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A 46-year-old woman was troubled by a 3-year history of constant headaches and arthralgias. She was treated with paracetamol with no symptom resolution. An abnormal fasting glucose level prompted endocrine evaluation. On physical examination, she casually mentioned that her wedding ring no longer fit, and she also confirmed an increase in shoe size. There were no characteristic facial features for acromegaly and there was no evidence of acral enlargement. Biochemical evaluation, including insulin-like growth factor type 1 (IGF-1) measurement and oral glucose loading with growth hormone (GH) measurement confirmed excess GH production and a diagnosis of acromegaly. Pituitary magnetic resonance imaging showed a central pituitary microadenoma. After transsphenoidal surgical resection, tissue immunohistochemistry revealed a densely granulated somatotroph adenoma. Currently, the patient is asymptomatic with biochemical disease control, normal fasting glucose levels, and no pituitary hormone deficiencies. This patient is illustrative of a type 1 acromegaly with mild clinical manifestations. Clinicians should be aware of acromegaly subtypes to avoid delay in diagnosis and to individualize therapy. [ABSTRACT FROM AUTHOR]

Sense of Community is one of the most researched processes in Community Psychology. Since its initial formulation, belonging to broader social and geographical structures has been part of the definition of the concept. Research on the topic has tended to focus on the analysis of the environmental and collective factors that modulate the integration of individuals into groups and communities and has paid less attention to the individual aspects that guide the direct interactions that people have in these spaces. In this study we analyse the relationship between individual attachment styles and personality traits on the sense of community in 305 respondents from different neighborhoods in Seville (Spain) and Barranquilla (Colombia). The results show a modest predictive effect of secure attachment style and agreeableness mainly on the self and belonging dimensions of sense of community. These results show the need to take into account different levels of analysis in the assessment of belonging to community contexts and the usefulness of defining models that include the interaction of individual and contextual factors in their explanation. [ABSTRACT FROM AUTHOR]

This article describes the design of the "First Comprehensive Strategic Plan for Volunteering and Citizen Participation in Andalusia," which establishes the priorities and strategies for promoting citizen engagement in the Autonomous Community of southern Spain. The drawing up of the strategic plan was developed in two phases. First, a theoretical analysis of the effective practices for promoting citizen participation was conducted. Second, the opinion of a total of 35 representatives of Third Sector organizations was obtained. The review of evidence‐based practices made it possible to identify 13 basic strategies for community awareness, education for participation, volunteer management, and the development of inter‐organizational networks. Next, 19 interviews were conducted with representatives of the most prominent social entities in the region and two participatory workshops with 16 leaders of the volunteer movement in Andalusia were held. The results showed the existence of a consolidated social fabric, with a "community of practice" constituted over two decades in which awareness‐raising and training strategies have been effectively combined to promote volunteering. Representatives of the Third Sector consider educational strategies for participation as a priority, such as service‐learning, early participation experiences during adolescence and the training of volunteers and members of associations. On the other hand, although social organizations are aware of the need to adapt to new forms of participation (more individualized, one‐off, or episodic), they generally defend strategies that contribute to a higher level of organizational commitment. The resulting plan integrates measures to promote participation and volunteering through cross‐cutting actions. [ABSTRACT FROM AUTHOR]

DNA barcoding is a powerful method for the identification of lichenized fungi groups for which the diversity is already well-represented in nucleotide databases, and an accurate, robust taxonomy has been established. However, the effectiveness of DNA barcoding for identification is expected to be limited for understudied taxa or regions. One such region is Antarctica, where, despite the importance of lichens and lichenized fungi identification, their genetic diversity is far from characterized. The aim of this exploratory study was to survey the lichenized fungi diversity of King George Island using a fungal barcode marker as an initial identification tool. Samples were collected unrestricted to specific taxa in coastal areas near Admiralty Bay. Most samples were identified using the barcode marker and verified up to the species or genus level with a high degree of similarity. A posterior morphological evaluation focused on samples with novel barcodes allowed for the identification of unknown Austrolecia, Buellia, and Lecidea s.l. species. These results contribute to better represent the lichenized fungi diversity in understudied regions such as Antarctica by increasing the richness of the nucleotide databases. Furthermore, the approach used in this study is valuable for exploratory surveys in understudied regions to guide taxonomic efforts towards species recognition and discovery. [ABSTRACT FROM AUTHOR]

Dystrophin Dp71 is the most abundant product of the Duchenne muscular dystrophy gene in the nervous system, and mutations impairing its function have been associated with the neurodevelopmental symptoms present in a third of DMD patients. Dp71 is required for the clustering of neurotransmitter receptors and the neuronal differentiation of cultured cells; nonetheless, its precise role in neuronal cells remains to be poorly understood. In this study, we analyzed the effect of two pathogenic DMD gene point mutations on the Dp71 function in neurons. We engineered C272Y and E299del mutations to express GFP-tagged Dp71 protein variants in N1E-115 and SH-SY5Y neuronal cells. Unexpectedly, the ectopic expression of Dp71 mutants resulted in protein aggregation, which may be mechanistically caused by the effect of the mutations on Dp71 structure, as predicted by protein modeling and molecular dynamics simulations. Interestingly, Dp71 mutant variants acquired a dominant negative function that, in turn, dramatically impaired the distribution of different Dp71 protein partners, including β-dystroglycan, nuclear lamins A/C and B1, the high-mobility group (HMG)-containing protein (BRAF35) and the BRAF35-family-member inhibitor of BRAF35 (iBRAF). Further analysis of Dp71 mutants provided evidence showing a role for Dp71 in modulating both heterochromatin marker H3K9me2 organization and the neuronal genes' expression, via its interaction with iBRAF and BRAF5. [ABSTRACT FROM AUTHOR]

