Optimization of avian perching manoeuvres.

Perching at speed is among the most demanding flight behaviours that birds perform1,2 and is beyond the capability of most autonomous vehicles. Smaller birds may touch down by hovering3-8, but larger birds typically swoop up to perch1,2-presumably because the adverse scaling of their power margin prohibits hovering9 and because swooping upwards transfers kinetic to potential energy before collision1,2,10. Perching demands precise control of velocity and pose11-14, particularly in larger birds for which scale effects make collisions especially hazardous6,15. However, whereas cruising behaviours such as migration and commuting typically minimize the cost of transport or time of flight16, the optimization of such unsteady flight manoeuvres remains largely unexplored7,17. Here we show that the swooping trajectories of perching Harris' hawks (Parabuteo unicinctus) minimize neither time nor energy alone, but rather minimize the distance flown after stalling. By combining motion capture data from 1,576 flights with flight dynamics modelling, we find that the birds' choice of where to transition from powered dive to unpowered climb minimizes the distance over which high lift coefficients are required. Time and energy are therefore invested to provide the control authority needed to glide safely to the perch, rather than being minimized directly as in technical implementations of autonomous perching under nonlinear feedback control12 and deep reinforcement learning18,19. Naive birds learn this behaviour on the fly, so our findings suggest a heuristic principle that could guide reinforcement learning of autonomous perching.

The sphingosine 1-phosphate analogue, FTY720, modulates the lipidomic signature of the mouse hippocampus.

The small-molecule drug, FTY720 (fingolimod), is a synthetic sphingosine 1-phosphate (S1P) analogue currently used to treat relapsing-remitting multiple sclerosis in both adults and children. FTY720 can cross the blood-brain barrier (BBB) and, over time, accumulate in lipid-rich areas of the central nervous system (CNS) by incorporating into phospholipid membranes. FTY720 has been shown to enhance cell membrane fluidity, which can modulate the functions of glial cells and neuronal populations involved in regulating behaviour. Moreover, direct modulation of S1P receptor-mediated lipid signalling by FTY720 can impact homeostatic CNS physiology, including neurotransmitter release probability, the biophysical properties of synaptic membranes, ion channel and transmembrane receptor kinetics, and synaptic plasticity mechanisms. The aim of this study was to investigate how chronic FTY720 treatment alters the lipid composition of CNS tissue in adolescent mice at a key stage of brain maturation. We focused on the hippocampus, a brain region known to be important for learning, memory, and the processing of sensory and emotional stimuli. Using mass spectrometry-based lipidomics, we discovered that FTY720 increases the fatty acid chain length of hydroxy-phosphatidylcholine (PCOH) lipids in the mouse hippocampus. It also decreases PCOH monounsaturated fatty acids (MUFAs) and increases PCOH polyunsaturated fatty acids (PUFAs). A total of 99 lipid species were up-regulated in the mouse hippocampus following 3 weeks of oral FTY720 exposure, whereas only 3 lipid species were down-regulated. FTY720 also modulated anxiety-like behaviours in young mice but did not affect spatial learning or memory formation. Our study presents a comprehensive overview of the lipid classes and lipid species that are altered in the hippocampus following chronic FTY720 exposure and provides novel insight into cellular and molecular mechanisms that may underlie the therapeutic or adverse effects of FTY720 in the central nervous system.

Machine learning in small sample neuroimaging studies: Novel measures for schizophrenia analysis.

Novel features derived from imaging and artificial intelligence systems are commonly coupled to construct computer-aided diagnosis (CAD) systems that are intended as clinical support tools or for investigation of complex biological patterns. This study used sulcal patterns from structural images of the brain as the basis for classifying patients with schizophrenia from unaffected controls. Statistical, machine learning and deep learning techniques were sequentially applied as a demonstration of how a CAD system might be comprehensively evaluated in the absence of prior empirical work or extant literature to guide development, and the availability of only small sample datasets. Sulcal features of the entire cerebral cortex were derived from 58 schizophrenia patients and 56 healthy controls. No similar CAD systems has been reported that uses sulcal features from the entire cortex. We considered all the stages in a CAD system workflow: preprocessing, feature selection and extraction, and classification. The explainable AI techniques Local Interpretable Model-agnostic Explanations and SHapley Additive exPlanations were applied to detect the relevance of features to classification. At each stage, alternatives were compared in terms of their performance in the context of a small sample. Differentiating sulcal patterns were located in temporal and precentral areas, as well as the collateral fissure. We also verified the benefits of applying dimensionality reduction techniques and validation methods, such as resubstitution with upper bound correction, to optimize performance.

