Bayesian consolidation of retinal micro(nano)plastic hypothesis: From existential confirmation to spatial–phenotypic inference

Recent empirical confirmation of polymeric micro- and nanoplastics (MNPs) in human retinal tissue marks a decisive epistemic shift-from theoretical plausibility to verified biological occurrence. Five months before this discovery, a Bayesian hypothesis framework published in BioSystems proposed that MNPs may exist in the human retina and could plausibly explain certain imaging anomalies, despite the absence of direct evidence. The present work extends that framework by formalizing how definitive empirical detection collapses existential uncertainty and advances the Bayesian model toward its next inferential stage. Using the posterior probability (P = 0.023) derived in the original model as a new prior, strong empirical evidence (P (E | H) = 0.99; P (E | ￢H) = 0.01 or 0.001) yields posteriors between 0.7 and 0.96-representing more than a thirty-fold increase in belief. Sensitivity analysis demonstrates that above a 90 % detection rate, posterior belief asymptotically approaches unity, signifying epistemic closure of the existential hypothesis (H: retinal MNPs exist). This quantitative update does not re-analyze laboratory data but illustrates the formal process by which definitive evidence transforms a probabilistic conjecture into an empirically anchored premise. The resulting posterior of H becomes the prior for a second-stage hypothesis (H): retinal MNP distribution and polymer profile correlate with specific imaging or pathological phenotypes. Framed within an iterative Bayesian logic, this transition exemplifies how probabilistic reasoning can integrate theoretical prediction and empirical validation-converting a speculative biological proposition into a structured platform for future mechanistic exploration.