Abstract: Long-wavelength flank waviness plays a critical role in the excitation behavior of geared transmissions. While coordinate measuring machine (CMM) exports provide detailed geometric information, conventional evaluations typically focus on individual tooth curves and do not quantify circumferential inhomogeneity across teeth. This study introduces a tooth-to-tooth long-wavelength waviness inhomogeneity indicator (ΔW1) derived directly from Klingelnberg-style MKA plot files and demonstrates its behavior on a large industrial dataset comprising 3375 measured gear parts. Each flank curve was detrended using a second-order polynomial fit, and lobe-based waviness amplitudes (W1–W3) were extracted via sine–cosine projection. The proposed ΔW1 metric was defined as the difference between the maximum and minimum W1 values across measured teeth within the same part. To eliminate measurement edge effects, a mid-section evaluation (10–90% of the face width) was additionally performed. Population-level analysis revealed consistent separation between geometrically homogeneous and inhomogeneous parts, with ΔW1 values in the most critical components exceeding 7–9 µm after mid-section filtering. Unsupervised clustering based on ΔW1 and maximum W1 further distinguished a defect-prone subset of parts exhibiting systematic long-wavelength modulation patterns. The results demonstrate that circumferential waviness variability can be quantified using standard CMM outputs without additional hardware or specialized measurement procedures. The proposed indicator provides a practical geometric screening tool for large production batches and establishes a reproducible framework for linking detailed flank geometry to manufacturing consistency assessment. Although acoustic validation is outside the scope of the present work, the metric is intended as an NVH-relevant geometric risk indicator for future vibroacoustic correlation studies.

Abstract: Background/ Objectives: Phytosterols (Ps), plant-derived bioactive compounds not synthesized by the organism, reduce intestinal cholesterol absorption and, when consumed regularly, lower plasma cholesterol concentrations. MicroRNAs (miRNAs) are small non-coding RNAs that regulate post-transcriptional gene expression and participate in various physiological processes, with their dysregulation being associated with diseases. Among them, miR-33a/b, intronic microRNAs (miRNAs) located within the sterol regulatory element-binding protein 2 and 1 genes (SREBP-2 and -1), respectively, have recently been shown to regulate lipid homeostasis in concert with their host genes. However, there is a scarcity of studies on the interaction between Ps and miRNAs. We aimed at evaluating the effects of Ps on the expression of miR-33a/b and genes related to cholesterol transport (ABCA1, ABCG1, NPC1L1, ABCG5, ABCG8) in hepatocytes (Hep-G2), enterocytes (Caco-2), and macrophages (THP-1). Methods: Hep-G2, Caco-2, and THP-1 cells were treated with β-sitosterol (Ps), cholesterol (Ch), Ps+Ch (25 µM/24 h), or culture medium only (control). Total RNA, including miRNAs, was extracted with TRIzol™ and the expression of miRNAs was analyzed by RT-qPCR using the Poly-A tailing protocol and the 2-ΔΔCt method. Comparisons were made using ANOVA or Kruskal-Wallis (p < 0.05). Results: Ps increased miR-33a/b in Hep-G2 (p <0.001), while Ch reduced their expression. In THP-1, Ch elevated miR-33a/b (p <0.005) and Ps reduced them, with a concomitant increase in ABCA1. In Caco-2, no significant changes were observed. Conclusions: Ps distinctly modulate miR-33a/b in hepatocytes and macrophages, suggesting a role in cholesterol homeostasis and reverse cholesterol transport. These findings reinforce the cardioprotective potential of phytosterols.

