Search Results (6,164)

As multi-view datasets expand across diverse practical fields, feature selection (FS) has become an indispensable preparatory stage for machine learning models. Nevertheless, real-world multi-view data is often unlabeled and distributed among isolated clients, posing significant challenges to traditional centralized methods due to privacy concerns and communication constraints. Furthermore, existing centralized and federated approaches frequently suffer from entrapment in local optima and lack robust convergence guarantees. To address these issues, we propose Fed-MUFSHT, a federated framework for multi-view unsupervised FS (MUFS) that integrates tensor learning with a novel metaheuristic optimizer, Hierarchical-Cognitive Tianji’s Horse Racing Optimization (HC-THRO). Within the federated learning paradigm, Fed-MUFSHT follows a dual-stage local optimization process. Stage 1 applies HC-THRO, which integrates Hierarchical Competitive Learning and Adaptive Cognitive Mapping to simulate multi-level strategic competition and cognitive adaptation among individuals. This design enhances global exploration, adaptive learning, and fine-grained feature selection in high-dimensional spaces. Stage 2 employs a TL module based on canonical polyadic (CP) decomposition to perform missing-view imputation and refine latent representation learning. At the global level, a privacy-preserving aggregation strategy based on Normalized Mutual Information (NMI) and feature weights enables efficient model coordination without exposing raw data. Comparative experiments on several public benchmark datasets reveal that Fed-MUFSHT maintains clear advantages over strong competing methods, showing better optimization results together with more dependable convergence characteristics. The overall evidence suggests that the proposed approach is both robust and effective for distributed optimization tasks involving privacy protection. Full article

Early detection of bearing faults in rotating machinery is essential for ensuring system reliability and effective maintenance planning. Vibration signals inherently contain characteristic fault-related frequency components, providing rich information for both physically interpretable and data-driven analyses. In this study, a multi-representation and correlation-aware feature extraction framework is proposed for automatic classification of bearing faults from vibration signals. Experimental evaluations are conducted using the Case Western Reserve University (CWRU) Bearing Dataset. The dataset includes vibration recordings corresponding to inner race, outer race, ball faults, and healthy conditions under different damage severities. The proposed approach first applies Variational Mode Decomposition (VMD) to suppress noise and enhance frequency-related characteristics. Three different feature representations are then constructed: analytical spectral descriptors, raw Transformer-based deep representations, and a hybrid feature vector obtained by combining these two representations. The hybrid structure is further enhanced through regularized Canonical Correlation Analysis (rCCA), which models the relationship between Transformer representations and spectral descriptors, enabling correlation-aware feature fusion. Spectral, raw Transformer, and rCCA-enhanced hybrid feature vectors are evaluated separately using SVM, Random Forest, and XGBoost classifiers. The results demonstrate that both spectral and Transformer-based representations provide strong performance individually; however, integrating these complementary information sources while modeling their correlations leads to superior and more balanced classification performance. In particular, the rCCA-enhanced hybrid feature vector achieves the best results across all performance metrics. The findings indicate that combining physically meaningful frequency-domain information with data-driven deep representations yields a more robust and generalizable solution for bearing fault diagnosis. Full article

Intracellular calcium (Ca²⁺) signaling is a central regulator of corticogenesis, governing haveneural stem cell behavior, fate transitions, neuronal migration, and circuit assembly. Beyond its canonical role as a second messenger, Ca²⁺ shapes cytoskeletal organization by modulating microtubule dynamics essential for mitotic spindle function, radial glial scaffold, nucleokinesis, and neurite extension. This review synthesizes evidence from in vivo, ex vivo, and in vitro studies to delineate Ca²⁺-dependent pathways and Ca²⁺-binding proteins that couple, within restricted Ca²⁺ microdomains in space and time, to microtubule regulation during mammalian cortical development. We highlight mechanistic nodes involving calmodulin, Ca²⁺/calmodulin-dependent kinases (CaMKs), S100 proteins, cadherins/protocadherins, centrins (CENs), and Ca²⁺ sensors such as STIM1 and calneurons, which collectively coordinate spindle orientation, progenitor division modes, radial migration, and neurite outgrowth. Finally, we discuss how perturbations in Ca²⁺-controlled cytoskeletal programs may contribute to abnormal cortical cytoarchitecture and neurodevelopmental disease. By integrating Ca²⁺ microdomain transients with microtubule control modules, this review provides a unified framework for understanding how Ca²⁺ orchestrates key cellular events during mammalian corticogenesis and propose that Ca²⁺ oscillatory codes are translated into direct or indirect microtubule/cytoskeletal remodeling transitions that determine neural stem cell fate, migration, and maturation, to accurately establish cortical architecture and function. Full article

