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Our understanding of how cis-regulatory elements work has advanced rapidly, outpacing our evolutionary models. In this review, we consider the implications of new mechanistic findings for evolutionary developmental biology. We focus on three different debates: whether evolutionary innovation occurs more often via the modification of old cis-regulatory elements or the emergence of new ones; the extent to which individual elements are specific and autonomous or multifunctional and interdependent; and how the robustness of cis-regulatory architectures influences the rate of trait evolution. These discussions lead us to propose new questions for the evo-devo of cis-regulation.

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Improving the connectivity of ecological networks (ENs) is a proven strategy for biological conservation. However, without a clear understanding of animal movement, research on ENs may not provide a sufficient reference for maintaining biodiversity. To address this gap, we embraced central concepts of movement ecology and conducted a study in the Qilian Mountains. The predictability and seasonality of environmental conditions were combined to identify ecological sources with rich temporal niches and improve the informed preference character of resistance surface. Then, we constructed ENs with six dispersal thresholds. Further, integrating modularity and circuit theory, we pinpointed priority areas for restoration within the ENs. Our findings indicated that the eastern part of the Qilian Mountains showed higher biodiversity suitability, with terrain being the primary factor limiting dispersal. Additionally, comparative analyses demonstrate that the new method for measuring biodiversity from the perspective of temporal niche is reliable and better aligns with the needs of biodiversity conservation. In light of emerging challenges within the study area, where apex predators seriously suppress the populations of some smaller predators, we propose a novel conservation idea that emphasizes the strategic retention and removal of barriers to maintain biological balance. This study enriches methodologies for biodiversity measurement, provides forward-looking conservation strategies, and offers practical contributions toward mitigating biodiversity loss.

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Alzheimer's disease (AD) has been conceptualized as a syndrome of brain network dysfunction. Recent imaging connectomics studies have provided unprecedented opportunities to map structural and functional brain networks in AD. By reviewing molecular, imaging, and computational modeling studies, we have shown that highly connected brain hubs are primarily distributed in the medial and lateral prefrontal, parietal, and temporal regions in healthy individuals and that the hubs are selectively and severely affected in AD as manifested by increased amyloid-beta deposition and regional atrophy, hypo-metabolism, and connectivity dysfunction. Furthermore, AD-related hub degeneration depends on the imaging modality with the most notable degeneration in the medial temporal hubs for morphological covariance networks, the prefrontal hubs for structural white matter networks, and in the medial parietal hubs for functional networks. Finally, the AD-related hub degeneration shows metabolic, molecular, and genetic correlates. Collectively, we conclude that the brain-network-hub-degeneration framework is promising to elucidate the biological mechanisms of network dysfunction in AD, which provides valuable information on potential diagnostic biomarkers and promising therapeutic targets for the disease.

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Urban pluvial floods pose a significant risk to cities, occurring when precipitation exceeds the carrying capacity of the urban drainage network. Coupled green-grey infrastructure has emerged as a sustainable solution for mitigating urban pluvial floods. This study aims to explore best practices in the network configuration of urban drainage systems coupled with low-impact development (LID) to enhance flow distribution and stormwater infiltration. To do so, we focused on two competing key concepts in network analysis: (1) Centralization and (2) Decentralization. We integrated a one-dimensional stormwater model with a rapid flood spreading model to assess the flood mitigation performance of various centralized and decentralized network configurations in the Gangnam region of Seoul, South Korea. To further assess the combined effects of green and grey infrastructure, we compared the performance of each drainage network configuration with and without identical mixed LID practices. Here we show that the centralized drainage network scenario performed best in reducing flood volume by 40.3%, the decentralized drainage network scenario performed best in shortening flood duration by 47.8%, and the LID practices scenario performed best in mitigating peak flooding rates by 4.2%, each as independent scenarios. When all three scenarios were coupled together, flood volume could be reduced by 73.5%, flood duration by 54.7%, and peak flooding rates by 19.8% in the study area. This exploratory study underscores the potential of network analysis in urban flood research, particularly the effectiveness of loosely-connected network topology. Our findings contribute to the development of best practices for coupled green-grey infrastructure, facilitating sustainable stormwater management and urban flood resilience.

