We report here a new, label-free approach to measure serum protein binding constants. The assay is able to measure HSA K d values in the milli-molar to micromolar range. The protein is not immobilized on any surface and the assay self-corrects for nonspecific adsorption. No mass balance is required to get accurate binding constants and it is not necessary to wait for equilibrium to extract the binding constant. The assay runs in a 96-well format using commercially available parts and is, therefore, relatively easy to implement and automate. As the chemical membranes used are not water permeable, there is no volume change due to the osmotic pressure and pretreatment (soaking) is not necessary. The concept can potentially be extended to other proteins and could thus serve as a label-free technique for general binding constant measurements.
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http://dx.doi.org/10.1021/jm7012826 | DOI Listing |
AIDS Care
January 2025
Department of Behavioral, Social, and Health Education Sciences, Emory University Rollins School of Public Health, Atlanta, GA, USA.
Violence experience, interpersonal and community-level, is commonly reported by people living with HIV (PLWH). Understanding the impact of the various forms of violence on HIV outcomes is critical for prioritizing violence screening and support resources in care settings. From February 2021 to December 2022, among 285 PLWH purposively sampled to attain diversity by gender, race/ethnicity, and HIV care retention status in Atlanta, Georgia, we examined interpersonal and community violence experiences and proxy measures of violence (post-traumatic stress disorder (PTSD), anxiety, depression) and their associations with HIV outcomes (engagement and retention in care and HIV viral suppression) using multivariable analysis.
View Article and Find Full Text PDFJ Sports Sci
January 2025
Department of Sport, Food and Natural Sciences, Western Norway University of Applied Sciences, Sogndal, Norway.
Multivariate pattern analysis was recently extended with covariate projections to solve the challenging task of modelling and interpreting associations in the presence of linear dependent multivariate covariates. Within a joint model, this approach allows quantification of the net association pattern between the outcome and the explanatory variables and between the individual covariates and these variables. The aim of this paper is to apply this methodology to establish the net multivariate association pattern between cardiorespiratory fitness (CRF) and a high-resolution linear dependent physical activity (PA) intensity descriptor derived from accelerometry in children and to validate the crucial sub-regions in the PA spectrum predicting CRF.
View Article and Find Full Text PDFConfl Health
January 2025
London School of Hygiene and Tropical Medicine, Department of Non-Communicable Diseases Epidemiology, Keppel street, London, WC1E 7HT, UK.
Background: Non-communicable diseases (NCDs) are the leading cause of death globally, and many humanitarian crises occur in countries with high NCD burdens. Peer support is a promising approach to improve NCD care in these settings. However, evidence on peer support for people living with NCDs in humanitarian settings is limited.
View Article and Find Full Text PDFNeurol Res Pract
January 2025
Institute of Clinical Epidemiology and Biometry, Julius-Maximilians-Universität Würzburg (JMU), Haus D7, Josef-Schneider-Straße 2, 97080, Würzburg, Germany.
Background: Comprehensive clinical data regarding factors influencing the individual disease course of patients with movement disorders treated with deep brain stimulation might help to better understand disease progression and to develop individualized treatment approaches.
Methods: The clinical core data set was developed by a multidisciplinary working group within the German transregional collaborative research network ReTune. The development followed standardized methodology comprising review of available evidence, a consensus process and performance of the first phase of the study.
J Cheminform
January 2025
School of Systems Biomedical Science, Soongsil University, 369 Sangdo-ro, Dongjak-gu, 06978, Seoul, Republic of Korea.
G protein-coupled receptors (GPCRs) play vital roles in various physiological processes, making them attractive drug discovery targets. Meanwhile, deep learning techniques have revolutionized drug discovery by facilitating efficient tools for expediting the identification and optimization of ligands. However, existing models for the GPCRs often focus on single-target or a small subset of GPCRs or employ binary classification, constraining their applicability for high throughput virtual screening.
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