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Design, validation, and functional impact of oligonucleotides for multigene silencing in Alzheimer's disease
Get PDFAlzheimer's disease (AD) is characterized by overlapping pathological processes, including amyloid-beta (Aβ) accumulation, tau hyperphosphorylation, mitochondrial dysfunction, and neuroinflammation. Monogenic therapies have shown limited benefits, and only in a subset of patients, as other pathological processes continue to drive disease progression. Given the multifactorial and heterogeneous nature of AD, therapeutics targeting more than one gene simultaneously represent a promising strategy to achieve broader therapeutic outcomes. This study highlights the advantages of multigene RNA-based therapeutics, which may overcome compensatory mechanisms and patient heterogeneity. Here, we report the design and functional validation of antisense oligonucleotides (ASOs) specifically engineered for simultaneous silencing of more than one AD-related gene. Using algorithm-assisted sequence design, we generated 11 bispecific gapmer ASOs from 20 candidate genes. In human and mouse cellular models, these ASOs achieved potent and sustained knockdown with picomolar to low-nanomolar IC50 values. Functionally, treatment led to significant reductions in Aβ42 production, up to 70%, while maintaining favorable safety and specificity profiles. Collectively, our findings establish a proof of concept for multigene silencing in AD, demonstrating that rationally designed ASOs can provide robust target suppression across key pathological pathways. This strategy introduces a new paradigm in oligonucleotide design, with the potential to deliver disease-modifying benefits for patients with AD
Discovery of skill-switching criteria for learning agile quadruped locomotion
Get PDFThis study develops a hierarchical learning and optimization framework that can learn and achieve well-coordinated multi-skill locomotion. The learned multi-skill policy can switch between skills automatically and naturally while tracking arbitrarily positioned goals and can recover from failures promptly. The proposed framework is composed of a deep reinforcement learning process and an optimization process. First, the contact pattern is incorporated into the reward terms to learn different types of gaits as separate policies without the need for any other references. Then, a higher-level policy is learned to generate weights for individual policies to compose multi-skill locomotion in a goal-tracking task setting. Skills are automatically and naturally switched according to the distance to the goal. The appropriate distances for skill switching are incorporated into the reward calculation for learning the high-level policy and are updated by an outer optimization loop as learning progresses. We first demonstrate successful multi-skill locomotion in comprehensive tasks on a simulated Unitree A1 quadruped robot. We also deploy the learned policy in the real world, showcasing trotting, bounding, galloping, and their natural transitions as the goal position changes. Moreover, the learned policy can react to unexpected failures at any time, perform prompt recovery, and successfully resume locomotion. Compared to baselines, our proposed approach achieves all the learned agile skills with improved learning performance, enabling smoother and more continuous skill transitions
Complete Classification of the Dehn Functions of Bestvina–Brady Groups
Get PDFWe prove that the Dehn function of every finitely presented Bestvina–Brady group grows as a linear, quadratic, cubic, or quartic polynomial. In fact, we provide explicit criteria on the defining graph to determine the degree of this polynomial. As a consequence, we identify an obstruction that prevents certain Bestvina–Brady groups from admitting a CAT(0) structure
Lethal effects of ivermectin structures on malaria vectors and in silico analysis of interactions with their glutamate-gated chloride ion channels
Get PDFIvermectin is lethal to Anopheles mosquitoes making it a possible malaria control intervention. The primary mode of action of ivermectin occurs when it binds to the glutamate-gated chloride channel (GluCl), allowing for continuous flow of chloride leading to flaccid paralysis and death of the mosquito. In Caenorhabditis elegans, ivermectin is thought to open the GluCl channel when the M2-M3 loop forms Van der Waals bonds with the first sugar ring and aglycone structure of ivermectin. Here we investigate in Anopheles dirus and Anopheles minimus the mosquito-lethal effect of ivermectin (both sugar rings), monosaccharide (one sugar ring), and aglycone (no sugar rings) demonstrating full, partial, and no effect, respectively. The Anopheles GluCl protein sequences were determined and used to a create 3-D structural docking models. The docking models identified new binding interactions with a hydrogen bond forming between the second sugar ring hydroxyl group (4″-OH) and THR304 of the Anopheles GluCl M2-M3 loop. This hydrogen bond is possible due to a single substitution in the M2-M3 loop from C. elegans ILE273 to Anopheles THR304. The work presented here improves our understanding of Anopheles GluCl-ivermectin interactions as well as how ivermectin resistance could arise in the future
Plasmodium ARK1 regulates spindle formation during atypical mitosis and forms a divergent chromosomal passenger complex
Get PDFMitosis in Plasmodium spp., the causative agent of malaria, is fundamentally different from model eukaryotes, proceeding via a bipartite microtubule organising centre (MTOC) and lacking canonical regulators such as Polo kinases. During schizogony, asynchronous nuclear replication produces a multinucleate schizont, while rapid male gametogony generates an octaploid nucleus before gamete formation. Here, we identify Aurora-related kinase 1 (ARK1) as a key component of inner MTOC and spindle formation, controlling kinetochore dynamics and driving mitotic progression. Conditional ARK1 depletion disrupts spindle biogenesis, kinetochore segregation, karyokinesis and cytokinesis in both stages, and affects parasite transmission. Interactome analysis shows that ARK1 forms the catalytic core of a non-canonical chromosomal passenger complex (CPC) containing two highly divergent inner centromere proteins (INCENPs), which we term INCENP-A and INCENP-B, and lacking the canonical chromatin-targeting subunits Survivin and Borealin. Comparative genomics suggests that apicomplexan INCENPs arose through recurrent lineage-specific duplications, reflecting an evolutionary rewiring of CPC architecture in this eukaryotic lineage. Together, these findings reveal key adaptations in Plasmodium mitosis involving ARK1 and its INCENP scaffolds, and identify the ARK1-INCENP interface as a potential multistage target for antimalarial intervention
Choice and complexity: In naturally occurring data, absolute complexity does not necessarily trigger relative complexity
Get PDFThis article interrogates two related assumptions widespread in many approaches to language: (1) languages do not like synonymy; (2) absolute complexity (i.e. the length of the grammatical description of a language) tends to be proportional to relative complexity (i.e. difficulty). Against this backdrop, we explore the link between syntactic synonymy (i.e., grammatical variation and optionality) and relative complexity (i.e., cognitive load) using methods from both corpus and psycholinguistics. We test two predictions: First, if synonymy avoidance is a design feature of human language, then grammatical variation should be sub-optimal and cause a measurable increase in production difficulty. Second, optionality will necessarily increase the absolute complexity of a language system. This increased absolute complexity will, in turn, increase relative complexity, i.e., cognitive load, also measured by increased production difficulty. Contrary to these predictions, analyses based on the SWITCHBOARD corpus of American English shows that the presence of choice contexts does not positively correlate with two metrics of production difficulty, namely filled pauses (um and uh) and unfilled pauses (speech planning time), not even when a typology of grammatical alternation type (insertion/deletion, substitution, permutation) is taken into account. These results challenge the view that grammatical optionality is sub-optimal and difficult for speakers, and that absolute complexity is necessarily proportional to relative complexity.
