Biology subjects

Munoz, F.

Publications and source records attributed to Munoz, F..

14 recordsLinked to original sources

bioRxiv2026

Aesthetic Appreciation and Environmental Values: A Cross-Cultural Study of Teachers in 34 Countries

BackgroundThe relationship between aesthetic appreciation and environmental values remains a critical yet under-researched area in environmental psychology. Although the Two-Major Environmental Values (2-MEV) model--encompassing preservation and utilization dimensions--serves as a standard framework for assessing environmental attitudes, the integration of aesthetic perception within this structure has largely remained unexplored. This study investigates the conceptual linkages across a diverse international sample to determine whether aesthetic appreciation functions independently of a traditional environmental value framework. Methods and FindingsWe conducted a large-scale, cross-sectional survey involving 11,800 pre- and in-service teachers across 34 countries. Participants environmental values were evaluated using the 2-MEV scale, while their aesthetic appreciation of nature and the built environment was assessed using Osgoods semantic differential technique. Employing principal component analysis, hierarchical exploratory factor analysis (EFA), analysis of variance (ANOVA), and within-class analysis (WCA), we accounted for cross-national variations and evaluated response consistency. The results demonstrate that aesthetic appreciation comprises two distinct dimensions-- focusing separately on nature and the built environment--that operate independently of traditional preservation and utilization values, showing only weak correlations. Furthermore, while the overarching psychological structure remains consistent globally, our findings reveal significant cross-national variations in respondent scores, particularly concerning utilization-related values. ConclusionsThese findings establish that aesthetic appreciation constitutes a distinct psychological construct separate from conventional environmental value frameworks. The observed cross-cultural variability underscores the necessity of accounting for national and cultural contexts when designing environmental education programs. By leveraging a robust, comprehensive global dataset, this study provides a vital empirical foundation for integrating aesthetic and value-based dimensions into future environmental research and educational policy.

scientific communication and education↗

bioRxiv2026

Transitive reasoning as linear classification

Transitive inference (TI) is the ability to reason about transitive relationships in an ordered set of items (e.g., if A>B and B>C, then A>C). TI is widely held to depend on a linear representation of the serial (rank) order of those items. By what computational mechanism is such an ordering constructed during learning, and how is it used to make choices that obey transitivity? Here we take a minimalist approach, applying least-squares estimation (LSE) to a serial learning task commonly used to test TI in humans and animals. In this formulation, LSE computes a linear classifier that maps task conditions onto behavioral outcomes. This algorithm makes no explicit assumptions about transitivity or serial order, yet it reproduces key empirical features of TI; namely, the ability to generalize beyond the training set, and a symbolic distance effect (SDE) in performance accuracy. Applying the classifier to individual items produces an internally ordered representation of rank from which both generalization and the SDE naturally emerge. The approach also yields a decision mechanism, in the form of a differencing operation, for selecting the correct item from any pair. These findings reframe TI as a linear classification problem, challenging conventional assumptions about the cognitive mechanisms required for transitive reasoning.

neuroscience↗

bioRxiv2025

Island biogeography through the lens of multiscale metapopulation dynamics: insights into species-area relationships

While island biogeography focuses on species richness equilibrium driven by immigration and extinction, and metapopulation theory examines single-species dynamics across fragmented habitats, their interplay remains poorly understood. In particular, the species-area relationship remains a subject of ongoing debate, yet there are limited theoretical foundations to explain it. To address this, we developed a multiscale stochastic metapopulation model to investigate diversity patterns on islands, bridging the gap between island biogeography and metapopulation theory. Our model integrates regional colonization from a mainland with local colonization-extinction processes within islands at the single-species level, then extends this to multiple, independent species. By analyzing the stationary properties of this model, we generate novel predictions of Species Area Relationship (SAR) based on local extinction rates, within-island colonization rates, and mainland immigration rates. We demonstrate how the interplay of these parameters influences the relationship, predicting patterns that can resemble either the power-law of Arrhenius or the semi-logarithmic relationship of Gleason, depending on the relative importance of mainland immigration versus within-island dynamics, and on the nature of the species abundance distribution in the mainland. This unified framework offers new insights into the mechanisms driving species richness and distribution across spatial scales, providing a more holistic understanding of biodiversity patterns in fragmented landscapes.

