University of Granada

Besides mulberry fruit, mulberry ( Morus alba L. ) has many byproducts, including leaves, branches, and roots. Although these byproducts have long been used as traditional Chinese medicine, their use is limited mainly to rheumatism, diabetes, arthritis. These natural products have a variety of bioactive ingredients, including flavonoids, alkaloids, polysaccharides, with antioxidant, anti-inflammatory, lipid-lowering and other biological functions. This review introduces the bioactive ingredients of mulberry leaves, branches, and roots and discusses their potential in alleviating cardiovascular diseases from antioxidant, anti-inflammatory, lipid regulation, blood glucose regulation, vascular protection and other aspects.

Gene expression (GE) and alternative splicing (AS) contribute to the formation of new interaction networks with potentially significant cellular functions. Here, we investigate ageing in the Drosophila female germline stem cell (GSC) niche and describe functional changes in both GE and AS. The GSC niche comprises three types of support cells, whose ageing transcriptomes reveal differential GE and AS variations related to cell adhesion, cytoskeleton and neural signalling. Because each population show distinctive GE and AS changes, niche cell types possess unique ageing signatures. Depending on the cell population, groups of genes display changes in both GE and AS, revealing a coordinated regulation of transcription and splicing during niche ageing. One such gene is Fasciclin 2, a neural adhesion molecule that we find is essential for niche functioning. Furthermore, genes involved in AS undergo changes in GE and/or AS themselves, providing a mechanistic explanation for the coordination of these two processes during niche ageing. This is the case of the splicing factor Smu1, described here as a key element necessary for ovarian niche homeostasis.

In this article, we investigate a hybrid discrete–continuous coagulation and fragmentation model employing the strongly continuous semigroups theory on operators. Under the appropriate assumptions on the coagulation and fragmentation kernels, we establish the global existence and uniqueness of solutions. This extends similar results obtained in earlier investigations for the pure hybrid discrete–continuous fragmentation model.

Despite the evolution of the grit conceptualization over the years, the psychometric validity of scales and construct structure remain unclear. Consequently, this study aims to provide new evidence that broadens the current understanding of the grit’s dimensional nature in the Spanish population by examining the psychometric properties of the Spanish Grit-S Scale. The sample comprised 1027 undergraduates. The average age of the participants was 20.93 years (ranging from 18 to 45 years). The internal structure was analyzed using confirmatory factor analysis, and the reliability was assessed using internal consistency measures and composite reliability. Findings indicated that a bidimensional factor structure (i.e., consistency of interest and perseverance in effort) achieved better fit indexes, while overall grit showed superior reliability. Perseverance in effort was more strongly related to academic performance. The results suggest that measuring grit as a two-dimensional construct is preferable because each dimension accounts for different variances in outcomes. This study may contribute to addressing the controversy surrounding the measurement of this construct and assist researchers and practitioners in evaluating interventions that include grit among their outcomes.

This article presents an interdisciplinary programme for research on historic landscapes that has emerged since 2020 in the framework of the project Terraces as Sustainable Agricultural Environments ('TerraSAgE'). While the methodology has been tested in specific Mediterranean case studies, it is also applicable in other locations and regions. Our integrated approach provides new insights into the development of terraced agrarian landscapes and the changing dynamics in land management. It can provide knowledge of the extent to which past change has influenced present-day landscapes and has implications for the development of sustainable landscape practices. The research framework proposed here has been tested through case studies in different landscape types across southern Europe, including small-scale mixed farming landscapes of the Aegean islands (Naxos, Greece); terraces for vines and olives (Pelješac, Croatia); a landscape of dairy production (northern Apennines, Italy), which was until quite recently agroforestry; modern cereal cultivation (around Els Prats de Rei, Catalonia, Spain); upland irrigated landscapes on the slopes of the Sierra Nevada (Andalucia, Spain) and mixed farming in a wooded Atlantic environment (Galicia, Spain).

