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Sex differences in the mediating role of brain-derived neurotrophic factor between inflammation and memory in cirrhotic patients with minimal hepatic encephalopathy
Get PDFMinimal hepatic encephalopathy (MHE) affects attention, visuo-motor coordination, and visual perception, with mixed evidence on its impact on memory. Brain-derived neurotrophic factor (BDNF) is associated with memory dysfunction, and plays a crucial role in modulating neuroplasticity. This study investigates the mediating role of BDNF in the relationship between pro-inflammatory cytokines (IL-6, IL-15, IL-18), and declarative memory performance, and the moderating effects of sex. Sixty-eight cirrhotic patients and 22 healthy volunteers performed the Psychometric Hepatic Encephalopathy Score for MHE diagnosis and logical memory subtest (Wechsler Memory Scale-III). Moderated mediation analysis using bias-corrected bootstrapping and multiple regression was performed. Results showed that increased levels of IL-18 and IL-15 were significantly associated with lower BDNF levels (p = 0.03 and p = 0.02 respectively). However, no direct effect was observed between IL-18 and IL-15 and memory. The conditional effects of BDNF on memory were significant only for women with and without MHE, and lower BDNF levels were associated with lower memory performance (without MHE: p = 0.002; MHE: p = 0.001). Moreover, BDNF mediated indirectly the relationship between pro-inflammatory cytokines and memory. IL-18 and IL-15 impacted memory through reduced BDNF levels only in women with and without MHE, whereas IL-6 showed no significant effect on BDNF or memory across groups. These findings underscore the important role of BDNF in memory in cirrhotic patients, especially women with MHE, by mediating the IL-18 and IL-15 effects. The study highlights the role of IL-18 and IL-15 cytokines in neuroplasticity-related memory decline, positioning BDNF as a key biomarker for inflammation-associated cognitive impairment in this population
Seroprevalence of Toxoplasma gondii in Wild European and American Mink (Mustela lutreola and Neogale vison) from Spain
Get PDFToxoplasmosis, caused by the intracellular parasite Toxoplasma gondii, affects a wide range of warm-blooded animals, including humans. Domestic and wild felines serve as definitive hosts, excreting oocysts that contaminate the environment. Intermediate hosts, such as the endangered European mink (Mustela lutreola) and the non-native American mink (Neogale vison), can become infected primarily through the ingestion of tissue cysts present in prey, while the ingestion of oocysts from contaminated soil or water plays a secondary role. This study analyzed the seroprevalence of T. gondii in 179 mink specimens (137 American mink and 42 European mink) collected in northern Spain from 2014 to 2020. Using an optimized indirect immunofluorescence assay, antibodies against T. gondii were detected in 47 samples (37 American mink and 10 European mink). Seroprevalence was higher in the Ebro basin than in the Cantabrian region, although the difference was not statistically significant. No significant associations were observed between seropositivity and species, sex, or habitat. These findings suggest environmental contamination by T. gondii oocysts in northern Spain and underscore the potential value of invasive American mink as sentinel species for monitoring public health risks associated with this parasite. The study also highlights the importance of wildlife surveillance in assessing environmental contamination and understanding transmission dynamics of infectious diseases in ecosystems
Voltage-controlled rotation of magnetic anisotropy in the Ni<sub>90</sub>Fe<sub>10</sub>/BaTiO<sub>3</sub>(001) heterostructure
No full textIn this work, we demonstrate the voltage control of magnetic anisotropy in a strain-mediated Ni90Fe10/BaTiO3(001) heterostructure. In the pristine state of the heterostructure, the magneto-optical Kerr effect measurements show a transcritical hysteresis loop for the Ni90Fe10 film, indicating a weak perpendicular anisotropy. This was further confirmed by X-ray magnetic circular dichroism – photoemission electron microscopy, revealing stripe domains in this film. X-ray diffraction analysis of the BaTiO3 substrate under varying electric fields was used to analyze the orientation of ferroelectric domains. These results indicated that BaTiO3 exhibits two distinct states depending on the applied electric field: one with domains aligned with the electric field and another with random domain orientation when the field is removed. After substrate poling, the Ni90Fe10 layer switches from weak perpendicular anisotropy to an in-plane uniaxial magnetic anisotropy, with the in-plane direction of anisotropy being controllable by 90° through an electric field. This effect is due to an efficient strain transfer from BaTiO3 to the Ni90Fe10 lattice, induced by ferroelectric polarization, as shown by XRD. Remarkably, this rotation of the magnetic anisotropy leads to an enhanced converse magnetoelectric coupling value of 1.43 μs m−1, surpassing previously reported values for other BaTiO3-based heterostructures by an order of magnitude. These results emphasize the potential of Ni90Fe10 alloys for next-generation magnetoelectric devices
Preserved efficacy of lyophilized SARS-CoV-2 mRNA vaccine incorporating novel ionizable lipids after one year at 25 °C
