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Mineral dust produced by wind erosion of arid and semi-arid surfaces is a major component of atmospheric aerosol that affects climate, weather, ecosystems, and socio-economic sectors such as human health, transportation, solar energy, and air quality. Understanding these effects and ultimately improving the resilience of affected countries requires a reliable, dense, and diverse set of dust observations, fundamental for the development and the provision of skillful dust forecasts tailored products. The last decade has seen a notable improvement of dust observational capabilities in terms of considered parameters, geographical coverage, and delivery times, as well as of tailored products of interest to both the scientific community and the various end-users. Given this progress, here we review the current state of observational capabilities including in-situ, ground-based and satellite remote sensing observations, in Northern Africa, the Middle East and Europe for the provision of dust information considering the needs of various users. We also critically discuss observational gaps and related unresolved questions while providing suggestions for overcoming the current limitations. Our review aims to be a milestone for discussing dust observational gaps at a global level to address the needs of users, from research communities to non-scientific stakeholders.

Traditional agroecological knowledge (i.e. TAeK) is gaining recognition for its potential contribution to climate change adaptation in food systems, ecosystems restoration and food insecurity. Despite the existing literature on Traditional Ecological Knowledge and its nexus with food security, how gender critically influences the distribution of such knowledge within agri-food systems has not yet been systematically analysed. In this regard, this systematic review attempts to answer four questions: 1) How does the literature on gender and TAeK in agri-food systems evolved temporally, geographically and in different agroecosystems? 2) How are gender and intersectionality mainly approached by such literature? 3) How do the articles address gendered dimensions in TAeK within the agri-food system activities? 4) What are the main drivers of change that influence TAeK and adaptive responses? The results show the gendered nature of TAeK in relation to food production, processing, and conservation activities, and how these activities are linked to tasks and activities, gender-specific knowledge, and spaces where gender discrimination is reproduced. The review also identifies elements that delimit and/or take part of the development of TAeK, such as gendered access to resources, gendered institutions, and the identification of the main drivers of change and impacts of TAeK erosion and biodiversity loss. These results are discussed in terms of power relations that interact with sociocultural norms and practices according to the specific geographical context and agroecosystem.

Socioeconomic-based affirmative action in higher education has gained importance following controversies over race-based alternatives. In many settings, these interventions use a school-based criterion that selects beneficiaries relative to their peers. Exploiting a nationwide quota policy in Brazil that reserved a large share of vacancies in higher education for public-school students, I show that the reform increases movements from private to public schools by 31% and that movers come disproportionately from low-SES and low-quality private schools. An exploration of the mechanisms shows that movers increase their future probability of higher education attendance at the expense of attending poorer and lower-performing public schools. The reform also leads to changes in school choice of indirectly exposed cohorts and general-equilibrium effects in the form of school closure.

Cardiovascular diseases are the leading death cause in Europe and entail large treatment costs. Cardiovascular risk prediction is crucial for the management and control of cardiovascular diseases. Based on a Bayesian network built from a large population database and expert judgment, this work studies interrelations between cardiovascular risk factors, emphasizing the predictive assessment of medical conditions, and providing a computational tool to explore and hypothesize such interrelations.

We present a robust framework with computational algorithms to support decision makers in sequential games. Our framework includes methods to solve games with complete information, assess the robustness of such solutions and, finally, approximate adversarial risk analysis solutions when lacking complete information. Existing simulation based approaches can be inefficient when dealing with large sets of feasible decisions; the game of interest may not even be solvable to the desired precision for continuous decisions. Hence, we provide a novel alternative solution method based on the use of augmented probability simulation. While the proposed framework conceptually applies to multi-stage sequential games, the discussion focuses on two-stage sequential defend-attack problems.

Adversarial Machine Learning (AML) is emerging as a major field aimed at protecting Machine Learning (ML) systems against security threats: in certain scenarios there may be adversaries that actively manipulate input data to fool learning systems. This creates a new class of security vulnerabilities that ML systems may face, and a new desirable property called adversarial robustness essential to trust operations based on ML outputs. Most work in AML is built upon a game-theoretic modeling of the conflict between a learning system and an adversary, ready to manipulate input data. This assumes that each agent knows their opponent’s interests and uncertainty judgments, facilitating inferences based on Nash equilibria. However, such common knowledge assumption is not realistic in the security scenarios typical of AML. After reviewing such game-theoretic approaches, we discuss the benefits that Bayesian perspectives provide when defending ML-based systems. We demonstrate how the Bayesian approach allows us to explicitly model our uncertainty about the opponent’s beliefs and interests, relaxing unrealistic assumptions, and providing more robust inferences. We illustrate this approach in supervised learning settings, and identify relevant future research problems. Supplementary materials for this article are available online.

The popular brain monitoring method of electroencephalography (EEG) has seen a surge in commercial attention in recent years, focusing mostly on hardware miniaturization. This has led to a varied landscape of portable EEG devices with wireless capability, allowing them to be used by relatively unconstrained users in real-life conditions outside of the laboratory. The wide availability and relative affordability of these devices provide a low entry threshold for newcomers to the field of EEG research. The large device variety and the at times opaque communication from their manufacturers, however, can make it difficult to obtain an overview of this hardware landscape. Similarly, given the breadth of existing (wireless) EEG knowledge and research, it can be challenging to get started with novel ideas. Therefore, this paper first provides a list of 48 wireless EEG devices along with a number of important—sometimes difficult-to-obtain—features and characteristics to enable their side-by-side comparison, along with a brief introduction to each of these aspects and how they may influence one's decision. Secondly, we have surveyed previous literature and focused on 110 high-impact journal publications making use of wireless EEG, which we categorized by application and analyzed for device used, number of channels, sample size, and participant mobility. Together, these provide a basis for informed decision making with respect to hardware and experimental precedents when considering new, wireless EEG devices and research. At the same time, this paper provides background material and commentary about pitfalls and caveats regarding this increasingly accessible line of research.