Stability shifts in gliding flight: hawks morph from an unstable to stable state when navigating a gap
Get PDFBirds control their flight by morphing their wing and tail configurations as they shift between steady glides and agile manoeuvres. Cadaveric studies have shown that birds have the capacity to adopt both stable and unstable configurations, but it remains unknown how birds exploit this ability in flight. Here, we fill this gap by studying the progression of wing and tail configurations of a free-gliding Harris’s hawk (Parabuteo unicinctus) during a wing-tucking manoeuvre. Wind tunnel experiments on three-dimensional-printed models revealed that tucked configurations were statically stable, while spread configurations displayed a nonlinear relationship between pitching moment and lift. This nonlinearity allows configurations to be either stable or unstable depending on the lift state, affording a previously under-explored source of flight performance flexibility. Furthermore, we found that the hawk transitioned from an unstable, spread configuration to a stable, tucked configuration as it traversed the gap, shifting the effective static margin from −25% to 19% of the reference chord. This notable stability shift suggests that adaptive flight control allows transition between flight modes and offers insight into flight conditions where shifting stability states may be relevant. This outcome will advance novel bio-inspired, fixed-wing uncrewed aerial vehicle designs capable of rapid transitions
Predisposed and learned preferences for multipoint visual statistics in visually naive newly hatched chicks
Get PDFRecent studies have revealed that human and non-human animals (rats) can detect luminance distribution and correlations between pixels in an image (ranging from 2-point to 4-point). This sensitivity is believed to stem from optimization processes in the visual system operating through efficient coding mechanisms that retain the most informative and significant features (here identified as the most variable correlations), thereby reducing costs to extract biologically relevant information from the environment. However, it is yet to be determined whether this optimization is evolutionarily given by inborn mechanisms or shaped by visual experience. Here we report that newly hatched visually naive domestic chicks (Galluls gallus) spontaneously prefer to approach luminance, 2-point and 4-point correlation patterns (respectively, horizontal lines and rectangular patterns), while showing no preference for 3-point correlation over noise controls. This parallels the ranking observed in adult humans and rats, thus suggesting that evolutionarily given biological predispositions largely drive efficient coding of natural images. We also found that learning by exposure to visual stimuli, as occurs naturally during visual imprinting, induced a preference for noise over point correlation patterns in chicks exposed to 3- and 4-point patterns. We hypothesize that this behaviour could reflect chicks’ preference for stimuli of lower statistical (correlation-based) complexity
Mapping the potential and limitations of using generative AI technologies to address socio-economic challenges in LMICs
No full textDrawing on the experiences and lessons learned from researchers based in low- and middle-income countries (LMICs) that leverage generative artificial intelligence (GenAI) technologies to address socio-economic challenges, we showcase the considerable potential to use GenAI to accelerate the progress towards achieving some of the Sustainable Development Goals, as well as considerable obstacles for creating locally adapted AI tools for fair development in LMICs. An expanded evidence base on GenAI in resource-limited settings is crucial for policymakers to understand opportunities and risks, while rights-based safeguards against AI harms can be strengthened by the lived experiences of local projects
How to invigorate and complete the fossil fuel transition
Get PDFThe global transition away from fossil fuels has stalled. While international announcements like the COP28 Global Stocktake signal political intent, actual geopolitical developments reveal a persistent interest in fossil fuels. Current fossil fuel production and consumption trajectories remain fundamentally misaligned with the temperature goals of the Paris Agreement. Yet the position of fossil fuels is more tenuous than recent trends imply. Several structural factors that have historically underpinned their dominance – most notably their control over energy supply options – are now weakening. We argue that the fossil fuel transition can be successfully completed if policymakers, businesses and financial institutions more systematically deploy solutions that already exist. The problem is not a lack of policy, technological, or financial tools, but their inconsistent application and the limited ambition with which they are implemented. We identify eight strategic challenges that together define the fossil fuel endgame (see Action Points below). These challenges span deep societal views about prosperity, institutional and regulatory distortions that favour fossil fuels, the practical management of decline in fossil fuel demand and supply, and the requirements for a net-zero-aligned residual fossil fuel sector. We show that for each challenge there are tested, scalable solutions. Although inertia and entrenched interests constitute significant barriers, with the right set of interventions, a successful fossil fuel transition is possible, desirable and more likely than is generally assumed