No full textmRNA vaccines have shown great efficacy against SARS-CoV-2, yet challenges remain in optimizing vaccine components to achieve enhanced immune response and vaccine stability. In this study, we developed CPVax-CoV, a new lyophilized mRNA vaccine that features novel thiolactone-based ionizable lipids and newly designed untranslated regions (UTRs) for enhanced expression. Incorporation of these optimized components into our vaccine candidate CPVax-CoV significantly improved immune responses in mice compared to commercially available mRNA vaccines. Moreover, lyophilized CPVax-CoV has proven to be thermostable, maintaining its biological activity for up to one year at 4 °C and 25 °C after lyophilization, overcoming the cold-chain limitations of current mRNA vaccines. This vaccine demonstrates protective efficacy against ancestral SARS-CoV-2 and the Omicron XBB variant, offering a scalable solution for global distribution and pandemic preparedness. These findings underscore the potential of this platform for future next-generation mRNA vaccine development
Relationships between heart shape, function, and disease in 38,858 UK biobank participants
No full textBackground. Cardiac functional metrics such as ejection fraction, strain, and valve excursion are important diagnostic and prognostic measures of cardiac disease. However, they ignore a large amount of systolic shape change information available from modern cardiovascular magnetic resonance (CMR) examinations.
We aimed to automatically quantify multidimensional shape and motion scores from CMR, investigate covariates, and test their discrimination of disease in the UK Biobank compared against standard functional metrics.
Methods. An automated analysis pipeline was used to obtain quality-controlled three-dimensional left and right ventricular shape models in 38,858 UK Biobank participants, 5149 of whom had one or more diagnoses of cardiovascular or cardiometabolic disease. Principal component analysis was used to obtain a statistical shape atlas and quantify each participant’s left and right ventricular shape at both end-diastole and end-systole simultaneously. Systolic strain was obtained from arc length changes computed from the shape model, and mitral/tricuspid annular plane systolic excursion (MAPSE/TAPSE) was computed from the displacement of the valves. Discrimination for prevalent disease was quantified using linear discriminant analysis area under the receiver operating characteristic curve.
Results. The first 25 principal component scores captured >90% of the total shape variance. Significantly stronger discrimination for atrial fibrillation, heart failure, diabetes, ischemic disease, and conduction disorders (p<0.001 for each) was obtained using shape scores compared with volumes, ejection fractions, strains, MAPSE, and TAPSE.
Conclusion. Automatically derived shape and motion z-scores capture more discriminative information on disease effects than standard metrics, including volumes, ejection fraction, strain and valve excursions
Exploring Intensity-Dependent Echogenic Response to Percutaneous Electrolysis in Tendon Tissue: A Cadaveric Study
No full textBackground: Percutaneous electrolysis (PE) is an emerging therapeutic approach for tendinopathies, applying a galvanic current through a dry-needling needle to induce regenerative tissue responses. However, current dosing strategies are often empirical and lack objective physiological feedback. Objective: This study aimed to evaluate the echogenic effects of different galvanic current intensities on cadaveric tendon tissue using quantitative ultrasound. Methods: An ex vivo study was conducted on 29 cadaveric patellar tendon samples, each exposed to a single intensity (0–10 mA for 1 s). Quantitative ultrasound analysis was performed post-intervention, and echogenic variables were extracted using UZ eDosifier software. A composite variable, Electrolysis_UZ_Dose, was created via multiple regression to capture the overall ultrasound-visible changes. Data were analyzed using correlation, regression models, and dose–range comparisons. Results: An intensity-dependent response was observed in key echogenic parameters. Minimal changes occurred at low intensities (0–2 mA), whereas a progressive response emerged between 2 and 6 mA. Beyond 6 mA, a plateau effect suggested either tissue saturation or imaging limitations due to gas-induced acoustic shadowing. The Electrolysis_UZ_Dose variable strongly correlated with applied intensity (R2 = 0.732). Conclusions: This study suggests an intensity-dependent echogenic effect of PE on tendon tissue in key ultrasound-derived parameters (A_Number, A_Area, A_Perimeter, A_Homogeneity, and A_ASM). However, as this study was conducted under experimental conditions with a single 1 s application per sample, the results should not be extrapolated to clinical practice without further validation
Mitigation of organic fouling in membrane distillation via 3D printed wavy composite membranes
