ReviewAdvanced biology2026
How Epitranscriptomic Machinery Senses Environmental Cues.
Review in Advanced 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
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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.
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Environmental fluctuations remodel RNA modification landscapes, yet the routes that connect cue detection to writer-eraser-reader control remain dispersed across disciplines. Here, we consolidate upstream mechanisms capable of driving epitranscriptomic change and organize them by response speed. At the fastest proximal level, catalytic output can be modulated through shifts in substrate and cofactor availability, redox and ionic state, temperature, and direct chemical or metal interference with enzyme active sites, although transcriptome-wide RNA readouts may appear later. Over minutes to hours, cue-responsive signaling can reach the machinery through post-translational modification, partner switching, subcellular trafficking, and stress-induced condensates that may gate access to modified transcripts. Across hours to days, regulator abundance and specificity are reshaped by transcriptional programs, translational control, and protein quality-control pathways, enabling adaptation and, in some contexts, persistence. We propose a kinetics-to-sensors approach for interpreting time-resolved epitranscriptomic datasets and prioritizing perturbations that discriminate among candidate upstream inputs. We also outline conceptual gaps and experimental practices needed to establish causal cue-to-mark chains.
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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.