Evidence map›Paper›PMID 41959393›Full record

ArticlebioRxiv : the preprint server for biology2026

Automated culture and monitoring of a high-throughput human heart-on-a-chip.

Bryan G Schellberg, Nolan T Burson, Joshua Gomes, Guohao Dai, Abigail N Koppes, Ryan A Koppes

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
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

1 citing paper in PubMed.

  1. Review
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

6 authors.

Bryan G SchellbergDepartment of Chemical Engineering, Northeastern University, Boston, Massachusetts, USA.ORCID 0000-0001-8405-429X
Nolan T BursonDepartment of Chemical Engineering, Northeastern University, Boston, Massachusetts, USA.ORCID 0000-0003-1603-0995
Joshua GomesParallel Fluidics, Boston, Massachusetts, USA.
Guohao DaiDepartment of Bioengineering, Northeastern University, Boston, Massachusetts, USA.ORCID 0000-0001-7346-2685
Abigail N KoppesDepartment of Chemical Engineering, Northeastern University, Boston, Massachusetts, USA.ORCID 0000-0003-0433-9290
Ryan A KoppesDepartment of Chemical Engineering, Northeastern University, Boston, Massachusetts, USA.ORCID 0000-0002-3376-6358

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Organ chips offer a disruptive innovation to study human diseases with tissue-specific resolution within a predictable and tunable in vitro environment. However, these platform technologies have for the most part failed to translate to broad use in the private sector due to a lack of high-throughput, user-friendly platforms. Here we present an automated high-throughput organ chip seeded with iPSC-derived cardiomyocytes transduced with GCaMP6f and interface with translational technologies to bridge the current academia-industry gap. Cardiomyocytes were seeded on-chip fully hands-free using an entry-level fluid handling robot to significantly reduce user handling requirements. Pipette interfaces were paramount to facilitating seeding and feeding through improved tolerances for establishing a functional connection to dispense and collect small fluidic volumes. Following successful seeding, GCaMP6f activity on-chip was monitored with our automated, non-invasive fiber-optic sensing platform. We show a significant decrease in cardiomyocyte beat rate in response to decreased ambient culture temperature using data collected with our optical sensing platform. This study provides a potential translational blueprint for academia-industry partnership toward broad adoption of organ chip technology in drug development and disease modeling.

Identifiers

PMID41959393
PMCPMC13060897

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.