ecology↗

bioRxiv2025

Lysine Potentiates Insulin Secretion via AASS-Dependent Catabolism and Regulation of GABA Content and Signaling

Background and aimLysine is an essential amino acid with insulinotropic effects in humans. In vitro, lysine also potentiates glucose-stimulated insulin secretion (GSIS) in {beta} cell lines and rodent pancreatic islets. For decades it has been assumed that insulinotropic action of lysine is mediated by plasma membrane depolarization similar to arginine. Aminoadipate-Semialdehyde Synthase (AASS) is a mitochondrial-located bifunctional enzyme engaged in the first two steps of the lysine catabolism. Whether AASS-dependent lysine catabolism occurs in {beta} cells and whether it is required for its insulinotropic action has not been investigated. MethodsmRNA expression of lysine catabolism pathway genes was assessed in human islets from non-diabetic (ND) and type 2 diabetes (T2D) subjects. AASS was silenced in human pancreatic islets and in INS1 832/13 {beta} cells. {beta} cell metabolism and function were investigated by ELISA, extracellular flux analysis, live cell calcium imaging, transcriptomics and metabolomics analyses. ResultsExpression of genes involved in lysine catabolism, including AASS, ALDH7A1, DHTKD1 and HADH, was reduced in pancreatic islets from T2D donors. Silencing of AASS resulted in reduced lysine- and glucose-stimulated insulin secretion in human islets and INS1 832/13 {beta} cells. Surprisingly, transcriptomics and metabolomics analysis in Aass-KD {beta} cells with suppressed lysine catabolism identified reduced {gamma}-aminobutyric acid (GABA)/glutamate ratio as well as altered expression of genes implicated in GABA metabolism. This was accompanied by altered mitochondrial TCA cycle and oxidative phosphorylation (OXPHOS) activity, reflected by elevated lactate/pyruvate and reduced whole-cell ATP/ADP content as well as ATP-linked mitochondrial respiration. Glucose-and GABA-stimulated cytosolic calcium was also altered in Aass-KD {beta} cells. Strikingly, addition of GABA recovered impaired insulin secretion in Aass-KD {beta} cells. ConclusionAASS-dependent lysine catabolism is required to maintain adequate GABA shunt metabolism and signaling. In addition, lysine catabolism supports mitochondrial energy production, calcium uptake and insulin secretion. Reduced AASS-dependent lysine catabolism may contribute to {beta} cell GABA depletion and dysfunction in T2D patients.

cell biology↗

bioRxiv2024

Natural disturbances and connectivity shape the seasonal variability of aquatic macroinvertebrate communities across Europe

Understanding the joint influence of natural disturbance, spatial connectivity and biogeography on biodiversity is essential to forecast its responses to climate change. Macroinvertebrate communities in drying river networks constitute an ideal study system to understand the interplay of these ecological processes. We analyze the taxonomic and functional structure of macroinvertebrate communities sampled across 126 reaches with perennial and intermittent streamflow, surveyed in six drying river networks (DRN) across Europe, six times over one year. Drying frequency decreased community richness and functional diversity of communities, whereas spatio-temporal connectivity increased community richness in intermittent reaches. Communities experiencing a high drying frequency increased the proportion of taxa with K-strategies and drying resistance traits. Communities experiencing a long drying duration compensated by high spatio-temporal connectivity had more taxa with a r-strategy and high dispersal ability. Perennial communities varied from taxa-poor communities of r-strategists in spring and autumn and taxa-rich communities of K-strategists in summer and had a constant functional diversity throughout the year. When drying frequency increased, communities showed a similar pattern except in autumn when they shifted towards species-poor communities of K-strategists. Functional diversity then peaked in summer. Community trait structure and in particular optimal drying resistance traits changed across biogeographical scales. It opposed communities from mountainous DRN (with more r-strategies and high dispersal ability) to non-mountainous DRN (with more K-strategies). Drying frequency, drying duration, and spatio-temporal connectivity drive divergent community structures, suggesting the presence of an ecological threshold that explains the variability of disturbed ecosystems across broad spatial scales. These factors also shaped seasonal community variations, particularly after summer, with intermittent communities influenced by stochastic recolonization events in spring and autumn. Spatial-temporal connectivity proved crucial for maintaining diversity in communities subjected to intense drying. Lastly, the effectiveness of drying resistance traits was dependent on the biogeographical and environmental conditions of drying river networks.