Empirical observations of how labs conduct research indicate that the adoption rate of open practices for transparent, reproducible, and collaborative science remains in its infancy. This is at odds with the overwhelming evidence for the necessity of these practices and their benefits for individual researchers, scientific progress, and society in general. To date, information required for implementing open science practices throughout the different steps of a research project is scattered among many different sources. Even experienced researchers in the topic find it hard to navigate the ecosystem of tools and to make sustainable choices. Here, we provide an integrated overview of community-developed resources that can support collaborative, open, reproducible, replicable, robust and generalizable neuroimaging throughout the entire research cycle from inception to publication and across different neuroimaging modalities. We review tools and practices supporting study inception and planning, data acquisition, research data management, data processing and analysis, and research dissemination. An online version of this resource can be found at https://oreoni.github.io. We believe it will prove helpful for researchers and institutions to make a successful and sustainable move towards open and reproducible science and to eventually take an active role in its future development.

The kinase suppressor of rat sarcoma (RAS) proteins (KSR1 and KSR2) have long been considered as scaffolding proteins required for optimal mitogen-activated protein kinase (MAPK) pathway signalling. However, recent evidence suggests that they play a more complex role within this pathway. Here, we demonstrate that ectopic expression of KSR1 or KSR2 is sufficient to activate the MAPK pathway and to induce cell proliferation in the absence of RAS proteins. In contrast, the ectopic expression of KSR proteins is not sufficient to induce cell proliferation in the absence of either rapidly accelerated fibrosarcoma (RAF) or MAPK-ERK kinase proteins, indicating that they act upstream of RAF. Indeed, KSR1 requires dimerization with at least one member of the RAF family to stimulate proliferation, an event that results in the translocation of the heterodimerized RAF protein to the cell membrane. Mutations in the conserved aspartic acid–phenylalanine–glycine motif of KSR1 that affect ATP binding impair the induction of cell proliferation. We also show that increased expression levels of KSR1 decrease the responsiveness to the KRASG12C inhibitor sotorasib in human cancer cell lines, thus suggesting that increased levels of expression of KSR may make tumour cells less dependent on KRAS oncogenic signalling.

[Background] The fungal pathogenBatrachochytrium dendrobatidis (Bd) threatens amphibian biodiversity and ecosystem stability worldwide. Amphibian skin microbial community structure has been linked to the clinical outcome of Bd infections, yet its overall functional importance is poorly understood. [Methods] Microbiome taxonomic and functional profiles were assessed using high-throughput bacterial 16S rRNA and fungal ITS2 gene sequencing, bacterial shotgun metagenomics and skin mucosal metabolomics. We sampled 56 wild midwife toads (Alytes obstetricans) from montane populations exhibiting Bd epizootic or enzootic disease dynamics. In addition, to assess whether disease-specific microbiome profiles were linked to microbe-mediated protection or Bd-induced perturbation, we performed a laboratory Bd challenge experiment whereby 40 young adult A. obstetricans were exposed to Bd or a control sham infection. We measured temporal changes in the microbiome as well as functional profiles of Bd-exposed and control animals at peak infection. [Results] Microbiome community structure and function differed in wild populations based on infection history and in experimental control versus Bd-exposed animals. Bd exposure in the laboratory resulted in dynamic changes in microbiome community structure and functional differences, with infection clearance in all but one infected animal. Sphingobacterium, Stenotrophomonas and an unclassified Commamonadaceae were associated with wild epizootic dynamics and also had reduced abundance in laboratory Bd-exposed animals that cleared infection, indicating a negative association with Bd resistance. This was further supported by microbe-metabolite integration which identified functionally relevant taxa driving disease outcome, of which Sphingobacterium and Bd were most influential in wild epizootic dynamics. The strong correlation between microbial taxonomic community composition and skin metabolome in the laboratory and field is inconsistent with

Social Ecological System (SES) research highlights the importance of understanding the potential of collective actions, among other factors, when it comes to influencing the transformative (re)configuration of agri-food systems in response to global change. Such a response may result in different desired outcomes for those actors who promote collective action, one such outcome being food sovereignty. In this study, we used an SES framework to describe the configuration of local agri-food systems in Andean Ecuador in order to understand which components of the SES interact, and how they support outcomes linked to five food sovereignty goals. Through a survey administered to mestizo and indigenous peasants, we analyze the key role played by the Agroecological Network of Loja (RAL) in transforming the local agri-food system through the implementation of a Participatory Guarantee System (PGS). This study demonstrates that participation in the RAL and PGS increases farmers’ adoption of agroecological practices, as well as their independence from non-traditional food. Additionally, RAL lobbying with the municipality significantly increases households’ on-farm income through access to local markets. Being part of indigenous communities also influences the configuration of the food system, increasing the participation in community work and access to credit and markets, thus positively affecting animal numbers, dairy production and income diversification. The complexity of the interactions described suggests that more research is needed to understand which key factors may foster or prevent the achieving of food sovereignty goals and promote household adaptation amid high uncertainty due to global change.

