Search

The increasing consumption of chia seeds is followed by a growing interest in their nutritional and toxicological characterization. To assess the characterization of the essential and PTEs of this novel food, 20 samples of conventional and organic chia seeds available on the European market were analyzed using ICP-OES. Then, the dietary exposure to these elements was assessed. An exhaustive investigation into the metal content of this food serves to elucidate the paucity of existing knowledge. The results show that the levels of essential elements are similar in both types of production, while the levels of PTEs are higher in the organic samples. The exposure assessment indicates that Mn contributes the most among the essential elements, followed by Cu in women. Exposure to PTEs through doses of 50 g/day of chia seeds analyzed would hardly pose short-term health risks as the contributions are below 10%, except for Sr, although they could produce a long-term toxicological risk. To promote safety in chia seed consumption, it is recommended to encourage responsible and moderate consumption, continue monitoring PTE levels in this novel food, and establish concentration limits for PTEs in future European regulations.

Neotropical species of the genus Fannia remain poorly known despite their potential collection as biological evidence in criminal investigations. This is partly due to taxonomic difficulties and a lack of specialists. Identifying neotropical species of Fannia relies mainly on the classical morphological characters of adult males, as females show high similarity between species. Here, landmark-based geometric morphometrics of the wing could constitute an additional tool for associating adult females with conspecifics in this genus. In this study, we used a reference dataset of males belonging to ten putative species of Fannia from Colombia and molecular data to test this hypothesis. We found a strong wing shape sexual dimorphism, resulting in an almost perfect sex assignment based solely on this trait. However, the differences in wing shape between sexes were greater than those between species, making conspecific identification difficult. Our data show that wing shape could only feasibly be used for identifying adult males and females of F. lamosca, and males of F. dorsomaculata and F. pseudoconstricta. Low discrimination scores among remaining species may be partly explained by high intraspecific variation, slight wing shape differences among closely related species, or sampling bias. Although this study provides the first wing size and shape comparison among neotropical Fannia species, more samples and species are needed to validate these findings and identify the potential factors influencing this trait. Furthermore, the wing shape sexual dimorphism across Fannia species suggests different life-history strategies between sexes and possible genetic canalization mechanisms.

Background: There are still discrepancies in the literature as to whether COVID-19 infection could impact biochemical, anthropometric, and cardiovascular markers. The purpose of this study was firstly to observe the effects of COVID-19 infection over 12 months on Type 2 diabetes (T2D) and obesity. Secondarily, we analyzed the individual influence of COVID-19 infection on changes in biochemical, anthropometric, and cardiovascular markers. Methods: This study is part of a secondary analysis of a recently published article. The research involved 84 participants with T2D, divided into two groups: the control group (40 participants) received only medical care, while the intervention group (44 participants) received both medical care and nutritional assessment. Consultations were held quarterly over 12 months, with a follow-up after 3 months. Data Analysis: For influence analysis, non-normal variables were compared using the Mann–Whitney test, and normal variables were compared using unpaired t-tests. For all cases, α = 0.05 and p < 0.05 were considered significant. Results: The analysis revealed a high percentage of patients in both groups who had a COVID-19 infection (70% control and 72.7% intervention) over 12 months. Regarding the influence analysis, participants in the intervention group who were infected with COVID-19 showed smaller reductions in glycated hemoglobin (HbA1c) (p = 0.0120) and systolic blood pressure (SBP) (p = 0.0460). For the other biochemical, anthropometric, and cardiovascular markers, in both groups, no significant differences were found (p > 0.05). Conclusion: COVID-19 possibly influenced SBP and HbA1c levels over 12 months in people with T2D and obesity. However, caution should be exercised in generalizing these results due to the limitations of this study. Additionally, influence analysis does not establish a causal relationship, and more clinical trials in different populations are needed to fully analyze this topic.

By taking into account our previously described series of 1,3,5-tris[(4-(substituted-aminomethyl)phenyl)methyl]benzene compounds, we have now designed, prepared, and evaluated in vitro against Plasmodium falciparum a novel series of structural analogues of these molecules, i.e., the 1,3,5-tris[(4-(substituted-aminomethyl)phenoxy)methyl]benzene derivatives. The pharmacological data showed antimalarial activity with IC50 values in the sub and μM range. The in vitro cytotoxicity of these new nitrogen polyphenoxymethylbenzene compounds was also evaluated on human HepG2 cells. The 1,3,5-tris[(4-(substituted-aminomethyl)phenoxy)methyl]benzene derivative 1m was found as one of the most potent and promising antimalarial candidates with favorable cytotoxic to antiprotozoal properties in the P. falciparum strains W2 and 3D7. In conclusion, this 1,3,5-tris[(4-(pyridin-3-ylmethylaminomethyl)phenoxyl)methyl]benzene 1m (IC50 = 0.07 μM on W2, 0.06 μM on 3D7, and 62.11 μM on HepG2) was identified as the most promising antimalarial derivative with selectivity indexes (SI) of 887.29 on the W2 P. falciparum chloroquine-resistant strain, and of 1035.17 on the chloroquine-sensitive and mefloquine decreased sensitivity strain 3D7. It has been previously described that the telomeres of P. falciparum could represent potential targets for these types of polyaromatic compounds; therefore, the capacity of our novel derivatives to stabilize the parasitic telomeric G-quadruplexes was assessed using a FRET melting assay. However, with regard to the stabilization of the protozoal G-quadruplex, we observed that the best substituted derivatives 1, which exhibited some interesting stabilization profiles, were not the most active antimalarial compounds against the two Plasmodium strains. Thus, there were no correlations between their antimalarial activities and selectivities of their respective binding to G-quadruplexes.

The emergence of mRNA vaccines for SARS-CoV-2 has opened a new page in vaccine development. Nevertheless, concerns of experts have been expressed about unintentional side effects on the gut microbiota (GM). Previous studies showed that this virus acts as a bacteriophage, which infects and destroys specific bacterial strains in the GM. The present manuscript hypothesizes that the synthetic spike protein could create changes in the composition and the functioning of the GM by entering the intestinal cells after vaccination and impairing the symbiotic relationship between intestinal cells and the GM. An experimental protocol to test the hypothesis is suggested.

A severe consequence of SARS-CoV-2 infection that manifests as systemic inflammation and multi-organ involvement is called Multisystem Inflammatory Syndrome in Children (MIS-C). This review examines the possible relationship between gut barrier integrity, the microbiome, dysregulation of interleukin 6 (IL-6) signaling, and MIS-C. Clinical and biochemical features of MIS-C are comparable to those of other hyper-inflammatory syndromes, suggesting a dysregulated immune response. One possible explanation for the systemic inflammation seen in MIS-C patients is the SARS-CoV-2-induced dysregulation of the IL-6 signaling pathway. In addition, new data suggest a reciprocal link between gut barrier integrity and IL-6. SARS-CoV-2 exhibits bacteriophage-like behavior, highlighting the role of bacteria as a reservoir for the virus and emphasizing the importance of understanding the bacteriophagic mechanism of the virus in fecal–oral transmission. The increased translocation of viral products and bacterial toxins may result from disrupting the intestinal barrier and cause systemic inflammation. On the other hand, systemic inflammation can weaken the integrity of the intestinal barrier, which feeds back into the loop of immunological dysregulation. In the context of MIS-C, understanding the interaction between SARS-CoV-2 infection, IL-6, and gut barrier integrity may shed light on the etiology of the disease and guide treatment options. Since children with gut dysbiosis may be more susceptible to MIS-C, it is critical to reinforce their microbiome through probiotics supplementation, and plant-fiber-rich diets (prebiotics). Early antibiotic treatment and the use of zonulin antagonists should also be considered.

