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Classifying Matter by State02:49

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Chemistry is the study of matter and the changes it undergoes. Matter is anything that has mass and occupies space. Matter is all around us; the air, water, soil, mountains, even our bodies are all examples of matter. Matter is divided into three states — solid, liquid, and gas — that are commonly found on earth. The fourth state of matter, plasma, occurs naturally in the interiors of stars. 
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Matter: Pure Substances and Mixtures
According to its composition, the matter can be classified into two broad categories — pure substances and mixtures. 
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The substance of the universe—from a grain of sand to a star—is called matter. Scientists define matter as anything that occupies space and has mass. An object’s mass and its weight are related concepts, but not quite the same. An object’s mass is the amount of matter contained in the object and is the same whether that object is on Earth or in the zero-gravity environment of outer space. An object’s weight, on the other hand, is its mass as affected by the pull of...
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The earliest recorded discussion of the basic structure of matter comes from ancient Greek philosophers. Leucippus and Democritus argued that all matter was composed of small, finite particles that they called atomos, meaning “indivisible.” Later, Aristotle and others came to the conclusion that matter consisted of various combinations of the four “elements” — fire, earth, air, and water — and could be infinitely divided. Interestingly, these philosophers...
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Solids, liquids, and gases are the three states of matter commonly found on Earth. A solid is rigid and possesses a definite shape. A liquid flows and takes the shape of its container, except it forms a flat or slightly curved upper surface when acted upon by gravity. Both liquid and solid samples have volumes nearly independent of pressure. A gas takes both the shape and volume of its container.
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Modeling white matter tract integrity in aging with diffusional kurtosis imaging.

Andreana Benitez1, Jens H Jensen2, Maria Fatima Falangola2

  • 1Center for Biomedical Imaging, Medical University of South Carolina, Charleston, SC, USA; Department of Neurology, Medical University of South Carolina, Charleston, SC, USA; Department of Radiology and Radiological Science, Medical University of South Carolina, Charleston, SC, USA.

Neurobiology of Aging
|July 29, 2018
PubMed
Summary

Aging causes myelin breakdown and neural fiber loss. New metrics using Diffusional Kurtosis Imaging reveal age-related white matter changes, primarily in extraaxonal space, aiding study of neurodegenerative decline.

Keywords:
AgingDiffusion MRIDiffusional kurtosis imagingWhite matterWhite matter tract integrity

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Area of Science:

  • Neuroscience
  • Radiology
  • Gerontology

Background:

  • Aging is associated with myelin breakdown and neural fiber loss.
  • Understanding age-related white matter changes is crucial for distinguishing normal aging from neurodegeneration.

Purpose of the Study:

  • To assess myelin loss and axonal density using advanced white matter tract integrity metrics.
  • To identify age-related changes and ontogenic differences in white matter tracts in cognitively unimpaired older adults.

Main Methods:

  • Utilized Diffusional Kurtosis Imaging (DKI) and biophysical modeling to derive white matter tract integrity metrics.
  • Employed tract-based spatial statistics and region of interest analyses on cross-sectional and longitudinal data.
  • Analyzed data using general linear and mixed-effects models.

Main Results:

  • White matter tract integrity metrics differentiated early- from late-myelinating tracts.
  • Metrics correlated with age in specific brain regions, indicating spatially distinct changes.
  • Identified predominantly extraaxonal changes over time, with annual declines of |0.3-0.9|% (cross-sectional) and |0.0-1.9|% (longitudinal).
  • Observed accelerated decline in late-myelinating tracts compared to early-myelinating tracts in older age.

Conclusions:

  • Novel white matter tract integrity metrics derived from DKI are sensitive to age-related changes.
  • These metrics primarily reflect extraaxonal changes and can differentiate tract types.
  • Findings support the use of these metrics to study the transition from normal aging to neurodegenerative processes.