Search Results (7,135)

Background: Solid organ transplantation (SOT) is a life-saving treatment for patients with end-stage diseases and/or organ failure. However, access to healthy organs is often limited by challenges in organ preservation. Furthermore, upon transplantation, ischemia–reperfusion injury (IRI) can lead to increased organ rejection or graft failures. The work presented aims to address both challenges using an innovative nanomedicine platform for simultaneous drug and oxygen delivery. In recent studies, resveratrol (RSV), a natural antioxidant, anti-inflammatory, and reactive oxygen species (ROS) scavenging agent, has been reported to protect against IRI by inhibiting ferroptosis. Here, we report the design, development, and scalable manufacturing of the first-in-class dual-function perfluorocarbon-nanoemulsion (PFC-NE) perfusate for simultaneous oxygen and antioxidant delivery, equipped with a near-infrared fluorescence (NIRF) reporter, longitudinal, non-invasive NIRF imaging of perfusate flow through organs/tissues during machine perfusion. Methods: A Quality-by-Design (QbD)-guided optimization was used to formulate a triphasic PFC-NE with 30% w/v perfluorooctyl bromide (PFOB). Drug-free perfluorocarbon nanoemulsions (DF-NEs) and RSV-loaded nanoemulsions (RSV-NEs) were produced at 250–1000 mL scales using M110S, LM20, and M110P microfluidizers. Colloidal attributes, fluorescence stability, drug loading, and RSV release were evaluated using DLS, NIRF imaging, and HPLC, respectively. PFC-NE oxygen loading and release kinetics were evaluated during perfusion through the BMI OrganBank^® machine with the MEDOS HILITE^® oxygenator and by controlled flow of oxygen. The in vitro antioxidant activity of RSV-NE was measured using the oxygen radical scavenging antioxidant capacity (ORAC) assay. The cytotoxicity and ferroptosis inhibition of RSV-NE were evaluated in RAW 264.7 macrophages. Results: PFC-NE batches maintained a consistent droplet size (90–110 nm) and low polydispersity index (<0.3) across all scales, with high reproducibility and >80% PFOB loading. Both DF-NE and RSV-NE maintained colloidal and fluorescence stability under centrifugation, serum exposure at body temperature, filtration, 3-month storage, and oxygenation. Furthermore, RSV-NE showed high drug loading and sustained release (63.37 ± 2.48% at day 5) compared with the rapid release observed in free RSV solution. In perfusion studies, the oxygenation capacity of PFC-NE consistently exceeded that of University of Wisconsin (UW) solution and demonstrated stable, linear gas responsiveness across flow rates and FiO₂ (fraction of inspired oxygen) inputs. RSV-NE displayed strong antioxidant activity and concentration-dependent inhibition of free radicals. RSV-NE maintained higher cell viability and prevented RAS-selective lethal compound 3 (RSL3)-induced ferroptosis in murine macrophages (macrophage cell line RAW 264.7), compared to the free RSV solution. Morphological and functional protection against RSL3-induced ferroptosis was confirmed microscopically. Conclusions: This study establishes a robust and scalable PFC-NE platform integrating antioxidant and oxygen delivery, along with NIRF-based non-invasive live monitoring of organ perfusion during machine-supported preservation. These combined features position PFC-NE as a promising next-generation acellular perfusate for preventing IRI and improving graft viability during ex vivo machine perfusion. Full article

The increasing urgency to mitigate plastic pollution has accelerated the shift from linear manufacturing toward circular systems. This review synthesizes current advances in mechanical, chemical, biological, and upcycling pathways, emphasizing how artificial intelligence (AI) is reshaping decision-making, performance prediction, and system-level optimization. Intelligent sensing technologies—such as FTIR, Raman spectroscopy, hyperspectral imaging, and LIBS—combined with Machine Learning (ML) classifiers have improved material identification, reduced reject rates, and enhanced sorting precision. AI-assisted kinetic modeling, catalyst performance prediction, and enzyme design tools have improved process intensification for pyrolysis, solvolysis, depolymerization, and biocatalysis. Life Cycle Assessment (LCA)-integrated datasets reveal that environmental benefits depend strongly on functional-unit selection, energy decarbonization, and substitution factors rather than mass-based comparisons alone. Case studies across Europe, Latin America, and Asia show that digital traceability, Extended Producer Responsibility (EPR), and full-system costing are pivotal to robust circular outcomes. Upcycling strategies increasingly generate high-value materials and composites, supported by digital twins and surrogate models. Collectively, evidence indicates that AI moves from supportive instrumentation to a structural enabler of transparency, performance assurance, and predictive environmental planning. The convergence of AI-based design, standardized LCA frameworks, and inclusive governance emerges as a necessary foundation for scaling circular plastic systems sustainably. Full article

