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Related Concept Videos

Mean free path and Mean free time01:22

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Consider the gas molecules in a cylinder. They move in a random motion as they collide with each other and change speed and direction. The average of all the path lengths between collisions is known as the "mean free path."
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Consider the two thermodynamic processes involving an ideal gas that are represented by paths AC and ABC in Figure 1:
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Genomics is the science of genomes: it is the study of all the genetic material of an organism. In humans, the genome consists of information carried in 23 pairs of chromosomes in the nucleus, as well as mitochondrial DNA. In genomics, both coding and non-coding DNA is sequenced and analyzed. Genomics allows a better understanding of all living things, their evolution, and their diversity. It has a myriad of uses: for example, to build phylogenetic trees, to improve productivity and...
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Interference: Path Lengths01:10

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Consider two sources of sound, that may or may not be in phase, emitting waves at a single frequency, and consider the frequencies to be the same.
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Behavior of Gas Molecules: Molecular Diffusion, Mean Free Path, and Effusion03:48

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Although gaseous molecules travel at tremendous speeds (hundreds of meters per second), they collide with other gaseous molecules and travel in many different directions before reaching the desired target. At room temperature, a gaseous molecule will experience billions of collisions per second. The mean free path is the average distance a molecule travels between collisions. The mean free path increases with decreasing pressure; in general, the mean free path for a gaseous molecule will be...
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Genomic Imprinting and Inheritance02:30

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Diploid organisms inherit genetic material through chromosomes from both parents. Copies of the same gene are known as alleles. In most cases, both alleles are simultaneously expressed and allow various cellular processes to function optimally. If one of the alleles is missing or mutated, the expression of the other allele can compensate; however, this is not true for all genes.
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Ultra-long Read Sequencing for Whole Genomic DNA Analysis
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Genomics in CKD: Is This the Path Forward?

Girish N Nadkarni1, Carol R Horowitz1

  • 1Department of Medicine, Division of Nephrology, Icahn School of Medicine, New York, NY; Department of Population Health Science and Policy, Icahn School of Medicine, New York, NY; and Department of Medicine, Icahn School of Medicine, New York, NY.

Advances in Chronic Kidney Disease
|March 17, 2016
PubMed
Summary
This summary is machine-generated.

Genomic insights into chronic kidney disease (CKD) risk are advancing, but clinical application lags. Understanding genetic factors could improve treatment responses and outcomes for diverse patient populations.

Keywords:
CKDDisparitiesGeneticsGenomicsPharmacogenomics

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Area of Science:

  • Genomics and Precision Medicine
  • Nephrology
  • Pharmacogenomics

Background:

  • Recent advances in genomics and sequencing technologies have improved understanding of genetic risk factors in chronic kidney disease (CKD).
  • Genetic variations, linked to ancestry, may explain differential responses to medications like antihypertensives and immunosuppressants among racial groups.
  • A significant gap exists between the generation of genomic knowledge and its integration into routine clinical practice for CKD management.

Purpose of the Study:

  • To review recent advancements in the field of genomics as applied to CKD.
  • To explore the reasons behind the underutilization of genomic information in clinical settings.
  • To identify potential pathways for applying genomic data to enhance clinical care and improve outcomes in CKD patients.

Main Methods:

  • Literature review of recent studies on genomics and CKD.
  • Analysis of factors contributing to the slow adoption of genomic medicine in nephrology.
  • Discussion of strategies for integrating genomic insights into clinical decision-making for CKD.

Main Results:

  • Genomic research has significantly enhanced the understanding of CKD etiology and progression.
  • Ancestry-related genetic differences are implicated in variable drug responses in CKD patients.
  • Clinical implementation of genomic findings in CKD care remains limited.

Conclusions:

  • Genomic information holds significant potential for personalizing CKD treatment and improving patient outcomes.
  • Addressing the barriers to clinical adoption is crucial for realizing the benefits of genomic medicine in nephrology.
  • Future research should focus on translating genomic discoveries into actionable clinical guidelines for CKD management.