Miracle-dz/UniFAR-FTUs huggingface dataset:
Regulation of Toxic RNA Foci and Mutant DMPK Transcripts: Role of MBNL Proteins and RNA Decay Pathways

Myotonic dystrophy type 1 (DM1) is a progressive, multisystemic disorder caused by an expansion of CTG repeats in the 3’ untranslated region of the DMPK gene. When transcribed the mutant RNAs accumulate in affected tissues appearing as distinct foci when visualised by in situ hybridisation. The RNA foci are aggregates of CUG repeat-containing RNAs that sequester RNA-binding proteins, particularly muscleblind-like (MBNL) proteins, leading to their dysfunction and causing downstream molecular and cellular defects. Here we show the double knock-out of MBNL1 and 2 prevents RNA foci formation and nuclear retention of mutant DMPK mRNA in DM1 cells as well as promoting their degradation and nuclear export. Using stochastic optical reconstruction microscopy (STORM), we find the presence of both large foci and micro foci in DM1 cells. Large foci consist of multiple DMPK transcripts, while many micro foci are (CUG)n fragments. The absence of MBNL proteins not only prevents the aggregation of multiple DMPK transcripts into large foci, but also promotes their degradation and nuclear processing. However, although a substantial amount of MBNL1 proteins are bound to the mutant transcripts, the pools of free MBNL1 proteins are similar in DM1 nuclei to those in controls. Furthermore, we have identified several factors that are involved in the control of mutant DMPK mRNA turnover, including XRN2, EXOSC10, UPF1 and STAU1. Our study indicates that these factors are implicated in the RNA foci accumulation and the degradation of mutant DMPK mRNA. UPF1 and STAU1 may have additional roles beyond degradation, impacting the nuclear processing of mutant DMPK mRNA. Our study also highlights the critical role of MBNL proteins in regulating mutant DMPK mRNA metabolism: the absence of MBNLs in DM1 appears to expedite the processing of mutant DMPK mRNA mediated by these RNA decay factors. Significance statement Our investigations uncovered valuable data on the RNA foci dynamics in DM1, revealing the intricate mechanisms that underlie their formation, stability, and turnover. Our findings also contributed to delineate the complex pathways involved in the transportation and degradation of the mutant mRNA and provided insights into the critical role played by MBNL proteins in these processes. Studying the degradation mechanism of mutant DMPK mRNA in myotonic dystrophy may provide a foundation for comprehending the mechanisms of RNA degradation in other diseases caused by short tandem repeat (STR) mutations, such as Huntington’s disease, Fragile X syndrome, and several types of ataxia. Additionally, the use of cutting-edge STORM technology can provide a valuable tool for investigating RNA foci in other STR expansion disorders.
Migration distance and mating system are not associated with genetic diversity and differentiation among bats (Chiroptera)

Genetic variation is critical for evolutionary responses to environmental change. Links between genetic variation and behavioural or life history traits may reveal how varied strategies influence evolutionary trends in speciation and adaptation. Traits associated with movement typically correlate with population genetic structure and could help predict populations’ vulnerability to geographic processes such as habitat fragmentation and disease spread. With their wide diversity in behaviours and ecologies, bats provide a useful testing ground for hypotheses about population structure related to species-specific movement patterns. We used a global sample of microsatellite data (n=233 sites from 17 bat species) associated with published studies to examine potential links between genetic variation and migration and mating strategies. The genetic measures we tested were population-specific differentiation, gene diversity, and allelic richness. Using Bayesian models that accounted for phylogenetic distances among species, we identified no correlations between migration or mating strategy and genetic variation. Our results do not support long-standing hypotheses about dispersal-mediated genetic structure, and contrast with prior studies on bat genetic diversity and differentiation. We discuss the need for continued research into the complex association of ecological, biogeographical, and behavioural factors that facilitate gene flow among populations, especially in species with diverse movement patterns.
Declining ozone exposure of European vegetation under climate change and reduced precursor emissions