Fungal diseases are a major threat to the horticultural industry and cause substantial postharvest losses. While secondary metabolites from Trichoderma sp. have been explored for their antifungal properties, limited information exists on the phenolic compounds produced by less studied species like Trichoderma longibrachiatum. In this study, phenolic compounds were extracted from a liquid culture of T. longibrachiatum using various solvents and methods (conventional and ultrasonic-assisted). Phenolic compounds were quantified by spectrophotometry and identified by high-performance liquid chromatography with diode array detection (HPLC-DAD). The antifungal activity against Alternaria alternata and Fusarium oxysporum was determined by mycelial growth inhibition assays, maximum growth rate (µmax) by the Gompertz equation, and spore germination tests. Although no significant differences (p ≥ 0.05) were found between the extraction methods, the type of solvent significantly influenced the phenolic content (p ≤ 0.05). Extraction with 70% ethanol showed the highest content of phenolic compounds and flavonoids. More than eight phenolic compounds were detected. Further, this is the first report of the phenolics ferulic, chlorogenic and p-coumaric acids identification in T. longibrachiatum, along with flavonoids such as epicatechin and quercetin, among others. The 70% ethanolic extracts notably inhibited the mycelial growth of A. alternata and F. oxysporum, reducing their maximum growth rate by 1.5 and 1.4 mm/h, respectively. Furthermore, p-coumaric and ferulic acids significantly inhibited spore germination of both pathogens, with a minimum inhibitory concentration (MIC) of 1.5 mg/mL and a minimum fungicidal concentration (MFC) of 2 mg/mL. These findings demonstrate the potential of T. longibrachiatum and its phenolic compounds as viable alternatives for biological control in horticulture and postharvest disease management.

The younger generations are exerting a profound influence on the future of the media. The current crisis of reputation facing traditional media is compelling those involved in the creation, production, and distribution of content to rethink the logic underpinning these processes. The consumption of entertainment and information via smartphones is becoming increasingly concentrated in screen devices and social platforms. In light of the particularities of a convergence of media and the characteristics of the digital sphere of users, it is necessary to investigate the information consumption habits and preferences of young university students towards conventional and digital media platforms, as well as social networks within the digital sphere. The objective of this research was to ascertain the news consumption habits of young university students in the context of the new digital landscape, characterised by the pervasiveness of connectivity and the ascendency of smartphones as the primary gateway to the internet. A survey of 1300 students was conducted in October 2023 to investigate their adoption, use, and consumption of traditional and digital media, as well as the devices they use and the importance of podcasts. The results, viewed through the lens of a specific ecosystem, such as that of Colombia, challenge prevailing stereotypes and suggest that younger generations continue to value traditional journalistic brands, potentially due to familial influence. The majority of content is accessed through screen devices and social media platforms. Despite the existence of prejudices, young people supplement their musical preferences with informational content and leisure and entertainment products.

The aim of the present study was to determine the gender respiratory differences of bilateral diaphragm thickness, respiratory pressures, and pulmonary function in patients with low back pain (LBP). A sample of 90 participants with nonspecific LBP was recruited and matched paired by sex (45 women and 45 men). Respiratory outcomes included bilateral diaphragm thickness by ultrasonography, respiratory muscle strength by maximum inspiratory (MIP) and expiratory (MEP) pressures, and pulmonary function by forced expiratory volume during 1 s (FEV1), forced vital capacity (FVC) and FEV1/FVC spirometry parameters. The comparison of respiratory outcomes presented significant differences (p < 0.001), with a large effect size (d = 1.26–1.58) showing means differences (95% CI) for MIP of −32.26 (−42.99, −21.53) cm H2O, MEP of −50.66 (−64.08, −37.25) cm H2O, FEV1 of −0.92 (−1.18, −0.65) L, and FVC of −1.00 (−1.32, −0.69) L, with lower values for females versus males. Gender-based respiratory differences were presented for maximum respiratory pressures and pulmonary function in patients with nonspecific LBP. Women presented greater inspiratory and expiratory muscle weakness as well as worse lung function, although these differences were not linked to diaphragm thickness during normal breathing.

Acute graft-versus-host disease (aGVHD) remains a barrier to successful allogeneic hematopoietic stem cell transplantation (HSCT) outcomes. Contemporary comprehensive analyses of real-world clinical outcomes among patients who develop aGVHD post-HSCT are needed to better understand the unmet needs of this patient population. This multicenter, retrospective chart review describes treatment patterns and clinical outcomes among patients (≥18 years old) from Finland, Sweden, and France who developed grades II–IV aGVHD after their first HSCT (January 2016–June 2017). From 13 participating centers, 151 patients were included. The median (Q1, Q3) age at HSCT was 56 (45, 62) years old. One line of aGVHD treatment was received by 47.7%, and the most common first-line treatment was methylprednisolone (alone or in a combination regimen, 74.2%; monotherapy, 25.8%). Among patients treated with methylprednisolone, 79.5% achieved a complete or partial response. The median (Q1, Q3) number of treatment lines was 2.0 (1.0, 3.0). The median (Q1, Q3) time to obtain an aGVHD diagnosis from transplant was 29.5 (21.0, 44.0) days, and 14.5 (7.0, 34.0) days to achieve the best response for 110 evaluable patients. At 6 and 12 months, 53.6% and 49.0%, respectively, achieved a complete response. Chronic GVHD occurred in 37.7% of patients, and aGVHD reoccurred in 26.5%. Following aGVHD diagnosis, mortality rates were 30.0% at 6 months and 37.3% at 12 months. Findings from this study demonstrate a continuing unmet need for new therapies that control aGVHD and improve mortality.

The public service media Radio Televisión Española (RTVE) conducted a proof-of-concept study to automatically generate reports on the results of the local elections of 28 May 2023 in Spanish communities with fewer than 1000 inhabitants. This study describes the creation, testing and application of the methodological tool used to evaluate the quality of the reports generated using artificial intelligence in order to optimize the algorithm. The application of the proposed datasheet provided a systematic analysis, and the iterative use of the tool made it possible to gradually improve the results produced by the system until a suitable threshold was reached for publication. The study also showed that, despite the ability of AI systems to automatically generate a large volume of information, both human labour and the reliability of the data that feed the system are essential to ensure journalistic quality.

The optical properties and structural characterization of multicomponent silicate glasses of low Al2O3 and different Y2O3 concentrations have been studied. These glasses have also been crystallized to obtain glass–ceramic materials, and their properties have been characterized. The obtained glasses were transparent and their refractive indexes increased with Y2O3 concentration. After a heat treatment at 930 °C for 10 min, these glasses maintained their transparency, but a brown color appeared, and after 30 min, those glasses with high Y2O3 concentrations turned opaque or white in color. These processes of crystallization for obtaining the new glass–ceramics have been studied by means of FTIR and Raman spectroscopies, and the crystallized materials were characterized with XRD and FE-SEM techniques. These glasses and glass–ceramics have also been characterized by means of UV–vis spectroscopy, and the corresponding optical properties (reflectance, color, band-gap) have been determined as a function of the Y2O3 concentrations and the structural properties.

