Association of Cardiovascular Risk Factors With Major and Minor Electrocardiographic Abnormalities: A Report From the Cross-Sectional Phase of Tehran Cohort Study.

Background And Aims: In the current study, we aimed to identify the association between major and minor electrocardiographic abnormalities and cardiovascular risk factors.

Methods: We used the Tehran cohort study baseline data, an ongoing multidisciplinary, longitudinal study designed to identify cardiovascular disease risk factors in the adult population of Tehran. The electrocardiograms (ECGs) of 7630 Iranian adults aged 35 years and above were analyzed.

Serum vitamin D concentration and anthropometric indicators of adiposity in adults without or with low dose statin users: a cross-sectional study.

Background: This study sought to determine the accuracy of several anthropometric parameters in association with serum Vit. D concentrations and to compare the novel indices with the conventional ones.

Methods: A total of 947 individuals referred to the cardiology clinic who have not used statin or take low-dose statin were evaluated through a cross-sectional study.

The rGO@AuNPs modified label-free electrochemical immunosensor to sensitive detection of CP-BNYVV protein of Rhizomania disease agent in sugar beet.

For the first time, a novel simple label-free electrochemical immunosensor was fabricated for sensitive detection of the coat protein of beet necrotic yellow vein virus (CP-BNYVV) as the causal agent of Rhizomania disease in sugar beet. To boost the amplification of the electrochemical signal, gold nanoparticles-reduced graphene oxide (AuNPs-rGO) nanocomposite was employed to modify the glassy carbon electrode. Anti-BNYVV polyclonal was immobilized onto a modified electrode by applying a thiol linker via a self-assembly monolayer (SAM) and activating the functionalized surface using (3-aminopropyl triethoxysilane) and glutaraldehyde.

Particle formation in response to different protein formulations and containers: Insights from machine learning analysis of particle images.

Subvisible particle count is a biotherapeutics stability indicator widely used by pharmaceutical industries. A variety of stresses that biotherapeutics are exposed to during development can impact particle morphology. By classifying particle morphological differences, stresses that have been applied to monoclonal antibodies (mAbs) can be identified.