A physiologically based pharmacokinetic computer model and program have been developed that depict internal disposition of chemicals during pregnancy in the mother and embryo/fetus. The model is based on human physiology but has been extended to simulate laboratory animal data. The model represents the distribution, metabolism, and elimination of two chemicals in both the maternal and embryo/fetal systems; the program handles the two chemicals completely independently or interactively with the two chemicals sharing routes of metabolism and/or elimination. The FORTRAN program computes the concentration of the two chemicals in 26 organs/tissues in the pregnant mother and 15 organs/tissues in the embryo/fetus using a 486DX4 or Pentium PC. Adjustments for embryo/fetal organ and tissue volumes as a function of developmental age are made utilizing the Gompertz growth equation for the developing embryo/fetus and allometric relationships for the developing organs. Various changes in the maternal compartments which could affect the distribution of a xenobiotic during pregnancy are also included in the model. Input files require estimates of binding coefficients, first- and/or second-order metabolism constants, level of interaction between the two chemicals, and dosing information. Different possible routes of administration are included (e.g., i.v., infusion, oral, dermal, and inhalation, as well as repeated doses or exposures). Regression analysis can be conducted on any combination of these various parameters to fit actual data. Output concentration-time curves are available simultaneously from all 82 differential equations. An illustrative example compares observed data with simulations for imipramine and its demethylated metabolite, desipramine, in both the maternal rat and her fetuses. Methyl mercury data for the non-pregnant and pregnant rat also are compared with human data. Based on parameters determined from analysis of rat data, the model is readjusted for human physiology and predicts human maternal and fetal tissue concentrations as a function of time.
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http://dx.doi.org/10.1016/s0169-2607(97)00020-5 | DOI Listing |
Mol Divers
January 2025
Key Laboratory of Prevention and Treatment of Cardiovascular and Cerebrovascular Diseases Ministry of Education, Jiangxi Province Key Laboratory of Biomaterials and Biofabrication for Tissue Engineering, Gannan Medical University, Ganzhou, 341000, Jiangxi, China.
Identifying drug-target binding affinity (DTA) plays a critical role in early-stage drug discovery. Despite the availability of various existing methods, there are still two limitations. Firstly, sequence-based methods often extract features from fixed length protein sequences, requiring truncation or padding, which can result in information loss or the introduction of unwanted noise.
View Article and Find Full Text PDFEur Arch Otorhinolaryngol
January 2025
Department of Otorhinolaryngology, University Medical Center of the Johannes Gutenberg-University Mainz, Langenbeckstraße 1, 55131, Mainz, Germany.
Introduction: Tumor boards are a cornerstone of modern cancer treatment. Given their advanced capabilities, the role of Large Language Models (LLMs) in generating tumor board decisions for otorhinolaryngology (ORL) head and neck surgery is gaining increasing attention. However, concerns over data protection and the use of confidential patient information in web-based LLMs have restricted their widespread adoption and hindered the exploration of their full potential.
View Article and Find Full Text PDFMed Care
February 2025
Fogelman College of Business and Economics, The University of Memphis, Memphis, TN.
Objective: Mobile health applications (mHealth apps) can provide health care and health-promoting information while contributing to improving cancer survivors' quality of life and health outcomes. However, little is known about the rural-urban distribution of mHealth app ownership and utilization. In this study, we explore the characteristics of cancer survivors who own and use mHealth apps and examine rural-urban disparities in mHealth app ownership and utilization among cancer survivors.
View Article and Find Full Text PDFNanomaterials (Basel)
December 2024
Department of Computer Engineering, Modeling, Electronics, and Systems Engineering, University of Calabria, 87036 Rende, Italy.
This paper presents Cryo-SIMPLY, a reliable smart material implication (SIMPLY) operating at cryogenic conditions (77 K). The assessment considers SIMPLY schemes based on spin-transfer torque magnetic random access memory (STT-MRAM) technology with single-barrier magnetic tunnel junction (SMTJ) and double-barrier magnetic tunnel junction (DMTJ). Our study relies on a temperature-aware macrospin-based Verilog-A compact model for MTJ devices and a 65 nm commercial process design kit (PDK) calibrated down to 77 K under silicon measurements.
View Article and Find Full Text PDFCells
December 2024
Department of Herbal Pharmacology, College of Korean Medicine, Gachon University, 1342 Seongnamdae-ro, Sujeong-gu, Seongnam-si 13120, Republic of Korea.
The NLRP3 inflammasome, plays a critical role in the pathogenesis of rheumatoid arthritis (RA) by activating inflammatory cytokines such as IL1β and IL18. Targeting NLRP3 has emerged as a promising therapeutic strategy for RA. In this study, a multidisciplinary approach combining machine learning, quantitative structure-activity relationship (QSAR) modeling, structure-activity landscape index (SALI), docking, molecular dynamics (MD), and molecular mechanics Poisson-Boltzmann surface area MM/PBSA assays was employed to identify novel NLRP3 inhibitors.
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