Search Results (468)

Individual differences in second-language (L2) proficiency are expected to influence how listeners parse and represent continuous speech, yet their neural signatures under naturalistic conditions remain unclear. We investigated this question using task-based fMRI during continuous speech listening. A total of 43 healthy participants completed four listening runs synchronized with MRI acquisition via PsychoPy(Peirce 2007), with eyes open throughout scanning. To promote sustained attention and comprehension, participants provided a native-language oral recall after each run. Based on behavioral proficiency scores, participants were grouped into low- (LP, n = 14), moderate- (MP, n = 14), and high-proficiency (HP, n = 15) groups. We evaluated three temporal information-encoding frameworks derived from BOLD dynamics: direct temporal series, functional connectivity (FC), and self-information weighted inter-subject correlation (ISC-W). Using a 10 × 5-fold nested cross-validation scheme, we tested both categorical classification (Support Vector Machines) for discrete proficiency groups (LP, MP, HP) and continuous multivariate regression (Ridge/Lasso) for continuous proficiency scores. Furthermore, we applied ROI-based ANOVA and univariate Neural Correlation Analysis (NCA) to identify key brain regions, evaluating significance via nonparametric permutation testing (1000 permutations) and False Discovery Rate (FDR) correction. Results indicated that while categorical classification yielded numerical trends—with ISC-W performing best—it did not reach statistical significance under stringent permutation testing. However, multivariate continuous regression using ISC-W features successfully predicted continuous proficiency scores with statistical significance (p < 0.05). Exploratory ROI analysis highlighted the bilateral orbital inferior frontal gyrus (IFG_orb_bilat) as a highly sensitive region. These findings suggest that L2 proficiency is best represented as a distributed, continuous neural variable, and that self-information weighting effectively filters background noise to capture cognitive variance. Methodologically, this study provides a reproducible pipeline integrating information-theoretic feature construction with rigorous whole-brain nonparametric inference. Full article

Aging is a significant risk factor for several neurodegenerative diseases. Understanding brain aging processes is a fundamental step in identifying the early signs of pathological dysfunction. Nonetheless, regional functional changes are still poorly characterized. In this study, we employed Detrended Fluctuation Analysis (DFA) to investigate age-related changes in the scale-free temporal dynamics of blood oxygen level-dependent (BOLD) signal fluctuations derived from resting-state networks. We compared DFA to fractional amplitude of low-frequency fluctuations (fALFF) to assess their ability to discriminate between young and old adults. Significant decreases (p < 0.01) in fALFF in the visuospatial and dorsal default mode networks and in DFA in the salience network, were identified as key predictors of functional brain aging. Using machine learning, we showed that DFA and fALFF provide complementary information for predicting aging, with an accuracy of approximately 80% achieved only through their combined use. Overall, DFA captures alterations in scale-free temporal organization that complement conventional spectral measures, providing additional insight into network-specific functional aging. Full article

Urbanization is a major and rapidly expanding form of land-use change worldwide and is one of the main drivers of the decline in arthropod diversity. Within urban matrices, remnants of natural or semi-natural habitats serve as important refuges for native organisms. However, these urban fragments are typically small, isolated, and strongly affected by various forms of disturbance. Therefore, connectivity among urban remnant patches may enhance population persistence and resilience. Increased tendencies to explore novel environments, tolerate human disturbance, and exploit unpredictable resources can be advantageous in urban environments. Accordingly, in this study of a flightless ground beetle species, we hypothesized that individuals from urban habitats—especially from isolated ones—would be bolder and more exploratory than their rural conspecifics, that sexes would differ in behavior, and that these behaviors would be temporally consistent, indicating animal personality. Activity-, exploration-, and boldness-related behavioral traits were significantly repeatable, providing evidence for animal personality, particularly in females and rural beetles. Contrary to our hypothesis, no behavioral differences were detected between rural and urban individuals. Furthermore, no significant sex-dependent differences in behavior were observed. Overall, our findings highlight the importance of species-specific traits and ecological context in shaping behavioral variation. Full article