Biophysical characterization and design of a minimal version of the Hoechst RNA aptamer.

RNA aptamers are oligonucleotides, selected through Systematic Evolution of Ligands by EXponential Enrichment (SELEX), that can bind to specific target molecules with high affinity. One such molecule is the RNA aptamer that binds to a blue-fluorescent Hoechst dye that was modified with bulky t-Bu groups to prevent non-specific binding to DNA. This aptamer has potential for biosensor applications; however, limited information is available regarding its conformation, molecular interactions with the ligand, and binding mechanism. The study presented here aims to biophysically characterize the Hoechst RNA aptamer when complexed with the t-Bu Hoechst dye and to further optimize the RNA sequence by designing and synthesizing new sequence variants. Each variant aptamer-t-Bu Hoechst complex was evaluated through a combination of fluorescence emission, native polyacrylamide gel electrophoresis, fluorescence titration, and isothermal titration calorimetry experiments. The results were used to design a minimal version of the aptamer consisting of only 21 nucleotides. The performed study also describes a more efficient method for synthesizing the t-Bu Hoechst dye derivative. Understanding the biophysical properties of the t-Bu Hoechst dye-RNA complex lays the foundation for nuclear magnetic resonance spectroscopy studies and its potential development as a building block for an aptamer-based biosensor that can be used in medical, environmental or laboratory settings.

Educational attainment, structural brain reserve and Alzheimer's disease: a Mendelian randomization analysis.

Higher educational attainment is observationally associated with lower risk of Alzheimer's disease. However, the biological mechanisms underpinning this association remain unclear. The protective effect of education on Alzheimer's disease may be mediated via increased brain reserve. We used two-sample Mendelian randomization to explore putative causal relationships between educational attainment, structural brain reserve as proxied by MRI phenotypes and Alzheimer's disease. Summary statistics were obtained from genome-wide association studies of educational attainment (n = 1 131 881), late-onset Alzheimer's disease (35 274 cases, 59 163 controls) and 15 measures of grey or white matter macro- or micro-structure derived from structural or diffusion MRI (nmax = 33 211). We conducted univariable Mendelian randomization analyses to investigate bidirectional associations between (i) educational attainment and Alzheimer's disease; (ii) educational attainment and imaging-derived phenotypes; and (iii) imaging-derived phenotypes and Alzheimer's disease. Multivariable Mendelian randomization was used to assess whether brain structure phenotypes mediated the effect of education on Alzheimer's disease risk. Genetically proxied educational attainment was inversely associated with Alzheimer's disease (odds ratio per standard deviation increase in genetically predicted years of schooling = 0.70, 95% confidence interval 0.60, 0.80). There were positive associations between genetically predicted educational attainment and four cortical metrics (standard deviation units change in imaging phenotype per one standard deviation increase in genetically predicted years of schooling): surface area 0.30 (95% confidence interval 0.20, 0.40); volume 0.29 (95% confidence interval 0.20, 0.37); intrinsic curvature 0.18 (95% confidence interval 0.11, 0.25); local gyrification index 0.21 (95% confidence interval 0.11, 0.31)]; and inverse associations with cortical intracellular volume fraction [-0.09 (95% confidence interval -0.15, -0.03)] and white matter hyperintensities volume [-0.14 (95% confidence interval -0.23, -0.05)]. Genetically proxied levels of surface area, cortical volume and intrinsic curvature were positively associated with educational attainment [standard deviation units change in years of schooling per one standard deviation increase in respective genetically predicted imaging phenotype: 0.13 (95% confidence interval 0.10, 0.16); 0.15 (95% confidence interval 0.11, 0.19) and 0.12 (95% confidence interval 0.04, 0.19)]. We found no evidence of associations between genetically predicted imaging-derived phenotypes and Alzheimer's disease. The inverse association of genetically predicted educational attainment with Alzheimer's disease did not attenuate after adjusting for imaging-derived phenotypes in multivariable analyses. Our results provide support for a protective causal effect of educational attainment on Alzheimer's disease risk, as well as potential bidirectional causal relationships between education and brain macro- and micro-structure. However, we did not find evidence that these structural markers affect risk of Alzheimer's disease. The protective effect of education on Alzheimer's disease may be mediated via other measures of brain reserve not included in the present study, or by alternative mechanisms.

