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相关概念视频

Obesity01:24

Obesity

1.1K
The Body Mass Index (BMI) is a numerical value derived from a person's weight and height, used to categorize individuals into weight ranges. It is calculated using the formula: weight in kilograms divided by height in meters squared. Obesity is a health condition characterized by excessive accumulation of adipose tissue that poses health risks, often diagnosed with a BMI ≥ 30. This excess fat storage occurs when surplus dietary calories are converted into triglycerides and stored in...
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Pharmacokinetics in Obese Patients: Drug Absorption and Distribution01:25

Pharmacokinetics in Obese Patients: Drug Absorption and Distribution

218
Obesity significantly alters the pharmacokinetic processes of drug absorption and distribution, presenting unique challenges in medical treatment. The increased fat tissue and decreased lean muscle in obese individuals can significantly affect how drugs are absorbed into the body and distributed across different tissues. This alteration can lead to variances in the effectiveness and safety of medications, necessitating adjustments in dosing or drug selection for obese patients.One notable...
218
Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion01:20

Pharmacokinetics in Obese Patients: Drug Metabolism and Excretion

153
Drug metabolism, a critical process in the liver, involves two primary phases: Phase I reactions and Phase II conjugation. Obesity introduces significant alterations in this metabolic process, primarily due to fatty infiltration of the liver, leading to conditions such as nonalcoholic fatty liver disease (NAFLD). This condition can modify the activities of both Phase I and II enzymes, impacting how drugs are metabolized in obese patients.Phase I metabolism sees variable effects across...
153

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相关实验视频

Updated: Jan 7, 2026

Multidisciplinary Approach to Obesity Management: A Case Report
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Multidisciplinary Approach to Obesity Management: A Case Report

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多模式 (生物) 标志物和肥胖风险 - - 一个全面的范围审查.

Farhad Vahid1, Alejandra Loyola-Leyva1, Josep Tur2

  • 1Department of Precision Health, Luxembourg Institute of Health, L-1445 Strassen, Luxembourg.

Advances in nutrition (Bethesda, Md.)
|December 26, 2025
PubMed
概括

早期发现肥胖风险需要采用多模式方法,整合各种生物标志物和人工智能等先进工具. 这一策略对于有效的预防和个性化干预策略至关重要.

关键词:
饮食 饮食 饮食 饮食这些都是情绪,情绪.我们的肠道微生物组.这是一个小RNARNA.这是一个多维的多维空间.多类标记器多类标记器多元组件标记器的使用.体重过重的人超重.

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Segmentation and Measurement of Fat Volumes in Murine Obesity Models Using X-ray Computed Tomography
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科学领域:

  • 生物医学科学 生物医学科学
  • 公共卫生 公共卫生
  • 预防医学 预防医学

背景情况:

  • 肥胖是一种复杂的,多因素的疾病,与慢性疾病有关,尽管全球努力,但患病率仍然很高.
  • 早期发现肥胖风险对于及时干预至关重要,但单个生物标志物不足以准确地分层风险.
  • 许多因素导致肥胖,包括遗传学,生活方式,心理状态和肠道微生物群.

研究的目的:

  • 通过多式模式生物标志物方法,回顾目前肥胖风险预测方面的进展.
  • 突出新的策略,并评估这些生物标志物在临床环境中的可行性和有效性.
  • 为未来的肥胖预防研究和临床应用提供建议.

主要方法:

  • 对有关肥胖生物标志物和风险预测的现有文献进行范围审查.
  • 综合古典标记,多omics数据,行为因素,心理特征和肠道微生物群的多模式方法的分析.
  • 检查机器学习和人工智能在解释复杂生物标记数据中的作用.

主要成果:

  • 多式联络方法,结合多种数据类型和先进的分析,显示了改善肥胖风险预测的希望.
  • 整合遗传学,表观遗传学,代谢学,行为数据和肠道微生物群,可以更全面地了解个人风险.
  • 机器学习和人工智能对于合成复杂数据集和实现个性化风险分层至关重要.

结论:

  • 多模式生物标志物策略对于准确的肥胖风险评估和个性化预防至关重要.
  • 未来的研究应该专注于在不同人群和临床试验中验证这些综合方法.
  • 这些生物标志物的有效应用可以导致更有针对性和成功的肥胖对策启动.