Evidence map›Paper›PMID 42282579›Full record

ArticlebioRxiv : the preprint server for biology2026

A digital droplet microarray for measuring tolerance to antibiotics.

Rena Fukuda, Nadia Nikulin, Shenghao Tan, Tobias Dörr, Nate J Cira

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. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Rena FukudaMeinig School of Biomedical Engineering, Cornell University; Ithaca, 14853, United States.ORCID 0000-0001-9717-3415
Nadia NikulinDepartment of Microbiology, Cornell University, Ithaca, United States.ORCID 0000-0003-0068-6375
Shenghao TanMeinig School of Biomedical Engineering, Cornell University; Ithaca, 14853, United States.ORCID 0009-0007-9750-2777
Tobias DörrDepartment of Microbiology, Cornell University, Ithaca, United States.ORCID 0000-0003-3283-9161
Nate J CiraMeinig School of Biomedical Engineering, Cornell University; Ithaca, 14853, United States.ORCID 0000-0002-7818-2962

Funding

Establishing culture conditions for uncultured microbesR35GM157104 · NIGMS · CORNELL UNIVERSITY · PI Nate Cira · 2025 to 2026
$797k
NIGMS NIH HHS R35 GM157104
6 · The paper itself

Abstract

Antibiotic tolerance enables populations of microbes to survive normally lethal antibiotic concentrations, increasing the likelihood of reinfection and facilitating the evolution of resistance. Tolerance measurements typically involve quantifying viable cells after antibiotic exposure. Existing methods range from accessible but low-throughput approaches, such as plate counting, to higher-throughput but semi-quantitative techniques, such as the TDtest. Here, we develop a new system for rapid, precise and high-throughput tolerance measurements. We utilize Surface Patterned Omniphobic Tiles (SPOTs) to discretize cell suspensions into nano- to microliter droplets and estimate the viable cell concentrations following antibiotic exposure from the proportion of empty droplets using Poissonian statistics. We apply the platform to monitor

Identifiers

PMID42282579
PMCPMC13252167

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.