The persistent threat of emerging plant disease pandemics to global food security.

Plant disease outbreaks are increasing and threaten food security for the vulnerable in many areas of the world. Now a global human pandemic is threatening the health of millions on our planet. A stable, nutritious food supply will be needed to lift people out of poverty and improve health outcomes. Plant diseases, both endemic and recently emerging, are spreading and exacerbated by climate change, transmission with global food trade networks, pathogen spillover, and evolution of new pathogen lineages. In order to tackle these grand challenges, a new set of tools that include disease surveillance and improved detection technologies including pathogen sensors and predictive modeling and data analytics are needed to prevent future outbreaks. Herein, we describe an integrated research agenda that could help mitigate future plant disease pandemics.

Correction: Planthopper bugs use a fast, cyclic elastic recoil mechanism for effective vibrational communication at small body size.

[This corrects the article DOI: 10.1371/journal.pbio.3000155.].

Gap selection and steering during obstacle avoidance in pigeons.

The ability of birds to fly through cluttered environments has inspired biologists interested in understanding its underlying mechanisms, and engineers interested in applying its underpinning principles. To analyse this problem empirically, we break it down into two distinct, but related, questions: How do birds select which gaps to aim for? And how do they steer through them? We answered these questions using a combined experimental and modelling approach, in which we released pigeons (Columbia livia domestica) inside a large hall with an open exit separated from the release point by a curtain creating two vertical gaps - one of which was obstructed by an obstacle. We tracked the birds using a high-speed motion capture system, and found that their gap choice seemed to be biased by their intrinsic handedness, rather than determined by extrinsic cues such as the size of the gap or its alignment with the destination. We modelled the pigeons' steering behaviour algorithmically by simulating their flight trajectories under a set of six candidate guidance laws, including those used previously to model target-oriented flight behaviours in birds. We found that their flights were best modelled by delayed proportional navigation commanding turning in proportion to the angular rate of the line-of-sight from the pigeon to the midpoint of the gap. Our results are consistent with this being a two-phase behaviour, in which the pigeon heads forward from the release point before steering towards the midpoint of whichever gap it chooses to aim for under closed-loop guidance. Our findings have implications for the sensorimotor mechanisms that underlie clutter negotiation in birds, uniting this with other kinds of target-oriented behaviours including aerial pursuit.

Lessons from natural flight for aviation: then, now and tomorrow.

Powered flight was once a capability limited only to animals, but by identifying useful attributes of animal flight and building on these with technological advances, engineers have pushed the frontiers of flight beyond our predecessors' wildest imaginations. Yet, there remain many key characteristics of biological flight that elude current aircraft design, motivating a careful re-analysis of what we have learned from animals already, and how this has been revealed experimentally, as well as a specific focus on identifying what remains unknown. Here, we review the literature to identify key contributions that began in biology and have since been translated into aeronautical devices or capabilities. We identify central areas for future research and highlight the importance of maintaining an open line of two-way communication between biologists and engineers. Such interdisciplinary, bio-informed analyses continue to push forward the frontiers of aeronautics and experimental biology alike.

Action selection in early stages of psychosis: an active inference approach.

