Miracle-dz/UniFAR-FTUs huggingface dataset:
Quantitative Analysis of Robustness in Systems Biology - Combining Global and Local Approaches

To characterize the behavior and robustness of cellular circuits is a major challenge for Systems Biology. Many of the published methods that address this question quantify the local robustness of the models. In this thesis, I tried to underpin the inappropriateness of such local measures and proposed an alternative solution: a glocal measure for robustness that combines both global and local aspects. It comprises a broad exploration of the parameter space and a further refinement based on different local measures. The method is general and such glocal analysis could be applied to many problems. Along with the theoretical and formal aspects of this new analysis method, I developed sampling algorithms that efficiently investigate the generally highdimensional parameter space of models. To show the usefulness of my method, I applied it on different models of cyclic systems such as the circadian clock and the mitotic cycle. I first considered two models of the cyanobacterial circadian clock and compared their robustness properties. Also in the context of circadian rhythms, I studied the effect of additional feedback loops on the robustness properties in relation with entrainment. Models of the mitotic cycle are also used to assess the effect of an additional positive feedback loop on circuit robustness to parameter changes and molecular noise. Finally, I established some principles for the design of a synthetic circuit based on robustness. The thesis carries on with a discussion that emphasizes the advantages of the glocal method for robustness analysis: in all works, correlations between parameter values and local robustness can be found. Such results facilitate our understanding of the biochemical systems and can be a guide for new experiments to discriminate models or give directions for altering the robustness of the systems. I conclude by discussing potential applications for my method and possible improvements.
EXERCISE DEPENDENCE AMONG MARATHON RUNNERS IN RELATION TO THEIR DEMOGRAPHIC AND TRAINING STATUS

Introduction and purpose. Taking into account that endurance athletes might be at an increased risk for exercise dependence there is a need for monitoring the prevalence and correlates of this phenomenon in them. The aim of the study was assessing the prevalence of exercise addiction among marathon runners and identify its socio-demographic and training correlates. Material and method. A total of 132 runners ranging in age from 18–69 years old took part in the study. To assess the exercise dependence a polish version of the Exercise Dependence Scale-21 was used. Results. The results suggest that being at risk for exercise dependence concerns 12% of runners and – except of withdrawal factor - is not related to sex but is related to age. No significant differences were found between training volume groups and exercise dependence. C onclusions . More than one on ten marathoners seem to be addicted to running suggesting the need to increase knowledge on this phenomenon in this community.
OAJSM_A_235143 87..98

Department of Family Medicine, Medstar Franklin Square Medical Center, Baltimore, MD, USA Abstract: Numerous publications have described the behaviors employed by professional jockeys on a daily basis to achieve and maintain a minimum racing weight. This narrative review provides an update of recent publications that report on the impact of such practices. Although rapid weight-loss techniques such as calorie restriction and dehydration are commonly thought to be deleterious to jockeys, little evidence exists of enduring health consequences. There is evidence to suggest that jockey training behaviors and dietary choices are not aligned with optimum preparation for the physiological demands of the sport. Further research is necessary to better measure the health impact of jockey weightmaking behaviors; such data might guide reforms of athlete behavior and regulatory practices within the global sport of horse racing.
Tangible Interfaces for Learning - Training Spatial Skills in Vocational Classrooms

There have been many claims that Tangible User Interfaces (TUIs) can have a positive impact on learning. Alleged benefits include increasing usability, improving engagement and collaboration of students, and providing a better perception of the task, especially spatial ones. However, there exists little empirical data to back up these claims. Moreover, for all their potential benefits for learning, TUIs are still scarcely used in schools. This thesis explores these two issues in the specific context of vocational education and training of carpenter apprentices. The learning objectives concern spatial skills and in particular, the mapping between 2D and 3D representations. We study (1) whether TUIs can support the training of spatial skills, and if so what features allow them to do so, and (2) what kinds of classroom pedagogical scenarios TUIs can support. We follow a design-based research approach and run empirical studies, mostly in classrooms. The contributions of this thesis touch on three research domains: 1. Spatial skills. Our results show that TUIs can help teach spatial skills to carpenter apprentices. The tangible nature of TUIs can help the learner relate multiple representations of an object, especially for difficult problems. It can also lower the barrier to entry into a learning domain for beginners. 2. Learning with TUIs. According to our results, TUIs can benefit learning, but the mere fact of using TUIs does not guarantee learning. Instead, special attention needs to be given to the design of the TUI. Small design variations, such as the physical correspondence between the tangible object and its virtual representations, or the type and timing of feedback given to the user, can have a significant impact on learning. 3. Classroom technologies and orchestration. We explore several classroom pedagogical scenarios that TUIs can support. The most promising one is to use a TUI as part of a hybrid classroom learning activity that includes both TUI and non TUI steps. Additionally, we devise two ways to promote the integration of TUIs in classroom. First, we introduce 5 design principles that reduce the classroom orchestration load. Second, we show how new web technologies can be used to deploy TUIs in schools at a lower cost.
REPORT RAPPORT

