Evidence map›Paper›PMID 26331920›Full record

ArticleRapid communications in mass spectrometry : RCM2015

SANIST: a rapid mass spectrometric SACI/ESI data acquisition and elaboration platform for verifying potential candidate biomarkers.

Adriana Albini, Daniela Briga, Matteo Conti, Antonino Bruno, Daniela Farioli, Sara Canali, Ilaria Sogno, Gioacchino D'Ambrosio, Paolo Consonni, Douglas M Noonan

Registry-linked trialOpen access · hybridAbstract read
In one paragraph

Article in Rapid communications in mass spectrometry : RCM, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT04735289 (Evaluation of Dietary Habits, Metabolome, Immune Profile and Microbiota in Patients With Bone Sarcoma), which is not on this map. Cited by 9 papers.

0numbers the graph read from it
0cells of the map it votes in
9citing papers in PubMed
0.5field-weighted citation impact, top 36% 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.

NCT04735289 unknown statusnot on this mapstarted 2021, after this paper: background citation

Evaluation of Dietary Habits, Metabolome, Immune Profile and Microbiota in Patients With Bone Sarcoma

Typeobservational_patient_registrySponsorIstituto Ortopedico RizzoliRan2021 to 2024Enrolled810ConditionsOsteosarcoma, Ewing SarcomaArmsEPIC-COS Food Frequency Questionnaire diet Evaluation, Metabolome, Microbiota, Lymphocytes subpopulations
3 · Its place in the literature

Who cites it

9 citing papers in PubMed, 16 citations in OpenAlex.

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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

10 authors at 4 institutions in 1 country.

Adriana AlbiniIRCCS - Arcispedale Santa Maria Nuova in Reggio Emilia, Italy.
Daniela BrigaScientific and Technological Pole, IRCCS MultiMedica, Milan, Italy.
Matteo ContiSant'Orsola Malpighi Hospital, Bologna, Italy.
Antonino BrunoScientific and Technological Pole, IRCCS MultiMedica, Milan, Italy.
Daniela FarioliIRCCS - Arcispedale Santa Maria Nuova in Reggio Emilia, Italy.
Sara CanaliScientific and Technological Pole, IRCCS MultiMedica, Milan, Italy.
Ilaria SognoScientific and Technological Pole, IRCCS MultiMedica, Milan, Italy.
Gioacchino D'AmbrosioScientific and Technological Pole, IRCCS MultiMedica, Milan, Italy.
Paolo ConsonniScientific and Technological Pole, IRCCS MultiMedica, Milan, Italy.
Douglas M NoonanScientific and Technological Pole, IRCCS MultiMedica, Milan, Italy.
Istituti di Ricovero e Cura a Carattere Scientifico · ITMultiMedica · ITOspedale Santa Maria · ITPoliclinico S.Orsola-Malpighi · IT

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

rationaleSurface-Activated Chemical Ionization/Electrospray Ionization mass spectrometry (SACI/ESI-MS) is a technique with high sensitivity and low noise that allows accurate biomarker discovery studies. We developed a dedicated SACI/ESI software, named SANIST, for both biomarker fingerprint data acquisition and as a diagnostic tool, using prostate cancer (PCa) as the disease of interest.

methodsLiquid chromatography (LC)/SACI/ESI-MS technology was employed to detect a potential biomarker panel for PCa disease prediction. Serum from patients with histologically confirmed or negative prostate biopsies for PCa was employed. The biomarker data (m/z or Thompson value, retention time and extraction mass chromatogram peak area) were stored in an ascii database. SANIST software allowed identification of potential biomarkers. A Bayesian scoring algorithm developed in house allowed sample separation based on comparison with samples in the database.

resultsBiomarker candidates from the carnitine family were detected at significantly lower levels in patients showing histologically confirmed PCa. Using these biomarkers, the SANIST scoring algorithm allowed separation of patients with PCa from biopsy negative subjects with high accuracy and sensitivity.

conclusionsSANIST was able to rapidly identify and perform a preliminary evaluation of the potential diagnostic efficiency of potential biomarkers for PCa.

Indexed as

AlgorithmsBayes TheoremBiomarkersComputational BiologyHumansMaleMiddle AgedProstatic NeoplasmsReproducibility of ResultsSensitivity and SpecificitySpectrometry, Mass, Electrospray IonizationBiomarkers

Identifiers

PMID26331920
PMCPMC5049612
OpenAlexW2125941078

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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.