Abstract: Artificial intelligence (AI) is often employed in various sectors of e-commerce. Conse-quently, it becomes necessary to identify the impact of various parameters of the algorithm on buyer behavior. This study aims to investigate the impact of algorithmic anthropomor-phism, algorithmic transparency and perceived algorithmic fairness on buyer purchase intentions. In addition, this study has endeavored to establish the role of Technology Ac-ceptance Model as a moderating variable. A structured questionnaire was dispersed among 384 online buyers via Qualtrics. The proposed model was tested using PROCESS macro (Hayes, 2022) for mediation and moderation analyses. The results reveal that: (1) algorithmic anthropomorphism positively affects both algorithmic transparency and per-ceived algorithmic fairness; (2) algorithmic transparency has a significant positive effect on both perceived fairness and purchase intention; (3) perceived algorithmic fairness me-diates the relationships between algorithmic anthropomorphism and purchase intention, as well as between algorithmic transparency and purchase intention; and (4) TAM posi-tively influences purchase intention, though its moderating effect on the anthropomor-phism–purchase intention link is only marginally significant. These findings offer theo-retical contributions to AI-driven consumer behavior research and practical implications for the design of algorithmic e-commerce systems.

Abstract: Front Running Simulation (FRS) is a Digital Twin–enabled capability that continuously replicates the current state of physical systems, predicts probable future states, and identifies actions to navigate to defined goals while minimizing the expenditure of scarce physical resources. Unlike traditional simulation, which operates offline with predefined initial conditions, FRS is continuously synchronized with reality through Digital Twin Instances (DTIs), allowing forward-looking simulation from the present state. FRS is based on three core activities—replication, prediction, and navigation—supported by data, Models of Reality (MoR), simulation, and information. Data enables replication. Simulation based on MoRs, enables prediction through causal and probabilistic methods; and information enables goal-directed action selection. The integration of Digital Twin Aggregates (DTAs) and Artificial Intelligence introduces Bayesian, data-driven prediction that complements physics-based simulation. This hybrid approach combines exploration of possible futures with rapid identification of probable outcomes. As the examples demonstrate, FRS shifts the focus from only adverse event avoidance to goal attainment under constraints, enabling proactive, information-driven decision-making. It provides a unifying Digital Twin FRS framework for Models of Reality, data, simulation, information, and AI to improve operational efficiency and effectiveness in complex systems.

Abstract: Flexible thermoplastic polyurethane (TPU) materials fabricated using fused deposition modeling (FDM) are increasingly used in engineering and biomedical applications where exposure to moisture is unavoidable. However, the relationship between mate-rial hardness, water absorption, diffusion behaviour, and dimensional stability re-mains insufficiently understood and investigated. In this study, the hygroscopic behaviour of eight commercially available TPU filaments (60A–98A Shore hardness) was systematically investigated. Specimens were produced using FDM 3d printer under controlled processing conditions and immersed in physi-ological solution (0,9% NaCl) for up to 96 h. Water absorption, dimensional changes, and diffusion characteristics were analysed. Diffusion coefficients were determined using the Fickian diffusion model based on the initial stage of water uptake. The results revealed a clear transition in behaviour between lower- and high-er-hardness materials. Softer TPU materials (60A–85A) exhibited higher water absorp-tion (up to ~1.80%) and a strong linear relationship between hardness and absorption (R² = 0.999). In contrast, higher-hardness materials (89A–98A) showed lower absorp-tion (~1.18–1.42%) and no clear correlation with hardness (R² = 0.4214). Diffusion coef-ficients ranged from 1.06 × 10⁻¹² to 3.40 × 10⁻¹² m²s-1, with no monotonic dependence on hardness. Additionally, no clear correlation between diffusion kinetics and equilibrium absorption or volumetric expansion was observed. These findings demonstrate that hygroscopic behaviour of FDM-printed TPU materials cannot be reliably predicted based solely on hardness, and that diffusion, absorption, and swelling are governed by different mechanisms. The identified transition from hardness-dependent to structure-controlled behaviour provides new insight for the design and selection of flexible polymer components in moisture-exposed environ-ments, particularly in biomedical applications.

