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Related Concept Videos

Mutations01:39

Mutations

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Overview
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Mutations01:35

Mutations

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Mutations are changes in the sequence of DNA. These changes can occur spontaneously or they can be induced by exposure to environmental factors. Mutations can be characterized in a number of different ways: whether and how they alter the amino acid sequence of the protein, whether they occur over a small or large area of DNA, and whether they occur in somatic cells or germline cells.
Chromosomal Alterations Are Large-Scale Mutations
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Viral Mutations00:36

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A mutation is a change in the sequence of bases of DNA or RNA in a genome. Some mutations occur during replication of the genome due to errors made by the polymerase enzymes that replicate DNA or RNA. Unlike DNA polymerase, RNA polymerase is prone to errors because it is not capable of “proofreading” its work. Viruses with RNA-based genomes, like HIV, therefore accrue mutations faster than viruses with DNA-based genomes. Because mutation and recombination provide the raw material...
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In a population that is not at Hardy-Weinberg equilibrium, the frequency of alleles changes over time. Therefore, any deviations from the five conditions of Hardy-Weinberg equilibrium can alter the genetic variation of a given population. Conditions that change the genetic variability of a population include mutations, natural selection, non-random mating, gene flow, and genetic drift (small population size).
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Spin–Spin Coupling: Two-Bond Coupling (Geminal Coupling)01:20

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Two NMR-active nuclei bonded to a central atom can be involved in geminal or two-bond coupling. Geminal coupling is commonly seen between diastereotopic protons in chiral molecules and unsymmetrical alkenes, among others.
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Spin–Spin Coupling: Three-Bond Coupling (Vicinal Coupling)01:22

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Vicinal or three-bond coupling is commonly observed between protons attached to adjacent carbons. Here, nuclear spin information is primarily transferred via electron spin interactions between adjacent C‑H bond orbitals. This generally favors the antiparallel arrangement of spins, so 3J values are usually positive.
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Coupled, multi-strain epidemic models of mutating pathogens.

Michael T Meehan1, Daniel G Cocks2, James M Trauer3

  • 1Australian Institute of Tropical Health and Medicine, James Cook University, Townsville, Australia.

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|December 31, 2017
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Summary
This summary is machine-generated.

This study introduces multi-strain epidemic models to understand mutant pathogen spread. Key findings show strain reproductive numbers are independent of mutation rates, and diverse strains can coexist, impacting public health strategies.

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Area of Science:

  • Epidemiology
  • Mathematical Biology
  • Infectious Disease Dynamics

Background:

  • Emergence of mutant pathogen strains, such as drug-resistant variants, poses significant public health challenges.
  • Understanding the complex dynamics of multi-strain epidemics is crucial for effective disease control.

Purpose of the Study:

  • To introduce and analyze coupled, multi-strain epidemic models.
  • To investigate the mathematical and biological properties governing the emergence and dissemination of mutant pathogen strains.
  • To derive expressions for the basic reproduction number and explore factors influencing strain coexistence and prevalence.

Main Methods:

  • Development of a general class of multi-strain epidemic models with coupled infectious compartments.
  • Derivation of explicit mathematical expressions for the basic reproduction number (R0) of each strain.
  • Analysis of model properties to determine conditions for epidemic outbreaks, endemic states, and strain coexistence.

Main Results:

  • The basic reproduction number for each strain was found to be independent of mutation rates between strains.
  • Coupling terms in the model were shown to promote strain coexistence, challenging the competitive exclusion principle.
  • The most prevalent strain was not always the one with the highest reproductive capacity.

Conclusions:

  • Mathematical models provide insights into the complex dynamics of multi-strain infectious diseases.
  • Public health policy should consider that dominant strains may not always be the most reproductively capable.
  • Understanding strain interactions is vital for effective epidemic control and resource allocation.