Evidence map›Paper›PMID 38526726›Full record

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

Single-Cell Proteomics by Barcoded Phage-Displayed Screening via an Integrated Microfluidic Chip.

Yujiao Wang, Jing Zhao, Zhenwei Jiang, Yuan Ma, Rui Zhang

Abstract read
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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, top 91% 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

0 citing papers in PubMed, 0 citations in OpenAlex.

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

5 authors at 3 institutions in 1 country.

Yujiao WangState Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing, China.
Jing ZhaoState Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing, China.
Zhenwei JiangState Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing, China.
Yuan MaState Key Laboratory of Tribology in Advanced Equipment, Tsinghua University, Beijing, China. yuanma@tsinghua.edu.cn.
Rui ZhangDepartment of Clinical Laboratory, Beijing Chao-yang Hospital, Capital Medical University, Beijing, China. zr189169@163.com.
Tsinghua University · CNBeijing Chao-Yang Hospital · CNCapital Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Recent advancements in the profiling of proteomes at the single-cell level necessitate the development of quantitative and versatile platforms, particularly for analyzing rare cells like circulating tumor cells (CTCs). In this chapter, we present an integrated microfluidic chip that utilizes magnetic nanoparticles to capture single tumor cells with exceptional efficiency. This chip enables on-chip incubation and facilitates in situ analysis of cell-surface protein expression. By combining phage-based barcoding with next-generation sequencing technology, we successfully monitored changes in the expression of multiple surface markers induced by CTC adherence. This innovative platform holds significant potential for comprehensive screening of multiple surface antigens simultaneously in rare cells, offering single-cell resolution. Consequently, it will contribute valuable insights into biological heterogeneity and human disease.

Indexed as

Microfluidic Analytical TechniquesNeoplastic Cells, CirculatingCell Line, TumorCell SeparationHumansMicrofluidicsProteomicsBarcoded phage-displayed antibody screeningCirculating tumor cellsMicrofluidicsPhage-based profilingProtein expressionSingle cell

Identifiers

PMID38526726
OpenAlexW4393170886

What OpenQuestion holds

Textmetadata
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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.