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  1. Article ; Online: AI, Machine Learning, and ChatGPT in Hypertension.

    Layton, Anita T

    Hypertension (Dallas, Tex. : 1979)

    2024  Volume 81, Issue 4, Page(s) 709–716

    Abstract: Hypertension, a leading cause of cardiovascular disease and premature death, remains incompletely understood despite extensive research. Indeed, even though numerous drugs are available, achieving adequate blood pressure control remains a challenge, ... ...

    Abstract Hypertension, a leading cause of cardiovascular disease and premature death, remains incompletely understood despite extensive research. Indeed, even though numerous drugs are available, achieving adequate blood pressure control remains a challenge, prompting recent interest in artificial intelligence. To promote the use of machine learning in cardiovascular medicine, this review provides a brief introduction to machine learning and reviews its notable applications in hypertension management and research, such as disease diagnosis and prognosis, treatment decisions, and omics data analysis. The challenges and limitations associated with data-driven predictive techniques are also discussed. The goal of this review is to raise awareness and encourage the hypertension research community to consider machine learning as a key component in developing innovative diagnostic and therapeutic tools for hypertension. By integrating traditional cardiovascular risk factors with genomics, socioeconomic, behavioral, and environmental factors, machine learning may aid in the development of precise risk prediction models and personalized treatment approaches for patients with hypertension.
    MeSH term(s) Humans ; Artificial Intelligence ; Machine Learning ; Hypertension/diagnosis ; Hypertension/drug therapy ; Cardiovascular Diseases ; Genomics
    Language English
    Publishing date 2024-02-21
    Publishing country United States
    Document type Journal Article ; Review
    ZDB-ID 423736-5
    ISSN 1524-4563 ; 0194-911X ; 0362-4323
    ISSN (online) 1524-4563
    ISSN 0194-911X ; 0362-4323
    DOI 10.1161/HYPERTENSIONAHA.124.19468
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: A comparative modeling study of the mitochondrial function of the proximal tubule and thick ascending limb cells in the rat kidney.

    Layton, Anita T

    American journal of physiology. Renal physiology

    2023  Volume 326, Issue 2, Page(s) F189–F201

    Abstract: To reabsorb >99% of the glomerular filtrate, the metabolic demand of the kidney is high. Interestingly, renal blood flow distribution exhibits marked inhomogeneity, with typical tissue oxygen tension ( ... ...

    Abstract To reabsorb >99% of the glomerular filtrate, the metabolic demand of the kidney is high. Interestingly, renal blood flow distribution exhibits marked inhomogeneity, with typical tissue oxygen tension (Po
    MeSH term(s) Rats ; Animals ; Kidney/metabolism ; Kidney Tubules, Proximal/metabolism ; Oxygen/metabolism ; Mitochondria/metabolism ; Adenosine Triphosphate/metabolism ; Kidney Medulla/metabolism ; Mammals/metabolism
    Chemical Substances Oxygen (S88TT14065) ; Adenosine Triphosphate (8L70Q75FXE)
    Language English
    Publishing date 2023-11-23
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 603837-2
    ISSN 1522-1466 ; 0363-6127
    ISSN (online) 1522-1466
    ISSN 0363-6127
    DOI 10.1152/ajprenal.00290.2023
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article ; Online: "Hi, how can i help you?": embracing artificial intelligence in kidney research.

    Layton, Anita T

    American journal of physiology. Renal physiology

    2023  Volume 325, Issue 4, Page(s) F395–F406

    Abstract: In recent years, biology and precision medicine have benefited from major advancements in generating large-scale molecular and biomedical datasets and in analyzing those data using advanced machine learning algorithms. Machine learning applications in ... ...

    Abstract In recent years, biology and precision medicine have benefited from major advancements in generating large-scale molecular and biomedical datasets and in analyzing those data using advanced machine learning algorithms. Machine learning applications in kidney physiology and pathophysiology include segmenting kidney structures from imaging data and predicting conditions like acute kidney injury or chronic kidney disease using electronic health records. Despite the potential of machine learning to revolutionize nephrology by providing innovative diagnostic and therapeutic tools, its adoption in kidney research has been slower than in other organ systems. Several factors contribute to this underutilization. The complexity of the kidney as an organ, with intricate physiology and specialized cell populations, makes it challenging to extrapolate bulk omics data to specific processes. In addition, kidney diseases often present with overlapping manifestations and morphological changes, making diagnosis and treatment complex. Moreover, kidney diseases receive less funding compared with other pathologies, leading to lower awareness and limited public-private partnerships. To promote the use of machine learning in kidney research, this review provides an introduction to machine learning and reviews its notable applications in renal research, such as morphological analysis, omics data examination, and disease diagnosis and prognosis. Challenges and limitations associated with data-driven predictive techniques are also discussed. The goal of this review is to raise awareness and encourage the kidney research community to embrace machine learning as a powerful tool that can drive advancements in understanding kidney diseases and improving patient care.
    MeSH term(s) Humans ; Artificial Intelligence ; Kidney ; Machine Learning ; Acute Kidney Injury ; Renal Insufficiency, Chronic
    Language English
    Publishing date 2023-08-17
    Publishing country United States
    Document type Journal Article ; Review ; Research Support, Non-U.S. Gov't
    ZDB-ID 603837-2
    ISSN 1522-1466 ; 0363-6127
    ISSN (online) 1522-1466
    ISSN 0363-6127
    DOI 10.1152/ajprenal.00177.2023
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: A modeling analysis of whole body potassium regulation on a high-potassium diet: proximal tubule and tubuloglomerular feedback effects.