ecology↗

bioRxiv2024

Assessing the risk of highly pathogenic avian influenza H5 viruses spread within French broiler and layer production networks

Since 2015, French poultry production is threatened almost every year by a reintroduction of highly pathogenic avian influenza H5 viruses. The duck sector was the most concerned by this crisis but other sectors such as broiler, layer and turkey were also affected by outbreaks. The objective of this work was to assess the risk of highly pathogenic avian influenza H5 virus transmission from one farm to another within the French broiler and layer production network. This study used the WOAH risk assessment framework. After drawing up a scenario tree of virus transmission from one farm to another, data were collected through a literature review or through experts elicitation. Three questionnaires were developed according to the experts field of expertise: avian influenza, broiler and layer sectors. The experts estimates were combined using a beta distribution weighted by their confidence level. A Monte Carlo iteration process was used to combine the different probabilities of the scenario tree and to assess the transmission risk. In the broiler sector, the highest transmission probabilities were observed if the exposed farm was an indoor broiler farm and the source a broiler farm (indoor or free-range). The high transmission probability between broiler farms integrated within the same association suggests that integration is an important risk factor. Person movement, transport of feed and manure management were the pathways with the highest transmission probabilities between two integrated indoor broiler farms with good biosecurity levels. In the layer sector, the highest transmission probabilities were observed if the source farm was a free-range farm and the exposed farm a production farm (indoor or free-range). The pathways with the highest transmission probabilities were egg transport and person movement. The sensitivity analysis showed that the exposed farms biosecurity had a significant impact on the transmission probability. Our results provide an insight on the role of each type of farms in the virus spread within the French broiler and layer production sectors and will be useful for the implementation of control measures such as movement restriction or vaccination.

ecology↗

bioRxiv2023

Proteomic Analysis Reveals the Molecular Pathways Responsible for Solar UV-B Acclimation in High-altitude Malbec Berries

Grapevine cultivation at high altitudes provides a viable option for producing premium quality wines in the context of climate change. This is primarily attributed to cooler temperatures, wider thermal amplitudes, and increased UV-B radiation. Although high UV-B levels can cause oxidative-stress, grape berries acclimate by generating UV-blocking anthocyanins and antioxidant compounds accumulated in the berry skins, thereby enhancing the organoleptic qualities and aging capacity of wine. This UV-B exclusion study examines how Malbec berries respond to solar UV-B at a high-altitude vineyard in Mendoza, Argentina (1350 m a.s.l.). The results showed that high solar UV-B acts both as a photomorphogenic signal and a stressor. The proteomic changes of berries exposed to +UV-B conditions indicate a decrease of photosynthesis and oxidative phosphorylation, coupled with an increase of glycolysis and tricarboxylic acid cycle as compensatory respiration pathways. Furthermore, numerous chaperones and proteins associated with the antioxidant system exhibited increased abundance to maintain cellular homeostasis. Lastly, veraison-stage berries exposed to +UV-B displayed an activation of the UVR8 signaling cascade and the phenylpropanoid pathway, resulting in higher concentration of phenolic compounds and more oxidation-resistant types of anthocyanins. This is the first report of field-grown grape berry proteomic modulation in response to solar UV-B, and it may have significant implications for the cultivation of high-quality wine grapes in both current and future climate scenarios. Significance

plant biology↗

bioRxiv2023

Revealing Shared Proteins and Pathways in Cardiovascular and Cognitive Diseases Using Protein Interaction Network Analysis

One of the primary goals of systems medicine is detecting putative proteins and pathways involved in disease progression and pathological phenotypes. Vascular Cognitive Impairment (VCI) is a heterogeneous condition manifesting as cognitive impairment resulting from vascular factors. The precise mechanisms underlying this relationship remain unclear, which poses challenges for experimental research. Here, we applied computational approaches like systems biology to unveil and select relevant proteins and pathways related to VCI by studying the crosstalk between cardiovascular and cognitive diseases. In addition, we specifically included signals related to oxidative stress, a common etiologic factor tightly linked to aging, a major determinant of VCI. Our results show that pathways associated with oxidative stress are quite relevant, as most of the prioritized vascular-cognitive genes/proteins were enriched in these pathways. Our analysis provided a short list of proteins that could be contributing to VCI: DOLK, TSC1, ATP1A1, MAPK14, YWHAZ, CREB3, HSPB1, PRDX6, and LMNA. Moreover, our experimental results suggest a high implication of glycative stress, generating oxidative processes and post-translational protein modifications through advanced glycation end-products (AGEs). We propose that these products interact with their specific receptors (RAGE) and Notch signaling to contribute to the etiology of VCI.

