Diverse invertebrate species have been used for studies of learning and comparative cognition. Although we have gained invaluable information from this, in this study we argue that our approach to comparative learning research is rather deficient. Generally invertebrate learning research has focused mainly on arthropods, and most of that within the Hymenoptera and Diptera. Any true comparative analysis of the distribution of comparative cognitive abilities across phyla is hampered by this bias, and more fundamentally by a reporting bias toward positive results. To understand the limits of learning and cognition for a species, knowing what animals cannot do is at least as important as reporting what they can. Finally, much more effort needs to be focused on the neurobiological analysis of different types of learning to truly understand the differences and similarities of learning types. In this review, we first give a brief overview of the various forms of learning in invertebrates. We also suggest areas where further study is needed for a more comparative understanding of learning. Finally, using what is known of learning in honeybees and the well-studied honeybee brain, we present a model of how various complex forms of learning may be accounted for with the same neural circuitry required for so-called simple learning types. At the neurobiological level, different learning phenomena are unlikely to be independent, and without considering this it is very difficult to correctly interpret the phylogenetic distribution of learning and cognitive abilities. WIREs Cogn Sci 2013, 4:561-582. doi: 10.1002/wcs.1248 For further resources related to this article, please visit the WIREs website.
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Front Biosci (Landmark Ed)
November 2024
Department of General Surgery, The First Affiliated Hospital of Anhui Medical University, 230022 Hefei, Anhui, China.
Background: Aneuploidy is crucial yet under-explored in cancer pathogenesis. Specifically, the involvement of brain expressed X-linked gene 4 () in microtubule formation has been identified as a potential aneuploidy mechanism. Nevertheless, 's comprehensive impact on aneuploidy incidence across different cancer types remains unexplored.
View Article and Find Full Text PDFJ Integr Neurosci
December 2024
Department of Computer Science and Engineering, Shaoxing University, 312000 Shaoxing, Zhejiang, China.
Background: Motor imagery (MI) plays an important role in brain-computer interfaces, especially in evoking event-related desynchronization and synchronization (ERD/S) rhythms in electroencephalogram (EEG) signals. However, the procedure for performing a MI task for a single subject is subjective, making it difficult to determine the actual situation of an individual's MI task and resulting in significant individual EEG response variations during motion cognitive decoding.
Methods: To explore this issue, we designed three visual stimuli (arrow, human, and robot), each of which was used to present three MI tasks (left arm, right arm, and feet), and evaluated differences in brain response in terms of ERD/S rhythms.
JACS Au
December 2024
Key Laboratory of Molecular Enzymology and Engineering of Ministry of Education, School of Life Sciences, Jilin University, Changchun 130023, P. R. China.
In this study, we developed a machine-learning-aided protein design strategy for engineering hemoglobin (VHb) as carbene transferase. A Natural Language Processing (NLP) model was used for the first time to construct an algorithm (EESP, enzyme enantioselectivity score predictor) and predict the enantioselectivity of VHb. We identified critical amino acid residue sites by molecular docking and established a simplified mutation library by site-saturated mutagenesis.
View Article and Find Full Text PDFJ Inflamm Res
December 2024
Department of Nephrology, Blood Purification Research Center, the First Affiliated Hospital, Fujian Medical University, Fuzhou, People's Republic of China.
Objective: A comprehensive bioinformatics analysis was conducted to investigate potential new diagnostic biomarkers and immune infiltration characteristics associated with tubulointerstitial injury in lupus nephritis (LN), and to examine possible correlations between key genes and infiltrating immune cells.
Methods: The GSE32591, GSE113342, and GSE200306 datasets were downloaded from the Gene Expression Omnibus database and differentially expressed genes (DEGs) were identified in the pooled dataset. Support vector machine-recursive feature elimination analysis and the least absolute shrinkage and selection operator regression model were used to screen for possible markers, and the compositional patterns of the 22 types of immune cell fractions in LN were determined using CIBERSORT.
J Inflamm Res
December 2024
Department of Dermatology, China-Japan Friendship Hospital, National Center for Integrative Medicine, Beijing, 100029, People's Republic of China.
Background: Psoriasis represents a persistent, immune-driven inflammatory condition affecting the skin, characterized by a lack of well-established biologic treatments without adverse events. Consequently, the identification of novel targets and therapeutic agents remains a pressing priority in the field of psoriasis research.
Methods: We collected single-cell RNA sequencing (scRNA-seq) datasets and inferred T cell differentiation trajectories through pseudotime analysis.
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