Abstract: Background/Objectives: Disease-related malnutrition is highly prevalent in oncology and is associated with poor clinical outcomes. Early detection through nutritional screening is essential; however, the optimal screening tool for ambulatory cancer patients remains uncertain. This study aimed to evaluate the agreement and diagnostic performance of the Malnutrition Screening Tool (MST) and NUTRISCORE compared with the Global Leadership Initiative on Malnutrition (GLIM) criteria in a large nationwide cohort of ambulatory cancer patients. Methods: In this multicenter, observational, cross-sectional nationwide study, adult patients attending oncology day hospitals for intravenous antineoplastic treatment between April and November 2021 were included. Nutritional risk was assessed using MST (cut-off ≥ 2) and NUTRISCORE (cut-off ≥ 5). Malnutrition was diagnosed according to GLIM criteria. Agreement between tools was assessed with Cohen’s kappa, and diagnostic performance was evaluated by sensitivity, specificity, accuracy, positive predictive value, and negative predictive value. Analyses were stratified by tumor nutritional risk and cancer stage. Results: Among 4440 patients from 86 hospitals, 50.7% met the GLIM criteria for malnutrition; 72.5% had moderate and 27.5% severe malnutrition. MST identified 37.5% of patients as being at nutritional risk, compared with 17.3% identified by NUTRISCORE. Agreement between MST and NUTRISCORE was moderate overall (κ = 0.48; 95% CI, 0.45–0.51), but varied markedly according to tumor nutritional risk, ranging from high agreement in high-risk tumors (κ = 0.82) to low agreement in low-risk tumors (κ = 0.28). Relative to GLIM, MST was more sensitive than NUTRISCORE (0.51 vs. 0.27), whereas NUTRISCORE was more specific (0.92 vs. 0.76) and had a higher positive predictive value (0.77 vs. 0.68). Negative predictive value was low for both tools. Conclusions: GLIM-defined malnutrition was highly prevalent in this large cohort of ambulatory patients with cancer. MST provided greater case detection, whereas NUTRISCORE showed a more conservative profile with higher specificity but substantially lower sensitivity. These findings suggest that the choice of screening tool should consider clinical context and tumor-related nutritional risk, and that neither instrument alone reliably excludes malnutrition in outpatient oncology settings.

Abstract: Olfaction plays a fundamental yet often underappreciated role in human sexual be-havior, attraction, and relationship dynamics. Beyond the debated existence of human pheromones, emerging evidence supports a broader framework of chemosensory communication influencing emotional, cognitive, and behavioral aspects of sexuality. This review synthesizes recent literature examining the relationship between ol-factory function and human sexual experience in a clinical context. Studies were in-cluded if they met the following criteria: (i) empirical research conducted in human populations, (ii) assessment of olfactory function or chemosensory cues, (iii) evaluation of sexuality-related outcomes (e.g., sexual desire, arousal, satisfaction, intimacy, or mate selection), and (iv) publication in peer-reviewed journals in English between 2010 and 2025. We provide an overview of how olfactory capacities can impact on 3 types of close mating-related aspects: (1) chemosignals and socio-sexual effects, (2) olfactory function and sexual behavior, and (3) olfactory dysfunction and sexual outcomes. Accumulating evidence suggests that olfactory function is associated with sexual satisfaction, partner bonding, and relationship stability. Conversely, olfactory dysfunction, whether con-genital or acquired, appears to negatively affect sexual motivation, intimacy, and emo-tional aspects of sexual experience. Current findings indicate that olfactory processing may represent a clinically relevant, yet often overlooked, component of sexual health. Integrating olfactory assessment into clinical andrological practice may provide addi-tional insight in cases of unexplained sexual dysfunction.

Abstract: Space charge accumulation is a primary factor in the premature aging and electrical breakdown of High Voltage Direct Current (HVDC) cables. Conventional continuum models often fail to capture the stochastic nature of charge hopping in disordered polymeric insulations like cross-linked polyethylene (XLPE). This paper proposes a novel transport model based on the Persistent Random Walk (PRW) theory, specifically adapted to describe hopping conduction between discrete trap states. We map the trap depth and temperature-dependent Poole-Frenkel release rates to the scattering rate of the PRW. Our simulations demonstrate a strong temperature dependence of the internal electric field. At low temperatures (300 K), carriers remain trapped near the injection electrode, creating a severe local field enhancement (homocharge effect) exceeding 80% of the applied stress. Conversely, as temperature increases, thermal energy facilitates detrapping, leading to charge relaxation and a return to a uniform field distribution. Furthermore, a comparison with Space-Charge-Limited Current (SCLC) theory at the transition temperature (450 K) validates the model, showing the charge packet tail follows a power-law decay with a slope close to the theoretical − 2 / 3 prediction. These results highlight a competing physical mechanism where high temperature mitigates the electrostatic risk associated with space charge, providing critical insights for the design of reliable HVDC insulation systems