The work in this article uses artificial neural networks and support vector machine to forecast electricity consumption in an industrial facility. The main objective is to show that such a problem should be treated with a contextual approach that identifies the most adequate technic in each moment for a single building, contrary to the previous works in the literature that compare the accuracy of each method for the complete data set representing aggregated loads. 72 different algorithms have been implemented and tested. After that, the three most suitable ones are selected in order to support the automated decisions of the best algorithm according to the context. In this way, the implemented methodology finds the best method for the prediction of each 5 min. It can be later used to update the production planning in the industrial facility. It also discussed the size of historical data and the most suitable learning parameters for each method. The case study includes test data for one week and more than one year of training data. [ABSTRACT FROM AUTHOR]

In this paper, we study the post-hoc calibration of modern neural networks, a problem that has drawn a lot of attention in recent years. Despite the plethora of calibration methods proposed, there is no consensus yet on the inherent complexity of the task and, while some authors claim that simple functions solve the problem, others suggest that more expressive models are needed to capture misscalibration. As a first approach, we focus on the task of confidence scaling, specifically on post-hoc methods that generalize Temperature Scaling, which we refer to as the Adaptive Temperature Scaling family. We begin by demonstrating that while complex models like neural networks provide an advantage when there is ample data, they fail in scenarios where it is limited, notably common in fields like medical diagnosis. We then show how under this ideal data conditions the more expressive methods learn a relationship between the entropy of a prediction and its level of overconfidence, and based on this observation, we propose Entropy-based Temperature Scaling, a simple method that scales the confidence of a prediction according to this relationship. Results show that our method obtains state-of-the-art performance and is robust against data scarcity. Moreover, our proposed model enables a deeper understanding of the calibration process by the interpretation of the entropy as a measure of uncertainty in the network outputs. [ABSTRACT FROM AUTHOR]

The iPSC Neurodegenerative Disease Initiative (iNDI) is the largest-ever iPSC genome engineering project. iNDI will model more than 100 mutations associated with Alzheimer's disease and related dementias (ADRD) in isogenic iPSC lines. Resulting cell lines and phenotypic datasets will be broadly shared. [ABSTRACT FROM AUTHOR]

The real-time analysis of single analytes in flow is becoming increasingly relevant in cell biology. In this work, we theoretically predict and experimentally demonstrate hydrodynamic focusing with hollow nanomechanical resonators by using an interferometric system which allows the optical probing of flowing particles and tracking of the fundamental mechanical mode of the resonator. We have characterized the hydrodynamic forces acting on the particles, which will determine their velocity depending on their diameter. By using the parameters simultaneously acquired: frequency shift, velocity and reflectivity, we can unambiguously classify flowing particles in real-time, allowing the measurement of the mass density: 1.35 ± 0.07 g·mL-1 for PMMA and 1.7 ± 0.2 g·mL-1 for silica particles, which perfectly agrees with the nominal values. Once we have tested our technique, MCF-7 human breast adenocarcinoma cells are characterized (1.11 ± 0.08 g·mL-1) with high throughput (300 cells/minute) observing a dependency with their size, opening the door for individual cell cycle studies. [ABSTRACT FROM AUTHOR]

This study analyzes the strategies displayed by non-governmental organizations in the social services sector to face the resource dependence on public administration in Southern Spain. We focus on the reorganization of the public subsidies system in Spain and its specific impact on the entities registered in Andalusia. In 2017, the Autonomous Communities assumed the management of a proportion of the subsidies with a charge to the Personal Income Tax for "social purposes," which was previously managed by the General State Administration in its entirety. The case study combines the description of (a) the process of transferring the management of a line of subsidies from the state to the regional level, (b) the strategies of non-governmental organizations to face the context of instability and financial uncertainty, and (c) the impact of the regulatory bases of grant calls on programs implementation. First, the database with all the applications submitted in the calls of 2017 and 2018 is analyzed (n = 11,610 applications). Second, we describe the perception of the change in the management system, from the point of view of the third-sector social services entities. The combination of both strategies allows us to examine in detail the response of social service organizations to ensure the continuity of the budget and the continuity of services. The results show that the change in the management system gave rise to a wide debate among non-governmental social services organizations about the calls for grants managed by the regional government. However, the qualitative case study showed that the reaction of the entities has more to do with the needs of adaptation to an unstable, uncertain, and highly competitive financial environment, than with specific characteristics of grant calls. [ABSTRACT FROM AUTHOR]

Modifier genes are believed to account for the clinical variability observed in many Mendelian disorders, but their identification remains challenging due to the limited availability of genomics data from large patient cohorts. Here, we present GENDULF (GENetic moDULators identiFication), one of the first methods to facilitate prediction of disease modifiers using healthy and diseased tissue gene expression data. GENDULF is designed for monogenic diseases in which the mechanism is loss of function leading to reduced expression of the mutated gene. When applied to cystic fibrosis, GENDULF successfully identifies multiple, previously established disease modifiers, including EHF, SLC6A14, and CLCA1. It is then utilized in spinal muscular atrophy (SMA) and predicts U2AF1 as a modifier whose low expression correlates with higher SMN2 pre‐mRNA exon 7 retention. Indeed, knockdown of U2AF1 in SMA patient‐derived cells leads to increased full‐length SMN2 transcript and SMN protein expression. Taking advantage of the increasing availability of transcriptomic data, GENDULF is a novel addition to existing strategies for prediction of genetic disease modifiers, providing insights into disease pathogenesis and uncovering novel therapeutic targets. SYNOPSIS: GENDULF predicts modifiers of loss‐of‐function monogenetic diseases using healthy and disease gene expression data. Application to cystic fibrosis (CF) and spinal muscular atrophy (SMA) identifies established CF modifiers and a new putative modifier of SMA, U2AF1. GENDULF is a novel algorithm that identifies genetic modifiers for monogenetic diseases from healthy and disease gene expression data, by detecting patterns of co‐expression that are uniquely observed in healthy tissues.GENDULF may be used to provide a list of candidates for large‐scale analysis or may be incorporated with other approaches or a knowledge‐based step to yield a small list of candidates for small‐scale experimental evaluation.Different applications are demonstrated for CF, where the performance is estimated against previously established modifiers, and for SMA where it is used to uncover a new modifier, U2AF1. [ABSTRACT FROM AUTHOR]