Anthropogenic mercury (Hg) undergoes long-range transport to the Arctic where some of it is transformed into methylmercury (MeHg), potentially leading to high exposure in some Arctic inhabitants and wildlife. The environmental exposure of Hg is determined not just by the amount of Hg entering the Arctic, but also by biogeochemical and ecological processes occurring in the Arctic. These processes affect MeHg uptake in biota by regulating the bioavailability, methylation and demethylation, bioaccumulation and biomagnification of MeHg in Arctic ecosystems. Here, we present a new budget for pools and fluxes of MeHg in the Arctic and review the scientific advances made in the last decade on processes leading to environmental exposure to Hg. Methylation and demethylation are key processes controlling the pool of MeHg available for bioaccumulation. Methylation of Hg occurs in diverse Arctic environments including permafrost, sediments and the ocean water column, and is primarily a process carried out by microorganisms. While microorganisms carrying the hgcAB gene pair (responsible for Hg methylation) have been identified in Arctic soils and thawing permafrost, the formation pathway of MeHg in oxic marine waters remains less clear. Hotspots for methylation of Hg in terrestrial environments include thermokarst wetlands, ponds and lakes. The shallow sub-surface enrichment of MeHg in the Arctic Ocean, in comparison to other marine systems, is a possible explanation for high MeHg concentrations in some Arctic biota. Bioconcentration of aqueous MeHg in bacteria and algae is a critical step in the transfer of Hg to top predators, which may be dampened or enhanced by the presence of organic matter. Variable trophic position has an important influence on MeHg concentrations among populations of top predator species such as ringed seal and polar bears distributed across the circumpolar Arctic. These scientific advances highlight key processes that affect the fate of anthropogenic Hg

Although widely used, standard game-theoretic approaches to security games face severe shortcomings, being the common knowledge assumption a critical one. Adversarial Risk Analysis (ARA) is an alternative modeling framework that mitigates such limitations. However, from a computational perspective, ARA is much more involved than its game theoretical counterparts. We propose an approach for finding ARA solutions to security games represented as bi-agent influence diagrams that is based on augmented probability simulation. We motivate this approach using two simple cases: sequential and simultaneous defend-attack models. We next provide the general framework and illustrate it in handling risks in a cybersecurity setting.

Current technology is unable to produce massively deployable, fully automated vehicles that do not require human intervention. Given that such limitations are projected to persist for decades, scenarios requiring a driver to assume control of a semiautomated vehicle, and vice versa, will remain a feature of modern roadways for the foreseeable future. Herein, we adopt a comprehensive perspective of this problem by simultaneously considering operational design domain supervision, driver and environment monitoring, trajectory planning, and driver-intervention performance assessment. More specifically, we develop a modeling framework for each of the aforementioned functions by leveraging decision analysis and Bayesian forecasting. Utilizing this framework, a suite of algorithms is subsequently proposed for driving-mode management and early warning emission, according to a management by exception principle. The efficacy of the developed methods is illustrated and examined via a simulated case study.

Most available results on optimal decisions under partial information are derived under “separation”. But this principle does not always hold. We derive a non-standard first order condition of optimality from first principles when signal extraction and optimal policy must be jointly determined. This allows us to solve a model of optimal fiscal policy where separation does not apply. Tax smoothing prevails in normal times, but taxes respond strongly in recessions. This non-linearity arises because signal extraction interacts differently with optimal policy depending on the value of the observed signals. Existing results based on the “separation principle” follow as special cases.

RNAs of different shapes and sizes, natural or synthetic, can regulate gene expression in prokaryotes and eukaryotes. Circular RNAs have recently appeared to be more widespread than previously thought, but their role in prokaryotes remains elusive. Here, by inserting a riboregulatory sequence within a group I permuted intron-exon ribozyme, we created a small noncoding RNA that self-splices to produce a circular riboregulator in Escherichia coli. We showed that the resulting riboregulator can trans-activate gene expression by interacting with a cis-repressed messenger RNA. We characterized the system with a fluorescent reporter and with an antibiotic resistance marker, and we modeled this novel posttranscriptional mechanism. This first reported example of a circular RNA regulating gene expression in E. coli adds to an increasing repertoire of RNA synthetic biology parts, and it highlights that topological molecules can play a role in the case of prokaryotic regulation.

Carbon‐based nanomaterials (CNMs) are being explored for neurological applications. However, systematic in vivo studies investigating the effects of CNM nanocarriers in the brain and how brain cells respond to such nanomaterials are scarce. To address this, functionalized multiwalled carbon nanotubes and graphene oxide (GO) sheets are injected in mice brain and compared with charged liposomes. The induction of acute neuroinflammatory and neurotoxic effects locally and in brain structures distant from the injection site are assessed up to 1 week postadministration. While significant neuronal cell loss and sustained microglial cell activation are observed after injection of cationic liposomes, none of the tested CNMs induces either neurodegeneration or microglial activation. Among the candidate nanocarriers tested, GO sheets appear to elicit the least deleterious neuroinflammatory profile. At molecular level, GO induces moderate activation of proinflammatory markers compared to vehicle control. At histological level, brain response to GO is lower than after vehicle control injection, suggesting some capacity for GO to reduce the impact of stereotactic injection on brain. While these findings are encouraging and valuable in the selection and design of nanomaterial‐based brain delivery systems, they warrant further investigations to better understand the mechanisms underlying GO immunomodulatory properties in brain.

In autosomal dominant optic atrophy (ADOA), caused by mutations in the mitochondrial cristae biogenesis and fusion protein optic atrophy 1 (Opa1), retinal ganglion cell (RGC) dysfunction and visual loss occur by unknown mechanisms. Here, we show a role for autophagy in ADOA pathogenesis. In RGCs expressing mutated Opa1, active 5’ AMP-activated protein kinase (AMPK) and its autophagy effector ULK1 accumulate at axonal hillocks. This AMPK activation triggers localized hillock autophagosome accumulation and mitophagy, ultimately resulting in reduced axonal mitochondrial content that is restored by genetic inhibition of AMPK and autophagy. In C. elegans, deletion of AMPK or of key autophagy and mitophagy genes normalizes the axonal mitochondrial content that is reduced upon mitochondrial dysfunction. In conditional, RGC specific Opa1-deficient mice, depletion of the essential autophagy gene Atg7 normalizes the excess autophagy and corrects the visual defects caused by Opa1 ablation. Thus, our data identify AMPK and autophagy as targetable components of ADOA pathogenesis.