systems biology↗

bioRxiv2022

Temporal variation of patch connectivity determines biodiversity recovery from recurrent disturbances

Understanding the capacity of ecological systems to withstand and recover from disturbances is a major challenge for ecological research in the context of environmental change. Disturbances have multi-scale effects: they can cause species extinctions locally and alter connectivity between habitat patches at the metacommunity level. Yet, our understanding of how disturbances influence landscape connectivity remains limited. To fill this gap, we develop a novel connectivity index that integrates the temporal variation of patch connectivity induced by disturbances, which can be applied to any spatially-structured habitat. We then combine this index with a metacommunity model to specifically investigate biodiversity recovery from drying events in river network metacommunities. We demonstrate that patch connectivity explains variations of species richness between groups of organisms with contrasting dispersal modes and captures the effect of drying intensity (i.e., fraction of patches that dry-up) and drying location on community recovery. As a general rule, loss of patch connectivity decreases community recovery, regardless of patch location in the river network, dispersal mode, or drying intensity. Local communities of flying organisms maintained higher patch connectivity in drying river networks compared to organisms with strictly aquatic dispersal, which explained the higher recovery capacity of this group from drying events. The general relationship between patch connectivity and community recovery we found can be applied to any spatial network subject to temporal variation of connectivity, thus providing a powerful tool for biodiversity management in dynamic landscapes.

ecology↗

bioRxiv2021

Long Term Study of Motivational and Cognitive Effects of Low-intensity Focused Ultrasound Neuromodulation in the Dorsal Striatum of Nonhuman Primates

Noninvasive brain stimulation using focused ultrasound (FUS) has many potential applications as a research and clinical tool, including incorporation into neural prosthetics for cognitive rehabilitation. To develop this technology, it is necessary to evaluate the safety and efficacy of FUS neuromodulation for specific brain targets and cognitive functions. It is also important to test whether repeated long-term application of FUS to deep brain targets improves or degrades behavioral and cognitive function. To this end, we investigated the effects of FUS in the dorsal striatum of nonhuman primates (NHP) performing a visual-motor decision-making task for small or large rewards. Over the course of 2 years, we performed 129 and 147 FUS applications, respectively, in two NHP. FUS (0.5 MHz @ 0.2 - 0.8 MPa) was applied to the putamen and caudate in both hemispheres to evaluate the effects on movement accuracy, motivation, decision accuracy, and response time. Sonicating the caudate or the putamen unilaterally resulted in modest but statistically significant improvements in motivation and decision accuracy, but at the cost of slower reaction times. The effects were dose (i.e., FUS pressure) and reward dependent. There was no effect on reaching accuracy, nor was there long-term behavioral impairment or neurological trauma evident on T1-weighted, T2-weighted, or susceptibility-weighted MRI scans. Sonication also resulted in significant changes in resting state functional connectivity between the caudate and multiple cortical regions. The results indicate that applying FUS to the dorsal striatum can positively impact the motivational and cognitive aspects of decision making. The capability of FUS to improve motivation and cognition in NHPs points to its therapeutic potential in treating a wide variety of human neural diseases, and warrants further development as a novel technique for non-invasive deep brain stimulation.

neuroscience↗

bioRxiv2019

Neuronal responses in posterior parietal cortex during learning of implied serial order

Monkeys are able to learn the implied ordering of pairs of images drawn from an ordered set, without ever seeing all of the images simultaneously and without explicit spatial or temporal cues. The learning of implied order differs from learning of explicit visual or motor sequences. We recorded the activity of parietal neurons in rhesus macaques while they learned 7-item TI lists when only 2 items were presented on each trial. Behavior and ensemble neuronal activity were significantly influenced by the ordinal relationship of the stimulus pairs, specifically symbolic distance (the difference in rank) and joint ranks (the sum of the ranks). Symbolic distance strongly predicted decision accuracy, and learning was consistently faster as symbolic distance increased. An effect of joint rank on performance was also found nested within the symbolic distance effect. Across the population of neurons, there was significant modulation of firing correlated with the relative ranks of the two stimuli presented on each trial. Neurons exhibited selectivity for stimulus rank during learning, but not before or after. The observed behavior during learning is best explained by a virtual workspace model, not by associative or reward mechanisms. The neural data support a role for posterior parietal cortex in representing several variables that contribute to serial learning, particularly information about the ordinal ranks of the stimuli presented during a given trial. Thus, parietal cortex appears to belong to a neural substrate for learning and representing abstract relationships in a virtual workspace.