The improvement of the educational experience of minors and the development of personal skills reduce the risk of child labor. In this study we assess the impact of a psychoeducational intervention for the prevention of child labor in two neighborhoods in the periphery of Lima. With a pretest-posttest design, we evaluate the changes in self-esteem, self-efficacy, social skills, school attendance and academic performance of 48 students between 8 and 13 years old (M=10.38, SD=1.22). The results showed an improvement in perceived self-esteem and a decrease in social self-efficacy and social skills self-report. The qualitative evaluation of the perception of changes by students, parents and teachers demonstrated improvements in the socio-affective development of the participants. The evaluation of the program implies the existence of a process of awareness of the personal abilities of the participants, together with small improvements in the academic field that can have an indirect impact on the risk of child labor. [ABSTRACT FROM AUTHOR]

BACKGROUNDSpinal muscular atrophy (SMA) is caused by deficient expression of survival motor neuron (SMN) protein. New SMN-enhancing therapeutics are associated with variable clinical benefits. Limited knowledge of baseline and drug-induced SMN levels in disease-relevant tissues hinders efforts to optimize these treatments.METHODSSMN mRNA and protein levels were quantified in human tissues isolated during expedited autopsies.RESULTSSMN protein expression varied broadly among prenatal control spinal cord samples, but was restricted at relatively low levels in controls and SMA patients after 3 months of life. A 2.3-fold perinatal decrease in median SMN protein levels was not paralleled by comparable changes in SMN mRNA. In tissues isolated from nusinersen-treated SMA patients, antisense oligonucleotide (ASO) concentration and full-length (exon 7 including) SMN2 (SMN2-FL) mRNA level increases were highest in lumbar and thoracic spinal cord. An increased number of cells showed SMN immunolabeling in spinal cord of treated patients, but was not associated with an increase in whole-tissue SMN protein levels.CONCLUSIONSA normally occurring perinatal decrease in whole-tissue SMN protein levels supports efforts to initiate SMN-inducing therapies as soon after birth as possible. Limited ASO distribution to rostral spinal and brain regions in some patients likely limits clinical response of motor units in these regions for those patients. These results have important implications for optimizing treatment of SMA patients and warrant further investigations to enhance bioavailability of intrathecally administered ASOs.FUNDINGSMA Foundation, SMART, NIH (R01-NS096770, R01-NS062869), Ionis Pharmaceuticals, and PTC Therapeutics. Biogen provided support for absolute real-time RT-PCR. [ABSTRACT FROM AUTHOR]

The forensic comparison of glass aims to compare a glass sample of an unknown source with a control glass sample of a known source. In this work, we use multi-elemental features from Laser Ablation Inductively Coupled Plasma with Mass Spectrometry (LA-ICP-MS) to compute a likelihood ratio. This calculation is a complex procedure that generally requires a probabilistic model including the within-source and between-source variabilities of the features. Assuming the within-source variability to be normally distributed is a practical premise with the available data. However, the between-source variability is generally assumed to follow a much more complex distribution, typically described with a kernel density function. In this work, instead of modeling distributions with complex densities, we propose the use of simpler models and the introduction of a data pre-processing step consisting on the Gaussianization of the glass features. In this context, to obtain a better fit of the features with the Gaussian model assumptions, we explore the use of different normalization techniques of the LA-ICP-MS glass features, namely marginal Gaussianization based on histogram matching, marginal Gaussianization based on Yeo-Johnson transformation and a more complex joint Gaussianization using normalizing flows. We report an improvement in the performance of the Likelihood Ratios computed with the previously Gaussianized feature vectors, particularly relevant in their calibration, which implies a more reliable forensic glass comparison. • Feature-based models yield badly calibrated LRs in forensic glass comparison. • Different Gaussianizations schemes over the between-source and within-source variabilities have been analyzed. • A Gaussianization based on histogram matching is the most robust to dataset shifts. • The computation of LRs with Gaussianized features improves their calibration. [ABSTRACT FROM AUTHOR]

Endogenous Cushing's syndrome is a chronic disease associated with increased morbidity and mortality if not appropriately treated. Recurrence and/or persistence of hypercortisolemia after surgical treatment, especially for Cushing's disease, are high, and long-term medical treatment is used to decrease cortisol levels and risk of metabolic comorbidities. Medical treatment is also often required while waiting for radiation effects to take place. In some cases, severe or life-threatening hypercortisolism must be urgently and medically treated, via intravenous medications or with combination therapy, before patients can undergo surgery. In the last decade, medical treatment has progressed from a few steroidogenesis inhibitors to three novel drug groups: new inhibitors for steroidogenic enzymes with possibly fewer side effects, pituitary-directed drugs that aim to inhibit the pathophysiological pathways of Cushing's disease, and glucocorticoid receptor antagonists that block cortisol's action. Understanding the pathophysiology of Cushing's syndrome has also led to the identification of potential targets that may decrease adrenocorticotrophic hormone and/or cortisol excess, and/or decrease tumor cell proliferation, and induce senescence or apoptosis. We provide here a review of current and near-future medical options to treat Cushing's syndrome, and discuss updates on clinical trials and the efficacy and safety of novel or in-development drugs, as well as future potential targets. [ABSTRACT FROM AUTHOR]

Radioactive corrosion products released into the primary coolant loop dominate the final shutdown radiation fields of pressurized water reactors. Thus, reducing the concentration of these corrosion products is a paramount duty in the optimization process of the reactor performance. However, the complexity and uncertainty present in this process make it difficult to predict their evolution in a theoretical way. We propose the application of structural learning of Bayesian networks to discover the complex relations between the corrosion products and the most relevant variables in the primary loop, giving rise to probabilistic models that obtain accurate and reliable predictions of the corrosion products. Our analysis of 5 power plants demonstrates that our approach results in simpler and more reliable models. Additionally, we conclude that the learned structures may represent an interpretable tool for power plant technicians since they reveal useful information that can be directly employed to improve the reactor operation. • Radioactive corrosion products govern shutdown radiation fields of a PWR power plant. • BNs with a fixed structure are already in use to predict the corrosion products. • Conditional Independences of variables are found with Structure learning algorithms. • Structure learning algorithms give rise to simpler and more calibrated BNs. • Resulting models are more reliable than Bayesian Networks with a fixed structure. [ABSTRACT FROM AUTHOR]