    Stadt, Melissa M / Layton, Anita T

    American journal of physiology. Regulatory, integrative and comparative physiology

    2024  Volume 326, Issue 5, Page(s) R401–R415

    Abstract: Potassium ( ... ...

    Abstract Potassium (K
    MeSH term(s) Feedback ; Kidney Tubules, Proximal ; Electrolytes ; Potassium ; Hormones
    Chemical Substances Electrolytes ; Potassium (RWP5GA015D) ; Hormones
    Language English
    Publishing date 2024-03-11
    Publishing country United States
    Document type Journal Article
    ZDB-ID 603839-6
    ISSN 1522-1490 ; 0363-6119
    ISSN (online) 1522-1490
    ISSN 0363-6119
    DOI 10.1152/ajpregu.00283.2023
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Book: Mathematical modeling in renal physiology

    Layton, Anita T. / Edwards, Aurélie

    (Lecture notes on mathematical modelling in the life sciences)

    2014  

    Author's details Anita T. Layton ; Aurélie Edwards
    Series title Lecture notes on mathematical modelling in the life sciences
    Keywords Niere ; Physiologie ; Mathematisches Modell
    Subject Humanphysiologie ; Mensch ; Körperfunktion ; Nephros ; Ren
    Language English
    Size VIII, 221 S. : Ill., graph. Darst.
    Publisher Springer
    Publishing place Heidelberg u.a.
    Publishing country Germany
    Document type Book
    HBZ-ID HT018382439
    ISBN 978-3-642-27366-7 ; 3-642-27366-1 ; 9783642273674 ; 364227367X
    Database Catalogue ZB MED Medicine, Health

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  6. Article ; Online: Predicting sex differences in the effects of diuretics in renal epithelial transport during angiotensin II-induced hypertension.

    Zheng, Kaixin / Layton, Anita T

    American journal of physiology. Renal physiology

    2024  Volume 326, Issue 5, Page(s) F737–F750

    Abstract: Chronic angiotensin II (ANG II) infusion is an experimental model that induces hypertension in rodents. The natriuresis, diuresis, and blood pressure responses differ between males and females. This is perhaps not unexpected, given the rodent kidney, ... ...

    Abstract Chronic angiotensin II (ANG II) infusion is an experimental model that induces hypertension in rodents. The natriuresis, diuresis, and blood pressure responses differ between males and females. This is perhaps not unexpected, given the rodent kidney, which plays a key role in blood pressure regulation, exhibits marked sex differences. Under normotensive conditions, compared with males, the female rat nephron exhibits lower Na
    MeSH term(s) Animals ; Angiotensin II ; Hypertension/chemically induced ; Hypertension/metabolism ; Hypertension/physiopathology ; Male ; Female ; Sodium-Hydrogen Exchanger 3/metabolism ; Natriuresis/drug effects ; Diuretics/pharmacology ; Blood Pressure/drug effects ; Sex Factors ; Computer Simulation ; Sodium/metabolism ; Rats ; Sodium Chloride Symporter Inhibitors/pharmacology ; Sex Characteristics ; Disease Models, Animal ; Diuresis/drug effects ; Sodium Potassium Chloride Symporter Inhibitors/pharmacology ; Kidney/metabolism ; Kidney/drug effects ; Kidney/physiopathology
    Chemical Substances Angiotensin II (11128-99-7) ; Sodium-Hydrogen Exchanger 3 ; Slc9a3 protein, rat ; Diuretics ; Sodium (9NEZ333N27) ; Sodium Chloride Symporter Inhibitors ; Sodium Potassium Chloride Symporter Inhibitors
    Language English
    Publishing date 2024-03-14
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't ; Comparative Study
    ZDB-ID 603837-2
    ISSN 1522-1466 ; 0363-6127
    ISSN (online) 1522-1466
    ISSN 0363-6127
    DOI 10.1152/ajprenal.00398.2023
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  7. Article: How the kidney regulates magnesium: a modelling study.

    Dutta, Pritha / Hakimi, Shervin / Layton, Anita T

    Royal Society open science

    2024  Volume 11, Issue 3, Page(s) 231484

    Abstract: The kidneys are crucial for maintaining ... ...

    Abstract The kidneys are crucial for maintaining Mg
    Language English
    Publishing date 2024-03-20
    Publishing country England
    Document type Journal Article
    ZDB-ID 2787755-3
    ISSN 2054-5703
    ISSN 2054-5703
    DOI 10.1098/rsos.231484
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  8. Article ; Online: Did you know how SGLT2 inhibitors protect the kidney?