Abstract: The rheological behavior of chitosan–vanillin crosslinked olive oil–in–water emulsions (Φ=0.52) was systematically studied as a function of key processing (homogenization time and speed, reaction temperature) and compositional variables (chitosan concentration, vanillin-to-chitosan molar ratio, and Tween® surfactant) to optimize their performance as oleogel precursors. All emulsions displayed viscous-dominant behavior, with a characteristic inflection in the storage modulus slope at ~0.1 Hz, except for Tween®-containing systems, which superimposable flow curves confirmed non-thixotropic Herschel–Bulkley pseudoplastic behavior (n ≈ 0.73) was observed. Optimal homogenization conditions (4 min, ≥ 9,500 rpm) promoted microstructural refinement without compromising emulsion stability. Increasing reaction temperature to 55 °C, approaching the chitosan percolation threshold (~0.8–0.9% w/w), and a vanillin-to-chitosan molar ratio of 0.7 maximized yield stress (up to 14.21 Pa), consistency, and thermal robustness, attributed to enhanced Schiff-base crosslinking and network densification. Tween® 20 and Tween® 60 induced oscillatory stiffening but caused pronounced softening under rotational shear due to interfacial displacement effects, with Tween® 20 providing superior thermal stability. Overall, a surfactant-free formulation (0.9% w/w chitosan, molar ratio 0.7, 55 °C) yielded highly structured, gel-like emulsions, demonstrating enhanced suitability as templates for olive oil oleogel development compared to conventional stabilization strategies.

Abstract: Limited interaction between students and lecturers during the learning process often leads to suboptimal information transfer. This issue becomes more critical when addressing multiple integral calculus, a subject that is abstract and requires strong visual comprehension. To address this challenge, innovative learning media that promote student autonomy and support the visualization of complex concepts are needed. This study aims to evaluate the feasibility of a GeoGebra-assisted electronic module (e-module) for a multiple integral calculus course. The research employed a development design based on Sugiyono’s model, consisting of seven stages: identifying potential and problems, data collection, product design, design validation, design revision, product trial, and final product revision. The participants were 35 mathematics education students selected through purposive sampling. Data were collected using validation sheets to assess product quality, student response questionnaires to measure practicality, and learning outcome tests to determine effectiveness. The data were analyzed using descriptive statistics, with the percentage of students achieving a minimum score of 70% used as the indicator of effectiveness. The validation results categorized the module as “very valid,” while student responses indicated that it was “very practical.” Furthermore, 72.4% of students achieved learning outcomes above the minimum mastery level, which falls into the “good” category. Therefore, the GeoGebra-assisted e-module is considered feasible, practical, and effective as a digital learning resource to enhance students’ conceptual understanding and visualization skills in multiple integral calculus.

Abstract: Aging is a fundamental biological process characterized by morphological and functional decline ultimately leading to death. Current research in aging is directed toward extending both healthspan and lifespan by elucidating the molecular and cellular mechanisms that drive aging and by developing interventions capable of delaying, preventing, or reversing age-associated physiological decline and multimorbidity. In this chapter, we take a broader view beyond the healthspan and lifespan of individuals, to consider deep issues impacting the duration and nature of our embodiment, including the nature of change, the meaning of personal persistence, and the future of humanity at multiple scales. If you don’t change, you die out (or become irrelevant); but if you change, are you still present? We argue that aging, like traumatic injury and cancer, is a fundamental challenge to an embodied mind seeking to maintain its distinct nature, differentiated from the environment. Understanding aging thus must take place within the context of a broader story of how biological individuals come to exist, how they continue to exist despite continual challenge, and how their plasticity can be leveraged for transformative change beyond mere persistence. Here, we will present our aging framework grounded in the collective intelligence of cells, then we will discuss the implication for the human- and the species-level aspects of artificial chimerism and its corollary - multiscale (non-Darwinian) evolution. We conclude with some important open questions for humanity with respect to the implications of rejuvenation and longevity technologies.

Abstract: Decentralized wastewater treatment systems afford a unique opportunity to implement a One Water paradigm through water reuse and resource recovery. Simultaneously, poorly managed on-site wastewater treatment systems (OWTSs) pose significant threats to human health, although their role in environmental antimicrobial resistance (AMR) is understudied. We deployed culture-based methods adapted from the World Health Organization’s Tricycle Protocol to assess the potential role of OWTSs in discharging third generation cephalosporin-resistant E. coli (3GCR-Ec) and extended-spectrum beta lactamase-producing E. coli (ESBL-Ec). We detected 3GCR-Ec in 74% of ATU effluents (geometric mean of 440 CFU/100 mL) and ESBL-Ec in 19%. E. coli isolates in these effluents were resistant to an average of 4.11 antibiotic compounds. ESBL-Ec were detected in up to 19% of surface water samples from rivers known to be impacted by OWTS discharges. Human sewage marker abundance was significantly higher in samples containing 3GCR-Ec (p = 0.0026) and ESBL-Ec (p = 0.0121) and the proportion of samples positive for 3GCR-Ec was strong correlated with river discharge percentile (r > 0.67, p < 0.0292). Our findings emphasize the unique human-environment interface of decentralized wastewater treatments systems must be carefully considered in both One Health and One Water paradigms to safely and sustainably meet our needs.