Global chestnut production has grown significantly in recent years, driven by its health benefits and growing interest in sustainable agriculture. Chestnut processing produces a solid residue consisting primarily of the fruit’s outer shell (pericarp), which is generally disposed of by on-farm combustion. However, this waste biomass shows a high potential for valorization due to its nutritional composition, particularly as a source of dietary fiber and polyphenols. In this study, the valorization potential of chestnut outer shells was evaluated through two approaches, demonstrating possible applicability at an industrial level: (1) the recovery of polyphenols using a simple and environmentally friendly extraction method, easily applicable on-farm, based on hot water as a solvent under different time–temperature combinations according to Response Surface Methodology (Central Composite Design); (2) the addition of chestnut outer shell flour during breadmaking as a source of fiber supplementation. Optimization of the extraction process using Response Surface Methodology combined with the desirability function identified optimal conditions at 102 min and 115 °C, yielding a maximum of approximately 172.30 mg of polyphenols per gram of dry outer shell. The incorporation of chestnut outer shell flour into bread formulations resulted in reduced dough workability, increased crust hardness (13.00 ± 0.87; 36.00 ± 1.00), and a darker bread color (1278.33 ± 39.27; 584.33 ± 25.90 RGB), particularly in the crumb. Full article

Next-generation therapeutic devices will rely on an intelligent integrated system that consolidates multiple functions into a single platform. These individual chemical components exhibit diverse physicochemical properties, demonstrating multifunctional characteristics. In this review, we focus on how the distinctive properties of upconversion nanoparticles (UCNPs), achieved via refined preparation methods, unlock novel functionalities in biomedical applications. Specifically, features such as near-infrared excitation, deep-tissue penetration, low autofluorescence, and tunable multicolor emission endow UCNPs with substantial potential in fields including deep-tissue imaging, targeted drug delivery, and photodynamic therapy. This article systematically reviews recent advances in the design and functionalization of UCNPs, elucidating their role in facilitating the development of integrated diagnostic and therapeutic platforms and fostering the establishment of intelligent responsive treatment systems. Finally, we address current technical challenges—including uniformity in large-scale production, long-term biosafety, and in vivo metabolic mechanisms—and provide insights into future interdisciplinary integration, clinical translation pathways, and their potential role in personalized medicine. Full article

Soil organic matter (SOM) is a key indicator for evaluating soil fertility and ecological functions, and hyperspectral technology provides an effective means for its rapid and non-destructive estimation. However, in practical soil systems, the spectral response of SOM is often highly covariant with mineral composition, moisture conditions, and soil structural characteristics. Under small-sample conditions, hyperspectral SOM modeling results are usually highly sensitive to spectral preprocessing methods, sample perturbations, and model architecture and parameter configurations, leading to fluctuations in predictive performance across independent runs and thereby limiting model stability and practical applicability. To address these issues, this study proposes a multi-strategy collaborative deep learning modeling framework for small-sample conditions (SE-EDCNN-DA-LWGPSO). Under unified data partitioning and evaluation settings, the framework integrates spectral preprocessing, data augmentation based on sensor perturbation simulation, multi-scale dilated convolution feature extraction, an SE channel attention mechanism, and a linearly weighted generalized particle swarm optimization algorithm. Subtropical red soil samples from Guangxi were used as the study object. Samples were partitioned using the SPXY method, and multiple independent repeated experiments were conducted to evaluate the predictive performance and training consistency of the model under fixed validation conditions. The results indicate that the combination of Savitzky–Golay filtering and first-derivative transformation (SG–1DR) exhibits superior overall stability among various preprocessing schemes. In model structure comparison and ablation analysis, as dilated convolution, data augmentation, and channel attention mechanisms were progressively introduced, the fluctuations of prediction errors on the validation set gradually converged, and the performance dispersion among different independent runs was significantly reduced. Under ten independent repeated experiments, the final model achieved R² = 0.938 ± 0.010, RMSE = 2.256 ± 0.176 g·kg⁻¹, and RPD = 4.050 ± 0.305 on the validation set, demonstrating that the proposed framework has good modeling consistency and numerical stability under small-sample conditions. Full article