Abstract: Water body extraction using remote sensing is crucial for ecological environment monitoring and water resource management. Nevertheless, the irregular and complicated shapes of water bodies make it difficult to obtain fine-grained characterization and preserve structural consistency with current approaches. To overcome the shortcomings of fixed receptive fields and sampling schemes of traditional convolutional networks, this paper proposes UNet-LSCNet, an advanced architecture based on U-Net. The proposed model integrates dynamic snake convolutions (DSConv), the convolutional block attention module (CBAM), and a lightweight Vision Transformer (LaViT) to enable local adaptive geometric modeling and contextually enriched semantics representation. The experimental findings demonstrate that the suggested approach outperforms various widely applied models. Specifically, UNet-LSCNet achieves a mIoU of 95.67% and an F1-score of 96.32%, while maintaining a competitive inference speed of 4.18 frames per second (FPS). Furthermore, it exhibits greater stability in highly complex situations, such as slender meandering rivers and fragmented small-scale water bodies. Ablation experiments confirm the synergistic utility of each module, revealing that the proposed model enhances segmentation accuracy and morphological resilience without compromising inference efficiency.

Abstract: Background and Purpose: Whole-body electrical muscle stimulation (WB-EMS) is an emerging modality that activates multiple large muscle groups simultaneously via a wearable electrode suit. Although neuromuscular electrical stimulation (NMES) has demonstrated efficacy as an adjunctive strategy in cardiac rehabilitation (CR), WB-EMS has not previously been investigated in patients with heart failure and reduced ejection fraction (HFrEF) undergoing CR. This report presents preliminary findings from the active arm of an ongoing randomized trial. Methods: A 73-year-old male with recurrent non-ST-elevation myocardial infarction (NSTEMI), chronic HF (left ventricular ejection fraction [LVEF] 20–25%), and NYHA functional class III was admitted for inpatient CR. Standard CR (cycle ergometry, treadmill, resistance exercises, respiratory physiotherapy, and patient education, five days/week for 24 days) was augmented with WB-EMS (Wiems Revolution Pro device; 85 Hz bipolar, 350 μs, 4s on/4s off, 20-minute sessions) three times per week (~9 sessions). Safety was monitored with serial creatine kinase (CK), high-sensitivity troponin I (hs-TnI), NT-proBNP, C-reactive protein (CRP), and venous blood gas with lactate, measured before and 2–3 hours after each session. Results: LVEF improved from 27% to 54% (Simpson biplane); peak workload from 66 to 97 W (+47%); six-minute walk test (6MWT) distance from 390 to 590 m (+51%); and NT-proBNP declined from 544 to 318 pg/ml (−41.5%). EQ-5D-5L EQ-VAS improved from 60 to 90/100. One-month IPAQ data demonstrated sustained increases in daily physical activity. All safety biomarkers remained within acceptable limits throughout the programme. No adverse events were recorded. Discussion: To our knowledge, this is the first report of WB-EMS combined with standard CR in an HFrEF patient. The comprehensive serial biomarker monitoring confirmed a favorable safety profile. The striking improvements observed across functional, echocardiographic, neurohormonal, and quality-of-life domains are promising but require confirmation in the ongoing randomized trial, as multiple concurrent therapeutic interventions preclude causal attribution to WB-EMS alone.

