Evidence map›Paper›PMID 30112543›Full record

ArticleLab on a chip2018

Automated microfluidic droplet sampling with integrated, mix-and-read immunoassays to resolve endocrine tissue secretion dynamics.

Xiangpeng Li, Juan Hu, Christopher J Easley

Open access · greenAbstract read
In one paragraph

Article in Lab on a chip, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed
2.7field-weighted citation impact, top 10% 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

23 citing papers in PubMed, 43 citations in OpenAlex.

  1. Article
  2. Dynamic sampling fromLab on a chip · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Review
  9. Article
  10. Autologous Human Immunocompetent White Adipose Tissue-on-Chip.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022
    Article
  11. Article
  12. Review
  13. Article
  14. Active Flow Control and Dynamic Analysis in Droplet Microfluidics.Annual review of analytical chemistry (Palo Alto, Calif.) · 2021
    Review
  15. Review
  16. Review
  17. Review
  18. Frontiers in endocrinology · 2021
    Article
  19. Article
  20. Article
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

3 authors at 1 institution in 1 country.

Xiangpeng LiDepartment of Chemistry and Biochemistry, Auburn University, Auburn, AL 36849, USA. chris.easley@auburn.edu.
Juan Hu
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

A fully automated droplet generation and analysis device based on pressure driven push-up valves for precise pumping of fluid and volumetric metering has been developed for high resolution hormone secretion sampling and measurement. The device consists of a 3D-printer templated reservoir for single cells or single tissue culturing, a Y-shaped channel for reagents and sample mixing, a T-junction channel for droplet formation, a reference channel to overcome drifts in fluorescence signal, and a long droplet storage channel allowing incubation for homogeneous immunoassays. The droplets were made by alternating peristaltic pumping of aqueous and oil phases. Device operation was automated, giving precise control over several droplet parameters such as size, oil spacing, and ratio of sample and reference droplets. By integrating an antibody-oligonucleotide based homogeneous immunoassay on-chip, high resolution temporal sampling into droplets was combined with separation-free quantification of insulin secretion from single islets of Langerhans using direct optical readout from the droplets. Quantitative assays of glucose-stimulated insulin secretion were demonstrated at 15 second temporal resolution while detecting as low as 10 amol per droplet, revealing fast insulin oscillations that mirror well-known intracellular calcium signals. This droplet sampling and direct optical analysis approach effectively digitizes the secretory time record from cells into droplets, and the system should be generalizable to a variety of cells and tissue types.

Indexed as

Lab-On-A-Chip DevicesAnimalsAutomationEquipment DesignImmunoassayInsulinIslets of LangerhansMiceMice, Inbred C57BLSystems IntegrationInsulin

Identifiers

PMID30112543
PMCPMC6234046
OpenAlexW2885804131

What OpenQuestion holds

Textmetadata
LicenceTDM
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.