The integration of microalgal cultivation with wastewater streams offers a promising pathway to enhance resource efficiency within circular bioeconomy frameworks. However, the suitability of clarified aquaponics sedimentation effluent for producing carbohydrate-rich microalgal biomass remains insufficiently evaluated, particularly with respect to nutrient recovery and bioethanol-relevant feedstock potential. In this study, clarified aquaponics sedimentation effluent was assessed as a cultivation medium for Chlorella sp. under controlled laboratory conditions. Biomass productivity, nutrient removal performance, and carbohydrate accumulation were systematically evaluated and compared with conventional synthetic medium. Chlorella sp. cultivated in clarified aquaponic effluent achieved a maximum biomass concentration of approximately 2.05 g L⁻¹, exceeding that obtained in Bold’s Basal Medium. Carbohydrate content exceeded 40% of dry weight, indicating suitability for fermentable sugar production. Nitrate and phosphate removal efficiencies greater than 95% were achieved, with mass balance analysis confirming biological assimilation as the primary removal mechanism (~87.4%). This confirms the dual functionality of the system. The effective nutrient assimilation and confirmed the dual functionality of the system as both a biomass production and nutrient recovery process. Comparable performance under diluted and undiluted effluent conditions further indicated that freshwater dilution is not required following clarification. Light saturation was observed at 180–190 μmol m⁻² s⁻¹, providing guidance for energy-efficient operation. These findings demonstrate that clarified aquaponics effluent can serve as an effective alternative growth medium for producing carbohydrate-rich Chlorella sp. biomass while enabling nutrient recovery. The estimated bioethanol potential is theoretical, based on stoichiometric conversion assumptions, and experimental fermentation was not conducted. This work provides quantitative evidence supporting the integration of microalgae into aquaponic systems and establishes a foundation for future pilot-scale, techno-economic, and life-cycle assessments. Full article

Parasitism plays an important role in many fundamental ecological processes and is widespread both geographically and taxonomically. Interactions between parasites and hosts are often complex, and much attention has been paid to the relationship between host traits and parasitism. However, a comprehensive review of the association between host personality and parasitic infection is lacking. In this review, we systematically synthesized 54 studies published over the past few decades. Generally, the relationship between animal personality traits and parasitic infection is complex, and no generic pattern exists. Many biological processes may be involved, and biological factors (such as host sex and parasite type) may significantly shape the personality–infection relationship. Different personality traits may also indicate different relationships with parasitic infection. We confirmed that host personality and parasitic infection exhibit a mutually influential, multi-feedback dynamic. Finally, several research gaps were described, and we emphasized the importance of incorporating the BACI design in experiments. Full article

Lyme borreliosis (LB), the most common European tick-borne disease, can manifest as an erythema migrans (EM) rash or as disseminated LB. The prospective Burden of Lyme Disease (BOLD) study evaluated the frequency of LB clinical manifestations, including signs, symptoms, and treatment patterns in 14 healthcare practices in endemic regions of six European countries: the Czech Republic, Germany, Poland, Slovakia, Slovenia, and Sweden. Between April 2021 and December 2022, patients with suspected LB were evaluated using predefined case definitions that were applied by investigators to identify medically attended LB cases. Enrolled cases were interviewed about their symptoms. Among the 797 LB cases, 615 (77.2%) had EM and 182 (22.8%) had disseminated disease; 154 of the disseminated cases had Lyme arthritis (LA), five had Lyme neuroborreliosis, and three had Lyme carditis. Geographically, the proportion of disseminated disease varied by country, from 1.1% in Slovenia to 78.0% in Slovakia. Overall, 76.3% of all LB cases in Slovakia were LA. Antibiotic use varied by country, although every country prescribed doxycycline. The frequency of LB manifestations varied substantially between countries. EM was the most common manifestation in all countries except Slovakia, where LA was most common. This study underscores the need for improved prevention strategies. Full article