Introduction: Massage therapy delivers structured mechanosensory input that can influence brain function, yet the central mechanisms and potential for neuroplastic change have not been synthesized across neuroimaging modalities. This mechanistic review integrates evidence from electroencephalography (EEG), functional MRI (fMRI), and functional near-infrared spectroscopy (fNIRS) to map how massage alters human brain activity acutely and over time and to identify signals of longitudinal adaptation. Materials and Methods: We conducted a scoping, mechanistic review informed by PRISMA/PRISMA-ScR principles. PubMed/MEDLINE, Cochrane Library, Google Scholar, and ResearchGate were queried for English-language human trials (January 1990–July 2025) that (1) delivered a practitioner-applied manual massage (e.g., Swedish, Thai, shiatsu, tuina, reflexology, myofascial techniques) and (2) measured brain activity with EEG, fMRI, or fNIRS pre/post or between groups. Non-manual stimulation, structural-only imaging, protocols, and non-English reports were excluded. Two reviewers independently screened and extracted study, intervention, and neuroimaging details; heterogeneity precluded meta-analysis, so results were narratively synthesized by modality and linked to putative mechanisms and longitudinal effects. Results: Forty-seven studies met the criteria: 30 EEG, 12 fMRI, and 5 fNIRS. Results: Regarding EEG, massage commonly increased alpha across single sessions with reductions in beta/gamma, alongside pressure-dependent autonomic shifts; moderate pressure favored a parasympathetic/relaxation profile. Connectivity effects were state- and modality-specific (e.g., reduced inter-occipital alpha coherence after facial massage, preserved or reorganized coupling with hands-on vs. mechanical delivery). Frontal alpha asymmetry frequently shifted leftward (approach/positive affect). Pain cohorts showed decreased cortical entropy and a shift toward slower rhythms, which tracked analgesia. Somatotopy emerged during unilateral treatments (contralateral central beta suppression). Adjuncts (e.g., binaural beats) enhanced anti-fatigue indices. Longitudinally, repeated programs showed attenuation of acute EEG/cortisol responses yet improvements in stress and performance; in one program, BDNF increased across weeks. In preterm infants, twice-daily massage accelerated EEG maturation (higher alpha/beta, lower delta) in a dose-responsive fashion; the EEG background was more continuous. In fMRI studies, in-scanner touch and reflexology engaged the insula, anterior cingulate, striatum, and periaqueductal gray; somatotopic specificity was observed for mapped foot areas. Resting-state studies in chronic pain reported normalization of regional homogeneity and/or connectivity within default-mode and salience/interoceptive networks after multi-session tuina or osteopathic interventions, paralleling symptom improvement; some task-based effects persisted at delayed follow-up. fNIRS studies generally showed increased prefrontal oxygenation during/after massage; in motor-impaired cohorts, acupressure/massage enhanced lateralized sensorimotor activation, consistent with use-dependent plasticity. Some reports paired hemodynamic changes with oxytocin and autonomic markers. Conclusions: Across modalities, massage reliably modulates central activity acutely and shows convergent signals of neuroplastic adaptation with repeated dosing and in developmental windows. Evidence supports (i) rapid induction of relaxed/analgesic states (alpha increases, network rebalancing) and (ii) longer-horizon changes—network normalization in chronic pain, EEG maturation in preterm infants, and neurotrophic up-shifts—consistent with trait-level recalibration of stress, interoception, and pain circuits. These findings justify integrating massage into rehabilitation, pain management, mental health, and neonatal care and motivate larger, standardized, multimodal longitudinal trials to define dose–response relationships, durability, and mechanistic mediators (e.g., connectivity targets, neuropeptides). Full article

