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Wearable technologies for assisted mobility in the real world
Get PDFMobility impairments from aging, injury, or medical conditions limit independence and social participation. Conventional assistive devices lack adaptability in complex environments. Recent wearable technologies integrating neural sensing, electronics, and co-design offer personalized, responsive mobility support. This perspective focuses on advances in wearable sensing and multimodal fusion for intent recognition, environmental interaction, and adaptive control in exoskeletons, prosthetics, smart wheelchairs, and navigation systems. Emphasizing human-in-the-loop and cognitive–sensorimotor integration, it outlines emerging trends and challenges, promoting intelligent, user-centered solutions to restore function and enhance autonomy, accessibility, and inclusion for individuals with mobility impairments
Structural basis of undecaprenyl phosphate glycosylation leading to polymyxin resistance in Gram-negative bacteria
Get PDFIn Gram-negative bacteria, the enzymatic modification of Lipid A with aminoarabinose (L-Ara4N) leads to resistance against polymyxin antibiotics and cationic antimicrobial peptides. ArnC, an integral membrane glycosyltransferase, attaches a formylated form of aminoarabinose to the lipid undecaprenyl phosphate, enabling its association with the bacterial inner membrane. Here, we present cryo-electron microscopy structures of ArnC from S. enterica in apo and nucleotide-bound conformations. These structures reveal a conformational transition that takes place upon binding of the partial donor substrate. Using coarse-grained and atomistic simulations, we provide insights into substrate coordination before and during catalysis, and we propose a catalytic mechanism that may operate on all similar metal-dependent polyprenyl phosphate glycosyltransferases. The reported structures provide a new target for drug design aiming to combat polymyxin resistance
Ultra-fast physics-based modeling of the elephant trunk
Get PDFWith more than 90,000 muscle fascicles, the elephant trunk is a complex biological structure and the largest known muscular hydrostat. It achieves unprecedented control through intricately orchestrated contractions of a wide variety of muscle architectures. Fascinated by the elephant trunk’s unique performance, scientists of all disciplines are studying its anatomy, function, and mechanics, and use it as an inspiration for biomimetic soft robots. Yet, to date, there is no precise mapping between microstructural muscular activity and macrostructural trunk motion, and our understanding of the elephant trunk remains incomplete. Specifically, no model of the elephant trunk employs formal physics-based arguments that account for its complex muscular architecture, while preserving low computational cost to enable fast screening of its configuration space. Here we create a reduced-order model of the elephant trunk that can – within a fraction of a second – predict the trunk’s motion as a result of its muscular activity. To ensure reliable results in the finite deformation regime, we integrate first principles of continuum mechanics and the theory of morphoelasticity for fibrillar activation. We employ dimensional reduction to represent the trunk as an active slender structure, which results in closed-form expressions for its curvatures and extension as functions of muscle activation and anatomy. We create a high-resolution digital representation of the trunk from magnetic resonance images to quantify the effects of different muscle groups. We propose a general solution method for the inverse motion problem and apply it to extract the muscular activations in three representative trunk motions: picking a fruit; lifting a log; and lifting a log asymmetrically. For each task, we identify key features in the muscle activation profiles. Our results suggest that the elephant trunk either autonomously reorganizes muscle activation upon reaching the maximum contraction or chooses the inverse problem branches that avoid reaching the contraction constraints throughout the motion. Our study provides a complete quantitative characterization of the fundamental science behind elephant trunk biomechanics, with potential applications in the material science of flexible structures, the design of soft robots, and the creation of flexible prosthesis and assist devices
Neural spacetimes for DAG representation learning
Get PDFWe propose a class of trainable deep learning-based geometries called Neural SpaceTimes (NSTs), which can universally represent nodes in weighted Directed Acyclic Graphs (DAGs) as events in a spacetime manifold. While most works in the literature focus on undirected graph representation learning or causality embedding separately, our differentiable geometry can encode both graph edge weights in its spatial dimensions and causality in the form of edge directionality in its temporal dimensions. We use a product manifold that combines a quasimetric (for space) and a partial order (for time). NSTs are implemented as three neural networks trained in an end-to-end manner: an embedding network, which learns to optimize the location of nodes as events in the spacetime manifold, and two other networks that optimize the space and time geometries in parallel, which we call a neural (quasi-)metric and a neural partial order, respectively. The latter two networks leverage recent ideas at the intersection of fractal geometry and deep learning to shape the geometry of the representation space in a data-driven fashion, unlike other works in the literature that use fixed spacetime manifolds such as Minkowski space or De Sitter space to embed DAGs. Our main theoretical guarantee is a universal embedding theorem, showing that any k-point DAG can be embedded into an NST with 1 + O(log(k)) distortion while exactly preserving its causal structure. The total number of parameters defining the NST is sub-cubic in k and linear in the width of the DAG. If the DAG has a planar Hasse diagram, this is improved to O(log(k) + 2) spatial and 2 temporal dimensions. We validate our framework computationally with synthetic weighted DAGs and real-world network embeddings; in both cases, the NSTs achieve lower embedding distortions than their counterparts using fixed spacetime geometries
