The development of a colorimetric biosensing assay for the detection of Helicobacter pylori in feces.

As Helicobacter pylori (H. pylori) is closely related to the occurrence of gastric diseases such as chronic gastritis, peptic ulcer, and gastric cancer, early detection of H. pylori is an urgent need. In this study, oligonucleotide probes conjugated with gold nanoparticles (AuNPs) were used in combination with H. pylori-specific aptamers for the rapid detection of H. pylori in stool samples, which converted the method of detection from proteins to nucleic acids. Therefore, qualitative detection of H. pylori can be achieved by observing color changes through the aggregation (red to purple) or deaggregation (purple to red) of AuNPs, and further quantitative detection can be achieved through UV spectrometry. The detection limit of the colorimetric biosensing method is 25 CFU/mL (S/N = 3), which is favorably comparable to other reported detection methods. Compared with the existing detection methods for H. pylori, this colorimetric biosensing method has no limitations to the test subjects. All these features render the colorimetric biosensing assay a promising method for the clinical field detection of H. pylori.

Image smoothing using regularized entropy minimization and self-similarity for the quantitative analysis of drug diffusion.

BACKGROUND: Targetable drug delivery is an important method for the treatment of liver tumors. For the quantitative analysis of drug diffusion, the establishment of a method for information collection and characterization of extracellular space is developed by imaging analysis of magnetic resonance imaging (MRI) sequences. In this paper, we smoothed out interferential part in scanned digital MRI images. MATERIALS AND METHODS: Making full use of priors of low rank, nonlocal self-similarity, and regularized sparsity-promoting entropy, a block-matching regularized entropy minimization algorithm is proposed. Sparsity-promoting entropy function produces much sparser representation of grouped nonlocal similar blocks of image by solving a nonconvex minimization problem. Moreover, an alternating direction method of multipliers algorithm is proposed to iteratively solve the problem above. RESULTS AND CONCLUSIONS: Experiments on simulated and real images reveal that the proposed method obtains better image restorations compared with some state-of-the-art methods, where most information is recovered and few artifacts are produced.