Abstract: Heart failure (HF) is a heterogeneous clinical syndrome in which abnormalities of myocardial relaxation, contractile performance, and neurohormonal activation contribute variably across disease phenotypes and stages. While advanced heart failure with reduced ejection fraction (HFrEF) is dominated by impaired systolic function and low cardiac output, heart failure with preserved ejection fraction (HFpEF) and earlier disease stages are primarily characterized by diastolic dysfunction, increased myocardial stiffness, and elevated filling pressures. These distinctions have important therapeutic implications, particularly with respect to lusitropic versus inotropic strategies.β₃-adrenergic receptors (β₃-ARs) exhibit signaling properties distinct from classical β₁- and β₂-receptors and are increasingly recognized as modulators of cardiovascular function under pathological conditions. β₃-AR activation preferentially engages nitric oxide–cyclic guanosine monophosphate pathways, promoting vasodilation, reducing oxidative stress, and enhancing myocardial relaxation, albeit with mild context-dependent negative inotropy. Experimental and early clinical data suggest that β₃-AR agonism may be beneficial in clinical settings dominated by impaired relaxation and elevated filling pressures, including HFpEF and pulmonary hypertension.Conversely, sustained β₃-AR signaling in advanced systolic HF may contribute to contractile depression, mitochondrial dysfunction, and energetic inefficiency. Preclinical and translational studies indicate that selective β₃-AR antagonism can improve systolic performance and myocardial energetics without increasing heart rate or adrenergic drive, positioning β₃ blockade as a potential “smart inotropic” strategy.This review proposes a physiology-guided, stage-dependent framework for β₃-adrenergic modulation in HF, in which agonism and antagonism represent complementary therapeutic approaches tailored to dominant pathophysiology rather than opposing strategies.

Abstract: Article 136 of the newly revised Law of the People's Republic of China on Penalties for Public Order Violations establishes a ‘system for sealing public order violation records,’ with the provision that ‘records of public order violations such as drug use may be sealed’ provoking significant public debate. Against this backdrop, Professor Yin Bo of China University of Political Science and Law has repeatedly engaged with media interviews to offer a systematic theoretical defence of the sealing system. He emphasises its alignment with principles such as proportionality, protection of personal dignity, and the integration of punishment with education, positioning it as a preliminary exploration of a ‘criminal record expungement system’. This article, after comprehensively reviewing Yin Bo's principal arguments and the new legal provisions, introduces a Marxist legal analysis framework, Xi Jinping Thought on the Rule of Law and the overall national security outlook, alongside formal logic and argumentation theory, to conduct a systematic critical analysis of his reasoning. The article contends: Firstly, from the perspective of class analysis and social structure, abstracting the sealing system as ‘universal rights protection’ risks obscuring its asymmetrical benefits within existing power structures. This may objectively reinforce ‘secondary protection’ for privileged classes while exacerbating relative insecurity among ordinary workers. Second, from the perspective of Xi Jinping Thought on the Rule of Law and key discourses on drug control, the fundamental stance of ‘putting people at the centre’ and ‘zero tolerance for drugs’ demands a higher degree of preventive prudence in balancing rights protection and public security. Yet Yinbo's argumentation significantly underestimates the external risks associated with high-risk behaviours such as drug use. Third, logically, the argument confuses categories (‘minor offences—general offences—high-risk offences’), commits the fallacy of ‘generalising from the particular’ by extrapolating systemic overreach from individual injustices, and deliberately blurs the conceptual distinction between ‘record sealing’ and ‘expungement of criminal records’. This paper ultimately advocates: while upholding the positive role of the sealing system in ‘correcting labelling discrimination,’ it is imperative to strictly differentiate between types of conduct and occupational risks. A systemic combination of ‘tiered sealing + meticulous review + rigid accountability’ should be established to genuinely achieve an institutional equilibrium that both aligns with the direction of building a China governed by law and does not undermine the overall defence of the people's war on drugs and national security in the new era.

