Evidence map›Paper›PMID 38506436›Full record

ArticleCurrent protocols2024

Data-Independent Acquisition and Label-Free Quantification for Quantitative Proteomics Analysis of Human Cerebrospinal Fluid.

Karl A T Makepeace, Alexander W Rookyard, Lipi Das, Badri N Vardarajan, Jayanta K Chakrabarty, Anu Jain, Min Suk Kang, Emily G Werth, Dolly Reyes-Dumeyer, Marielba Zerlin-Esteves and 3 more

Open access · greenAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Current protocols, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.5field-weighted citation impact, top 44% 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

3 citing papers in PubMed, 2 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

13 authors at 3 institutions in 1 country.

Karl A T MakepeaceDepartment of Biological Sciences, Quantitative Proteomics and Metabolomics Center, Columbia University, New York, New York.ORCID https://orcid.org/0000-0001-9584-2750
Alexander W RookyardDepartment of Biological Sciences, Quantitative Proteomics and Metabolomics Center, Columbia University, New York, New York.
Lipi DasDepartment of Biological Sciences, Quantitative Proteomics and Metabolomics Center, Columbia University, New York, New York.
Badri N VardarajanTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Jayanta K ChakrabartyDepartment of Biological Sciences, Quantitative Proteomics and Metabolomics Center, Columbia University, New York, New York.
Anu JainDepartment of Biological Sciences, Quantitative Proteomics and Metabolomics Center, Columbia University, New York, New York.
Min Suk KangTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Emily G WerthDepartment of Biological Sciences, Quantitative Proteomics and Metabolomics Center, Columbia University, New York, New York.
Dolly Reyes-DumeyerTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Marielba Zerlin-EstevesThe Gertrude H. Sergievsky Center, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Lawrence S HonigTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Richard MayeuxTaub Institute for Research on Alzheimer's Disease and the Aging Brain, Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Lewis M BrownDepartment of Biological Sciences, Quantitative Proteomics and Metabolomics Center, Columbia University, New York, New York.ORCID https://orcid.org/0000-0002-1864-3077
Abterra Biosciences (United States) · USColumbia University · USNewYork–Presbyterian Hospital · US

Funding

Genetic Epidemiology and Multi-Omics Analyses in Familial and Sporadic Alzheimer's Disease Among Secular Caribbean Hispanics and Religious OrderR01AG067501 · NIA · COLUMBIA UNIVERSITY HEALTH SCIENCES · PI MAYEUX, RICHARD P, MILLER, GARY W · 2020 to 2024
$11.7M
NIA NIH HHS R01 AG067501NIH HHS R01 AG067501
6 · The paper itself

Abstract

This article presents a practical guide to mass spectrometry-based data-independent acquisition and label-free quantification for proteomics analysis applied to cerebrospinal fluid, offering a robust and scalable approach to probing the proteomic composition of the central nervous system. © 2024 Wiley Periodicals LLC. Basic Protocol 1: Cerebrospinal fluid sample collection and preparation for mass spectrometry analysis Basic Protocol 2: Mass spectrometry sample analysis with data-independent acquisition Support Protocol: Data-dependent mass spectrometry and spectral library construction Basic Protocol 3: Analysis of mass spectrometry data.

Indexed as

ProteomeProteomicsCerebrospinal Fluid ProteinsHumansMass SpectrometryCerebrospinal Fluid ProteinsProteomeAlzheimer's diseasecerebrospinal fluiddata-independent acquisitionlabel-free quantificationmass spectrometryproteomics

Identifiers

PMID38506436
PMCPMC11032743
OpenAlexW4393001921

What OpenQuestion holds

Textmetadata
LicenceTDM
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.