Communicative and Integrative Biology最新文献

Based on a systematic literature search, I recently reviewed learning in the phylum Cnidaria, animals possessing a nerve net as a nervous system but no centralized brain. I found abundant evidence of non-associative learning, both habituation and sensitization, but only sparse evidence of associative learning. Only one well-controlled study on classical conditioning in sea anemones provided firm evidence, and no studies firmly supported operant conditioning in Cnidaria, although several provided suggestive evidence. More research on associative learning in this phylum is needed.

Cell Competition emerged in Drosophila as an unexpected phenomenon, when confronted clones of fit vs unfit cells genetically induced. During the last decade, it has been shown that this mechanism is physiologically active in Drosophila and higher organisms. In Drosophila, Flower (Fwe) eliminates unfit cells during development, regeneration and disease states. Furthermore, studies suggest that Fwe signaling is required to eliminate accumulated unfit cells during adulthood extending Drosophila lifespan. Indeed, ahuizotl (azot) mutants accumulate unfit cells during adulthood and after physical insults in the brain and other epithelial tissues, showing a decrease in organismal lifespan. On the contrary, flies carrying three functional copies of the gene, unfit cell culling seems to be more efficient and show an increase in lifespan. During aging, Azot is required for the elimination of unfit cells, however, the specific organs modulating organismal lifespan by Azot remain unknown. Here we found a potential connection between gut-specific Azot expression and lifespan which may uncover a more widespread organ-specific mechanism modulating organismal survival.

Glutamate receptor-like (GLR) 3.3 and 3.6 proteins are required for mediating wound-induced leaf-to-leaf electrical signaling. In the previous study, we found that the carboxy-terminal tail of GLR3.3 contains key residues that are indispensable for its action in electrical signaling. In the present work, we generated plants that expressed the truncated C-tail fraction of GLR3.3. To our expectation, the truncated C-tail itself was not functional in propagating leaf-to-leaf signals. However, we identified that the C-tail-mVENUS fusion proteins had dual localization patterns in sieve elements and companion cells. In companion cells, the fusion proteins overlapped largely with the nucleus. We speculated that a possible nuclear localization signal is present in the C-tail of GLR3.3, paralleling the C-tails of the ionotropic glutamate receptors in animal cells. Our further findings on the C-tail of GLR3.3 open up new possibilities for the regulatory roles of the C-tails to GLR proteins.

Fruits, like other parts of the plant, appear to have a rich electrical activity that may contain information. Here, we present data showing differences in the electrome complexity of tomato fruits through ripening and discuss possible physiological processes involved. The complexity of the signals, measured through approximate entropy, varied along the fruit ripening process. When analyzing the fruits individually, a decrease in entropy values was observed when they entered the breaker stage, followed by a tendency to increase again when they entered the light red stage. Consequently, the data obtained showed a decrease in signal complexity in the breaker stage, probably due to some physiological process that ends up predominating to the detriment of others. This result may be linked to processes involved in ripening, such as climacteric. Electrophysiological studies in the reproductive stage of the plant are still scarce, and research in this direction is of paramount importance to understand whether the electrical signals observed can transmit information from reproductive structures to other modules of plants. This work opens the possibility of studying the relationship between the electrical activity and fruit ripening through the analysis of approximate entropy. More studies are necessary to understand whether there is a correlation or a cause-response relationship in the phenomena involved. There is a myriad of possibilities for the applicability of this knowledge to different areas, from understanding the cognitive processes of plants to achieving more accurate and sustainable agriculture.

Infants' first-person experiences are crucial to early cognitive and neural development. To a vast extent, these early experiences involve play, which in infancy takes the form of object exploration. While at the behavioral level infant play has been studied both using specific tasks and in naturalistic scenarios, the neural correlates of object exploration have largely been studied in highly controlled task settings. These neuroimaging studies did not tap into the complexities of everyday play and what makes object exploration so important for development. Here, we review selected infant neuroimaging studies, spanning from typical, highly controlled screen-based studies on object perception to more naturalistic designs and argue for the importance of studying the neural correlates of key behaviors such as object exploration and language comprehension in naturalistic settings. We suggest that the advances in technology and analytic approaches allow measuring the infant brain at play with the use of functional near-infrared spectroscopy (fNIRS). Naturalistic fNIRS studies offer a new and exciting avenue to studying infant neurocognitive development in a way that will draw us away from our laboratory constructs and into an infant's everyday experiences that support their development.