Face milling is among the processes that can produce a high-precision surface finish. Tool condition monitoring and signal processing algorithms are under extensive research to improve production quality and productivity in machining processes. In the present research, the time–frequency analysis technique was applied to the signal obtained from a sensor integrated into the primary AC power circuitry during the milling of steel bars to evaluate its applicability in detecting the current variations associated with the cutting force. The signal acquired from the sensor was processed in the time–frequency domain using wavelet analysis, and the results were compared with the traditional time and frequency analyses. The results showed that the signal variations produced by the cutting force were well localized in the frequency spectra with both approaches. However, the wavelet processing method yielded a poorly defined cutting force signal shape due to the limited resolution inherent in the sub-bands containing the frequencies of interest.

The media has become a central aspect of everyday life, providing information and entertainment, and serving as a basis for citizen consumption. The content that appears on the internet today is the result of numerous experiences accumulated throughout the history of media, particularly in the last four decades of technological and social development. The following text analyses how the hybridisation of analogue and digital technologies affects audience consumption patterns and expectations, leading to a more flexible relationship with the media. This study employed a theoretical examination of documentary sources, including texts, articles, and digital materials. The findings indicate a shift from simple, vertical, and linear communication systems to networks that enable horizontal and personalised consumption. The conclusion drawn is that technology has redefined structures and concepts, with the smartphone serving as the focal point of media consumption. Living culture is shaped by technology, because the message, more than the specific content, is the meaning, recognition, and exchange of a world that needs to be re-thought.

Lung ultrasound is an increasingly utilized non-invasive imaging modality for assessing lung condition but interpreting it can be challenging and depends on the operator’s experience. To address these challenges, this work proposes an approach that combines artificial intelligence (AI) with feature-based signal processing algorithms. We introduce a specialized deep learning model designed and trained to facilitate the analysis and interpretation of lung ultrasound images by automating the detection and location of pulmonary features, including the pleura, A-lines, B-lines, and consolidations. Employing Convolutional Neural Networks (CNNs) trained on a semi-automatically annotated dataset, the model delineates these pulmonary patterns with the objective of enhancing diagnostic precision. Real-time post-processing algorithms further refine prediction accuracy by reducing false-positives and false-negatives, augmenting interpretational clarity and obtaining a final processing rate of up to 20 frames per second with accuracy levels of 89% for consolidation, 92% for B-lines, 66% for A-lines, and 92% for detecting normal lungs compared with an expert opinion.

Background: Gaucher disease (GD) is a rare autosomal recessive disorder caused by mutations in the GBA1 gene that lead to a deficiency in the glucocerebrosidase gene. This deficiency results in the accumulation of glucocerebrosides in macrophages, primarily affecting the liver, spleen, and bone marrow. Focusing on the Mexican population, this study aims to review GD’s epidemiology, clinical manifestations, and treatment options to enhance early diagnosis and optimize treatment outcomes. Methods: This study is a comprehensive literature review analyzing epidemiological data, clinical presentations, and current therapeutic approaches for Gaucher disease, including enzyme replacement therapy (ERT) and substrate reduction therapy (SRT). Conclusions: Early diagnosis and individualized treatment, primarily through enzyme replacement therapy, significantly improve the prognosis of patients with Gaucher disease, particularly type 1. Continued research is required to enhance therapeutic approaches for the neuropathic types and better understand the disease’s epidemiology in Mexico. These efforts will contribute to improved clinical outcomes and quality of life for patients.

Academic performance is the level of achievement that students reach in their educational activities. It is influenced by several factors that should be analysed and prioritised, especially in engineering courses, characterised by their difficulty and low success rates compared to other careers. This paper analyses the impact of these factors on academic performance during exams in a technical college in southwestern Spain, with a particular focus on environmental conditions, identified as a relevant and independent variable. The results show a significant connection between thermal comfort and academic performance. Temperatures within the comfort range (23–26 °C) improved students’ satisfaction with exams. In contrast, those who experienced thermal discomfort pointed to environmental conditions as the main obstacle to their performance, overcoming factors such as prior preparation and coincidence of exams. These findings underline the importance of optimising the classroom’s thermal environment through strategies that promote a more favourable learning space, improving both students’ well-being and their academic performance.

In the past, the Silk Road was a vital trade route that spanned Eurasia, connecting East Asia to the Mediterranean Sea. The genus Prunus, belonging to the Rosaceae family and encompassing plums, peaches, apricots, cherries, and almonds, thrived as human travel along the Silk Road increased. The majority of fruits within this genus, whether wild or cultivated, are naturally sweet and easily preserved by drying for storage and transport. The interaction along the Silk Road between wild populations and diverse varieties of Prunus fruits led to the development of various hybrids. This article provides a summary of archaeological findings related to prominent Prunus fruits such as peaches, apricots, plums, cherries, and almonds, shedding light on their evolutionary history, genetic diversity, population structure, and historical dynamics crucial for species conservation. The origins of biodiversity may involve factors like migration of pre-adapted lineages, in situ variation, or the persistence of ancestral lineages. Furthermore, climate change is affecting spatial genetic patterns and potentially further threatening rare Prunus species. Evaluating the scope and composition of genetic diversity within germplasm collections is essential for enhancing plant breeding initiatives and preserving genetic resources in this changing context. From a molecular point of view, techniques such as genome-wide association studies (GWASs) and the identification of quantitative trait loci (QTLs) and genes responsible for phenotypic changes in cultivars and germplasm collections should be of great interest in these breeding programs, while genomic estimated breeding values (GEBVs) derived from genome-wide DNA polymorphism information can facilitate the selection of superior genotypes.

Macroalgae-derived oils offer a sustainable and environmentally friendly alternative to conventional mineral oils and additives in lubricant formulation. Their favorable fatty acid profiles can contribute to mitigating the environmental impacts caused by using fossil-based products. This study evaluates the potential of Sargassum spp. oil, collected from the Mexican Caribbean, as a lubricity-enhancing additive in synthetic base oils. The impact of Sargassum spp. oil on viscosity and tribological performance was analyzed. The results indicated that Sargassum spp. oil has potential as an anti-wear additive since a formulation using 10% v/v Sargassum spp. oil in a synthetic lubricant (PAO6) resulted in a wear scar diameter value of 703.03 ± 15.56 µm, which is about 10% lower than PAO6 used as commercial synthetic control. Additionally, the formulation significantly enhanced the viscosity index, with a value of 169, which was notably higher than the control (137). The parameter of the coefficient of friction was significantly reduced from 0.1 to 0.08 (about 27%) when using the formulation with 10% v/v Sargassum spp. oil. These findings underline the potential of algae oils as additives in synthetic lubricants, promoting a transition towards greener products and reducing the environmental impact derived from conventional formulations of polyalphaolefins and esters.

Medical image segmentation is crucial for diagnostics and treatment planning, yet traditional methods often struggle with the variability of real-world clinical data. Deep learning models, like the Segment Anything Model (SAM), have been proposed as a powerful tool that helps to delimit regions using a prompt. This work proposes a methodology to improve the quality of the segmentation by integrating test-time augmentation (TTA) with the SAM for medical applications (MedSAM) by using random circular shifts, addressing challenges such as misalignments and imaging variability. The method generates several input variations during inference that are combined after, improving robustness and segmentation accuracy without requiring retraining. Evaluated across diverse computed tomography (CT) datasets, including Medical Segmentation Decathlon (MSD), KiTS, and COVID-19-20, the proposed method demonstrated consistent improvements in Dice Similarity Coefficient (DSC) and Normalized Surface Dice (NSD) metrics. The highest performances were 93.6% DSC and 97% NSD. Notably, it achieved superior boundary precision and surface alignment in complex regions like the pancreas and colon, outperforming baseline models, including MedSAM and DeepLabv3+. The approach is computationally feasible, leveraging a balance of augmentation intensity and segmentation accuracy.

