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相关概念视频

End Point Prediction: Gran Plot01:07

End Point Prediction: Gran Plot

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A Gran plot is used to predict the equivalence volume or endpoint of a potentiometric or acid-base titration without reaching the endpoint. Typically, titration data is collected as a function of the titrant's volume up to a point less than the equivalence volume and then transformed into a linear format. The straight line is extended to the x-axis, indicating the necessary titrant volume to achieve the equivalence point.
For potentiometric titration, the Gran plot is created by plotting...
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Metabolic States of the Body: The Absorptive State01:25

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During the absorptive state, which lasts approximately four hours after a meal, the body absorbs nutrients from the gastrointestinal tract. The carbohydrates, proteins, and lipids we consume are broken down into monosaccharides, amino acids, and free fatty acids for absorption. While carbohydrates and proteins are absorbed as-is, lipids are absorbed in their broken-down forms and then re-esterified into triglycerides within enterocytes before being packaged into chylomicrons. These absorbed...
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Metabolic States of the Body: The Postabsorptive State01:18

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The postabsorptive state usually starts about four hours after a meal and lasts until the next meal is eaten. During this time, the digestive system stops absorbing nutrients, and the body uses stored energy reserves to maintain stable blood glucose levels.
Initially, glycogen stored in the liver is broken down to release glucose into the bloodstream, while glycogen in the muscles is broken down to supply glucose for energy directly within the muscle cells. As glycogen stores diminish,...
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Living cells constantly carry out various chemical reactions which are necessary for their proper functioning. These reactions are interlinked to one another via multiple pathways. The collection of these chemical reactions is known as metabolism.
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Metabolism encompasses all biochemical reactions in a living organism, facilitating both the breakdown and synthesis of biomolecules. These metabolic processes are categorized into catabolic and anabolic pathways, which operate in a coordinated manner to ensure energy balance and cellular function.Catabolic Pathways and Energy ReleaseCatabolic pathways involve the breakdown of complex macromolecules such as carbohydrates, lipids, and proteins into smaller structures like monosaccharides, fatty...
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相关实验视频

Updated: Jul 19, 2025

Studying Metabolic Brain Connectivity Using 2-Deoxy-2-[18F]Fluoro-D-Glucose Dynamic Positron Emission Tomography at the Single-subject Level
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CMMS-GCL:与图形对比学习的交叉模式代谢稳定性预测.

Bing-Xue Du1,2, Yahui Long3, Xiaoli Li2

  • 1School of Life Sciences, Northwestern Polytechnical University, Xi'an 710072, China.

Bioinformatics (Oxford, England)
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概括

一个新的计算模型,CMMS-GCL,通过整合分子序列和图形数据,准确地预测药物代谢稳定性. 这种可解释的工具有助于有效地选候选药物和优化线.

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科学领域:

  • 计算化学的计算化学
  • 药物发现 药物发现 药物发现
  • 机器学习 机器学习

背景情况:

  • 代谢稳定性对于药物开发至关重要,影响候选查和优化.
  • 对代谢稳定性的实验性评估是昂贵和耗时的.
  • 在 silico 预测提供了一个替代方案,但强大的和可解释的方法是有限的.

研究的目的:

  • 开发一种用于预测分子代谢稳定的新型计算模型.
  • 通过识别关键功能组来提高预测的解释性.
  • 为药物发现和率优化提供高效准确的工具.

主要方法:

  • 开发了一种跨模态图对比学习模型 (CMMS-GCL).
  • 利用深度学习从SMILES序列 (BiGRU编码器) 和分子图形 (图形对比学习编码器) 中提取特征.
  • 集成的序列和结构表示使用完全连接的神经网络.

主要成果:

  • 在两个基准数据集上,CMMS-GCL的表现优于七种最先进的方法.
  • 通过案例研究和统计分析证明了模型的可解释性,确定了关键的功能组.
  • 在预测代谢稳定性方面取得了持续的改进.

结论:

  • CMMS-GCL是预测药物代谢稳定的有效和可解释的工具.
  • 该模型促进了高效的候选药物选和化合物优化.
  • 识别了关键的功能组,为药物化学家提供了宝贵的见解.