Abstract: Water scarcity has increased the need for efficient treatment technologies such as membrane distillation (MD). MD performance depends strongly on membrane fabrication parameters, particularly polymer concentration and nanoparticle incorporation, which control key transport and separation properties. This study considers fabrication of membranes using different concentrations of polyvinylidene fluoride (PVDF) with the incorporation of different types of nanoparticles to determine the optimum membrane formulation for membrane distillation applications. The results demonstrate that both PVDF concentration and nanoparticle type play a critical role in membrane performance in terms of permeate flux and salt rejection. Among the nanoparticles studied in this work, carbon nanotubes (CNTs) exhibited the most significant enhancement, leading to a substantial increase in water vapor flux while maintaining excellent separation efficiency. The optimized CNT incorporated membrane achieved approximately 99% salt rejection, with superior flux performance, indicating its strong potential for high-efficiency desalination and water treatment using membrane distillation.

Abstract: In modern cyber-physical vehicle networks, the security of component-level Electronic Control Units (ECUs) is essential for overall system reliability. While CAN bus security is well-studied, the Local Interconnect Network (LIN) has received less attention despite its growing role in critical functions and diagnostic services (UDS). The inherent constraints of the LIN protocol, specifically its low bandwidth and Master-Slave architecture, make traditional fuzz testing impractical due to extremely long execution times. This paper proposes BB-FAST, an optimized framework for faster vulnerability detection in LIN-based systems. By integrating batch processing and binary search techniques, BB-FAST overcomes communication bottlenecks and enables efficient error localization. Experiments on a physical automotive ECU show that BB-FAST significantly reduces testing time—by 55.56% and 93.44% depending on the diagnostic session—ensuring high efficiency even under frequent reset conditions. By mitigating these physical limitations through algorithmic optimization, this work enables thorough security verification for LIN-based diagnostic interfaces that was previously constrained by protocol latency, thereby enhancing the integrity of cyber-physical automotive networks.

Abstract: Per- and polyfluoroalkyl substances (PFAS) are environmentally persistent chemicals associated with a wide range of adverse health effects, yet individual PFAS compounds may exert distinct toxicological mechanisms. In this study, we investigate the toxic effects of perfluorooctanoic acid (PFOA) and perfluorononanoic acid (PFNA) in Drosophila melanogaster using survival assays and measurements of acetylcholinesterase (AChE) activity as indicators of systematic toxicity and neurotoxicity, respectively. Male flies were exposed to PFOA and PFNA under different feeding conditions, concentrations, and temperatures. Both compounds reduced fly viability and impaired neuronal function, but with markedly different toxicological profiles. PFNA caused a pronounced, concentration-dependent reduction in lifespan under all tested conditions, indicating a stronger systemic toxicity. In contrast, PFOA exerted a comparatively weaker effect on survival but induced a more pronounced reduction in AChE activity, consistent with enhanced neurotoxicity. PFOA-induced neurotoxicity in Drosophila may represent early molecular events that predispose neurons to degeneration, contributing to conditions such as dementia. Together, these findings demonstrate that structurally similar PFAS compounds can induce distinct toxicological outcomes and highlight the importance of evaluating individual PFAS using complementary assays. Moreover, this study underscores the utility of Drosophila melanogaster as a sensitive and mechanistically informative model for dissecting compound-specific PFAS toxicity.