Abstract: emergence of musculoskeletal disorders associated with prolonged and improper posture. Medical students are some of the most affected groups due to reliance on such devices due to academic demands. Text neck syndrome is caused by prolonged and repetitive flexion of the neck while using smart devices. TNS has been associated with neck pain, functional disability, reduced mobility, and overall quality of life. Despite the increasing reliance on digital devices and the burdens associated with them, evidence regarding the prevalence and risk factors remains limited. The aim of this study was to assess the prevalence of TNS among medical students in West Bank universities and to identify factors associated with TNS. Methods: In this cross-sectional study, an online, self-administered questionnaire was used to collect data regarding the use of smart devices, ergonomic practices, sociodemographic characteristics, TNS symptoms, and neck disability using the Neck Disability Index (NDI). Results: Among the 358 medical students included in this study, the prevalence of TNS was 46.6%, significant associations included university, year of study, female gender, shorter break time from using devices, degree of neck tilting, tablet holder non-use, height, time on devices, time spent sitting, NDI score, and category. Multivariable regression analysis also showed independent associations with academic year, gender, time spent on digital devices, degree of neck tilting, and non-use of tablet holders. Statistical significance was set at p < 0.05, with a 95% confidence interval. NDI showed that 42.7% had no disability, 45.5% had mild disability, 11.2% moderate disability, and 0.6% had severe disability; no cases of complete disability were reported. Conclusion: TNS was prevalent among medical students and had significant associations with sociodemographic, ergonomic, academic, and device use factors, highlighting the need for preventative measures and further research.

Abstract: Agriculture and cultural heritage generate knowledge in similar ways as they are both rooted in land-based, intergenerational, and tacit forms of transmission. This is complicated when generative AI systems are used to replicate these forms of knowledge but often struggle to fully capture relational forms of knowing. As generative AI becomes increasingly more ubiquitous in society, it becomes more important to understand not only how this technology is being used within these respective fields of study but also how it represents these bodies of knowledge. To this effect, this paper uses a case study approach to examine how generative AI like ChatGPT responds to questions related to farming and cultural heritage. Utilizing Critical Discourse Analysis and autoethnography, we critically interrogate ChatGPT prompts that require an understanding of relational knowledge. We show the limitations of ChatGPT and the need to honour relational knowledge practices.

Abstract: Osteosarcoma, the most common primary malignant bone tumor in adolescents, faces treatment challenges due to metastasis and chemoresistance. This study developed a novel Au@Rh core-shell nanoparticle system functionalized with indocyanine green (ICG) to overcome hypoxia-limited photodynamic therapy (PDT). Au@Rh nanoparticles were synthesized via wet chemistry, characterized by UV-Vis spectroscopy, TEM, and cyclic voltammetry (CV). The system exhibited core-shell morphology, defined crystalline planes, photothermal conversion and electrocatalytic activity. The Au@Rh nanoparticles (109 nm total size, 90 nm Au core, 15 nm Rh shell) demonstrated dual functionality: the gold core provided photothermal conversion (7 °C temperature increase under NIR irradiation), while the rhodium shell exhibited pH-independent electrocatalytic activity for H₂O₂ decomposition, generating oxygen to alleviate tumor hypoxia. Crucially, the system showed excellent biocompatibility, with no significant cytotoxicity in both osteosarcoma (HOS) and normal osteoblast (hFOB) cells after 48-hour exposure. When activated by NIR irradiation (808 nm, 16.6 J/cm²), the complete Au@Rh-ICG system achieved selective 67% cytotoxicity in HOS cells versus only 30% in hFOB cells, demonstrating targeted therapeutic efficacy. These results position Au@Rh-ICG as a promising theranostic platform for osteosarcoma treatment, combining enhanced PDT with photothermal therapy while addressing tumor hypoxia.

Abstract: This study addresses the speed control problem of an induction motor (IM) under the field-oriented control (FOC) architecture by proposing a robust controller design that combines the slime mould algorithm (SMA) with sliding mode theory (SMT). Distinct from traditional controller designs with fixed gains, the proposed theory defines the ranges of three gain parameters of the exponential reaching law sliding mode controller—namely, the sliding mode dynamic trajectory control gain, the exponential reaching gain, and the constant speed reaching gain—as the search space for the SMA. An adaptive fitness function is constructed using speed error and the rate of change of speed error to continuously evaluate and update these three gain parameters, thereby determining the optimal gains for the current state. This method allows the system to increase gain values to accelerate reaching when far from the sliding surface, and reduce gains to suppress chattering and minimize overshoot when approaching the sliding surface. Finally, Matlab/Simulink simulation software is used to simulate the proposed robust controller applied to an IM drive system. Its performance is compared with three other controllers: constant speed reaching law, exponential reaching law, and zebra optimization algorithm (ZOA) combined with exponential reaching law. Simulation results confirm that the proposed novel controller demonstrates control performance superior to the other three controllers in both speed command tracking and load regulation response.