Porcine epidemic diarrhea virus (PEDV) has emerged as a major pathogen responsible for porcine diarrheal diseases, causing outbreaks of severe diarrhea and high mortality in neonatal piglets, thereby inflicting severe economic losses on the global swine industry. Current commercial PED vaccines, comprising conventional inactivated and live attenuated formulations, have exhibited progressively diminished efficacy in the face of emerging PEDV variants. The development of high-efficiency vaccine platforms is therefore critical for PED control. This study engineered a cellular membrane nanovesicle (CMN)-based vaccine, which differs from existing inactivated or subunit vaccines by presenting the PEDV spike (S) protein on the cell membranes to mimic the bilayer phospholipid structure of the viral envelope. The full-length S protein (FS, aa 19-1309) or a truncated S protein fragment (TS, aa 19-726) was expressed in Expi293F cells, followed by extraction of cell membranes to assemble antigen-displaying CMN vaccines. Compared with commercial live attenuated vaccine, administration of the CMN vaccine elicited high-titer neutralizing antibodies and elevated IFN-γ-producing CD8⁺ T cells in murine studies. Safety assessments revealed no adverse effects on body weight, hepatic/renal function indices, or histopathological parameters in vaccinated mice. Furthermore, immunization of piglets elicited notable humoral and CD8⁺ T cell immune responses. Collectively, the strategy of CMN-based vaccine described herein delivers a potential PEDV vaccine platform, thereby offering a novel avenue for next-generation veterinary vaccine development. Full article

This study analyzes the relationship between macroeconomic distress and financial dollarization in Türkiye using annual regional panel data for 26 Nomenclature of Territorial Units for Statistics 2 regions over the period 2005–2021. Macroeconomic distress is captured using the misery index, computed as the compound of inflation and unemployment rates, while the share of foreign-currency-denominated deposits in total deposits measures financial dollarization. Applying second-generation panel econometric models that account for regional heterogeneity, we investigate both long-run equilibrium relationships and short-run interactions. Panel cointegration tests show a long-run connection between macroeconomic distress and dollarization. Short-run effects estimated using a Panel Vector Error Correction Model and a Cross-Sectionally Augmented ARDL framework point to bidirectional causality. Long-run coefficient estimates obtained via Dynamic Ordinary Least Squares indicate an apparent asymmetry. Increases in dollarization exert a substantial and economically significant effect on macroeconomic distress, whereas the long-run impact of distress on dollarization is comparatively modest. The findings suggest that dollarization functions not only as a response to macroeconomic instability but also as a structural element that intensifies inflationary pressures and labor market distortions over time. Focusing on regional patterns rather than national aggregates, the paper provides new evidence on the spatial dimension of the dollarization–instability link. Full article

Based upon density functional theory (DFT) calculations, we present the basic electronic structure of CuPb₉(PO₄)₆O (Cu-doped lead apatite, aka LK-99), in two scenarios: (1) where the structure is constrained to the P3 symmetry and (2) where no symmetry is imposed. At the DFT level, the former is predicted to be metallic while the latter is found to be a charge-transfer insulator. In both cases the filling of these states is nominally $d^9$, consistent with the standard Cu²⁺ valence state, and Cu with a local magnetic moment of order 0.7 μ_B. In the metallic case we find these states to be unusually flat (∼0.2 eV dispersion), giving a very high density of electronic states (DOS) at the Fermi level that we argue can be a host for novel electronic physics. The flatness of the bands is the likely origin of symmetry-lowering gapping possibilities that would remove the spectral weight from $E_F$. Motivated by some initial experimental observations of metallic or semiconducting behavior, we propose that disorder (likely structural) is responsible for closing the gap. Here, we consider a variety of possibilities that could possibly close the charge-transfer gap but limit consideration to kinds of disorder that preserve electron count. Of the possible kinds we considered (spin disorder, O populating vacancy sites, and Cu on less energetically favorable Pb sites), the local Cu moment, and consequently the charge-transfer gap, remains robust. We conclude that disorder responsible for metallic behavior entails some kind of doping where the electron count changes. Further, we claim that the emergence of the flat bands should be due to weak wave function overlap between the orbitals on Cu and O sites, owing to the directional character of the constituent orbitals. Therefore, finding an appropriate host structure for minimizing hybridization between Cu and O while allowing them to still weakly interact should be a promising route for generating flat bands at $E_F$ which can lead to interesting electronic phenomena, regardless of whether LK-99 is a superconductor. Full article