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Oscillatory complex networks in the metastable regime have been used to study the emergence of integrated and segregated activity in the brain, which are hypothesised to be fundamental for cognition. Yet, the parameters and the underlying mechanisms necessary to achieve the metastable regime are hard to identify, often relying on maximising the correlation with empirical functional connectivity dynamics. Here, we propose and show that the brain's hierarchically modular mesoscale structure alone can give rise to robust metastable dynamics and (metastable) chimera states in the presence of phase frustration. We construct unweighted 3-layer hierarchical networks of identical Kuramoto-Sakaguchi oscillators, parameterized by the average degree of the network and a structural parameter determining the ratio of connections between and within blocks in the upper two layers. Together, these parameters affect the characteristic timescales of the system. Away from the critical synchronization point, we detect the emergence of metastable states in the lowest hierarchical layer coexisting with chimera and metastable states in the upper layers. Using the Laplacian renormalization group flow approach, we uncover two distinct pathways towards achieving the metastable regimes detected in these distinct layers. In the upper layers, we show how the symmetry-breaking states depend on the slow eigenmodes of the system. In the lowest layer instead, metastable dynamics can be achieved as the separation of timescales between layers reaches a critical threshold. Our results show an explicit relationship between metastability, chimera states, and the eigenmodes of the system, bridging the gap between harmonic based studies of empirical data and oscillatory models.

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Despite converging evidence of hierarchical organization in the cerebral cortex, with sensory-motor and association regions at opposite ends, the mechanism of such hierarchical interactions remains elusive. This organization was primarily investigated regarding the spatiotemporal dynamics of intrinsic connectivity networks (ICNs). However, more effort is needed to investigate network dynamics in the frequency domain. We aimed to examine the integrative role of brain regions in the frequency domain with graph metrics. Phase-based connectivity estimation was performed in three frequency bands (0.011-0.038, 0.043-0.071, and 0.076-0.103 Hz) in the BOLD signal during rest. We applied modularity analysis to connectivity matrices and investigated those areas, which we called integrative regions, that showed frequency-domain flexibility. Integrative regions, mostly belonging to attention networks, were densely connected to higher-order cognitive ICNs in lower frequency bands but to sensory-motor ICNs in higher frequency bands. We compared the normalized participation coefficient (Pnorm) values of integrative and core regions with respect to their relation to higher-order cognition using a permutation-based t-test for multiple linear regression. Regression parameters of integrative regions in relation to three cognitive scores in executive functions, and working memory were significantly larger than those of core regions (Pfdr < 0.05) for salience ventral attention network. Parameters of integrative regions in relation to intelligence scores were significantly larger than those with core regions (Pfdr < 0.05) in dorsal attention network. Larger parameters of neuropsychological test scores in relation to these flexible parcels further indicate their essential role at an intermediate level in behavior. Results emphasize the importance of frequency-band analysis of brain networks.

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BACKGROUND: Modular acetabular components for total hip arthroplasty (THA) provide intraoperative flexibility; however, polyethylene liner dissociation may occur. This study aimed to examine the incidence and causes of liner dissociation associated with a specific acetabular component design at a single centre. MATERIALS AND METHODS: A retrospective analysis of 7027 patients who underwent primary THA was performed to identify isolated liner dislocations. Patient demographics, clinical presentations, surgical and implant details, and both radiographic and computed tomography (CT) findings were analysed. Patients with liner dislocation were matched to a control group via 2:1 propensity score matching, and a logistic regression analysis was employed to identify associated risk factors. RESULTS: A total of 32 patients (0.45%) experienced liner dislocation at a mean 71.47 ± 60.10 months post surgery. Significant factors contributing to dislocations included the use of a conventional compared with a highly crosslinked polyethylene component (p = 0.049) and screw fixation (p = 0.028). Radiographic and CT analysis highlighted the importance of proper component orientation, revealing that patients experiencing dislocations demonstrated significantly lower acetabular cup anteversion angles (p = 0.001) compared with the control group. Impingement and malposition, identified in 41% and 47% of the cases, respectively, further underscored the multifactorial nature of dislocation risks. CONCLUSIONS: While the overall rate of polyethylene liner dislocation was low, the findings of this study highlight the importance of appropriate cup placement to decrease the risk of dissociation. It further substantiates the influence of impingement and malposition in liner displacement, with increased mechanical stress exerted on the locking mechanism under adverse conditions and the potential risk increase due to screw placement.