The purpose of this article is to examine the role of social spending policies in reducing child deprivation and inequality between family structures. In particular, based on the idea that the redistributive effects of such policies affect economic well-being in childhood, we analyse whether three functions of social spending (family/children, housing/social exclusion and sickness/disability) are associated with the reduction of different types of child deprivation (nutrition, clothing, education, leisure and social life) in Europe. We employ multilevel techniques for this purpose. Our findings are consistent with the hypothesis that greater social spending on sickness/disability benefits can reduce the risk of child deprivation, particularly for single-parent families, although we cannot exclude the possibility that this association is spurious. Family/children benefits and housing/social exclusion benefits seem to have a somewhat more limited effect but still contribute to reducing inequalities between single-parent and two-parent families in some types of deprivation.

Objective The present study evaluated the correlation between ocular sagittal height and lens sagittal depth, specifically focusing on the sagittal difference (δ‐sag) that defines an optimal lens fit. Methods The ocular sagittal height (spanning a 14.2‐mm chord in the ocular surface flattest meridian) of 30 subjects was measured using the Oculus Pentacam HR. Participants were fitted with eight different standard daily disposable soft contact lenses, each having a known sagittal depth. To evaluate the fit, both objective methods (using ImageJ software) and subjective assessments (by two experienced eye care professionals [ECPs]) were employed. Descriptive statistics were obtained for different δ‐sag, and correlations and a regression model were applied to determine the δ‐sag range indicative of a satisfactory lens fit, based on the objective and subjective evaluations. Results The δ‐sag achieved in most cases ranged between 200 and 600 μm. Participants reported high comfort levels independently of δ‐sag ( H = 8.99; p = 0.25) and type of contact lens ( χ ² = 1.47; p = 0.98). Significant correlations were found between δ‐sag and objective assessments of lens centration (inferior, nasal and temporal) and movement (nasal lag). The regression model, based on the subjective assessment conducted by the ECPs, yielded a δ‐sag of between 120 and 280 μm for a score considered as good. Conclusions Objective and subjective assessments showed significant associations with δ‐sag. A standard cast‐moulded disposable soft contact lens whose sagittal depth exceeded the ocular sagitta corresponding to the chord equivalent to the total contact lens diameter by 120–280 μm would most likely result in an optimal fit. These findings could help improve fitting accuracy and reduce dropout rates, thereby enhancing patient experience and ocular health.

Given the significance of social commerce, extensive research has been conducted from various perspectives, resulting in numerous reviews and meta-analytical papers. However, these previous studies have highlighted information gaps and variations in approaches. Therefore, there is a need for a comprehensive examination of social commerce research, encompassing past, present, and future themes, as well as an investigation into additional features of social commerce. To address this need, the present study undertakes a comprehensive thematic review of social commerce research for two distinct periods: 2008–2018 and 2019–2022. Bibliometric analyses were conducted using data extracted from the Web of Science database. The research employed science mapping techniques through the utilization of SciMAT and VOSviewer software. The findings of this study identified several themes related to social commerce during the first period, including product, perceived sociability, impulse buying, information technology, motivation, mobile commerce, and others, which were extensively explored. In the second period, themes such as UTAUT, SMEs, perceived risk, live stream, SOR (stimulus-organism-response), and the concept swift guanxi received significant attention. These findings, among others, contribute to the evolving understanding of the social commerce concept. By conducting a comprehensive thematic review and employing bibliometric analyses, this research fills existing knowledge gaps and provides a broader understanding of social commerce research across different periods. The findings shed light on the evolution of social commerce and pave the way for future investigations in this field.

