ReviewNature protocols2023
High-quality and robust protein quantification in large clinical/pharmaceutical cohorts with IonStar proteomics investigation.
Review in Nature protocols, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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.
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.
Who cites it
16 citing papers in PubMed, 24 citations in OpenAlex.
- L-fucose-dependent biofilm formation byBiofilm · 2026Article
- Article
- L-Fucose-Dependent Biofilm Formation bybioRxiv : the preprint server for biology · 2026Article
- Article
- Navigating the data processing for cytometry-based single-cell proteomics.Nature protocols · 2026Review
- Isolation of Cytoskeleton and Cytoskeleton-Bound Polysome, and Identification of Cytoskeletal Proteins from a Grain Legume.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Multicompartment Quantitative Proteomics Revealing Potential Mechanisms Underlying the Treatment Effects of Mesenchymal-Derived Extracellular Vesicles in a Monkey Model of Cortical Injury.Journal of proteome research · 2025Article
- An Antibody Cocktail-Based Immunoaffinity-LC-MS Method Enabled Ultra-Sensitive and Robust Quantification of Circulating Proinsulin Proteoforms and C-Peptide.Analytical chemistry · 2025Article
- Anticancer Quinolinol Small Molecules Target Multiple Pathways to Promote Cell Death and Eliminate Melanoma Cells Resistant to BRAF Inhibitors.Molecules (Basel, Switzerland) · 2025Article
- Persistent Fibrosis and Left Ventricular Chamber Stiffening Despite Cessation of Repetitive Pressure Overload in Swine.JACC. Basic to translational science · 2025Article
- The Complement Factor H (Y402H) risk polymorphism for age-related macular degeneration affects metabolism and response to oxidative stress in the retinal pigment epithelium.Free radical biology & medicine · 2024Article
- RESC14 and RESC8 cooperate to mediate RESC function and dynamics during trypanosome RNA editing.Nucleic acids research · 2024Article
- Systems Pharmacodynamic Model of Combined Gemcitabine and Trabectedin in Pancreatic Cancer Cells. Part I: Effects on Signal Transduction Pathways Related to Tumor GrowthJournal of pharmaceutical sciences · 2024Article
- Therapeutic TNF Inhibitors Exhibit Differential Levels of Efficacy in Accelerating Cutaneous Wound Healing.JID innovations : skin science from molecules to population health · 2024Article
- Systems Pharmacodynamic Model of Combined Gemcitabine and Trabectedin in Pancreatic Cancer Cells. Part II: Cell Cycle, DNA Damage Response, and Apoptosis Pathways.Journal of pharmaceutical sciences · 2024Article
- Tuning plant phenotypes by precise, graded downregulation of gene expression.Nature biotechnology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 5 institutions in 2 countries.
Funding
Abstract
Robust, reliable quantification of large sample cohorts is often essential for meaningful clinical or pharmaceutical proteomics investigations, but it is technically challenging. When analyzing very large numbers of samples, isotope labeling approaches may suffer from substantial batch effects, and even with label-free methods, it becomes evident that low-abundance proteins are not reliably measured owing to unsufficient reproducibility for quantification. The MS1-based quantitative proteomics pipeline IonStar was designed to address these challenges. IonStar is a label-free approach that takes advantage of the high sensitivity/selectivity attainable by ultrahigh-resolution (UHR)-MS1 acquisition (e.g., 120-240k full width at half maximum at m/z = 200) which is now widely available on ultrahigh-field Orbitrap instruments. By selectively and accurately procuring quantitative features of peptides within precisely defined, very narrow m/z windows corresponding to the UHR-MS1 resolution, the method minimizes co-eluted interferences and substantially enhances signal-to-noise ratio of low-abundance species by decreasing noise level. This feature results in high sensitivity, selectivity, accuracy and precision for quantification of low-abundance proteins, as well as fewer missing data and fewer false positives. This protocol also emphasizes the importance of well-controlled, robust experimental procedures to achieve high-quality quantification across a large cohort. It includes a surfactant cocktail-aided sample preparation procedure that achieves high/reproducible protein/peptide recoveries among many samples, and a trapping nano-liquid chromatography-mass spectrometry strategy for sensitive and reproducible acquisition of UHR-MS1 peptide signal robustly across a large cohort. Data processing and quality evaluation are illustrated using an example dataset ( http://proteomecentral.proteomexchange.org ), and example results from pharmaceutical project and one clinical project (patients with acute respiratory distress syndrome) are shown. The complete IonStar pipeline takes ~1-2 weeks for a sample cohort containing ~50-100 samples.
Indexed as
Identifiers
What OpenQuestion holds
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.