    Layton, Anita T / Vallon, Volker

    Acta physiologica (Oxford, England)

    2023  Volume 238, Issue 4, Page(s) e14011

    MeSH term(s) Humans ; Sodium-Glucose Transporter 2 Inhibitors/pharmacology ; Sodium-Glucose Transporter 2 Inhibitors/therapeutic use ; Kidney ; Hypoglycemic Agents ; Diabetes Mellitus, Type 2/drug therapy
    Chemical Substances Sodium-Glucose Transporter 2 Inhibitors ; Hypoglycemic Agents
    Language English
    Publishing date 2023-06-18
    Publishing country England
    Document type Editorial
    ZDB-ID 2218636-0
    ISSN 1748-1716 ; 1748-1708
    ISSN (online) 1748-1716
    ISSN 1748-1708
    DOI 10.1111/apha.14011
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Article ; Online: His and her mathematical models of physiological systems.

    Layton, Anita T

    Mathematical biosciences

    2021  Volume 338, Page(s) 108642

    Abstract: Beyond the reproductive system and reproductive behaviors, men and women exhibit major differences in many organ systems, including the anatomy of the brain, the activities of the stress and immune systems, and the metabolic and cardiovascular functions. ...

    Abstract Beyond the reproductive system and reproductive behaviors, men and women exhibit major differences in many organ systems, including the anatomy of the brain, the activities of the stress and immune systems, and the metabolic and cardiovascular functions. A comprehensive understanding of the impact of these sex differences on health and disease is crucial to the development of effective sex-based therapies. Mathematical modeling has the potential of facilitating and contributing to advancing the understanding of sex differences in health and disease. Indeed, explosion of mathematical models have been developed in recent decades for different aspects of human physiology and pathophysiology. This review contains a survey of sex-specific mathematical models of physiological systems, describe insights that have been revealed in those modeling studies, and discuss future opportunities.
    MeSH term(s) Female ; Humans ; Male ; Models, Biological ; Physiology ; Sex Factors
    Language English
    Publishing date 2021-06-10
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Review
    ZDB-ID 1126-5
    ISSN 1879-3134 ; 0025-5564
    ISSN (online) 1879-3134
    ISSN 0025-5564
    DOI 10.1016/j.mbs.2021.108642
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  10. Article ; Online: Mathematical modeling of calcium homeostasis in female rats: An analysis of sex differences and maternal adaptations.

    Stadt, Melissa M / Layton, Anita T

    Journal of theoretical biology

    2023  Volume 572, Page(s) 111583

    Abstract: Calcium plays a vital role in various biological processes, including muscle contractions, blood clotting, skeletal mineralization, and cell signaling. While extracellular calcium makes up less than 1% of total body calcium, it is tightly regulated since ...

    Abstract Calcium plays a vital role in various biological processes, including muscle contractions, blood clotting, skeletal mineralization, and cell signaling. While extracellular calcium makes up less than 1% of total body calcium, it is tightly regulated since too high or too low extracellular calcium concentration can have dangerous effects on the body. Mathematical modeling is a well-suited approach to investigate the complex physiological processes involved in calcium regulation. While mathematical models have been developed to study calcium homeostasis in male rats, none have been used to investigate known sex differences in hormone levels nor the unique physiological states of pregnancy and lactation. Calcitriol, the active form of vitamin D, plays a key role in intestinal calcium absorption, renal calcium reabsorption, and bone remodeling. It has been shown that, when compared to age-matched male rats, females have significantly lower calcitriol levels. In this study we first seek to investigate the impact of this difference as well as other known sex differences on calcium homeostasis using mathematical modeling. Female bodies differ from male bodies in that during their lifetime they may undergo massive adaptations during pregnancy and lactation. Indeed, maternal adaptations impact calcium regulation in all mammals. In pregnant rodents, intestinal absorption of calcium is massively increased in the mother's body to meet the needs of the developing fetus. In a lactating rodent, much of the calcium needs of milk are met by bone resorption, intestinal absorption, and renal calcium reabsorption. Given these observations, the goal of this project is to develop multi-scale whole-body models of calcium homeostasis that represents (1) how sex differences impact calcium homeostasis in female vs. male rats and (2) how a female body adapts to support the excess demands brought on by pregnancy and lactation. We used these models to quantify the impact of individual sex differences as well as maternal adaptations during pregnancy and lactation. Additionally, we conducted "what if" simulations to test whether sex differences in calcium regulation may enable females to better undergo maternal adaptations required in pregnancy and lactation than males.
    MeSH term(s) Pregnancy ; Rats ; Female ; Male ; Animals ; Calcitriol ; Lactation ; Calcium ; Sex Characteristics ; Mammals ; Homeostasis ; Models, Theoretical
    Chemical Substances Calcitriol (FXC9231JVH) ; Calcium (SY7Q814VUP)
    Language English
    Publishing date 2023-07-27
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 2972-5
    ISSN 1095-8541 ; 0022-5193
    ISSN (online) 1095-8541
    ISSN 0022-5193
    DOI 10.1016/j.jtbi.2023.111583
    Database MEDical Literature Analysis and Retrieval System OnLINE

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