Evolution of phenotypic fluctuation under host-parasite interactions

Quantum Biology and the Potential Role of Entanglement and Tunneling in Non-Targeted Effects of Ionizing Radiation: A Review and Proposed Model

It is well established that cells, tissues, and organisms exposed to low doses of ionizing radiation can induce effects in non-irradiated neighbors (non-targeted effects or NTE), but the mechanisms remain unclear. This is especially true of the initial steps leading to the release of signaling molecules contained in exosomes. Voltage-gated ion channels, photon emissions, and calcium fluxes are all involved but the precise sequence of events is not yet known. We identified what may be a quantum entanglement type of effect and this prompted us to consider whether aspects of quantum biology such as tunneling and entanglement may underlie the initial events leading to NTE. We review the field where it may be relevant to ionizing radiation processes. These include NTE, low-dose hyper-radiosensitivity, hormesis, and the adaptive response. Finally, we present a possible quantum biological-based model for NTE.

From Parasitized to Healthy-Looking Ants (Hymenoptera: Formicidae): Morphological Reconstruction Using Algorithmic Processing

Background: Parasites cause predictable alternative phenotypes of host individuals. Investigating these parasitogenic phenotypes may be essential in cases where parasitism is common or taxa is described based on a parasitized individual. Ignoring them could lead to erroneous conclusions in biodiversity-focused research, taxonomy, evolution, and ecology. However, to date, integrating alternative phenotypes into a set of wild-type individuals in morphometric analysis poses extraordinary challenges to experts. This paper presents an approach for reconstructing the putative healthy morphology of parasitized ants using algorithmic processing. Our concept enables the integration of alternative parasitogenic phenotypes in morphometric analyses. Methods: We tested the applicability of our strategy in a large pool of Cestoda-infected and healthy individuals of three Temnothorax ant species (T. nylanderi, T. sordidulus, and T. unifasciatus). We assessed the stability and convergence of morphological changes caused by parasitism across species. We used an artificial neural network-based multiclass classifier model to predict species based on morphological trait values and the presence of parasite infection. Results: Infection causes predictable morphological changes in each species, although these changes proved to be species-specific. Therefore, integrating alternative parasitogenic phenotypes in morphometric analyses can be achieved at the species level, and a prior species hypothesis is required. Conclusion: Despite the above limitation, the concept is appropriate. Beyond parasitogenic phenotypes, our approach can also integrate morphometric data of an array of alternative phenotypes (subcastes in social insects, alternative morphs in polyphenic species, and alternative sexes in sexually dimorphic species) whose integrability had not been resolved before.