Context: There is limited information on the quantification of external load and reconditioning programs during adductor longus injuries in soccer. Case Presentation: This case report describes a male professional soccer player (LaLiga) returning to performance following an adductor longus muscle injury during the 2022/2023 season. The player suffered the injury during a change of direction in a match. The injury was confirmed by ultrasound after 48 h, and the previously validated rehabilitation and reconditioning program was applied to the injured player. This case report has focused on the development of the on-field reconditioning program and the quantification of the load during this phase. The goal of this case report was to return the player to pre-injury loads using global positioning systems (GPS). Variables such as total distance, distances covered at different speeds and metabolic load variables were quantified during the injury process, with the aim of increasing them through training and reaching at least 75% of the game load. Therefore, objective performance criteria for making return-to-play decisions based on the use of GPS was determined. In addition, the return to play (RTP) was on the 20th day after the injury, and then four RTPs were recorded in the following 6 weeks after the injury occurred, without re-injury. Conclusions: The approach to the competition performance profile, through the quantification of the external load during the rehabilitation process of the injured player, allowed us a safe return to competition and continued competition with a 6-week follow-up.

The use of ecofriendly natural minerals in photocatalytic processes to deal with the antimicrobial activity (AA) associated with antibiotics in aqueous systems is still incipient. Therefore, in this work, the capacity of a natural iron material (NIM) in photo-treatments, generating reactive species, to remove the antibiotic enrofloxacin and decrease its associated AA from water is presented. Initially, the fundamental composition, oxidation states, bandgap, point of zero charge, and morphological characteristics of the NIM were determined, denoting the NIM’s feasibility for photocatalytic processes. Consequently, the effectiveness of different advanced processes such as using solar light with the NIM (Light–NIM) and solar light with the NIM and H2O2 (Light–NIM–H2O2) to reduce AA was evaluated. The NIM acts as a semiconductor under solar light, effectively degrading enrofloxacin (ENR) and reducing its AA, although complete elimination was not achieved. The addition of hydrogen peroxide (NIM–Light–H2O2) enhanced the generation of reactive oxygen species (ROS), thereby increasing the elimination of ENR and AA. The role of ROS, specifically O2•− and HO●, in the degradation of enrofloxacin was distinguished using scavenger species and electron paramagnetic resonance (EPR) analysis. Additionally, the five primary degradation products generated during the advanced processes were elucidated. Furthermore, the relationship between the structure of these products and the persistence or elimination of AA, which was differentiated against E. coli but not against S. aureus, was discussed. The effects of the matrix during the process and the extent of the treatments, including their capacity to promote disinfection, were also studied. The reusability of the natural iron material was examined, and it was found that the NIM–Light–H2O2 system showed an effective reduction of 5 logarithmic units in microbiological contamination in an EWWTP and can be reused for up to three cycles while maintaining 100% efficiency in reducing AA.

In the original publication [...]

Video games have become one of the most popular forms of entertainment around the world. Currently, agents (bots or non-player characters) are predominantly programmed using procedural and deterministic imperative techniques, which pose significant drawbacks in terms of cost and time efficiency. An interesting and alternative line of work is to develop declarative scripting languages which align the programming task closer to human logic. This allows programmers to intuitively implement agents’ behaviors using straightforward rules. In this regard, most of these languages are interpreted, which may impact performance. Hence, this article presents the design and implementation of a new declarative and compiled scripting language called Obelysk for controlling agents. To test and evaluate the language, a video game was created using the Godot game engine, which allowed us to demonstrate the correct functionality of our scripting language to program the AIs participating in the video game. Finally, an analytics platform was also developed to evaluate the correct behavior of the programmed agents.

Background: MECP2 duplication syndrome (MDS) (MIM#300260) is a rare X-linked neurodevelopmental disorder. This study aims to (1) develop a specific clinical severity scale, (2) explore its correlation with clinical and molecular variables, and (3) automate diagnosis using the Face2gene platform. Methods: A retrospective study was conducted on genetically confirmed MDS patients who were evaluated at a pediatric hospital between 2012 and 2024. Epidemiological, clinical, and molecular data were collected. A standardized clinical questionnaire was collaboratively developed with input from physicians and parents. Patient photographs were used to train Face2Gene. Results: Thirty-five patients (0–24 years, 30 males) were included. Key features in males comprised intellectual disability (100%), hypotonia (93%), autism spectrum disorder (77%) and developmental regression (52%). Recurrent respiratory infections (79%), dysphagia (73%), constipation (73%) and gastroesophageal reflux (57%) were common. Seizures occurred in 53%, with 33% being treatment-refractory. The Face2Gene algorithm was successfully trained to identify MDS. A specific clinical severity scale (MECPDup) was developed and validated, correlating with the MBA (a scale developed for Rett syndrome). The MECPDup score was significantly higher in males (p < 0.001) and those with early death (p = 0.003). It showed significant positive correlations with age (p < 0.001) and duplication size (p = 0.044). Conclusions: This study expands the understanding of MDS through comprehensive clinical and molecular insights. The integration of AI-based facial recognition technology and the development of the MECPDup severity scale hold promise for enhancing diagnostic accuracy, monitoring disease progression, and evaluating treatment responses in individuals affected by MDS.

In the field of mechanical engineering, understanding mechanisms is essential for designing and developing devices and systems. Mechanisms, composed of interconnected elements, transform the energy applied to the input link into motion or force in the output link. Mechanisms are found in a wide variety of machines, from industrial machines to household machines. In this paper, a mechanism synthesis method is developed that can model four-bar linkages and build their cognate mechanisms to be able to select the mechanism that best suits the required work. Studying four-bar mechanisms offers a strong foundation for grasping more complex mechanical systems. The concepts and principles learned from four-bar mechanisms are widely applicable to advanced mechanical systems, making them a crucial starting point in mechanical engineering education and research. The mechanism synthesis method proposed in this article is organized into three main sections. The first section provides a comprehensive overview of the theoretical and mathematical foundations required for modeling mechanisms, laying the groundwork for understanding the subsequent calculations. The second section delves into the process of obtaining and analyzing the initial mechanism and constructing cognate mechanisms, detailing the procedures and algorithms used for modeling and calculating the coupling curve. Finally, the third section discusses the practical implementation of the method, including the graphical representation of mechanisms and a comparative analysis of the solutions obtained, assessing dimensional differences, design and manufacturing efficiency, and their suitability for various practical applications. The proposed four-bar mechanism synthesis method serves as a valuable tool for mechanism design, offering versatile and adaptable solutions that can optimize both technical performance and economic viability across a wide range of engineering applications.

Forest health monitoring is crucial for sustainable management, especially with the challenges posed by climate warming. Remote sensing data provide vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), that are widely used in assessing forest health. However, studies considering the validation of these data with field assessments of tree vigor are still scarce. To address this issue, we explored the relationships in declining (D) and non-declining (N) silver fir (Abies alba Mill.) stands from the Spanish Pyrenees between changes in canopy (a proxy of vigor), vegetation indices (NDVI, EVI) and climate variables. We compared trends in the NDVI and EVI for the period of 1984–2023 for D and N stands showing high and low crown defoliation levels, respectively. The EVI values allowed for the separation of stands according to their vigor earlier and more clearly than NDVI values, which did not show clear patterns throughout the time series. Significant negative correlations were found between the EVI and stand defoliation (r = −0.57) or mean radial growth (r = 0.81). Late-spring drought reduced the EVI. The EVI series reflected similar spatial patterns in terms of stand defoliation and tree growth, offering complementary information, along with the strengths of remote sensing with respect to its spatial and temporal coverage, for the early detection of forest dieback. This study also contributes to a better understanding of remote sensing indices, which is useful for forest health monitoring.

