Miracle-dz/UniFAR-FTUs huggingface dataset:
The solution of the point kinetics equations via converged accelerated Taylor series (CATS)

This paper deals with finding accurate solutions of the point kinetics equations including non-linear feedback, in a fast, efficient and straightforward way. A truncated Taylor series is coupled to continuous analytical continuation to provide the recurrence relations to solve the ordinary differential equations of point kinetics. Non-linear (Wynn-epsilon) and linear (Romberg) convergence accelerations are employed to provide highly accurate results for the evaluation of Taylor series expansions and extrapolated values of neutron and precursor densities at desired edits. The proposed Converged Accelerated Taylor Series, or CATS, algorithm automatically performs successive mesh refinements until the desired accuracy is obtained, making use of the intermediate results for converged initial values at each interval. Numerical performance is evaluated using case studies available from the literature. Nearly perfect agreement is found with the literature results generally considered most accurate. Benchmark quality results are reported for several cases of interest including step, ramp, zigzag and sinusoidal prescribed insertions and insertions with adiabatic Doppler feedback. A larger than usual (9) number of digits is included to encourage honest benchmarking. The benchmark is then applied to the enhanced piecewise constant algorithm (EPCA) currently being developed by the second author. (authors)
Waking Up to the Importance of Sleep: Opportunities for Policy Makers

Insufficient sleep is associated with an increased risk for a range of negative physical and mental health outcomes. Causes of insufficient sleep involve many factors, and the consequences are not evenly distributed across populations. Indeed, stark sleep disparities disadvantage racial and ethnic minorities and those low in socioeconomic status, who are more readily affected by poor sleep than their White and high socioeconomic status comparators. Sleep is situated in the context of a socioecological model that recognizes societal, community, and individual factors that shape poor sleep and drive sleep-related outcomes. Policy opportunities address each level of the presented model and addressing these barriers should promote better sleep for those affected and potentially reduce sleep disparities.
Digital technologies and the COVID-19 pandemic: Opportunities and challenges for environmental educators in Barcelona

Abstract The COVID-19 lockdowns forced environmental educators to increase the use of digital technologies, bringing to the forefront the need for critical research on the implications for teaching practice. Through interviews in Barcelona, we explore how environmental educators perceived related opportunities and difficulties and how these connect with their competencies in environmental education. Non-formal educators reported a more comprehensive range of digital tools than those in formal settings and particularly highlighted the difficulty of sustaining the impact on environmental learning when replacing face-to-face methods with digital technologies. Interviewees commonly perceived motivational challenges. We discuss how these experiences were less related to educators’ previous use of digital technologies and more to mastering specific competencies that can help them deal with emotions.
Nocturnal increase in cerebrospinal fluid secretion as a regulator of intracranial pressure

It is crucial to maintain the intracranial pressure (ICP) within the physiological range to ensure proper brain function. The ICP may fluctuate during the light-dark phase cycle, complicating diagnosis and treatment choice in patients with pressure-related disorders. Such ICP fluctuations may originate in circadian or sleep-wake cycle-mediated modulation of cerebrospinal fluid (CSF) flow dynamics, which in addition could support diurnal regulation of brain waste clearance. Through a combination of patient data and in vivo telemetric pressure measurements in adult male rats, we demonstrated that ICP increases in the dark phase in both species, independently of vascular parameters. This increase aligns with elevated CSF collection in patients and CSF production rate in rats, the latter obtained with the ventriculo-cisternal perfusion assay. The dark-phase increase in CSF secretion in rats was, in part, assigned to increased transport activity of the choroid plexus Na+,K+,2Cl- cotransporter (NKCC1), which is implicated in CSF secretion by this tissue. In conclusion, CSF secretion, and thus ICP, increases in the dark phase in humans and rats, irrespective of their diurnal/nocturnal activity preference, in part due to altered choroid plexus transport activity. Our findings suggest that CSF dynamics are modulated by the circadian rhythm, rather than merely sleep itself.
BQsupports: systematic assessment of the support and novelty of new biomedical associations

