↓ Skip to main content

Go with the flow—biology and genetics of the lactation cycle

Overview of attention for article published in Frontiers in Genetics, March 2015
Altmetric Badge

About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • Good Attention Score compared to outputs of the same age (75th percentile)
  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

Mentioned by

twitter
4 X users
wikipedia
1 Wikipedia page

Citations

dimensions_citation
72 Dimensions

Readers on

mendeley
192 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Go with the flow—biology and genetics of the lactation cycle
Published in
Frontiers in Genetics, March 2015
DOI 10.3389/fgene.2015.00118
Pubmed ID
Authors

Eva M. Strucken, Yan C. S. M. Laurenson, Gudrun A. Brockmann

Abstract

Lactation is a dynamic process, which evolved to meet dietary demands of growing offspring. At the same time, the mother's metabolism changes to meet the high requirements of nutrient supply to the offspring. Through strong artificial selection, the strain of milk production on dairy cows is often associated with impaired health and fertility. This led to the incorporation of functional traits into breeding aims to counteract this negative association. Potentially, distributing the total quantity of milk per lactation cycle more equally over time could reduce the peak of physiological strain and improve health and fertility. During lactation many factors affect the production of milk: food intake; digestion, absorption, and transportation of nutrients; blood glucose levels; activity of cells in the mammary gland, liver, and adipose tissue; synthesis of proteins and fat in the secretory cells; and the metabolic and regulatory pathways that provide fatty acids, amino acids, and carbohydrates. Whilst the endocrine regulation and physiology of the dynamic process of milk production seems to be understood, the genetics that underlie these dynamics are still to be uncovered. Modeling of longitudinal traits and estimating the change in additive genetic variation over time has shown that the genetic contribution to the expression of a trait depends on the considered time-point. Such time-dependent studies could contribute to the discovery of missing heritability. Only very few studies have estimated exact gene and marker effects at different time-points during lactation. The most prominent gene affecting milk yield and milk fat, DGAT1, exhibits its main effects after peak production, whilst the casein genes have larger effects in early lactation. Understanding the physiological dynamics and elucidating the time-dependent genetic effects behind dynamically expressed traits will contribute to selection decisions to further improve productive and healthy breeding populations.

X Demographics

X Demographics

The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 192 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Netherlands 1 <1%
United Kingdom 1 <1%
New Zealand 1 <1%
Denmark 1 <1%
Russia 1 <1%
Unknown 187 97%

Demographic breakdown

Readers by professional status Count As %
Student > Master 26 14%
Student > Ph. D. Student 24 13%
Student > Bachelor 24 13%
Researcher 23 12%
Student > Doctoral Student 11 6%
Other 34 18%
Unknown 50 26%
Readers by discipline Count As %
Agricultural and Biological Sciences 70 36%
Veterinary Science and Veterinary Medicine 20 10%
Biochemistry, Genetics and Molecular Biology 13 7%
Medicine and Dentistry 6 3%
Nursing and Health Professions 5 3%
Other 21 11%
Unknown 57 30%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 6. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 30 November 2021.
All research outputs
#5,500,089
of 22,796,179 outputs
Outputs from Frontiers in Genetics
#1,539
of 11,761 outputs
Outputs of similar age
#63,784
of 263,459 outputs
Outputs of similar age from Frontiers in Genetics
#41
of 148 outputs
Altmetric has tracked 22,796,179 research outputs across all sources so far. Compared to these this one has done well and is in the 75th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 11,761 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done well, scoring higher than 86% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 263,459 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 75% of its contemporaries.
We're also able to compare this research output to 148 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.