The complexities of bone architecture, with its hierarchical organization and varying spatiotemporal scales, necessitate advanced modeling techniques to capture its mechanical behavior precisely. This review aims to highlight recent trends in capturing the multiscale nature of bone using two primary computational approaches: classical and data-driven frameworks. Each class is assessed regarding its versatility in achieving scale dimensions, modeling complex behavior, integrating biological data, and balancing computational efficiency and interpretability. In addition, hybrid techniques have been shown to offer future avenues for promising robust and generalizable modeling. Therefore, particular attention has been given to the synergy between these techniques. A hierarchical decision matrix is proposed to translate this review into actionable guidance, shedding light on the selection or combination of appropriate techniques based on specific application contexts, such as data availability, modeling objectives, and computational constraints. This review aims to serve as both a state-of-the-art synthesis and a practical reference for future advancements in multiscale bone biomechanics.

Emergent Language Symbolic Autoencoder (ELSA) with weak supervision to model hierarchical brain networks.

Extrusion-based 3D printing of cross-scale porous bone scaffolds and their micro-topological structures for bone repair.

Tissues are organized through the assembly of diverse cell types into multicellular structures that exhibit hierarchical spatial organization. We present HRCHY-CytoCommunity, a graph neural network framework for identifying multi-level tissue structures directly from cell-type annotated spatial maps. It integrates differentiable graph pooling, adaptive edge pruning, and consistency and balance regularization in an end-to-end model, simultaneously inferring robust structures across multiple scales while preserving complete cellular coverage and fully nested relationships. The framework also supports cross-sample hierarchy alignment via cell-type enrichment-based clustering. Benchmarking on diverse spatial omics datasets, HRCHY-CytoCommunity outperforms existing hierarchical and non-hierarchical methods in identifying both coarse-grained tissue compartments and fine-grained cellular neighborhoods. Applied to a breast cancer cohort with clinical outcomes, the framework enables hierarchical prognostic stratification of patients and reveals survival-associated spatial patterns. HRCHY-CytoCommunity represents a general and scalable tool for deciphering tissue organization from single cells to multicellular modules, and ultimately to intact tissues and organs.

ABSTRACT This study examines the semiotic construction of Islamic sacred space within secular institutional environments, focusing on non-institutional prayer rooms (muṣallās) in Taiwan. Through a decolonial visual-semiotic analysis of signage and spatial markers across universities, airports, malls, and hospitals, the research investigates how portable semiotic resources, such as qiblah arrows, multilingual instructions, and religious icons, materialise ‘micro-sacralities’ in otherwise bureaucratic settings. Drawing on theories of language ideology, indexicality, and enregisterment, the analysis reveals a hierarchical organisation of sacred authority (often anchored in Arabic) and vernacular accessibility (predominantly Chinese and English), which together guide bodily orientation, ritual purity, and ethical comportment. The findings illustrate a spectrum of negotiated visibility, from aspirational belonging, where community-driven signs elevate a muṣallā to the status of a ‘mosque’, to contingent accommodation, where access is mediated through institutional protocols. By bridging Islamic theological conceptions of space with sociolinguistic practice, this study contributes to the emerging ‘sociolinguistics of Islam’, demonstrating how sacred space is relationally activated through semiotic means in minoritized, mobile, and secular contexts.

Understanding the evolution of animal cognitive capacities requires us to study their full range of naturally occurring sequences of behavior. It has long been theorized that cognitive capacities are revealed through the sequential structure of natural behavior, particularly its hierarchical organization. Progress in understanding the origins of this capacity has, however, been limited by a lack of techniques for identifying and measuring hierarchical structure in behavioral sequences. To fill this methodological gap, we introduce here an analysis pipeline for measuring hierarchical structure in sequential behavior. We then establish the validity of our approach by first applying it to chimpanzee percussive tool-use (PTU) sequences and comparing it to markov-simulated control sequences. Secondly, we apply our analysis to a dataset on PTU in humans and compare the hierarchical complexity of chimpanzee and human PTU. Despite decades of speculation, our study is the first empirical demonstration of hierarchical structuring in chimpanzee tool-use. We found chimpanzee PTU is characterized by a level of hierarchical complexity beyond that which can be generated through markov process, but is nonetheless systematically less hierarchically complex than human PTU, as expected. Altogether, our analyses demonstrate the potential for our approach to successfully detect and measure hierarchical structuring in natural sequences of behavior, which we believe will play a pivotal role in shedding light on old questions, as well as opening up entirely new lines of inquiry in the study of human and animal behavior.

