Phylogeny and Evolutionary History of the Amniote Egg

We review morphological features of the amniote egg and embryos in a comparative phylogenetic framework, including all major clades of extant vertebrates. We discuss 40 characters that are relevant for an analysis of the evolutionary history of the vertebrate egg. Special attention is given to the morphology of the cellular yolk sac, the eggshell, and extraembryonic membranes. Many features that are typically assigned to amniotes, such as a large yolk sac, delayed egg deposition, and terrestrial reproduction have evolved independently and convergently in numerous clades of vertebrates. We use phylogenetic character mapping and ancestral character state reconstruction as tools to recognize sequence, order, and patterns of morphological evolution and deduce a hypothesis of the evolutionary history of the amniote egg. Besides amnion and chorioallantois, amniotes ancestrally possess copulatory organs (secondarily reduced in most birds), internal fertilization, and delayed deposition of eggs that contain an embryo in the primitive streak or early somite stage. Except for the amnion, chorioallantois, and amniote type of eggshell, these features evolved convergently in almost all major clades of aquatic vertebrates possibly in response to selective factors such as egg predation, hostile environmental conditions for egg development, or to adjust hatching of young to favorable season. A functionally important feature of the amnion membrane is its myogenic contractility that moves the (early) embryo and prevents adhering of the growing embryo to extraembryonic materials. This function of the amnion membrane and the liquid-filled amnion cavity may have evolved under the requirements of delayed deposition of eggs that contain developing embryos. The chorioallantois is a temporary embryonic exchange organ that supports embryonic development. A possible evolutionary scenario is that the amniote egg presents an exaptation that paved the evolutionary pathway for reproduction on land. As shown by numerous examples from anamniotes, reproduction on land has occurred multiple times among vertebrates—the amniote egg presenting one “solution” that enabled the conquest of land for reproduction

EEG-based Graph Neural Network Classification of Alzheimer's Disease:An Empirical Evaluation of Functional Connectivity Methods

Alzheimer’s disease (AD) is the leading form of dementia worldwide. AD disrupts neuronal pathways and thus is commonly viewed as a network disorder. Many studies demonstrate the power of functional connectivity (FC) graph-based biomarkers for automated diagnosis of AD using electroencephalography (EEG). However, various FC measures are commonly utilised, as each aims to quantify a unique aspect of brain coupling. Graph neural networks (GNN) provide a powerful framework for learning on graphs. While a growing number of studies use GNN to classify EEG brain graphs, it is unclear which method should be utilised to estimate the brain graph. We use eight FC measures to estimate FC brain graphs from sensor-level EEG signals. GNN models are trained in order to compare the performance of the selected FC measures. Additionally, three baseline models based on literature are trained for comparison. We show that GNN models perform significantly better than the other baseline models. Moreover, using FC measures to estimate brain graphs improves the performance of GNN compared to models trained using a fixed graph based on the spatial distance between the EEG sensors. However, no FC measure performs consistently better than the other measures. The best GNN reaches 0.984 area under sensitivity-specificity curve (AUC) and 92% accuracy, whereas the best baseline model, a convolutional neural network, has 0.924 AUC and 84.7% accuracy

Cross-Frequency Multilayer Network Analysis with Bispectrum-based Functional Connectivity:A Study of Alzheimer's Disease

Alzheimer's disease (AD) is a neurodegenerative disorder known to affect functional connectivity (FC) across many brain regions. Linear FC measures have been applied to study the differences in AD by splitting neurophysiological signals, such as electroencephalography (EEG) recordings, into discrete frequency bands and analysing them in isolation from each other. We address this limitation by quantifying cross-frequency FC in addition to the traditional within-band approach. Cross-bispectrum, a higher-order spectral analysis approach, is used to measure the nonlinear FC and is compared with the cross-spectrum, which only measures the linear FC within bands. This work reports the reconstruction of a cross-frequency FC network where each frequency band is treated as a layer in a multilayer network with both inter- and intra-layer edges. Cross-bispectrum detects cross-frequency differences, mainly increased FC in AD cases in δ-θ coupling. Overall, increased strength of low-frequency coupling and decreased level of high-frequency coupling is observed in AD cases in comparison to healthy controls (HC). We demonstrate that a graph-theoretic analysis of cross-frequency brain networks is crucial to obtain a more detailed insight into their structure and function. Vulnerability analysis reveals that the integration and segregation properties of networks are enabled by different frequency couplings in AD networks compared to HCs. Finally, we use the reconstructed networks for classification. The extra cross-frequency coupling information can improve the classification performance significantly, suggesting an important role of cross-frequency FC. The results highlight the importance of studying nonlinearity and including cross-frequency FC in characterising AD.UnknownSupports Open Acces

Submersed Aquatic Vegetation Trends in Impounded and Backwater Habitat Types of Pool 13, Upper Mississippi River System: 1994-2000

