死亡后胰腺自解作为早期死亡后间隔的组织学标记:在热带环境中进行的法医解剖研究
Sunon Sripirom1, Vichan Peonim1, Wisarn Worasuwannarak1
1Department of Pathology, Faculty of Medicine Ramathibodi Hospital, Mahidol University, Bangkok, Thailand.
Forensic science international. Synergy
|January 26, 2026
概括
死亡后胰腺自解是早期死亡后间隔估计的有用组织学标记,特别是在热带环境中. 虽然它本身并不精确,但当与其他方法相结合时,它有助于法医解剖.
科学领域:
- 法医病理学 法医病理学
- 历史学 历史学 历史学
- 死亡后间隔估计估计
背景情况:
- 准确的死后间隔 (PMI) 估计在法医调查中至关重要.
- 器官的组织学变化为PMI提供了潜在的标志物,特别是在早期阶段.
- 胰腺自解,死后降解过程,已被探索为一个潜在的指标.
研究的目的:
- 在法医解剖中评估死后胰腺自解作为早期PMI的组织学标志物.
- 为了研究胰腺自解 (头部,身体,尾部) 的区域差异.
- 评估胰腺自解在热带环境中的适用性.
主要方法:
- 研究了30个已知PMI<24小时的法医尸检案例.
- 从头部,身体和尾部收集了胰腺组织样本.
- 经过处理和染色的样本 (血素-素) 用于视觉定量自溶性变化.
主要成果:
- PMI显示了所有胰腺区域的自解和平均自解 (p ≤ 0.002) 的显著正相关性.
- 自溶变得可见于死后2小时左右; >50%的自溶在5小时之前没有观察到.
- 在创伤性死亡中,PMI和自解之间的相关性更强.
结论:
- 死亡后胰腺自解提供了对早期PMI有价值的见解.
- 它最好用作多式联络方法中的补充组织学工具,而不是作为唯一的决定因素.
- 这种方法在温暖,潮湿的 (热带) 法医环境中尤为重要.
更多相关视频
07:40Field Postmortem Rabies Rapid Immunochromatographic Diagnostic Test for Resource-Limited Settings with Further Molecular Applications
Published on: June 29, 2020
14.5K
08:16High-resolution Structural Magnetic Resonance Imaging of the Human Subcortex In Vivo and Postmortem
Published on: December 30, 2015
15.8K
相关概念视频
01:03Prediction Intervals
3.4K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
3.4K
01:21Confidence Intervals
10.6K
An unbiased point estimate is often insufficient to predict a population estimate, such as population mean or population proportion. In this scenario, a confidence interval is used. A confidence interval is an estimate similar to a sample proportion. However, unlike the point estimate which is a single value, the confidence interval contains a range of values. These values have lower and upper limits, known as confidence limits, and can be designated as L1 and L2, respectively.
A...
A...
10.6K
00:54Uncertainty: Confidence Intervals
11.6K
The confidence interval is the range of values around the mean that contains the true mean. It is expressed as a probability percentage. The interpretation of a 95% confidence interval, for instance, is that the statistician is 95% confident that the true mean falls within the interval. The upper and lower limits of this range are known as confidence limits. The confidence limits for the true mean are estimated from the sample's mean, the standard deviation, and the statistical factor...
11.6K
01:19Interpretation of Confidence Intervals
10.0K
A confidence interval is a better estimate of the population than a point estimate, as it uses a range of values from a sample instead of a single value.
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
Confidence intervals have confidence coefficients that are crucial for their interpretation. The most common confidence coefficients are 0.90, 0.95, and 0.99, which can be written as percentages–90%, 95%, and 99%, respectively.
Suppose a person calculates a confidence interval with a confidence coefficient of 0.95. In that case, they can...
10.0K
00:55Interval Level of Measurement
18.8K
For effective statistical analysis, data are classified into four levels of measurement—nominal, ordinal, interval, and ratio.
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
Data measured using the interval scale are similar to ordinal level data because they have a definite arrangement. However, in the interval level of measurement, the differences between data values are meaningful even though the data does not have a starting point.
Temperature is measured using the interval scale. It is measurable data, and the difference between...
18.8K
01:26Stomach Histology
3.1K
The stomach comprises several layers that work together to facilitate digestion and protect the organ. The outermost layer is called the serosa, which provides support and protection to the stomach. The muscularis externa layer is responsible for the mechanical breakdown of food by contracting and moving the stomach. The submucosa layer, located beneath the muscularis externa, contains connective tissue, blood vessels, nerves, and glands that secrete mucus and other substances essential for...
3.1K