The relentless evolution of SARS-CoV-2 underscores the urgent need to decipher the molecular principles that enable certain antibodies to maintain exceptional breadth and resilience against immune escape. In this study, we employ a multi-pronged computational framework integrating structural analysis, conformational dynamics, mutational scanning, MM-GBSA binding energetics, and the landscape-based frustration profiling of the RBD-antibody interactions to quantify the mechanisms of ultrapotent neutralization by a cohort of broadly reactive Class 1 antibodies (BD55-1205, 19-77, ZCP4C9, ZCP3B4) and the Class 4/1 ADG20 antibody. We reveal a unifying biophysical architecture driving binding for Class 1 antibodies that exploit pre-configured interfaces and distribute binding energy across extensive epitopes through numerous suboptimal yet synergistic interactions. Mutational scanning identifies a hierarchical hotspot organization where primary hotspots (e.g., H505, Y501, Y489, Y421), which overlap with ACE2-contact residues and incur high fitness costs upon mutation, are buffered by secondary hotspots (e.g., F456, L455) that are more permissive to variation. MM-GBSA energy decomposition confirms that van der Waals-driven hydrophobic packing dominates binding, with primary hotspots contributing disproportionately to affinity, while electrostatic networks provide auxiliary stabilization. Conformational and mutational frustration analyses demonstrate that immune escape hotspots reside in neutral-frustration "playgrounds" that permit mutational exploration without destabilizing the RBD, explaining the repeated emergence of convergent mutations across lineages. Our results establish that broad neutralization arises not from ultra-high-affinity anchors, but rather from strategic energy distribution across rigid, evolutionary interfaces. By linking distributed binding, neutral frustration landscapes, and viral fitness constraints, this framework provides a predictive blueprint for designing next-generation therapeutics and vaccines capable of withstanding viral evolution.

Racemic compounds, consisting of an equimolar mixture of enantiomers in crystalline form, are conventionally regarded as fully symmetric and are often dismissed as a trivial phenomenon due to their abundance-as they account for a substantial fraction (90 to 95%) of entries in structural databases. Here, we uncover the symmetry-breaking hierarchical organization within racemic compounds: single-handed molecules first self-assemble into homochiral domains, which then periodically self-organize with domains of opposite chirality to form the final crystal. Using a folded-plane model by applying isometry, we introduce a quantitative descriptor (angle θ) to probe symmetry breaking in racemic compounds, directly derived from crystal symmetry and unit cell parameters. We further develop a big-data analysis tool based on coset decomposition (a method of group theory) to comprehensively examine structural data from Cambridge Structural Database. Our analysis confirms the widespread occurrence of symmetry breaking in racemic compounds. This finding challenges the traditional view of racemic crystals as inherently symmetric, revealing their hidden complexity and potential implications for crystallography, materials science, and so on.

Noradrenergic projections from the locus coeruleus (LC) to the thalamus and anterior cingulate cortex (ACC) contribute to pain-like behaviors, yet their hierarchical organization remains unclear. This article examines how locus coeruleus-derived norepinephrine inputs to the paraventricular thalamic nucleus (PVA) and ACC differentially regulate nociceptive sensitization. In adult male and female mice, complete Freund's adjuvant was used to induce pain-like behaviors. To examine functional connectivity among locus coeruleus, PVA, and ACC, targeted recombination in active populations (Fos-TRAP), in vivo recordings, and viral tracing were combined. Then optogenetic and chemogenetic tools were used to selectively manipulate locus coeruleus projections and assess their impact on neural activity and pain behaviors. Complete Freund's adjuvant led to enhanced c-Fos expression in locus coeruleus, PVA, and ACC (cells per microscopic field; locus coeruleus: 13.60 ± 2.24 vs. 44.50 ± 7.72; PVA: 8.00 ± 1.58 vs. 66.40 ± 9.45; ACC: 12.80 ± 2.28 vs. 36.70 ± 2.59; P < 0.001), alongside increased γ-band activity and single-unit firing rates. Monosynaptic LC-ACC and polysynaptic LC-PVA-ACC circuits were identified. Notably, nociception-related locus coeruleus neurons preferentially projected to PVA, which subsequently targeted hyperactive ACC neurons. Under inflammatory pain conditions, activation of the LC-PVA-ACC circuits evoked greater ACC firing (Hz; LC-PVA-ACC vs. LC-ACC: 15.75 ± 2.88 vs. 9.72 ± 2.06; P < 0.001) and tactile stimulus-evoked responses (Hz; 22.98 ± 2.60 vs. 15.34 ± 1.86; P < 0.001) than direct LC-ACC activation. Consistently, optogenetic or chemogenetic manipulation of the LC-PVA-ACC circuit produced stronger modulation of mechanical and thermal pain sensitivity than direct LC-ACC stimulation. This study identified the LC-PVA-ACC pathway as a hierarchical noradrenergic circuit that modulates nociceptive sensitization via a thalamocortical relay, thereby revealing a circuit-specific mechanism by which the locus coeruleus-norepinephrine system regulates pain processing.

