Search Results (1,800)

Tau proteins are microtubule-associated proteins that regulate axonal structure, dynamics, and transport, and their dysregulation underlies several neurodegenerative diseases. The MAPT gene produces multiple tau isoforms through alternative splicing, including the high-molecular-weight isoform known as Big tau, which contains an insert of the large 4a exon of approximately 250 amino acids. Big tau is predominantly expressed in neurons of the peripheral nervous system (PNS), cranial motor nuclei, and select neurons of the central nervous system (CNS) such as the cerebellum and brainstem. Developmental expression studies indicate a switch from low-molecular-weight isoforms of tau to Big tau during axonal maturation, suggesting that Big tau optimizes cytoskeletal dynamics to accommodate long axonal projections. Comparative sequence and biophysical analyses show that the exon-4a insert is highly acidic, intrinsically disordered, and evolutionarily conserved in its length but not its primary sequence, implying a structural role. Emerging modeling and in vitro assays suggest that the extended projection domain provided by the exon-4a insert spatially and electrostatically shields the aggregation-prone PHF6 and PHF6* motifs in tau’s microtubule-binding domain, thereby reducing β-sheet driven aggregation. This mechanism may explain why tauopathies that involve aggregation of tau have little effect on the PNS and specific regions of the CNS such as the cerebellum, where Big tau predominates. Transcriptomic and proteomic data further suggest that alternative Big tau variants, including 4a-L, are expressed in certain cancerous tissues, indicating broader roles in cytoskeletal remodeling beyond neurons. Despite its putative anti-aggregation properties, the physiological regulation, interaction partners, and in vivo mechanisms of Big tau remain poorly defined. This review summarizes what is known about Big tau and what is missing toward a better understanding of how expansion via inclusion of exon 4a modifies tau’s structural and functional properties. Our purpose is to inspire future studies that could lead to novel therapeutic strategies to mitigate tau aggregation in neurodegenerative diseases. Full article

In the filamentous fungus Neurospora crassa, a gene not having a pairing partner during meiosis is seen as a potential intruder and is targeted by a mechanism called meiotic silencing by unpaired DNA (MSUD). MSUD employs core RNA interference (RNAi) components such as the SMS-2 Argonaute, which uses small interfering RNAs (siRNAs) as guides to seek out mRNAs from unpaired genes for silencing. In Drosophila melanogaster, the heat shock protein 70 (Hsp70) chaperone system facilitates the conformational activation of an Argonaute and allows it to load siRNAs. Here, our results demonstrate that an Hsp70 protein in Neurospora interacts with SMS-2 and mediates the silencing of unpaired genes. Full article

The flavivirus NS1 protein is a component of the viral replication complex and plays diverse, yet poorly understood, roles in the viral life cycle. To enable real-time visualization of the developing replication organelle and biochemical analysis of tagged NS1 and its interacting partners, we engineered a replication-competent yellow fever virus (YFV) replicon encoding a C-terminal fusion of NS1 with green fluorescent protein (NS1–GFP). The initial variant was non-viable in the absence of trans-complementation with wild-type NS1; however, viability was partially restored through the introduction of co-adaptive mutations in GFP (Q204R/A206V) and NS4A (M108L). Subsequent cell culture adaptation generated a 17-nucleotide frameshift within the NS1–GFP linker, resulting in a more flexible and less hydrophobic linker sequence. The optimized genome, in the form of a replicon, replicates in packaging cells that produce YFV structural proteins, as well as in naive BHK-21 cells. In the packaging cells, the adapted NS1–GFP replicon produces titers of infectious particles of approximately 10^6 FFU/mL and is genetically stable over five passages. The expressed NS1–GFP fusion protein localizes to the endoplasmic reticulum and co-fractionates with detergent-resistant heavy membranes, a hallmark of flavivirus replication organelles. This NS1–GFP replicon provides a novel platform for studying NS1 functions and can be further adapted for proximity-labeling strategies aimed at identifying the still-unknown protease responsible for NS1–NS2A cleavage. Full article

