The design and synthesis of a combined MRI-optical probe for bio-imaging are reported. The materials studied join the properties of lanthanide (Ln(3+)) complexes and nanoparticles (NPs), offering an excellent solution for bimodal imaging. The hybrid SiO(2)@APS/DTPA:Gd:Ln (Ln = Eu(3+) or Tb(3+)) (APS: 3-aminopropyltriethoxysilane, DTPA: diethylenetriamine pentaacetic acid) system increases the payload of the active magnetic centre (Gd(3+)) and introduces a Ln(3+) long-life excited state (Eu(3+): 0.35 ± 0.02 ms, Tb(3+): 1.87 ± 0.02 ms), with resistance to photobleaching and sharp emission bands. The Eu(3+) ions reside in a single low-symmetry site. Although the photoluminescence emission is not influenced by the simultaneous presence of Gd(3+) and Eu(3+), a moderate r(1) increase and a larger enhancement of r(2) are observed, particularly at high fields, due to susceptibility effects on r(2). The presence of Tb(3+) instead of Eu(3+) further raises r(1) but decreases r(2). These values are constant over a wide (5-13) pH range, indicating the paramagnetic NPs stability and absence of leaching. The uptake of NPs by living cells is fast and results in an intensity increase in the T(1)-weighted MRI images. The optical properties of the NPs in cellular pellets are also studied, confirming their potential as bimodal imaging agents.
Download full-text PDF |
Source |
---|---|
http://dx.doi.org/10.1016/j.biomaterials.2011.09.086 | DOI Listing |
Sci Rep
January 2025
Healthcare Technology Innovation Centre, Indian Institute of Technology Madras, Chennai, India.
The local pulse wave velocity (PWV) from large elastic arteries and its pressure-dependent changes within a cardiac cycle are potential biomarkers for cardiovascular risk stratification. However, pulse wave reflections can impair the accuracy of local PWV measurements. We propose a method to measure pressure-dependent variations in local PWV while minimizing the influence of pulse wave reflections.
View Article and Find Full Text PDFBMC Med Imaging
January 2025
Department of Ultrasound, Renji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200030, China.
Neoadjuvant chemotherapy (NAC) is a systemic and systematic chemotherapy regimen for breast cancer patients before surgery. However, NAC is not effective for everyone, and the process is excruciating. Therefore, accurate early prediction of the efficacy of NAC is essential for the clinical diagnosis and treatment of patients.
View Article and Find Full Text PDFSci Rep
January 2025
Department of Pharmaceutics, School of Pharmaceutical Sciences, Delhi Pharmaceutical Sciences & Research University, Pushp Vihar, Sector 3, New Delhi, 110017, India.
The repercussions of hormone replacement therapy (HRT) and bisphosphonates pose serious clinical challenges and warrant novel therapies for osteoporosis in menopausal women. To confront this issue, the present research aimed to design and fabricate daidzein (DZ); a phytoestrogen-loaded hydroxyapatite nanoparticles to mimic and compensate for synthetic estrogens and biomineralization. Hypothesizing this bimodal approach, hydroxyapatite nanoparticles (HAPNPs) were synthesized using the chemical-precipitation method followed by drug loading (DZHAPNPs) via sorption.
View Article and Find Full Text PDFBioorg Chem
January 2025
Cardiovascular Center, The First Hospital of Jilin University, Changchun 130021, China. Electronic address:
The assessment of early atherosclerosis (AS) via fluorescence imaging is crucial for advancing early diagnosis research. Abnormal inflammation biomarkers, including hypochlorous acid (HClO) and viscosity within mitochondria, have been closely linked to the pathogenesis of AS. However, current fluorescent probes predominantly rely on unimodal imaging that targets a single biomarker and lacks mitochondrial specificity, which can result in potential false signal readouts due to the complex intracellular environment.
View Article and Find Full Text PDFJ 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.
Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!