Search PubMed⌕ Search

PubMed · 10936803

Sodium modeling.

Abstract

The most serious side effects induced by hemodialysis therapy are caused by changes in sodium concentration and subsequent water shift between the intracellular and extracellular fluid compartment. Because of inadequate precision of proportioning, a certain sodium concentration and considerable error in the measurement of sodium concentration in dialysis fluid and plasma water, an error of up to 10 g in the diffusive exchange of sodium chloride remains in most dialysis sessions. Common side effects occur within this sodium balance error. Sodium modeling is a simplified mathematical method to describe quantitatively the fluid exchange in the body caused by changes in extracellular sodium concentration. It is based on fundamental physiologic properties of sodium and its permeability through the corresponding membranes. It also explains the different working mechanisms of sodium- and urea-related changes in osmolarity. Sodium modeling is a helpful tool for the illustration of the effects of changes in sodium concentration and ultrafiltration rate on sodium balance during one dialysis session. Sodium profiling is a method employed to avoid unwanted side effects of hemodialysis therapy by deliberately changing the sodium concentration in dialysis fluid during the course of a dialysis session. Clinical reports on practicing sodium profiling are unsatisfactory, involving only short trial periods in most cases. Most of the studies reported positive sodium balance with temporary decreases in intradialytic hypotension and less blood volume reduction, but with increases in thirst and body weight. To date, no validated studies with suitable control of sodium balance have been published that clearly demonstrate the long-term benefits of this mode of therapy compared with the use of constant dialysate sodium concentrations.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

H Mann, S Stiller. 2000. Sodium modeling.. https://pubmed.ncbi.nlm.nih.gov/10936803/

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

Global Genomic Surveillance.

Global genomic surveillance has emerged as a foundational pillar of public health in the twenty-first century, enabling real-time tracking of pathogen evolution and informing outbreak response. This chapter examines the strategic architecture of global genomic surveillance, focusing on its application to arboviruses such as chikungunya virus (CHIKV). It explores the integration of genomic data with epidemiological, clinical, and environmental information within a One Health framework, while addressing critical challenges in governance, equity, and interoperability. The discussion covers the entire genomic surveillance workflow, from sample collection and sequencing to bioinformatic analysis and phylogenetic inference, and highlights the transformative role of artificial intelligence (AI) in predictive surveillance. By analyzing global initiatives, operational barriers, and emerging technologies, this chapter underscores the necessity of sustainable, equitable, and interoperable genomic systems to proactively address current and future infectious disease threats.

Humans↗

Systematic Dissection of Key Driver Perturbation Signatures in Single Cells via ECCITE-seq.

CRISPR screens, such as expanded CRISPR-compatible cellular indexing of transcriptomes and epitopes by sequencing (ECCITE-seq), enable the simultaneous measurement of transcriptomes, gRNA identity, and cell-surface protein expression at single-cell resolution to systematically interrogate gene function. This platform provides a powerful and scalable experimental approach for validating disease-associated regulators identified by large-scale association studies and other computational methods, including network-based analyses of multi-omics data. Here, as an example application, we describe an ECCITE-seq framework to characterize the transcriptomic consequences of perturbing multiple neuronal key driver genes associated with Alzheimer's disease (AD) in human-induced pluripotent stem cell (hiPSC)-derived neurons. More broadly, by integrating customized pooled gRNA libraries with different CRISPR effectors across multiple cell types, this approach allows for the assessment of the regulatory impact of candidate genes implicated in development and disease processes.

Humans↗

Identification of Genome-Wide Chromatin Structural Aberration in Cancer by Hi-C Analysis.

Aberrant three-dimensional genome organization is a hallmark of cancer, often driving oncogene activation through mechanisms such as enhancer hijacking. High-throughput chromosome conformation capture (Hi-C) maps these interactions on a genome-wide scale. Unlike earlier dilution-based methods, in situ Hi-C performs proximity ligation within intact nuclei, minimizing random ligation noise and enabling fine-scale structure detection. This chapter describes an optimized in situ Hi-C protocol tailored for cancer cell lines using MboI digestion and biotin-mediated pull-down to generate high-complexity libraries. We further outline a computational workflow that extends beyond standard topological mapping of compartments and topologically associating domains to identify cancer-specific aberrations. Specifically, we focus on detecting chromosomal rearrangements (structural variants) and characterizing the distinct circular topology of extrachromosomal DNA. This integrated experimental and analytical framework provides the necessary tools to dissect the spatial dysregulation underlying tumor evolution.

Humans↗