Evidence map›Paper›PMID 42195449›Full record

ArticleMicromachines2026

A Droplet-Based Microfluidic Platform for Rapid Optical Detection of Bacteria: Proof-of-Concept for Radiopharmaceutical Sterility Testing.

Adriano Colombelli, Daniela Lospinoso, Vita Guarino, Alessandra Zizzari, Monica Bianco, Valentina Arima, Roberto Rella, Maria Grazia Manera

Abstract read
In one paragraph

Article in Micromachines, 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

8 authors.

Adriano ColombelliCNR IMM-Istituto per la Microelettronica e i Microsistemi, Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy.ORCID 0000-0001-7840-9699
Daniela LospinosoCNR IMM-Istituto per la Microelettronica e i Microsistemi, Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy.ORCID 0000-0001-6143-2040
Vita GuarinoCNR Nanotec-Istituto di Nanotecnologia, Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy.ORCID 0000-0001-6877-5169
Alessandra ZizzariCNR Nanotec-Istituto di Nanotecnologia, Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy.ORCID 0000-0002-9651-7922
Monica BiancoCNR Nanotec-Istituto di Nanotecnologia, Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy.ORCID 0000-0002-1791-7232
Valentina ArimaCNR Nanotec-Istituto di Nanotecnologia, Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy.
Roberto RellaCNR IMM-Istituto per la Microelettronica e i Microsistemi, Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy.ORCID 0000-0002-9696-1476
Maria Grazia ManeraCNR IMM-Istituto per la Microelettronica e i Microsistemi, Campus Ecotekne, Via Monteroni, 73100 Lecce, Italy.ORCID 0000-0001-9718-2530

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rapid sterility testing of radiopharmaceuticals is essential due to their short half-lives and strict safety requirements. Conventional culture-based methods require several days and are not compatible with clinical workflows. In this work, we present a proof-of-concept droplet-based microfluidic platform for rapid optical detection of bacterial contamination through optical extinction analysis of microdroplets. Monodisperse water-in-oil microdroplets were generated and optically interrogated using a fiber-based detection system. Calibration was first performed using 500 nm polystyrene nanoparticles to establish the relationship between particle concentration and optical extinction. Subsequently,

Indexed as

bacteriamicrofluidicsoptical sensingradiopharmaceuticals

Identifiers

PMID42195449
PMCPMC13209008

What OpenQuestion holds

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LicenceCC BY
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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.