Background/Objectives: Quantifying cerebrovascular reactivity (CVR) is essential for stroke risk assessment in patients with Moyamoya Angiopathy (MMA). Breath-hold functional MRI (bh-fMRI) is an easily implementable method to assess CVR. Determining the optimal time period of the BOLD signal for analyzing the best bh-fMRI data quality remains an open question. Methods: A retrospective analysis of 46 bh-fMRI data sets of MMA patients was conducted. The percentage BOLD signal changes were evaluated at different time periods (time point of the maximum cerebellar signal peak (TP_{cereb. max}) ± 0 s, TP_{cereb. max} ± 1 s, TP_{cereb. max} ± 2 s, TP_{cereb. max} ± 3 s, TP_{cereb. max} ± 4 s, TP_{cereb. max} ± 5 s). The agreement between the bh-fMRI maps and [¹⁵O]water PET maps was independently and consensually rated on a 4-point Likert scale (1 = poor, 2 = moderate, 3 = good, 4 = excellent) and compared with the Friedman test. The inter-rater agreement was calculated separately for each time period using quadratic weighted Cohen’s kappa κ_w. Results: The selected time period had a significant impact on the agreement between bh-fMRI and [¹⁵O]water PET (χ²(5) = 79.448, p < 0.001, W = 0.345). Short time periods of TP_cereb.max ± 0 s or TP_cereb.max ±1 s demonstrated the highest level of concordance between bh-fMRI and [¹⁵O]water PET (median = 3.5 for TP_cereb.max ± 0 s; median = 3 for TP_cereb.max ± 1 s, modus = 4 in both cases). The agreement between bh-fMRI and [¹⁵O]water PET was significantly higher when evaluating time periods of TP_cereb.max ± 0 s than when evaluating all time periods ≥ TP_{cereb. max} ± 2 s. The inter-rater agreement was almost perfect for all time periods except one (TP_{cereb. max} ± 1 s). Conclusions: Short time periods should be selected when evaluating CVR with bh-fMRI, as this study suggests a high level of validity in comparison to [¹⁵O]water PET. Full article

Musculoskeletal (MSK) diseases present major health and economic challenges globally. Advancing age, diseases like osteoarthritis (OA), osteoporosis (OP), fracture and other conditions significantly reduce the quality of life (QOL) of these patients. Current pharmaceutical approaches are able to manage symptoms for some of these; however, they do not provide long-term solutions. Surgeries which are usually the final resort, present an added layer of challenges with the risk of post-surgical complications. The last couple of decades have observed an increase in the use of tissue engineering and regenerative medicine (TERM) for bone tissue engineering (BTE) applications. With the advent of artificial intelligence (AI), there will inevitably be an intersection of AI with TERM for MSK conditions. As of 2025, AI is already in use for small-scale applications in BTE including data extraction, image analysis, scaffold design and fabrication using three-dimensional (3D) printing techniques. This review outlines the convergence of these three fields and discusses the potential of their intersection. The author describes the need for this convergence, a brief update of TERM in MSK in the last decade, followed by the potential of AI in MSK-TERM. The review concludes on the challenges and future directions of the emerging field and hopes to encourage bold and ambitious collaborations between industry, academia, hospitals and health-care start-ups to realize the potential of this unique intersection. Full article

The Scythrididae Rebel, 1901, comprises small and morphologically homogeneous microlepidoptera whose identification relies mainly on genitalia examination. In Italy, this group has been more extensively investigated than other microlepidoptera families, but molecular data remain scarce. This study aims to improve the knowledge of Scythrididae diversity in southern Italy through DNA barcoding. Twenty-nine specimens collected in Calabria and Basilicata underwent DNA barcoding, yielding 28 sequences of 602–658 bp, which clustered into 10 Barcode Index Numbers (BINs), corresponding to 10 species. Three BINs are newly created in the Barcode of Life Data System (BOLD), enriching the global reference library. Except for Scythris aspromontis Jäckh, 1978, described for the study area, the remaining species represent faunistic novelties at different scales: Scythris dissitella (Zeller, 1847) is new for continental Italy and eight additional species are new for southern Italy or Calabria and Basilicata regions. Moreover, a significant genetic distance was observed between our sequence of Scythris cf. tabidella (Herrich-Schäffer, 1855) and sequences of tabidella available on BOLD, which will be addressed in detail in the discussions. The results highlight the underexplored diversity of Scythrididae in the Mediterranean region and confirm the effectiveness of integrative taxonomy combining DNA barcoding and morphology. This study provides the first molecular contribution to the Scythrididae fauna of southern Italy and contributes to improving the taxonomic knowledge of a group that remains insufficiently investigated in the Mediterranean region. Full article