Interspecies communication is increasingly recognized as an affective–cognitive process co-created between humans and animals rather than a one-directional transmission of signals. This review integrates findings from ethology, neuroscience, welfare science, behavioral studies, and posthumanist ethics to examine how emotional expression, communicative intentionality, and relational engagement shape understanding across species. Research on primates, dogs, elephants, and marine mammals demonstrates that empathy, consolation, cooperative signaling, and multimodal perception rely on evolutionarily conserved mechanisms, including mirror systems, affective contagion, and oxytocin-mediated bonding. These biological insights intersect with ethical considerations concerning animal agency, methodological responsibility, and the interpretation of non-human communication. Emerging technological tools—bioacoustics, machine vision, and AI-assisted modeling—offer new opportunities to analyze complex vocal and behavioral patterns, yet they require careful contextualization to avoid anthropocentric misclassification. Synthesizing these perspectives, the review proposes a relational framework in which meaning arises through shared emotional engagement, embodied interaction, and ethically grounded interpretation. This approach highlights the importance of welfare-oriented, minimally invasive methodologies and supports a broader shift toward recognizing animals as communicative partners whose emotional lives contribute to scientific knowledge. This review primarily synthesizes empirical and theoretical research on primates and dogs, complemented by selected examples from elephants and marine mammals, which provide the most developed evidence base for the affective–cognitive and relational mechanisms discussed. Full article

Over the past five years, generative AI has carved out a major role in architecture, especially in education and visual idea generation. Most of the time, the literature talks about AI as a tool, an assistant, or sometimes a co-creator, always highlighting efficiency and the end product in architectural design. There is a steady rise in empirical studies, yet the real impact on how young architects learn still lacks a solid theory behind it. In this systematic review, we dig into peer-reviewed work from 2015 to 2025, looking at how generative AI fits into architectural design education. Using PRISMA guidelines, we pull together findings from 40 papers across architecture, design studies, human–computer interaction and educational research. What stands out is a clear tension: on one hand, students crank out more creative work; on the other, their reflective engagement drops, especially when AI steps in as a replacement during early ideation instead of working alongside them. To address this, we introduce the idea of “AI sparring”. Here, generative AI is not just a helper—it becomes a provocateur, pushing students to think critically and develop stronger architectural concepts. Our review offers new ways to interpret AI’s role, moving beyond seeing it just as a productivity booster. Instead, we argue for AI as an active, reflective partner in education, and we lay out practical recommendations for studio-based teaching and future research. This paper is a theoretical review and conceptual proposal, and we urge future studies to test these ideas in practice. Full article

Geothermal energy is a crucial component of climate adaptation and sustainability transitions, as it provides a dependable, low-carbon source of baseload power that can accelerate sustainable energy transitions and enhance climate resilience. Yet, in East Africa—one of the world’s most promising geothermal regions, with the East African Rift—a unique climate-energy opportunity zone—the harnessing of geothermal power remains slow and uneven. This study examines the contextual conditions that facilitate the successful and sustainable development of geothermal power in the region. Drawing on semi-structured interviews with 17 experienced professionals who have worked extensively on geothermal projects across East Africa, the analysis identifies how technical, institutional, managerial, and relational circumstances interact to shape outcomes. The findings indicate an interdependent configuration of success conditions, with structural, institutional, managerial, and meta-conditions jointly influencing project trajectories rather than operating in isolation. The most frequently emphasised enablers were resource confirmation and technical design, leadership and team competence, long-term stakeholder commitment, professional project management and control, and collaboration across institutions and communities. A co-occurrence analysis reinforces these insights by showing strong patterns of overlap between core domains—particularly between structural and managerial factors and between managerial and meta-conditions, highlighting the mediating role of managerial capability in translating contextual conditions into operational performance. Together, these interrelated circumstances form a system in which structural and institutional foundations create the enabling context, managerial capabilities operationalise this context under uncertainty, and meta-conditions sustain cooperation, learning, and adaptation over time. The study contributes to sustainability research by providing a context-sensitive interpretation of how project success conditions manifest in geothermal development under climate transition pressures, and it offers practical guidance for policymakers and partners working to advance SDG 7 (Affordable and Clean Energy), SDG 9 (Industry, Innovation and Infrastructure), and SDG 13 (Climate Action) in Africa. Full article