Living a Big Data era in Biomedicine, there is an unmet need to systematically assess experimental observations in the context of available information. This assessment would offer a means for an unbiased validation of the results and provide an initial estimate of the potential novelty of the findings. Here we present BQsupports, a web-based tool built upon the Bioteque biomedical descriptors that systematically analyzes and quantifies the current support to a given set of observations. The tool relies on over 1,000 distinct types of biomedical descriptors, covering over 11 different biological and chemical entities, including genes, cell lines, diseases and small molecules. By exploring hundreds of descriptors, BQsupports provide support scores for each observation across a wide variety of biomedical contexts. These scores are then aggregated to summarize the biomedical support of the assessed dataset as a whole. Finally, the BQsupports also suggests predictive features of the given dataset, which can be exploited in downstream machine learning applications. Availability and implementation The web application and underlying data are available online (https://bqsuppports.irbbarcelona.org). Contact patrick.aloy@irbbarcelona.org
Rhythmic tapping to a moving beat: motion kinematics overrules motion naturalness

Beat induction is the cognitive ability that allow humans to listen to a regular pulse in music and move in synchrony with it. Although auditory rhythmic cues are known to induce more consistent synchronization than flashing visual metronomes, this asymmetry can be canceled out by visual moving metronomes. Here, we investigated whether the naturalness of the visual motion or its kinematics could provide a synchronization advantage over flashing metronomes. Subjects tap in sync with visual isochronous metronomes defined by vertically or horizontally accelerating and decelerating motion, either congruent or not with natural gravity, and then continue tapping with no metronome. We found that motion kinematics was the predominant factor determining rhythm synchronization, as accelerating moving metronomes in either cardinal direction produced more precise and predictive tapping than decelerating or flashing conditions. Notably, a Bayesian observer model revealed that error correction during tapping synchronization and regression towards the mean in accuracy during tapping continuation in the absence of external cues are optimal control strategies independently of the moving properties of the visual metronomes. Our results support the notion that accelerating visual metronomes convey a strong sense of beat as seen in the cueing movements of an orchestra director.
Shared input and recurrency in neural networks for metabolically efficient information transmission

Shared input to a population of neurons induces noise correlations, which decreases the information carried by a population activity. Inhibitory feedback in recurrent neural networks can reduce the noise correlations and thus increase the information carried by the averaged population activity. However, the activity of inhibitory neurons is costly. This inhibitory feedback decreases the gain of the population. Thus, depolarization of its neurons requires stronger excitatory synaptic input, which is associated with higher ATP consumption. Given that the goal of neural populations is to transmit as much information as possible at minimal metabolic costs, it is unclear whether the increased information transmission reliability provided by inhibitory feedback compensates for the additional costs. We analyze this problem in a network of leaky integrate-and-fire neurons receiving correlated input. By maximizing mutual information with metabolic cost constraints, we show that there is an optimal strength of recurrent connections in the network, which maximizes the value of mutual information-per-cost. For higher values of input correlation, the mutual information-per-cost is higher for recurrent networks with inhibitory feedback compared to feedforward networks without any inhibitory neurons. Our results, therefore, show that the optimal synaptic strength of a recurrent network can be inferred from metabolically efficient coding arguments and that decorrelation of the input by inhibitory feedback compensates for the associated increased metabolic costs.
Modulation of Polar Auxin Transport Identifies the Molecular Determinants of Source-Sink Carbon Relationships and Sink Strength in Poplar