BACKGROUND: To interact successfully with their environment, humans need to build a model to make sense of noisy and ambiguous inputs. An inaccurate model, as suggested to be the case for people with psychosis, disturbs optimal action selection. Recent computational models, such as active inference, have emphasized the importance of action selection, treating it as a key part of the inferential process. Based on an active inference framework, we sought to evaluate previous knowledge and belief precision in an action-based task, given that alterations in these parameters have been linked to the development of psychotic symptoms. We further sought to determine whether task performance and modelling parameters would be suitable for classification of patients and controls. METHODS: Twenty-three individuals with an at-risk mental state, 26 patients with first-episode psychosis and 31 controls completed a probabilistic task in which action choice (go/no-go) was dissociated from outcome valence (gain or loss). We evaluated group differences in performance and active inference model parameters and performed receiver operating characteristic (ROC) analyses to assess group classification. RESULTS: We found reduced overall performance in patients with psychosis. Active inference modelling revealed that patients showed increased forgetting, reduced confidence in policy selection and less optimal general choice behaviour, with poorer action-state associations. Importantly, ROC analysis showed fair-to-good classification performance for all groups, when combining modelling parameters and performance measures. LIMITATIONS: The sample size is moderate. CONCLUSION: Active inference modelling of this task provides further explanation for dysfunctional mechanisms underlying decision-making in psychosis and may be relevant for future research on the development of biomarkers for early identification of psychosis.

Through Hawks' Eyes: Synthetically Reconstructing the Visual Field of a Bird in Flight.

Birds of prey rely on vision to execute flight manoeuvres that are key to their survival, such as intercepting fast-moving targets or navigating through clutter. A better understanding of the role played by vision during these manoeuvres is not only relevant within the field of animal behaviour, but could also have applications for autonomous drones. In this paper, we present a novel method that uses computer vision tools to analyse the role of active vision in bird flight, and demonstrate its use to answer behavioural questions. Combining motion capture data from Harris' hawks with a hybrid 3D model of the environment, we render RGB images, semantic maps, depth information and optic flow outputs that characterise the visual experience of the bird in flight. In contrast with previous approaches, our method allows us to consider different camera models and alternative gaze strategies for the purposes of hypothesis testing, allows us to consider visual input over the complete visual field of the bird, and is not limited by the technical specifications and performance of a head-mounted camera light enough to attach to a bird's head in flight. We present pilot data from three sample flights: a pursuit flight, in which a hawk intercepts a moving target, and two obstacle avoidance flights. With this approach, we provide a reproducible method that facilitates the collection of large volumes of data across many individuals, opening up new avenues for data-driven models of animal behaviour. Supplementary Information: The online version contains supplementary material available at 10.1007/s11263-022-01733-2.

Reversal learning in those with early psychosis features contingency-dependent changes in loss response and learning.

INTRODUCTION: People with psychotic disorders commonly feature broad decision-making impairments that impact their functional outcomes. Specific associative/reinforcement learning problems have been demonstrated in persistent psychosis. But these phenotypes may differ in early psychosis, suggesting that aspects of cognition decline over time. METHODS: The present proof-of-concept study examined goal-directed action and reversal learning in controls and those with early psychosis. RESULTS: Equivalent performance was observed between groups during outcome-specific devaluation, and reversal learning at an 80:20 contingency (reward probability for high:low targets). But when the low target reward probability was increased (80:40) those with early psychosis altered their response to loss, whereas controls did not. Computational modelling confirmed that in early psychosis there was a change in punishment learning that increased the chance of staying with the same stimulus after a loss, multiple trials into the future. In early psychosis, the magnitude of this response was greatest in those with higher IQ and lower clinical severity scores. CONCLUSIONS: We show preliminary evidence that those with early psychosis present with a phenotype that includes altered responding to loss and hyper-adaptability in response to outcome changes. This may reflect a compensatory response to overcome the milieu of corticostriatal changes associated with psychotic disorders.

Exploring the role of halogen bonding in iodonium ylides: insights into unexpected reactivity and reaction control.