Abstract: This paper examines the state of academic literature on the development of after-sales and maintenance services for electric vehicles (EVs), highlighting their critical yet underexplored role in the transition to electrified mobility. Against the backdrop of rising EV sales, the study investigates how service ecosystems influence long-term adoption. A systematic review was conducted to identify recurring themes, barriers, and proposed solutions related to EV maintenance and after-sales systems. The findings indicate that, despite lower mechanical complexity compared to internal combustion vehicles, EVs generate new service demands due to their reliance on electronics, software, and high-voltage systems. Key barriers to EV adoption include high purchase costs, limited charging infrastructure, and shortages of skilled technicians, which collectively affect consumer confidence beyond the point of acquisition. The analysis shows that after-sales services constitute both a technical and economic bottleneck in large-scale EV diffusion. Existing literature predominantly emphasizes theoretical solutions, such as digitalized maintenance and data-driven business models, with limited focus on practical implementation strategies. The paper concludes that sustainable EV adoption depends not only on technological and infrastructural progress but also on workforce adaptation, proposing a transitional management framework to support independent workshops in shifting toward fully electric service operations.

Abstract: Facial expression recognition (FER) is a well-established task in computer vision, yet its application to non-photorealistic domains, such as anime and manga, remains largely underexplored. The stylized, exaggerated, and often non-proportional facial features of illustrated characters present unique challenges for deep learning models trained predominantly on realistic imagery. In this work, we construct a balanced dataset of 3,000 manga and anime face images spanning six emotion categories (Angry, Embarrassed, Happy, Psycho-Crazy, Sad, Scared) and conduct a systematic comparison of two major deep learning paradigms: Convolutional Neural Networks (CNNs) and Vision Transformers (ViTs). Specifically, we evaluate ResNet-18, ResNet-50, ViT-B/16, and ViT-S/16 under four fine-tuning strategies: linear probing, partial fine-tuning, full fine-tuning, and progressive unfreezing; enabling a controlled comparison of both architectural families and transfer learning depth. Our results show that fine-tuning strategy significantly impacts performance: the best configuration (ViT-B/16 with progressive unfreezing) achieves 80.89% test accuracy, compared to 61.33% for the weakest linear probe baseline (ViT-S/16), a gap of 19.56 percentage points. Vision Transformers benefit disproportionately from fine-tuning, and the relative ranking of architectures changes across fine-tuning regimes. Confusion matrix analysis reveals persistent cross-class confusion between visually similar emotions (e.g., Happy vs. Embarrassed), while highly distinctive categories such as Psycho-Crazy are consistently well recognized across all architectures.

Abstract: Metabolic dysfunction–associated steatotic liver disease (MASLD) is characterized by impaired metabolic flexibility, oxidative stress, and disruption of the temporal coordination of hepatic processes. Obesogenic diets contribute to this dysfunction by altering redox homeostasis and autophagy, thereby promoting lipid accumulation and cellular stress. In this study, we investigated whether grape seed proanthocyanidin extract (GSPE), a polyphenol-rich compound with antioxidant properties, can modulate these alterations in a time-dependent manner. Male Fischer 344 rats were fed a standard or cafeteria diet and supplemented with GSPE (25 mg/kg) at the onset of the active phase (ZT12). Liver samples were collected across four Zeitgeber times to evaluate circadian-related proteins, autophagy markers, antioxidant responses, lipid content, and metabolomic profiles. Cafeteria feeding disrupts hepatic homeostasis, reducing BMAL1 protein levels, altering the temporal organization of autophagy markers, and impairing redox regulation. GSPE did not restore core clock protein expression but induced a pronounced, time-specific activation of the NRF2/HO-1 axis, with a marked increase in HO-1 at the onset of the active phase. This effect was associated with a metabolic shift toward amino acid–related pathways linked to redox balance. These findings indicate that GSPE enhances antioxidant defenses in a time-dependent manner, improving redox–metabolic coordination under obesogenic conditions.

