Evidence map›Paper›PMID 42529381›Full record

ArticleChemical & biomedical imaging2026

Fast, Streamlined

Wenjie Zhang, Yanqing Cai, Mason Hong Cheung, Ying Xu, Angela Ruohao Wu, Yi Liao

Abstract read
In one paragraph

Article in Chemical & biomedical imaging, 2026. 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

6 authors.

Wenjie ZhangDivision of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R. 999077, China.ORCID https://orcid.org/0009-0005-2351-2142
Yanqing CaiDivision of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R. 999077, China.ORCID https://orcid.org/0009-0005-9769-4639
Mason Hong CheungDivision of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R. 999077, China.ORCID https://orcid.org/0009-0002-3858-848X
Ying XuDivision of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R. 999077, China.ORCID https://orcid.org/0000-0002-7880-5066
Angela Ruohao WuDivision of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R. 999077, China.ORCID https://orcid.org/0000-0002-3531-4830
Yi LiaoDivision of Life Science, The Hong Kong University of Science and Technology, Clear Water Bay, Kowloon, Hong Kong S.A.R. 999077, China.ORCID https://orcid.org/0000-0002-0414-439X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Temporal dynamics, such as cell-cycle oscillations, transcriptional bursting, and the regulated assembly and disassembly of phase-separated condensates, constitute an important layer of regulation in biology. Yet, existing technologies, including DNA sequencing, plate readers, and fluorescence microscopy, face a fundamental trade-off between temporal resolution, single-cell and subcellular information, and experimental throughput. This trade-off not only fragments our understanding of fundamental cellular processes but also impedes large-scale screening for dynamic phenotypes. Efforts to mitigate such limitations are beginning to emerge. One promising approach combines live-cell time-lapse imaging of pooled bacterial libraries in microfluidic chips with sequential fluorescence

Indexed as

biological dynamicshigh-throughput screeningin situ genotypingmother machine microfluidicsseqFISHsingle-cell bacteriology

Identifiers

PMID42529381
PMCPMC13417533

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.