In this work, we analyze the cross-entropy function, widely used in classifiers both as a performance measure and as an optimization objective. We contextualize cross-entropy in the light of Bayesian decision theory, the formal probabilistic framework for making decisions, and we thoroughly analyze its motivation, meaning and interpretation from an information-theoretical point of view. In this sense, this article presents several contributions: First, we explicitly analyze the contribution to cross-entropy of (i) prior knowledge; and (ii) the value of the features in the form of a likelihood ratio. Second, we introduce a decomposition of cross-entropy into two components: discrimination and calibration. This decomposition enables the measurement of different performance aspects of a classifier in a more precise way; and justifies previously reported strategies to obtain reliable probabilities by means of the calibration of the output of a discriminating classifier. Third, we give different information-theoretical interpretations of cross-entropy, which can be useful in different application scenarios, and which are related to the concept of reference probabilities. Fourth, we present an analysis tool, the Empirical Cross-Entropy (ECE) plot, a compact representation of cross-entropy and its aforementioned decomposition. We show the power of ECE plots, as compared to other classical performance representations, in two diverse experimental examples: a speaker verification system, and a forensic case where some glass findings are present. [ABSTRACT FROM AUTHOR]

In this work the normative transition of a cohort of secondary school students from Alcalá de Guadaíra that start college education in Seville is examined. The evolution of the social network of the cohort of students together with the changes experienced in the composition and structure of their personal networks is analyzed. The longitudinal tracking is developed over 17 months when respondents (n = 57) begin to distribute their time between the town in which they live and the city where they study, so there is an increase in the frequency of commuting to the capital. This is one of the first studies collecting information from the personal networks of the members of a complete social network, and combining both personal and sociocentric indicators in the analysis. With models for the longitudinal analysis of social networks, using the RSIENA software, we found that average betweenness of personal networks has a significant effect on the social network of students completing secondary education. The average betweenness also seems to influence the change rate in the sense of community with the city of residence. We conclude by proposing that the decoupling of relations, as well as active competition between multiple relationships, are two key mechanisms of changes in the structure of personal networks in the process of ecological transition. [ABSTRACT FROM AUTHOR]

We study the evolution under the Ricci flow of surfaces with singularities of cone type. Firstly we provide a complete classification of gradient Ricci solitons on surfaces, which is of independent interest. Secondly, we prove that closed cone surfaces with cone angles less or equal to π converge, up to rescaling, to closed soliton metrics under the Ricci flow. [ABSTRACT FROM AUTHOR]

Carbapenem-resistant Enterobacteriaceae have recently become an important cause of morbidity and mortality due to healthcare-associated infections. Most commonly used diagnostic methods are incompatible with fast and accurate directed therapy. We report here the direct identification of the blaOXA48 gene, which codes for the carbapenemase OXA-48, in lysate samples from Klebsiella pneumoniae. The method is PCR-free and label-free. It is based on the measurement of changes in the stiffness of DNA self-assembled monolayers anchored to microcantilevers that occur as a consequence of the hybridization. The stiffness of the DNA layer is measured through changes of the sensor resonance frequency upon hybridization and at varying relative humidity. [ABSTRACT FROM AUTHOR]

Free-standing dielectric structures with a substrate underneath, as the SiN microdrums studied here, are the basis of optomechanical devices. Optimization of the optomechanical coupling is demanding in order to enhance the performance of these devices. The optomechanical coupling in the case of drum resonators critically depends on the thickness of the drum, the surface stress, the cavity length and the wavelength. Here, we develop a methodology that combines spatially multiplexed microspectrophotometry, optical modelling of the cavity and finite element method simulation of the mechanical eigenmodes that enables obtaining the properties of the optomechanical cavity and predicting the wavelength that optimizes the optomechanical coupling. By choosing this illumination wavelength we are able to spatially resolve the thermal motion of the microdrums up to the fourth mechanical mode ~ 20 MHz. The presented study opens the door for further optimization pathways for optomechanical detection and actuation. [ABSTRACT FROM AUTHOR]

We have designed a series of tacrine-based homo- and heterodimers that incorporate an antioxidant tether (selenoureido, chalcogenide) as new dual compounds: for the treatment of Alzheimer's disease and as antiproliferative agents. Symmetrical homodimers bearing a dichalcogenide or selenide-based tether, the best compounds in the series, were found to be strong and highly selective electric eel AChE inhibitors, with inhibition constants within the low nanomolar range. This high inhibitory activity was confirmed on recombinant human AChE for the most interesting derivatives. The three most promising homodimers also showed a good inhibitory activity towards amyloid-β self aggregation. The symmetric disulfide derivative bis[5-(1′,2′,3′,4’-tetrahydroacridin-9′-ylamino)pentyl]disulfide ( 19 ) showed the best multipotent profile and was not neurotoxic on immortalized mouse cortical neurons even at 50 μM concentration. These results represent an improvement in activity and selectivity compared to parent tacrine, the first marketed drug against Alzheimer's disease. Title compounds also exhibited excellent in vitro antiproliferative activities against a panel of 6 human tumor cell lines, with GI 50 values within the submicromolar range for the most potent derivatives (0.12–0.95 μM); such values represent a spectacular increase compared to currently-used chemotherapeutic agents, such as 5-FU (up to 306−fold) and cisplatin (up to 162−fold). Cell cycle experiments indicated the accumulation of cells in the G 1 phase of the cycle, a different mechanism than the reported for cisplatin. The breast cancer cell lines turned out to be the most sensitive one of the panel tested. [ABSTRACT FROM AUTHOR]