Abstract:

Background: The production of evidence syntheses has expanded substantially, yet confusion persists regarding the distinct roles, structures, and scientific validity of protocols, narrative reviews, systematic reviews, and umbrella reviews. Mislabeling or conflating these forms undermines research reproducibility and evidence-based decision-making. Objective: To provide a comprehensive, side-by-side methodological comparison of protocols, narrative reviews, systematic reviews, and umbrella reviews, including definitions, purposes, key methodological steps, strengths, limitations, and appropriate use cases. Methods: A structured comparative methodological analysis was conducted between February and March 2026. Authoritative guidance documents were identified through a targeted search of PubMed and Google Scholar using keywords “systematic review methodology,” “narrative review,” “umbrella review,” and “protocol registration.” Included sources were the Cochrane Handbook for Systematic Reviews of Interventions (Higgins et al., 2023), PRISMA 2020 (Page et al., 2021), PRISMA-P (Shamseer et al., 2015), the PRIOR statement for overviews of reviews (Gates et al., 2022), SWiM guideline for narrative synthesis (Campbell et al., 2020), PRISMA-ScR for scoping reviews (Tricco et al., 2018), JBI methodology for umbrella reviews (Aromataris et al., 2015), PROSPERO registry standards, ROBIS (Whiting et al., 2016), AMSTAR 2 (Shea et al., 2017), RoB 2 (Sterne et al., 2019), and GRADE (Schünemann et al., 2011). Key methodological domains (research question formulation, search strategy, risk of bias assessment, synthesis methods, transparency, reproducibility) were extracted and synthesized for side-by-side comparison. Results: A protocol is a pre-registered plan, not a review. A systematic review is a reproducible, bias-minimizing synthesis of eligible primary studies on a focused question. A narrative review is a subjective, flexible summary of a broader topic. An umbrella review is a higher-order synthesis that systematically compiles, appraises, and synthesizes existing systematic reviews. Umbrella reviews extend this hierarchy by synthesizing review-level evidence. Across all domains, systematic reviews and umbrella reviews demonstrated the highest methodological rigor, characterized by predefined protocols, comprehensive search strategies, and formal risk of bias assessment. Protocols functioned exclusively as methodological safeguards, while narrative reviews showed substantial variability and lack of reproducibility. Conclusion: Choosing among these four forms depends on the review question, available evidence base, resources, and intended use. Protocols should precede systematic reviews and umbrella reviews; narrative reviews serve complementary roles in education and hypothesis generation. Accurate differentiation is a prerequisite for maintaining the integrity of evidence-based healthcare.

Abstract: Previous studies showed that IGF1 binds to α6β4 and induces α6β4-IGF1-IGF1R complex, which leads to the IGF1R kinase activation. An IGF1 mutant defective in integrin binding was defective in signaling and ternary complex formation, and acted as an antagonist, although the mutant still bound to IGF1R, suggesting that IGF1 binding to α6β4 plays a critical role in IGF1R activation. β4 has a unique long tail (>1000 residues) and deletion of part of the β4 tail containing the calx-β domain is known to reduce cell proliferation. We thus hypothesized that calx-β is involved in IGF1 signaling. Docking simulation predicted that calx-β binds to IGF1R kinase. We discovered that isolated calx-β bound to the IGF1R kinase domain. Point mutations in the predicted calx-β binding site in IGF1R kinase inhibited calx-β binding to IGF1R kinase. Notably, the isolated calx-β domain with cell-penetrating peptide (Tat-calx-β) enhanced survival of keratinocytes and non-transformed cells without IGF1. Tat-calx-β did not enhance survival of cancer cells. Several missense mutations are clustered in the predicted IGF1R kinase binding site of the calx-β domain of β4 in genetic skin blistering disease (JEB-PA). We discovered that several JEB-PA mutants were defective in calx-β binding to the IGF1R kinase and inhibited cell survival of keratinocytes, suggesting that these mutations may suppress calx-b binding to IGF1R kinase. These findings suggest that IGF1 binding to α6β4 triggers calx-β binding to the IGF1R kinase and activates IGF1R kinase.