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Mammalian functional architecture flexibly adapts, transitioning from integration where information is distributed across the cortex, to segregation where information is focal in densely connected communities of brain regions. This flexibility in cortical brain networks is hypothesized to be driven by control signals originating from subcortical pathways, with the basal ganglia shifting the cortex towards integrated processing states and the cerebellum towards segregated states. In a sample of healthy human participants (N=242), we used fMRI to measure temporal variation in global brain networks while participants performed two tasks with similar cognitive demands (Stroop and Multi-Source Inference Task (MSIT)). Using the modularity index, we determined cortical networks shifted from integration (low modularity) at rest to high modularity during easier i.e. congruent (segregation). Increased task difficulty (incongruent) resulted in lower modularity in comparison to the easier counterpart indicating more integration of the cortical network. Influence of basal ganglia and cerebellum was measured using eigenvector centrality. Results correlated with decreases and increases in cortical modularity respectively, with only the basal ganglia influence preceding cortical integration. Our results support the theory the basal ganglia shifts cortical networks to integrated states due to environmental demand. Cerebellar influence correlates with shifts to segregated cortical states, though may not play a causal role.

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Background and Objective: Knee replacement following anterior cruciate ligament (ACL) reconstruction can be demanding due to altered anatomy, soft tissue scars, bone loss, extensor mechanism complications, and knee instability. This narrative review summarizes the strategies and approaches to managing operative challenges in total knee arthroplasty (TKA) following ACL reconstruction. Methods: Studies reporting outcomes of patients who underwent TKA after ACL reconstruction were retrieved and assessed to be included in this review that synthesizes the available evidence highlighting the pitfalls encountered during surgery, the intraoperative challenges posed by ligament balancing and exposure, and the leading role of modular and retained implants. Key Content and Findings: TKA following ACL reconstruction has a high rate of intra-operative complications such as instability, bone loss, difficult exposure and demanding soft tissue balancing, representing a revision surgery rather than routine primary knee arthroplasty and a revision-oriented skill set and modular components are recommended to significantly optimize both surgical strategy and patient outcomes. With a rising incidence of ACL injuries and growing reconstructions, anticipating an increase in TKA procedures, this review aims to provide a call for rethinking clinical approaches to ensure effective and patient-centric care. Conclusions: This narrative review seems to indicate that TKA after ACL reconstruction should be considered as revision surgery and modular components should be used. However, future prospective and high-quality studies are required to better clarify risk factors and give strong recommendations for this complex surgery.

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Eye size affects many aspects of visual function, but eyes are costly to grow and maintain. The allometry of eyes can provide insight into this trade-off, but this has mainly been explored in species that have two eyes of equal size. By contrast, animals possessing larger visual systems can exhibit variable eye sizes within individuals. Spiders have up to four pairs of eyes whose sizes vary dramatically, but their ontogenetic, static, and evolutionary allometry has not yet been studied in a comparative context. We report variable dynamics in eye size across 1,098 individuals in 39 species and 8 families, indicating selective pressures and constraints driving the evolution of different eye pairs and lineages. Supplementing our sampling with a recently published phylogenetically comprehensive dataset, we confirmed these findings across more than 400 species; found that ecological factors such as visual hunting, web building, and circadian activity correlate with eye diameter; and identified significant allometric shifts across spider phylogeny using an unbiased approach, many of which coincide with visual hunting strategies. The modular nature of the spider visual system provides additional degrees of freedom and is apparent in the strong correlations between maximum/minimum investment and interocular variance and three key ecological factors. Our analyses suggest an antagonistic relationship between the anterior and posterior eye pairs. These findings shed light on the relationship between spider visual systems and their diverse ecologies and how spiders exploit their modular visual systems to balance selective pressures and optical and energetic constraints.