The impacts of changes in ozone precursor emis- sions as well as climate change on the future ozone ex- posure of the vegetation in Europe were investigated. The ozone exposure is expressed as AOT40 (Accumulated expo- sure Over a Threshold of 40 ppb O3) as well as PODY (Phy- totoxic Ozone Dose above a threshold Y ). A new method is suggested to express how the length of the period during the year when coniferous and evergreen trees are sensitive to ozone might be affected by climate change. Ozone precursor emission changes from the RCP4.5 scenario were combined with climate simulations based on the IPCC SRES A1B sce- nario and used as input to the Eulerian Chemistry Transport Model MATCH from which projections of ozone concentra- tions were derived. The ozone exposure of vegetation over Europe expressed as AOT40 was projected to be substantially reduced between the periods 1990-2009 and 2040-2059 to levels which are well below critical levels used for vegeta- tion in the EU directive 2008/50/EC as well as for crops and forests used in the LRTAP convention, despite that the future climate resulted in prolonged yearly ozone sensitive periods. The reduction in AOT40 was mainly driven by the emis- sion reductions, not changes in the climate. For the toxico- logically more relevant POD1 index the projected reductions were smaller, but still significant. The values for POD 1 for the time period 2040-2059 were not projected to decrease to levels which are below critical levels for forest trees, repre- sented by Norway spruce. This study shows that substantial reductions of ozone precursor emissions have the potential to strongly reduce the future risk for ozone effects on the Euro-
Biogeography of Greater Antillean freshwater fishes, with a review of competing hypotheses

In biogeography, vicariance and long-distance dispersal are often characterized as competing scenarios. However, they are related concepts, both relying on reciprocal illumination from geological, ecological, and phylogenetic evidence. This can be illustrated for freshwater fishes, which may immigrate to islands when freshwater connections are temporarily present (vicariance), or by unusual means when oceanic gaps are crossed (long-distance dispersal). Marine barriers have a strong filtering effect, limiting immigrants to those most capable of oceanic dispersal. The roles of landspans and oceanic dispersal are being debated for freshwater fishes of the Greater Antilles. We review three active hypotheses (Cretaceous vicariance, GAARlandia, long-distance dispersal) and propose long-distance dispersal to be an appropriate null model due to a lack of reciprocal illumination for landspan hypotheses. Greater Antillean freshwater fishes have six potential source bioregions (defined from faunal similarity): Northern Gulf of México, Western Gulf of México, Maya Terrane, Chortís Block, Eastern Panamá, and Northern South America. Faunas of the Greater Antilles are composed of taxa immigrating from many of these bioregions, but there is strong compositional disharmony between island and mainland fish faunas (>90% of the species are cyprinodontiforms, compared to <10% in Northern Gulf of México and Northern South America, and ≤50% elsewhere), consistent with a hypothesis of long-distance dispersal. Ancestral area analysis indicates there were 16 or 17 immigration events over the last 51 my, 14 or 15 of these by cyprinodontiforms. Published divergence estimates and evidence available for each immigration event suggest they occurred at different times and by different pathways, possibly with rafts of vegetation discharged from rivers or washed to sea during storms. If so, ocean currents likely provide critical pathways for immigration when flowing from one landmass to another, but create dispersal barriers when flowing perpendicular between landmasses. In addition to high salinity tolerance, cyprinodontiforms (collectively) display a variety of adaptations that could enhance their ability to live with rafts (small body size, viviparity, low metabolism, amphibiousness, diapause, self-fertilization). These adaptations likely also helped immigrants establish island populations after arrival and persist long term thereafter. Cichlids may have used a pseudo bridge (Nicaragua Rise) to reach the Greater Antilles, persisting only on the largest islands (Cuba, Hispaniola). Gar (Lepisosteidae) may have crossed the Straits of Florida to Cuba, a relatively short crossing that is not a barrier to gene flow for several cyprinodontiform immigrants. Indeed, widespread distributions of Quaternary migrants (Cyprinodon, Gambusia, Kryptolebias), within the Greater Antilles and among neighbouring bioregions, imply long-distance dispersal is not necessarily inhibitory for well-adapted species, even though it appears to be virtually impossible all other freshwater fishes.
Stable Estimation of Survival Causal Effects