Osteoporosis is an age-related metabolic bone disorder characterized by an imbalance between bone resorption and formation. Natural polyphenols have gained attention as potential complementary strategies for its prevention. In this study, we investigated the effects of a sustainable, polyphenol-rich extract from red grape pomace (GPE) on human mesenchymal stem cell (MSC) fate and its underlying mechanisms of action. We found that GPE significantly promoted osteogenic differentiation while suppressing adipogenic differentiation in canonical bone marrow-derived MSCs (BMSCs). This biological effect was preserved in adipose tissue-derived MSCs (AdMSCs) obtained from elderly patients (>65 years) at high cardiovascular risk. Mechanistically, GPE downregulated adipogenic markers (PPARγ, CD36 and FABP4) and enhanced osteogenic markers (RUNX2, ALP, OSX, BMP-2, OPN, COL1A1 and OCN). Moreover, GPE activated NRF2-dependent redox signaling, as evidenced by increased NRF2 nuclear translocation and transcriptional activity. Accordingly, GPE treatment significantly upregulated, or consistently increased, the expression of multiple NRF2 target genes, including HO-1, GPX, CAT, GCLC, and NQO1. Importantly, pharmacological inhibition of NRF2 attenuated GPE-induced ALP activity, confirming NRF2 as a key mediator of its osteogenic effects. Overall, grape pomace-derived polyphenols act as upstream modulators of redox-sensitive and osteogenic transcription factors, rebalancing MSC differentiation toward osteogenesis and mitigating age-related bone fragility. Full article

This paper extends the metacybernetic framework by grounding its conceptual descriptions in first principles of information physics. We demonstrate that for living systems to organise efficiently under uncertainty, they must adhere to a strict recursive pattern, a “fractal seed” originating in the third-order interaction between potential and action. By utilising Fisher Information Field Theory (FIFT) within an Informational Realism paradigm, we formalise this process through variational analysis on an implicate–explicate manifold. Under a rigorous informational parsimony constraint (a functional analogue of the holographic principle), we treat the J-field as the dispositional reservoir of latent potential and the I-field as the operative field of structured configurations, and show how their autopoietic coupling generates the system’s Potential–Actuation trait poles as a scale-invariant viability structure This coupling reveals that the boundary substructure, which encodes the holographic content, directly conditions the emergent superstructure through a deterministic parity rule inherited from the dyadic logic of the minimal generic living system represented by ${\widehat{\theta }}_2$. Drawing on the application of Fisher Information, we show that maintaining informational parsimony requires the system’s architecture to oscillate: odd-numbered orders express two traits (dyads), whereas even-numbered orders express three (triads). This produces a canonical 2–3–2–3–2 sequence, preventing a combinatorial explosion of traits as systemic depth increases. We present the Cogitor5 model as a complete fifth-order exemplar of this rule, demonstrating how this rhythmic structural pattern enables self-evolution, systemic coherence, and collective intelligence in both biological and artificial agencies. Full article

Oxidative stress and redox imbalance are central features of both age-related neurodegenerative disorders and the persistent neurological sequelae of coronavirus disease 2019. Increasing evidence suggests that severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection disrupts neuronal redox homeostasis via mitochondrial dysfunction, iron dysregulation, inflammatory signaling, and the depletion of pyridine nucleotide pools. In that context, ferroptosis provides a unifying mechanistic framework linking lipid peroxidation to progressive neuronal injury. This review proposes that neuronal vulnerability might depend not only on the oxidative burden itself but also on the failure of membrane-localized antioxidant defenses. Particular emphasis is placed on the plasma membrane redox system (PMRS), a membrane-associated quinone-reducing network that can support coenzyme Q redox cycling and constrain lipid radical propagation at the plasma membrane. Unlike canonical ferroptosis defense systems that rely predominantly on NADPH, components of the PMRS, particularly cytochrome b5 reductase, can also use NADH, conferring partial metabolic flexibility in conditions of redox stress. We further discuss how SARS-CoV-2-induced NAD⁺ depletion might progressively destabilize this membrane-proximal defense architecture, potentially lowering the ferroptotic threshold of vulnerable neurons. Finally, we outline therapeutic strategies that might reinforce PMRS-dependent membrane redox control through NRF2 activation, NAD⁺ restoration, coenzyme Q-centered interventions, and modulation of iron-catalyzed lipid oxidation. Full article