Background. Self-congruency refers to the coherence between emotional experience (internal states) and enacted behavior (outward actions). Reduced self-congruency has been linked to vulnerability in mental health, yet its physiological correlates remain poorly characterized. Heart–brain temporal coupling may provide a candidate physiological marker of this psychological coherence. Methods. Thirty-eight healthy adults underwent resting-state functional magnetic resonance imaging while cardiac activity was simultaneously recorded using photoplethysmography to derive heart rate variability (HRV). Self-congruency was assessed using a graphic rating scale based on the spatial overlap between emotional experience and enacted behavior. Heart–brain temporal coupling between HRV and regional blood-oxygen-level-dependent (BOLD) signals was quantified using cross-covariance analysis across biologically plausible temporal shifts. Results. Heart–brain temporal coupling predominantly reflected brain-to-heart temporal ordering, particularly within regions central to the neurovisceral integration model, including the ventromedial prefrontal and anterior cingulate cortices. In contrast, higher self-congruency was associated with stronger heart-to-brain temporal coupling, notably within the right rostral middle frontal gyrus and supramarginal gyrus, regions implicated in emotion regulation and socio-emotional processing. Conclusions. While global heart–brain temporal coupling is dominated by top-down neural regulation, greater alignment between emotional experience and enacted behavior is associated with enhanced bottom-up cardiac temporal ordering on neural activity. These findings seem to identify a physiological–psychological axis that may inform original prevention-oriented approaches in mental health. Full article

Let $(M_1,F_1)$ and $(M_2,F_2)$ be two Finsler manifolds. A Minkowskian product Finsler manifold is defined to be the product manifold $M_1\times M_2$, which is endowed with a Finsler metric F. This metric F is constructed by taking the square root of a product function f, which itself operates on the squares of the original metrics $F_1$ and $F_2$. This paper focuses on new classes of stretch Minkowskian product Finsler manifolds. We prove that the Minkowskian product Finsler manifold $(M,F)$ is a $\tilde{\mathbf{B}}$-manifold (resp. $\tilde{\mathbf{B}}$-stretch manifold, $\mathbf{H}$-stretch manifold) if and only if $(M_1,F_1)$ and $(M_2,F_2)$ are both $\tilde{\mathbf{B}}$-manifold (resp. $\tilde{\mathbf{B}}$-stretch manifold, $\mathbf{H}$-stretch manifold). Thus an effective method for constructing special Finsler manifolds mentioned above is given. Full article

With the intensification of social aging and the improvement of living standards, delaying aging has become a focus of common concern, especially in regard to skin aging. Although collagen peptides have been widely reported as therapeutic agents in relieving skin aging, the molecular mechanisms remain inadequately elucidated. This review emphasizes that the alleviation of skin aging by collagen peptides is a systematic and complex process, including the removal of reactive oxygen species, inhibition of inflammation, inhibition of extracellular matrix (ECM) degradation and melanin deposition, activation of lysosomal and mitochondrial function, and promotion of ECM synthesis. It also highlights that lysosomes and mitochondria may be the key organelles that regulate collagen peptides to alleviate skin aging. Current research on the mechanism of collagen peptides in alleviating skin aging still requires bold breakthroughs and should not be confined to the transforming growth factor (TGF-β)/Smad, mitogen-activated protein kinase, and nuclear factor kappa-B pathways. In addition, many natural antioxidant components have been proven to alleviate skin aging by regulating organelle function. Therefore, the regulatory effects of collagen peptides with antioxidant activity on mitochondrial and lysosome functions in aging skin need more attention and exploration, which is of great significance for further research on precise skin care and targeted anti-skin aging therapy. Full article