In this work, we present the construction and control of a four-degrees-of-freedom (DOF) manipulator aimed at addressing one of the key challenges faced by the Academy-Industry Cooperation Center (CCAI): the need for mechatronic equipment to support and facilitate the development of advanced robotic cells. We begin by designing the robot’s structure and components using SolidWorks software for computer-aided design (CAD) modeling. This ensures that all the links and parts fit together properly without collisions. The robot links are then manufactured using 3D printing. Additionally, we performed kinematic modeling, dynamic analysis, and PI-V control, along with control using a trigonometric function (hyperbolic tangent). To evaluate the robot’s movement, we simulate these processes using Matlab R2019a/Simulink software, focusing on key parameters such as position, velocity, and acceleration, which inform the design of PI-V control for each link. We also present the electrical and electronic designs, followed by system implementation. The kinematics of the robot play a crucial role in the dynamics and controller design. We validate the kinematics using Peter Corke’s libraries based on the Denavit–Hartenberg parameters. The results show that the controller based on the trigonometric function improves the response time, particularly enhancing the performance of axes 2 and 3.

Background: Solubility is one of the most important parameters in the research and development processes of the pharmaceutical industry. In this context, cosolubility is one of the most used strategies to improve the solubility of poorly soluble drugs, besides allowing to identify some factors involved in the dissolution process. The aim of this research is to evaluate the solubility of sulfamethazine in acetotinitrile + 1-propanol cosolvent mixtures at 9 temperatures (278.15, 283.15, 288.15, 293.15, 298.15, 303.15, 308.15, 313.15, and 318.15 K); a drug used in human and veterinary therapy and two solvents of great chemical–pharmaceutical interest. Methods: The determination was carried out by the shaking flask method and the drug was quantified by UV/Vis spectrophotometry. Results: The solubility of sulfamethazine increases from pure 1-propanol (solvent in which it reaches its lowest solubility at 278.15 K) to pure acetonitrile (solvent in which it reaches its maximum solubility at 318.15 K), behaving in a logarithmic-linear fashion. Conclusions: The increase in solubility is related to the acid/base character of the cosolvent mixtures and not to the solubility parameter of the mixtures. The dissolution process is endothermic and favored by the solution entropy, and also shows a strong entropic compensation.

Background: Regular physical activity plays a crucial role in modulating cellular metabolism and mitigating the progression of neurodegenerative diseases such as Alzheimer’s, Parkinson’s, and Multiple Sclerosis. Objective: The objective of this review is to evaluate the molecular mechanisms by which exercise influences cellular metabolism, with a focus on its potential as a therapeutic intervention for neurological disorders. Methods: A comprehensive literature review was conducted using peer-reviewed scientific articles, with a focus on the period between 2015 and 2024, to analyze the effects of exercise on mitochondrial function, oxidative stress, and metabolic health. Results: The findings indicate that exercise promotes mitochondrial biogenesis, enhances oxidative phosphorylation, and reduces reactive oxygen species, contributing to improved energy production and cellular resilience. These metabolic adaptations are associated with delayed disease progression and reduced symptoms in patients with neurodegenerative conditions. Additionally, integrating exercise with nutritional strategies may further enhance therapeutic outcomes by addressing metabolic disturbances comprehensively. Conclusions: This review concludes that personalized exercise protocols should be developed to optimize metabolic benefits for patients with neurological diseases, while future research should focus on biomarker development for individualized treatment approaches. These findings highlight the importance of non-pharmacological interventions in managing neurodegenerative diseases.

The Delottococcus aberiae is a mealybug pest known as Cotonet de les Valls in the province of Castellón (Spain). This tiny insect is causing large economic losses in the Spanish agricultural sector, especially in the citrus industry. The European Copernicus program encourages the progress of Earth observation (EO) in relation to the development of agricultural monitoring tools. In this context, this work is based on the analysis of the temporal evolution of spectral surface reflectance data from Sen2Like, analyzing healthy and fields affected by the mealybug. The study area is focused on the surroundings of Vall d’Uixó (Castellón, Spain), involving an approximate area of 25 ha distributed in a total of 21 fields of citrus trees with different mealybug incidence, classified as healthy or unhealthy, during the 2020–2021 season. The relationship between the mealybug infestation level and the Normalized Difference Vegetation Index (NDVI) and other optical bands (Red, NIR, SWIR, derived from Sen2Like) were analyzed by studying the time-series evolution of each parameter across the time period 2017–2022. In this study, we also demonstrate that evergreen fruit trees such as citrus, show a seasonality across the EO-based time series, which is linked to directional effects caused by the sensor–sun geometry. This can be mitigated by using a Bidirectional Reflectance Distribution Function (BRDF) model such as the High-Resolution Adjusted BRDF Algorithm (HABA). To study the infested fields separately from healthy ones and avoid mixing fields with very different spectral responses caused by field type, separation between rows, or age, we studied the evolution of each parcel separately using monthly linear regressions, considering the 2017–2018 seasons as a reference when the pest had not developed yet. The observations indicate the feasibility of the distinction between affected and healthy plots during a year utilizing specific spectral ranges, with SWIR proving a notably effective channel, enabling separability from mid-summer to the fall. Furthermore, the anomaly inspection demonstrates an increase in the effects of the pest from 2020 to 2022 in all spectral regions and enables a first approximation for identifying healthy and affected fields based on negative anomalies in the red and SWIR channels and positive anomalies in the NIR and NDVI. This work contributes to the development of new monitoring tools for efficient and sustainable action in pest control.

Acute-phase proteins (APPs) are biomarkers of systemic inflammation, which allow monitoring the response to surgery and post-operative complications. Ovariectomy (OVE) can be a useful model to evaluate surgical trauma and inflammation in feline species. The objective of this study was to evaluate and compare the acute-phase response (APR) after applying two different OVE techniques by measuring serum levels of serum amyloid A (SAA), haptoglobin (Hp), total serum proteins (TSPs), albumin (ALB), and paraoxonase-1 (PON-1) during the first 48 h post-surgery (hospital stay). Forty-two female cats were selected for elective spaying. The animals were randomly distributed into two groups: laparoscopic OVE (L-OVE) and midline OVE (M-OVE). Serum SAA, Hp, TSPs, ALB, and PON-1 were measured before surgery and 1, 6, 12, 24, and 48 h post-surgery. Unlike negative APPs such as PON-1 and ALB, SAA is the most sensitive positive APP for monitoring the inflammatory response in cats undergoing OVE following laparoscopic and conventional surgery. OVE performed in cats via both laparoscopic and midline techniques results in a significative increase in SAA levels, with early recovery, minor variations in serum total protein, and no significant changes in albumin, haptoglobin, or PON-1 over a 48-h period post-procedure. Based on SAA concentrations, the response to surgical trauma does not differ between surgical techniques.

