Evidence map›Paper›PMID 39622899›Full record

ArticleScientific reports2024

Nanomechanical detection to empower robust monitoring of sepsis and microbial adaptive immune system-mediated proinflammatory disease.

Kessarin Thanapirom, Walid Al-Akkad, Aylin Pelut, Zahra Sadouki, Jemima B Finkel, Stefan Nardi-Hiebl, Wieland Vogt, Benjamin Vojnar, Hinnerk Wulf, Leopold Eberhart and 5 more

Abstract read
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In one paragraph

Article in Scientific reports, 2024. 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

15 authors.

Kessarin ThanapiromDivision of Medicine, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Walid Al-AkkadDivision of Medicine, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Aylin PelutDivision of Medicine, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Zahra SadoukiUCL Centre for Clinical Microbiology, Division of Infection and Immunity, University College London, Gower Street, WC1E 6BT, London, United Kingdom.
Jemima B FinkelDivision of Medicine, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Stefan Nardi-HieblDepartment of Anaesthesia and Intensive Care, University Hospital of the Philipps-University of Marburg Baldingerstrasse, 35043, Marburg, Germany.
Wieland VogtMedical Innovations and Management, Steinbeis University, Ernst-August-Strasse 15, 12489, Berlin, Germany.
Benjamin VojnarDepartment of Anaesthesia and Intensive Care, University Hospital of the Philipps-University of Marburg Baldingerstrasse, 35043, Marburg, Germany.
Hinnerk WulfDepartment of Anaesthesia and Intensive Care, University Hospital of the Philipps-University of Marburg Baldingerstrasse, 35043, Marburg, Germany.
Leopold EberhartDepartment of Anaesthesia and Intensive Care, University Hospital of the Philipps-University of Marburg Baldingerstrasse, 35043, Marburg, Germany.
Timothy D McHughUCL Centre for Clinical Microbiology, Division of Infection and Immunity, University College London, Gower Street, WC1E 6BT, London, United Kingdom.
Krista RomboutsDivision of Medicine, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Massimo PinzaniDivision of Medicine, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Emmanouil TsochatzisDivision of Medicine, University College London, Gower Street, London, WC1E 6BT, United Kingdom.
Joseph W NdieyiraDivision of Medicine, University College London, Gower Street, London, WC1E 6BT, United Kingdom. j.ndieyira@ucl.ac.uk.

Funding

Devices & Diagnostics TIN Pilot Data Scheme 178973Royal Free Charity 563691Wellcome Trust
6 · The paper itself

Abstract

The correlation between circulating microbes and sepsis as well as proinflammatory diseases is increasingly gaining recognition. However, the detection of microbes' cell-free DNA (cfDNA), which exist at concentrations of a billion times lower than blood proteins, poses a significant challenge for early disease detection. Here, we present Nano mechanics combined with highly sensitive readout sequences to address the challenges of ultralow counts of disease biomarkers, thus enabling robust quantitative monitoring of chronic medical conditions at different stages of human disease progression. To showcase the effectiveness of our approach, we employ fragments of cfDNA and human cell secretory proteins as models with predictive capabilities for human diseases. Notably, our method reveals a reliable representation over an impressive three to four orders of magnitude in the detection limit and dynamic range, surpassing commercially available quantitative polymerase chain reaction (qPCR) commonly used in routine clinical practice. This concept underpins a highly sensitive and selective medical device designed for the early detection of circulating microbes in patients undergoing intensive cancer therapy. This will help pinpoint individuals at risk of complications, including damage to the intestinal barrier and development of neutropenic fever/Sirsa/Sepsis. Moreover, this approach introduces new avenues for stratifying antibiotic prophylaxis in proinflammatory diseases.

Indexed as

Cell-Free Nucleic AcidsSepsisAdaptive ImmunityBiomarkersHumansInflammationNanotechnologyBiomarkersCell-Free Nucleic Acids

Identifiers

PMID39622899
PMCPMC11612153

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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.