Abstract:

Despite significant advances in bank regulation and the widespread adoption of macroprudential frameworks, emerging market economies remain persistently vulnerable to global financial shocks. Episodes such as the Global Financial Crisis, the COVID-19 market turmoil, and recent monetary tightening cycles reveal that financial stress originating in core markets continues to transmit rapidly and forcefully to emerging economies. This paper argues that such vulnerability reflects structural features of contemporary financial systems rather than deficiencies in domestic banking regulation alone. Adopting a conceptual and analytical approach, the article develops an integrated framework of macro-financial blind spots that links global financial cycles, non-bank financial intermediation, and regulatory fragmentation. The analysis highlights how funding liquidity, collateral valuation, margin dynamics, and market-based leverage amplify global shocks through channels that lie largely outside traditional, bank-centric macroprudential frameworks. As market-based finance expands, systemic risk increasingly originates in activities rather than institutions, limiting the effectiveness of entity-based regulation and reinforcing emerging markets’ role as price-takers in global portfolios. The paper contributes to the literature by synthesizing insights from macroprudential policy, market liquidity, and non-bank finance to explain the persistence of emerging market vulnerability in an era of globalized funding. It further derives policy implications for macro-financial governance, emphasizing the need for system-wide, activity-based approaches, improved data and transparency, and stronger domestic and international regulatory coordination. These findings are relevant for policymakers seeking to reconcile financial integration with systemic resilience in emerging markets.

Abstract: Reversible thermochromic materials change color in response to temperature variations and hold significant potential in smart textiles. Their reversible color-changing property not only offers temperature indication and enhances textile performance, but also pro-motes smart textile development. This is achieved by improving the intelligence, mul-tifunctionality, and environmental adaptability of textiles. This review summarizes the characteristics and recent advancements of reversible thermochromic materials, including organic, liquid crystal (LC), inorganic, and photonic crystal (PC) types. It emphasizes recent progress in integrating these materials into textiles through techniques such as microencapsulation, printing and dyeing, and fiber fabrication. Furthermore, the review systematically examines applications of reversible thermochromic materials in smart textiles, covering areas such as anti-counterfeiting, temperature-sensitive regulation, and aesthetic enhancement. Current challenges, including limited stability, inadequate wash durability, and low color sensitivity, are also addressed, alongside potential development directions. The aim of this review is to provide a theoretical foundation and technical guidance for designing and developing reversible thermochromic smart textiles.

Abstract: Obsessive-compulsive disorder (OCD) remains treatment-resistant in 40–60 % of patients despite optimised serotonin-reuptake inhibitor therapy and antipsychotic augmentation. Emerging evidence points to glutamatergic dysregulation in cortico-striato-thalamo-cortical circuits as a core driver of rigid, maladaptive synaptic patterns. The Cheung Glutamatergic Regimen (CGR)—a fully oral, low-cost combination of dextromethorphan (NMDA antagonism), a CYP2D6 inhibitor (to prolong DXM exposure), piracetam (AMPA positive allosteric modulation), and optional L-glutamine (glutamate replenishment)—aims to replicate the rapid neuroplastic cascade triggered by intravenous ketamine. Naturalistic case series and individual reports from routine practice describe rapid reductions in obsessive intensity and ritual frequency, often within days to weeks, particularly when CYP2D6 inhibition is sustained and piracetam is added. Most side effects are mild, like temporary tremors, fast heartbeats, and trouble sleeping. However, serotonin toxicity and hypomanic activation need close monitoring. The evidence is uncontrolled and only based on one clinician's experience, though it is promising.