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Background: Machine learning (ML) prediction models in healthcare and pharmacy-related research face challenges with encoding high-dimensional Healthcare Coding Systems (HCSs) such as ICD, ATC, and DRG codes, given the trade-off between reducing model dimensionality and minimizing information loss. Objectives: To investigate using Network Analysis modularity as a method to group HCSs to improve encoding in ML models. Methods: The MIMIC-III dataset was utilized to create a multimorbidity network in which ICD-9 codes are the nodes and the edges are the number of patients sharing the same ICD-9 code pairs. A modularity detection algorithm was applied using different resolution thresholds to generate 6 sets of modules. The impact of four grouping strategies on the performance of predicting 90-day Intensive Care Unit readmissions was assessed. The grouping strategies compared: 1) binary encoding of codes, 2) encoding codes grouped by network modules, 3) grouping codes to the highest level of ICD-9 hierarchy, and 4) grouping using the single-level Clinical Classification Software (CCS). The same methodology was also applied to encode DRG codes but limiting the comparison to a single modularity threshold to binary encoding.The performance was assessed using Logistic Regression, Support Vector Machine with a non-linear kernel, and Gradient Boosting Machines algorithms. Accuracy, Precision, Recall, AUC, and F1-score with 95% confidence intervals were reported. Results: Models utilized modularity encoding outperformed ungrouped codes binary encoding models. The accuracy improved across all algorithms ranging from 0.736 to 0.78 for the modularity encoding, to 0.727 to 0.779 for binary encoding. AUC, recall, and precision also improved across almost all algorithms. In comparison with other grouping approaches, modularity encoding generally showed slightly higher performance in AUC, ranging from 0.813 to 0.837, and precision, ranging from 0.752 to 0.782. Conclusions: Modularity encoding enhances the performance of ML models in pharmacy research by effectively reducing dimensionality and retaining necessary information. Across the three algorithms used, models utilizing modularity encoding showed superior or comparable performance to other encoding approaches. Modularity encoding introduces other advantages such as it can be used for both hierarchical and non-hierarchical HCSs, the approach is clinically relevant, and can enhance ML models' clinical interpretation. A Python package has been developed to facilitate the use of the approach for future research.

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Breast cancer, characterized by its complexity and diversity, presents significant challenges in understanding its underlying biology. In this study, we employed gene co-expression network analysis to investigate the gene composition and functional patterns in breast cancer subtypes and normal breast tissue. Our objective was to elucidate the detailed immunological features distinguishing these tumors at the transcriptional level and to explore their implications for diagnosis and treatment. The analysis identified nine distinct gene module clusters, each representing unique transcriptional signatures within breast cancer subtypes and normal tissue. Interestingly, while some clusters exhibited high similarity in gene composition between normal tissue and certain subtypes, others showed lower similarity and shared traits. These clusters provided insights into the immune responses within breast cancer subtypes, revealing diverse immunological functions, including innate and adaptive immune responses. Our findings contribute to a deeper understanding of the molecular mechanisms underlying breast cancer subtypes and highlight their unique characteristics. The immunological signatures identified in this study hold potential implications for diagnostic and therapeutic strategies. Additionally, the network-based approach introduced herein presents a valuable framework for understanding the complexities of other diseases and elucidating their underlying biology.

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PURPOSE: Modular cementless knee arthroplasty systems are capable of precise reconstruction of the mechanical axis. However, they are considered more susceptible to complications. In contrast, non-modular cemented systems are said to be more forgiving and show good long-term results. The aim of this study was to investigate the resulting leg axis after implantation of a non-modular cemented rotating hinged knee prosthesis. Furthermore, potential risk factors for the occurrence of malalignment and complications should be identified. METHODS: Between 2005 and 2015, 115 patients could be included in this monocentric retrospective cohort study. All patients underwent primary hinged non-modular cemented total knee arthroplasty. Preoperative and postoperative standardized long radiographs were analysed to determine resulting leg axis. Furthermore, epidemiological and intraoperative data as well as perioperative complications were surveyed. RESULTS: Average leg axis was 5.8° varus preoperatively and 0.6° valgus postoperatively. Considering an axis deviation of 3° as the target corridor, 27% of all cases examined were outside the desired range. 21% cases showed a femoral deviation from the target corridor and 15% showed a tibial deviation. There was a significant relationship between the preoperative mLDFA and the mechanical alignment of the femoral component (R = 0.396, p < 0.001) as well as between the preoperative mMPTA and the mechanical alignment of the tibial component (R = 0.187, p = 0.045). The mean operative duration was 96 min. No periprosthetic fractures were observed within the study cohort. CONCLUSION: The main result of the present work is that a non-modular cemented rotating hinged knee arthroplasty system can reconstruct the mechanical leg axis precisely and comparable to modular cementless and unconstrained total knee prostheses. Component malalignment is primarily dependent upon extraarticular deformity preoperatively. Periprosthetic fracture rates and duration of surgery were lower compared with current literature. LEVEL OF EVIDENCE: Level III: Retrospective cohort study.

