Evidence map›Paper›PMID 38907147›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2024

Fully Integrated Online Strategy for Highly Sensitive Proteome Profiling.

Yun Yang, Ruijun Tian

Abstract read
PubMed Publisher
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

2 authors.

Yun YangInternational Academy of Phronesis Medicine (Guang Dong), Guangzhou, China.
Ruijun TianDepartment of Chemistry, School of Science, Southern University of Science and Technology, Shenzhen, China. tianrj@sustech.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Low-input proteomics, which treats tens to hundreds of mammalian cells, is the gap between standard proteomics and single-cell proteomics. Low-input proteomics is widely applicable and needs special sample preparation methods to achieve deep proteome profiling. This chapter describes protocols for the preparation and application of an easy-to-use and scalable device for processing low-input samples. Protein preconcentration, impurity removal, reduction, alkylation, digestion, and desalting are fully integrated into this workflow, and the device can be directly connected to online nanoLC-MS to avoid sample transfer.

Indexed as

ProteomeProteomicsChromatography, LiquidHumansTandem Mass SpectrometryWorkflowProteomeLow-input proteomicsnanoLC-MSSample preparation

Identifiers

PMID38907147

What OpenQuestion holds

Textmetadata
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.