AI Article Synopsis
Article Abstract
Protein Quantum dots interaction is crucial to investigate for better understanding of the biological interactions of QDs. Here in, the model protein Bovine serum albumin (BSA) was used to evaluate the process of protein QDs interaction and adsorption on QDs surface. The modified Stern-Volmer quenching constant (Ka), number of binding sites (n) at different temperatures (298 308 and 318 K ± 1) and corresponding thermodynamic parameters (ΔG < 0, ΔH < 0, and ΔS > 0) were calculated. The quenching constant (Ks) and number of binding sites (n) is found to be inversely proportional to temperature. It signified that static quenching mechanism is dominant over dynamic quenching. The standard free energy change (ΔG < 0) implies that the binding process is spontaneous, while the enthalpy change (ΔH < 0) suggest that the binding of QDs to BSA is an enthalpy-driven process. The standard entropy change (ΔS > 0) suggest that hydrophobic force played a pivotal role in the interaction process. The adsorption process were assessed and evaluated by pseudofirst-order, pseudosecond-order kinetic model, and intraparticle diffusion model.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1007/s10895-016-1773-8 | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
A multiscale molecular structural neural network for molecular property prediction.
Mol Divers
January 2025
Key Laboratory for Macromolecular Science of Shaanxi Province, School of Chemistry and Chemical Engineering, Shaanxi Normal University, Xi'an, 710119, People's Republic of China.
Molecular Property Prediction (MPP) is a fundamental task in important research fields such as chemistry, materials, biology, and medicine, where traditional computational chemistry methods based on quantum mechanics often consume substantial time and computing power. In recent years, machine learning has been increasingly used in computational chemistry, in which graph neural networks have shown good performance in molecular property prediction tasks, but they have some limitations in terms of generalizability, interpretability, and certainty. In order to address the above challenges, a Multiscale Molecular Structural Neural Network (MMSNet) is proposed in this paper, which obtains rich multiscale molecular representations through the information fusion between bonded and non-bonded "message passing" structures at the atomic scale and spatial feature information "encoder-decoder" structures at the molecular scale; a multi-level attention mechanism is introduced on the basis of theoretical analysis of molecular mechanics in order to enhance the model's interpretability; the prediction results of MMSNet are used as label values and clustered in the molecular library by the K-NN (K-Nearest Neighbors) algorithm to reverse match the spatial structure of the molecules, and the certainty of the model is quantified by comparing virtual screening results across different K-values.
View Article and Find Full Text PDFPan-Cancer Upregulation of the Transcription Factor.
Genes (Basel)
January 2025
Department of Pharmacy and Biotechnology, University of Bologna, 40138 Bologna, Italy.
Background: The human transcription factor controls cell cycle progression and genome stability, and it has been correlated to the onset and progression of many tumor types.
Methods: In our study, we collected all recent sequence and quantitative transcriptomics data about , testing its presence across vertebrate evolution and its upregulation in cancer, both in bulk tissue contexts (by comparing the TCGA tumor dataset and the GTEx normal tissue dataset) and in single-cell contexts.
Results: is significantly and consistently upregulated in all tested tumor types, as well as in tumor cells within a cancer microenvironment.
Deep-Learning-Assisted Digital Fluorescence Immunoassay on Magnetic Beads for Ultrasensitive Determination of Protein Biomarkers.
Anal Chem
January 2025
The School of Information Sciences and Technology, Northwest University, Xi'an 710127, P.R.China.
Digital fluorescence immunoassay (DFI) based on random dispersion magnetic beads (MBs) is one of the powerful methods for ultrasensitive determination of protein biomarkers. However, in the DFI, improving the limit of detection (LOD) is challenging since the ratio of signal-to-background and the speed of manual counting beads are low. Herein, we developed a deep-learning network (ATTBeadNet) by utilizing a new hybrid attention mechanism within a UNet3+ framework for accurately and fast counting the MBs and proposed a DFI using CdS quantum dots (QDs) with narrow peak and optical stability as reported at first time.
View Article and Find Full Text PDFAnti-Tissue-Transglutaminase IgA Antibodies Presence Determination Using Electrochemical Square Wave Voltammetry and Modified Electrodes Based on Polypyrrole and Quantum Dots.
Biosensors (Basel)
January 2025
Faculty of Applied Chemistry and Materials Science, National University of Science and Technology Politehnica Bucharest, 313 Splaiul Independentei, Sector 6, 060042 Bucharest, Romania.
A novel electrochemical detection method utilizing a cost-effective hybrid-modified electrode has been established. A glassy carbon (GC) modified electrode was tested for its ability to measure electrochemical tTG antibody levels, which are essential for diagnosing and monitoring Celiac disease (CD). Tissue transglutaminase protein biomolecules are immobilized on a quantum dots-polypyrrole nanocomposite in the improved electrode.
View Article and Find Full Text PDFInactivation of antibiotic resistant bacteria by nitrogen-doped carbon quantum dots through spontaneous generation of intracellular and extracellular reactive oxygen species.
Mater Today Bio
February 2025
State Key Laboratory of Ophthalmology, Optometry and Visual Science, School of Ophthalmology and Optometry, School of Biomedical Engineering, Eye Hospital, Wenzhou Medical University, Wenzhou, 325027, China.
The widespread antibiotic resistance has called for alternative antimicrobial agents. Carbon nanomaterials, especially carbon quantum dots (CQDs), may be promising alternatives due to their desirable physicochemical properties and potential antimicrobial activity, but their antimicrobial mechanism remains to be investigated. In this study, nitrogen-doped carbon quantum dots (N-CQDs) were synthesized to inactivate antibiotic-resistant bacteria and treat bacterial keratitis.
View Article and Find Full Text PDFWant 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!