Fluorescence enhancement of quercetin complexes by silver nanoparticles and its analytical application

Energy transfer in liquid and solid nanoobjects: application in luminescent analysis

Radiationless resonance electronic excitation energy transfer (ET) is a fundamental physical phenomenon in luminescence spectroscopy playing an important role in natural processes, especially in photosynthesis and biochemistry. Besides, it is widely used in photooptics, optoelectronics, and protein chemistry, coordination chemistry of transition metals and lanthanides as well as in luminescent analysis. ET involves the transfer of electronic energy from a donor (D) (molecules or particles) which is initially excited, to an acceptor (A) at the ground state to emit it later. Fluorescence or phosphorescence of the acceptor that occurs during ET is known as sensitized. There do many kinds of ET exist but in all cases along with other factors the rate and efficiency of ET in common solvents depends to a large extent on the distance between the donor and the acceptor. This dependency greatly limits the efficiency of ET and, correspondingly, does not allow the determination of analytes in highly diluted (10–9–10–15 M) solutions. To solve the problem of distance-effect, the effects of concentrating and bring close together the donor and acceptor in surfactant micelles (liquid nanosystems) or sorption on solid nanoparticles are used. Various approaches to promote the efficiency of ET for improvement determination selectivity and sensitivity using liquid and solid nanoobjects is reviewed and analyzed.

Sensitive fluorescent assay for copper(ii) determination in aqueous solution using quercetin-cyclodextrin inclusion

Environmentally friendly probe materials for detecting copper ions were studied in this research. Fluorescent emission of quercetin (Q) was observed in the buffer solution (pH = 7.40), and (2-hydroxypropyl)-β-cyclodextrin (CD) could enhance the fluorescence intensity of Q. The UV/Vis spectrum showed that the Q-CD system was formed. After adding copper ions into the Q-CD system, the fluorescent emission intensity of Q-CD system generated quenching, and other metal ions could not bring change, which meant the Q-CD system showed good selectivity to copper ions. The fluorescence titration spectra showed that the concentration of copper ions was inversely proportional to fluorescence intensity, and gave a good linear change in fluorescence emission intensity in response to the concentration of copper ions ranging from 5.0 × 10-8 to 8.3 × 10-6 mol L-1. The calibration curve of the relationship between the intensity and copper ions concentration was y = -9.24x + 844.51 (R 2 = 0.997). The detection limit of copper ions was measured to be 2.3 × 10-8 mol L-1. The probable mechanism was studied by UV/Vis spectrum and Job's plot method. The results indicated that Q-CD-Cu(ii) complex was formed and intramolecular charge transfer (ICT) took place. At last, the probe was successfully applied for determination of copper ions in water bodies, vegetables and fruits with good recovery. The study showed that Q-CD system could detect copper ions as a fluorescent probe with high selectivity, sensitivity and larger linearity range.

Preliminary Study on Molecular Subtypes of Breast Cancer Based on Magnetic Resonance Imaging Texture Analysis

OBJECTIVE

The aim of the study was to investigate the molecular subtypes of breast cancer based on the texture features derived from magnetic resonance images (MRIs).

METHODS

One hundred seven patients with preoperative confirmed breast cancer were recruited. One hundred eight breast lesions were divided into 4 subtypes according to the status of estrogen receptor, progesterone receptor, human epidermal growth factor receptor type 2, and Ki67. Fisher discriminant analysis was performed on the texture features that extracted from the enhanced high-resolution T1-weighted images and diffusion weighted images to establish the classification model of molecular subtypes.

RESULTS

The differentiation accuracies of Fisher discriminant analysis on the enhanced high-resolution T1-weighted images were 82.8% and 86.4% for 1.5T and 3.0T imaging. Fisher discriminant analysis on diffusion weighted imaging texture features were achieved with a classification ability of 73.4% and 88.6%. The combined discriminant results for 2 kinds magnetic resonance images were 95.0%, 97.7% in 1.5T and 3.0T imaging, respectively.

CONCLUSIONS

The fine results indicated a promising approach to predict the molecular subtypes of breast cancer.