The development of the skull base during the fetal period is critical, as the configuration of the cavernous sinus, middle fossa, and paraclival triangles forms the basis for future neurovascular relationships relevant to skull base surgery. Despite their clinical importance, normative morphometric data for these regions during the second trimester are limited. This study aimed to characterize the anatomical organization of fetal skull base triangles and to evaluate whether their proportional arrangement and bilateral symmetry are established prenatally. Second-trimester fetal specimens were examined using microsurgical dissection under operative microscopy. The cavernous sinus, middle fossa, and paraclival triangles were identified according to established classifications, and bilateral area measurements were obtained using a digital caliper. Intraobserver reliability was assessed by repeated measurements and Pearson correlation analysis. No significant differences were observed between the right and left sides (P>0.05), indicating preserved bilateral symmetry at this developmental stage. Within each side, a consistent hierarchical organization was evident, with clinoidal and oculomotor-related triangles occupying proportionally larger areas, while middle-fossa triangles were smaller. High intraobserver reliability was demonstrated across all measurements. These findings indicate that the proportional and hierarchical organization of skull base triangles is already established during the second trimester, suggesting that fundamental surgical corridors of the anterior and middle cranial base are present well before birth. This normative data set provides a foundation for future anatomical, embryological, and neurosurgical studies.

Mental events are fundamental to daily cognition, including the recollection of past experiences, the anticipation of future scenarios, and engagement in imaginative, fictitious thought. Typically, these temporally extended mental events unfold within coherent spatial contexts, rich in naturalistic scenes and objects. However, there remains a significant gap in understanding how these events are represented in the brain. This study aimed to investigate the neural patterns involved in the construction of temporally extended mental events. Using ultra-high field functional magnetic resonance imaging, we examined brain regions previously implicated in this cognitive process, including the ventromedial prefrontal cortex (vmPFC), hippocampus, and posterior neocortex. We employed a novel experimental paradigm in which participants engaged in three forms of mental imagery: single objects (e.g., "a black espresso"), single scenes (e.g., "a busy café"), and extended scenarios (e.g., "meeting a friend for coffee"). We identified a shared neural network, comprising the vmPFC, hippocampus, and posterior neocortex, engaged across all forms of mental imagery. However, we observed a hierarchical organization in their contributions: the posterior neocortex supported the construction of objects, scenes, and scenarios, while the hippocampus primarily contributed to scenes and scenarios. The vmPFC exhibited a stepwise increase in activation, peaking during scenario construction. These findings suggest that the construction of mental events involves dynamic interactions between perceptual representations in the posterior neocortex, spatial coherence provided by the hippocampus, and integrative processes within the vmPFC. While the vmPFC may play a particularly prominent role in constructing temporally extended scenarios, it likely also contributes to the integration of elements within single scenes.

Mental events are fundamental to daily cognition, including the recollection of past experiences, the anticipation of future scenarios, and engagement in imaginative, fictitious thought. Typically, these temporally extended mental events unfold within coherent spatial contexts, rich in naturalistic scenes and objects. However, there remains a significant gap in understanding how these events are represented in the brain. This study aimed to investigate the neural patterns involved in the construction of temporally extended mental events. Using ultra-high field functional magnetic resonance imaging, we examined brain regions previously implicated in this cognitive process, including the ventromedial prefrontal cortex (vmPFC), hippocampus, and posterior neocortex. We employed a novel experimental paradigm in which participants engaged in three forms of mental imagery: single objects (e.g., “a black espresso”), single scenes (e.g., “a busy café”), and extended scenarios (e.g., “meeting a friend for coffee”). We identified a shared neural network, comprising the vmPFC, hippocampus, and posterior neocortex, engaged across all forms of mental imagery. However, we observed a hierarchical organization in their contributions: the posterior neocortex supported the construction of objects, scenes, and scenarios, while the hippocampus primarily contributed to scenes and scenarios. The vmPFC exhibited a stepwise increase in activation, peaking during scenario construction. These findings suggest that the construction of mental events involves dynamic interactions between perceptual representations in the posterior neocortex, spatial coherence provided by the hippocampus, and integrative processes within the vmPFC. While the vmPFC may play a particularly prominent role in constructing temporally extended scenarios, it likely also contributes to the integration of elements within single scenes.