This Guideline proposes a protocol for the validation of forensic evaluation methods at the source level, using the Likelihood Ratio framework as defined within the Bayes' inference model. In the context of the inference of identity of source, the Likelihood Ratio is used to evaluate the strength of the evidence for a trace specimen, e.g. a fingermark, and a reference specimen, e.g. a fingerprint, to originate from common or different sources. Some theoretical aspects of probabilities necessary for this Guideline were discussed prior to its elaboration, which started after a workshop of forensic researchers and practitioners involved in this topic. In the workshop, the following questions were addressed: "which aspects of a forensic evaluation scenario need to be validated?", "what is the role of the LR as part of a decision process?" and "how to deal with uncertainty in the LR calculation?". The questions: "what to validate?" focuses on the validation methods and criteria and "how to validate?" deals with the implementation of the validation protocol. Answers to these questions were deemed necessary with several objectives. First, concepts typical for validation standards [1], such as performance characteristics, performance metrics and validation criteria, will be adapted or applied by analogy to the LR framework. Second, a validation strategy will be defined. Third, validation methods will be described. Finally, a validation protocol and an example of validation report will be proposed, which can be applied to the forensic fields developing and validating LR methods for the evaluation of the strength of evidence at source level under the following propositions. [ABSTRACT FROM AUTHOR]

This study presents a method for computing likelihood ratios (LRs) from multimodal score distributions, as the ones produced by some commercial off-the-shelf automated fingerprint identification systems (AFISs). The AFIS algorithms used to compare fingermarks and fingerprints were primarily developed for forensic investigation rather than for forensic evaluation purposes. Thus, in some of those algorithms, the computation of discriminating scores is speed-optimised. In the case of the AFIS algorithm used in this work, the speed-optimisation is achieved by performing the comparison in three different stages, each of which outputs scores of different magnitudes. As a consequence, all scores together present a multimodal distribution, even though each fingermark-to-fingerprint comparison generates one single score. This multimodal distribution of scores might be typical for other biometric systems or other algorithms, and the method proposed in this work can be also applied to those cases. As a result, the authors propose a probabilistic model for LR computation that presents more robustness to overfitting and data sparsity than other traditional approaches, like the use of models based on kernel density functions. [ABSTRACT FROM AUTHOR]

Fibroblast growth factors (FGFs) are a superfamily of 22 proteins related to cell proliferation and tissue repair after injury. A subgroup of three proteins, FGF19, FGF21, and FGF23, are major endocrine mediators. These three FGFs have low affinity to heparin sulfate during receptor binding; in contrast they have a strong interaction with the cofactor Klotho/β-Klotho. FGF21 has received particular attention because of its key role in carbohydrate, lipids, and energy balance regulation. FGF21 improves glucose and lipids metabolism as well as increasing energy expenditure in animal models and humans. Conditions that induce human physical stress such as exercise, lactation, obesity, insulin resistance, and type 2 diabetes influence FGF21 circulating levels. FGF21 also has an anti-oxidant function in human metabolic diseases which contribute to understanding the FGF21 compensatory increment in obesity, the metabolic syndrome, and type 2 diabetes. Interestingly, energy expenditure and weight loss is induced by FGF21. The mechanism involved is through 'browning' of white adipose tissue, increasing brown adipose tissue activity and heat production. Therefore, clinical evaluation of therapeutic action of exogenous FGF21 administration is warranted, particularly to treat diabetes and obesity. [ABSTRACT FROM AUTHOR]

This study presents a method for computing likelihood ratios (LRs) from multimodal score distributions, as the ones produced by some commercial off‐the‐shelf automated fingerprint identification systems (AFISs). The AFIS algorithms used to compare fingermarks and fingerprints were primarily developed for forensic investigation rather than for forensic evaluation purposes. Thus, in some of those algorithms, the computation of discriminating scores is speed‐optimised. In the case of the AFIS algorithm used in this work, the speed‐optimisation is achieved by performing the comparison in three different stages, each of which outputs scores of different magnitudes. As a consequence, all scores together present a multimodal distribution, even though each fingermark‐to‐fingerprint comparison generates one single score. This multimodal distribution of scores might be typical for other biometric systems or other algorithms, and the method proposed in this work can be also applied to those cases. As a result, the authors propose a probabilistic model for LR computation that presents more robustness to overfitting and data sparsity than other traditional approaches, like the use of models based on kernel density functions. [ABSTRACT FROM AUTHOR]

Summary The neuromuscular disorder spinal muscular atrophy (SMA), the most common inherited killer of infants, is caused by insufficient expression of survival motor neuron (SMN) protein. SMA therapeutics development efforts have focused on identifying strategies to increase SMN expression. We identified a long non-coding RNA (lncRNA) that arises from the antisense strand of SMN , SMN-AS1 , which is enriched in neurons and transcriptionally represses SMN expression by recruiting the epigenetic Polycomb repressive complex-2. Targeted degradation of SMN-AS1 with antisense oligonucleotides (ASOs) increases SMN expression in patient-derived cells, cultured neurons, and the mouse central nervous system. SMN-AS1 ASOs delivered together with SMN2 splice-switching oligonucleotides additively increase SMN expression and improve survival of severe SMA mice. This study is the first proof of concept that targeting a lncRNA to transcriptionally activate SMN2 can be combined with SMN2 splicing modification to ameliorate SMA and demonstrates the promise of combinatorial ASOs for the treatment of neurogenetic disorders. [ABSTRACT FROM AUTHOR]

The abundant HSV-1 tegument protein VP11/12 encoded by gene UL46 is essential for induction of the PI3K/Akt-signaling pathway during infection. VP11/12 utilizes tyrosine-based motifs within its C-terminal region to bind the SH2 domains of Src family kinases, the p85 subunit of PI3 Kinase and Grb2, and the PTB domain of Shc. We previously proposed that the interaction with SFKs and p85 is used to gain control over the PI3K/Akt signaling pathway. We tested this model by evaluating the effects of mutations that eliminate each of these interactions on the ability of HSV-1 to activate Akt. Inhibiting the interaction of VP11/12 with SFKs, p85 and Grb2 reduced Akt activation, while inhibiting the interaction with Shc had little effect. Overall these data support the suggestion that VP11/12 stimulates the PI3K/Akt pathway by mimicking an activated growth factor receptor. [ABSTRACT FROM AUTHOR]

