ArticlePRX life
How the Immune System Learns.
Article in PRX life. 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
3 authors.
Funding
Abstract
The adaptive immune system can mount pathogen-specific responses against a vast world of evolving pathogens (antigens). The humoral immune system is a part of adaptive immunity. It has the remarkable ability to learn about an antigen after exposure to it through a mutation-selection evolutionary process, resulting in more potent responses than those that emerge initially. Recent studies have revealed that upon reexposure to antigens, feedback regulation mediated by past responses steers the evolutionary learning algorithm to generate new responses. This feature enables the immune system to learn to generalize responses to target unseen variants of the original pathogen upon "training" with a limited number of samples. We summarize these new findings and suggest new questions that emerge from them. This is the right time to address these questions by bringing together statistical physics, machine learning, immunology, and evolutionary biology.
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.