Abstract: The TCGS-SEQUENTION framework maps diverse ``dark'' anomalies---galactic rotation curves in physics and convergent evolutionary design in biology---to a single geometric origin: the extrinsic response of a 3-D shadow manifold $\Sigma$ embedded into a static 4-D counterspace $\mathcal{C}$ by a projection map $X$. In its present form, the framework treats the extrinsic constitutive law (the $\mu$-function) as an empirically constrained response that remains materially unspecified. Here we show that the recent theory of evolution by natural induction (NI) provides a concrete micro-physical mechanism: any high-dimensional network with slightly viscoelastic interactions and intermittent perturbations exhibits a second-order relaxation (creep of interaction parameters) that implements an associative inductive bias without natural selection. We formalize a dictionary between NI and TCGS and prove a regime correspondence between material state and projection permeability. Crucially, we argue that the ``low-gradient'' sectors---often misidentified as dynamical modifications---are actually the shadow of \textbf{elastic stiffness (the un-yielded state)} in the projection substrate, whereas standard Newtonian behavior emerges from \textbf{viscoelastic yielding} (plastic flow) at high gradients. Because NI is fundamentally a two-level relaxation, its reliance on ``timescales'' is reinterpreted in TCGS as geometric depth in $\mathcal{C}$, strictly preserving the axiom that time is a gauge artifact. This reframing resolves the ``ecosystem anomaly'' highlighted by NI---adaptive organization without reproduction---as a natural consequence of Whole Content on $\mathcal{C}$. Finally, we introduce two cartographic inquiries diagnostic of a viscoelastic micro-physics: (P6) a Williams-Landel-Ferry (WLF) signature in adaptation rates; and (P7) enriched convergent ``associative'' correlates beyond functional utility. Under this mapping, ``chance'' is not denied but recast as slice-level sampling of deterministic creep in the source geometry.

Abstract: Digital sustainable marketing is used by firms to communicate environmental efforts through social media and e-commerce platforms, yet its effectiveness in shaping green choices remains unclear in emerging markets like Saudi Arabia. This study investigates how digital sustainable marketing influences green consumer choices directly and indirectly through green perceived value and green skepticism. A cross-sectional survey was administered to 400 Saudi consumers who use digital channels and purchase offerings promoted as green or sustainable. Data were analyzed using partial least squares structural equation modelling. The results show that digital sustainable marketing has a significant positive effect on green consumer choices and on green perceived value, while it reduces green skepticism. Green perceived value increases, and green skepticism decreases, green consumer choices. Both mediators partially transmit the impact of digital sustainable marketing on green consumer choices, revealing a value-enhancing path and a skepticism-reducing path operating in parallel. The study contributes by integrating positive and negative psychological mechanisms into a single dual-path model of digital sustainable marketing and by providing evidence from the Saudi market. The findings offer guidance for designing digital sustainability campaigns that enhance perceived value while limiting skepticism to accelerate green consumption.

Abstract: We propose a novel mathematical framework for understanding conscious experience based on the topology of 4-manifolds and the theory of Painlevé transcendents, with deep connections to quantum field theory and topological quantum field theory (TQFT). We conjecture that consciousness emerges through a \emph{two-stage quantum-to-classical transition}: pre-conscious processing corresponds to the $I_0^*$ fiber (dual graph $\tilde{D}_4$) of Painlevé VI (PVI); an intermediate quantum ``bipolar'' state corresponds to the $I_1^*$ ``fishtail'' fiber ($\tilde{D}_5$) of Painlevé V (PV), characterized by two bordered cusps representing coexisting quantum modes; and full classical consciousness corresponds to the $I_2^*$ fiber ($\tilde{D}_6$) of PVdeg (equivalent to $\text{PIII}^{D_6}$), with a single cusp representing unified percept. Each stage is modeled as a coalescence of punctures or cusp-removal on a Riemann sphere: symmetry-breaking transitions analogous to phase transitions in gauge theories on 4-manifolds. This topological structure is not arbitrary: 4-manifolds play a central role in quantum field theory, Painlevé equations arise naturally in quantum integrable systems, and the monodromy groups in our framework are mathematically identical to gauge holonomy in Yang-Mills theory. We demonstrate through WKB (semiclassical) analysis that the fishtail fiber ($I_1^*$) of PV naturally generates gamma-band oscillations (30-80 Hz) with temporal characteristics matching empirical observations of neural gamma bursts. The key insight is that gamma oscillations emerge at the \emph{quantum intermediate stage} (PV, fishtail): the PVI $\to$ PV transition initiates coherent oscillations, while the subsequent PV $\to$ PVdeg transition (cusp removal) represents the classical collapse from bipolar quantum superposition to unified classical percept. This provides a potential mathematical realization of Penrose-Hameroff Orch-OR theory while making testable predictions about observable neural activity. Our framework unifies concepts from Seiberg-Witten theory, topological quantum computation, and neuroscience, suggesting that consciousness may be fundamentally describable as a quantum-to-classical phase transition on a 4-dimensional spatiotemporal manifold with singularity structure governed by integrable systems.