Halogen bonding is commonly found with iodine-containing molecules, and it arises when Lewis bases interact with iodine's σ-holes. Halogen bonding and σ-holes have been encountered in numerous monovalent and hypervalent iodine-containing compounds, and in 2022 σ-holes were computationally confirmed and quantified in the iodonium ylide subset of hypervalent iodine compounds. In light of this new discovery, this article provides an overview of the reactions of iodonium ylides in which halogen bonding has been invoked. Herein, we summarize key discoveries and mechanistic proposals from the early iodonium ylide literature that invoked halogen bonding-type mechanisms, as well as recent reports of reactions between iodonium ylides and Lewis basic nucleophiles in which halogen bonding has been specifically invoked. The reactions discussed herein are organized to enable the reader to build an understanding of how halogen bonding might impact yield and chemoselectivity outcomes in reactions of iodonium ylides. Areas of focus include nucleophile σ-hole selectivity, and how ylide structural modifications and intramolecular halogen bonding (e.g., the ortho-effect) can improve ylide stability or solubility, and alter reaction outcomes.

Impairments in goal-directed action and reversal learning in a proportion of individuals with psychosis.

Cognitive impairment in psychosis is one of the strongest predictors of functional decline. Problems with decision-making processes, such as goal-directed action and reversal learning, can reflect cortico-striatal dysfunction. The heterogenous symptoms and neurobiology observed in those with psychosis suggests that specific cognitive phenotypes may reflect differing causative mechanisms. As such, decision-making performance could identify subgroups of individuals with more severe cortico-striatal dysfunction and help to predict their functional decline. The present work evaluated the relationship between goal-directed action, reversal learning, and symptom profiles in those with psychosis. We assessed decision-making processes in healthy controls (N = 34) and those with persistent psychosis (N = 45), subclassifying subjects based on intact/impaired goal-directed action. Compared with healthy controls (<20%), a large proportion (58%) of those with persistent psychosis displayed impaired goal-directed action, predicting poor serial reversal learning performance. Computational approaches indicated that those with impaired goal-directed action had a decreased capacity to rapidly update their prior beliefs in the face of changing contingencies. Impaired decision-making also was associated with reduced levels of grandiosity and increased problems with abstract thinking. These findings suggest that prominent decision-making deficits, indicative of cortico-striatal dysfunction, are present in a large proportion of people with persistent psychosis. Moreover, these impairments would have significant functional implications in terms of planning and abstract thinking.

First Direct Detection Constraints on Planck-Scale Mass Dark Matter with Multiple-Scatter Signatures Using the DEAP-3600 Detector.

Dark matter with Planck-scale mass (≃10^{19} GeV/c^{2}) arises in well-motivated theories and could be produced by several cosmological mechanisms. A search for multiscatter signals from supermassive dark matter was performed with a blind analysis of data collected over a 813 d live time with DEAP-3600, a 3.3 t single-phase liquid argon-based detector at SNOLAB. No candidate signals were observed, leading to the first direct detection constraints on Planck-scale mass dark matter. Leading limits constrain dark matter masses between 8.3×10^{6} and 1.2×10^{19} GeV/c^{2}, and ^{40}Ar-scattering cross sections between 1.0×10^{-23} and 2.4×10^{-18} cm^{2}. These results are interpreted as constraints on composite dark matter models with two different nucleon-to-nuclear cross section scalings.

σ-Holes in Iodonium Ylides: Halogen-Bond Activation of Carboxylic Acids, Phenols and Thiophenols May Enable Their X-H Insertion Reactions.

The first systematic evaluation of the electrostatic potential energy maps of iodonium ylides was conducted. We determined that they possess two σ-holes of differing electron deficiencies, with the more electropositive σ-hole located opposite the dative I-C bond to the ß-dicarbonyl motif, and the lesser electropositive σ-hole located opposite the iodoarene C-I bond. We also conducted the first systematic evaluation of carboxylic acids, phenols and thiophenols in the O/S-alkylation reaction of iodonium ylides. While carboxylic acids and thiophenols were found to be generally viable, only phenols possessing electron-withdrawing substituents were effective. This high-yielding and highly chemoselective reaction is believed to involve halogen-bond activation of heteroatoms, and nicely complements existing diazo-based methods for alkylation of acidic functional groups.

Grey and white matter microstructure is associated with polygenic risk for schizophrenia.

