Miracle-dz/UniFAR-FTUs huggingface dataset:
Spatio-temporal analysis at landscape scale of the Iberian oak decline epidemic caused by Phytophthora cinnamomi

Phytophthora cinnamomi Rands is considered a main factor behind the Iberian oak decline (IOD). This epidemic is decimating Holm oaks (Quercus ilex L.) and cork oaks (Quercus suber L.) which are the keystone trees of a multipurpose, silvo-pastoral and semi-natural ecosystem of 3.1 million hectares in the south west of Europe. Forest diseases are characterized by pronounced spatial patterns, since many of the underlying ecological processes are inherently spatial. To improve the current understanding of such processes, we carried out a complete census of diseased sites via aerial imagery at landscape scale at four different dates over a period of 35 years. We validated our photographic interpretation of P. cinnamomi presence in-situ by subsampling soil and roots of diseased sites. To analyse the role of host population heterogeneities in shaping the spread of IOD, we used a ‘self-exciting’ spatio-temporal point process model. Its so-called epidemic component represents the inoculum pressure arising from nearby foci whereas its background component allows for sporadic infections from unobserved sources or disease transmission over larger distances. The best fit was obtained with a lagged power-law for the spatial dispersal kernel, where 49% of the infections triggered by an infected site occur within a distance of 250 meters. Both risk components were found to increase over time. The rate of sporadic infections appeared to be significantly lower in silvo-pastoral systems (dehesas) than in forests and higher in mixed stands and shrub encroached oak-lands. These results may have direct implications for IOD management, for example, the estimated spatial dispersal function helps to define a suitable target area for more efficient control measures. Our results also suggest that silviculture treatments aimed at controlling the density and species composition of oak stands, as well as the abundance of shrubs, could play a key role for disease management
Non-invasive surveys of mammalian viruses using environmental DNA

Environmental DNA (eDNA) and invertebrate-derived DNA (iDNA) have been used to survey biodiversity non-invasively to mitigate difficulties of obtaining wildlife samples, particularly in remote areas or for rare species. Recently, eDNA/iDNA have been applied to monitor known wildlife pathogens, however, most wildlife pathogens are unknown and often evolutionarily divergent. To detect and identify known and novel mammalian viruses from eDNA/iDNA sources, we used a curated set of RNA oligonucleotides as viral baits in a hybridization capture system coupled with high throughput sequencing. We detected multiple known and novel mammalian RNA and DNA viruses from multiple viral families from both waterhole eDNA and leech derived iDNA. Congruence was found between detected hosts and viruses identified in leeches and waterholes. Our results demonstrate that eDNA/iDNA samples represent an effective non-invasive resource for studying wildlife viral diversity and for detecting novel potentially zoonotic viruses prior to their emergence.
Analysis of computational codon usage models and their association with translationally slow codons

Improved computational modeling of protein translation rates, including better prediction of where translational slowdowns along an mRNA sequence may occur, is critical for understanding co-translational folding. Because codons within a synonymous codon group are translated at different rates, many computational translation models rely on analyzing synonymous codons. Some models rely on genome-wide codon usage bias (CUB), believing that globally rare and common codons are the most informative of slow and fast translation, respectively. Others use the CUB observed only in highly expressed genes, which should be under selective pressure to be translated efficiently (and whose CUB may therefore be more indicative of translation rates). No prior work has analyzed these models for their ability to predict translational slowdowns. Here, we evaluate five models for their association with slowly translated positions as denoted by two independent ribosome footprint (RFP) count experiments from S. cerevisiae, because RFP data is often considered as a “ground truth” for translation rates across mRNA sequences. We show that all five considered models strongly associate with the RFP data and therefore have potential for estimating translational slowdowns. However, we also show that there is a weak correlation between RFP counts for the same genes originating from independent experiments, even when their experimental conditions are similar. This raises concerns about the efficacy of using current RFP experimental data for estimating translation rates and highlights a potential advantage of using computational models to understand translation rates instead.
The Polycomb Repressive Complex 2.1 Links the Food Environment to a Persistent Neural State

Interactions between genes and environment sculpt the responses of cells to environmental stimuli. In neuronal cells this process can lead to long term changes in the behavioral repertoire of animals, which in turn impacts disease risk. Here we show that the Polycomb Repressive Complex 2.1 (PRC2.1) modulates the physiology of sweet gustatory neurons and the taste behavior of D. melanogaster fruit flies in response to the food environment. A high sugar diet caused a redistribution of PRC2.1 chromatin occupancy resulting in the repression of a transcriptional network required for the responsiveness of the gustatory neurons to sweet stimuli. These changes led to lower sweet sensation, which in turn promoted obesity. Nearly half of the transcriptional changes mediated by PRC2.1 on a sugar diet persisted when animals were moved back to a control diet, causing a permanent decrease in sweet taste that was dependent on the constitutive activity of PRC2.1. Thus, our results point to a novel mechanism involved in modulating neural plasticity, behavior, and disease in response to the food environment.
Identifying optimal working points of individual Virtual Brains: A large-scale brain network modelling study