Three-dimensional (3D) scaffolds with tailored stiffness, porosity, and conductive properties are particularly important in tissue engineering for electroactive cell attachment, proliferation, and vascularization. Carbon nanotubes (CNTs) and poly(3,4-ethylenedioxythiophene) (PEDOT) have been extensively used separately as neural interfaces showing excellent results. Herein, we combine both the materials and manufacture 3D structures composed exclusively of PEDOT and CNTs using a methodology based on vapor phase polymerization of PEDOT onto a CNT/sucrose template. Such a strategy presents versatility to produce porous scaffolds, after leaching out the sucrose grains, with different ratios of polymer/CNTs, and controllable and tunable electrical and mechanical properties. The resulting 3D structures show Young’s modulus typical of soft materials (20–50 kPa), as well as high electrical conductivity, which may play an important role in electroactive cell growth. The conductive PEDOT/CNT porous scaffolds present high biocompatibility after 3 and 6 days of C8-D1A astrocyte incubation.

Standard optimal Debt Management (DM) models prescribe a dominant role for long bonds and advocate against issuing short bonds. They require very large positions in order to complete markets and assume each period that governments repurchase all outstanding bonds and reissue (r/r) new ones. These features of DM are inconsistent with U.S. data. We introduce incomplete markets via small transaction costs which serves to make optimal DM more closely resemble the data : r/r are negligible, short bond issuance substantial and persistent and short and long bonds positively co-vary. Intuitively, long bonds help smooth taxes over states and short bonds over time. Solving incomplete market models with multiple assets is challenging so a further contribution of this article is introducing a novel computational method to find global solutions.

CIC (also known as Capicua) is a transcriptional repressor negatively regulated by RAS/MAPK signaling. Whereas the functions of Cic have been well characterized in Drosophila, little is known about its role in mammals. CIC is inactivated in a variety of human tumors and has been implicated recently in the promotion of lung metastases. Here, we describe a mouse model in which we inactivated Cic by selectively disabling its DNA-binding activity, a mutation that causes derepression of its target genes. Germline Cic inactivation causes perinatal lethality due to lung differentiation defects. However, its systemic inactivation in adult mice induces T-cell acute lymphoblastic lymphoma (T-ALL), a tumor type known to carry CIC mutations, albeit with low incidence. Cic inactivation in mice induces T-ALL by a mechanism involving derepression of its well-known target, Etv4. Importantly, human T-ALL also relies on ETV4 expression for maintaining its oncogenic phenotype. Moreover, Cic inactivation renders T-ALL insensitive to MEK inhibitors in both mouse and human cell lines. Finally, we show that Ras-induced mouse T-ALL as well as human T-ALL carrying mutations in the RAS/MAPK pathway display a genetic signature indicative of Cic inactivation. These observations illustrate that CIC inactivation plays a key role in this human malignancy

Runway excursions at landing constitute a major threat to aviation safety. Among them, runway overruns, defined as those occurrences when an aircraft departs the end of a runway, are the most frequent events. Although their occurrence rate is low, the entailed consequences may be very severe in terms of lives and aircraft damage. The main contributing factors to this event and their relationships are studied with the aid of a Bayesian network, while also modeling the nodes' conditional distributions. Then, inferences and predictions are made for the quantities of interest. The issues uncovered suggest several operational recommendations to reduce the probability of facing a runway overrun when landing.

Stackelberg Games are gaining importance in the last years due to the raise of Adversarial Machine Learning (AML). Within this context, a new paradigm must be faced: in classical game theory, intervening agents were humans whose decisions are generally discrete and low dimensional. In AML, decisions are made by algorithms and are usually continuous and high dimensional, e.g. choosing the weights of a neural network. As closed form solutions for Stackelberg games generally do not exist, it is mandatory to have efficient algorithms to search for numerical solutions. We study two different procedures for solving this type of games using gradient methods. We study time and space scalability of both approaches and discuss in which situation it is more appropriate to use each of them. Finally, we illustrate their use in an adversarial prediction problem.

The use of graphene-based materials to engineer sophisticated biosensing interfaces that can adapt to the central nervous system requires a detailed understanding of how such materials behave in a biological context. Graphene’s peculiar properties can cause various cellular changes, but the underlying mechanisms remain unclear. Here, we show that single-layer graphene increases neuronal firing by altering membrane-associated functions in cultured cells. Graphene tunes the distribution of extracellular ions at the interface with neurons, a key regulator of neuronal excitability. The resulting biophysical changes in the membrane include stronger potassium ion currents, with a shift in the fraction of neuronal firing phenotypes from adapting to tonically firing. By using experimental and theoretical approaches, we hypothesize that the graphene–ion interactions that are maximized when single-layer graphene is deposited on electrically insulating substrates are crucial to these effects.

The transcriptional repressor Capicua (CIC) has emerged as an important rheostat of cell growth regulated by RAS/MAPK signaling. Cic was originally discovered inDrosophila, where it was shown to be inactivated by MAPK signaling downstream of the RTKs Torso and EGFR, which results in signal-dependent responses that are required for normal cell fate specification, proliferation and survival of developing and adult tissues. CIC is highly conserved in mammals, where it is also negatively regulated by MAPK signaling. Here, we review the roles of CIC during mammalian development, tissue homeostasis, tumor formation and therapy resistance. Available data indicate that CIC is involved in multiple biological processes, including lung development, liver homeostasis, autoimmunity and neurobehavioral processes. Moreover, CIC has been shown to be involved in tumor development as a tumor suppressor, both in human as well as in mouse models. Finally, several lines of evidence implicate CIC as a determinant of sensitivity to EGFR and MAPK pathway inhibitors, suggesting that CIC may play a broader role in human cancer than originally anticipated

