The MR/FI bimodal imaging has attracted widely studied due to combining the advantages of MRI and FI can bridge gaps in sensitivity and depth between these two modalities. Herein, a novel MR/FI bimodal imaging probe is facile fabricated by coating the Mn-phenolic coordination polymer on the surface of the carbon quantum dots. The structure of the as-prepared nanocomposite probe is carefully validated via SEM, TEM, and XPS. The content of Mn is calculated through the EDS and TGA. The quantum yield (QY) and emission wavelength of the probe are about 7.24% and 490 nm, respectively. The longitudinal r1 value (2.43 mM s) with low r2/r1 (4.45) of the probe is obtained. Subsequently, fluorescence and MR imaging are performed. The metabolic pathways in vivo are inferred by studying the bio-distribution of the probe in major organs. Thus, these results indicate that probe would be an excellent dual-modal imaging probe for enhanced MR imaging and fluorescence imaging. MR/FI bimodal imaging probe is built via in-situ coated Mn-phenolic coordination polymer on the surface of the carbon quantum dots. The in vitro and vivo image property of the probe is evaluated.
Download full-text PDF |
Source |
|---|---|
| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8786750 | PMC |
| http://dx.doi.org/10.1007/s10856-021-06629-0 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
PIDGN: An explainable multimodal deep learning framework for early prediction of Parkinson's disease.
J Neurosci Methods
January 2025
School of Mathematics and Statistics, Ludong University, Yantai 264025, China. Electronic address:
Background: Parkinson's disease (PD), the second most common neurodegenerative disease in the world, is usually not diagnosed until the later stages of the disease, when patients might have already missed the best treatment period. Therefore, more effective prediction methods based on artificial intelligence (AI) are needed to assist physicians in timely diagnosis.
New Methods: An explainable deep learning-based early Parkinson's disease diagnostic model, Parkinson's Integrative Diagnostic Gated Network (PIDGN), was designed by fusing Single Nucleotide Polymorphism (SNP) and brain sMRI data.
Photosensitizer spatial heterogeneity and its impact on personalized interstitial photodynamic therapy treatment planning.
J Biomed Opt
January 2025
University of Toronto, University Health Network, Princess Margaret Cancer Centre, Department of Medical Biophysics, Toronto, Ontario, Canada.
Significance: Personalized photodynamic therapy (PDT) treatment planning requires knowledge of the spatial and temporal co-localization of photons, photosensitizers (PSs), and oxygen. The inter- and intra-subject variability in the photosensitizer concentration can lead to suboptimal outcomes using standard treatment plans.
Aim: We aim to quantify the PS spatial variation in tumors and its effect on PDT treatment planning solutions.
Application of functional near-infrared spectroscopy and machine learning to predict treatment response after six months in major depressive disorder.
Transl Psychiatry
January 2025
Department of Biomedical Engineering, National University of Singapore, Singapore, Singapore.
Article Synopsis
- Depression treatment effectiveness differs greatly among individuals, highlighting the need for objective biomarkers that can accurately predict therapy outcomes to improve treatment efficiency.
- This study used functional near-infrared spectroscopy (fNIRS) combined with clinical assessments to explore whether machine learning techniques could forecast treatment responses in patients with major depressive disorder (MDD).
- Findings revealed that changes in total hemoglobin levels in a specific brain region (dlPFC) correlated significantly with treatment response, and the fNIRS-only model demonstrated better predictive accuracy compared to a model that also included clinical data.
Optical Methods for Determining the Phagocytic Activity Profile of CD206-Positive Macrophages Extracted from Bronchoalveolar Lavage by Specific Mannosylated Polymeric Ligands.
Polymers (Basel)
December 2024
Faculty of Chemistry, Lomonosov Moscow State University, Leninskie Gory, 1/3, 119991 Moscow, Russia.
Macrophage (Mph) polarization and functional activity play an important role in the development of inflammatory lung conditions. The previously widely used bimodal classification of Mph into M1 and M2 does not adequately reflect the full range of changes in polarization and functional diversity observed in Mph in response to various stimuli and disease states. Here, we have developed a model for the direct assessment of Mph from bronchial alveolar lavage fluid (BALF) functional alterations, in terms of phagocytosis activity, depending on external stimuli, such as exposure to a range of bacteria (, and ).
View Article and Find Full Text PDFThree-dimensional morphometry of the human thoracic aorta using centerline analysis based on least-squares plane fitting.
JTCVS Open
December 2024
Department of Cardiovascular Surgery, Seirei Mikatahara General Hospital, Hamamatsu, Japan.
Objective: A novel approach to 3-dimensional morphometry of the thoracic aorta was developed by applying centerline analysis based on least-squares plane fitting, and a preliminary study was conducted using computed tomography imaging data.
Methods: We retrospectively compared 3 groups of patients (16 controls without aortic disease, and 16 cases each with acute type B aortic dissection and congenital bicuspid aortic valve). In addition to the standard assessment indices for curvature κ and torsion τ, we conducted coordinate transformation based on the least-squares plane, divided the centerline into 3 representative features (transverse, anterior-posterior, and longitudinal displacements), and analyzed the overall and local displacement in each direction.
Want AI Summaries of new PubMed Abstracts delivered to your In-box?
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!