We study the problem of estimating survival causal effects, where the aim is to characterize the impact of an intervention on survival times, i.e., how long it takes for an event to occur. Applications include determining if a drug reduces the time to ICU discharge or if an advertising campaign increases customer dwell time. Historically, the most popular estimates have been based on parametric or semiparametric (e.g. proportional hazards) models; however, these methods suffer from problematic levels of bias. Recently debiased machine learning approaches are becoming increasingly popular, especially in applications to large datasets. However, despite their appealing theoretical properties, these estimators tend to be unstable because the debiasing step involves the use of the inverses of small estimated probabilities -- small errors in the estimated probabilities can result in huge changes in their inverses and therefore the resulting estimator. This problem is exacerbated in survival settings where probabilities are a product of treatment assignment and censoring probabilities. We propose a covariate balancing approach to estimating these inverses directly, sidestepping this problem. The result is an estimator that is stable in practice and enjoys many of the same theoretical properties. In particular, under overlap and asymptotic equicontinuity conditions, our estimator is asymptotically normal with negligible bias and optimal variance. Our experiments on synthetic and semi-synthetic data demonstrate that our method has competitive bias and smaller variance than debiased machine learning approaches.
Long-period geomagnetic variations and mantle conductivity: an inversion using Bailey's method

Summary. We have implemented an algorithm which is based on Bailey's solution of the inverse problem of electromagnetic induction in the Earth. The study was motivated by recent determinations of very long period data and also benefited from recent redeterminations of high frequency data. The algorithm has been successfully tested to provide reliable estimates of conductivity down to a depth of 2000 km, using synthetic data in the period range from 4 days to 11 years. Smooth data sets, which are required for the inversion, were constructed from various sources. At a given depth, the range of inverted models is less than one order of magnitude. Due to the lack of high frequency data, the conductivity of the upper 600 km of the mantle, which is found to be of the order of lo-' i2-l m-', may be overestimated. The algorithm performs well in the middle mantle, where conductivity rises steadily from 1 to 50 i2-l m-'. The lack of very low frequency data and limitations of the algorithm prevent one from obtaining meaningful estimates in the lower mantle. However, the study of the propagation of the late 1960s secular variation acceleration provides an estimate of the mean conductivity of the whole mantle. Thus, a complete mantle profile can be constructed. It is found that deep mantle conductivity probability does not exceed a few hundred i2-l m-'.
Candidate quantum disordered intermediate phase in the Heisenberg antiferromagnet on the maple-leaf lattice

Quantum antiferromagnets on geometrically frustrated lattices have long attracted interest for the formation of quantum disordered states and the possible emergence of quantum spin liquid (QSL) ground states. Here we turn to the nearest-neighbor spin-$1/2$ Heisenberg antiferromagnet on the maple-leaf lattice, which is known to relieve frustration by the formation of canted $120^{\circ}$ magnetic order or valence bond crystal order when varying the bond anisotropy. Employing a pseudo-fermion functional renormalization group approach to assess its ground state phase diagram in detail, we present evidence for a QSL regime sandwiched between these two limiting phases. The formation of such a QSL might signal proximity to a possible deconfined quantum critical point from which it emerges, and that is potentially accessible by tuning the exchange couplings. Our conclusions are based on large-scale simulations involving a careful finite-size scaling analysis of the behavior of magnetic susceptibility and spin-spin correlation functions under renormalization group flow.
Willingness to Pay for Rural Landscape Preservation: A Case Study in Mediterranean Agriculture