A new kind of fluorescent organic nanoparticles (FONs) is obtained using quatsomes (QSs), a family of nanovesicles proposed as scaffolds for the nanostructuration of commercial lipophilic carbocyanines (1,1′‐dioctadecyl‐3,3,3′,3′‐tetramethyl‐indocarbocyanine perchlorate (DiI), 1,1′‐dioctadecyl‐3,3,3′,3′‐tetramethyl‐indodicarbocyanine perchlorate (DiD), and 1,1′‐dioctadecyl‐3,3,3′,3′‐tetramethyl‐indotricarbocyanine iodide (DiR)) in aqueous media. The obtained FONs, prepared by a CO2‐based technology, show excellent colloidal‐ and photostability, outperforming other nanoformulations of the dyes, and improve the optical properties of the fluorophores in water. Molecular dynamics simulations provide an atomistic picture of the disposition of the dyes within the membrane. The potential of QSs for biological imaging is demonstrated by performing superresolution microscopy of the DiI‐loaded vesicles in vitro and in cells. Therefore, fluorescent QSs constitute an appealing nanomaterial for bioimaging applications.

[EN] Synthetic gene circuits allow the behavior of living cells to be reprogrammed, and non-coding small RNAs (sRNAs) are increasingly being used as programmable regulators of gene expression. However, sRNAs (natural or synthetic) are generally used to regulate single target genes, while complex dynamic behaviors would require networks of sRNAs regulating each other. Here, we report a strategy for implementing such networks that exploits hybridization reactions carried out exclusively by multifaceted sRNAs that are both targets of and triggers for other sRNAs. These networks are ultimately coupled to the control of gene expression. We relied on a thermo-dynamic model of the different stable conformational states underlying this system at the nucleotide level. To test our model, we designed five different RNA hybridization networks with a linear architecture, and we implemented them in Escherichia coli. We validated the network architecture at the molecular level by native polyacrylamide gel electrophoresis, as well as the network function at the bacterial population and single-cell levels with a fluorescent reporter. Our results suggest that it is possible to engineer complex cellular programs based on RNA from first principles. Because these networks are mainly based on physical interactions, our designs could be expanded to other organisms as portable regulatory resources or to implement biological computations.

HMG-box proteins, including Sox/SRY (Sox) and TCF/LEF1 (TCF) family members, bind DNA via their HMG-box. This binding, however, is relatively weak and both Sox and TCF factors employ distinct mechanisms for enhancing their affinity and specificity for DNA. Here we report that Capicua (CIC), an HMG-box transcriptional repressor involved in Ras/MAPK signaling and cancer progression, employs an additional distinct mode of DNA binding that enables selective recognition of its targets. We find that, contrary to previous assumptions, the HMG-box of CIC does not bind DNA alone but instead requires a distant motif (referred to as C1) present at the C-terminus of all CIC proteins. The HMG-box and C1 domains are both necessary for binding specific TGAATGAA-like sites, do not function via dimerization, and are active in the absence of cofactors, suggesting that they form a bipartite structure for sequence-specific binding to DNA. We demonstrate that this binding mechanism operates throughout Drosophila development and in human cells, ensuring specific regulation of multiple CIC targets. It thus appears that HMG-box proteins generally depend on auxiliary DNA binding mechanisms for regulating their appropriate genomic targets, but that each sub-family has evolved unique strategies for this purpose. Finally, the key role of C1 in DNA binding also explains the fact that this domain is a hotspot for inactivating mutations in oligodendroglioma and other tumors, while being preserved in oncogenic CIC-DUX4 fusion chimeras associated to Ewing-like sarcomas

To successfully develop biomedical applications for magnetic nanoparticles, it is imperative that these nanoreagents maintain their magnetic properties in vivo and that their by-products are safely metabolized. When placed in biological milieu or internalized into cells, nanoparticle aggregation degree can increase which could affect magnetic properties and metabolization. To evaluate these aggregation effects, we synthesized citric acid-coated iron oxide nanoparticles whose magnetic susceptibility can be modified by aggregation in agar dilutions and dextran-layered counterparts that maintain their magnetic properties unchanged. Macrophage models were used for in vitro uptake and metabolization studies, as these cells control iron homeostasis in the organism. Electron microscopy and magnetic susceptibility studies revealed a cellular mechanism of nanoparticle degradation, in which a small fraction of the particles is rapidly degraded while the remaining ones maintain their size. Both nanoparticle types produced similar iron metabolic profiles but these profiles differed in each macrophage model. Thus, nanoparticles induced iron responses that depended on macrophage programming. In vivo studies showed that nanoparticles susceptible to changes in magnetic properties through aggregation effects had different behavior in lungs, liver and spleen. Liver ferritin levels increased in these animals showing that nanoparticles are degraded and their by-products incorporated into normal metabolic routes. These data show that nanoparticle iron metabolization depends on cell type and highlight the necessity to assess nanoparticle aggregation in complex biological systems to develop effective in vivo biomedical applications. Statement of Significance Magnetic iron oxide nanoparticles have great potential for biomedical applications. It is however imperative that these nanoreagents preserve their magnetic properties once inoculated, and that their degradation products can be elimin

Genetic studies in mice have provided evidence that H-Ras and K-Ras proteins are bioequivalent. However, human tumors display marked differences in the association of RAS oncogenes with tumor type. Thus, to further assess the bioequivalence of oncogenic H-Ras and K-Ras, we replaced the coding region of the murine K-Ras locus with H-Ras oncogene sequences. Germline expression of H-Ras or K-Ras from the K-Ras locus resulted in embryonic lethality. However, expression of these genes in adult mice led to different tumor phenotypes. Whereas H-Ras elicited papillomas and hematopoietictumors, K-Ras induced lung tumors and gastric lesions. Pulmonary expression of H-Ras created a senescence-like state caused by excessive MAPK signaling. Likewise, H-Ras but not K-Ras induced senescence in mouse embryonic fibroblasts. Label-free quantitative analysis revealed that minor differences in H-Ras expression levels led to drastically different biological outputs, suggesting that subtle differences in MAPK signaling confer nonequivalent functions that influence tumor spectra induced by RAS oncoproteins.