The accessory olfactory bulb (AOB) processes chemical signals crucial for species-specific socio-sexual behaviors. There is limited information about the AOB of wild rodents, and this study aims to characterize the neurochemical organization of the AOB in the fossorial water vole (Arvicola scherman), a subterranean Cricetidae rodent. We employed histological, immunohistochemical, and lectin-histochemical techniques. The AOB of these voles exhibits a distinct laminar organization, with prominent mitral cells and a dense population of periglomerular cells. Lectin histochemistry and G-protein immunohistochemistry confirmed the existence of an antero-posterior zonation. Immunohistochemical analysis demonstrated significant expression of PGP 9.5, suggesting its involvement in maintaining neuronal activity within the AOB. In contrast, the absence of SMI-32 labelling in the AOB, compared to its strong expression in the main olfactory bulb, highlights functional distinctions between these two olfactory subsystems. Calcium-binding proteins allowed the characterization of atypical sub-bulbar nuclei topographically related to the AOB. All these features suggest that the AOB of Arvicola scherman is adapted for enhanced processing of chemosensory signals, which may play a pivotal role in its subterranean lifestyle. Our results provide a foundation for future studies exploring the implications of these adaptations, including potential improvements in the management of these vole populations.

In this work, an improved and scalable implementation of Cuppen’s algorithm for diagonalizing symmetric tridiagonal matrices is presented. This approach uses a hybrid-heterogeneous parallelization technique, taking advantage of GPU and CPU in a distributed hardware architecture. Cuppen’s algorithm is a theoretical concept and a powerful tool in various scientific and engineering applications. It is a key player in matrix diagonalization, finding its use in Functional Density Theory (FDT) and Spectral Clustering. This highly efficient and numerically stable algorithm computes eigenvalues and eigenvectors of symmetric tridiagonal matrices, making it a crucial component in many computational methods. One of the challenges in parallelizing algorithms for GPUs is their limited memory capacity. However, we overcome this limitation by utilizing multiple nodes with both CPUs and GPUs. This enables us to solve subproblems that fit within the memory of each device in parallel and subsequently combine these subproblems to obtain the complete solution. The hybrid-heterogeneous approach proposed in this work outperforms the state-of-the-art libraries and also maintains a high degree of accuracy in terms of orthogonality and quality of eigenvectors. Furthermore, the sequential version of the algorithm with our approach in this work demonstrates superior performance and potential for practical use. In the experiments carried out, it was possible to verify that the performance of the implementation that was carried out scales by 2× using two graphic cards in the same node. Notably, Symmetric Tridiagonal Eigenvalue Solvers are fundamental to solving more general eigenvalue problems. Additionally, the divide-and-conquer approach employed in this implementation can be extended to singular value solvers. Given the wide range of eigenvalue problems encountered in scientific and engineering domains, this work is essential in advancing computational methods for efficient and accurate matrix diagonalization.

The aim of this study was to analyse the differentiated role played by academic self-concept on teacher identity, taking into account the mediating role of teacher efficacy and the gender of the pre-service physical-education teachers. In this cross-sectional study, 478 master’s degree students in Secondary Education Teacher Training participated (Mean = 27.09; SD = 6.32; 54.8% male, 44.8% female, 0.4% other). The following scales were used: academic self-concept, teaching identity, and teacher self-efficacy. After finding significant differences in academic effort, a structural equation analysis (SEM) with the multigroup option was conducted to answer the research objective. The results revealed that the women had significantly higher mean academic effort values than the men. In addition, the SEM, which showed excellent fit indices, revealed that, for the men, teacher efficacy acted as a mediating variable between academic confidence and teacher identity. In contrast, for the women, teacher efficacy acted as a mediator between academic effort and teacher identity. However, academic effort also acted as a direct predictor of teacher identity in male pre-service teachers. As a main conclusion, it can be said that the findings highlight the importance of academic self-concept in undertaking the master’s degree by increasing teacher identity through the teaching efficacy of pre-service teacher educators.

Background: Alternative Splicing (AS) is a post-transcriptional process that allows a single RNA to produce different mRNA variants and, in some cases, multiple proteins. Various processes, many yet to be discovered, regulate AS. This study focuses on regulation by RNA-binding proteins (RBPs), which are not only crucial for splicing regulation but also linked to cancer prognosis and are emerging as therapeutic targets for cancer treatment. CLIP-seq experiments help identify where RBPs bind on nascent transcripts, potentially revealing changes in splicing status that suggest causal relationships. Selecting specific RBPs for CLIP-seq experiments is often driven by a priori hypotheses. Results: We developed an algorithm to detect RBPs likely related to splicing changes between conditions by integrating several CLIP-seq databases and a differential splicing detection algorithm. This work refines a previous study by improving splicing event prediction, testing different enrichment statistics, and performing additional validation experiments. The new method provides more accurate predictions and is included in the Bioconductor package EventPointer 3.14. We tested the algorithm in four experiments involving knockdowns of seven different RBPs. The algorithm accurately assessed the statistical significance of these RBPs using only splicing alterations. Additionally, we applied the algorithm to study sixteen cancer types from The Cancer Genome Atlas (TCGA) and three from TARGET. We identified relationships between RBPs and various cancer types, including alterations in CREBBP and MBNL2 in adenocarcinomas of the lung, liver, prostate, rectum, stomach, and colon. Some of these findings are validated in the literature, while others are novel. Conclusions: The developed algorithm enhances the ability to predict and understand RBP-related splicing changes, offering more accurate predictions and novel insights into cancer-related splicing alterations. This work highlights the potential of RBPs as therapeutic targets and contributes to the broader understanding of their roles in cancer biology.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is often asymptomatic and underdiagnosed; consequently, there is a demand for simple, non-invasive diagnostic tools. In this study, we developed a method to quantify liver steatosis based on miRNAs, present in liver and serum, that correlate with liver fat. The miRNAs were analyzed by miRNAseq in liver samples from two cohorts of patients with a precise quantification of liver steatosis. Common miRNAs showing correlation with liver steatosis were validated by RT-qPCR in paired liver and serum samples. Multivariate models were built using partial least squares (PLS) regression to predict the percentage of liver steatosis from serum miRNA levels. Leave-one-out cross validation and external validation were used for model selection and to estimate predictive performance. The miRNAseq results disclosed (a) 144 miRNAs correlating with triglycerides in a set of liver biobank samples (n = 20); and (b) 124 and 102 miRNAs correlating with steatosis by biopsy digital image and MRI analyses, respectively, in liver samples from morbidly obese patients (n = 24). However, only 35 miRNAs were common in both sets of samples. RT-qPCR allowed to validate the correlation of 10 miRNAs in paired liver and serum samples. The development of PLS models to quantitatively predict steatosis demonstrated that the combination of serum miR-145-3p, 122-5p, 143-3p, 500a-5p, and 182-5p provided the lowest root mean square error of cross validation (RMSECV = 1.1, p-value = 0.005). External validation of this model with a cohort of mixed MASLD patients (n = 25) showed a root mean squared error of prediction (RMSEP) of 5.3. In conclusion, it is possible to predict the percentage of hepatic steatosis with a low error rate by quantifying the serum level of five miRNAs using a cost-effective and easy-to-implement RT-qPCR method.

