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Prof Robin Dunbar, Emeritus Professor of Evolutionary Psychology has been in conversation with Jim Al-Khalili on Radio 4's Life Scientific. This fascinating podcast gives takes us on a journey from his early beginnings in science, and his fascinating research and groundbreaking discoveries he's made deciphering the mysteries as to why humans and animals evolve the social habits to exist in friendship circles.
Direct specification of lymphatic endothelium from mesenchymal progenitors.
During embryogenesis, endothelial cells (ECs) are generally described to arise from a common pool of progenitors termed angioblasts, which diversify through iterative steps of differentiation to form functionally distinct subtypes of ECs. A key example is the formation of lymphatic ECs (LECs), which are thought to arise largely through transdifferentiation from venous endothelium. Opposing this model, here we show that the initial expansion of mammalian LECs is primarily driven by the in situ differentiation of mesenchymal progenitors and does not require transition through an intermediate venous state. Single-cell genomics and lineage-tracing experiments revealed a population of paraxial mesoderm-derived Etv2+Prox1+ progenitors that directly give rise to LECs. Morphometric analyses of early LEC proliferation and migration, and mutants that disrupt lymphatic development supported these findings. Collectively, this work establishes a cellular blueprint for LEC specification and indicates that discrete pools of mesenchymal progenitors can give rise to specialized subtypes of ECs.
Matching Sensing to Actuation and Dynamics in Distributed Sensorimotor Architectures
In this article we explore the benefits of matching sensing characteristics to actuation and dynamics in the context of spatially distributed sensorimotor architectures, motivated by recently discovered connections in blowfly flight physics and visual physiology. Within the proposed framework, we present novel semidefinite programs with linear matrix inequality constraints which yield directions encoded in the sensory output that maximize the smallest unstable Hankel singular value of the system. This is a coordinate-invariant metric that minimizes the control energy required to stabilize an unstable system and maximizes the achievable robustness to unstructured additive uncertainty over all possible controllers. We also reformulate the problem to achieve a prescribed speed of response, which can be applied to stable and unstable systems. We adapt a maximally robust controller synthesis method from previous work which provides a tool for validation. We additionally present an H∞ controller formulation which allows for a trade-off between minimization of actuator effort and robustness versus disturbance rejection and tracking capability, providing design flexibility over the maximally robust controller.
Mechanical network equivalence between the katydid and mammalian inner ears.
Mammalian hearing operates on three basic steps: 1) sound capturing, 2) impedance conversion, and 3) frequency analysis. While these canonical steps are vital for acoustic communication and survival in mammals, they are not unique to them. An equivalent mechanism has been described for katydids (Insecta), and it is unique to this group among invertebrates. The katydid inner ear resembles an uncoiled cochlea, and has a length less than 1 mm. Their inner ears contain the crista acustica, which holds tonotopically arranged sensory cells for frequency mapping via travelling waves. The crista acustica is located on a curved triangular surface formed by the dorsal wall of the ear canal. While empirical recordings show tonotopic vibrations in the katydid inner ear for frequency analysis, the biophysical mechanism leading to tonotopy remains elusive due to the small size and complexity of the hearing organ. In this study, robust numerical simulations are developed for an in silico investigation of this process. Simulations are based on the precise katydid inner ear geometry obtained by synchrotron-based micro-computed tomography, and empirically determined inner ear fluid properties for an accurate representation of the underlying mechanism. We demonstrate that the triangular structure below the hearing organ drives the tonotopy and travelling waves in the inner ear, and thus has an equivalent role to the mammalian basilar membrane. This reveals a stronger analogy between the inner ear basic mechanical networks of two organisms with ancient evolutionary differences and independent phylogenetic histories.
The mode-sensing hypothesis: Matching sensors, actuators and flight dynamics
Here we elaborate upon the recent hypothesis that the sensory systems of insects are matched to their flight dynamics, such that they are configured to make or encode measurements within a modal coordinate system. This hypothesis is inspired by several distinctive organizational principles of insect sensory systems: namely, that insects appear to be configured a) to sense relative, rather than absolute, quantities; b) to make measurements in highly non-orthogonal axis systems; and c) to fuse sensory inputs from different modalities prior to using them as feedback to the actuators. Having elaborated upon the hypothesis itself and considered the functional advantages of the resulting control architecture, we discuss some of the physiological details of how the requisite coordinate systems might in practice be set up in the fly visual system. We also provide a mathematical framework for testing the quantitative match between sensory system and flight dynamics in the specific context of the visual systems of flies.
