Jove
Visualize
联系我们
JoVE
x logofacebook logolinkedin logoyoutube logo
关于 JoVE
概览领导团队博客JoVE 帮助中心
作者
出版流程编辑委员会范围与政策同行评审常见问题投稿
图书馆员
用户评价订阅访问资源图书馆顾问委员会常见问题
研究
JoVE JournalMethods CollectionsJoVE Encyclopedia of Experiments存档
教育
JoVE CoreJoVE BusinessJoVE Science EducationJoVE Lab Manual教师资源中心教师网站
使用条款与条件
隐私政策
政策

相关概念视频

Assessing Body Temperature - Temporal Artery01:19

Assessing Body Temperature - Temporal Artery

1.6K
Here is a stepwise guide to assessing the body temperature at the temporal artery using a temporal artery thermometer
Step 1: Perform hand hygiene and don a fresh pair of gloves to prevent cross-infection and ensure patient safety.
Step 2: Explain the procedure to the patient to establish trust. Clear communication establishes trust with the patient, ensures they understand what to expect, promotes cooperation, and enhances comfort during the procedure.  
Step 3: Assess the patient's...
1.6K

您也可能阅读

相关文章

通过共同作者、期刊和引用图与本文相关的文章。

排序
Same author

Integrated deep learning and multi-scale modeling for the discovery of pan-genotypic HCV NS5B polymerase inhibitors.

Molecular diversity·2026
Same author

Decoding the Toxicity of Synthetic Cannabinoids: From Receptor Activation to Multiorgan Dysfunction.

Medicinal research reviews·2026
Same author

Depressive symptoms, social support, and family functioning among pregnant women with a history of recurrent pregnancy loss and their spouses: An analysis of the actor-partner interdependence mediation model.

Midwifery·2026
Same author

Excitatory synapses onto axonic spines jump-start action potentials and route information flow.

Nature neuroscience·2026
Same author

The SoxE factor Sox9 is selectively expressed in indirect pathway striatal projection neurons and regulates synaptogenesis.

Fundamental research·2026
Same author

Complete genome sequence of ramie marafivirus 1, a novel marafivirus infecting ramie (Boehmeria nivea).

Archives of virology·2026

相关实验视频

Updated: May 3, 2026

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images
09:21

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Published on: February 18, 2015

12.3K

根据多器官代谢学和机器学习算法,根据不同的环境温度估计死后间隔.

Weihao Fan1, Xinhua Dai2, Yi Ye1

  • 1Department of Analytical Toxicology, West China School of Basic Medical Sciences and Forensic Medicine, Sichuan University, Chengdu, Sichuan, 610041, PR China.

International journal of legal medicine
|May 27, 2025
PubMed
概括

使用代谢学和机器学习改进了自死亡以来的估计时间. 肝脏,脏和肌肉中的代谢物的多器官分析提供了准确的死后间隔估计跨温度.

关键词:
环境温度 环境温度在GC-MS中使用GC-MS.机器学习是机器学习.多个器官的代谢组.验尸后的时间间隔.

更多相关视频

Analytical Determination of Mitochondrial Function of Excised Solid Tumor Homogenates
11:32

Analytical Determination of Mitochondrial Function of Excised Solid Tumor Homogenates

Published on: August 6, 2021

2.8K
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

660

相关实验视频

Last Updated: May 3, 2026

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images
09:21

Human Brown Adipose Tissue Depots Automatically Segmented by Positron Emission Tomography/Computed Tomography and Registered Magnetic Resonance Images

Published on: February 18, 2015

12.3K
Analytical Determination of Mitochondrial Function of Excised Solid Tumor Homogenates
11:32

Analytical Determination of Mitochondrial Function of Excised Solid Tumor Homogenates

Published on: August 6, 2021

2.8K
Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics
11:02

Identification and Quantification of Deranged Metabolites in Critically Ill Patients Using NMR-Based Metabolomics

Published on: November 29, 2024

660

科学领域:

  • 法医科学 法医科学 法医科学
  • 代谢学 代谢学 代谢学
  • 机器学习 机器学习

背景情况:

  • 准确的死后间隔估计在法医调查中至关重要.
  • 现有的死后间隔估计方法有局限性.
  • 代谢学与机器学习相结合,为更精确的估计提供了一个有希望的方法.

研究的目的:

  • 调查多器官代谢学对死后间隔估计的有用性.
  • 开发和验证机器学习模型,用于在不同温度下进行死后间隔估计.
  • 建立适用于特定温度范围的死后间隔估计的通用模型.

主要方法:

  • 气色谱-质谱法 (GC-MS) 用于分析大鼠肝脏,脏和肌肉组织中的代谢物.
  • 多变量统计分析确定了与死后间隔相关的差异性代谢物.
  • 使用单器官和多器官代谢学数据开发了支持向量回归模型,用于死后间隔估计.

主要成果:

  • 与死后间隔相关的不同代谢物在肝脏 (24),脏 (18) 和肌肉 (19) 组织中被确定.
  • 与单个器官模型相比,多器官代谢模型在死后间隔估计中表现出更高的准确性.
  • 一个综合多器官数据和温度变量综合的综合模型准确估计了5-35°C之间的死后间隔.

结论:

  • 多器官代谢学与机器学习相结合,为死后间隔估计提供了强大而准确的方法.
  • 开发的模型为法医应用提供了显著的进步,特别是在不同的温度条件下.
  • 这项研究为在法医科学中对自死亡确定以来的时间进行代谢学实践实施奠定了基础.