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The shared functions of the skull are thought to result in common evolutionary patterns in mammalian cranial shape. Craniofacial evolutionary allometry (CREA) is a particularly prominent pattern where larger species display proportionally elongate facial skeletons and smaller braincases. It was recently proposed that CREA arises from biomechanical effects of cranial scaling when diets are similar. Thus, deviations from CREA should occur with changes in cranial biomechanics, for example due to dietary change. Here, we test this using 3D geometric morphometric analysis in a dataset of Australian murine crania, which are highly allometric. We contrast allometric and non-allometric variation in the cranium by comparing evolutionary mode, allometry, ordinations, as well as allometry, integration, and modularity in functional modules. We found evidence of stabilising selection in allometry-containing and size-free shape, and substantial non-allometric variation aligned with dietary specialisation in parallel with CREA. Integration among cranial modules was higher, and modularity lower, with size included, but integration between rostrum and cranial vault, which are involved in the CREA pattern, dropped dramatically after size removal. Our results thus support the hypothesis that CREA is a composite arising from selection on cranial function, with substantial non-allometric shape variation occurring alongside CREA where dietary specialisation impacts selection on gnawing function. This emphasises the need to research mammalian cranial evolution in the context of allometric and non-allometric selection on biomechanical function.

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Spatial interactions among anatomical elements help to identify topological factors behind morphological variation and can be investigated through network analysis. Here, a whole-brain network model of the chimpanzee (Pan troglodytes, Blumenbach 1776) is presented, based on macroanatomical divisions, and compared with a previous equivalent model of the human brain. The goal was to contrast which regions are essential in the geometric balance of the brains of the two species, to compare underlying phenotypic patterns of spatial variation, and to understand how these patterns might have influenced the evolution of human brain morphology. The human and chimpanzee brains share morphologically complex inferior-medial regions and a topological organization that matches the spatial constraints exerted by the surrounding braincase. These shared topological features are interesting because they can be traced back to the Chimpanzee-Human Last Common Ancestor, 7-10 million years ago. Nevertheless, some key differences are found in the human and chimpanzee brains. In humans, the temporal lobe, particularly its deep and medial limbic aspect (the parahippocampal gyrus), is a crucial node for topological complexity. Meanwhile, in chimpanzees, the cerebellum is, in this sense, more embedded in an intricate spatial position. This information helps to interpret brain macroanatomical change in fossil hominids.

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Greater physical activity and better sleep are associated with reduced risk of cognitive decline and dementia among older adults, but little is known about their combined associations with measures of brain function and neuropathology. This study investigated potential independent and interactive cross-sectional relationships between actigraphy-estimated total volume of physical activity (TVPA) and sleep patterns [i.e., total sleep time (TST), sleep efficiency (SE)] with resting-state functional magnetic resonance imaging (rs-fMRI) measures of large scale network connectivity and positron emission tomography (PET) measures of amyloid-ß. Participants were 135 non-demented older adults from the BIOCARD study (116 cognitively normal and 19 with mild cognitive impairment; mean age = 70.0 years). Using multiple linear regression analyses, we assessed the association between TVPA, TST, and SE with connectivity within the default-mode, salience, and fronto-parietal control networks, and with network modularity, a measure of network segregation. Higher TVPA and SE were independently associated with greater network modularity, although the positive relationship of SE with modularity was only present in amyloid-negative individuals. Additionally, higher TVPA was associated with greater connectivity within the default-mode network, while greater SE was related to greater connectivity within the salience network. In contrast, longer TST was associated with lower network modularity, particularly among amyloid-positive individuals, suggesting a relationship between longer sleep duration and greater network disorganization. Physical activity and sleep measures were not associated with amyloid positivity. These data suggest that greater physical activity levels and more efficient sleep may promote more segregated and potentially resilient functional networks and increase functional connectivity within specific large-scale networks and that the relationship between sleep and functional networks connectivity may depend on amyloid status.

