As a novel functional material with great application values, magnetic nanobead has been in fast development in recent years. Magnetic nanobead is provided with characteristics of beth polymeric and mag-netic particles, so it can be detected easily fi'om the medium and can be easily located since they can move di-rectionally when motivated by external electric field. The magnetic nanobead is widely used in biomedical engi-neering research due to its unique physical and chemical properties which simplify the complex experiments op-erations and shorten the testing period.

IgA nephropathy is a common primary glomerulopathy; the main clinical manifestation is hematuria, with or without proteinuria. However, the pathogenesis associated with mucosal immunity is not completely clear. At present, modern medical treatment delays the progression of IgA nephropathy mainly by controlling blood pressure, reducing proteinuria and delaying renal function failure. The method of combination of disease and syndrome of TCM has received satisfactory efficacy in the treatment of IgA nephropathy. Based on the relationship between mucosal immune and treated from pharynx, this article investigated the occurrence, development and treatment of IgA nephropathy.

As a novel BioChip technique, LiquiChip technique uses fluorescent polystyrene beads as the carrriers of various probes, thus the related reactions of bio-molecules are in liquid system. LiquiChip technique is of use in the methods to detect bio-macromolecules, e. g. DNA detection, immunoassay, cytokine assay, hormone assay, environmental survey and analysis. In comparison to conventional biochip, LiquiChip presents the advantages of high-throughput, high sensitivity, high accuracy, fine repeatability, wide linear range, etc. Now LiquiChip technique is widely used in biomedical engineering field.
Animals ; Biomedical Engineering ; trends ; Biosensing Techniques ; methods ; Humans ; Microfluidic Analytical Techniques ; methods ; Molecular Imprinting ; Protein Array Analysis ; methods

Heart sound is a physiological parameter with individual characteristics generated by heart beat. To do the individual classification and recognition, in this paper, we present our study of using wavelet transform in the signal denoising, with the Mel-Frequency cepstrum coefficients (MFCC) as the feature parameters, and propose a research of reducing the dimensionality through principal components analysis (PCA). We have done the preliminary study to test the feasibility of biometric identification method using heart sound. The results showed that under the selected experimental conditions, the system could reach a 90% recognition rate. This study can provide a reference for further research.
Algorithms ; Artificial Intelligence ; Heart Sounds ; physiology ; Humans ; Individuality ; Pattern Recognition, Physiological ; physiology ; Principal Component Analysis ; Signal Processing, Computer-Assisted ; Wavelet Analysis