Abstract:

Tau protein is a nonspecific marker of neurodegeneration, and its phosphorylated form, ptau-181, is specifically associated with Alzheimer's disease (AD). Calculating the ratio of the phosphorylated form to total tau protein can help distinguish AD from other tauopathies or neurodegeneration, as well as reduce the impact of individual differences in total tau protein levels. This also allows for monitoring and comparing the dynamics of changes within the same patient. For this purpose, two SPRi biosensors were constructed, sensitive to the proteins described: total tau and ptau-181 for plasma determinations. The use of these biosensors requires prior sensor validation, during which specific parameters of the analytical method are established. A study of the optimal concentration of the receptor layer in which particular antibodies were immobilized found that the optimal concentration for total tau protein determinations was 1000 ng/mL. For ptau-181, it was 90 ng/mL. Biosensor layer formation was confirmed by analysis over a wide angle range, which enabled the generation of SPR curves. The dynamic range of the sensors is 1–50 pg/mL for total tau and 1–100 pg/mL for ptau-181. The limits of detection are 0.18 pg/mL and 0.037 pg/mL, respectively. Low standard deviation (SD) and coefficient of variation (CV) values indicate good precision and accuracy of the results obtained using the SPRi biosensors. Specificity testing confirmed that no interferents influenced the assay. The method is therefore suitable for researching biological materials, such as blood plasma. Proteins were thus measured in the blood plasma of AD patients and controls. Statistical analysis revealed significant differences in the concentrations of tau and ptau-181 protein in both groups. The calculated ptau/total tau ratio for both sample groups also demonstrated high statistical significance. This suggests that a high ratio may be characteristic of AD. However, more extensive analysis is needed to obtain cutoff values. The ROC curves indicate that both biosensors have good diagnostic utility, with lower specificity for total tau.

Abstract: Muscle regeneration following injury reveals a striking paradox: the same phenomenon, fiber branching, can serve as both a beneficial adaptation in healthy muscle and a pathological hallmark in disease. In healthy muscle, branched fibers emerge as an adaptive response to extreme mechanical loading, redistributing stress, enhancing hypertrophy, and protecting against injury. Conversely, in conditions such as Duchenne Muscular Dystrophy, excessive and complex branching contributes to mechanical weakness, increased susceptibility to damage, and progressive functional decline. This review explores the dichotomy of fiber branching in muscle physiology, synthesizing current research on its molecular and cellular mechanisms. By understanding the paradoxical nature of fiber branching, we aim to uncover new perspectives for therapeutic strategies that balance its adaptive and pathological roles to improve outcomes for muscle diseases.

Abstract:

Rapid phylogenomic analysis is essential for outbreak surveillance and large-scale viral comparative genomics, yet conventional alignment-based workflows remain computationally intensive and difficult to deploy at scale. Covary is a computational framework designed for large-scale biological sequence analysis. It is a translation-aware, alignment-free machine learning framework that encodes genomic information into biologically informed vector representations, enabling efficient genome-scale comparison without multiple sequence alignment (MSA). Here, Covary was applied to thousands-scale analysis of outbreak-causing viral genomes to assess its scalability and biological resolution. A total of 4,000 complete genomes of SARS-CoV-2, dengue virus, measles virus, and alphainfluenza virus were retrieved from the NCBI Viral Genomes Resource, of which 3,831 passed quality filtering and were analyzed using Covary. Results showed that Covary rapidly processed all genomes and consistently grouped sequences according to expected taxonomic assignments and known ingroup structure, including SARS-CoV-2 Pango lineages, dengue virus subtypes, measles virus geographic origin, and alphainfluenza virus clades. Covary completed the analysis in 45 minutes on free-tier Google Colab, inferring genome-wide relationships using modest computational resources. These results demonstrate that Covary enables rapid, alignment-free phylogenomic analysis of thousands of outbreak-causing viral genomes without requiring advanced computational infrastructure. In conclusion, Covary represents a scalable, deploy-ready machine learning pipeline for genome-informed outbreak surveillance and monitoring systems.

Abstract: The ongoing miniaturization of electronic systems and the increasing demand for sustainable, autonomous technologies driven by the Internet of Things (IoT) highlight the importance of efficient, ultra-low-power energy harvesting devices. This study evaluates fifteen such devices manufactured by five of the eight industry leaders. The study assesses the technological suitability of these devices for small-scale, intelligent, autonomous seed germination systems. The evaluation is based on a flexible, practical, multicriteria analysis framework that incorporates a broad set of criteria related to the context of the case study system. The framework also considers the functional and operational limitations of the low-power energy harvesters under analysis. The findings suggest that a comprehensive and transparent methodological approach can generate a prioritized list of energy harvesters aligned with the case study system. This list facilitates selecting the most suitable energy harvesters for IoT-based, small-scale seed germination systems. The analysis demonstrates the feasibility of systematically and structurally selecting the analyzed energy harvesting devices while considering conflicting technical, economic, and environmental priorities. Finally, the study emphasizes that distinct device prioritization lists can emerge when the scope or objective of the project changes because these alterations impact the set of evaluation criteria, their ranking, and weighting. This study outlines a structured evaluation framework that can be adapted to different contexts to facilitate technology selection. Technology researchers and practitioners can use this replicable, auditable tool to identify the advantages and disadvantages of incorporating technology into specific projects.

Abstract: This paper is dedicated to long term atmospheric corrosion behaviour of magnesium alloys. Five different magnesium alloys namely AZ31, AM60, AZ61, AZ80 and AZ91 were exposed for 4 years under harsh conditions at the marine corrosion site of Brest (France). From the results, the corrosion performance increased in the following order: AZ31<AM60<AZ91<AZ61<AZ80. The corrosion was highly localised during the first year of exposure, but more general corrosion prevailed after long term of exposure. All materials followed a power law with rather similar kinetics of corrosion. The observed difference in the corrosion performance of the alloys was explained by the amount of secondary phases as well as that of the Al-content in the α-Mg phase.

Abstract: Faizal et al. (2025) argue that Gödel–Tarski–Chaitin limits render a purely algorithmic Theory of Everything impossible, concluding that the universe cannot be a computer simulation. We demonstrate that this conclusion commits a quantifier overreach by conflating two distinct notions: (i) algorithmic simulation, which attempts to compute all truths about the fundamental layer, and (ii) projection simulation, which approximates observables on a well-posed shadow manifold. Within the Timeless Counterspace and Shadow Gravity (TCGS-SEQUENTION) framework, we show that the 4-D counterspace C functions as the Tarskian “semantic truth” (the Territory), while the 3-D shadow Σ constitutes “syntactic provability” (the Map). Undecidability theorems constrain the Map, not the Territory. Crucially, the TCGS framework provides a concrete geometric instantiation of the “Meta-Theory of Everything” (MToE) that Faizal et al. invoke abstractly: the projection map X : Σ → C plays the role of their external truth predicate T(x), grounding non-algorithmic truths in geometric structure rather than meta-logical assertion. We prove three main results: (A) the undecidability-based no-go theorem applies only to algorithmic simulations targeting the Territory; (B) the shadow manifold Σ admits well-posed dynamics under a single extrinsic constitutive law, rendering all empirical observables computably approximable to arbitrary accuracy; (C) the inference from “no algorithmic simulation of C” to “no simulation whatsoever” is a formal quantifier error. We conclude that non-algorithmicity at the source is fully compatible with deterministic, simulable shadow phenomenology—and that quantum complementarity, dark-sector phenomenology, and biological convergence all manifest as projection artifacts of this same geometric architecture.