G-quadruplexes are secondary, non-canonical RNA/DNA structures formed by guanine-rich sequences assembled into four-stranded helical structures by the progressive stacking of G-Tetrads, planar arrangements of guanines stabilised by monovalent ions such as [Formula: see text] or [Formula: see text]. Their stability plays a very important role in the prevention of DNA degradation, leading to the promotion or inhibition of specific biological pathways upon formation. In this work, we explore the occurrences of intermediates originating from the unfolding of these structures by using all-atom simulations, analyzing a small number of significant reaction coordinates to follow the evolution of the system by applying a mesoscopic simplification of the structures followed by two different dimensionality reduction techniques: Principal Component Analysis (PCA) and time-Independent Component Analysis (tICA). The data of the reduced trajectories are then encoded into a Complex Markov Network which, in conjunction with an Stochastic Steepest Descent, provides a hierarchical organization of the different nodes into basins of attraction. This procedure is able to reveal the main intermediates and the most relevant transitions the system undergoes in its denaturation path.

The resolution revolution in single particle cryo-electron microscopy (cryo-EM) has dramatically expanded our structural knowledge of large biomolecular complexes. While high-resolution cryo-EM density maps enable atomic model building, lower-resolution maps can still reveal secondary structures, folds, and domains. When combined with integrative modeling approaches, such data can provide meaningful insights into biomolecular structure and function. Constructing accurate models, however, remains challenging: at low resolutions it is difficult to interpret density maps features reliably, and at high resolutions traditional model-building workflows can become a time-consuming bottleneck. Deep learning, which is transforming problem-solving across scientific domains, offers powerful new tools to automate and accelerate this process. In this review, we discuss deep learning-based methods developed to automate model building in cryo-EM density maps, assessing their impact on streamlining structure determination. Recognizing that biomacromolecular structures exhibit hierarchical organization, we classify these methods according to their ability to model primary, secondary, tertiary, and quaternary structures of biomolecules. Deep learning tools for building atomic models in cryo-EM density maps are further grouped as de novo, where the model is predicted directly from features learned from the cryo-EM density, or hybrid, where it is derived by integrating structural templates with these features. We outline current limitations, including the challenge of obtaining sufficiently large and diverse datasets for training networks to model different types of biomolecules in the cryo-EM density maps, and the open challenge of constructing training sets that capture the conformational heterogeneity often observed in the cryo-EM maps. We conclude by highlighting emerging directions for this rapidly advancing field, which promise to make automated, data-driven model building an integral part of structural biology.

We investigate the emergence of chaos, bifurcation phenomena, and fractal phase-space structures in a high-energy relativistic Hamiltonian system subject to a periodically kicked electromagnetic field. The model is based on a modified relativistic dispersion relation incorporating Planck-scale corrections, leading to a nonlinear stroboscopic map that generalizes the classical kicked-rotor dynamics. By analyzing bifurcation diagrams and maximal Lyapunov exponents over a broad range of control parameters, we demonstrate that relativistic effects profoundly reshape the route to chaos. In particular, the presence of velocity saturation suppresses unbounded phase-space stretching, resulting in delayed bifurcations, truncated period-doubling cascades, and saturation of Lyapunov exponents even in strongly chaotic regimes. The system exhibits a rich mixed phase space characterized by the coexistence of chaotic seas, stable islands, cantori, and fractal basin boundaries, with transport properties that differ qualitatively from their nonrelativistic counterparts. Our results show that increasing the drift parameter enhances chaotic transport, while stronger relativistic corrections stabilize motion and preserve hierarchical phase-space organization. These findings highlight the fundamental role of modified dispersion relations in constraining instability and shaping chaos at high energy, providing new insights into nonlinear dynamics in relativistic and quantum-gravity-inspired systems.