Abstract: Background: Genome-scale metabolic models (GEMs) are foundational tools for systems biology, enabling quantitative interrogation of human metabolism across physiological and pathological states. However, many legacy reconstructions exhibit heterogeneous identifier usage, incomplete pathway integration, and limited thermodynamic refinement, constraining reproducibility, interoperability, and translational applicability. Methods: We present EHMN 2026, an update of the Edinburgh Human Metabolic Network. The reconstruction was refined through systematic identifier reconciliation using MetaNetX and ChEBI mappings, duplicate reaction consolidation, thermodynamic directionality assessment, and structured pathway annotation via Reactome. The final model was encoded in SBML Level 3 Version 2 with the Flux Balance Constraints (FBC2) package, ensuring explicit gene–protein–reaction (GPR) representation and compatibility with modern constraint-based modelling toolchains. Results: EHMN 2026 comprises 11 compartments, 14,321 metabolites (species), and 22,640 reactions, supported by 3,996 gene products. Of all reactions, 9,638 (42.6%) contain GPR associations, linking metabolic transformations to 2,887 unique Ensembl gene identifiers (ENSG). Pathway integration yielded 2,194 unique Reactome identifiers, providing structured pathway-level organisation of metabolic functions. Thermodynamic refinement reduced infeasible energy-generating cycles and improved reaction directionality coherence while preserving global network connectivity. The reconstruction is fully SBML-compliant and portable across major modelling platforms. Conclusion: EHMN 2026 delivers a rigorously harmonised, thermodynamically refined, and pathway-annotated human metabolic reconstruction with enhanced annotation depth and standards-based interoperability. By combining genome-scale coverage with structured gene and pathway integration, the model establishes a robust computational backbone for reproducible metabolic analysis and provides a scalable foundation for future multi-layer systems pharmacology and integrative modelling frameworks.

Abstract: We introduce quantum information copy time as a task-defined latency for transport: it is theearliest time at which a receiver confined to a region B can certify, with prescribed advantage,which of two global hypotheses was prepared by local operations in a distant sender region A.The benchmark definition is information-theoretic—the Helstrom advantage on B, given bythe trace distance between reduced states—and it admits natural refinements that incorporateexplicit measurement restrictions (few-body and moment channels). We first derive kinematiclocality constraints for Hamiltonian/Lindbladian dynamics with Lieb–Robinson tails and forcircuits/quantum cellular automata with strict light cones. We then establish a theorem-leveldiffusive benchmark in the quantum symmetric simple exclusion process (Q-SSEP): for locallyprepared charge-biased hypotheses, the Helstrom copy time obeys an unconditional diffusion-limited lower bound expressed in terms of the diffusion constant Dand the static susceptibility χ.For closed Hamiltonian systems we formulate, with assumptions stated explicitly, a projection-based route that ties restricted copy times to a single slow transport pole on a diagnosticallycheckable time window. We provide conservative exact-diagonalization diagnostics in the XXZchain together with a bundled TEBD/MPS reference implementation and convergence protocol(Supplementary S2 and Code SC1), validated against exact evolution on small sizes; large-LTEBD studies are left as future work. Finally, we contrast copy time with scrambling diagnosticsbased on out-of-time-ordered correlators and identify regimes in which conservation laws delaycertifiability well beyond the ballistic operator-growth front.

Abstract: Cystic fibrosis transmembrane conductance regulator (CFTR) is a chloride channel in humans and other vertebrates, whose mutation leads to cystic fibrosis. CFTR inhibitory factor — Cif — is a recently discovered bacterial epoxide hydrolase that downregulates CFTR protein upon the bacterial infection. However, its cleaving activity towards fatty acid epoxides — epoxygenase-derived oxylipins — has been recently characterized. We identified a list of host-associated bacteria with putative Cif proteins, identified their most prevalent ecological functions by systematic literature review, and performed similar review for the previously assembled list of host-associated bacteria carrying lipoxygenase (LOX). Both Cif and LOX showed the association with pathogenesis and symbiosis in broad host range, and similar ecological profiles of their carriers suggested that they both might target oxylipin signaling in hosts. We also described the association of Cif with plant hormone biosynthesis and plant growth promotion — which indirectly supports our previous model of bacterial LOX action in plant and vertebrate hosts.

Abstract: Lower-limb rehabilitation exoskeletons must balance biomechanical compatibility, structural safety, and low mass to enable practical, repeatable gait assistance. This paper proposes a planar pantograph-derived exoskeleton leg driven by a Chebyshev Lambda linkage and develops an integrated workflow from mechanism synthesis to manufac-turable optimization and experimental verification. A mannequin-coupled multibody model was built in MSC ADAMS to evaluate joint kinematics, end-point (foot) trajec-tories, and joint reaction forces under multiple scenarios (fixed-frame, ramp, stair as-cent, and inclined-plane walking). The extracted joint loads were transferred to a par-ametric finite element model in ANSYS Workbench, where response-surface surrogates and a multi-objective genetic algorithm (MOGA) were used to minimize mass under stiffness and strength constraints. For the optimized load-bearing link, the selected minimum-mass design reached a component mass of 0.542 kg while respecting the imposed structural limits, i.e., a maximum total deformation below 0.2 mm and a maximum equivalent (von Mises) stress below 55 MPa (e.g., ~0.188 mm deformation and ~39 MPa stress in the optimal candidate). A rapid prototype was manufactured by 3D printing and experimentally evaluated using CONTEMPLAS high-speed video tracking, providing measured X_M(t) and Y_M(t) trajectories and joint-angle histories for quantita-tive comparison with simulations via RMSE metrics.