Source-to-sink carbon (C) allocation driven by the sink strength, i.e., the ability of a sink organ to import C, plays a central role in tissue growth and biomass productivity. However, molecular drivers of sink strength have not been thoroughly characterized in trees. Auxin, as a major plant phytohormone, regulates the mobilization of photoassimilates in source tissues and elevates the translocation of carbohydrates toward sink organs, including roots. In this study, we used an ‘auxin-stimulated carbon sink’ approach to understand the molecular processes involved in the long-distance source-sink C allocation in poplar. Poplar cuttings were foliar sprayed with polar auxin transport modulators, including auxin enhancers (AE) (i.e., IBA and IAA) and auxin inhibitor (AI) (i.e., NPA), followed by a comprehensive analysis of leaf, stem, and root tissues using biomass evaluation, phenotyping, C isotope labeling, metabolomics, and transcriptomics approaches. Auxin modulators altered root dry weight and branching pattern, and AE increased photosynthetically fixed C allocation from leaf to root tissues. The transcriptome analysis identified highly expressed genes in root tissue under AE condition including transcripts encoding polygalacturonase and β-amylase that could increase the sink size and activity. Metabolic analyses showed a shift in overall metabolism including an altered relative abundance levels of galactinol, and an opposite trend in citrate levels in root tissue under AE and AI conditions. In conclusion, we postulate a model suggesting that the source-sink C relationships in poplar could be fueled by mobile sugar alcohols, starch metabolism-derived sugars, and TCA-cycle intermediates as key molecular drivers of sink strength.
The role of folate receptor α in the partial rejuvenation of dentate gyrus cells. Improvement of cognitive function in elderly mice

In this work, we have studied the effect of small compounds in the partial rejuvenation of dentate gyrus cells by measuring the improvement of cognitive functions in elderly mice. Aging has been related to a change in DNA methylation and some one-carbon metabolites linked to that methylation process, like vitamin B12, folate or methionine have been involved in cognitive performance during aging. However, their role in this process and the possible mechanisms behind its cognitive effects are still unclear. Through direct infusion of these molecules in the dentate gyrus we have tested their effects on cognition in elderly mice. Only positive results were found for folate. A partial rejuvenation of dentate gyrus cells related to an increase in neuroplasticity by reorganizing extracellular matrix structures and rising the expression of juvenile genes like GluN2B was found. Since folate is involved in several cellular pathways in addition to DNA methylation, we have focused in its interaction with its folate receptor alpha (FRα), a protein that is present at the cell nucleus, acting as transcription factor. We have found that most of folate effects on brain would be mediated by the activation of FRα. In addition, we propose that the mechanism for cell rejuvenation by folate, or other FRα binding molecules, may involve the expression of proteins, like SOX2, a Yamanaka factor present in young neurons. Thus, the use of molecules that activate the FRα pathway could constitute an interesting strategy to be considered for the study of brain rejuvenation.
Predictive reward-prediction errors of climbing fiber inputs integrate modular reinforcement learning with supervised learning

Although the cerebellum is typically linked to supervised learning algorithms, it also exhibits extensive connections to reward processing. In this study, we investigated the cerebellum’s role in executing reinforcement learning algorithms, with a particular emphasis on essential reward-prediction errors. We employed the Q-learning model to accurately reproduce the licking responses of mice in a Go/No-go auditory-discrimination task. This method enabled the calculation of reinforcement learning variables, such as reward, predicted reward, and reward-prediction errors in each learning trial. By tensor component analysis of two-photon Ca2+ imaging data, we found that climbing fiber inputs of the two distinct components, which were specifically activated during Go and No-go cues in the learning process, showed an inverse relationship with predictive reward-prediction errors. Given the hypothesis of bidirectional parallel-fiber Purkinje-cell synaptic plasticity, Purkinje cells in these components could develop specific motor commands for their respective auditory cues, guided by the predictive reward-prediction errors from their climbing fiber inputs. These results indicate a possible role of context-specific actors in modular reinforcement learning, integrating with cerebellar supervised learning capabilities.
Metabolic influence of core ciliates within the rumen microbiome

