Calcium Pattern Assessment in Patients with Severe Aortic Stenosis Via the Chou's 5-Steps Rule

BACKGROUND

Progression of aortic valve calcifications (AVC) leads to aortic valve stenosis (AS). Importantly, the AVC degree has a great impact on AS progression, treatment selection and outcomes. Methods of AVC assessment do not provide accurate quantitative evaluation and analysis of calcium distribution and deposition in a repetitive manner.

OBJECTIVE

We aim to prepare a reliable tool for detailed AVC pattern analysis with quantitative parameters.

METHODS

We analyzed computed tomography (CT) scans of fifty patients with severe AS using a dedicated software based on MATLAB version R2017a (MathWorks, Natick, MA, USA) and ImageJ version 1.51 (NIH, USA) with the BoneJ plugin version 1.4.2 with a self-developed algorithm.

RESULTS

We listed unique parameters describing AVC and prepared 3D AVC models with color pointed calcium layer thickness in the stenotic aortic valve. These parameters were derived from CT-images in a semi-automated and repeatable manner. They were divided into morphometric, topological and textural parameters and may yield crucial information about the anatomy of the stenotic aortic valve.

CONCLUSION

In our study, we were able to obtain and define quantitative parameters for calcium assessment of the degenerated aortic valves. Whether the defined parameters are able to predict potential long-term outcomes after treatment, requires further investigation.

Trends and Challenges in Pesticide Resistance Detection

Pesticide resistance is a crucial factor to be considered when developing strategies for the minimal use of pesticides while maintaining pesticide efficacy. This goal requires monitoring the emergence and development of resistance to pesticides in crop pests. To this end, various methods for resistance diagnosis have been developed for different groups of pests. This review provides an overview of biological, biochemical, and molecular methods that are currently used to detect and quantify pesticide resistance. The agronomic, technical, and economic advantages and drawbacks of each method are considered. Emerging technologies are also described, with their associated challenges and their potential for the detection of resistance mechanisms likely to be selected by current and future plant protection methods.

Accurate Quantification of Disease Markers in Human Serum Using Iron Oxide Nanoparticle-linked Immunosorbent Assay

Accurate and reliable quantification of biomarkers in the blood is essential in disease screening and diagnosis. Here we describe an iron oxide nanoparticle (IONP)-linked immunosorbent assay (ILISA) for detecting biomolecules in human serum. Sandwich ILISA was optimized for the detection of four important serological markers, IgA, IgG, IgM, and C-reactive protein (CRP), and assessed with normal sera, simulated disease-state sera and the serum samples from patients infected with West Nile virus (WNV) or human herpes virus (HHV). Our study shows that using the detection assay formulated with 18.8 nm wüstite nanocrystals, ILISA can achieve sub-picomolar detection sensitivity, and all four markers can be accurately quantified over a large dynamic range. In addition, ILISA is not susceptible to variations in operating procedures and shows better linearity and higher stability compared with ELISA, which facilitates its integration into detection methods suitable for point of care. Our results demonstrate that ILISA is a simple and versatile nanoplatform for highly sensitive and reliable detection of serological biomarkers in biomedical research and clinical applications.