Background/Objectives: Obstructive sleep apnea (OSA) is marked by repetitive occurrences of upper airway (UA) obstruction during sleep. Morbidities impacting the metabolic, cardiovascular (CV) and neurological systems are correlated with OSA. Only a few studies have described the existence of different characteristics depending on sex and, to date, the girl phenotype in OSA pediatrics is not well known. The objective of this systematic review is to identify the specific phenotype of OSA in pediatric and adolescent females compared to males. Methods: A systematic review was performed. The terms “pediatric sleep apnea” and “sex differences” were used to look for publications using PubMed, the Cochrane Library and Web of Science. Inclusion criteria: (1) peer-reviewed journal articles written in English; (2) investigations conducted on individuals diagnosed with OSA; and (3) investigations providing information about sex differences. Exclusion criteria: (1) studies carried out with individuals aged 18 years and older; (2) studies involving a sample size of fewer than 10 patients; and (3) editorials, letters and case reports. Results: Fifteen studies were included and classified in sections related to sex-based differences. Conclusions: Limited information related to sex-based OSA differences in the pediatric population exists. These differences are conditioned by hormonal status, and are minimal in the premenarcheal period. Moreover, adolescent women present a lower prevalence of obesity and craniofacial alterations, lower OSA severity related to higher UA area and earlier tonsil regression. Hyperactivity is more frequent in boys. Some studies pointed to a higher risk of high diastolic blood pressure in girls than in boys.

Background/Objectives: The relationship between executive functions, special educational needs (SEN), and learning difficulties in school-aged children is critical for developing effective educational interventions. This study explores the connection between executive functions and SEN in primary school students, examining differences in executive function profiles between those with and without SEN and their impact on learning difficulties. Methods: In total, 123 primary school students aged 6 to 12 and their teachers and parents participated in this study. The Behavior Rating Inventory of Executive Function (BRIEF-2) and the Prediscal test were used to assess difficulties in reading and mathematics, and sociodemographic and clinical data were collected through ad hoc records. Results: The results indicated that students with SEN exhibited significantly more affected executive function profiles compared to their peers without SEN in both family and school contexts, highlighting areas such as cognitive flexibility, initiative, working memory, planning and organisation, task supervision, and material organisation. Additionally, significant negative correlations were found between executive functions and performance in reading and mathematics, suggesting that deficits in executive functions are strongly associated with SEN. Conclusions: These findings underscore the critical role of executive functions in understanding and addressing SEN and learning difficulties, emphasising the need for comprehensive assessment programmes and early intervention targeting executive function deficits to support the academic and overall development of students with SEN.

The work presents an analysis of the Gorlov helical turbine (GHT) design using both computational fluid dynamics (CFD) simulations and response surface methodology (RSM). The RSM method was applied to investigate the impact of three geometric factors on the turbine’s power coefficient (CP): the number of blades (N), helix angle (γ), and aspect ratio (AR). Central composite design (CCD) was used for the design of experiments (DOE). For the CFD simulations, a three-dimensional computational domain was established in the Ansys Fluent software, version 2021R1 utilizing the k-ω SST turbulence model and the sliding mesh method to perform unsteady flow simulations. The objective function was to achieve the maximum CP, which was obtained using a high-correlation quadratic mathematical model. Under the optimum conditions, where N, γ, and AR were 5, 78°, and 0.6, respectively, a CP value of 0.3072 was achieved. The optimal turbine geometry was validated through experimental testing, and the CP curve versus tip speed ratio (TSR) was determined and compared with the numerical results, which showed a strong correlation between the two sets of data.

Gravitational vortex turbines can provide a sustainable and efficient solution for generating renewable energy from small watercourses, minimizing environmental impact, and contributing to the decentralization of energy production. Their design allows for high energy efficiency even under low flow conditions, thus benefiting rural communities and reducing their dependence on fossil fuels. This paper presents an experimental assessment of the hydrodynamic behavior of gravitational vortex turbines by examining various geometric configurations. The combinations of two types of inlet channels (spiral and tangential) and two types of discharge basins (conical and cylindrical) were investigated. Additionally, different geometries and placements of the runners were evaluated to determine their influence on the efficiency and performance of the turbine. The results indicate that the highest efficiency of 60.85% was achieved with a configuration that included a spiral inlet channel, cylindrical discharge, and a runner placement of 50%.

Forest fuels are the core element of fire management; each fuel component plays an important role in fire behavior. Therefore, accurate determination of their characteristics and spatial distribution is crucial. This paper introduces a novel method for mapping the spatial distribution of litter and duff fuel loads using data collected by unmanned aerial vehicles. The approach leverages a very high-resolution multispectral data analysis within a machine learning framework to achieve precise and detailed results. A set of vegetation indices and texture metrics derived from the multispectral data, optimized by a “Variable Selection Using Random Forests” (VSURF) algorithm, were used to train random forest (RF) models, enabling the modeling of high-resolution maps of litter and duff fuel loads. A field campaign to measure fuel loads was conducted in the mixed forest of the natural protected area of “Sierra de Quila”, Jalisco, Mexico, to measure fuel loads and obtain field reference data for calibration and validation purposes. The results revealed moderate determination coefficients between observed and predicted fuel loads with R2 = 0.32, RMSE = 0.53 Mg/ha for litter and R2 = 0.38, RMSE = 13.14 Mg/ha for duff fuel loads, both with significant p-values of 0.018 and 0.015 for litter and duff fuel loads, respectively. Moreover, the relative root mean squared errors were 33.75% for litter and 27.71% for duff fuel loads, with a relative bias of less than 5% for litter and less than 20% for duff fuel loads. The spatial distribution of the litter and duff fuel loads was coherent with the structure of the vegetation, despite the high complexity of the study area. Our modeling approach allows us to estimate the continuous high-resolution spatial distribution of litter and duff fuel loads, aligned with their ecological context, which dictates their dynamics and spatial variability. The method achieved acceptable accuracy in monitoring litter and duff fuel loads, providing researchers and forest managers with timely data to expedite decision-making in fire and forest fuel management.

Sulfamerazine (SMR) is a drug used as an antibacterial agent in the treatment of some pathologies, such as bronchitis, prostatitis and urinary tract infections. Although this drug was developed in 1945 and, due to its toxicity, was partially displaced by penicillin, due to the current problem of bacterial resistance, compounds such as SMR have regained validity. In this context, the thermodynamic study of SMR in cosolvent mixtures of acetonitrile (MeCN) + ethanol (EtOH) at nine temperatures (278.15–318.15 K) is presented. The solubility of SMR was determined by UV–Vis spectrophotometry, following the guidelines of the shake-flask method. The solubility process was endothermic in all cases; thus, the minimum solubility was reached in pure EtOH at 278.15 K, and the maximum solubility was reached in pure MeCN at 318.15 K. Both the solution process and the mixing process were entropy-driven. On the other hand, the solubility data were modeled by using the van’t Hoff–Yalkowsky–Roseman model, obtaining an overall average relative deviation of 3.9%. In general terms, it can be concluded that the solution process of SMR in {MeCN (1) + EtOH (2)} mixtures is thermodependent, favored by the entropy of the solution and mixture; additionally, the van’t Hoff–Yalkowsky–Roseman model allows very good approximations to be obtained and is a simple model that starts from only four experimental data.

(1) Background: As far back as the 1930s, it was already thought that gestures, clothing, speech, posture, and gait could express an individual’s personality. Different research programs, some focused on linguistic cues, were launched, though results were inconsistent. The development of new speech analysis technology and the generalization of big data analysis have created an opportunity to test the predictive power of voice features on personality dimensions. This study aims to explore the feasibility of an automatic personality assessment system in the context of personnel selection. (2) Methods: One hundred participants were recorded during an individual interview for voice analysis. They also completed the NEO-FFI and were required to ask and collect the assessment of their personality by a close significant other. Furthermore, an expert estimated participants’ personality dimensions based on the viewing of the recorded interviews. (3) Results: Results showed there are specific voice features related to the externalization of individuals’ personalities (predictions ranging from 0.3 to 0.4). Voice features also predicted significant others’ estimations and expert ratings of the target individual’s personality, though the features were not exactly the same. (4) Conclusions: It is noteworthy that predictions were made based on voice recordings obtained using ordinary devices in controlled but not restricted speech situations, which may make such an approach a promising tool for personality assessment in contexts such as personnel selection.