Abstract: Consequent behavioral effects are documented at both individual and market levels: elevated turnover, revenge trading, impaired calibration and amplified volatility. Cross-domain findings from pedagogy, neuroscience and decision-support research are marshalled to show that process-focused training, biofeedback, explainable analytics and carefully engineered platform feedback can foster rule-governed behavior and attenuate affect-driven mispricing. The paper specifies concrete proxy measures for procedural fidelity, describes scalable training and platform interventions, and emphasizes the need to match interventions to trader segment, platform design and market regime. Proxy process measures often seem to demand institutional access, technical integration and continuous data streams, and may therefore be costly, vulnerable to gaming, and poorly scalable for dispersed retail traders. These limitations may undermine the feasibility and fidelity of many otherwise promising interventions. By contrast, a simple, intra-psychic proxy may offer a cost-free, accessible signal that redirects attention. This narrative review examines the psychological dynamics of outcome-focused trading and advances a process-oriented alternative for stabilizing trader behavior and improving learning. Drawing on experimental, physiological, neuroscientific and large-scale field evidence, the review characterizes outcome fixation as an attentional and affective orientation toward realized short-term profits and losses that amplifies emotional reactivity, promotes impulsive and compensatory risk-taking, and undermines adherence to pre-specified decision rules. The review then identifies proximal cognitive and biophysiological mechanisms such as loss salience, anticipatory reward signaling, stress-related endocrine effects and capacity limits on deliberative processing, that link momentary feedback to departures from disciplined practice. In this review, we introduce a hypothetical construct termed the “discipline coin” (DISC). DISC integrates the key features discussed above—simplicity, cost-free use, independence from outcome-based feedback and accessibility—and can be employed as an intrapsychic signal to shift attention from short-term profits and losses to consistent adherence to a trading process. However, further research is needed to validate these assumptions empirically.

Abstract: Background: Routine cardiac catheterization has traditionally been considered mandatory prior to the bidirectional Glenn procedure in patients with single-ventricle physiology, aiming to assess pulmonary artery anatomy, pulmonary pressures, and ventricular filling. However, invasive assessment carries procedural risk and cumulative radiation exposure, while advances in non-invasive imaging have challenged this paradigm. Main Body: This review synthesizes historical practice, contemporary evidence, and evolving guideline recommendations regarding pre-Glenn assessment. Landmark randomized data, most notably from Brown et al., demonstrated that cardiac magnetic resonance provides equivalent surgical decision-making and early outcomes compared with routine catheterization, while significantly reducing adverse events, hospital stay, and cost. Subsequent institutional experiences and international guidelines (2020–2023) have reinforced a selective approach, favoring non-invasive imaging—particularly cardiac magnetic resonance —unless an intervention is anticipated or non-invasive findings are equivocal. Furthermore, we propose a phenotype-guided strategy for a subset of patients with favorable ventricular morphology and shunt-dependent pulmonary blood flow, in whom targeted echocardiography with adjunctive computed tomography angiography may suffice. Conclusion: Accumulating evidence supports a shift from universal invasive assessment toward individualized, risk-stratified pre-Glenn evaluation. A selective imaging-driven strategy may safely reduce procedural burden while preserving diagnostic accuracy in carefully chosen patients.

