ReviewMikrochimica acta2025
Transforming cytokine diagnostics: AI, multiplexing, and point-of-care biosensing technologies.
Review in Mikrochimica acta, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Electrochemical tyrosine-click bioconjugation enables multiplexed cytokine sensing and immunoprofiling in native serum.Nature communications · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cytokines are central regulators of immune responses and have emerged as key biomarkers in diverse pathological conditions, including infections, autoimmune disorders, and cancer. Conventional laboratory methods for cytokine detection, while accurate, often lack the speed, portability, and multiplexing capacity required for timely clinical decision-making. Recent advances in biosensor technology-particularly at the point-of-care (POC)-are reshaping this landscape by enabling rapid, decentralized, and sensitive detection of cytokine panels in complex biological samples. AI-enabled multiplex POC platforms now achieve limits of detection as low as 0.01-100 pg/mL, with dynamic ranges spanning 3-4 orders of magnitude, using 1-50 µL of sample and delivering results within 5-30 min. Compared with centralized single-plex workflows, these systems provide faster, lower-volume, and more clinically actionable testing. Artificial intelligence further strengthens performance by providing calibrated predictive outputs, uncertainty estimates, and drift monitoring. This review highlights the convergence of multiplexed biosensing strategies with artificial intelligence (AI) to enhance the analytical performance, interpretability, and clinical utility of cytokine diagnostics. We first discuss the evolution from traditional platforms to portable and miniaturized systems, and then summarize emerging review literature addressing cytokine biosensing in contexts such as sepsis, metabolic disorders, and systemic inflammation. Next, we examine experimental studies demonstrating POC-compatible platforms for multiplexed cytokine detection, and finally focus on next-generation biosensors that integrate machine learning (ML) algorithms-including convolutional neural networks (CNNs) and decision-tree models-for autonomous signal processing and decision support. Despite challenges in validation, hardware integration, and explainability, these technologies hold transformative potential for real-time immune monitoring, precision medicine, and global health applications.
Indexed as
Identifiers
41175281What 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.