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The adaptive potential of plastic phenotypes relies on combined developmental responses. We investigated how manipulation of developmental conditions related to foraging mode in the fish Megaleporinus macrocephalus induces plastic responses at different levels: (a) functional modularity of skull bones, (b) biomechanical properties of the chondrocranium using finite element models, (c) bmp4 expression levels, used as a proxy for molecular pathways involved in bone responses to mechanical load. We identified new modules in experimental groups, suggesting increased integration in specific head bone elements associated with the development of subterminal and upturned mouths, which are major features of Megaleporinus plastic morphotypes released in the lab. Plastic responses in head shape involved differences in the magnitude of mechanical stress, which seem restricted to certain chondrocranium regions. Three bones represent a "mechanical unit" related to changes in mouth position induced by foraging mode, suggesting that functional modularity might be enhanced by the way specific regions respond to mechanical load. Differences in bmp4 expression levels between plastic morphotypes indicate associations between molecular signaling pathways and biomechanical responses to load. Our results offer a multilevel perspective of epigenetic factors involved in plastic responses, expanding our knowledge about mechanisms of developmental plasticity that originate novel complex phenotypes.

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Metacommunity processes have the potential to determine most features of the community structure. However, species diversity has been the dominant focus of studies. Nestedness, modularity and checkerboard distribution of species occurrences are main components of biodiversity organisation. Within communities, these patterns emerge from the interaction between functional diversity, spatial heterogeneity and resource availability. Additionally, the connectivity determines the pool of species for community assembly and, eventually, the pattern of species co-occurrence within communities. Despite the recognised theoretical expectations, the change in occurrence patterns within communities along ecological gradients has seldom been considered. Here, we analyse the spatial occurrence of animal species along sampling units within 18 temporary ponds and its relationship with pond environments and geographic isolation. Isolated ponds presented a nested organisation of species with low spatial segregation-modularity and checkerboard-and the opposite was found for communities with high connectivity. A pattern putatively explained by high functional diversity in ponds with large connectivity and heterogeneity, which determines that species composition tracks changes in microhabitats. On the contrary, nestedness is promoted in dispersal-limited communities with low functional diversity, where microhabitat filters mainly affect richness without spatial replacement between functional groups. Vegetation biomass promotes nestedness, probably due to the observed increase in spatial variance in biomass with the mean biomass. Similarly, the richness of vegetation reduced the spatial segregation of animals within communities. This result may be due to the high plant diversity of the pond that is observed similarly along all sampling units, which promotes the spatial co-occurrence of species at this scale. In the study system, the spatial arrangement of species within communities is related to local drivers as heterogeneity and metacommunity processes by means of dispersal between communities. Patterns of species co-occurrence are interrelated with community biodiversity and species interactions, and consequently with most functional and structural properties of communities. These results indicate that understanding the interplay between metacommunity processes and co-occurrence patterns is probably more important than previously thought to understand biodiversity assembly and functioning.