This paper deals with the problem of unsupervised image segmentation. Our goal is to propose a method which is able to segment a color image without any human intervention. The only input is the observed image, all other parameters are estimated during the segmentation process. Our method is model-based, we use a (cid:12)rst order Markov random (cid:12)eld (MRF) model (also known as the Potts model) where the singleton energies derive from a multivariate Gaussian distribution and second order potentials favor similar classes in neighboring pixels. The most di(cid:14)cult part is the estimation of the number of pixel classes or in other words, the estimation of the number of Gaussian mixture components. Reversible jump Markov chain Monte Carlo (MCMC) is used to solve this problem. These jumps enable the possible splitting and merging of classes. The algorithm (cid:12)nds the most likely number of classes, their associated model parameters and generates a segmentation of the image by classifying the pixels into these classes. The estimation is done according to the Maximum A Posteriori (MAP) criteria. Experimental results are promising, we have obtained accurate results on a variety of real color images. 1991 Mathematics Subject Classi(cid:12)cation:
Structural conservation of MALAT1 long non-coding RNA in cells and in evolution

Although not canonically polyadenylated, the long non-coding RNA MALAT1 (Metastasis Associated Lung Adenocarcinoma Transcript 1) is stabilized by a highly conserved 159 nucleotide triple helix structure on its 3’ end. The entire MALAT1 transcript is over 8,000 nucleotides long in humans and is considered one of the most conserved lncRNAs, at both the sequence and structure levels. The strongest structural conservation signal (as measured by co-variation of base-pairs) is in the triple helix structure. Primary sequence analysis of co-variation alone cannot confirm the degree of structural conservation of the entire full-length transcript. Furthermore, RNA structure is often context dependent; RNA binding proteins that are differentially expressed in different cell types may alter structure. We investigate here the in cell and cell free structures of the full-length human and green monkey (Chlorocebus sabaeus) MALAT1 transcripts in multiple tissue-derived cell lines using SHAPE chemical probing. Our data reveals surprising levels of uniform structural conservation in different cell lines, in cells and cell free, and even between species, despite significant differences in primary sequence. The uniformity of the structural conservation across the entire transcript suggests that, despite seeing co-variation signals only in the three-helix junction of the lncRNA, the rest of the transcript’s structure is remarkably conserved at least in primates and across multiple cell types and conditions.
Multiscale functional connectivity patterns of the aging brain learned from rsfMRI data of 4,259 individuals of the multi-cohort iSTAGING study

To learn multiscale functional connectivity patterns of the aging brain, we built a brain age prediction model of functional connectivity measures at seven scales on a large fMRI dataset, consisting of resting-state fMRI scans of 4259 individuals with a wide age range (22 to 97 years, with an average of 63) from five cohorts. We computed multiscale functional connectivity measures of individual subjects using a personalized functional network computational method, harmonized the functional connectivity measures of subjects from multiple datasets in order to build a functional brain age model, and finally evaluated how functional brain age gap correlated with cognitive measures of individual subjects. Our study has revealed that functional connectivity measures at multiple scales were more informative than those at any single scale for the brain age prediction, the data harmonization significantly improved the brain age prediction performance, and harmonization in the tangent space worked better than in the original space. Moreover, brain age gap scores of individual subjects derived from the brain age prediction model were significantly correlated with clinical and cognitive measures. Overall, these results demonstrated that multiscale functional connectivity patterns learned from a large-scale multi-site rsfMRI dataset were informative for characterizing the aging brain and the derived brain age gap was associated with cognitive and clinical measures.
A learning experience elicits sex‐dependent neurogenomic responses in Bicyclus anynana butterflies