In this study, we advance a robust methodology for identifying specific intelligence-related proteins across phyla. Our approach exploits a support vector machine-based classifier capable of predicting intelligence-related proteins based on a pool of meaningful protein features. For the sake of illustration of our proposed general method, we develop a novel computational two-layer predictor, Intell_Pred, to predict query sequences (proteins or transcripts) as intelligence-related or non-intelligence-related proteins or transcripts, subsequently classifying the former sequences into learning and memory-related classes. Based on a five-fold cross-validation and independent blind test, Intell_Pred obtained an average accuracy of 87.48 and 88.89, respectively. Our findings revealed that a score >0.75 (during prediction by Intell_Pred) is a well-grounded choice for predicting intelligence-related candidate proteins in most organisms across biological kingdoms. In particular, we assessed seismonastic movements and associate learning in plants and evaluated the proteins involved using Intell_Pred. Proteins related to seismonastic movement and associate learning showed high percentages of similarities with intelligence-related proteins. Our findings lead us to believe that Intell_Pred can help identify the intelligence-related proteins and their classes using a given protein/transcript sequence.

A person trapped in a building engulfed in a raging fire, a person dealing with severe chronic disease, people dealing with a virus pandemic, and people fighting in a protracted war may appear dissimilar but are fundamentally in a similar situation and their behaviors follow a predictable and similar pattern. In this paper, the behaviors of rational people dealing with a significant persistent unpleasant, or dangerous stimulus that is inescapable are elucidated. The unique modulatory effects of stimulus persistence on human behavior as well as the role of means and interest are discussed.

The theory of island biogeography predicts that island size is a key predictor of community species richness. Islands can include any habitat surrounded environments that are inhospitable to the resident species. In arid environments, nurse trees act as islands in an environment uninhabitable to many plant species, and the size of the canopy controls the size of the understory plant community. We predicted that plant species richness will be affected by the area of the habitat and decrease with habitat isolation. We sampled the adult and seedling plant communities at canopy center, canopy edge, and outside canopy microhabitats. We found that species richness in both adult and seedling communities increases with increasing island area. However, richness in seedling communities was greater than in adult communities, and this effect was greatest at the canopy center microhabitat. Competition has been demonstrated to be more important in controlling species distributions near the canopy center, and stress is more important near the canopy edge. Thus, our results suggest that neutral forces, biotic interactions, and abiotic filtering act together to control species richness in these island communities.

Psilocybin fungi, aka "magic" mushrooms, are well known for inducing colorful and visionary states of mind. Such psychoactive properties and the ease of cultivating their basidiocarps within low-tech setups make psilocybin fungi promising pharmacological tools for mental health applications. Understanding of the intrinsic electrical patterns occurring during the mycelial growth can be utilized for better monitoring the physiological states and needs of these species. In this study we aimed to shed light on this matter by characterizing the extra-cellular electrical potential of two popular species of psilocybin fungi: Psilocybe tampanensis and P. cubensis. As in previous experiments with other common edible mushrooms, the undisturbed fungi have shown to generate electric potential spikes and trains of spiking activity. This short analysis provides a proof of intrinsic electrical communication in psilocybin fungi, and further establishes these fungi as a valuable tool for studying fungal electro-physiology.

Microorganisms are present in the universe and they play role in beneficial and harmful to human life, society, and environments. Plant microbiome is a broad term in which microbes are present in the rhizo, phyllo, or endophytic region and play several beneficial and harmful roles with the plant. To know of these microorganisms, it is essential to be able to isolate purification and identify them quickly under laboratory conditions. So, to improve the microbial study, several tools and techniques such as microscopy, rRNA, or rDNA sequencing, fingerprinting, probing, clone libraries, chips, and metagenomics have been developed. The major benefits of these techniques are the identification of microbial community through direct analysis as well as it can apply in situ. Without tools and techniques, we cannot understand the roles of microbiomes. This review explains the tools and their roles in the understanding of microbiomes and their ecological diversity in environments.