Los procesos metacomunitarios tienen el potencial de determinar la mayoría de las características de la estructura de las comunidades. Sin embargo, los trabajos se han enfocado principalmente en los patrones de diversidad de especies. El anidamiento, la modularidad y la distribución en damero de la ocurrencia espacial de las especies son propiedades básicas de las comunidades. Estos patrones surgen de la interacción entre la diversidad funcional, la heterogeneidad espacial y la disponibilidad de recursos dentro de las comunidades. Además, el pool de especies disponibles para el ensamblaje está determinado por la conectividad de la comunidad, afectando así su patrón de co­ocurrencia de especies. A pesar de las reconocidas expectativas teóricas, el cambio en los patrones de ocurrencia dentro de las comunidades a lo largo de gradientes ecológicos ha sido poco considerado. Aquí, analizamos la ocurrencia espacial de especies animales dentro de 18 charcos temporales y su relación con las características ambientales y el aislamiento geográfico de los charcos. Los charcos aislados presentaron alto anidamiento espacial mientras que los charcos de alta conectividad una distribución de ocurrencias modular y en damero. Por un lado, la baja diversidad funcional en charcos aislados, determinaría que los filtros microambientales afecten la riqueza de especies sin reemplazo espacial entre grupos funcionales, promoviendo un arreglo anidado de ocurrencias. Por otro lado, la alta diversidad funcional en charcos con alta conectividad y heterogeneidad permitiría el reemplazo espacial de especies en gradientes microambientales, determinando los patrones de segregación observados. La biomasa vegetal promueve el anidamiento, probablemente debido al aumento observado en la variación espacial de la biomasa con la biomasa media. La riqueza vegetal también redujo la segregación espacial de los animales dentro de las comunidades. Este resultado puede deberse a que la alta diversidad de plantas de los charcos es también observada a nivel de unidades muestreales, favoreciendo esto la coexistencia espacial de especies. El arreglo espacial de especies dentro de las comunidades estudiadas estaría determinado tanto por factores locales como la heterogeneidad, como por procesos regionales operando a través de la dispersión de individuos entre comunidades. Los patrones de co­ocurrencia de especies están interrelacionados con la diversidad comunitaria y las interacciones bióticas, y consecuentemente con la mayoría de las propiedades estructurales y funcionales de las comunidades. Este estudio evidencia la importancia de la conexión entre procesos metacomunitarios y la co­ocurrencia espacial de especies para comprender el ensamblaje y funcionamiento de la biodiversidad.

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Introduction: This study aims to use diffusion tensor imaging (DTI) in conjunction with brain graph techniques to define brain structural connectivity and investigate its association with personal income (PI) in individuals of various ages and intelligence quotients (IQ). Methods: MRI examinations were performed on 55 male subjects (mean age: 40.1 ± 9.4 years). Graph data and metrics were generated, and DTI images were analyzed using tract-based spatial statistics (TBSS). All subjects underwent the Wechsler Adult Intelligence Scale for a reliable estimation of the full-scale IQ (FSIQ), which includes verbal comprehension index, perceptual reasoning index, working memory index, and processing speed index. The performance score was defined as the monthly PI normalized by the age of the subject. Results: The analysis of global graph metrics showed that modularity correlated positively with performance score (p = 0.003) and negatively with FSIQ (p = 0.04) and processing speed index (p = 0.005). No significant correlations were found between IQ indices and performance scores. Regional analysis of graph metrics showed modularity differences between right and left networks in sub-cortical (p = 0.001) and frontal (p = 0.044) networks. TBSS analysis showed greater axial and mean diffusivities in the high-performance group in correlation with their modular brain organization. Conclusion: This study showed that PI performance is strongly correlated with a modular organization of brain structural connectivity, which implies short and rapid networks, providing automatic and unconscious brain processing. Additionally, the lack of correlation between performance and IQ suggests a reduced role of academic reasoning skills in performance to the advantage of high uncertainty decision-making networks.

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The human brain's complex morphology is spatially constrained by numerous intrinsic and extrinsic physical interactions. Spatial constraints help to identify the source of morphological variability and can be investigated by employing anatomical network analysis. Here, a model of human craniocerebral topology is presented, based on the bony elements of the skull at birth and a previously designed model of the brain. The goal was to investigate the topological components fundamental to the craniocerebral geometric balance, to identify underlying phenotypic patterns of spatial arrangement, and to understand how these patterns might have influenced the evolution of human brain morphology. Analysis of the craniocerebral network model revealed that the combined structure of the body and lesser wings of the sphenoid bone, the parahippocampal gyrus, and the parietal and ethmoid bones are susceptible to sustain and apply major spatial constraints that are likely to limit or channel their morphological evolution. The results also showcase a high level of global integration and efficient diffusion of biomechanical forces across the craniocerebral system, a fundamental aspect of morphological variability in terms of plasticity. Finally, community detection in the craniocerebral system highlights the concurrence of a longitudinal and a vertical modular partition. The former reflects the distinct morphogenetic environments of the three endocranial fossae, while the latter corresponds to those of the basicranium and calvaria.