Abstract: In this study, we investigated the effect of annealing ultrathin silver (Ag) films of varying thicknesses (1–6 nm) on both their optical absorption and the performance of poly(3-hexylthiophene-2,5-diyl) (P3HT) and [6,6]-phenyl-C61-butyric acid methyl ester (PCBM) organic solar cells (OSCs). The Ag films were deposited on indium tin oxide (ITO) anodes and annealed at 300 °C for 1–2 hours to modify the anodic interface. The optical and electrical properties of the resulting devices were systematically characterized and optimized. The results revealed that a 1 nm AgO layer annealed for 2 hours significantly enhanced the device performance, yielding a 6% increase in power conversion efficiency compared to the standard configuration. This improvement is attributed to two main factors: (i) a 25% increase in light absorption of the AgO/P3HT:PCBM film due to localized surface plasmon resonance of Ag nanoparticles, and (ii) an 11% reduction in series resistance resulting from the favorable alignment of the Ag work function with the ITO anode and the polymer HOMO, which facilitates efficient hole extraction. These findings highlight the potential of ultrathin, annealed Ag/AgO interfacial layers as an effective strategy to enhance light absorption and charge transport in OSCs.

Abstract: The Greater Caribbean manatee is classified as vulnerable, yet the lack of data related to population status in the Costa Rican Caribbean severely hinders conservation policy due to limited ecological knowledge. This study aims to address this challenge by refining a pipeline for the automated manatee count method to enhance classification robustness and efficiency for accurate spatial and temporal density estimation. The bioacoustics analysis consists of a deep learning manatee call detector and an unsupervised individual manatee counting. Methodologically, we implemented an offline feature extraction strategy to avoid a substantial initial computational bottleneck, measured at almost 13h, required to convert 43,031 audio samples into labeled images. To mitigate the high risk of overfitting associated with class imbalance, common in bioacoustic databases, a bootstrapping method was applied post-data splitting, generating a labeled dataset of 100,000 spectrograms. Transfer learning with the VGG-16 architecture yielded superior results, achieving a robust mean 10-fold cross-validation accuracy of 98.94% (±0.10%) and normalized F1-scores of 0.99. Furthermore, this optimized fine-tuning was rapidly executed in just 22min and 36s. Subsequently, the unsupervised individual manatee counting utilized k-means clustering on the top three music information retrieval descriptors along with dimensionality reduction, successfully segregating detected calls into three acoustically distinct clusters, likely representing three individuals. This performance was validated by a silhouette coefficient of 79.03%. These validated results confirm the refined automatic manatee count method as a robust and scalable framework ready for deployment on Costa Rican passive acoustic monitoring data to generate crucial scientific evidence for species conservation.

Abstract: We present a maximum-entropy (MaxEnt) derivation of spacetime geometry starting from a quantum thermal ensemble of local displacement fluctuations. The sole constraint imposed is the expectation value of a quadratic line-element observable. Maximization of entropy yields a Gaussian displacement kernel whose second moments encode an emergent metric structure. Beginning in a locally inertial (flattened Minkowski) frame, we show how curved spacetime geometry and field-space metrics arise through pushforward of the same MaxEnt measure, performed entirely inside the defining integrals. We demonstrate the equivalence of this formulation with the quantum thermal (Matsubara) density-matrix description, without assuming a prior Hilbert-space structure. The resulting geometry is expectation-valued and information-theoretic in origin. This framework provides a unified statistical foundation for spacetime geometry consistent with information geometry, quantum statistical mechanics, and covariant field theory.