Background: Acetic acid, released during hydrolysis of lignocellulosic feedstocks for second generation bioethanol production, inhibits yeast growth and alcoholic fermentation. Yeast biomass generated in a propagation step that precedes ethanol production should therefore express a high and constitutive level of acetic acid tolerance before introduction into lignocellulosic hydrolysates. However, earlier laboratory evolution strategies for increasing acetic acid tolerance of Saccharomyces cerevisiae, based on prolonged cultivation in the presence of acetic acid, selected for inducible rather than constitutive tolerance to this inhibitor. Results: Preadaptation in the presence of acetic acid was shown to strongly increase the fraction of yeast cells that could initiate growth in the presence of this inhibitor. Serial microaerobic batch cultivation, with alternating transfers to fresh medium with and without acetic acid, yielded evolved S. cerevisiae cultures with constitutive acetic acid tolerance. Single-cell lines isolated from five such evolution experiments after 50-55 transfers were selected for further study. An additional constitutively acetic acid tolerant mutant was selected after UV-mutagenesis. All six mutants showed an increased fraction of growing cells upon a transfer from a non-stressed condition to a medium containing acetic acid. Whole-genome sequencing identified six genes that contained (different) mutations in multiple acetic acid-tolerant mutants. Haploid segregation studies and expression of the mutant alleles in the unevolved ancestor strain identified causal mutations for the acquired acetic acid tolerance in four genes (ASG1, ADH3, SKS1 and GIS4). Effects of the mutations in ASG1, ADH3 and SKS1 on acetic acid tolerance were additive. Conclusions: A novel laboratory evolution strategy based on alternating cultivation cycles in the presence and absence of acetic acid conferred a selective advantage to constitutively acetic acid-tolerant mutants and may be applicable for selection of constitutive tolerance to other stressors. Mutations in four genes (ASG1, ADH3, SKS1 and GIS4) were identified as causative for acetic acid tolerance. The laboratory evolution strategy as well as the identified mutations can contribute to improving acetic acid tolerance in industrial yeast strains. [ABSTRACT FROM AUTHOR]

In nuclear power plants, there are high-exposure jobs, like refuelling and maintenance, that require getting close to the reactor between operation cycles. Therefore, reducing radiation dose during these periods is of paramount importance regarding safety regulations. While there are some manipulable variables, like levels of certain corrosion products, that can influence the final level of radiation dose, there is no way to determine it in a principled way. In this work, we propose to use Machine Learning to predict the radiation dose in the reactor at the cycle end based on information available during the cycle operation. In particular, we use a Gaussian Process to model the relation between cobalt radioisotopes (a certain kind of corrosion product) and radiation dose levels. Gaussian Processes acknowledge the uncertainty on their predictions, a desirable property considering the high-risk nature of the present application. We report experiments on real data gathered from five different power plants in Spain. Results show that these models can be used to estimate the future values of radiation dose in a data-driven way. Moreover, there are tools based on these models currently in development for their application in power plants. • Control and monitoring of the radiation dose in pressurized-water nuclear power plant reactors is paramount. • The dose at shutdown is strongly related to the presence of radioisotopes in the primary cooling circuit of the reactor. • Radioisotopes levels can be monitored during the operation cycle, and its values tuned through chemical engineering. • A Gaussian Process is proposed to model radiation dose as a function of radioisotopes levels in a data-driven way. • The proposed model is probabilistic; hence robust to data scarcity problems. • The proposed model is interpretable allowing its use by operators without deep knowledge of machine learning. [ABSTRACT FROM AUTHOR]

In forensic science, trace evidence found at a crime scene and on suspect has to be evaluated from the measurements performed on them, usually in the form of multivariate data (for example, several chemical compound or physical characteristics). In order to assess the strength of that evidence, the likelihood ratio framework is being increasingly adopted. Several methods have been derived in order to obtain likelihood ratios directly from univariate or multivariate data by modelling both the variation appearing between observations (or features) coming from the same source (within-source variation) and that appearing between observations coming from different sources (between-source variation). In the widely used multivariate kernel likelihood-ratio, the within-source distribution is assumed to be normally distributed and constant among different sources and the between-source variation is modelled through a kernel density function (KDF). In order to better fit the observed distribution of the between-source variation, this paper presents a different approach in which a Gaussian mixture model (GMM) is used instead of a KDF. As it will be shown, this approach provides better-calibrated likelihood ratios as measured by the log-likelihood ratio cost (Cllr) in experiments performed on freely available forensic datasets involving different trace evidences: inks, glass fragments and car paints. [ABSTRACT FROM AUTHOR]

Introduction: Analysis of a series of works of world literature, discussing the accuracy of palpation and cervical lymph node imaging, highlighted the need to assess the method used in our teaching hospital. Objective: To evaluate the diagnostic accuracy of preoperative evaluation through palpation and CT cervical lymph nodes of patients with head and neck squamous cell carcinoma. Methods: We analyzed 398 patients with head and neck tumors. They compared the clinical stage assessed by palpation and CT scan of the neck with the data found by the anatomical and pathological analysis in the product of neck dissections conducted in order to determine the concordance rate between the two evaluations. Results: Of 398 patients included in the study, there was concordance rate of 83.6% between clinical staging considered negative and observed after emptying confirmed by pathological examination. It was noted that the accuracy of diagnosis of lymph node metastases in the preoperative period was 78.4% while the accuracy of agreement between the two staging was 69.1%. Conclusion: The use of imaging methods, particularly computed tomography associated with palpation, shows a significant increase in the diagnostic capacity of lymph node metastases. [ABSTRACT FROM AUTHOR]

