ArticlemSystems2024
Preliminary evidence for chaotic signatures in host-microbe interactions.
Article in mSystems, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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
8 citing papers in PubMed.
- Impact of Climate Change on Cyanobacteria-Cyanophage Interactions and Their Role in Cyanobacterial Blooms in Freshwater Lakes.Global change biology · 2026Article
- Microbial transformation of secondary bile acids: roles in gut ecology and autoimmune diseases.Frontiers in immunology · 2026Review
- The dynamics ofmSphere · 2025Article
- Is pathogen prediction possible?PLoS biology · 2025Article
- The Dynamics ofbioRxiv : the preprint server for biology · 2025Article
- Unpacking the sepsis controversy.Trauma surgery & acute care open · 2025Review
- From resonance to chaos by modulating spatiotemporal patterns through a synthetic optogenetic oscillator.Nature communications · 2024Article
- Review
Corrections and comments
- Update of
Authors and funding
7 authors.
Funding
Abstract
Host-microbe interactions constitute dynamical systems that can be represented by mathematical formulations that determine their dynamic nature and are categorized as deterministic, stochastic, or chaotic. Knowing the type of dynamical interaction is essential for understanding the system under study. Very little experimental work has been done to determine the dynamical characteristics of host-microbe interactions, and its study poses significant challenges. The most straightforward experimental outcome involves an observation of time to death upon infection. However, in measuring this outcome, the internal parameters and the dynamics of each particular host-microbe interaction in a population of interactions are hidden from the experimentalist. To investigate whether a time-to-death (time-to-event) data set provides adequate information for searching for chaotic signatures, we first determined our ability to detect chaos in simulated data sets of time-to-event measurements and successfully distinguished the time-to-event distribution of a chaotic process from a comparable stochastic one. To do so, we introduced an inversion measure to test for a chaotic signature in time-to-event distributions. Next, we searched for chaos in the time-to-death of
Indexed as
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.