Association of poultry vaccination with interspecies transmission and molecular evolution of H5 subtype avian influenza virus.
The effectiveness of poultry vaccination in preventing the transmission of highly pathogenic avian influenza viruses (AIVs) has been debated, and its impact on wild birds remains uncertain. Here, we reconstruct the movements of H5 subtype AIV lineages among vaccinated poultry, unvaccinated poultry, and wild birds, worldwide, from 1996 to 2023. We find that there is a time lag in viral transmission among different host populations and that movements from wild birds to unvaccinated poultry were more frequent than those from wild birds to vaccinated poultry. Furthermore, our findings suggest that the HA (hemagglutinin) gene of the AIV lineage that circulated predominately in Chinese poultry experienced greater nonsynonymous divergence and adaptive fixation than other lineages. Our results indicate that the epidemiological, ecological, and evolutionary consequences of widespread AIV vaccination in poultry may be linked in complex ways and that much work is needed to better understand how such interventions may affect AIV transmission to, within, and from wild birds.
Toward optimal disease surveillance with graph-based active learning.
Tracking the spread of emerging pathogens is critical to the design of timely and effective public health responses. Policymakers face the challenge of allocating finite resources for testing and surveillance across locations, with the goal of maximizing the information obtained about the underlying trends in prevalence and incidence. We model this decision-making process as an iterative node classification problem on an undirected and unweighted graph, in which nodes represent locations and edges represent movement of infectious agents among them. To begin, a single node is randomly selected for testing and determined to be either infected or uninfected. Test feedback is then used to update estimates of the probability of unobserved nodes being infected and to inform the selection of nodes for testing at the next iterations, until certain test budget is exhausted. Using this framework, we evaluate and compare the performance of previously developed active learning policies for node selection, including Node Entropy and Bayesian Active Learning by Disagreement. We explore the performance of these policies under different outbreak scenarios using simulated outbreaks on both synthetic and empirical networks. Further, we propose a policy that considers the distance-weighted average entropy of infection predictions among neighbors of each candidate node. Our proposed policy outperforms existing ones in most outbreak scenarios given small test budgets, highlighting the need to consider an exploration-exploitation trade-off in policy design. Our findings could inform the design of cost-effective surveillance strategies for emerging and endemic pathogens and reduce uncertainties associated with early risk assessments in resource-constrained situations.
Efgartigimod efficacy and safety in refractory myasthenia gravis: UK's first real-world experience.
BACKGROUND: We report our experience of patients with generalised myasthenia gravis (gMG) treated with efgartigimod, an neonatal Fc receptor antagonist, under the Early Access to Medicine Scheme (EAMS) in the UK. METHODS: Data from all UK patients treated with efgartigimod under the EAMS July 2022 to July 2023 were collected retrospectively. Efgartigimod was administered as per the ADAPT protocol (consisting of a treatment cycle of four infusions at weekly intervals with further cycles given according to clinical need). RESULTS: 48 patients with acetylcholine receptor antibody-positive gMG were treated in 12 centres. Most (75%) were female and most had a disease duration of over 10 years. The average MG-Activities of Daily Living (ADL) score at baseline was 11.2. Most (72.9%) patients had undergone thymectomy. 77.0% were taking prednisolone at baseline. All patients had used non-steroidal immunosuppressant treatments, the average number tried was 2.6 (range 1-6). 51% had received rituximab. 54.2% of patients required regular intravenous immunoglobulin/plasma exchange.75% of patients had a mean reduction in the MG-ADL of≥2 points in the first cycle and this remained stable throughout the study. The mean intracycle reduction in the MG-ADL score in the first, second, third and fourth cycles were -4.6 to -3.9, -3.4 and -4.2, respectively. Side effects were generally mild. No rescue treatments were required. At the end of the study, 96% of patients remained on efgartigimod. CONCLUSION: Efgartigimod is a safe and effective treatment for patients with refractory, treatment-resistant gMG.