Protozoa comprise a major fraction of the microbial biomass in the rumen microbiome, of which the entodiniomorphs (order: Entodiniomorphida ) and holotrichs (order: Vestibuliferida ) are consistently observed to be dominant across a diverse genetic and geographical range of ruminant hosts. Despite the apparent core role that protozoal species exert, their major biological and metabolic contributions to rumen function remain largely undescribed in vivo. Here, we have leveraged (meta)genome-centric metaproteomes from rumen fluid samples originating from both cattle and goats fed diets with varying inclusion levels of lipids and starch, to detail the specific metabolic niches that protozoa occupy in the context of their microbial co-habitants. Initial proteome estimations via total protein counts and label-free quantification highlight that entodiniomorph species Entodinium and Epidinium as well as the holotrichs Dasytricha and Isotricha comprise an extensive fraction of the total rumen metaproteome. Proteomic detection of protozoal metabolism such as hydrogenases ( Dasytricha , Isotricha, Epidinium, Enoploplastron ), carbohydrate-active enzymes ( Epidinium, Diplodinium, Enoploplastron , Polyplastron ), microbial predation ( Entodinium ) and volatile fatty acid production ( Entodinium and Epidinium ) was observed at increased levels in high methane-emitting animals. Despite certain protozoal species having well-established reputations for digesting starch, they were unexpectedly less detectable in low methane emitting-animals fed high starch diets, which were instead dominated by propionate/succinate-producing bacterial populations suspected of being resistant to predation irrespective of host. Finally, we reaffirmed our abovementioned observations in geographically independent datasets, thus illuminating the substantial metabolic influence that under-explored eukaryotic populations have in the rumen, with greater implications for both digestion and methane metabolism.
An oral cholera vaccine in the prevention and/or treatment of inflammatory bowel disease

The oral cholera vaccine WC-rBS consists of 4 different inactivated strains of Vibrio cholerae (LPS source) admixed with recombinant cholera toxin B subunit. Because of its unique composition and anti-inflammatory properties reported for both CTB and low doses of LPS from other Gram-negative bacteria, we speculated that WC-rBS might have anti-inflammatory potential in a chronic autoimmune disease such as inflammatory bowel diseases. First in vitro endotoxin tolerance experiments showed the surprising WC-rBS potential in the modulation of inflammatory responses on both PBMCs and THP1 cells. WC-rBS was further evaluated in the Dextran Sodium Sulfate colitis mouse model. Administrated orally at different dosages, WC-rBS vaccine was safe and showed immunomodulatory properties when administered in a preventive mode (before and during the induction of DSS colitis) as well as in a curative mode (after colitis induction); with improvement of disease activity index (from 27 to 73%) and histological score (from 65 to 88%). Interestingly, the highest therapeutic effect of WC-rBS vaccine was observed with the lowest dosage, showing even better anti-inflammatory properties than mesalamine; an approved 5-aminosalicylic acid drug for treating IBD patients. In summary, this is the first time that a prophylactic medicine, safe and approved for prevention of an infectious disease, showed a benefit in an inflammatory bowel disease model, potentially offering a novel therapeutic modality for IBD patients.
Inhibition of type III secretion system induced leukotriene B4 production by Yersinia pestis: A mechanism for early immune evasion