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Compared with traditional two-dimensional (2D) models, patient-derived CRC organoids more faithfully preserve the genomic, transcriptomic, and architectural features of primary tumors, making them a powerful intermediate platform bridging basic discovery and clinical translation. Over the past several years, organoid systems have rapidly expanded beyond conventional epithelial-only cultures toward increasingly complex architectures, including immune-organoid co-culture models and mini-colon systems that enable long-term, spatially resolved tracking of tumor evolution. These advanced platforms, combined with high-throughput technologies and clustered regularly interspaced short palindromic repeats (CRISPR)-based functional genomics, have substantially enhanced our ability to dissect CRC mechanisms, identify therapeutic vulnerabilities, and evaluate drug responses in a physiologically relevant context. However, current models still face critical limitations, such as the lack of systemic physiology (e.g., gut–liver or gut–brain axes), limited standardization across platforms, and the need for large-scale, prospective clinical validation. These gaps highlight an urgent need for next-generation platforms and computational frameworks. The development of high-throughput multi-omics, CRISPR-based perturbation, drug screening technologies, and artificial intelligence-driven predictive approaches will offer a promising avenue to address these challenges, accelerating mechanistic studies of CRC, enabling personalized therapy, and facilitating clinical translation. In this perspective, we propose a roadmap for CRC organoid research centered on two major technical pillars: advanced organoid platforms, including immune co-culture and mini-colon systems, and mechanistic investigations leveraging multi-omics and CRISPR-based functional genomics. We then discuss translational applications, such as high-throughput drug screening, and highlight emerging computational and translational strategies that may support future clinical validation and precision medicine. Full article

Defect modes in phononic crystals (PnCs) provide strongly localized resonances that are essential for frequency-dependent wave filtering and highly sensitive sensing. Their functionality increases greatly when their spectral characteristics can be externally tuned without altering the structural configuration. However, existing feedback control strategies rely on laminated piezoelectric defects, which have uniform electromechanical loading that causes voltage cancellation for even-symmetric defect modes. Consequently, only odd-symmetric defect bands can be manipulated effectively, which limits multi-band tunability. To overcome this constraint, we propose a segmented piezoelectric sensor–actuator design that enables symmetry-dependent feedback at the defect site. We develop a transfer-matrix analytical framework to incorporate complex-valued feedback gains directly into dispersion and transmission calculations. Analytical predictions demonstrate that real-valued feedback yields opposite stiffness modifications for odd- and even-symmetric modes. This enables the simultaneous tuning of both defect bands and induces an exceptional-point-like coalescence. In contrast, imaginary feedback preserves stiffness but modulates effective damping, generating a parity-dependent amplification-suppression response. The analytical results closely match those of fully coupled finite-element simulations, reducing computation time by more than two orders of magnitude. These findings demonstrate that segmentation-enabled feedback provides an efficient and scalable approach to tunable, multi-band, non-Hermitian wave control in piezoelectric PnCs. Full article

Photodynamic therapy (PDT) is a minimally invasive therapeutic modality that relies on the activation of photosensitizers (PS) by specific wavelengths of light to generate reactive oxygen species (ROS), resulting in localized cytotoxicity with relative sparing of healthy tissues. Depending on the PS properties, light dose, and intrinsic cellular features, PDT can elicit multiple cell death pathways, including apoptosis, necrosis, and autophagy. Increasing evidence indicates that PDT is also a potent inducer of ferroptosis, an iron-dependent form of regulated cell death driven by excessive lipid peroxidation (LPO), glutathione (GSH) depletion, and inactivation of glutathione peroxidase 4 (GPX4). PDT-derived ROS promote ferroptosis both indirectly by exhausting antioxidant defenses and directly by peroxidizing PUFAs within membrane phospholipids. At the same time, intense oxidative stress generated by PDT can activate adaptive responses such as mitophagy, a selective autophagic process that removes damaged mitochondria to limit ROS production and preserve redox homeostasis. Ferroptosis and mitophagy are therefore tightly interconnected, functioning as opposing yet complementary regulators of cell fate. PDT emerges as a key upstream modulator of the ferroptosis–mitophagy balance, as spatially and temporally confined oxidative stress can shift cellular responses from adaptive mitochondrial quality control to irreversible ferroptotic injury. Despite growing interest in both PDT and ferroptosis, their mechanistic interplay, particularly in relation to mitophagy, remains underexplored. This narrative review provides an integrated overview of current knowledge on how PDT influences ferroptosis and mitophagy, highlighting the molecular mechanisms that connect these pathways and discussing their implications for improving therapeutic efficacy and overcoming resistance. Full article

