ArticleAnalytical chemistry2021
BoxCarmax: A High-Selectivity Data-Independent Acquisition Mass Spectrometry Method for the Analysis of Protein Turnover and Complex Samples.
Article in Analytical chemistry, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 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
21 citing papers in PubMed, 41 citations in OpenAlex.
- Data-independent acquisition-based quantitative proteomics in plants.Frontiers in plant science · 2026Review
- Integrating endogenous TurboID and data-independent acquisition mass spectrometry for in vivo proximity labeling.The EMBO journal · 2026Article
- Multiplexed Data-Independent Acquisition-Based Proteomics Enabled by TMTpro Complementary Ions.Analytical chemistry · 2025Article
- Improving Proteomic Dynamic Range with Multiple Accumulation Precursor Mass Spectrometry.Journal of proteome research · 2025Article
- Expanding Targeted Instrumentation for Discovery Applications: Complement Reporter Ion Quantification with a Quadrupole-Ion Trap Instrument.Journal of proteome research · 2025Article
- A robust multiplex-DIA workflow profiles protein turnover regulations associated with cisplatin resistance and aneuploidy.Nature communications · 2025Article
- Article
- An Extensive Atlas of Proteome and Phosphoproteome Turnover Across Mouse Tissues and Brain Regions.bioRxiv : the preprint server for biology · 2024Article
- Instrumentation at the Leading Edge of Proteomics.Analytical chemistry · 2024Review
- EGFR targeting PhosTACs as a dual inhibitory approach reveals differential downstream signaling.Science advances · 2024Article
- An integrated workflow for quantitative analysis of the newly synthesized proteome.Nature communications · 2023Article
- Quantitative Time-Course Analysis of Osmotic and Salt Stress in Arabidopsis thaliana Using Short Gradient Multi-CV FAIMSpro BoxCar DIA.Molecular & cellular proteomics : MCP · 2023Article
- A basic phosphoproteomic-DIA workflow integrating precise quantification of phosphosites in systems biology.Biophysics reports · 2023Article
- Strategies for Increasing the Depth and Throughput of Protein Analysis by plexDIA.Journal of proteome research · 2023Review
- Toward a hypothesis-free understanding of how phosphorylation dynamically impacts protein turnover.Proteomics · 2023Article
- Increasing the throughput of sensitive proteomics by plexDIA.Nature biotechnology · 2023Article
- Coisolation of Peptide Pairs for Peptide Identification and MS/MS-Based Quantification.Analytical chemistry · 2022Article
- Proteotype coevolution and quantitative diversity across 11 mammalian species.Science advances · 2022Article
- Biomarkers in Neurodegenerative Diseases: Proteomics Spotlight on ALS and Parkinson's Disease.International journal of molecular sciences · 2022Review
- Advances in stable isotope labeling: dynamic labeling for spatial and temporal proteomic analysis.Molecular omics · 2022Review
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 at 1 institution in 1 country.
Funding
Abstract
The data-independent acquisition (DIA) performed in the latest high-resolution, high-speed mass spectrometers offers a powerful analytical tool for biological investigations. The DIA mass spectrometry (DIA-MS) combined with the isotopic labeling approach holds a particular promise for increasing the multiplexity of DIA-MS analysis, which could assist the relative protein quantification and the proteome-wide turnover profiling. However, the wide MS1 isolation windows employed in conventional DIA methods lead to a limited efficiency in identifying and quantifying isotope-labeled peptide pairs through peptide fragment ions. Here, we optimized a high-selectivity DIA-MS named BoxCarmax that supports the analysis of complex samples, such as those generated from Stable isotope labeling by amino acids in cell culture (SILAC) and pulse SILAC (pSILAC) experiments. BoxCarmax enables multiplexed acquisition at both MS1 and MS2 levels, through the integration of BoxCar and MSX features, as well as a gas-phase separation strategy. We found BoxCarmax significantly improved the quantitative accuracy in SILAC and pSILAC samples by mitigating the ratio suppression of isotope-peptide pairs. We further applied BoxCarmax to measure protein degradation regulation during serum starvation stress in cultured cells, revealing valuable biological insights. Our study offered an alternative and accurate approach for the MS analysis of protein turnover and complex 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.