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相关概念视频

Vaccinations01:51

Vaccinations

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Overview
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Infection01:20

Infection

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When a pathogen enters the body and reproduces, it can cause an infection, damage body cells, and cause illness symptoms that eventually lead to disease. Therefore, its prevention requires breaking the chain of infection.
The chain begins with pathogens: bacteria, viruses, fungi, prions, or parasites such as protozoa helminths. These can be present on the skin as transient or resident flora, or they can be acquired from the environment. Identifying and treating the type of infection and...
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Pharmacodynamic Models: Direct Effect Model and Indirect Response Model01:29

Pharmacodynamic Models: Direct Effect Model and Indirect Response Model

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Pharmacodynamic models are essential tools in understanding the relationship between drug concentrations and their effects on biological systems. By characterizing the dynamics of drug action, these models guide dose selection, optimize therapeutic efficacy, and inform the development of new drugs. Two major classes of pharmacodynamic models include direct effect and indirect response models.Direct Effect ModelsDirect effect models describe the immediate relationship between drug concentration...
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Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions01:15

Impact of Pharmacokinetic–Pharmacodynamic Models: Regulatory Decisions

58
PK–PD modeling has significantly influenced FDA regulatory decisions, particularly drug approval, dosage optimization, and labeling. These models integrate pharmacokinetics (PK) and pharmacodynamics (PD) to predict drug behavior and effects, aiding in optimizing dosing regimens and enhancing the probability of clinical trial success.One notable example is Nesiritide (Natrecor®), a recombinant human brain natriuretic peptide for treating acute decompensated congestive heart failure...
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Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model01:14

Pharmacodynamic Models: Link Model and Systems Pharmacodynamic Model

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The link model is a fundamental pharmacokinetic-pharmacodynamic (PK–PD) approach to account for delayed drug responses when the observed effect does not immediately correlate with the drug's plasma concentration peak. This delay is mathematically addressed by introducing an effect compartment concentration, Ce, which is kinetically linked to the plasma concentration, Cp, via a first-order rate constant, ke0. The linkage allows for a more accurate prediction of drug effects over time. A...
65
Immune Response Against Viral Pathogens01:29

Immune Response Against Viral Pathogens

2.3K
The immune system's response to viral infections is a complex and coordinated process involving natural killer (NK) cells, T cell-mediated responses, and antibody-mediated responses.
NK Cells
NK cells are a crucial part of our innate immune system, acting as the first line of defense against viral infections. These cells can recognize and kill infected cells without prior exposure to the virus, effectively slowing down the spread of infection. Additionally, NK cells produce proinflammatory...
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相关实验视频

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Generating a Reproducible Model of Mid-Gestational Maternal Immune Activation using PolyI:C to Study Susceptibility and Resilience in Offspring
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Generating a Reproducible Model of Mid-Gestational Maternal Immune Activation using PolyI:C to Study Susceptibility and Resilience in Offspring

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面向系统免疫:模拟虚假信息传播动态与干预和网络驱动的风险级联.

Chunbing Bao1, Haoqian Xie1, Wenting Chen1

  • 1School of Management, Shandong University, Jinan, Shandong, China.

Risk analysis : an official publication of the Society for Risk Analysis
|March 9, 2026
PubMed
概括
此摘要是机器生成的。

这项研究引入了社交媒体传播虚假信息的新模式,考虑了个人行为和网络结构. 它提供了打击假新闻和增强数字社会的弹性工具.

关键词:
虚假信息干预干预干预网络驱动的风险管理传播动态的传播动态系统平衡 系统平衡

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Whole-animal Imaging and Flow Cytometric Techniques for Analysis of Antigen-specific CD8+ T Cell Responses after Nanoparticle Vaccination
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科学领域:

  • 计算社会科学 计算社会科学
  • 网络科学 网络科学
  • 行为经济学是一种行为经济学.

背景情况:

  • 社交媒体上的虚假信息威胁到数字社会,导致认知扭曲和公共危机.
  • 现有的模型未能捕捉到个体异质性,完整的理性假设或跨规模风险合.

研究的目的:

  • 提出一种新的虚假信息传播模型,整合个人动态,网络拓和干预分析.
  • 为虚假信息免疫系统开发一个理论框架,并为数字治理提供可量化的决策工具.

主要方法:

  • 构建了一个网络传播模型,结合了风险感知,决策灵敏度和认知惯性.
  • 开发了一个双指数系统,根据风险暴露和脆弱性来识别超级传播者.
  • 制定了一个干预模型,将认知纠正和传播抑制结合起来,分析平衡和趋同.

主要成果:

  • 在非干预模型中证明了平衡的存在,并在干预中获得了独特的趋同条件.
  • 确立了有限干预效率定理,并推导了对收时间的下限.
  • 通过个人异质性和干预强度量化系统性风险的联合调制.

结论:

  • 拟议的模型提供了一个全面的框架,用于理解和减轻虚假信息的传播.
  • 调查结果为数字治理提供了可量化的工具,增强了对虚假新闻带来的系统风险的抵御力.