We evaluated the surgical stress response of dogs undergoing three ovariohysterectomy (OVH) techniques. Twenty-nine healthy females were allocated into groups: celiotomy and ligature (CelioSut), celiotomy and bipolar energy (CelioBip), and a video-assisted technique using two portals and bipolar energy (VidBip). Clinical evaluation was performed, and the following blood analyses were determined: acute phase proteins (C-reactive protein and haptoglobin), white blood cell counting (WBC), and biomarkers of oxidative status. The VidBip required more time despite a smaller incision, lower heart rate, and earlier feeding and urination. All groups had high white blood cells counts; the C-reactive protein (CRP) levels peaked at 6 and 12 h in all groups and was higher in the CelioBip and VidBip groups compared to CelioSut; haptoglobin concentrations peaked at 48 h in all groups and increased in dogs of the CelioSut group. Trolox equivalent antioxidant capacity, ferric reducing ability of plasma, cupric reducing antioxidant capacity, and advanced oxidation protein were not significantly different among the groups or time points. Total thiol concentrations were lower in CelioBip and CelioSut groups. All surgical techniques induced an inflammatory and oxidative stress response, but the video-assisted technique produced early clinical recovery. The bipolar device produces fewer disturbances than suspensory ligament rupture and ligature.

Adaptive thermal comfort models are increasingly utilized to condition thermal environments by considering occupants’ adaptability. The most widely recognized models internationally are the ASHRAE 55-2020 and UNE-EN 16798-1:2020 standards, primarily applied in residential and office buildings. However, their use in heritage buildings such as museums has been very limited. These environments present unique challenges that complicate the implementation of conventional energy-saving methodologies due to restrictions on interventions in the buildings to safeguard their historical value. Therefore, it is essential to develop research that evaluates the applicability of these standards as an alternative strategy to the specific conditions of museums in heritage buildings in Spain. This study aims to explore the application of the international adaptive thermal comfort models of the ASHRAE 55-2020 and UNE-EN 16798-1:2020 standards in parallel with the preventive conservation conditions of the collections established by the UNE-EN 15757:2011 standard. The aim is to evaluate new strategies for environmental reconditioning to improve visitor comfort while ensuring the conservation of the collections in the exhibition spaces of the Museum of Popular Arts and Customs, housed in a 1914 building known as the Mudejar Pavilion in Seville. Field monitoring was conducted to assess the thermal environment and visitor comfort. The results revealed that the monitored environmental conditions of the exhibition spaces of the Mudejar Pavilion, in accordance with ASHRAE 55-2020 standards, showed high effectiveness in ensuring thermal comfort for visitors, achieving comfort 99% of the time annually, with an acceptability of 80%. High suitability for the conservation of collections was also observed, with optimal conditions achieved 87% of the time. However, under the standards of UNE-EN 15757:2011 for a Category III expectation level, comfort was only achieved 70% of the year, while stability of conservation conditions was achieved 88% of the time. Finally, the implementation of specific correction guidelines is proposed to achieve the acceptability limits of greater energy efficiency.

Introduction: This article provides an overview of several experimental models, including in vivo, genetics, chemical, knock-in, knock-out, electrical, in vitro, and optogenetics models, that have been employed to investigate epileptogenesis. The present review introduces a novel categorization of these models, taking into account the fact that the most recent classification that gained widespread acceptance was established by Fisher in 1989. A significant number of such models have become virtually outdated. Objective: This paper specifically examines the models that have contributed to the investigation of partial seizures, generalized seizures, and status epilepticus. Discussion: A description is provided of the primary features associated with the processes that produce and regulate the symptoms of various epileptogenesis models. Numerous experimental epilepsy models in animals have made substantial contributions to the investigation of particular brain regions that are capable of inducing seizures. Experimental models of epilepsy have also enabled the investigation of the therapeutic mechanisms of anti-epileptic medications. Typically, animals are selected for the development and study of experimental animal models of epilepsy based on the specific form of epilepsy being investigated. Conclusions: Currently, it is established that specific animal species can undergo epileptic seizures that resemble those described in humans. Nevertheless, it is crucial to acknowledge that a comprehensive assessment of all forms of human epilepsy has not been feasible. However, these experimental models, both those derived from channelopathies and others, have provided a limited comprehension of the fundamental mechanisms of this disease.

In this paper, the authors generalize the fractional curvature of plane curves introduced by Rubio et al. in 2023, to regular curves in the Euclidean space R3, and study the geometric properties of the curve using Caputo’s fractional derivative. Furthermore, we introduce a new definition of fractional curvature and fractional mean curvature of a regular surface, using fractional principal curvatures; and prove that such concepts are invariant under isometries; i.e., they belong to the intrinsic geometry of the regular surface. Also, a geometric interpretation is given to Caputo’s fractional derivative of algebraic polynomials.

Objective: We aimed to evaluate the use of CDK4/6 inhibitors as a risk factor for medication-related osteonecrosis of the jaw (MRONJ) in a cohort of patients with metastatic breast cancer treated with denosumab. Methods: This was a multicentre, retrospective, observational study. All patients with breast cancer treated with denosumab (January 2011–December 2022) were included. The relationship between CDK4/6 inhibitors and MRONJ was analysed. Results: A total of 243 patients were included, ninety-five (44.2%) of whom used a CDK4/6 inhibitor. There were 21 patients with MRONJ. In patients treated with denosumab without CDK4/6 inhibitors, the incidence of MRONJ and mean time to the occurrence of MRONJ were 6.6% (8/120) and 16.8 months (SD 7.8), respectively; in patients treated with denosumab and CDK4/6 inhibitor, these values were 13.7% (13/95) and 15.4 months (SD 8.7), respectively. The difference in the incidence was not significant (p = 0.085). Among the 19 patients who used abemaciclib, the probability of MRONJ occurrence was significantly higher compared to patients not using CDK4/6 inhibitors (p = 0.0178). Conclusions: These results suggest that the incidence of MRONJ in patients with metastatic breast cancer treated with denosumab is higher, and the onset of MRONJ occurs earlier in the presence of CDK4/6 inhibitors. The differences were statistically significant in the patients who used abemaciclib. Given that the use of this combination is very common in routine clinical practice, it would be advisable to carry out larger prospective studies to clarify the risk of this association.

The COVID-19 pandemic forced museums to rethink their activity in the context of social media, thus generating new ways of communicating and educating about the heritage they preserve. This article explores the indissoluble relationship established between these emerging edu-communication models and the spaces destined to safeguard the intangible cultural heritage (ICH), since the latter is a sociocultural phenomenon whose museumization requires education and civic participation. In order to determine to what extent museum edu-communication inspired by the co-creative paradigm can be extended into formal teaching contexts for the generation of heritage bonds and communities around ICH, two cases produced at the J. Trepat Factory Museum in Tàrrega (Spain) are analyzed through an autoethnographic approach. Both examples encourage a reflection on how the co-creative paradigm makes it possible to raise awareness and involve the entire community in the safeguarding of heritage, while at the same time promoting the expansion and reformulation of the institution’s proposals. We conclude that the integration of this approach into formal pedagogical practices contributes to overcoming some of the limitations of non-formal and informal edu-communication, as well as to generating a rhizomatic identization around ICH.