Abstract: This study investigates the microstructural evolution and mechanical behavior of a Ni-based superalloy subjected to combined heat treatment and laser processing. Special emphasis is placed on the quantitative analysis of γ′ Ni₃(Al,Ti) and η (Ni₃Ti) phase distributions using SEM-based statistical methods. OM/XRD were employed for initial structural and phase identification, followed by detailed microstructural characterization using SEM/EDS. The results reveal that γ′ precipitates exhibit a fine and uniform distribution with a high number density, whereas the η (Ni₃Ti) phase appears as relatively coarse and sparsely distributed particles. Statistical size distribution analysis demonstrates that processing parameters significantly influence precipitate morphology and phase stability. Laser treatment promotes redistribution of γ′ precipitates and suppresses η (Ni₃Ti) phase formation, resulting in improved microstructural homogeneity. Mechanical characterization shows a strong correlation between γ′ Ni₃(Al,Ti) phase refinement and enhanced hardness and tensile properties. Fractography analysis indicates predominantly ductile fracture behavior with microvoid coalescence. The findings provide a quantitative understanding of phase evolution and establish a microstructure property relationship for optimizing Ni-based superalloys through advanced processing techniques.

Abstract: Not all sleep loss is the same, and failing to recognise this is the biggest barrier to advancing research in sleep and neurological diseases. This review systematically compares nine rodent sleep deprivation paradigms: gentle handling, the multiple platform method and its variants, the disk-over-water method, the Unpredictable Chronic Sleep Deprivation (UCSD) paradigm developed in our laboratory, novel object introduction, the curling prevention by water approach, automated mechanical systems, and the head-lifting method. It evaluates each for stress confound profile, sleep stage specificity, chronicity, and the neurobiological outcome domains to which it is appropriately suited. We describe the neuroimmune and neurochemical consequences of sleep loss across these models, covering hippocampal synaptic plasticity, prefrontal neurochemistry, glymphatic waste clearance, neuroinflammation, oxidative stress, hippocampal neurogenesis, and circadian clock gene regulation, and situate these findings within the translational context of Alzheimer's disease, Parkinson's disease, and neuropsychiatric comorbidities. Special attention is given to the UCSD paradigm, in which five established sleep disrupters, gentle handling, 24/0 h light/dark cycle, platform-over-water, crowded cage, and stroboscopic light, were applied in daily rotation without repetition across fourteen days. Using this paradigm, our group showed that chronic unpredictable sleep disruption, especially when combined with high-dose caffeine, causes prefrontal antioxidant depletion, serotonin loss, acetylcholinesterase upregulation, and synaptophysin reduction, confirmed through immunohistochemistry in Long-Evans rats, a neurochemical signature that aligns with early markers of neurodegeneration. We propose a disease-target-driven model selection framework, a six-priority translational research agenda, and minimum reporting standards for the field.

Abstract: Background: Patients with Kawasaki disease (KD) who develop coronary artery aneurysms (CAAs) are at increased risk of future fatal coronary events. Pharmacotherapeutic strategies to prevent coronary stenosis are still lacking. This study investigated the therapeutic effect of the angiotensin receptor blocker (ARB) losartan, on coronary artery stenosis in a murine model. Methods: Five-week-old male C57BL/6J mice were intraperitoneally injected with 1,000 μg of Lactobacillus casei cell wall extract (LCWE) (n=12) to induce coronary artery stenosis. Two weeks later, LCWE-injected mice (n=12) were divided into two groups: six received drinking water containing losartan (100 mg/L) (LCWE+ARB), while six received normal drinking water (LCWE group). A control group (n=5) received phosphate-buffered saline (PBS) instead of LCWE. Sixteen weeks after LCWE administration—corresponding to the peak of coronary artery stenosis and 14 weeks after treatment initiation—the mice were euthanized for histological evaluation of the coronary arteries. Results: Losartan treatment significantly reduced the coronary arteritis score (4.3±3.3 vs. 19.3±2.8, p=0.003). LCWE-induced neointimal formation with vascular smooth muscle cell (VSMC) proliferation and subsequent coronary artery stenosis were markedly attenuated in losartan-treated mice (25% vs. 100%, p<0.001). Moreover, losartan inhibited coronary artery stenosis, at least in part, by preventing the phenotypic switch of vascular VSMCs from a contractile to a synthetic phenotype. Conclusions: Losartan is a potential therapeutic agent for preventing coronary events in KD by suppressing intimal proliferation and modulating the VSMC phenotype.