Increasing evidence supports the role of the placenta in neurodevelopment and in the onset of neuropsychiatric disorders. Recently, mQTL and iQTL maps have proven useful in understanding relationships between SNPs and GWAS that are not captured by eQTL. In this context, we propose that part of the genetic predisposition to complex neuropsychiatric disorders acts through placental DNA methylation. We construct a public placental cis-mQTL database including 214,830 CpG sites calculated in 368 fetal placenta DNA samples from the INMA project, and run cell type-, gestational age- and sex-imQTL models. We combine these data with summary statistics of GWAS on ten neuropsychiatric disorders using summary-based Mendelian randomization and colocalization. We also evaluate the influence of identified DNA methylation sites on placental gene expression in the RICHS cohort. We find that placental cis-mQTLs are enriched in placenta-specific active chromatin regions, and establish that part of the genetic burden for schizophrenia, bipolar disorder, and major depressive disorder confers risk through placental DNA methylation. The potential causality of several of the observed associations is reinforced by secondary association signals identified in conditional analyses, the involvement of cell type-imQTLs, and the correlation of identified DNA methylation sites with the expression levels of relevant genes in the placenta.

Although children who grow up in a low socioeconomic situation present deficits in literacy skills, the present research aimed to shed light on the skills they possess and how detecting them can help improve their development. A total of 439 children were analysed for their literacy skills, learning potential in reading‐ and writing‐related skills as determined by dynamic assessment methodology, and behaviour during the test situation. Participants belonged to three groups: children with socioeconomic disadvantage, children with literacy difficulties and children with typical development. Results showed that children with socioeconomic disadvantage and those with literacy difficulties showed similar results in traditional reading and writing tests. Nonetheless, children with socioeconomic disadvantage showed higher learning potential in these skills than children with literacy difficulties. This result supports the accuracy of dynamic assessment for classification. In addition, the behavioural profile in a test situation differed between the groups. The study conclusions relate to the importance of developing intervention programmes in reading and writing skills for children at risk of learning difficulties, considering not only their initial level but also their learning potential and behavioural profiles.

In this paper we consider a doubly critical nonlinear elliptic problem with Neumann boundary conditions. The existence of blow-up solutions for this problem is related to the blow-up analysis of the classical geometric problem of prescribing negative scalar curvature $K=-1$ on a domain of $\mathbb {R}^n$ and mean curvature $H=D(n(n-1))^{-1/2}$, for some constant $D>1$, on its boundary, via a conformal change of the metric. Assuming that $n\ge 6$ and $D>\sqrt{(n+1)/(n-1)}$, we establish the existence of a positive solution which concentrates around an elliptic boundary point which is a stable critical point of the original mean curvature.

Objectives To perform a systematic review and meta‐analysis to evaluate the effectiveness of machine learning (ML) algorithms in the diagnosis of vestibular migraine. Background Due to the absence of defined biomarkers for diagnosing vestibular migraine (VM), it is valuable to determine which clinical, physical, and exploratory information is most crucial to diagnosing this disease. The use of artificial intelligence tools could streamline this process. Methods This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta‐Analyses guidelines and searched for records from PubMed, Scopus, and Web of Science. Observational (case–control and cohort) studies were included to assess the ability of artificial intelligence (AI) to distinguish VM from other vestibular disorders. Risk of bias and applicability concerns were assessed using the Quality Assessment of Diagnostic Accuracy Studies‐AI tool. Results A total of 14 articles were included in the systematic review, and 10 were eligible for meta‐analysis. The main inputs included for the ML algorithms were anamnesis (medical history), physical examination, results from audiological and vestibular tests, and imaging. The global sensitivity was 0.85 (95% confidence interval [CI] 0.73–0.92, I ² = 96%), while the global specificity was 0.89 (95% CI 0.84–0.93, I ² = 95%). The pooled diagnostic odds ratio was 48.15 (95% CI 17.64–131.43, I ² = 97%). Using the bivariate model, the area under the curve and for the summary receiver operating characteristic curve, using the 10 available studies, was 0.94 (95% CI 0.86–0.96). Conclusion Machine learning algorithms could be used as effective tools for the diagnosis process in VM. The use of models trained with three to four inputs yield the highest accuracy, compared to other strategies. However, the design and validation of these studies could be improved to ensure the reproducibility and generalizability of results.