Subverting the host immune response to inhibit inflammation is a key virulence factor of Yersinia pestis. The inflammatory cascade is tightly controlled via the sequential action of lipid and protein mediators of inflammation. Because delayed inflammation is essential for Y. pestis to cause lethal infection, defining the mechanisms used by Y. pestis to manipulate the inflammatory cascade is necessary to understand this pathogen’s virulence. While previous studies have established that Y. pestis actively inhibits the expression of host proteins that mediate inflammation, there is currently a gap in our understanding of inflammatory lipid mediator response during plague. Here we use in vivo lipidomics to define the synthesis of lipid mediators of inflammation within the lungs during pneumonic plague. Interestingly, while we observed an early cyclooxygenase response during pneumonic plague, there was a significant delay in the synthesis of leukotriene B4 (LTB4), a pro-inflammatory lipid chemoattractant and activator of immune cells. Furthermore, in vitro studies with primary leukocytes from mice and humans further revealed that Y. pestis actively inhibited the synthesis of LTB4. Finally, using Y. pestis mutants in the Ysc type 3 secretion system (T3SS) and Yersinia outer protein (Yop) effectors, we demonstrate that leukocytes recognize the T3SS to initiate the synthesis of LTB4 rapidly. However, the Yop effectors secreted through the same system effectively inhibit this host response. Together, these data demonstrate that Y. pestis actively inhibits the synthesis of LTB4, an inflammatory lipid, required for rapid recruitment of leukocytes to the site of infection. Author Summary Yersinia pestis, the bacteria that causes plague, targets the host’s innate immune response to inhibit inflammation. Because the generation of this non-inflammatory environment is required for infection, we are interested in mechanisms used by Y. pestis to block inflammation. Lipid mediators are potent signaling molecules that regulate multiple host immune responses, including inflammation. While there have been studies on how Y. pestis blocks the proteins that mediate inflammation, there is a gap in our understanding of the inflammatory lipid mediator response during plague. Here we show that Y. pestis inhibits the production of one of these critical lipid mediators, leukotriene B4, by host immune cells. Furthermore, we identify both the signals that induce LTB4 production by leukocytes and the mechanisms used by Y. pestis to inhibit this process. Together, these data represent the first comprehensive analysis of inflammatory lipids produced during plague and improve our current understanding of how Y. pestis manipulates the host immune response to generate a permissive non-inflammatory environment required for bacterial colonization.
Lattice Boltzmann simulations for flow and heat/mass transfer problems in a three‐dimensional porous structure

The lattice Boltzmann method (LBM) for a binary miscible fluid mixture is applied to problems of transport phenomena in a three‐dimensional porous structure. Boundary conditions for the particle distribution function of a diffusing component are described in detail. Flow characteristics and concentration profiles of diffusing species at a pore scale in the structure are obtained at various Reynolds numbers. At high Reynolds numbers, the concentration profiles are highly affected by the flow convection and become completely different from those at low Reynolds numbers. The Sherwood numbers are calculated and compared in good agreement with available experimental data. The results indicate that the present method is useful for the investigation of transport phenomena in porous structures. Copyright © 2003 John Wiley & Sons, Ltd.
Model set design of the adaptive interacting multiple model tracking algorithm

Adaptive Interacting Multiple Model (AIMM) estimation is a method for improving the Interacting Multiple Model (IMM) estimation. But some new problems appear in the AIMM, such as how to select the structure of the adaptive model set, how to inherit the different data from the filters based on the old model set. In this paper some instructive conclusions and formulas of the design of the model set and the model transition probability are presented to solve these problems. Simulation results show that the tracking performance is improved when considering these factors.
Electro-mechanical delay in Hill-type muscle models

In this study, we investigated to which extent Hill-type muscle models can explain the electro-mechanical delay (EMD). The EMD is a phenomenon that has been well examined in muscle experiments. The EMD is the time lag between a change in muscle stimulation and the subsequent measurable change in muscle force. A variety of processes as, e.g., signal conduction and interaction of contractile and elastic muscle structures contribute to the EMD. The relative contributions of the particular processes have not been fully unveiled so far. Thereto, we simulated isometric muscle contractions using two Hill-type muscle models. Their parameters were extracted from experiments on the cat soleus muscle. In agreement with literature data, predicted EMD values depend on muscle-tendon complex (MTC) length and increase when reducing MTC lengths. The highest EMD values (28 and 27 ms) occur at the lowest MTC length examined (78% of optimal length). Above optimal MTC length, we find EMD saturation (2 ms) in one model. In the other model, the EMD slightly re-increases up to 9 ms at the highest length examined (113% of optimal length). The EMD values predicted by the two models were then compared to EMD values found in the same experiments from which the muscle parameters were extracted. At optimal MTC length, the EMD values, mapping ion release and visco-elastic interactions, predicted by both models (3.5 and 5.5 ms) just partly account for the measured value (15.8 ms). The biggest share (about 9 ms) of the remaining 11 ms can be attributed to signal conduction along the nerve and on the muscle surface. Further potential sources of delayed force generation are discussed.