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相关概念视频

Dose-Response Relationship: Overview01:03

Dose-Response Relationship: Overview

Agonists can bind with and activate receptors, resulting in the formation of drug-receptor complexes. Once formed, these complexes catalyze many biochemical processes at the cellular level and subsequently induce a pharmacologic response. The degree of response is directly proportional to the fraction of activated receptors, which in turn, depends on the concentration of the drug at the receptor site as well as the sensitivity of the receptor. An increase in the administered dose contributes to...
Dose-Response Relationship: Selectivity and Specificity01:25

Dose-Response Relationship: Selectivity and Specificity

Drugs exert their therapeutic effects by interacting with receptors, enzymes, or ion channels that are present throughout the human body. The strength and duration of the interaction between a drug and its target receptor are characterized by the selectivity and specificity of the drug. Selectivity refers to a drug's strong preference for its intended target over other targets. For instance, isoprenaline, a non-selective β-adrenergic agonist, interacts with both β1- and β2-adrenergic receptors...
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches01:14

Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches

Drug disposition in the body is a complex process and can be studied using two major approaches: the model and the model-independent approaches.
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis00:59

Model-Independent Approaches for Pharmacokinetic Data: Noncompartmental Analysis

Noncompartmental analyses offer an alternative method for describing drug pharmacokinetics without relying on a specific compartmental model. In this approach, the drug's pharmacokinetics are assumed to be linear, with the terminal phase log-linear. This assumption allows for simplified analysis and interpretation of the drug's behavior in the body.
One important characteristic of noncompartmental analyses is that drug exposure increases proportionally with increasing doses. This relationship...
Bioavailability Study Design: Single Versus Multiple Dose Studies01:11

Bioavailability Study Design: Single Versus Multiple Dose Studies

Bioavailability studies are essential for understanding how a drug is absorbed, distributed, metabolized, and excreted in the body. These studies assess the extent and rate at which the active pharmaceutical agent becomes available at the site of action. The design of bioavailability studies can involve single-dose or multiple-dose regimens, each with distinct advantages and limitations.Single-dose studies are the preferred approach due to their simplicity and reduced drug exposure for...
Dose Response Curve: Conventional Versus Nonmonotonic01:21

Dose Response Curve: Conventional Versus Nonmonotonic

The correlation between a drug's dosage and its impact on a biological system is a cornerstone of pharmacology and toxicology. Conventional dose–response curves, which include graded and quantal relationships, are key to this understanding. Graded dose–response curves depict the spectrum of a biological reaction to different doses within an individual, indicating that as the drug dosage increases, so does the intensity of the response. On the other hand, quantal dose–response relationships...

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SOLA:使用半监督的工作流程在多omics数据中剖析剂量反应模式.

Wanxin Lai1, You Song2,3, Knut Erik Tollefsen2,3,4

  • 1Bioinformatics and Applied Statistics (BIAS), Faculty of Chemistry, Biotechnology and Food Science, Norwegian University of Life Sciences (NMBU), Akershus, Norway.

Frontiers in genetics
|December 17, 2024
PubMed
概括
此摘要是机器生成的。

这项研究引入了一种新的工作流程,即半监督的Omics景观分析 (SOLA),用于分析多omics数据,以了解玛辐射等环境压力因素的剂量反应模式.

关键词:
达夫尼亚大 (Daphnia magna) 是一个大的植物.不良结果路径 (AOP)剂量 - 反应模式.多种多种多种多种多种多种多种多种多种多种.网络分析 网络分析非单调的反应.辐射的影响 辐射效应一种半监督的方法.

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科学领域:

  • 生态毒理学 生态毒理学
  • 系统生物学 系统生物学
  • 生物信息学是一种生物信息学.

背景情况:

  • 在生态毒理学中,OMIC数据越来越多地用于研究环境压力因素的影响.
  • 使用多omics数据调查复杂的非单调的剂量反应模式仍然具有挑战性.

研究的目的:

  • 开发一种新的半监督网络分析工作流程 (SOLA),作为基准剂量 (BMD) 建模的替代方案.
  • 为了分析*Daphnia magna*暴露于慢性马辐射的多组数据.
  • 为了获得对辐射剂量依赖效应的新见解.

主要方法:

  • 无监督的共同表达网络分析以按剂量反应分组基因.
  • 对基因模块进行监督分类.
  • 使用转录因子结合基因重建监管网络.
  • 跨数据集的差异共同表达网络分析.
  • 路径丰富分析整合了转录组学和代谢组学数据.

主要成果:

  • SOLA的工作流确定了玛辐射对大的已知和新效应.
  • 分析显示,不同辐射剂量速率的生物反应发生了变化.
  • 这项研究提供了一种新的方法,用于多种菌剂的剂量反应分析.

结论:

  • 开发的SOLA工作流提供了一个强大的替代方案,用于分析复杂的多omics剂量反应数据.
  • 这种方法提高了对环境压力因素在机械层面的影响的理解.
  • SOLA可以应用于未来的生态毒理学研究,涉及各种压力因素和奥米克数据集.