A dynamic imitational model is developed of initial stages of cell evolution based on role of environmental cation concentration. The model is developed on our hypothesis, concerning the medium of the appearance of protocells. Could be potassium water reservoirs rather than sea salt water with its predominance of sodium salts. The necessary elements of appearance the protocells served organic molecules, code of their synthesis, and formation of macromolecules under favorable ion concentration in environment High K+ and Mg2+ concentration and bow Na+. The model is based on an assumption that one of the first stages in evolution of life was the appearance in potassium-magnesium water reservoirs of organic molecules capable for selfreplication on the basis of genetic code and formation of protocells with potassium cytoplasm. The model has demonstrated necessity of formation of cell envelope for development of the protocell. Replacement of the dominant cation in water reservoirs-potassium by sodium-required the appearance of ion-transporting devices in plasma membrane and their participation in adaptation of cells to environment. This stage of evolution was accompanied by the most important morpho-functional event--formation of the plasma membrane instead of cell envelope. The membrane provided the ion asymmetry in the cell (preservation of K+ in it) relatively to the sodium external medium for maintaining optimal intracellular medium. In the model system, predecessors of animal cells elaborated mechanism of maintenance of the potassium cytoplasm with the sodium counter-ion dominating in the environment.

Download full-text PDF

Source

Publication Analysis

Top Keywords

model developed
8
appearance protocells
8
protocells potassium
8
water reservoirs
8
organic molecules
8
potassium cytoplasm
8
cell envelope
8
plasma membrane
8
model
5
[imitational modeling
4

Similar Publications

Background: Barriers to mental health assessment and intervention have been well documented within South Africa, in both urban and rural settings. Internationally, evidence has emerged for the effectiveness of technology and, specifically, app-based mental health tools and interventions to help overcome some of these barriers. However, research on digital interventions specific to the South African context and mental health is limited.

View Article and Find Full Text PDF

Designing Health Recommender Systems to Promote Health Equity: A Socioecological Perspective.

J Med Internet Res

January 2025

Department High-Tech Business and Entrepreneurship Section, Industrial Engineering and Business Information Systems, University of Twente, Enschede, Overijssel, Netherlands.

Health recommender systems (HRS) have the capability to improve human-centered care and prevention by personalizing content, such as health interventions or health information. HRS, an emerging and developing field, can play a unique role in the digital health field as they can offer relevant recommendations, not only based on what users themselves prefer and may be receptive to, but also using data about wider spheres of influence over human behavior, including peers, families, communities, and societies. We identify and discuss how HRS could play a unique role in decreasing health inequities.

View Article and Find Full Text PDF

Background: Primary intracranial germ cell tumors (iGCTs) are highly malignant brain tumors that predominantly occur in children and adolescents, with an incidence rate ranking third among primary brain tumors in East Asia (8%-15%). Due to their insidious onset and impact on critical functional areas of the brain, these tumors often result in irreversible abnormalities in growth and development, as well as cognitive and motor impairments in affected children. Therefore, early diagnosis through advanced screening techniques is vital for improving patient outcomes and quality of life.

View Article and Find Full Text PDF

Background: Gastrointestinal bleeding (GIB) is a severe and potentially life-threatening complication in patients with acute myocardial infarction (AMI), significantly affecting prognosis during hospitalization. Early identification of high-risk patients is essential to reduce complications, improve outcomes, and guide clinical decision-making.

Objective: This study aimed to develop and validate a machine learning (ML)-based model for predicting in-hospital GIB in patients with AMI, identify key risk factors, and evaluate the clinical applicability of the model for risk stratification and decision support.

View Article and Find Full Text PDF

Background: Large language model (LLM) artificial intelligence chatbots using generative language can offer smoking cessation information and advice. However, little is known about the reliability of the information provided to users.

Objective: This study aims to examine whether 3 ChatGPT chatbots-the World Health Organization's Sarah, BeFreeGPT, and BasicGPT-provide reliable information on how to quit smoking.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!