Using The Virtual Brain (TVB, thevirtualbrian.org) simulation platform, we explored for 50 individual adult human brains (ages 18-80), how personalized connectome based brain network modelling captures various empirical observations as measured by functional magnetic resonance imaging (fMRI) and electroencephalography (EEG). We compare simulated activity based on individual structural connectomes (SC) inferred from diffusion weighted imaging with fMRI and EEG in the resting state. We systematically explore the role of the following model parameters: conduction velocity, global coupling and graph theoretical features of individual SC. First, a subspace of the parameter space is identified for each subject that results in realistic brain activity, i.e. reproducing the following prominent features of empirical EEG-fMRI activity: topology of resting-state fMRI functional connectivity (FC), functional connectivity dynamics (FCD), electrophysiological oscillations in the delta (3-4 Hz) and alpha (8-12 Hz) frequency range and their bimodality, i.e. low and high energy modes. Interestingly, FCD fit, bimodality and static FC fit are highly correlated. They all show their optimum in the same range of global coupling. In other words, only when our local model is in a bistable regime we are able to generate switching of modes in our global network. Second, our simulations reveal the explicit network mechanisms that lead to electrophysiological oscillations, their bimodal behaviour and inter-regional differences. Third, we discuss biological interpretability of the Stefanescu-Jirsa-Hindmarsh-Rose-3D model when embedded inside the large-scale brain network and mechanisms underlying the emergence of bimodality of the neural signal. With the present study, we set the cornerstone for a systematic catalogue of spatiotemporal brain activity regimes generated with the connectome-based brain simulation platform The Virtual Brain. Author Summary In order to understand brain dynamics we use numerical simulations of brain network models. Combining the structural backbone of the brain, that is the white matter fibres connecting distinct regions in the grey matter, with dynamical systems describing the activity of neural populations we are able to simulate brain function on a large scale. In order to make accurate prediction with this network, it is crucial to determine optimal model parameters. We here use an explorative approach to adjust model parameters to individual brain activity, showing that subjects have their own optimal point in the parameter space, depending on their brain structure and function. At the same time, we investigate the relation between bistable phenomena on the scale of neural populations and the changed in functional connectivity on the brain network scale. Our results are important for future modelling approaches trying to make accurate predictions of brain function.
25-hydroxyvitamin D and Biomarkers of Cardiometabolic Disease

Background: Vitamin D may have beneficial effects on cardiometabolic disease, but the evidence is equivocal. This may be due to unaccounted confounders, such as lifestyle factors and genetic variation. We examined the association between circulating 25-hydroxyvitamin D [25(OH)D] and biomarkers of cardiometabolic disease risk, including biomarkers of inflammation, glycemic dysregulation and lipid metabolism, and a panel of 54 plasma proteomic biomarkers, and determined whether lifestyle variables and genetic variation modified these
The Computational Diet: A Review of Computational Methods Across Diet, Microbiome, and Health

Food and human health are inextricably linked. As such, revolutionary impacts on health have been derived from advances in the production and distribution of food relating to food safety and fortification with micronutrients. During the past two decades, it has become apparent that the human microbiome has the potential to modulate health, including in ways that may be related to diet and the composition of specific foods. Despite the excitement and potential surrounding this area, the complexity of the gut microbiome, the chemical composition of food, and their interplay in situ remains a daunting task to fully understand. However, recent advances in high-throughput sequencing, metabolomics profiling, compositional analysis of food, and the emergence of electronic health records provide new sources of data that can contribute to addressing this challenge. Computational science will play an essential role in this effort as it will provide the foundation to integrate these data layers and derive insights capable of revealing and understanding the complex interactions between diet, gut microbiome, and health. Here, we review the current knowledge on diet-health-gut microbiota, relevant data sources, bioinformatics tools, machine learning capabilities, as well as the intellectual property and legislative regulatory landscape. We provide guidance on employing machine learning and data analytics, identify gaps in current methods, and describe new scenarios to be unlocked in the next few years in the context of current knowledge.
CRISPR/Cas9-Mediated Foxp1 Silencing Restores Immune Surveillance in an Immunocompetent A20 Lymphoma Model