Human–AI systems often involve repeated interaction among users, organizations, and AI components rather than isolated model outputs. In such settings, cooperation can be pursued either by changing agent incentives or by adding an explicit accountability layer. We formalize the Institutional Monitoring and Ledger (IML) framework, which augments a Markov game with monitoring, evidence logging, delayed settlement, and review while leaving the base dynamics unchanged. We derive conservative incentive checks that clarify how detection quality, review accuracy, settlement delay, and sanction size jointly shape deterrence and wrongful-penalty risk. We then provide pilot evidence in two canonical sequential social dilemmas, Harvest and Cleanup, using five agents, PPO training, five training seeds per condition, and comparisons against PPO, inequity aversion, social influence, and IML ablations. In these settings, IML avoided some of the optimization instability observed in the representative internalization baselines tested here, made monitoring error directly visible through ledger records, and showed how false positives can accumulate into a persistent welfare cost. Agent-level analyses in these symmetric environments found nearly uniform measured enforcement burden, while temporal analyses showed that late-stage enforcement is increasingly dominated by residual false positives. These results do not establish legitimacy in human-facing settings or deployment readiness. They instead position IML as a framework with pilot evidence for studying accountability mechanisms in cooperative human–AI systems and highlight measurement error, review design, and due process as central design constraints. Full article

Macrophages harness pattern recognition receptors (PRRs) to detect conserved bacterial components and mount effective immune responses. Many Gram-negative bacteria modify their lipid A structures to limit recognition by Toll-like receptor 4 (TLR4) and cytosolic Caspase-11 lipopolysaccharide sensors. One common evasion strategy is to reduce the lipid A acylation state from hexa- to tetra-acylation. This alteration can limit binding to receptors and dampen subsequent immune signaling responses, yet the proteomic alterations associated with this altered immunogenicity remain incompletely understood. Here, we systematically profiled proteomic alterations induced by extracellular or transfected hexa-acylated Kdo2-lipid A (Kdo2) and tetra-acylated lipid-IVa (IVa) to assess TLR4-dependent, TLR4-independent, and non-canonical inflammasome activation pathways. Kdo2 elicited stronger inflammatory responses in immortalized bone-marrow-derived macrophages (iBMDMs), as evidenced by robust TNF production, Caspase-11 cleavage, and IL-1α/IL-1β release. In contrast, IVa elicited minimal TNF secretion and failed to effectively induce non-canonical inflammasome activation. Global label-free quantitative proteomic analysis of iBMDMs stimulated with a low dose of immunogenic LPS displayed route-specific immune signatures: enrichment of TNF signaling, interferon-associated pathways, and mitochondrial metabolic remodeling. Equimolar amounts of low-acylated LPS failed to effectively induce these immune signatures, supporting a threshold-dependent model in which the lipid A structure and route of exposure define inflammatory progression. Collectively, our findings provide mechanistic insight into how lipid A structural variation modulates macrophage immune programming and cytosolic inflammasome activation. Full article

The Landauer principle motivates the definition of economic temperature as the monetary price of processing a bit irreversibly. No empirical test of this definition exists in transparent fee markets. This paper fills that gap using daily Bitcoin and Ethereum data, constructing canonical thermodynamic state variables and evaluating five diagnostic layers: state variable behavior, Maxwell-type integrability, Carnot-style efficiency bounds, nonlinear regime separation, and structural break sensitivity to protocol events. Bitcoin’s log-temperature behaves as a persistent mean-reverting process with an AR(1) coefficient of 0.97 and a half-life of 21 days; Ethereum is highly persistent, with weaker formal evidence of stationarity than Bitcoin. Maxwell integrability is frequency-dependent: Bitcoin passes all four relations at monthly frequency, whereas Ethereum passes two of four. Carnot-style evidence is the strongest: realized fee extraction efficiency stays well below the implied bound, with daily compliance exceeding 97% on both chains. Structural breaks around Bitcoin ordinals, EIP-1559, the merge, and Shanghai confirm that protocol changes reorganize the temperature relation. The thermodynamic framework provides structure that standard fee market analysis does not, including a first principles efficiency bound and a state space coherence test. The findings provide partial, frequency-dependent, and chain-specific empirical support for a Landauer-based thermodynamic description of blockspace markets. Full article

