Category Ranking
98%
Total Visits
921
Avg Visit Duration
2 minutes
Citations
20
Article Abstract
Layer-by-layer (LbL) self-assembled polyelectrolyte capsules have demonstrated their unique advantages and capability in drug delivery applications. These ordered micro/nanostructures are also promising candidates as imaging contrast agents for diagnostic and theranostic applications. Magnetic resonance imaging (MRI), one of the most powerful clinical imaging modalities, is moving forward to the molecular imaging field and requires advanced imaging probes. This paper reports on a new design of MRI-visible LbL capsules, loaded with redox-active gadolinium-doped cerium oxide nanoparticles (CeGdO NPs). CeGdO NPs possess an ultrasmall size, high colloidal stability, and pronounced antioxidant properties. A comprehensive analysis of LbL capsules by TEM, SEM, LCSM, and EDX techniques was carried out. The research demonstrated a high level of biocompatibility and cellular uptake efficiency of CeGdO-loaded capsules by cancer (human osteosarcoma and adenocarcinoma) cells and normal (human mesenchymal stem) cells. The LbL-based delivery platform can also be used for other imaging modalities and theranostic applications.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536467 | PMC |
| http://dx.doi.org/10.3390/polym15183840 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Explainable Deep Learning Framework for Classifying Mandibular Fractures on Panoramic Radiographs.
J Craniofac Surg
September 2025
Department of Oral and Maxillofacial Surgery, University of Ulsan Hospital, University of Ulsan College of Medicine.
This study aimed to develop a deep-learning model for the automatic classification of mandibular fractures using panoramic radiographs. A pretrained convolutional neural network (CNN) was used to classify fractures based on a novel, clinically relevant classification system. The dataset comprised 800 panoramic radiographs obtained from patients with facial trauma.
View Article and Find Full Text PDFEVOLVING TRENDS AND EMERGING THEMES IN GUT MICROBIOTA RESEARCH: A COMPREHENSIVE BIBLIOMETRIC ANALYSIS (2015-2024).
Arq Gastroenterol
September 2025
The Japanese Society of Internal Medicine, Editorial Department, Tokyo, Japan.
Background: This study aims to analyze research trends and emerging insights into gut microbiota studies from 2015 to 2024 through bibliometric analysis techniques. By examining bibliographic data from the Web of Science (WoS) Core Collection, it seeks to identify key research topics, evolving themes, and significant shifts in gut microbiota research. The study employs co-occurrence analysis, principal component analysis (PCA), and burst detection analysis to uncover latent patterns and the development trajectory of this rapidly expanding field.
View Article and Find Full Text PDFPersonalizing chemotherapy drug selection using a novel transcriptomic chemogram.
PLoS Comput Biol
September 2025
Systems Biology and Bioinformatics, Case Western Reserve University School of Medicine, Cleveland, Ohio, United States of America.
Gene signatures predictive of chemotherapeutic response have the potential to extend the reach of precision medicine by allowing oncologists to optimize treatment for individuals. Most published predictive signatures are only capable of predicting response for individual drugs, but most chemotherapy regimens utilize combinations of different agents. We propose a unified framework, called the chemogram, that uses predictive signatures to rank the relative predicted sensitivity of different drugs for individual tumors.
View Article and Find Full Text PDFEnhancing Automated Seizure Detection via Self-Calibrating Spatial-Temporal EEG Features with SC-LSTM.
IEEE J Biomed Health Inform
September 2025
Epilepsy, a highly individualized neurological disorder, affects millions globally. Electroencephalography (EEG) remains the cornerstone for seizure diagnosis, yet manual interpretation is labor-intensive and often unreliable due to the complexity of multi-channel, high-dimensional data. Traditional machine learning models often struggle with overfitting and fail in fully capturing the highdimensional, temporal dynamics of EEG signals, restricting their clinical utility.
View Article and Find Full Text PDFSensitization of cancer cells to DNA-damaging agents by expression of the REV1 C-terminal domain: Implications for chemotherapy.
Proc Natl Acad Sci U S A
September 2025
Department of Biology, Massachusetts Institute of Technology, Cambridge, MA 02139.
The mutagenic translesion synthesis (TLS) pathway, which is critically dependent on REV1's ability to recruit inserter TLS polymerases and the POLζ extender polymerase, enables cancer cells to bypass DNA lesions while introducing mutations that likely contribute to the development of chemotherapy resistance and secondary malignancies. Targeting this pathway represents a promising therapeutic strategy. Here, we demonstrate that the expression of the C-terminal domain (CTD) of human REV1, a ca.
View Article and Find Full Text PDF