neuroscience↗

bioRxiv2019

Distinguishing the signatures of local environmental filtering and regional trait range limits in the study of trait-environment relationships

Understanding the imprint of environmental filtering on community assembly along environmental gradients is a key objective of trait-gradient analyses. Depending on local constraints, this filtering generally entails that species departing from an optimum trait value have lower abundances in the community. The Community-Weighted Mean (CWM) and Variance (CWV) of trait values are then expected to depict the optimum and intensity of filtering, respectively. However, the trait distribution within the regional species pool and its limits can also affect local CWM and CWV values apart from the effect of environmental filtering. The regional trait range limits are more likely to be reached in communities at the extremes of environmental gradients. Analogous to the mid-domain effect in biogeography, decreasing CWV values in extreme environments can then represent the influence of regional trait range limits rather than stronger filtering in the local environment. We name this effect the "Trait-Gradient Boundary Effect" (TGBE). First, we use a community assembly framework to build simulated communities along a gradient from a species pool and environmental filtering with either constant or varying intensity while accounting for immigration processes. We demonstrate the significant influence of TGBE, in parallel to environmental filtering, on CWM and CWV at the extremes of the environmental gradient. We provide a statistical tool based on Approximate Bayesian Computation to decipher the respective influence of local environmental filtering and regional trait range limits. Second, as a case study, we reanalyze the functional composition of alpine plant communities distributed along a gradient of snow cover duration. We show that leaf trait convergence found in communities at the extremes of the gradient reflect an influence of trait range limits rather than stronger environmental filtering. These findings challenge correlative trait-environment relationships and call for more explicitly identifying the mechanisms responsible of trait convergence/divergence along environmental gradients.

ecology↗

bioRxiv2018

Assessing metacommunity processes through signatures in spatiotemporal turnover of community composition

Although metacommunity ecology has been a major field of research in the last decades, with both conceptual and empirical outputs, the analysis of the temporal dynamics of metacommunities has only emerged recently and consists mostly of repeated static analyses. Here, we propose a novel analytical framework to assess metacommunity processes using path analyses of spatial and temporal diversity turnovers. We detail the principles and practical aspects of this framework and apply it to simulated datasets to illustrate its ability to decipher the respective contributions of entangled drivers of metacommunity dynamics. We then apply it to four empirical datasets. Empirical results support the view that metacommunity dynamics may be generally shaped by multiple ecological processes acting in concert, with environmental filtering being variable across both space and time. These results reinforce our call to go beyond static analyses of metacommunities that are blind to the temporal part of environmental variability.

ecology↗

bioRxiv2018

Deciphering hybrid larch reaction norms using random regression

The link between phenotypic plasticity and heterosis is a broad fundamental question, with stakes in breeding. We report a case-study evaluating temporal series of wood ring traits of hybrid larch (Larix decidua x L. kaempferi and reciprocal) in relation to soil water availability. Growth rings record the tree plastic responses to past environmental conditions, and we used random regressions to estimate the reaction norms of ring width and wood density with respect to water availability. We investigated the role of phenotypic plasticity on the construction of hybrid larch heterosis and on the expression of its quantitative genetic parameters. The data came from an intra-/interspecific diallel mating design between both parental species. Progenies were grown in two environmentally contrasted sites, in France. Ring width plasticity with respect to water availability was confirmed, as all three taxa produced narrower rings under the lowest water availability. Hybrid larch appeared to be the most plastic taxon as its superiority over its parental species increased with increasing water availability. Despite the low heritabilities of the investigated traits, we found that the quantitative genetic parameters varied along the water availability gradient. Finally, by means of a complementary simulation, we demonstrated that random regression can be applied to model the reaction norms of non-repeated records of phenotypic plasticity bound by a family structure. Random regression is a powerful tool for the modeling of reaction norms in various contexts, especially perennial species.

genetics↗