We evaluated the antimicrobial and antioxidant capabilities of a bacteriocin purified from a recently identified marine Lactococcus lactis (L. lactis) NAN6399 strain, a lactic acid bacterium recovered from Mediterranean coastal waters near Alexandria, Egypt, and identified by combined API 50 CHL phenotypic profiling and 16S rRNA gene sequencing. Bacteriocin purification was achieved by sequential ammonium sulfate precipitation and reverse-phase high-performance liquid chromatography (RP-HPLC). The purified bioactive fraction had an approximate molecular weight of 20 kDa by SDS-PAGE and a 106-amino-acid N-terminal sequence that, upon BLAST alignment, returned 98.1% overall identity to the Lactococcin 972 family bacteriocin AAK06118.1 from L. lactis IL1403, with divergence confined exclusively to the terminal two C-terminal residues. This sequence is structurally and functionally distinct from canonical Lcn972 (L. lactis IPLA 972): the two peptides share an identical 25-residue signal peptide but diverge entirely in their mature bioactive domains, which exhibit only 9.1% sequence identity. Canonical Lcn972 operates through Lipid II-mediated septum disruption and inhibits only Lactococcus species; the NAN6399 peptide, correctly designated as a novel member of the Lcn972-like peptide family, demonstrated broad-spectrum antimicrobial efficacy against multiple indicator organisms (Staphylococcus aureus, Salmonella typhimurium, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, and Enterococcus faecalis), producing inhibition zones of up to 30 mm and minimum inhibitory concentration (MIC) values as low as 1.25 μg/mL against S. aureus. Antioxidant capacity was assessed using the DPPH radical scavenging assay, with the purified preparation achieving 73.14 ± 0.34% inhibition. Collectively, these data establish L. lactis NAN6399 as the producer of a bifunctional Lcn972-family bacteriocin with both antimicrobial and antioxidant potential, provide the first experimental characterization of the antimicrobial activity of this Lcn972-family branch, and highlight marine LAB as a productive reservoir for novel bioactive peptide discovery. Full article

Exposure to high-altitude hypoxia leads to complex physiological and molecular adaptations, particularly in skeletal muscle. MicroRNAs (miRNAs), including muscle-enriched (myomiRNAs) and hypoxia-responsive (hypoxamiRNAs), play critical roles in regulating these responses. We investigated miRNA expression changes in the skeletal muscle of healthy, non-smoking Italian adults (mean age 36.7 ± 12.4 years) participating in the Himalayan expedition “Lobuche Peak—Pyramid Exploration & Physiology” conducted in the Sagaramāthā (Mount Everest) National Park, Nepal. The peak overnight stay altitude was ≈5000 m at the Pyramid International Laboratory—Observatory. Muscle biopsies were taken before and after the expedition from Vastus lateralis, at one-third of the distance from the upper margin of the rotula to the anterior superior iliac spine. Small RNA sequencing was used to profile differentially expressed miRNAs. Several miRNAs were differentially expressed (exploratory analysis), suggesting potential involvement in hypoxia-related adaptation. These encompass both canonical myomiRNAs (e.g., miR-206, miR-486-5p) and hypoxamiRNAs (e.g., miR-378a-5p, miR-199a-3p, let-7b-5p). In enrichment analysis, we found several connections between miRNAs and pathways that may play a role in physiological regeneration or differentiation in muscle cells. Among functions, focal adhesion (p-value = 0.001), regulation of actin cytoskeleton (p-value = 0.026), Rap-1 (p-value = 0.007), cAMP (p-value = 0.017), MAPK (p-value = 0.019), and Hippo (p-value = <0.001) signaling pathways were predicted to be the most targeted. These findings provide preliminary insights into physiological adaptation, requiring confirmation in larger and controlled cohorts. Full article

