ReviewiScience2025
Profiling signaling mediators for cell-cell interactions and communications with microfluidics-based single-cell analysis tools.
Review in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- Review
- Decoding Cellular Heterogeneity with Microfluidic Single-Cell Secretion Analysis Tools.ACS omega · 2026Review
- CellTrap: an instrument-free microfluidic platform for cell-cell interactions at stochastically generated effector-to-target ratios.RSC advances · 2026Article
- Chip Calorimetry for Single-Cell Analysis: Advances, Challenges, and Opportunities.Sensors (Basel, Switzerland) · 2026Review
- Strength through diversity: how cancers thrive when clones cooperate.Molecular oncology · 2026Review
- Single-cell dissection of hepatocellular carcinoma immunity: from heterogeneous subtypes to precision therapeutics.Frontiers in immunology · 2026Review
- Microfluidic engineering of immune-competent organs-on-chips and their applications.Frontiers in immunology · 2026Review
- Article
- Droplet-based single-cell RNA sequencing: decoding cellular heterogeneity for breakthroughs in cancer, reproduction, and beyond.Journal of translational medicine · 2025Review
- Chip-Sized Lensless Holographic Microscope for Real-Time On-Chip Biological Sensing.Sensors (Basel, Switzerland) · 2025Article
- Article
- Article
- An Organ-on-a-Chip Modular Platform with Integrated Immunobiosensors for Monitoring the Extracellular Environment.Micromachines · 2025Article
- On the Effects of 3D Printed Mold Material, Curing Temperature, and Duration on Polydimethylsiloxane (PDMS) Curing Characteristics for Lab-on-a-Chip Applications.Micromachines · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cell-cell interactions and communication represent the fundamental cornerstone of cells' collaborative efforts in executing diverse biological processes. A profound understanding of how cells interface through various mediators is pivotal across a spectrum of biological systems. Recent strides in microfluidic technologies have significantly bolstered the precision and prowess in capturing and manipulating cells with exceptional spatial and temporal resolution. These advanced methodologies converge with multi-signal mediator detection systems, furnishing potent, high-throughput platforms for dissecting cell-cell interactions at the single-cell level. This approach empowers researchers to delve into intricate cellular dynamics with unprecedented accuracy and efficiency. Here, we present a critical evaluation of the latest advancements in microfluidics-driven techniques for detecting signal mediators involved in cell-cell interactions and communication at the single-cell level. We underscore notable biological applications that have benefited from these technologies and identify pressing challenges that must be addressed in future endeavors leveraging microfluidic tools for single-cell interaction studies.
Indexed as
Identifiers
What Socratic 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 Socratic graph.