Submersed aquatic vegetation (SAV) was sampled from 1994-2000 at fixed sires along established transects in Pool 13 of the Upper Mississippi River System (UMRS), as part of the Long Term Resource Monitoring Program (LTRMP). These data were used to quantify the annual percent frequency of occurrence and mean relative density of SAV within three backwaters (Brown\u27s Lake, Savanna Bay, and Spring Lake) and the impounded area of Pool 13. This investigation used Spearman rank correlation to assess the strength of bivariate relationships between measurements of SAV abundance and biological, physical, and hydrological variables at fixed water quality monitoring sites within vegetation monitoring areas. In backwater habitats, the percent frequency of occurrence and mean relative density of SAV exhibited significant negative correlations (P\u3c 0.05) with May-August median turbidity and mean velocity. Mean velocity and median turbidity were strongly correlated, which suggested that water inputs from channel habitats caused observed differences in water clarity, as well as subsequent differences in the percent frequency of occurrence and mean relative density of SAV. In the impounded area of Pool 13, the percent frequency of occurrence and mean relative density of SAV increased during the period of study and was strongly correlated with tooted floating leaved vegetation (RFV). None of the other physical or hydrological variables analyzed for the impounded area demonstrated significant correlations. The cause for the lack of significant relationships between independent variables and measurements of SAV abundance in the impounded area of Pool 13 are uncertain, bur the differences may be due to previously established SAV beds creating favorable near-shore habitat with increased water clarity and reduced velocities when compared to main channel habitat

Characterising Alzheimer's Disease with EEG-based Energy Landscape Analysis

Alzheimer's disease (AD) is one of the most common neurodegenerative diseases, with around 50 million patients worldwide. Accessible and non-invasive methods of diagnosing and characterising AD are therefore urgently required. Electroencephalography (EEG) fulfils these criteria and is often used when studying AD. Several features derived from EEG were shown to predict AD with high accuracy, e.g. signal complexity and synchronisation. However, the dynamics of how the brain transitions between stable states have not been properly studied in the case of AD and EEG data. Energy landscape analysis is a method that can be used to quantify these dynamics. This work presents the first application of this method to both AD and EEG. Energy landscape assigns energy value to each possible state, i.e. pattern of activations across brain regions. The energy is inversely proportional to the probability of occurrence. By studying the features of energy landscapes of 20 AD patients and 20 healthy age-matched counterparts, significant differences were found. The dynamics of AD patients' brain networks were shown to be more constrained - with more local minima, less variation in basin size, and smaller basins. We show that energy landscapes can predict AD with high accuracy, performing significantly better than baseline models.Comment: 11 pages, 7 figure

Using remote substituents to control solution structure and anion binding in lanthanide complexes.

A study of the anion-binding properties of three structurally related lanthanide complexes, which all contain chemically identical anion-binding motifs, has revealed dramatic differences in their anion affinity. These arise as a consequence of changes in the substitution pattern on the periphery of the molecule, at a substantial distance from the binding pocket. Herein, we explore these remote substituent effects and explain the observed behaviour through discussion of the way in which remote substituents can influence and control the global structure of a molecule through their demands upon conformational space. Peripheral modifications to a binuclear lanthanide motif derived from α,α′-bis(DO3 Ayl)-m-xylene are shown to result in dramatic changes to the binding constant for isophthalate. In this system, the parent compound displays considerable conformational flexibility, yet can be assumed to bind to isophthalate through a well-defined conformer. Addition of steric bulk remote from the binding site restricts conformational mobility, giving rise to an increase in binding constant on entropic grounds as long as the ideal binding conformation is not excluded from the available range of conformers

Serial Recall Order and Semantic Features of Category Fluency Words to Study Semantic Memory in Normal Ageing

Copyright © 2021 De Marco, Blackburn and Venneri. Background: Category Fluency Test (CFT) is a common measure of semantic memory (SM). Test performance, however, is also influenced by other cognitive functions. We here propose a scoring procedure that quantifies the correlation between the serial recall order (SRO) of words retrieved during the CFT and a number of linguistic features, to obtain purer SM measures. To put this methodology to the test, we addressed a proof-of-concept hypothesis whereby, in alignment with the literature, older adults would show better SM. Methods: Ninety participants (45 aged 18–21 years; 45 aged 70–81 years) with normal neurological and cognitive functioning completed a 1-min CFT. SRO was scored as an ordinal variable incrementing by one unit for each valid entry. Each word was also scored for 16 additional linguistic features. Participant-specific normalised correlation coefficients were calculated between SRO and each feature and were analysed with group comparisons and graph theory. Results: Younger adults showed more negative correlations between SRO and “valence” (a feature of words pleasantness). This was driven by the first five words generated. When analysed with graph theory, SRO had significantly higher degree and lower betweenness centrality among older adults. Conclusion: In older adults, SM relies significantly less on pleasantness of entries typically retrieved without semantic control. Moreover, graph-theory metrics indicated better optimised links between SRO and linguistic features in this group. These findings are aligned with the principle whereby SM processes tend to solidify with ageing. Although additional work is needed in support of an SRO-based item-level scoring procedure of CFT performance, these initial findings suggest that this methodology could be of help in characterising SM in a purer form.Neurocare (United Kingdom), Grant agreement No. 181924 to MDM and AV; Alzheimer’s Research United Kingdom, Pump Priming Grant scheme to MDM