This work describes the snow and meteorological dataset available for the Izas Experimental Catchment, in the Central Spanish Pyrenees, from 2011 to 2016 snow seasons. The experimental site is located in the southern side of the Pyrenees between 2000 and 2300 m above sea level with an extension of 55 ha. The site is a good example of sub-alpine ambient in which snow accumulation and melting dynamics have major importance in many mountain processes. The climatic dataset includes information on different meteorological variables acquired with an Automatic Weather Station (AWS) such as precipitation, air temperature, incoming and reflected short and long-wave radiation, relative humidity, wind speed and direction, atmospheric air pressure, surface temperature (snow or soil surface) and soil temperature; all of them at 10 minute intervals. Snow depth distribution was measured during 23 field campaigns using a Terrestrial Laser Scanner (TLS), and there is also available daily information of the Snow Covered Area (SCA) retrieved from time-lapse photography. The data set (https://doi.org/10.5281/zenodo.579979) is valuable since it provides high spatial resolution information on the snow depth and snow cover distribution, which is particularly useful in combination with meteorological variables to simulate the snow energy and mass balance. This information has already been analyzed in different scientific works studying snow pack dynamics and its interaction with the local climatology or terrain topographic characteristics. However, the database generated till the date has great potential for understanding other environmental processes from a hydrometerological or ecological perspective in which snow dynamics play a determinant role.

Adversarial risk analysis (ARA) provides a framework to deal with risks originating from intentional actions of adversaries. We show how ARA may be used to allocate security resources in the protection of urban spaces. We take into account the spatial structure and consider both proactive and reactive measures, in that we aim at both trying to reduce criminality as well as recovering as best as possible from it, should it happen. We deal with the problem by deploying an ARA model over each spatial unit, coordinating the models through resource constraints, value aggregation, and proximity. We illustrate our approach with an example that uncovers several relevant policy issues.

Friedreich's ataxia (FRDA), the most commonly inherited ataxia in populations of European origin, is a neurodegenerative disorder caused by a decrease in frataxin levels. One of the hallmarks of the disease is the accumulation of iron in several tissues including the brain, and frataxin has been proposed to play a key role in iron homeostasis. We found that the levels of zinc, copper, manganese and aluminum were also increased in a Drosophila model of FRDA, and that copper and zinc chelation improve their impaired motor performance. By means of a candidate genetic screen, we identified that genes implicated in iron, zinc and copper transport and metal detoxification can restore frataxin deficiency-induced phenotypes. Taken together, these results demonstrate that the metal dysregulation in FRDA includes other metals besides iron, therefore providing a new set of potential therapeutic targets.

In this paper we study the role of religiosity in influencing the choice of labor effort. Many religions promote restrictions on personal liberties such as divorce, abortion, gender parity, or gay marriage. We assume that the higher the degree of religiosity of an individual the less he enjoys such personal liberties, and moreover the less he likes to be in a society which allows such liberties. The model implies that under some simple conditions, individual labor supply is decreasing in the level of religiosity and that this negative relationship is enhanced by the width of liberties. We show empirically that this holds and that the size of the effect is large. Specifically, we construct an index of personal liberties and find solid evidence in support of the joint effect of religiosity and liberties on labor effort. Our empirical results indicate that negative externalities experienced by religious individuals when society allows for or practices such personal liberties are an important part of the effect of liberties on their economic choices

We report efficient vortex pinning in thickness-modulated tungsten-carbon-based (W-C) nanostructures grown by focused ion beam induced deposition (FIBID). By using FIBID, W-C superconducting films have been created with thickness modulation properties exhibiting periodicity from 60 to 140 nm, leading to a strong pinning potential for the vortex lattice. This produces local minima in the resistivity up to high magnetic fields (2.2 T) in a broad temperature range due to commensurability effects between the pinning potential and the vortex lattice. The results show that the combination of single-step FIBID fabrication of superconducting nanostructures with built-in artificial pinning landscapes and the small intrinsic random pinning potential of this material produces strong periodic pinning potentials, maximizing the opportunities for the investigation of fundamental aspects in vortex science under changing external stimuli (e.g., temperature, magnetic field, electrical current).

We show that consumption-based asset pricing models with time-separable preferences generate realistic amounts of stock price volatility if one allows for small deviations from rational expectations. Rational investors with subjective beliefs about price behavior optimally learn from past price observations. This imparts momentum and mean reversion into stock prices. The model quantitatively accounts for the volatility of returns, the volatility and persistence of the price-dividend ratio, and the predictability of long-horizon returns. It passes a formal statistical test for the overall fit of a set of moments provided one excludes the equity premium.

Telomeres are specialized nucleoprotein caps that protect chromosome ends assuring cell division. Single-cell telomere quantification in animals established a critical role for telomerase in stem cells, yet, in plants, telomere-length quantification has been reported only at the organ level. Here, a quantitative analysis of telomere length of single cells in Arabidopsis root apex uncovered a heterogeneous telomere-length distribution of different cell lineages showing the longest telomeres at the stem cells. The defects in meristem and stem cell renewal observed in tert mutants demonstrate that telomere lengthening by TERT sets a replicative limit in the root meristem. Conversely, the long telomeres of the columella cells and the premature stem cell differentiation plt1,2 mutants suggest that differentiation can prevent telomere erosion. Overall, our results indicate that telomere dynamics are coupled to meristem activity and continuous growth, disclosing a critical association between telomere length, stem cell function, and the extended lifespan of plants.

