Evidence map›Paper›PMID 27364357›Full record

ArticleScientific reports2016

Ultrasensitive multiplex optical quantification of bacteria in large samples of biofluids.

Nicolas Pazos-Perez, Elena Pazos, Carme Catala, Bernat Mir-Simon, Sara Gómez-de Pedro, Juan Sagales, Carlos Villanueva, Jordi Vila, Alex Soriano, F Javier García de Abajo and 1 more

Open access · goldAbstract read
In one paragraph

Article in Scientific reports, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed
3.8field-weighted citation impact, top 7% 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

19 citing papers in PubMed, 65 citations in OpenAlex.

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  13. Bacteria Detection: From Powerful SERS to Its Advanced Compatible Techniques.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2020
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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

11 authors at 5 institutions in 1 country.

Nicolas Pazos-PerezUniversitat Rovira i Virgili and Centro de Tecnología Química de Catalunya, Carrer de Marcel·lí Domingo s/n, 43007 Tarragona, Spain.
Elena PazosMedcom Advance S.A., Av. Roma, 08840 Barcelona, Spain.
Carme CatalaUniversitat Rovira i Virgili and Centro de Tecnología Química de Catalunya, Carrer de Marcel·lí Domingo s/n, 43007 Tarragona, Spain.
Bernat Mir-SimonMedcom Advance S.A., Av. Roma, 08840 Barcelona, Spain.
Sara Gómez-de PedroMedcom Advance S.A., Av. Roma, 08840 Barcelona, Spain.
Juan SagalesMedcom Advance S.A., Av. Roma, 08840 Barcelona, Spain.
Carlos VillanuevaMedcom Advance S.A., Av. Roma, 08840 Barcelona, Spain.
Jordi VilaDepartment of Clinical Microbiology, Hospital Clinic and School of Medicine, University of Barcelona, Barcelona, Spain.
Alex SorianoDepartment of Infectious Diseases, Hospital Clínic and School of Medicine, University of Barcelona, Barcelona, Spain.
F Javier García de AbajoICFO-Institut de Ciencies Fotoniques, The Barcelona Institute of Science and Technology, 08860 Castelldefels (Barcelona), Spain.
Ramon A Alvarez-PueblaUniversitat Rovira i Virgili and Centro de Tecnología Química de Catalunya, Carrer de Marcel·lí Domingo s/n, 43007 Tarragona, Spain.
Broadcom (Spain) · ESConsorci Institut D'Investigacions Biomediques August Pi I Sunyer · ESHospital Clínic de Barcelona · ESInstitució Catalana de Recerca i Estudis Avançats · ESUniversidad Rovira i Virgili · ES

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Efficient treatments in bacterial infections require the fast and accurate recognition of pathogens, with concentrations as low as one per milliliter in the case of septicemia. Detecting and quantifying bacteria in such low concentrations is challenging and typically demands cultures of large samples of blood (~1 milliliter) extending over 24-72 hours. This delay seriously compromises the health of patients. Here we demonstrate a fast microorganism optical detection system for the exhaustive identification and quantification of pathogens in volumes of biofluids with clinical relevance (~1 milliliter) in minutes. We drive each type of bacteria to accumulate antibody functionalized SERS-labelled silver nanoparticles. Particle aggregation on the bacteria membranes renders dense arrays of inter-particle gaps in which the Raman signal is exponentially amplified by several orders of magnitude relative to the dispersed particles. This enables a multiplex identification of the microorganisms through the molecule-specific spectral fingerprints.

Indexed as

Spectrum Analysis, RamanAntibodies, BacterialBacteriaBody FluidsEscherichia coliHumansMetal NanoparticlesMicrofluidicsMicroscopy, Electron, TransmissionPseudomonas aeruginosaSilverStreptococcusAntibodies, BacterialSilver

Identifiers

PMID27364357
PMCPMC4929498
OpenAlexW2465387921

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.