The interaction of lymphoma cells with their microenvironment has an important role in disease pathogenesis and is being actively pursued therapeutically using immunomodulatory drugs, including immune checkpoint inhibitors. Diffuse large B-cell lymphoma (DLBCL) is an aggressive high-grade disease that remains incurable in ~40% of patients treated with R-CHOP immunochemotherapy. The FOXP1 transcription factor is abundantly expressed in such high-risk DLBCL and we recently identified its regulation of immune response signatures, in particular, its suppression of the cell surface expression of major histocompatibility class II (MHC-II), which has a critical role in antigen presentation to T cells. Using CRISPR/Cas9 genome editing we have depleted Foxp1 expression in the aggressive murine A20 lymphoma cell line. When grown in BALB/c mice, this cell line provides a high-fidelity immunocompetent disseminated lymphoma model that displays many characteristics of human DLBCL. Transient Foxp1-depletion using siRNA, and stable depletion using CRISPR (generated by independently targeting Foxp1 exon six or seven) upregulated cell surface I-Ab (MHC-II) expression without impairing cell viability in vitro. RNA sequencing of Foxp1-depleted A20 clones identified commonly deregulated genes, such as the B-cell marker Cd19, and hallmark DLBCL signatures such as MYC-targets and oxidative phosphorylation. Immunocompetent animals bearing Foxp1-depleted A20 lymphomas showed significantly-improved survival, and 20% did not develop tumors; consistent with modulating immune surveillance, this was not observed in immunodeficient NOD SCIDγ mice. The A20 Foxp1 CRISPR model will help to further characterize the contribution of Foxp1 to lymphoma immune evasion and the potential for Foxp1 targeting to synergize with other immunotherapies.
Global Health Determinants Perceived and Expressed by Children and Adolescents Between 6 and 17 Years: A Systematic Review of Qualitative Studies

Aim: To identify the determinants of global health in the literature as perceived and expressed by children and adolescents in order to adapt prevention actions to this young audience. To also question the pertinence of a qualitative approach when interviewing children. Method:Systematic review of the literature from PubMed, Google Scholar, CINAHL, PsycINFO databases. The studies selected used qualitative methods alone for investigating the views of health determinants in children and adolescents. Results:185 articles were read to reach a final selection of 13 articles on global health, excluding studies with children who were ill, studies using quantitative, mixed, or retrospective methodologies, and those dealing exclusively with themes of health. Collecting information from children and adolescents showed the pertinence and effectiveness of qualitative methods. It also appears necessary to explore new paths: improving and adapting the tools and methodological supports used and combining them to enrich repositories. Conclusion:The small amount of qualitative data available with the views of children and adolescents on health determinants requires that new studies with better adapted collection methodologies be set up. To increase pertinence and effectiveness among a young audience, it is necessary, considering the methodologies identified during this literature review, to turn toward a multi-phase method that combines these methods. A methodology in several phases allows each one to use a different approach with young people and to obtain richer and more varied information. A corpus of images appeared as a powerful tool for collection: it facilitates children's capacity for oral expression and places the researcher in a position of listening.
Gamified Motor Training With Tangible Robots in Older Adults: A Feasibility Study and Comparison With the Young

Background: An increasing lifespan and the resulting change in our expectations of later life stages are dependent on a good health state. This emphasizes the importance of the development of strategies to further strengthen healthy aging. One important aspect of good health in later life stages is sustained skilled motor function. Objective: Here, we tested the effectiveness of robotic upper limb motor training in a game-like scenario assessing game-based learning and its transfer potential. Methods: Thirty-six healthy participants (n = 18 elderly participants, n = 18 young controls) trained with a Pacman-like game using a hand-held Cellulo robot on 2 consecutive days. The game-related movements were conducted on a printed map displaying a maze and targets that had to be collected. Gradually, the task difficulty was adjusted between games by modifying or adding different game elements (e.g., speed and number of chasing ghosts, additional rules, and haptic feedback). Transfer was assessed by scoring simple robot manipulation on two different trajectories. Results: Elderly participants were able to improve their game performance over time [t(874) = 2.97, p < 0.01]. The applied game elements had similar effects on both age groups. Importantly, the game-based learning was transferable to simple robot manipulation that resembles activities of daily life. Only minor age-related differences were present (smaller overall learning gain and different effects of the wall-crash penalty rule in the elderly group). Conclusions: Gamified motor training with the Cellulo system has the potential to translate into an efficient and relatively low-cost robotic motor training tool for promoting upper limb function to promote healthy aging.
Hand Control With Invasive Feedback Is Not Impaired by Increased Cognitive Load