Recent developments indicate that magnetic nanoparticles could help to improve clinical practice in the treatment of cancer, most probably in synergy with other conventional treatments [1]. There already exist methods to obtain magnetic nanoparticles with the appropriate properties to be used in diagnosis and therapy but these properties need to be optimized to avoid its alteration after intravenous injection, via interaction between the nanoparticles and the blood components, aggregation in lysosomes inside cells or accumulation in tissues [2]. In this work we will describe a number of proven synthesis routes for magnetic nanoparticles intended for their use in biomedical applications [3]. We will show the effect of different characteristics of the magnetic colloids, such as particle size and size distribution, colloidal properties of the aqueous suspensions, such as hydrodynamic size and surface modification, and magnetic properties on their MRI relaxivity and heating capacity. Finally, it will be shown that magnetic nanoparticles biodistribution following systemic administration and its transformation over time can be tracked by AC magnetic susceptibility measurements, which allow identifying and quantifying magnetic nanoparticles in tissues, differentiating them from other endogenous species such as the ferritin iron cores [4].

Bone marrow, spleen, liver and kidney proton transverse relaxation rates (R2), together with cardiac R2 from patients with sickle cell disease (SCD), paroxysmal nocturnal hemoglobinuria (PNH) and non-transfusion dependent thalassemia (NTDT) have been compared with a control group. Increased liver and bone marrow R2 values for the three groups of patients in comparison with the controls have been found. SCD and PNH patients also present an increased spleen R2 in comparison with the controls. The simultaneous measurement of R2 values for several tissue types by magnetic resonance imaging (MRI) has allowed the identification of iron distribution patterns in diseases associated with iron imbalance. Preferential liver iron loading is found in the highly transfused SCD patients, while the low transfused ones present a preferential iron loading of the spleen. Similar to the highly transfused SCD group, PNH patients preferentially accumulate iron in the liver. A reduced spleen iron accumulation in comparison with the liver and bone marrow loading has been found in NTDT patients, presumably related to the differential increased intestinal iron absorption. The correlation between serum ferritin and tissue R2 is moderate to good for the liver, spleen and bone marrow in SCD and PNH patients. However, serum ferritin does not correlate with NTDT liver R2, spleen R2 or heart R2. As opposed to serum ferritin measurements, tissue R2 values are a more direct measurement of each tissue's iron loading. This kind of determination will allow a better understanding of the different patterns of tissue iron biodistribution in diseases predisposed to tissue iron accumulation.

This study investigated the ability for magnetic nanoparticles to influence cellular migration in the presence of an external magnetic field. We found that the direction of migrating keratinocytes can be controlled and the migration speed of fibroblasts can be increased with the internalisation of these nanoparticles in the presence of a magnetic field. The possibility of shepherding cells towards a region of interest through the use of internalized nanoparticles is an attractive prospect for cell tracking, cell therapies, and tissue engineering applications.

Long-term in vivo studies in murine models have shown that DMSA-coated nanoparticles accumulate in spleen, liver and lung tissues during extended periods of time (at least up to 3 months) without any significant signs of toxicity detected. During that time, nanoparticles undergo a process of biotransformation either by reducing the size or the particle aggregation or both. Using a rat model, we have evaluated the transformations of magnetic nanoparticles injected at low doses. Particles with two different coatings, dimercaptosuccinic acid (NP-DMSA) and polyethylene glycol (NP-PEG-(NH2)2) have been administered to animals, to evaluate the role of coating in the degradation of the particles. We have found that low doses of magnetic nanoparticles are quickly metabolized by the animals. In fact, using a nanoparticle dose four times lower than in previous experiments, NP-DMSA were not observed 24 h after the administration either in the liver or in the lungs. Interestingly, an increased amount of ferritin, the iron storage protein, was observed in liver tissues from rats that were treated with the low dose of NP-DMSA in comparison with the control ones, suggesting a rapid metabolization of the particles into ferritin iron. On the other side we have found that, NP-PEG-(NH2)2 are still detectable in several organs 24 h after their administration at low doses. Probably, due to the longer circulation times of the NP-PEG-(NH2)2, there is a delay in the arrival of the particles to the tissue and this is the reason why we are able to see the particles 24 h post-administration. PEG coating could also be protecting the nanoparticles from rapid degradation of the reticuloendothelial system. Knowledge on the biodistribution, circulation time and degradation processes is required to gain a better understanding of the safety evaluation of this kind of nanomaterial for biomedical applications.

Schistosomiasis is a chronic parasitic disease of humans, with two species primarily causing the intestinal infection: Schistosoma mansoni and Schistosoma japonicum. Traditionally, diagnosis of schistosomiasis is achieved through direct visualisation of eggs in faeces using techniques that lack the sensitivity required to detect all infections, especially in areas of low endemicity. A recently developed method termed Helmintex™ is a very sensitive technique for detection of Schistosoma eggs and exhibits 100% sensitivity at 1.3 eggs per gram of faeces, enough to detect even low-level infections. The Helminthex™ method is based on the interaction of magnetic microspheres and schistosome eggs. Further understanding the underlying egg-microsphere interactions would enable a targeted optimisation of egg-particle binding and may thus enable a significant improvement of the Helmintex™ method and diagnostic sensitivity in areas with low infection rates. We investigated the magnetic properties of S. mansoni and S. japonicum eggs and their interactions with microspheres with different magnetic properties and surface functionalization. Eggs of both species exhibited higher binding affinity to the magnetic microspheres than the non-magnetic microspheres. Binding efficiency was further enhanced if the particles were coated with streptavidin. Schistosoma japonicum eggs bound more microspheres compared with S. mansoni. However, distinct differences within eggs of each species were also observed when the distribution of the number of microspheres bound per egg was modelled with double Poisson distributions. Using this approach, both S. japonicum and S. mansoni eggs fell into two groups, one having greater affinity for magnetic microspheres than the other, indicating that not all eggs of a species exhibit the same binding affinity. Our observations suggest that interaction between the microspheres and eggs is more likely to be related to surface charge-based electrostatic interactio