The application of Generative Artificial Intelligence (GenAI)—defined as a class of AI systems capable of autonomously generating new content such as images, texts, and design solutions based on learned data patterns—has become increasingly widespread in creative design. By supporting ideation, rapid trial-and-error, and data-driven decision-making, GenAI enables designers to explore design alternatives more efficiently and enhances human–computer interaction experiences. In design practice, GenAI functions not only as a productivity-enhancing tool but also as a collaborative partner that assists users in visual exploration, concept refinement, and iterative development. However, users still face a certain learning curve before effectively adopting these technologies. Within the framework of human-centered artificial intelligence, contemporary design practices place greater emphasis on inclusivity across diverse user groups and on enabling intuitive “what-you-think-is-what-you-get” interaction experiences. From a sustainable design perspective, GenAI’s capabilities in digital simulation, rapid iteration, and automated feedback contribute to more efficient design workflows, reduced collaboration costs, and broader access to creative participation for users with varying levels of expertise. These characteristics play a crucial role in enhancing the accessibility of design resources and supporting the long-term sustainability of creative processes. Focusing on the context of China’s digital design industry, this study investigates the application of GenAI in design workflows through an empirical case study of Zhitu AI, a generative design tool developed by Beijing Didi Infinity Technology Development Co., Ltd. The study conducts a literature review to outline the role of GenAI in visual design processes and employs observation-based experiments and semi-structured interviews with users of varying levels of design expertise. The findings reveal key pain points across stages such as prompt formulation, secondary editing, and asset generation. Drawing on the Kano model, the study further identifies potential design opportunities and discusses their value in improving efficiency, supporting non-expert users, and promoting more sustainable and inclusive design practices. Full article

Intimate relationship stability is fundamental to human wellbeing, yet its quantitative assessment faces dual challenges: the inherent subjectivity of psychological constructs and the complexity of social ecosystems. Symmetry, as a fundamental structural feature of social interaction, plays a pivotal role in shaping relational dynamics. To address these limitations, this study proposes an innovative computational framework that integrates Fuzzy Set Theory with Social Network Analysis (SNA). The framework consists of two complementary components: (1) a psychologically grounded fuzzy assessment model that employs differentiated membership functions to transform discrete subjective ratings into continuous and interpretable relationship quality indices and (2) an enhanced Fuzzy C-Means (FCM) threat detection model that utilizes Weighted Mahalanobis Distance to accurately identify and cluster potential interference sources within social networks. Empirical validation using a simulated dataset—comprising typical characteristic samples from 10 couples—demonstrates that the proposed framework not only generates interpretable relationship diagnostics by correcting biases associated with traditional averaging methods, but also achieves high precision in threat identification. The results indicate that stable relationships exhibit greater symmetry in partner interactions, whereas threatened nodes display structural and behavioural asymmetry. This study establishes a rigorous mathematical paradigm—“Subjective Fuzzification → Multidimensional Feature Engineering → Intelligent Clustering”—for relationship science, thereby advancing the field from descriptive analysis toward data-driven, quantitative evaluation and laying a foundation for systematic assessment of relational health. Full article

The presence of an extra DNA segment in a genome could indicate a transposon or another repetitive element on the move. In Neurospora crassa, a surveillance mechanism called meiotic silencing by unpaired DNA (MSUD) is maintained to monitor these selfish elements. MSUD utilizes common RNA interference (RNAi) factors, including the SMS-2 Argonaute, to target mRNAs from genes lacking a pairing partner during meiosis. In eukaryotes, an mRNA transcript is typically bound at the 5′ cap by the cap-binding complex (CBC), which assists in its nuclear export. Previously, we discovered that CBC and its interactor NCBP3 mediate MSUD, possibly by guiding the perinuclear SMS-2 to effectively recognize exported mRNAs. Here, we report that ARS2, a CBC cofactor, is involved in MSUD. ARS2 interacts with both CBC and NCBP3, and it may help bring them together. In addition to its role in silencing, ARS2 also contributes to vegetative growth and sexual sporulation. Full article

