ArticlebioRxiv : the preprint server for biology2026
Kinetic Modeling of Target-Amplification-Free CRISPR-Cas-Based Autocatalysis Reactions.
Article in bioRxiv : the preprint server for biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
CRISPR-Cas-based diagnostics utilize the Cas enzyme's trans-cleavage activity to generate signal and have become popular platforms for sensitive nucleic acid detection. Recently, autocatalytic systems have been demonstrated to improve the time to response and sensitivity in some cases. However, mechanistic description of these assays is limited and optimization relies on simple trial-and-error. In this work, we present the first comprehensive kinetic model that integrates all major biochemical processes involved in these assays, including cleavage reactions, nucleic acid equilibrium kinetics, inhibition of trans-cleavage by single-stranded DNA, and degradation of single-stranded reaction components. We discuss the biochemical foundations and implementation of the ordinary differential equation model, which is built for adaptation to different reaction schemes. We use the full model to investigate the role of nucleic acid stability in assay performance for a typical nucleic acid design and show that our model demonstrates inhibition effects consistent with experimental data. We describe the reaction behavior, derive a simplified analytical model and compare its performance to the full analytical model. Finally, we demonstrate tools developed for rapid
Identifiers
What OpenQuestion 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 OpenQuestion graph.