This study aims to determine the relationship of the critical power (CP) and the work above CP (W´) with physiological and neuromuscular performance factors. Twenty-one recreational runners, 11 men and 10 women were tested on 3 separate occasions spaced by 48-72 hours. In the first session, the vertical load-velocity and horizontal force-velocity profiles were determined. In the second testing session, the maximal oxygen uptake, running economy, first and second ventilatory thresholds and maximal aerobic power were determined through a graded exercise test. In the third testing session, the CP and W´ were determined through two-time trials of 9- and 3-min. The CP was significantly correlated with all physiological factors evaluated (r ≥ -0.479; p ≤ 0.028), meanwhile none were with W´ (r ≤ 0.377; p ≥ 0.092). On the other hand, W´ was positively associated with specific neuromuscular performance factors of the vertical load-velocity (r = 0.763; p < 0.001) (i.e., theoretical maximal vertical velocity) and horizontal force-velocity (r ≥ 0.658; p ≤ 0.001) (i.e., theoretical maximal horizontal velocity and maximal power) profiles. The CP modelling results in a feasible procedure to capture both physiological and neuromuscular performance determinants through the CP and W´ parameters, respectively.

Targeted maximum likelihood estimation (TMLE) is an increasingly popular framework for the estimation of causal effects. It requires modeling both the exposure and outcome but is doubly robust in the sense that it is valid if at least one of these models is correctly specified. In addition, TMLE allows for flexible modeling of both the exposure and outcome with machine learning methods. This provides better control for measured confounders since the model specification automatically adapts to the data, instead of needing to be specified by the analyst a priori . Despite these methodological advantages, TMLE remains less popular than alternatives in part because of its less accessible theory and implementation. While some tutorials have been proposed, none address the case of a time‐to‐event outcome. This tutorial provides a detailed step‐by‐step explanation of the implementation of TMLE for estimating the effect of a point binary or multilevel exposure on a time‐to‐event outcome, modeled as counterfactual survival curves and causal hazard ratios. The tutorial also provides guidelines on how best to use TMLE in practice, including aspects related to study design, choice of covariates, controlling biases and use of machine learning. R‐code is provided to illustrate each step using simulated data ( https://github.com/detal9/SurvTMLE ). To facilitate implementation, a general R function implementing TMLE with options to use machine learning is also provided. The method is illustrated in a real‐data analysis concerning the effectiveness of statins for the prevention of a first cardiovascular disease among older adults in Québec, Canada, between 2013 and 2018.

The Daylight Illuminant D65, a standardised reference light source in design and research with a colour temperature of 6500 K, is often used to describe the colour of the daylight. However, it represents the colour of an overcast sky, failing to capture the variability and richness of actual daylight, particularly the blue of clear skies. Recent research shows that both sunlight and skylight significantly influence our mood, perception and physiological responses. The colour of daylight is influenced by factors like sun position, weather conditions, as well as geographical location. To address these variations, researchers are collecting worldwide spectral daylight measurements, emphasising the need for localised spectral reference data to appropriately represent daylight in different locations.

Nitrous oxide (N 2 O) is a potent greenhouse gas and the main stratospheric ozone-depleting agent, yet its sources are not well resolved. In this work, we experimentally show a N 2 O production pathway not previously considered in greenhouse gas budgets, which we name photochemodenitrification. Sunlight induces substantial and consistent N 2 O production under oxic abiotic conditions in fresh and marine waters. We measured photochemical N 2 O production rates using isotope tracers and determined that nitrite is the main substrate and that nitrate can also contribute after being photoreduced to nitrite. Additionally, this N 2 O production was strongly correlated to the radiation dose. Photochemodenitrification exceeded biological N 2 O production in surface waters. Although previously overlooked, this process may contribute considerably to global N 2 O emissions through its occurrence in fresh and marine surface waters.