Evidence map›Paper›PMID 32239045›Full record

ArticleLab on a chip2020

Rapid lipolytic oscillations in ex vivo adipose tissue explants revealed through microfluidic droplet sampling at high temporal resolution.

Juan Hu, Xiangpeng Li, Robert L Judd, Christopher J Easley

Open access · greenAbstract read
In one paragraph

Article in Lab on a chip, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
1.6field-weighted citation impact, top 19% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

14 citing papers in PubMed, 21 citations in OpenAlex.

  1. Dynamic sampling fromLab on a chip · 2024
    Article
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  7. Autologous Human Immunocompetent White Adipose Tissue-on-Chip.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Article
  8. Active Flow Control and Dynamic Analysis in Droplet Microfluidics.Annual review of analytical chemistry (Palo Alto, Calif.) · 2021
    Review
  9. Review
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  11. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Juan HuDepartment of Chemistry and Biochemistry, Auburn University, Auburn, AL 36849, USA. chris.easley@auburn.edu.
Xiangpeng Li
Robert L Judd
Christopher J Easley
Auburn University · US

Funding

Unmasking mechanisms of lipolytic dynamics in adipose tissue using high-resolution microfluidic samplingR01DK093810 · NIDDK · AUBURN UNIVERSITY AT AUBURN · PI EASLEY, CHRISTOPHER J · 2012 to 2023
$3.8M
NIDDK NIH HHS R01 DK093810
6 · The paper itself

Abstract

Our understanding of adipose tissue biology has steadily evolved. While structural and energy storage functionalities have been in the forefront, a key endocrine role for adipocytes was revealed only over the last few decades. In contrast to the wealth of information on dynamic function of other endocrine tissues, few studies have focused on dynamic adipose tissue function or on tool development toward that end. Here, we apply our unique droplet-based microfluidic devices to culture, perfuse, and sample secretions from primary murine epididymal white adipose tissue (eWAT), and from predifferentiated clusters of 3T3-L1 adipocytes. Through automated control, oil-segmented aqueous droplets (∼2.6 nL) were sampled from tissue or cells at 3.5 second temporal resolution (including sample and reference droplets), with integrated enzyme assays enabling real-time quantification of glycerol (down to 1.9 fmol per droplet). This high resolution revealed previously unreported oscillations in secreted glycerol at frequencies of 0.2 to 2.0 min

Indexed as

Adipose TissueMicrofluidics3T3-L1 CellsAdipocytesAdipose Tissue, WhiteAnimalsMice

Identifiers

PMID32239045
PMCPMC7380261
OpenAlexW3012867506

What OpenQuestion holds

Textmetadata
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Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.