Antiretroviral Therapy Adherence Interventions in the Era of Universal Test and Treat: A Hybrid Systematic-Narrative Literature Review of Global Evidence
Get PDFAn undetectable viral load (VL) in people living with HIV (PWH) is key to both individual and public health success. But for the millions of PWH on oral antiretroviral therapy (ART) worldwide, this requires consistent, sustained adherence. Review of interventions to support adherence published in recent literature can provide insights into promising and effective strategies. We conducted a hybrid systematic-narrative literature review to explore optimal adherence strategies in the era of universal test-and-treat. We searched PubMed, Scopus, and Web of Science according to PRISMA guidelines for peer-reviewed studies, available in English, including people ≥ 12 years old taking ART, published between 01 January 2015 and 18 January 2024. We extracted data on the included studies and the adherence interventions (strategies used —allocated to one of 14 a priori categories or ‘other’, measures of adherence, and intervention outcomes). Descriptive statistics were used for study information and those interventions with a positive effect were described narratively. We extracted data from 230 studies evaluating a total of 262 interventions among 97,037 PWH. Most studies enrolled participants in Africa (106, 46%) or North America (80, 35%). The majority randomized participants (215, 94%), including 30 cluster-randomized trials. Most included general HIV clinic populations, with 51 (22%) focused on youth and 23 (10%) on pregnant and post-partum women. Many (146, 64%) used VL as an outcome. Self-reported adherence was also a commonly used outcome (129, 56%), but a minority used self-reported measures alone (36, 16%). The most common intervention strategies included across the 262 interventions were eHealth/ mHealth technologies (90, 34%) and adherence-focused counseling (81, 31%). The majority of interventions had ‘other’ intervention features (133, 51%), typically combined with one or more of the a priori-defined strategies (107, 80%). Most studies evaluated an approach with multiple strategies packaged into a single intervention (k = 182/262, 70%).The majority of interventions had some evidence of effect on an adherence outcome (k = 159, 61%). In studies reporting VL outcomes, 52% (k = 87/166) found some evidence of effect, while 28% (k = 47/166) found significant effects. Intervention strategies demonstrating significant impact on VL included task-shifting and changing dispensing schedules (3/5, 60% in both), while nearly half the evaluations of economic strategies demonstrated significant impact on VL (10/21). A number of different adherence intervention strategies have the potential to impact viral suppression in different populations. Variability in intervention strategies and the resulting outcomes, supports calls to target interventions to PWH who are most likely to benefit, while at the same time addressing social determinants of health and reducing barriers to accessing care to make services more person-centered. Greater attention to evaluating flexible, tailored, complex interventions may offer valuable insights for moving towards the next generation of highly generalizable, sustainable adherence support
EMQN best practice guidelines for analysis and reporting of microsatellite instability in solid tumours
Get PDFMicrosatellite instability (MSI) is the accumulation of insertion and deletion variants (instability) in short tandem repeat DNA sequences (microsatellites). High levels of MSI occur following loss of function of the DNA mismatch repair system (MMR). MMR deficiency is an increasingly important cancer biomarker that is associated with chemotherapy resistance and response to immune checkpoint blockade, as well as one of the commonest hereditary cancer syndromes, Lynch syndrome. Since its discovery over two decades ago, our biological understanding, the testing methods, and the clinical implications of MSI analysis have expanded rapidly and up-to-date best practice guidelines are needed. An expert working group reviewed the literature and devised 15 best practice recommendations that were finalised following consultation with clinical and laboratory scientists partnered with EMQN. These include seven recommendations on key technical aspects of MSI testing and eight recommendations on the clinical interpretation and reporting of results. The latter focuses on Lynch syndrome screening and immune checkpoint blockade therapy. Example report wording is provided to assist implementation and standardisation. Common terminology and MSI analysis methods are also discussed. These guidelines are aimed primarily at genomic scientists working in diagnostic testing laboratories, but will provide a useful review of MSI for clinicians, academics, and other related professionals
GABA A receptor availability in clinical high-risk and first-episode psychosis: a [ 11 C]Ro15-4513 positron emission tomography study