Two decades after the first bold proclamations that nanomedicine would deliver “magic-bullet” therapies capable of cell-level targeting, the field stands at a crossroads. While some initial promises (improved delivery of poorly water-soluble drugs and enhanced efficacy and biocompatibility of nano-based devices) have been fulfilled, other early promises (active targeting, biodegradability, multifunctionality, triggered responses, real-time data output, and implantable sensors) remain only partially realized. This article will compare the properties of approved nano-based products to those of the ideal products, assess the shortcomings of existing nano-based products, and discuss critical issues in nanotoxicity (biodistribution and protein corona effects, immune interactions, and biopersistence) and the lack of data on product and end-of-life life cycle analyses. The role of in silico tools in the various steps of nanodrug and nano-based device development and manufacturing—areas in which these tools are the most established (nanocarrier design, prediction of cellular effects, chemical composition optimization, manufacturing, and signal interpretation)—is also addressed. Future goals include biodegradable targeted delivery systems, better tissue integration of implants, and implantable sensors. It is expected that, alongside careful physicochemical characterization of the nanoproduct, toxicity testing focused on nano-specific effects and life cycle analyses of production and end-of-life phases will facilitate the approval of nano-based products. Full article

This contribution examines the key aspects of the aggiornamento of Ignatian spirituality promoted by French Jesuits through the journal Christus between 1954 and 1967. The founding of the journal can be understood as a response to a sense of identity crisis among French Jesuits, likely provoked by the Fourvière crisis and the abrupt end of the worker-priest movement, which was eventually prohibited by Rome. In this context, the call to reconnect with Ignatian sources became imperative to foster theological and spiritual reflection capable of shedding light on the tensions of the present. The generation led by Maurice Giuliani, Michel de Certeau, and François Roustang—who spearheaded this editorial project—distanced itself from the hermeneutics of their predecessors, particularly Joseph de Guibert, as regards the spiritual history of the Society of Jesus. Instead, they emphasized a mysticism of action, the necessary integration of spirituality and apostolic works, the ecclesial implications of Ignatian service, and a bold, increasingly open dialogue between Ignatian tradition and the human sciences. Full article

Background/Objectives: Diabetes is one of the most familiar and common diseases among people currently, and is a type of metabolic disease that is caused due to high levels of sugar in the blood for longer periods of time. If the disease is predicted at an earlier stage, the severity and risks associated with diabetes are significantly reduced, which helps to save the lifespan of people. In earlier investigations, various kinds of automated models based on artificial intelligence (AI) were developed for this purpose. However, key issues still revolve around the lack of robustness, dependability, and precise prediction. The motivation behind the proposed study is to design and develop an automated tool for the diagnosis of chronic disease with the use of novel AI methodology. Methods: For this purpose, a new detection framework is introduced, known as the Brass Optimized Learning-Based Diabetes Prediction (BOLD) model for remote healthcare applications. By using this kind of optimization-integrated deep learning technique, the overall performance and efficiency of the diabetes detection system are maximized. This framework preprocesses the input diabetes dataset before performing the data splitting, normalization, and cleaning activities. Next, the best attributes for improving the prognostic performance of the classifier are chosen using the Brassy Pelican Optimization (BPO) procedure. The Hunting Optimized Recurrent Neural Network—Long Short-Term Memory (RNN-LSTM) method is used to categorize the people into those who are diabetic and those who are not based on the chosen attributes. The approach employs a Deer Hunting Optimization (DHO) method to choose the hyperparameters needed to make an informed choice. A variety of parameters have been employed to confirm the results, which are evaluated for performance verification using the PIDD, Indonesia diabetic database, and kidney disease dataset. Results: The BOLD framework is successful to the extent that it has been able to achieve several metrics of comparably good results, such as an RMSE value of 0.015, a Cohen’s Kappa measure of 0.99, a precision of 0.991, a recall of 0.99, an accuracy equal to 0.996, and an AUC equal to 0.99. Conclusions: It is also remarkable that a very short time of 0.8 s was enough for it to deliver this kind of performance, making it a neat combination of both time and power efficiency. Full article