Sexually dimorphic behaviour is pervasive across animals, with males and females exhibiting different mate selection, parental care, foraging, dispersal, and territorial strategies. However, the genetic underpinnings of sexually dimorphic behaviours are poorly understood. Here we investigate gene networks and expression patterns associated with sexually dimorphic imprinting‐like learning in the butterfly Bicyclus anynana. In this species, both males and females learn visual preferences, but learn preferences for different traits and use different signals as salient, unconditioned cues. To identify genes and gene networks associated with this behaviour, we examined gene expression profiles of the brains and eyes of male and female butterflies immediately post training and compared them to the same tissues of naïve individuals. We found more differentially expressed genes and a greater number of associated gene networks in the eyes, indicating a role of the peripheral nervous system in visual imprinting‐like learning. Females had higher chemoreceptor expression levels than males, supporting the hypothesized sexual dimorphic use of chemical cues during the learning process. In addition, genes that influence B. anynana wing patterns (sexual ornaments), such as invected, spalt, and apterous, were also differentially expressed in the brain and eye, suggesting that these genes may influence both sexual ornaments and the preferences for these ornaments. Our results indicate dynamic and sex‐specific responses to social scenario in both the peripheral and central nervous systems and highlight the potential role of wing patterning genes in mate preference and learning across the Lepidoptera.
Message in a Bottle: Archived DNA Reveals Marine Heatwave-Associated Shifts in Fish Assemblages

Marine heatwaves can drive large-scale shifts in marine ecosystems but studying their impacts on whole species assemblages can be difficult. Here, we leverage the taxonomic breadth and resolution of DNA sequences derived from environmental DNA (eDNA) in the ethanol of a set of 23-year longitudinal ichthyoplankton samples, combining these with microscopy-derived ichthyoplankton identification to yield higher-resolution, species-specific quantitative abundance estimates of fish assemblages in the California Current Large Marine Ecosystem during and after the 2014–16 Pacific marine heatwave. This integrated dataset reveals patterns of tropicalization with increases in southern, mesopelagic species and associated declines in important temperate fisheries targets (e.g., North Pacific Hake (Merluccius productus) and Pacific Sardine (Sardinops sagax)). We observed novel assemblages of southern, mesopelagic fishes and temperate species (e.g., Northern Anchovy, Engraulis mordax) even after the return to average water temperatures. Our innovative preservative derived eDNA metabarcoding and quantitative modeling approaches open the door to reconstructing the historical dynamics of assemblages from modern and archived samples worldwide. Summary Novel quantitative abundance estimates from archived DNA reveals marine heatwave-associated shifts in fish assemblages.
A translational approach to measuring the neural systems underlying approach-avoidance conflict in humans

Approach-avoidance conflict (AAC) arises from decisions with embedded positive and negative outcomes, and appropriate management of these decisions is essential for adaptive functioning. However, translating key advances on AAC in non-human primates to tasks in humans has proven difficult in part due to the inherent limitations in existing human tasks in isolating relevant neural substrates of behavior. Here, we present, and validate, a novel task in humans (N= 38) of both sexes, derived from work in non-human primates utilizing primary reinforcers (shock/juice), and in doing so identify neural features specific to conflict, implementing a computational model of task behavior. We found that neural patterns of activation within the parietal, frontal, temporal and cingulate regions were associated with conflict-specific avoidance behavior. Importantly, a number of these regions were associated with trait anxiety, implicating a potential link between these neural regions and anxiety-driven avoidance behavior. This task platform may help advance both behavioral and biological research examining the neural patterning underlying approach-avoidance behavior in humans, providing an empirically oriented framework with which to translate between non-human primate and human work. Significance Statement The current paper describes and validates a novel task for studying Approach-Avoidance Conflict behavior that capitalizes on innate reinforcers and stringent thresholding, effectively bridging animal and human work in this field. The task is then used to identify the neural correlates of AAC behavior in humans, identifying patterns of activation linked to temporal variation in avoidance behavior specific to conflict. Further, a novel model is developed and applied to the behavioral data to more sensitively quantify response patterns using reinforcement learning, and neural patterns relating to these behavioral effects were identified. Finally, as anxiety is strongly associated in the animal and human literature with avoidance responding, we identified a subgroup of neural effects associated with trait anxiety.
Loss of aquaporin-4 results in glymphatic system dysfunction via brain-wide interstitial fluid stagnation

