Evidence map›Paper›PMID 40617925›Full record

ArticleScientific reports2025

Intracellular doppler spectroscopy of live tissue sentinels for a fast in-vitro bacterial infection assay.

Dawith Lim, Zhen Hua, Fernanda da Cunha, John Turek, Michael Ladisch, David Nolte

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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. 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

6 authors.

Dawith LimDepartment of Physics, Purdue University, West Lafayette, IN, 47906, USA. lim185@purdue.edu.
Zhen HuaNational Eye Institute, National Institutes of Health, Bethesda, MD, 20892, USA.
Fernanda da CunhaDepartment of Agricultural & Biological Engineering, Purdue University, West Lafayette, IN, 47906, USA.
John TurekDepartment of Basic Medical Sciences, Purdue University, West Lafayette, IN, 47906, USA.
Michael LadischDepartment of Agricultural & Biological Engineering, Purdue University, West Lafayette, IN, 47906, USA.
David NolteDepartment of Physics, Purdue University, West Lafayette, IN, 47906, USA.

Funding

National Science Foundation NSF-2200186
6 · The paper itself

Abstract

Living organisms are frequently used as sentinels to monitor changes in the environment, and organoids can serve a similar function as in vitro sentinels detecting microbiological processes. One such process of great interest is pathogenic infection, which causes alterations in the cellular dynamics of the sentinels. Doppler light scattering is well suited to measure such changes, as it is sensitive to the intracellular dynamics of the organoids even when the microbe density is too dilute to detect directly. In this paper, we present measurements of the endogenous changes of intracellular dynamics of DLD organoids (microclusters) in response to bacterial infection, detected using a long-coherence form of biodynamic imaging (BDI), a dynamic-contrast digital holography technique that captures the Doppler shifts encoded in the dynamic speckles. With a stable common-path digital holography system and using small in-vitro tissue microclusters, clinically relevant inoculum doses as low as 100 cfu/mL cause detectable changes in intracellular Doppler spectra within hours of infection and several hours before the proliferating bacteria population causes direct light scattering. Because it can measure effects for small bacterial populations, the method shows promise as a fast diagnostic tool to detect the presence of bacteria in patient fluid samples faster than traditional methods.

Indexed as

Bacterial InfectionsOrganoidsHolographyHumans

Identifiers

PMID40617925
PMCPMC12228712

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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.