In this paper we present welfare estimates from a contingent valuation (CV) study which investigates the potential benefits derived by tourists from the implementation of a programme aimed at preserving the traditional agricultural landscape in a typical Mediterranean area: the National Park of Cilento (Southern Italy). Here, under current market conditions, farming activities are being gradually abandoned. As a result, the alternative to the cultivated landscape is a much less appealing one, where the various stages of progression of land abandonment dominate. To ease the cognitive task of respondents, CV responses were elicited using the discrete choice referendum format. To supplement the inherent inefficiency of discrete choice responses one follow-up question was also administered. The sample responses are analysed by three methods. First, by a log-normal model which allows a random utility interpretation. Then by a series of beta models, which require the definition of the maximum in the range of willingness to pay and reflect a purely statistical approach. Finally, by means of the non-parametric Kaplan-Meier-Turnbull probability estimates, which is robust to potential parametric mis-specifications. The welfare estimates obtained by various methods were similar and approached one Euro per day-visit. Our results indicate that referendum CV provides plausible estimates of WTP for agricultural landscape conservation from the tourists' population. From a conservative inference it appears that in 1997 the traditional farming produced a landscape externality for tourists which reached at least 8 million Euro. Provision of landscape is only one of many unremunerated activities provided by farmers, so more research should be aimed at valuing public goods produced by farming in recreationally valuable areas and elsewhere. We argue that the policy tools currently employed in the European Common Agricultural Policy, for the purpose of rural landscape preservation, are inadequate in the context of typical Mediterranean agriculture. Here the main cause of rural landscape deterioration seems to be the abandonment of agricultural production, rather than its intensification, so the main features of interest are other than those currently protected by EU policy.
Average plane-size in complex-representable matroids

Melchior's inequality implies that the average line-length in a simple, rank-$3$, real-representable matroid is less than $3$. A similar result holds for complex-representable matroids, using Hirzebruch's inequality, but with a weaker bound of $4$. We show that the average plane-size in a simple, rank-$4$, complex-representable matroid is bounded above by an absolute constant, unless the matroid is the direct-sum of two lines. We also prove that, for any integer $k$, in complex-representable matroids with rank at least $2k-1$, the average size of a rank-$k$ flat is bounded above by a constant depending only on $k$. Finally, we prove that, for any integer $r\ge 2$, the average flat-size in rank-$r$ complex-representable matroids is bounded above by a constant depending only on $r$. We obtain our results using a theorem, due to Ben Lund, that gives a good estimate on the number of rank-$k$ flats in a complex-representable matroid.
$(\epsilon, u)$-Adaptive Regret Minimization in Heavy-Tailed Bandits

Heavy-tailed distributions naturally arise in several settings, from finance to telecommunications. While regret minimization under subgaussian or bounded rewards has been widely studied, learning with heavy-tailed distributions only gained popularity over the last decade. In this paper, we consider the setting in which the reward distributions have finite absolute raw moments of maximum order $1+\epsilon$, uniformly bounded by a constant $u<+\infty$, for some $\epsilon \in (0,1]$. In this setting, we study the regret minimization problem when $\epsilon$ and $u$ are unknown to the learner and it has to adapt. First, we show that adaptation comes at a cost and derive two negative results proving that the same regret guarantees of the non-adaptive case cannot be achieved with no further assumptions. Then, we devise and analyze a fully data-driven trimmed mean estimator and propose a novel adaptive regret minimization algorithm, AdaR-UCB, that leverages such an estimator. Finally, we show that AdaR-UCB is the first algorithm that, under a known distributional assumption, enjoys regret guarantees nearly matching those of the non-adaptive heavy-tailed case.
LC-Score: Reference-less estimation of Text Comprehension Difficulty

Being able to read and understand written text is critical in a digital era. However, studies shows that a large fraction of the population experiences comprehension issues. In this context, further initiatives in accessibility are required to improve the audience text comprehension. However, writers are hardly assisted nor encouraged to produce easy-to-understand content. Moreover, Automatic Text Simplification (ATS) model development suffers from the lack of metric to accurately estimate comprehension difficulty. We present LC-SCORE, a simple approach for training text comprehension metric for any text without reference i.e. predicting how easy to understand a given text is on a [0, 100] scale. Our objective with this scale is to quantitatively capture the extend to which a text suits to the Langage Clair (LC, Clear Language) guidelines, a French initiative closely related to English Plain Language. We explore two approaches: (i) using linguistically motivated indicators used to train statistical models, and (ii) neural learning directly from text leveraging pre-trained language models. We introduce a simple proxy task for comprehension difficulty training as a classification task. To evaluate our models, we run two distinct human annotation experiments, and find that both approaches (indicator based and neural) outperforms commonly used readability and comprehension metrics such as FKGL.
GRAPPEL: A Graph-based Approach for Early Risk Assessment of Acute Hypertension in Critical Care

