features from [Ga]Ga-PSMA-11 Positron Emission Tomography/Computed Tomography.

PURPOSE: The study aimed to develop machine learning (ML) models for pretherapy prediction of absorbed doses (ADs) in kidneys and tumoral lesions for ...

Radiomics of Dynamic Contrast-Enhanced MRI for Predicting Radiation-Induced Hepatic Toxicity After Intensity Modulated Radiotherapy for Hepatocellular Carcinoma: A Machine Learning Predictive Model Based on the SHAP Methodology.

OBJECTIVE: To develop an interpretable machine learning (ML) model using dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) radiomic data,...

Next-Generation Hydrogel Design: Computational Advances in Synthesis, Characterization, and Biomedical Applications.

Hydrogels are pivotal in advanced materials, driving innovations in medical fields, such as targeted drug delivery, regenerative medicine, and skin re...

Comparing methods to improve cone-beam computed tomography for dose calculations in adaptive proton therapy.

BACKGROUND AND PURPOSE: Proton therapy requires dose monitoring, often performed based on repeated computed tomography (reCT) scans. However, reCT sca...