Functional dynamics of G protein-coupled receptors reveal new routes for drug discovery.
G protein-coupled receptors (GPCRs) are the largest human membrane protein family that transduce extracellular signals into cellular responses. They are major pharmacological targets, with approximately 26% of marketed drugs targeting GPCRs, primarily at their orthosteric binding site. Despite their prominence, predicting the pharmacological effects of novel GPCR-targeting drugs remains challenging due to the complex functional dynamics of these receptors. Recent advances in X-ray crystallography, cryo-electron microscopy, spectroscopic techniques and molecular simulations have enhanced our understanding of receptor conformational dynamics and ligand interactions with GPCRs. These developments have revealed novel ligand-binding modes, mechanisms of action and druggable pockets. In this Review, we highlight such aspects for recently discovered small-molecule drugs and drug candidates targeting GPCRs, focusing on three categories: allosteric modulators, biased ligands, and bivalent and bitopic compounds. Although studies so far have largely been retrospective, integrating structural data on ligand-induced receptor functional dynamics into the drug discovery pipeline has the potential to guide the identification of drug candidates with specific abilities to modulate GPCR interactions with intracellular effector proteins such as G proteins and β-arrestins, enabling more tailored selectivity and efficacy profiles.
Automated characterisation of cerebral microbleeds using their size and spatial distribution on brain MRI.
Cerebral microbleeds (CMBs) are small, hypointense hemosiderin deposits in the brain measuring 2-10 mm in diameter. As one of the important biomarkers of small vessel disease, they have been associated with various neurodegenerative and cerebrovascular diseases. Hence, automated detection, and subsequent extraction of clinically useful metrics (e.g., size and spatial distribution) from CMBs are essential for investigating their clinical impact, especially in large-scale studies. While some work has been done for CMB segmentation, extraction of clinically relevant information is not yet explored. Herein, we propose the first automated method to characterise CMBs using their size and spatial distribution, i.e., CMB count in three regions (and their substructures) used in Microbleed Anatomical Rating Scale (MARS): infratentorial, deep, and lobar. Our method uses structural atlases of the brain for determining individual regions. On an intracerebral haemorrhage study dataset, we achieved a mean absolute error of 2.5 mm for size estimation and an overall accuracy > 90% for automated rating. The code and the atlas of MARS regions in Montreal Neurological Institute-MNI space are publicly available. RELEVANCE STATEMENT: Our method to automatically characterise cerebral microbleeds (size and location) showed a mean absolute error of 2.5 mm for size estimation and an over 90% accuracy for rating of infratentorial, deep and lobar regions. This is a promising approach to automatically provide clinically relevant cerebral microbleeds metrics. KEY POINTS: We present a method to automatically characterise cerebral microbleeds according to size and location. The method achieved a mean absolute error of 2.5 mm for size estimation. Automated rating for infratentorial, deep, and lobar regions achieved an over 90% overall accuracy. We made the code and atlas of Microbleed Anatomical Rating Scale regions publicly available.
Is Your Style Transfer Doing Anything Useful? An Investigation into Hippocampus Segmentation and the Role of Preprocessing
Brain atrophy assessment in MRI, particularly of the hippocampus, is commonly used to support diagnosis and monitoring of dementia. Consequently, there is a demand for accurate automated hippocampus quantification. Most existing segmentation methods have been developed and validated on research datasets and, therefore, may not be appropriate for clinical MR images and populations, leading to potential gaps between dementia research and clinical practice. In this study, we investigated the performance of segmentation models trained on research data that were style-transferred to resemble clinical scans. Our results highlighted the importance of intensity normalisation methods in MRI segmentation, and their relation to domain shift and style-transfer. We found that whilst normalising intensity based on min and max values, commonly used in generative MR harmonisation methods, may create a need for style transfer, Z-score normalisation effectively maintains style consistency, and optimises performance. Moreover, we show for our datasets spatial augmentations are more beneficial than style harmonisation. Thus, emphasising robust normalisation techniques and spatial augmentation significantly improves MRI hippocampus segmentation.