Promoting the development of aerospace vehicles toward structural–functional integration and intelligent sensing is a key strategy for achieving lightweight, high-reliability, and autonomous operation and maintenance of next-generation aircraft. However, traditional external sensors face significant limitations because of their bulky size, installation challenges, and incompatibility with aerodynamic surfaces. These issues are particularly pronounced on complex, high-curvature substrates, where achieving conformal bonding is difficult, thus restricting their application in critical components. In this study, aerosol jet printing (AJP) was employed to directly fabricate silver nanoparticle-based temperature sensors with real-time monitoring capabilities on the surface of high-curvature stainless steel sleeves, which serve as typical engineering components. This approach enables the in situ manufacturing of high-precision conformal sensors. Through optimized structural design and thermal treatment, the sensors exhibit reliable temperature sensitivity. Microscopic characterization reveals that the printed sensors possess uniform linewidths and well-defined outlines. After gradient sintering at 250 °C, a dense and continuous conductive path is formed, ensuring strong adhesion to the substrate. Temperature-monitoring results indicate that the sensor exhibits a nearly linear resistance response (R² > 0.999) across a broad detection range of 20–200 °C. It also demonstrates high sensitivity, characterized by a temperature coefficient of resistance (TCR) of 2.15 × 10^−3/°C at 20 °C. In repeated thermal cycling tests, the sensor demonstrates excellent repeatability and stability over 100 cycles, with resistance fluctuations kept within 0.5% and negligible hysteresis observed. These findings confirm the feasibility of using AJP technology to fabricate high-performance conformal sensors on complex surfaces, offering a promising strategy for the development of intelligent structural components in next-generation aerospace engineering. Full article

Bidirectional communication between the central nervous system and the immune system is crucial for brain function, particularly in regulating neuroplasticity: on the one hand, glial cells modulate neuronal function, brain circuitry, axon myelination, dendritic spine architecture, and information processing, while on the other hand, neuronal activity can alter the immune response. Neuroinflammation and dysregulation of astroglia and microglia can be detrimental to brain development and function. In particular, maladaptive responses and chronic glial activation have been correlated to synaptic dysfunction in diverse brain conditions. In the present review, we will provide a general introduction to the main players of the neuroimmune response and their ability to modulate neuroplasticity, followed by a comprehensive overview of experimental evidence linking the dysregulation of immune mediators to the disruption of synaptic plasticity in neurodegenerative and neurodevelopmental disorders, with a specific focus on Alzheimer’s disease, Parkinson’s disease, and autism spectrum disorder. Full article

This study explores the factors that influence Gen Z consumers’ green purchasing behavior, addressing a gap in current research by combining the Theory of Planned Behavior, the Theory of Consumption Values, and Generational Theory, and applying them to the touristic accommodation context. Based on a quantitative survey of Gen Z tourists from Spain, Norway, and Lithuania, the study examined traditional constructs of the Theory of Planned Behavior alongside subjective knowledge, environmental consciousness, perceived value, and green trust. Using Partial Least Squares Structural Equation Modeling (PLS-SEM), the results indicate a significant role for price-based functional value and emotional value in shaping Gen Z’s attitudes toward sustainable accommodation. Furthermore, subjective knowledge and environmental consciousness strengthen green trust, which in turn contributes to a more positive attitude toward sustainable touristic options. Attitude, subjective norms, and perceived behavioral control significantly predict behavioral intention, while both perceived behavioral control and behavioral intention directly influence actual purchasing behavior. The findings suggest that tourism marketers should focus on enhancing price-related and emotionally meaningful value propositions, while also fostering trust through clear communication of environmental performance. Overall, the study offers a comprehensive understanding of the drivers behind Gen Z’s sustainable accommodation choices and provides practical implications for promoting environmentally responsible tourism. Full article