Abstract: Drones have long been explored for supply. While several systems offering small pay-loads in drone delivery have seen operational use, large-scale supply drones have yet to be adopted. A range of setbacks cause this, including technological and operational challenges that hinder their adoption. Here, these challenges are evaluated from a conceptual modelling perspective to forecast their applicability once these barriers are overcome. The study uses technology trend modelling and bibliometric activity map-ping methodologies to predict the applicability of specific technologies that are cur-rently identified as operational challenges. Specifically for supply drones, trends in technological improvements of battery technology and aircraft control are modelled to project effects and focus on landing zone autonomy and powertrain. The prediction also focuses on the current state of hybrid power and higher levels of automation required for landing zone operations. These models are validated through several published case studies of small delivery drones and then applied to assess the feasibility and con-straints of larger supply drones. A case study, conceptual design of a supply drone large enough to move a shipping container, is presented to illustrate the critical technologies required to transition large supply drones from concept to operational reality. Key technologies required for large-scale supply drones have yet to build up a critical mass of research activity, particularly on landing zone autonomy and powertrain. Moreover, additional constraints beyond technological and operational challenges could include limitations in autonomy, certification hurdles, regulatory complexity, and the need for greater social trust and acceptance.

Abstract: Neurons have exceptionally high energy demands, sustained by thousands to millions of mitochondria per cell. Each mitochondrion depends on the integrity of its mitochondrial DNA (mtDNA), which encodes essential electron transport chain (ETC) subunits required for oxidative phosphorylation (OXPHOS). The continuous, high-level production of ATP through OXPHOS generates reactive oxygen species (ROS), posing a significant threat to the highly exposed mtDNA. To counter these insults, neurons rely on base excision repair (BER), the principal mechanism for removing oxidative and other small, non-bulky base lesions in nuclear and mtDNA. BER involves a coordinated enzymatic pathway that excises damaged bases and restores DNA integrity, helping maintain mitochondrial genome stability, which is vital for neuronal bioenergetics and survival. When mitochondrial BER is impaired, mtDNA becomes unstable, leading to ETC dysfunction and a self-perpetuating cycle of bioenergetic failure, elevated ROS levels, and continued mtDNA damage. Damaged mtDNA fragments can escape into the cytosol or extracellular space, where they act as damage-associated molecular patterns (DAMPs) that activate innate immune pathways and inflammasome complexes. Chronic activation of these pathways drives sustained neuroinflammation, exacerbating mitochondrial dysfunction and neuronal loss, and functionally links genome instability to innate immune signaling in neurodegenerative diseases. This review summarizes recent advancements in understanding how BER preserves mitochondrial genome stability, affects neuronal health when dysfunctional, and contributes to damage-driven neuroinflammation and neurodegenerative disease progression. We also explore emerging therapeutic strategies to enhance mtDNA repair, optimize its mitochondrial environment, and modulate neuroimmune pathways to counteract neurodegeneration.

Abstract: The impact of climate change on marine bivalves, particularly on their reproductive processes, is a current issue of concern. The aim of this study was to investigate how seawater temperatures influenced the gonadal development and overall condition of the grooved carpet shell clam population in the Baldaio Lagoon (NW Spain) over the last 20 years. Adult clams were collected and biometric, histological and biochemical analyses were performed. Gonadal development phases were assessed, several condition indices were calculated, water temperatures were recorded and statistical analyses were carried out. Results indicated variations in reproductive timing, including changes in gonadal maturation, an earlier spawning period and prolonged maturation phases which contrasted with previous reproductive patterns described for this species. These findings coincided with thermal changes in the lagoon, where mean minimum temperatures increased and maximum temperatures decreased, and the annual thermal range was reduced in comparison with historical data (1998-1999). Biochemical composition and condition indices also reflected variations linked to temperature fluctuations, suggesting that warmer water temperatures may alter energy storage and reproduction. This highlights the importance of continuous environmental monitoring to better understand the effects of climate change on marine invertebrate populations and to improve management strategies that could help to restore natural populations.