Nuclear factor kappa B (NF-κB) signaling plays a central role in inflammation, immunity, cell survival, and cancer progression. Its constitutive activation is frequently observed in breast cancer, contributing to tumor growth, treatment resistance, and metastasis. MicroRNAs (miRNAs) are key post-transcriptional regulators of gene expression and may modulate NF-κB signaling in a subtype-specific or -independent manner. The aim of the study was to identify miRNAs that may potentially regulate the activity of genes associated with NF-κB signaling across five molecular subtypes of breast cancer in Polish women. Tumor and matched normal tissue samples were collected from 405 patients with five breast cancer subtypes: luminal A (n = 130), HER2-negative luminal B (n = 100), HER2-positive luminal B (n = 96), non-luminal HER2-positive (n = 36), and triple-negative breast cancer (TNBC, n = 43). Expression profile of selected NF-κB-related genes were evaluated using mRNA microarrays and RT-qPCR. Protein levels were assessed by ELISA. Candidate regulatory miRNAs were identified via miRNA microarrays and validated using the miRDB database. A consistent upregulation of MAP3K7, TAB2, TNFAIP3, CSNK2A1, BCL2L1, XIAP, CXCL2, and PLAU was observed across all subtypes, suggesting activation of canonical NF-κB signaling. Downregulation of specific miRNAs, miR-1297 and miR-30a (targeting MAP3K7), miR-134 (TAB2), miR-125b (TNFAIP3), and miR-4329 (XIAP), may contribute to this deregulation. For CSNK2A1, BCL2L1, CXCL2, and PLAU, no regulatory miRNAs meeting our criteria were identified. Our study reveals a subtype-independent activation of the canonical NF-κB signaling pathway in breast cancer, underpinned by consistent upregulation of key components (at both the transcript and protein levels. Dysregulation of specific miRNAs likely contributes to this altered gene expression. These findings suggest the presence of a common NF-κB-driven oncogenic program across molecular subtypes, with potential implications for developing miRNA-based therapeutic strategies targeting inflammation, survival signaling, and treatment resistance in breast cancer. Full article

Tropodithietic acid (TDA) is a sulfur-containing secondary metabolite with pronounced antimicrobial activity that has been primarily described in marine Alphaproteobacteria of the Roseobacter clade. Despite extensive studies of these bacteria, the occurrence and genetic organization of the TDA biosynthetic pathway in other bacterial groups remain poorly understood. In this study, we report the production of TDA by the freshwater bacterium Janthinobacterium sp. PLB04 isolated from diseased cell cultures of the primmorphs from the Baikal sponge Lubomirskia baikalensis. The presence of a TDA biosynthetic gene cluster homologous to the canonical tda operon previously described in the marine Roseobacter clade was found in Janthinobacterium sp. PLB04 by genome mining with bioinformatic analysis. However, comparative analysis of the cluster architecture demonstrated the absence of the gene tdaC in the Janthinobacterium sp. PLB04 genome. Despite this difference, the strain retained the ability to synthesize TDA. TDA was extracted from the culture medium and identified using chromatographic and MALDI-TOF mass spectrometric analysis. These results suggest that tdaC may not be strictly required for TDA biosynthesis in this strain and may be functionally replaced with alternative enzymatic steps or functional redundancy within the pathway. The discovery of TDA production in a freshwater Janthinobacterium strain expands the known phylogenetic and ecological diversity of TDA-producing bacteria and provides new insights into the plasticity of the TDA biosynthetic gene cluster. Full article

Secret sharing schemes distribute a secret among participants so that only authorised subsets can reconstruct it. In this paper, we focus on space-efficient secret sharing and show that matrix normal forms can significantly reduce share sizes while achieving computational security properties. Our scheme is implemented within an online secret sharing architecture, where authenticated public data P is maintained and shares of private data Q are issued over a secure channel. We study an existing probabilistic matrix-based approach to share size reduction and prove that the expected number of iterations of the underlying cyclic vector algorithm is small, yielding an expected polynomial runtime. We then design a novel deterministic method based on the Frobenius canonical normal form, avoiding reliance on cyclic vector techniques, and derive its runtime complexity. This yields a space-efficient secret sharing scheme that is computationally secure under a suitably defined adversary model. We have implemented our algorithm in the computer algebra system Maple as an Open Source project and provide an evaluation of its performance. Our results demonstrate that matrix normal forms can provide a suitable mathematical framework for secure and practical secret sharing. Full article

The H5N1 subtype of highly pathogenic avian influenza (HPAI) poses a major zoonotic threat due to its high fatality rate and capacity for cross species transmission. In early 2025, Argentina detected a novel triple reassortant A(H5N1) virus in Chaco Province, combining Eurasian, North American, and South American lineage segments. Genomic analyses of subsequent outbreaks in Buenos Aires and Entre Ríos confirmed persistence of this reassortant and additional HA substitutions (T204K, P251S) potentially linked to increased mammalian receptor affinity. Although PB2 sequences lacked canonical mammalian-adaptive markers (E627K, Q591K, D701N), all contained I292M, a mutation associated with human adaptation. Phylogenetic analyses revealed distinct genotypes and increasing divergence. These findings indicate ongoing viral evolution and adaptation within Argentina, emphasizing the urgent need for sustained genomic surveillance, timely data sharing, and integrated One Health strategies to mitigate zoonotic and socioeconomic risks associated with H5N1 spread in South America. Full article