© 2015 Elsevier Ltd. The Mediterranean Sea is a hotspot for invasive species and projected Mediterranean warming might affect their future spreading. We experimentally examined ecophysiological responses to the temperature range 23-31. °C in three invasive seaweeds commonly found in the Mediterranean: Acrothamnion preissii, Caulerpa cylindracea and Lophocladia lallemandii. The warming range tested encompassed current and projected (for the end of 21st Century) maximum temperatures for the Mediterranean Sea. Optimal ecophysiological temperatures for A. preissii, C. cylindracea and L. lallemandii were 25. °C, 27. °C and 29. °C, respectively. Warming below the optimal temperatures enhanced RGR of all studied invasive seaweeds. Although sensitive, seaweed photosynthetic yield was less temperature-dependent than growth. Our results demonstrate that temperature is a key environmental parameter in regulating the ecophysiological performance of these invasive seaweeds and that Mediterranean warming conditions may affect their invasion trajectory.

We review current synthetic routes to magnetic iron oxide nanoparticles for biomedical applications. We classify the different approaches used depending on their ability to generate magnetic particles that are either single-core (containing only one magnetic core, i.e. a single domain nanocrystal) or multi-core (containing several magnetic cores, i.e. single domain nanocrystals). The synthesis of single-core magnetic nanoparticles requires the use of surfactants during the particle generation, and careful control of the particle coating to prevent aggregation. Special attention has to be paid to avoid the presence of any toxic reagents after the synthesis if biomedical applications are intended. Several approaches exist to obtain multi-core particles based on the coating of particle aggregates; nevertheless, the production of multi-core particles with good control of the number of magnetic cores per particle, and of the degree of polydispersity of the core sizes, is still a difficult task. The control of the structure of the particles is of great relevance for biomedical applications as it has a major influence on the magnetic properties of the materials.

[Background] A deeper knowledge on the effects of the degradation of magnetic nanoparticles on their magnetic properties is required to develop tools for the identification and quantification of magnetic nanoparticles in biological media by magnetic means., [Methods] Citric acid and phosphonoacetic acid-coated magnetic nanoparticles have been degraded in a medium that mimics lysosomal conditions. Magnetic measurements and transmission electron microscopy have been used to follow up the degradation process., [Results] Particle size is reduced significantly in 24 h at pH 4.5 and body temperature. These transformations affect the magnetic properties of the compounds. A reduction of the interparticle interactions is observed just 4 h after the beginning of the degradation process. A strong paramagnetic contribution coming from the degradation products appears with time., [Conclusions] A model for the in vivo degradation of magnetic nanoparticles has been followed to gain insight on the changes of the magnetic properties of iron oxides during their degradation. The degradation kinetics is affected by the particle coating, in our case being the phosphonoacetic acid-coated particles degraded faster than the citric acid-coated ones.

We provide a model of conflict and mass killing decisions to identify the key variables and situations that make mass killings more likely to occur. We predict that mass killings are most likely in countries with large amounts of natural resource rents, polarization, institutional constraints regarding rent sharing, and low productivity of labor. The role of resources such as oil, gas, and diamonds and other key determinants of mass killings is confirmed by our empirical results based on countrylevel as well as ethnic group–level analysis

© Oxford University Press 2015. All rights reserved. This article employs a Bayesian methodology to measure the uncertainty involved in the long-run holding of the purchasing power parity (PPP) and in the half-life (HL) of deviations from it. Our Bayesian approach combines estimates obtained from ARMA, ARFIMA, and ARIMA specifications so that it is able to take into account model uncertainty. Exact posterior distributions corresponding to all the features of interest (fractional orders of integration, impulse responses, HLs, etc.) are derived. Our results suggest that model uncertainty is high, which implies that uncertainty estimates can be severely biased downwards when the former is not explicitly considered. In spite of that, support for the long-run holding of the PPP is substantial in most countries. However, the speed at which this happens seems to be much slower than what has been suggested, as shown by the fact that the probability of the HL lying in the three- to five-year interval is very small.

The Mediterranean climate is expected to become warmer and drier during the twenty-first century. Mediterranean Sea response to climate change could be modulated by the choice of the socio-economic scenario as well as the choice of the boundary conditions mainly the Atlantic hydrography, the river runoff and the atmospheric fluxes. To assess and quantify the sensitivity of the Mediterranean Sea to the twenty-first century climate change, a set of numerical experiments was carried out with the regional ocean model NEMOMED8 set up for the Mediterranean Sea. The model is forced by air–sea fluxes derived from the regional climate model ARPEGE-Climate at a 50-km horizontal resolution. Historical simulations representing the climate of the period 1961–2000 were run to obtain a reference state. From this baseline, various sensitivity experiments were performed for the period 2001–2099, following different socio-economic scenarios based on the Special Report on Emissions Scenarios. For the A2 scenario, the main three boundary forcings (river runoff, near-Atlantic water hydrography and air–sea fluxes) were changed one by one to better identify the role of each forcing in the way the ocean responds to climate change. In two additional simulations (A1B, B1), the scenario is changed, allowing to quantify the socio-economic uncertainty. Our 6-member scenario simulations display a warming and saltening of the Mediterranean. For the 2070–2099 period compared to 1961–1990, the sea surface temperature anomalies range from +1.73 to +2.97 °C and the SSS anomalies spread from +0.48 to +0.89. In most of the cases, we found that the future Mediterranean thermohaline circulation (MTHC) tends to reach a situation similar to the eastern Mediterranean Transient. However, this response is varying depending on the chosen boundary conditions and socio-economic scenarios. Our numerical experiments suggest that the choice of the near-Atlantic surface water evolution, which is very uncertain in Ge