• Surveillance of deaths in NHPs is a key point for the prevention of YF in humans. • Determination of hepatic pathological features are crucial for screening YF in NHPs. • YF-associated hepatic injuries may vary between South American NHPs genera. • Humans and NHPs show marked differences in the set of YF-associated hepatic lesions. The early detection and diagnosis of deaths in free-ranging non-human primates (NHPs) are key points for the surveillance of Yellow Fever (YF) in Brazil. The histopathological identification of infectious diseases remains very useful and reliable in the screening and detection of emerging zoonotic diseases such as YF. We surveyed data records and liver slides stained with hematoxylin and eosin from the Epizootics Surveillance Network to control YF, Ministry of Health of Brazil, to evaluate histopathological hallmarks for the diagnosis of the YF virus infection. We selected natural fatal cases in NHPs from the genera Alouatta spp., Callithrix spp., and Sapajus spp. with a positive immunohistochemical assay for YF in liver samples. Our findings showed the full-spectrum YF-associated hepatic lesions in all NHPs, but some histopathological findings differed in the distribution and intensity between the three genera. In our study, South American NHPs showed significant differences in the YF-associated hepatic histopathological features compared to fatal cases reported in humans. [Display omitted] [ABSTRACT FROM AUTHOR]

We report the use of commercially available glass microcapillaries as micromechanical resonators for real-time monitoring of the mass density of a liquid that flows through the capillary. The vibration of a suspended region of the microcapillary is optically detected by measuring the forward scattering of a laser beam. The resonance frequency of the liquid filled microcapillary is measured for liquid binary mixtures of ethanol in water, glycerol in water and Triton in ethanol. The method achieves a detection limit in an air environment of 50 µg/mL that is only five times higher than that obtained with state-of-the-art suspended microchannel resonators encapsulated in vacuum. The method opens the door to novel advances for miniaturized total analysis systems based on microcapillaries with the add-on of mechanical transduction for sensing the rheological properties of the analyzed fluids without the need for vacuum encapsulation of the resonators. [ABSTRACT FROM AUTHOR]

Measuring the performance of forensic evaluation methods that compute likelihood ratios (LRs) is relevant for both the development and the validation of such methods. A framework of performance characteristics categorized as primary and secondary is introduced in this study to help achieve such development and validation. Ground-truth labelled fingerprint data is used to assess the performance of an example likelihood ratio method in terms of those performance characteristics. Discrimination, calibration, and especially the coherence of this LR method are assessed as a function of the quantity and quality of the trace fingerprint specimen. Assessment of the coherence revealed a weakness of the comparison algorithm in the computer-assisted likelihood ratio method used. [ABSTRACT FROM AUTHOR]

There are many studies on vegetation and ecosystem characterization in the occidental slope of the Central Andes of Peru. However the knowledge of the vegetation of the highlands of Lima is limited. Therefore, we conducted a study of the vegetation in the middle basin of the Lurin river, department of Lima. The aim was to characterize the upland vegetation of the Cochahuayco community according to an altitudinal gradient, ranging from 1720 to 2957 masl, based on samples and field observations. We established eight sampling units along the gradient, following a systematic sampling model with random start. The sampling units were evaluated on a quarterly basis from july-2009 to july-2010. Five vegetation units were differentiated, based on the composition, abundance and coverage of species of the shrub layer. These units were: Cacti Zone (between 1720 and 2000 masl), where Haageocereus acranthus and Espostoa melanostele were the dominant cacti; Bastardia Zone (from 2000 to 2230 masl), where Bastardia bivalvis was dominant; Tall shrubs Zone (from 2230 to 2500 masl), where Euphorbia cf. laurifolia and Perymenium jelskii were dominant; Sub-thorny shrubs Zone (from 2500 to 2850 masl), where Verbesina saubinetioides was dominant; and Thorny Shrubs Zone (from 2850 to 2957 masl), where Proustia cuneifolia was dominant. The first two units fell within the Subtropical desert scrub life zone, and the other three in the Lower montane thorn steppe life zone; all these belonged to the shrub thicket coverage type. [ABSTRACT FROM AUTHOR]

Background Alterations in postprandial metabolism have been described in familial combined hyperlipidemia (FCH); however, their underlying mechanisms are not well characterized. We aimed to identify factors related to the magnitude of postprandial lipemia and apolipoprotein (apo) A-V levels in subjects with FCH. Methods FCH cases (n = 99) were studied using a standardized meal test. Abdominal obesity was assessed using the waist to hip ratio (WHR). A linear regression model was performed to investigate the variables associated with the triglycerides incremental area under the curve (iAUC). Independent associations between metabolic variables and apo A-V iAUC were also investigated in a randomly selected subgroup (n = 44). The study sample was classified according to the presence of fasting hypertriglyceridemia (≥150 mg/dL) and abdominal obesity (WHR ≥0.92 in men and ≥0.85 in women) to explore differences in parameters. Results The fasting apo B-48 levels (r = 0.404), and the WHR (r = 0.359) were independent factors contributing to the triglycerides iAUC (r² = 0.29, P < 0.001). The triglycerides iAUC was independently associated with the apo A-V iAUC (r² = 0.54, P < 0.01). Patients with both hypertriglyceridemia and abdominal obesity showed the most robust triglycerides and apo AV postprandial responses. Conclusions In patients with FCH the fasting apo B-48 level is the main factor associated with postprandial lipemia. Abdominal obesity also contributes to the magnitude of the postprandial response. The triglycerides postprandial increment is the principal factor associated with the apo A-V postprandial response. [ABSTRACT FROM AUTHOR]

We investigate the coupling between mechanical and optical modes supported by coupled, freestanding, photonic crystal nanobeam cavities. We show that localized cavity modes for a given gap between the nanobeams provide weak optomechanical coupling with out-of-plane mechanical modes. However, we show that the coupling can be significantly increased, more than an order of magnitude for the symmetric mechanical mode, due to optical resonances that arise from the interaction of the localized cavity modes with standing waves formed by the reflection from thesubstrate. Finally, amplification of motion for the symmetric mode has been observed and attributed to the strong optomechanical interaction of our hybrid system. The amplitude of these self-sustained oscillations is large enough to put the system into a non-linear oscillation regime where a mixing between the mechanical modes is experimentally observed and theoretically explained. [ABSTRACT FROM AUTHOR]