Background: Human noroviruses are the leading cause of foodborne gastroenteritis worldwide. Accumulating evidence suggests that food matrices containing fucosylated or histo-blood group antigen (HBGA)-like glycans may facilitate viral attachment and persistence, yet the molecular mechanisms underlying these interactions remain unclear. Methods: In this study, we performed a comparative computational analysis of norovirus–glycan interactions by integrating AlphaFold3-based structure prediction, molecular docking, and molecular dynamics simulations. A total of 182 P-domain models representing all genotypes across five human norovirus genogroups (GI, GII, GIV, GVIII, and GIX) were predicted and docked with a lettuce-derived core-fucosylated hexasaccharide (H₂N₂F₂) previously identified by our group. The three complexes exhibiting the most favorable docking energies were further examined using 40 ns molecular dynamics simulations, followed by MM/GBSA binding free energy calculations and per-residue decomposition analyses. Results: Docking results indicated that the majority of modeled P proteins were able to adopt energetically favorable interaction poses with H₂N₂F₂, with predicted binding energies ranging from −3.7 to −7.2 kcal·mol⁻¹. The most favorable docking energies were observed for GII.6_S9c_KC576910 (−7.2 kcal·mol⁻¹), GII.3_MX_U22498 (−7.1 kcal·mol⁻¹), and GII.4_CARGDS11182_OR700741 (−6.8 kcal·mol⁻¹). Molecular dynamics simulations suggested stable ligand engagement within canonical HBGA-binding pockets, with recurrent residues such as Asp374, Gln393, and Arg345 contributing to electrostatic and hydrophobic interactions, consistent with previously reported HBGA-binding motifs. MM/GBSA analyses revealed comparatively favorable binding tendencies among these complexes, particularly for globally prevalent genotypes including GII.3, GII.4, and GII.6. Conclusions: This work provides a large-scale structural and energetic assessment of the potential interactions between a naturally occurring lettuce-derived fucosylated hexasaccharide and human norovirus P domains. The results support the notion that core-fucosylated food-associated glycans can serve as interaction partners for diverse norovirus genotypes and offer comparative molecular insights into glycan recognition patterns relevant to foodborne transmission. The integrative AlphaFold3–docking–dynamics framework presented here may facilitate future investigations of virus–glycan interactions within food matrices. Full article

Background: Poly(ADP-ribose) polymerase inhibitors (PARPi) have transformed cancer therapy for patients harbouring homologous recombination repair (HRR) deficiencies, notably BRCA1/2 mutations. However, resistance to PARPi remains a clinical challenge, with restoration of BRCA1 function via hypomorphic variants representing an understudied scenario. Methods: Here, we engineered a doxycycline-inducible BRCA1 expression system in the BRCA1-mutant, triple-negative breast cancer cell line MDAMB436, permitting controlled analysis of functionally distinct BRCA1 hypomorphs in vitro and in vivo. Results: Among multiple BRCA1 variants generated—including RING, coiled-coil, and BRCT domain mutants—only overexpression of the ∆exon11 hypomorph robustly conferred resistance to olaparib and carboplatin, with drug sensitivity correlating to ∆exon11 expression levels. While ∆exon11 BRCA1 mediated HRR restoration, its efficiency was consistently lower than full-length BRCA1, as measured by RAD51 foci formation and interaction with repair partners such as PALB2. In vivo, tumours expressing Δexon11 BRCA1 exhibited only partial resistance to olaparib compared to those expressing full-length BRCA1. Importantly, the combination of olaparib and the ATR inhibitor, ceralasertib, overcame ∆exon11-mediated resistance, impairing RAD51 foci formation in ∆exon11-expressing cells. Conclusions: Our findings identify a dose-dependent, hypomorphic HRR restoration by ∆exon11 BRCA1, help explain the variable resistance observed in BRCA1-mutant pre-clinical models expressing this hypomorph, and propose ATR inhibition in combination with PARPi as a clinical strategy to counteract therapeutic resistance mediated by ∆exon11 BRCA1 hypomorphs. Full article

Chatbots have emerged as a promising interface for facilitating access to complex datasets, allowing users to pose questions in natural language rather than relying on specialized technical workflows. At the same time, remote sensing has transformed archaeological practice by producing vast amounts of imagery from LiDAR, drones, and satellites. While these advances have created unprecedented opportunities for discovery, they also pose significant challenges due to the scale, heterogeneity, and interpretative demands of the data. In related scientific domains, multimodal conversational systems capable of integrating natural language interaction with image-based analysis have advanced rapidly, supported by a growing body of survey and review literature documenting their architectures, datasets, and applications across multiple fields. By contrast, archaeological applications of chatbots remain limited to text-based prototypes, primarily focused on education, cultural heritage mediation or archival search. This review synthesizes the historical development of chatbots, examines their current use in remote sensing, and evaluates the barriers to adapting such systems for archaeology. Four major challenges are identified: data scale and heterogeneity, scarcity of training datasets, computational costs, and uncertainties around usability and adoption. By comparing experiences across domains, this review highlights both the opportunities and the limitations of integrating conversational AI into archaeological workflows. The central conclusion is that domain-specific adaptation is essential if multimodal chatbots are to become effective analytical partners in archaeology. Full article