Recent experiments have shown that neural stimulation can successfully restore sensory feedback in upper-limb amputees improving their ability to control the prosthesis. However, the potential advantages of invasive sensory feedback with respect to non-invasive solutions have not been yet identified. Our hypothesis was that a difference would appear when the subject cannot focus all the attention to the use of the prosthesis, but some additional activities require his/her cognitive attention, which is a quite common situation in real-life conditions. To verify this hypothesis, we asked a trans-radial amputee, equipped with a bidirectional hand prosthesis, to perform motor tasks also in combination with a cognitive task. Sensory feedback was provided via intraneural (invasive) or electro-tactile (non-invasive) stimulation. We collected also data related to self-confidence. While both approaches were able to significantly improve the motor performance of the subject when no additional cognitive effort was asked, the manual accuracy was not affected by the cognitive task only when intraneural feedback was provided. The highest self-confidence was obtained when intraneural sensory feedback was provided. Our findings show that intraneural sensory feedback is more robust to dual tasks than non-invasive feedback. This is the first direct comparison between invasive and non-invasive approaches for restoring sensory feedback and it could suggest an advantage of using invasive solutions. Clinical Trial Registration: www.ClinicalTrials. gov, identifier NCT02848846.
Intestinal Flora and Disease Mutually Shape the Regional Immune System in the Intestinal Tract

The intestinal tract is the largest digestive organ in the human body. It is colonized by, and consistently exposed to, a myriad of microorganisms, including bifidobacteria, lactobacillus, Escherichia coli, enterococcus, clostridium perfringens, and pseudomonas. To protect the body from potential pathogens, the intestinal tract has evolved regional immune characteristics. These characteristics are defined by its unique structure, function, and microenvironment, which differ drastically from those of the common central and peripheral immune organs. The intestinal microenvironment created by the intestinal flora and its products significantly affects the immune function of the region. In turn, specific diseases regulate and influence the composition of the intestinal flora. A constant interplay occurs between the intestinal flora and immune system. Further, the intestinal microenvironment can be reconstructed by probiotic use or microbiota transplantation, functioning to recalibrate the immune homeostasis, while also contributing to the treatment or amelioration of diseases. In this review, we summarize the relationship between the intestinal flora and the occurrence and development of diseases as an in-turn effect on intestinal immunity. We also discuss improved immune function as it relates to non-specific and specific immunity. Further, we discuss the proliferation, differentiation and secretion of immune cells, within the intestinal region following remodeling of the microenvironment as a means to ameliorate and treat diseases. Finally, we suggest strategies for improved utilization of intestinal flora.
Parkinson's Disease Exhibits Amplified Intermuscular Coherence During Dynamic Voluntary Action

Parkinson's disease (PD) is typically diagnosed and evaluated on the basis of overt motor dysfunction, however, subtle changes in the frequency spectrum of neural drive to muscles have been reported as well. During dynamic actions, coactive muscles of healthy adults often share a common source of 6–15 Hz (alpha-band) neural drive, creating synchronous alpha-band activity in their EMG signals. Individuals with PD commonly exhibit kinetic action tremor at similar frequencies, but the potential relationship between the intermuscular alpha-band neural drive seen in healthy adults and the action tremor associated with PD is not well-understood. A close relationship is most tenable during voluntary dynamic tasks where alpha-band neural drive is strongest in healthy adults, and where neural circuits affected by PD are most engaged. In this study, we characterized the frequency spectrum of EMG synchronization (intermuscular coherence) in 16 participants with PD and 15 age-matched controls during two dynamic motor tasks: (1) rotation of a dial between the thumb and index finger, and (2) dynamic scaling of isometric precision pinch force. These tasks produce different profiles of coherence between the first dorsal interosseous and abductor pollicis brevis muscles. We sought to determine if alpha-band intermuscular coherence would be amplified in participants with PD relative to controls, if such differences would be task-specific, and if they would correlate with symptom severity. We found that relative to controls, the PD group displayed amplified, but similarly task-dependent, coherence in the alpha-band. The magnitude of coherence during the rotation task correlated with overall symptom severity as per the UPDRS rating scale. Finally, we explored the potential for our coherence measures, with no additional information, to discriminate individuals with PD from controls. The area under the Receiver Operating Characteristic curve (AUC) indicated a clear separation between groups (AUC = 0.96), even though participants with PD were on their typical medication and displayed only mild-moderate symptoms. We conclude that a task-dependent, intermuscular neural drive within the alpha-band is amplified in PD. Its quantification via intermuscular coherence analysis may provide a useful tool for detecting the presence of PD, or assessing its progression.