No full textMembrane distillation (MD) has the potential to tackle water scarcity challenges, as it can process non-traditional water sources to meet the growing water demand globally. However, long-term operation of MD systems is hampered by fouling of the membrane's surface which leads to reduced process efficiency. To address this, this study utilised 3D printed double sinusoidal (wavy) supports designed to enhance hydrodynamics at the membrane surface, mitigate organic fouling, and improve cleaning efficiency in air gap MD (AGMD). Computational Fluid Dynamics (CFD) simulations of turbulent water flow showed that wavy surfaces enhance surface shear stress and turbulent kinetic energy, reducing foulant deposition and facilitating foulant detachment during cleaning. Polyvinylidene fluoride (PVDF) hydrophobic films (thickness > 100 μm) were attached to 3D printed flat and wavy supports via vacuum filtration, and their long-term AGMD performance was assessed. The composite membranes were tested continuously over 12 days using saline solutions containing humic acid, with a cleaning cycle every 3.5 days. A wavy membrane with a mixed matrix PVDF selective layer containing clay as a filler material, showed best-in-class performance, with a flux decrease of only 28 % and a flux recovery of 91 % before and after the third cleaning cycle, respectively. For comparison, a commercial PVDF membrane and an in-house fabricated pristine PVDF membrane without any support, showed a flux decrease of 43 and 48 % and flux recovery of 65 and 60 %, respectively, confirming the CFD observations on the anti-fouling behaviour of wavy membranes. Overall, 3D printing allowed the fabrication of novel MD membranes with anti-fouling properties for long-term, efficient desalination and water treatment
Effects of Lottery Wins on Household Labor Supply
No full textThis paper analyzes the impact of lottery wins on household labor supply in the United Kingdom, using data from the British Household Panel Survey. We show that lottery wins do not have significant effects on hours of work of males, while female hours of work decrease in response to lottery wins. When we control for different lottery prize amounts, we find that large lottery wins reduce female annual hours of work by 120 h one and 2 years after the prize. The estimates are heterogeneous across age groups, levels of educational attainment, and household composition. These results suggest that shocks in unearned income may take some time to appear but have a lasting impact
SIBERIA: A Self-Sovereign Identity and Multi-Factor Authentication Framework for Industrial Access
No full textThe growing need for secure and privacy-preserving identity management in industrial environments has exposed the limitations of traditional, centralized authentication systems. In this context, SIBERIA was developed as a modular solution that empowers users to control their own digital identities, while ensuring robust protection of critical services. The system is designed in alignment with European standards and regulations, including EBSI, eIDAS 2.0, and the GDPR. SIBERIA integrates a Self-Sovereign Identity (SSI) framework with a decentralized blockchain-based infrastructure for the issuance and verification of Verifiable Credentials (VCs). It incorporates multi-factor authentication by combining a voice biometric module, enhanced with spoofing-aware techniques to detect synthetic or replayed audio, and a behavioral biometrics module that provides continuous authentication by monitoring user interaction patterns. The system enables secure and user-centric identity management in industrial contexts, ensuring high resistance to impersonation and credential theft while maintaining regulatory compliance. SIBERIA demonstrates that it is possible to achieve both strong security and user autonomy in digital identity systems by leveraging decentralized technologies and advanced biometric verification methods
Unsupervised clustering of biochemical markers reveals health profiles associated with function and survival in active aging
No full textThis study explores the relationships between biochemical phenotypes identified using machine learning, and key health outcomes, including body composition, physical function, and mortality risk. Data were collected from 536 physically active Spanish participants aged over 65 years (76.5% women) enrolled in the EXERNET cohort (2017–2018), with a 6-year mortality follow-up. Principal component analysis, and hierarchical and k-means clustering was used to identify distinct biochemical profiles. Associations between clusters and health outcomes were assessed using analysis of covariance and Cox proportional hazards models. Three distinct clusters emerged: ‘Healthy’, characterized by biochemical values within the normal range and used as the reference group; ‘Metabolic’, marked by dysregulated metabolic parameters; and ‘Hepatic’, which exhibited impaired liver function markers. Notably, all clusters showed subclinical levels of dysfunction. The ‘Healthy Cluster’ demonstrated the highest levels of organized physical activity (90%, p < 0.001), whereas the ‘Metabolic Cluster’ showed poorer body composition and reduced physical performance. Both the ‘Metabolic’ and ‘Hepatic’ clusters demonstrated a higher mortality risk, as confirmed through Cox regression analyses. Adjusted hazard ratios were significantly elevated when considering physical activity and adiposity, with values of 3.45 and 3.71 for the ‘Metabolic Cluster’, and 3.01 and 3.85 for the ‘Hepatic Cluster’ (p < 0.05). This study underscores the strong link between metabolic health, physical activity, body composition and 6-years mortality risk in older adults. Machine learning techniques for identifying phenotypic clusters offers a promising tool for early detection and targeted interventions to improve aging outcomes