Recent discovery of approximately 270 common genetic variants associated with schizophrenia has enabled polygenic risk scores (PRS) to be measured in the population. We hypothesized that normal variation in PRS would be associated with magnetic resonance imaging (MRI) phenotypes of brain morphometry and tissue composition. We used the largest extant genome-wide association dataset (N = 69,369 cases and N = 236,642 healthy controls) to measure PRS for schizophrenia in a large sample of adults from the UK Biobank (Nmax = 29,878) who had multiple micro- and macrostructural MRI metrics measured at each of 180 cortical areas, seven subcortical structures, and 15 major white matter tracts. Linear mixed-effect models were used to investigate associations between PRS and brain structure at global and regional scales, controlled for multiple comparisons. Polygenic risk was significantly associated with reduced neurite density index (NDI) at global brain scale, at 149 cortical regions, five subcortical structures, and 14 white matter tracts. Other microstructural parameters, e.g., fractional anisotropy, that were correlated with NDI were also significantly associated with PRS. Genetic effects on multiple MRI phenotypes were co-located in temporal, cingulate, and prefrontal cortical areas, insula, and hippocampus. Post-hoc bidirectional Mendelian randomization analyses provided preliminary evidence in support of a causal relationship between (reduced) thalamic NDI and (increased) risk of schizophrenia. Risk-related reduction in NDI is plausibly indicative of reduced density of myelinated axons and dendritic arborization in large-scale cortico-subcortical networks. Cortical, subcortical, and white matter microstructure may be linked to the genetic mechanisms of schizophrenia.

Planthopper bugs use a fast, cyclic elastic recoil mechanism for effective vibrational communication at small body size.

Vibrations through substrates are an important source of information for diverse organisms, from nematodes to elephants. The fundamental challenge for small animals using vibrational communication is to move their limited mass fast enough to provide sufficient kinetic energy for effective information transfer through the substrate whilst optimising energy efficiency over repeated cycles. Here, we describe a vibratory organ found across a commercially important group of plant-feeding insects, the planthoppers (Hemiptera: Fulgoromorpha). This elastic recoil snapping organ generates substrate-borne broadband vibrations using fast, cyclical abdominal motion that transfers kinetic energy to the substrate through the legs. Elastic potential energy is stored and released twice using two different latched energy-storage mechanisms, each utilising a different form of elastic recoil to increase the speed of motion. Comparison to the acoustic tymbal organ of cicadas (Hemiptera: Cicadomorpha) reveals functional convergence in their use of elastic mechanisms to increase the efficacy of mechanical communication.

Birds invest wingbeats to keep a steady head and reap the ultimate benefits of flying together.

Flapping flight is the most energetically demanding form of sustained forwards locomotion that vertebrates perform. Flock dynamics therefore have significant implications for energy expenditure. Despite this, no studies have quantified the biomechanical consequences of flying in a cluster flock or pair relative to flying solo. Here, we compared the flight characteristics of homing pigeons (Columba livia) flying solo and in pairs released from a site 7 km from home, using high-precision 5 Hz global positioning system (GPS) and 200 Hz tri-axial accelerometer bio-loggers. As expected, paired individuals benefitted from improved homing route accuracy, which reduced flight distance by 7% and time by 9%. However, realising these navigational gains involved substantial changes in flight kinematics and energetics. Both individuals in a pair increased their wingbeat frequency by 18% by decreasing the duration of their upstroke. This sharp increase in wingbeat frequency caused just a 3% increase in airspeed but reduced the oscillatory displacement of the body by 22%, which we hypothesise relates to an increased requirement for visual stability and manoeuvrability when flying in a flock or pair. The combination of the increase in airspeed and a higher wingbeat frequency would result in a minimum 2.2% increase in the total aerodynamic power requirements if the wingbeats were fully optimised. Overall, the enhanced navigational performance will offset any additional energetic costs as long as the metabolic power requirements are not increased above 9%. Our results demonstrate that the increases in wingbeat frequency when flying together have previously been underestimated by an order of magnitude and force reinterpretation of their mechanistic origin. We show that, for pigeons flying in pairs, two heads are better than one but keeping a steady head necessitates energetically costly kinematics.