Cushing's disease (CD) is characterized by an ACTH-producing anterior corticotrope pituitary adenoma. If hypothalamus-pituitary-adrenal (HPA) axis physiology is disrupted, ACTH secretion increases, which in turn stimulates adrenocortical steroidogenesis and cortisol production. Medical treatment plays an important role for patients with persistent disease after surgery, for those in whom surgery is not feasible, or while awaiting effects of radiation. Multiple drugs, with different mechanisms of action and variable efficacy and tolerability for controlling the deleterious effects of chronic glucocorticoid excess, are available. The molecular basis and clinical data for centrally acting drugs, adrenal steroidogenesis inhibitors, and glucocorticoid receptor antagonists are reviewed, as are potential novel molecules and future possible targets for CD treatment. Although progress has been made in the understanding of specific corticotrope adenoma receptor physiology and recent clinical studies have detected improved effects with a combined medical therapy approach, there is a clear need for a more efficacious and better-tolerated medical therapy for patients with CD. A better understanding of the molecular mechanisms in CD and of HPA axis physiology should advance the development of new drugs in the future. [ABSTRACT FROM AUTHOR]

The article describes the formative evaluation of an educational intervention program with working children in Barranquilla (Colombia). An international team of evaluators conducted qualitative interviews with a sample of facilitators (n = 8), families of participants (n = 38) and teachers of schools where the program was implemented (n = 40). The interviews focused on the implementation process and discussed the role of facilitators, which administered the program and develop strategies for community mediation. The results show the connection between the processes of community involvement and the effectiveness of the intervention. The facilitators connect the program with the organizational and community contexts. In the implementation process, the role of facilitators consisted on (a) to adjust the program to the peculiarities and difficulties of the context, (b) to exchange good practices, and (c) to mediate with teachers and families involved. While the role of mediation and community adjustment of the facilitators were planned in the design, the formation of an informal group among the most active applicators affects to the central components of the program. Paradoxically, this dynamic improved the implementation and outcomes. In this context we discuss the lessons learned in the prevention of child labor. [ABSTRACT FROM AUTHOR]

This paper reviews the literature on health education in educational institutions in Spain for the past 20 years. Articles were retrieved from various databases to analyze the type of intervention, the topics addressed, the methodology used, and compliance with the criteria established by the WHO for health promoting schools. The results revealed that a) only four of the 245 articles retrieved met the WHO criteria; b) interventions are based more on health prevention than health promotion, and c) health promotion is more widely disseminated in universities than schools. [ABSTRACT FROM AUTHOR]

Somatostatin (SST), an inhibitory polypeptide with two biologically active forms SST14 and SST28, inhibits GH, prolactin (PRL), TSH, and ACTH secretion in the anterior pituitary gland. SST also has an antiproliferative effect inducing cell cycle arrest and apoptosis. Such actions are mediated through five G-protein-coupled somatostatin receptors (SSTR): SSTR1-SSTR5. In GH-secreting adenomas, SSTR2 expression predominates, and somatostatin receptor ligands (SRLs; octreotide and lanreotide) directed to SSTR2 are presently the mainstays of medical therapy. However, about half of patients show incomplete biochemical remission, but the definition of resistance per se remains controversial. We summarize here the determinants of SRL resistance in acromegaly patients, including clinical, imaging features as well as molecular (mutations, SSTR variants, and polymorphisms), and histopathological (granulation pattern, and proteins and receptor expression) predictors. The role of SSTR5 may explain the partial responsiveness to SRLs in patients with adequate SSTR2 density in the cell membrane. In patients with ACTH-secreting pituitary adenomas, i.e. Cushing's disease (CD), SSTR5 is the most abundant receptor expressed and tumors show low SSTR2 density due to hypercortisolism-induced SSTR2 down-regulation. Clinical studies with pasireotide, a multireceptor-targeted SRL with increased SSTR5 activity, lead to approval of pasireotide for treatment of patients with CD. Other SRL delivery modes (oral octreotide), multireceptortargeted SRL (somatoprim) or chimeric compounds targeting dopamine D2 receptors and SSTR2 (dopastatin), are briefly discussed. [ABSTRACT FROM AUTHOR]

The spectral minutiae representation (SMC) has been recently proposed as a novel method to minutiae‐based fingerprint recognition, which is invariant to minutiae translation and rotation and presents low computational complexity. As high‐resolution palmprint recognition is also mainly based on minutiae sets, SMC has been applied to palmprints and used in full‐to‐full palmprint matching. However, the performance of that approach was still limited. As one of the main reasons for this is the much bigger size of a palmprint compared with a fingerprint, the authors propose a division of the palmprint into smaller regions. Then, to further improve the performance of spectral minutiae‐based palmprint matching, in this work the authors present anatomically inspired regional fusion while using SMC for palmprints. Firstly, the authors consider three regions of the palm, namely interdigital, thenar and hypothenar, which have inspiration in anatomic cues. Then, the authors apply SMC to region‐to‐region palmprint comparison and study regional discriminability when using the method. After that, the authors implement regional fusion at score level by combining the scores of different regional comparisons in the palm with two fusion methods, that is, sum rule and logistic regression. The authors evaluate region‐to‐region comparison and regional fusion based on spectral minutiae matching on a public high‐resolution palmprint database, THUPALMLAB. Both manual segmentation and automatic segmentation are performed to obtain the three palm regions for each palm. Essentially using the complex SMC, the authors obtain results on region‐to‐region comparison which show that the hypothenar and interdigital regions outperform the thenar region. More importantly, the authors achieve significant performance improvements by regional fusion using regions segmented both manually and automatically. One main advantage of the approach the authors took is that human examiners can segment the palm into the three regions without prior knowledge of the system, which makes the segmentation process easy to be incorporated in protocols such as in forensic science. [ABSTRACT FROM AUTHOR]

The purpose of this study was to explore the use of the social network Facebook by users after the death of a loved one and analyse the sharing of contents of the deceased user profile. This is a qualitative study and content analysis was used for data treatment. 195 comments posted were analyzed in the deceased user profile during the first month after death. It was possible to identify thematic categories that include comments to the deceased, feelings, emotions, mourning coping strategies indicators, religious beliefs and tributes. Virtual social networks allow the manifestation of feelings usually retract and the interaction of social issues, that are hardly treated openly, favouring the elaboration of mourning by patients, families and professionals facing the death/dying and mourning process [ABSTRACT FROM AUTHOR]