Evidence map›Paper›PMID 40283301›Full record

ReviewMicromachines2025

Advances in Microfluidic Single-Cell RNA Sequencing and Spatial Transcriptomics.

Yueqiu Sun, Nianzuo Yu, Junhu Zhang, Bai Yang

Abstract readReview
In one paragraph

Review in Micromachines, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Cell-Based Immuno-Biosensors Using Microfluidics.Sensors (Basel, Switzerland) · 2026
    Review
  4. Review
  5. Review
  6. Article
  7. Review
  8. Review
  9. Review
  10. Review
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

4 authors.

Yueqiu SunState Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130000, China.
Nianzuo YuState Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130000, China.
Junhu ZhangState Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130000, China.ORCID 0000-0001-9100-6608
Bai YangState Key Laboratory of Supramolecular Structure and Materials, College of Chemistry, Jilin University, Changchun 130000, China.

Funding

Jilin Province Science and Technology Department 202401648ZYTSNational Natural Science Foundation of China 22275071, 32401229
6 · The paper itself

Abstract

The development of micro- and nano-fabrication technologies has greatly advanced single-cell and spatial omics technologies. With the advantages of integration and compartmentalization, microfluidic chips are capable of generating high-throughput parallel reaction systems for single-cell screening and analysis. As omics technologies improve, microfluidic chips can now integrate promising transcriptomics technologies, providing new insights from molecular characterization for tissue gene expression profiles and further revealing the static and even dynamic processes of tissues in homeostasis and disease. Here, we survey the current landscape of microfluidic methods in the field of single-cell and spatial multi-omics, as well as assessing their relative advantages and limitations. We highlight how microfluidics has been adapted and improved to provide new insights into multi-omics over the past decade. Last, we emphasize the contributions of microfluidic-based omics methods in development, neuroscience, and disease mechanisms, as well as further revealing some perspectives for technological advances in translational and clinical medicine.

Indexed as

microfluidicssingle cellsingle-cell RNA sequencing (scRNA-seq)spatial transcriptome

Identifiers

PMID40283301
PMCPMC12029715

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.