Abstract: Virtual Power Plants (VPPs) face significant challenges in managing the uncertainty and variability of distributed energy resources (DERs), which can result in high trading risk and deter investment. This paper proposes and evaluates two advanced optimisation techniques—stochastic programming and robust optimisation—to derive risk-aware bidding strategies for VPP participation in the day-ahead and balancing electricity markets. These methods are benchmarked against a deterministic, expectation-based model. The novelty of this work lies in the comparative application of stochastic and robust frameworks to VPP bidding strategy design under real-world uncertainty, the introduction of scenario-based wind and conventional generation models, and the integration of energy storage into the optimisation framework to assess its impact on profitability and risk mitigation. Through a series of simulations using actual market data from the UK (Elexon), we evaluate three generation portfolio configurations—conventional, renewable, and aggregated. The results show that while stochastic optimisation consistently achieves the highest expected profit, the robust model ensures the highest minimum profit under worst-case conditions. Moreover, combining DER types and integrating battery storage further enhances profitability and reduces exposure to imbalance penalties. These findings provide valuable insights for the development of intelligent, risk-aware trading strategies for VPP operators.

Abstract: A cornerstone in transferring a classical Liquid Chromatography (LC) with UltraViolet/Visible (UV/Vis) detector into a greener and, beyond, towards a sustainable analytical method should consider the safety and health of the used organic solvent in the method. Toxic organic solvent portions used in the mobile phase can be replaced by an eco-friendly green solvent that is ideally bio-based and biodegradable to increase the greenness index of the method. However, the implementation of a new organic solvent for High Performance Liquid Chromatography (HPLC-UV/Vis) and/or UltraHigh Performance Liquid Chromatography (UHPLC-UV/Vis) requires not only a simple consideration of its environmental and health impact, cost-effectiveness, user-friendliness, and impact on the analytical performance of the method but rather a systematic evaluation of its chromatographic suitability. Existing greenness, blueness, and redness metrics expressing whiteness for evaluating the sustainability of liquid chromatographic methods after solvent replacement overlook the chromatographic suitability of the selected green solvent, potentially leading to suboptimal solvent replacement and an incomplete view of its capabilities. In this work, the authors present a Universal Suitability and Sustainability Index (USSI), a sixteen-parameter scoring system that quantifies four main factors for complete evaluation of a new solvent for implementation in liquid chromatography. This index is even beyond the white analytical chemistry principle. The four main factors are chromatographic suitability, greenness, blueness, and redness. Three of these factors, namely greenness, blueness, and redness, are based on available tools and metrics to evaluate the environmental and health, impact on the practicability, and the analytical performance of the method. The fourth factor is added as an important criterion to judge the suitability of the solvent to liquid chromatographic analysis and to give an overview about its analytical chromatography-oriented applicability. The new index has been used to evaluate traditional solvent-based liquid chromatographic methods as well as those based on alternative emerging green solvents and compare the factors together to give a universal overview that aids users to drive a rapid imprison on the weakness and strength aspects and makes it easier to judge the selection of the solvent and the evaluation of the overall method sustainability.

Abstract: Background/Objectives: Congenital heart defects (CHD) are the most common structural birth defects that exhibit high heritability. Emerging evidence suggested that CHD are as-sociated with disruptions in one-carbon metabolism. In a family-based trio design, we in-vestigated whether maternal, paternal, and child plasma concentrations of choline, beta-ine, and folate were associated with CHD severity. Subjects and Methods: The study in-cluded 72 children with CHD, 69 mothers and 64 fathers of the children. CHD severity was classified according to the European network of population-based registries for the epidemiological surveillance of congenital anomalies (EUROCAT) system and the Ger-man PAN study (Prevalence of Congenital Heart Defects in Newborns). Plasma and urine concentrations of choline and betaine and plasma folate vitamers were quantified using ultra-performance liquid chromatography–tandem mass spectrometry. Results: The chil-dren [mean (SD) age 3.1 (3.2) years, 59.7% males] presented with varying CHD severities according to EUROCAT (62.5% severe and 37.5% mild) and PAN classifications (45.8% severe, 30.6% moderate and 23.6% mild). Plasma concentrations of choline were < 10 µmol/L in 38 (66.7%) of the mothers and 27 (62.8%) of the fathers who provided blood samples. Maternal plasma choline concentrations < 10 µmol/L were associated with hav-ing a child with severe CHD [adjusted odds ratio (aOR) 3.7; 95% confidence intervals (95%CI) = 1.1, 12.2 compared to mothers with choline concentrations ≥ 10 µmol/L]. Low-ered paternal plasma choline concentrations were also associated with severe CHD (aOR 7.4; 95% CI = 1.7, 31.5). Plasma concentrations of choline in the children and those of be-taine and folate vitamers in parents and children were not associated with CHD severity. Conclusions: Lower plasma concentrations of choline in the parents detectable several years after conception, were related to having a child with severe CHD compared with families of children with higher plasma choline. These findings support a potential role for maternal and paternal choline metabolism in modulating CHD severity. Etiological studies aiming at prevention of prevalent congenital anomalies should focus on maternal and paternal risk factors.