An acute hypertensive episode (AHE) refers to a period of extremely high blood pressure (BP) that can arise suddenly in critical care, and, if not identified early, can subject patients to the risk of severe organ damage and even potential mortality. The early assessment of AHE risk saves lives by enabling proactive medical intervention. We propose GRAPPEL, a novel graph-based approach that assesses a patient's risk of experiencing an AHE before it occurs based on the analysis of their BP recorded over time in critical care. Our algorithm consists of two major components: (1) the construction of a time-evolving graph representation of a patient's time-series BP data to encode the temporal BP variations into a graph and (2) the generation of real-time AHE risk scores based on quantifying the graph changes at each time step, triggered by the arrival of a new BP record. Notably, GRAPPEL provides real-time and early AHE risk assessment based solely on BP records that can be irregularly spaced in time, making it suitable for critical care environments. Via our extensive experiments on 3,476 critical-care visit records, we demonstrate the superiority of our approach over existing methods by achieving an AUC-ROC score of 91% in identifying patients at risk of experiencing an AHE up to 170 minutes in advance (and an AUC-ROC score of 94% up to 20 minutes in advance).
Identification of host factors for Rift Valley Fever Phlebovirus

Background Rift Valley fever phlebovirus (RVFV) is a zoonotic pathogen that causes Rift Valley fever (RVF) in livestock and humans. Currently, there is no licensed human vaccine or antiviral drug to control RVF. Although multiple species of animals and humans are vulnerable to RVFV infection, host factors affecting susceptibility are not well understood. Methodology To identify the host factors or genes essential for RVFV replication, we conducted a CRISPR-Cas9 knock-out screen in human A549 cells. We then validated the putative genes using siRNA-mediated knockdowns and CRISPR-Cas9-mediated knockout studies, respectively. The role of a candidate gene in the virus replication cycle was assessed by measuring intracellular viral RNA accumulation, and the virus titers by plaque assay or TCID50 assay. Findings We identified approximately 900 genes with potential involvement in RVFV infection and replication. Further evaluation of the effect of six genes on viral replication using siRNA-mediated knockdowns found that silencing two genes (WDR7 and LRP1) significantly impaired RVFV replication. For further analysis, we focused on the WDR7 gene since the role of LRP1 in RVFV replication was previously described in detail. Knock-out A549 cell lines were generated and used to dissect the effect of WRD7 on RVFV and another bunyavirus, La Crosse encephalitis virus (LACV). We observed significant effects of WDR7 knock-out cells on both intracellular RVFV RNA levels and viral titers. At the intracellular RNA level, WRD7 affected RVFV replication at a later phase of its replication cycle (24h) when compared to LACV which was affected an earlier replication phase (12h). Conclusion In summary, we have identified WDR7 as an essential host factor for the replication of two relevant bunyaviruses, RVFV and LACV. Future studies will investigate the mechanistic role by which WDR7 facilitates Phlebovirus replication. Authors Summary Rift Valley fever phlebovirus is a high consequence pathogen that infects multiple animal species and also humans. Currently, there are no control measures available to treat RVF in humans and to prevent the incursion of Rift Valley fever virus into non-endemic countries. RVFV poses a significant threat to animal and human health in countries where it is endemic. RVFV replication depends on the host’s machinery to complete its replication cycle. Therefore, one way to control virus replication is to disrupt the interaction between the virus and the host proteins important for replication. In this study, we identified a host factor, the WDR7 gene, that is critical for RVFV replication. The identification of this host factor is important as it can potentially lead to the development of antiviral strategies to control Rift Valley fever in both humans and animals.