The glymphatic system is a fluid transport network of cerebrospinal fluid (CSF) entering the brain along arterial perivascular spaces, exchanging with interstitial fluid (ISF), ultimately establishing directional clearance of interstitial solutes. CSF transport is facilitated by the expression of aquaporin-4 (AQP4) water channels on the perivascular endfeet of astrocytes. Mice with genetic deletion of AQP4 (AQP4 KO) exhibit abnormalities in the brain structure and molecular water transport. Yet, no studies have systematically examined how these abnormalities in structure and water transport correlate with glymphatic function. Here we used high-resolution 3D magnetic resonance (MR) non-contrast cisternography, diffusion-weighted MR imaging (MR-DWI) along with intravoxel-incoherent motion (IVIM) DWI, while evaluating glymphatic function using a standard dynamic contrast-enhanced MR imaging to better understand how water transport and glymphatic function is disrupted after genetic deletion of AQP4. AQP4 KO mice had larger interstitial spaces and total brain volumes resulting in higher water content and reduced CSF space volumes, despite similar CSF production rates and vascular density compared to wildtype mice. The larger interstitial fluid volume likely resulted in increased slow but not fast MR diffusion scores and coincided with reduced glymphatic influx. This markedly altered brain fluid transport in AQP4 KO mice may result from a reduction in glymphatic clearance, leading to stagnation of ISF movement and enlargement of the interstitial space. Overall, diffusion MR is a useful tool to evaluate glymphatic function and may serve as valuable translational biomarker to study glymphatics in human disease.
Long-term Christmas Bird Counts describe neotropical urban bird diversity

A significant gap in understanding the response of biodiversity to urban areas is the lack of long-term studies. Most of the information on urban birds comes from studies carried out in the northern hemisphere, and they include data that don’t exceed three years. Although short-term studies contribute to knowledge about bird community diversity and their spatial distribution in urban areas, they could be biased towards more conspicuous and abundant species. One of the few multi-temporal datasets available for birds in urban areas is the Christmas Bird Count (CBC). Using annual CBC data available between 2001 and 2018 from 21 urban and peri-urban sample sites assessed from the main cities of Colombia, we identified and analyzed long-term trends on the cumulative diversity of bird communities as well as on their spatial distribution. We estimated comparative trends in richness, abundance, similarity, and complementarity of avifauna for each city and sample site based on their responses to urbanization and dietary guilds. We identified almost a quarter of the species registered in Colombia (464 of 1954). The representativeness of the community obtained during 18 years exceeds 84%, showing richness that ranges between 214 and 278 species in the three cities. Bird species and individuals registered showed wide variation of the sample sites. We found more dwellers, insectivorous and granivorous species in urban areas, with frugivores relegated to peri-urban sites, usually coinciding with avoider species. Natural peri-urban areas and intra-urban wetlands and urban parks were the most important refuges for birds and maintained the highest avoider and utilizer species richness. Long-term inventories are fundamental for determining consolidated bird diversity and distributional patterns. This information established a baseline for decision-making and applying recommendations that allow reconciling the growing demand for urban areas with the need to preserve the native avifauna in megadiverse Neotropical countries such as Colombia.
First experimental evidence for active farming in ambrosia beetles and strong heredity of garden microbiomes

Fungal cultivation is a defining feature for advanced agriculture in attine ants and fungus-farming termites. In a third supposedly fungus-farming group, wood-colonizing ambrosia beetles (Curculionidae: Scolytinae and Platypodinae), an experimental proof for the effectiveness of beetle activity for selective promotion of their food fungi over others is lacking and farming has only been assumed based on observations of social and hygienic behaviors. Here, we experimentally removed mothers and their offspring from young nests of the fruit-tree pinhole borer, Xyleborinus saxesenii (Scolytinae). By amplicon sequencing of bacterial and fungal communities of nests with and without beetles we could show that beetles are indeed able to actively shift symbiont communities. Although being consumed, the Raffaelea food fungi were more abundant when beetles were present while a weed fungus (Chaetomium sp.) as well as overall bacterial diversity were reduced in comparison to nests without beetles. Core symbiont communities were generally low diverse and there were strong signs for vertical transmission not only for the cultivars, but also for secondary symbionts. Our findings verify the existence of active farming, even though the exact mechanisms underlying the selective promotion and/or suppression of symbionts need further investigation.
Multiscale methods for advection-diffusion problems

The development of numerical methods for multiscale advection-diffusion problems presents a number of challenges. The one-scale structures may significantly in uence the coarser properties of the system, but are often impossible to solve in full details. The time integration of the evolution system is still due to the diffusion term and its stability properties have to be taken into account for its resolution. We discuss in this paper an algorithm, which combines Heterogeneous Multiscale Methods (HMM) with Orthogonal Runge-Kutta Chebyshev (ROCK) methods, for the efficient numerical resolution of multiscale advection-diffusion problems.