This study proposes a process model for sharing ambiguous category concepts in virtual reality (VR) using an active inference framework. The model executes a dual-layer Bayesian update after observing both self and partner actions and predicts actions that minimize free energy. To incorporate agreement-seeking with others into active inference, we added disagreement in category judgments as a risk term in the free energy, weighted by gaze synchrony measured using Dynamic Time Warping (DTW), which is assumed to reflect joint attention. To validate the model, an object classification task in VR including ambiguous items was created. The experiment was conducted first under a bot avatar condition, in which ambiguous category judgments were always incorrect, and then under a human–human pair condition. This design allowed verification of the collaborative learning process by which human pairs reached agreement from the same degree of ambiguity. Analysis of experimental data from 14 participants showed that the model achieved high prediction accuracy for observed values as learning progressed. Introducing gaze synchrony weighting (${\gamma }_0\ge 0.5$) further improved prediction accuracy, yielding optimal performance. This approach provides a new framework for modeling socially shared cognition using active inference in human–robot interaction contexts. Full article

Background/Objectives: Capric acid (CA)–therapeutic deep eutectic systems (THEDES) are emerging as a distinct class of biofunctional matrices capable of reshaping drug solubilization, permeability, and bioactivity. Methods: Relevant studies on CA–THEDES were identified through targeted database searches and screened for evidence on their design, mechanisms, and pharmaceutical performance. Results: This review synthesizes current evidence on their structural design, mechanistic behavior, and pharmaceutical performance, revealing several unifying principles. Across multiple drug classes, CA consistently drives strong, directional hydrogen bonding and drug amorphization, resulting in marked solubility enhancement and stabilization of non-crystalline or supersaturated states relative to crystalline drugs or conventional solvent systems. Its amphiphilic C10 chain further contributes to membrane fluidization, which explains the improved transdermal and transmucosal permeation repeatedly observed in CA-THEDES. Additionally, synergistic antimicrobial and anticancer effects reported in several systems confirm that CA acts not only as a solvent component but as a bioactive co-therapeutic. Collectively, the reviewed data show that CA serves as a structurally determinant element whose dual hydrogen-bonding and membrane-interacting roles underpin the high pharmaceutical performance of these systems. However, gaps remain in long-term stability, toxicological profiling, and regulatory classification. Emerging Artificial Intelligence (AI) and Machine Learning (ML)-guided predictive approaches offer promising solutions by enabling rational selection of eutectic partners, optimal ratios, and property optimization through computational screening. Conclusions: Overall, CA-THEDES represent a rationally designable platform for next-generation drug delivery, where solvent functionality and therapeutic activity converge within a single, green formulation system. Full article

We present a computational study that precedes the potential interactions between SARS-CoV-2 helicase (NSP13) and selected host proteins implicated in chaperone-assisted folding and polyamine metabolism. Using structure-based modelling and protein–protein docking (BioLuminate v4.6), followed by all-atom molecular dynamics (MD) simulations (GROMACS v2018.6), and comparative MM-GBSA scoring (HawkDock v2), we evaluated the stability and interface properties of NSP13 complexes with cytosolic heat shock proteins; heat shock protein 40 (HSP40), heat shock protein 70 (HSP70), heat shock protein 90 (HSP90) and the polyamine biosynthesis enzyme ornithine decarboxylase (ODC). Docking, MD, and interface analyses indicate distinct complex behaviours: HSP70-NSP13 complexes sampled compact conformations, HSP90-NSP13 ensembles displayed greater conformational heterogeneity but more favourable comparative MM-GBSA estimates, and ODC-NSP13 interfaces were comparatively well packed. Per-residue contact mapping identified a small set of recurrent NSP13 residues, Lys22 and Asn51, as putative interaction hotspots. The reported findings herein generate testable hypotheses about NSP13 recruitment of host chaperones and modulation of polyamine metabolism that may inform downstream experimental studies. Full article