Abstract:

The superconducting transition temperature of CaC₆ is investigated within the Roeser–Huber (RH) formalism using both rhombohedral and hexagonal crystallographic representations. While these two descriptions are crystallographically equivalent, they differ in their geometric construction of superconducting paths and near-atom environments. In the rhombohedral representation, only translationally closed Ca–Ca vectors consistent with the primitive lattice are considered, yielding three symmetry-distinct RH paths. In the hexagonal representation, the same superconducting channels are expressed in an expanded conventional cell, where some paths appear as unfolded or symmetry-related sublattice connections. For each representation, the RH path lengths and effective near-atom counts are evaluated and used to compute the superconducting transition temperature. The rhombohedral description yields $T_c^{\rm(calc)} = 10.35$ K, while the hexagonal representation gives $T_c^{\rm(calc)} = 10.91$ K, both in good agreement with the experimental value $T_c^{\rm(exp)} = 11.5$ K. The difference between the calculat\( {The superconducting transition temperature of CaC$_6$ is investigated within the Roeser–Huber (RH) formalism using both rhombohedral and hexagonal crystallographic representations. While these two descriptions are crystallographically equivalent, they differ in their geometric construction of superconducting paths and near-atom environments. In the rhombohedral representation, only translationally closed Ca–Ca vectors consistent with the primitive lattice are considered, yielding three symmetry-distinct RH paths. In the hexagonal representation, the same superconducting channels are expressed in an expanded conventional cell, where some paths appear as unfolded or symmetry-related sublattice connections. For each representation, the RH path lengths and effective near-atom counts are evaluated and used to compute the superconducting transition temperature. The rhombohedral description yields $T_c^{\rm(calc)} = 10.35$ K, while the hexagonal representation gives $T_c^{\rm(calc)} = 10.91$ K, both in good agreement with the experimental value $T_c^{\rm(exp)} = 11.5$ K. The difference between the calculated values amounts to approximately 5.4\%. These results show that the underlying RH superconducting channels and their near-atom environments are representation independent, while minor quantitative differences in $T_c^{\rm(calc)}$ arise from metric redistribution of equivalent paths. This directly confirms that the RH formalism captures intrinsic structural features of superconductivity rather than artifacts of unit-cell representation. \)d values amounts to approximately 5.4\%. These results show that the underlying RH superconducting channels and their near-atom environments are representation independent, while minor quantitative differences in $T_c^{\rm(calc)}$ arise from metric redistribution of equivalent paths. This directly confirms that the RH formalism captures intrinsic structural features of superconductivity rather than artifacts of unit-cell representation.

Abstract: Autophagy is an evolutionarily conserved degradation and recycling process through which cells deliver cytoplasmic components such as toxic or defective proteins and organelles to lysosomes for clearance. Unlike dividing cells, neurons depend on degradative pathways to prevent the buildup of cellular waste and to sustain nutrient and energy homeostasis. Emerging evidence indicates that autophagy is particularly critical during early development when neuronal circuits are being established, synaptic connections refined, and activity-dependent mechanisms sculpt overall network architecture. Accordingly, loss of key autophagy-related genes in newly formed neurons disrupts differentiation, synaptic formation and neurotransmission. Despite these insights, the developmental regulation of autophagy genes remains poorly understood, and the composition of the autophagic machinery at synapses is still largely unresolved. To address this, we performed genome-wide transcriptomic analyses of the cortical brain region to characterize the maturation-dependent dynamics of autophagy–lysosomal genes. In parallel, we examined the autophagy-associated proteome within synaptosomes to better understand how autophagic proteins contribute to synaptic processes during critical stages of network formation. Together, these complementary approaches reveal new aspects of autophagy regulation during development and provide a foundation for identifying therapeutic targets for neurological disorders linked to impaired synaptic and cellular homeostasis.