Get PDFDisrupted gamma-aminobutyric acid (GABA) neurotransmission may contribute to the pathophysiology of schizophrenia. Reductions in hippocampal GABAergic neurons have been found in schizophrenia, and increased hippocampal perfusion has been described in schizophrenia and in people at clinical high-risk for psychosis (CHRp). We have also found decreases in hippocampal GABAA receptors containing the α5 subunit (GABAARα5) in a well-validated neurodevelopmental rat model of relevance for schizophrenia. Positive allosteric modulation of these receptors in the hippocampus using a specific compound was shown to reverse the behavioural and neurophysiological phenotypes of this model. However, whether GABAARα5 availability is dysregulated in the psychosis spectrum at the regional or network levels is unknown. We addressed this issue by using [11C]Ro15-4513 and positron emission tomography (PET) in 22 individuals at CHRp, 10 people with a first-episode psychosis (FEP) and 23 healthy controls (HC). We quantified GABAARα5 availability in the hippocampus and across the brain, and employed a perturbation covariance method to assess individual molecular covariance deviations in CHRp and FEP groups compared to the HC group. Hippocampal GABAARα5 availability was not significantly different between groups (F(2,50) = 0.25, p = 0.78). However, network analysis identified significant deviations in GABAARα5 covariance between groups, both across all regions (all p < 0.001, pairwise Cohen’s d = 0.07–0.5) and relative to the hippocampus (all p < 0.001, pairwise Cohen’s d = 0.01–0.67). These findings suggest that individuals at clinical high-risk for psychosis and people with early psychosis may show alterations to the brain-wide organisation of the GABAARα5 system, rather than changes at a regional level
What does an ion feel at the electrochemical interface? Revisiting electrosorption through nonlocal electrostatics
Get PDFThe traditional Gouy–Chapman–Stern theory has been effective in explaining the behavior of dilute electrolytes in the electrical double layer but falls short when it comes to describing how ions behave at the metal/electrolyte interface. This is because it overlooks key factors such as the molecular structure of water at the interface and the effects of electron screening in the metal. To address these gaps, we revisit ion adsorption at the metal/electrolyte interface. The approach combines the method of images with a field-theoretic framework for dilute electrolytes and metals described by the Thomas–Fermi model. Nonlocal polarization correlations in water are described by a first-order gradient expansion in the Landau free energy functional. Unlike earlier approaches that relied on the “specular reflection approximation,” our method provides a less constrained way to handle the complex electrostatic boundary conditions at the interface. Analyzing the behavior of a test charge near the interface, an electrostatic energy minimum is found. This minimum depends on the metal’s screening properties and the overall potential drop across the double layer. In addition, the alignment of water dipoles at the interface creates an asymmetry in the energy experienced by positively and negatively charged ions. Finally, we derived an expression for the electrosorption isotherm by describing both the distribution of the electrostatic potential and the lateral interactions between charges along the interface. Our findings highlight how the structure of interfacial water can drive processes such as underpotential deposition by creating favorable electrostatic conditions for ion adsorption
Optimizing approaches for targeted integration of transgenic cassettes by integrase-mediated cassette exchange in mouse and human stem cells
Get PDFTo enable robust expression of transgenes in stem cells, recombinase-mediated cassette exchange at safe harbor loci is frequently adopted. The choice of recombinase enzyme is a critical parameter to ensure maximum efficiency and accuracy of the integration event. We have explored the serine recombinase family of site-specific integrases and have directly compared the efficiency of PhiC31, W-beta, and Bxb1 integrase for targeted transgene integration at the Gt(ROSA)26Sor locus in mouse embryonic stem cells. All 3 integrases were found to be suitable for efficient engineering and long-term expression of each integrase was compatible with pluripotency, as evidenced by germline transmission. Bxb1 integrase was found to be 2-3 times more efficient than PhiC31 and W-beta. The Bxb1 system was adapted for cassette exchange at the AAVS1 locus in human induced pluripotent stem (iPS) cells, and the 2 commonly used ubiquitous promoters, CAG and Ef1α (EIF1A), were tested for their suitability in driving expression of the integrated transgenic cargo. AAVS1-integrated Ef1α promoter led to a very mosaic pattern of expression in targeted hiPS cells, whereas the AAVS1-integrated CAG promoter drove consistent and stable expression. To validate the system for the integration of functional machinery, the Bxb1 integrase system was used to integrate CAG-driven CRISPR-activation and CRISPR-inhibition machinery in human iPS cells and robust sgRNA-induced up- and downregulation of target genes was demonstrated
Towards decarbonizing the supply chain of dairy industry: current practice and emerging strategies
Get PDFThe food supply chain is currently challenged by the imperative to sustainably feed the increasingly expanding population while simultaneously striving to meet global net-zero emission targets. The dairy sector is widely considered as a carbon-intensive industry, contributing to significant greenhouse gas (GHG) emissions thereby exacerbating global warming. Here, we first summarize recent studies on determining GHG emissions of various dairy products, which suggests that farms are the primary emission hotspots in the dairy supply chain. Next, the vital role of novel techniques and emerging strategies to reduce carbon emissions in the dairy industry is emphasized at both local- and systematic levels. The implementation of targeted techniques at each stage, along with policy initiatives such as carbon pricing, plant-based alternatives, international standards and clean air act, play a vital role in establishing global optimization to mitigate climate warming. Despite these progresses, standards and guidelines of emission reduction for the dairy industry are currently lacking, which calls for continuous efforts to fill the gap