Exercise improves cognition, mental wellbeing, and protects against neurodegeneration. However, most prior neuroscience studies have focused on localized brain changes without quantifying their impact on brain ageing. To quantify the effect of resistance training on brain health using longitudinal assessments. Using resting-state functional magnetic resonance imaging (rs-fMRI) data from 2,433 healthy adults, we trained models to predict brain age and applied them to 309 participants from the Live Active Successful Aging (LISA) randomized trial. Participants in this trial were assigned to one of three groups: heavy-resistance training, moderate-intensity training, or a non-exercise control group. They underwent repeated rs-fMRI and physical fitness assessments at baseline, with follow-up assessments at 1 and 2years. First, we examined changes in local connectivity between groups. Second, we assessed the impact of resistance training on brain ageing using brain clock models trained on the independent dataset of 2,433 adults. Local analyses revealed increased prefrontal functional connectivity following heavy training, while moderate- and heavy-resistance training significantly reduced brain age (-1.4 to -2.3years, pFDR < 0.05). These effects emerged at the whole-brain level, rather than within isolated networks such as the default mode, motor, or cerebellar systems. These findings suggest a hierarchical organization of brain aging, driven by distributed network-level changes and expressed through focal regional patterns. Resistance exercise training decelerates brain ageing, as indexed by brain clocks, reinforcing its role as a preventive strategy for brain health.

Abyssal hydrothermal vents are regarded as reactors for simple reduced carbon transforming into more complex forms of prebiotic organic chemistry. While the organic geochemical continuum and evolutionary transitions remain elusive, due to the intense hydrothermal alteration. We apply a metabolomics-inspired molecular fingerprinting strategy integrating mass spectral networking and hierarchical organization, to construct a molecular relatedness phylogenetic tree for vents from ultraslow-spreading Indian Ridge. Here we show that organic molecules from different vent fields and activity states share common molecular connection patterns. The observed progressive molecular evolution from alkanes through aromatics to complex heteroatom-bearing compounds reveals a systematic increase in molecular functionalization and polarity. This finding helps bridge the gap between simple reduced carbon and prebiotic molecular complexity, underscoring the role of hydrothermal systems in shaping life's essential feedstock on the primordial Earth. This framework may contribute to the search for life-markers on other astrobiological contexts, e.g., Mars, Enceladus,Callisto and Europa.

The genome is compacted in the nucleus through a hierarchical chromatin organization, ranging from chromosome territories to compartments, topologically associating domains (TADs), and individual nucleosomes. Nucleosome remodeling complexes hydrolyze ATP to translocate DNA and thereby mobilize histone proteins. While nucleosome remodeling complexes have been extensively studied for their roles in regulating nucleosome positioning and accessibility, their contributions to higher-order chromatin architecture remain less well understood. Here, we investigate the roles of two key nucleosome remodelers, esBAF and INO8°C, in shaping 3D genome organization in mouse embryonic stem cells. Using Hi-C, we find that loss of either remodeler has minimal effects on global compartment or TAD structures. In contrast, subcompartment organization is notably altered, suggesting that esBAF and INO8°C contribute to finer-scale chromatin topology. To overcome the limited resolution of Hi-C for detecting regulatory loops, we employed promoter capture Micro-C (PCMC), which revealed that the loss of esBAF or INO8°C alters a subset of promoter anchored looping interactions. Although these changes occur at distinct genomic loci for each remodeler, the affected sites are commonly enriched for bivalent chromatin regions bound by OCT4, SOX2, and NANOG (OSN), as well as BRG1 and INO80 themselves. Together, our findings reveal that esBAF and INO8°C selectively influence subcompartment identity and enhancer-promoter communication at key regulatory loci, highlighting a previously underappreciated role for nucleosome remodelers in higher-order chromatin organization.

Integrated Structural Analysis of Trunk Function Assessment After Stroke- New Evaluation Model Based on Multiscale Factor Analysis and Rasch Analysis.

Lignocellulosic biomass is one of the most abundant renewable carbon resources available, currently used predominantly for energy generation through direct combustion, yet still underutilized as a feedstock for higher-value biochemical conversion. Its structural complexity and intrinsic recalcitrance continue to challenge efficient biological processing. Overcoming these barriers requires an integrated understanding of plant cell-wall architecture, pretreatment chemistry, enzymatic mechanisms, and process engineering. This review provides a clear and conceptually grounded synthesis of these elements, illustrating how they converge to enable the development of second-generation (2G) lignocellulosic biorefineries. This review examines the hierarchical organization of cellulose, hemicelluloses, and lignin; the principles and performance of modern pretreatment technologies; the synergistic action of cellulolytic systems, including lytic polysaccharide monooxygenases (LPMOs) and non-hydrolytic proteins such as swollenins; advances in C5/C6 sugar fermentation; and emerging strategies for lignin upgrading. In addition to a comprehensive analysis of the literature, representative industrial and experimental case studies reported in the literature are discussed to illustrate practical process behavior and design considerations. By integrating mechanistic insight with industrially relevant examples, this review highlights the technical feasibility, current maturity, and remaining challenges of lignocellulosic biorefineries, underscoring their strategic role in enabling a competitive, low-carbon bioeconomy.