ArticleMethods in molecular biology (Clifton, N.J.)2023
Automated Sample Preparation for Mass Spectrometry-Based Clinical Proteomics.
Article in Methods in molecular biology (Clifton, N.J.), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Low-Input Proteomics Protocols for Laser-Captured FFPE Samples with Orbitrap Astral DIA-MS.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Clinical Proteomics Applied to Food Allergy.Advances in experimental medicine and biology · 2026Review
- PEPPI-SP3: A Gel-Based High-Resolution Sample Preparation Workflow for In-Depth Top-Down Analysis of Intact Proteoforms by Mass Spectrometry.Methods in molecular biology (Clifton, N.J.) · 2026Article
- Deep Proteome Profiling of Primary Skin Fibroblasts.Methods in molecular biology (Clifton, N.J.) · 2025Article
- A Fast-Tracking Sample Preparation Protocol for Proteomics of Formalin-Fixed Paraffin-Embedded Tumor Tissues.Methods in molecular biology (Clifton, N.J.) · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Mass spectrometry (MS)-based proteomics is a rapidly maturing discipline, thus gaining momentum for routine molecular profiling of clinical specimens to improve disease classification, diagnostics, and therapy development. Yet, hurdles need to be overcome to enhance reproducibility in preanalytical sample processing, especially in large, quantity-limited sample cohorts. Therefore, automated sonication and single-pot solid-phase-enhanced sample preparation (autoSP3) was developed as a streamlined workflow that integrates all tasks from tissue lysis and protein extraction, protein cleanup, and proteolysis. It enables the concurrent processing of 96 clinical samples of any type (fresh-frozen or FFPE tissue, liquid biopsies, or cells) on an automated liquid handling platform, which can be directly interfaced to LC-MS for proteome analysis of clinical specimens with high sensitivity, high reproducibility, and short turn-around times.
Indexed as
Identifiers
37665461What 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.