The LLAMA Brazilian-Argentinian radiotelescope project: progress in Brazil and BRICS collaboration.

We present briefly the LLAMA sub-mm radiotelescope, a joint project of Argentina and Brazil, being mounted in the Andes, Argentina, at 4800 m altitude. Here we focus on the activities that are going on mostly under the responsibility of Brazil, like the high frequency receivers, parts of the back-end and electronics, the optical system of the telescope to bring the radiation to the receivers, the equipment needed for the integration and verification phase (optical telescope and holography) and the computation system.The main scientific applications that are planned are dscribed. We also report on a joint program with BRICS countries approved in 2019, which will involve the use of LLAMA for testing high-frequency receivers.

Actin filament reorganisation controlled by the SCAR/WAVE complex mediates stomatal response to darkness.

Stomata respond to darkness by closing to prevent excessive water loss during the night. Although the reorganisation of actin filaments during stomatal closure is documented, the underlying mechanisms responsible for dark-induced cytoskeletal arrangement remain largely unknown. We used genetic, physiological and cell biological approaches to show that reorganisation of the actin cytoskeleton is required for dark-induced stomatal closure. The opal5 mutant does not close in response to darkness but exhibits wild-type (WT) behaviour when exposed to abscisic acid (ABA) or CaCl2 . The mutation was mapped to At5g18410, encoding the PIR/SRA1/KLK subunit of the ArabidopsisSCAR/WAVE complex. Stomata of an independent allele of the PIR gene (Atpir-1) showed reduced sensitivity to darkness and F1 progenies of the cross between opal5 and Atpir-1 displayed distorted leaf trichomes, suggesting that the two mutants are allelic. Darkness induced changes in the extent of actin filament bundling in WT. These were abolished in opal5. Disruption of filamentous actin using latrunculin B or cytochalasin D restored wild-type stomatal sensitivity to darkness in opal5. Our findings suggest that the stomatal response to darkness is mediated by reorganisation of guard cell actin filaments, a process that is finely tuned by the conserved SCAR/WAVE-Arp2/3 actin regulatory module.

Transcriptomics and physiological analyses reveal co-ordinated alteration of metabolic pathways in Jatropha curcas drought tolerance.

Jatropha curcas, a multipurpose plant attracting a great deal of attention due to its high oil content and quality for biofuel, is recognized as a drought-tolerant species. However, this drought tolerance is still poorly characterized. This study aims to contribute to uncover the molecular background of this tolerance, using a combined approach of transcriptional profiling and morphophysiological characterization during a period of water-withholding (49 d) followed by rewatering (7 d). Morphophysiological measurements showed that J. curcas plants present different adaptation strategies to withstand moderate and severe drought. Therefore, RNA sequencing was performed for samples collected under moderate and severe stress followed by rewatering, for both roots and leaves. Jatropha curcas transcriptomic analysis revealed shoot- and root-specific adaptations across all investigated conditions, except under severe stress, when the dramatic transcriptomic reorganization at the root and shoot level surpassed organ specificity. These changes in gene expression were clearly shown by the down-regulation of genes involved in growth and water uptake, and up-regulation of genes related to osmotic adjustments and cellular homeostasis. However, organ-specific gene variations were also detected, such as strong up-regulation of abscisic acid synthesis in roots under moderate stress and of chlorophyll metabolism in leaves under severe stress. Functional validation further corroborated the differential expression of genes coding for enzymes involved in chlorophyll metabolism, which correlates with the metabolite content of this pathway.

A Machine Learning Approach for Hot-Spot Detection at Protein-Protein Interfaces.

Understanding protein-protein interactions is a key challenge in biochemistry. In this work, we describe a more accurate methodology to predict Hot-Spots (HS) in protein-protein interfaces from their native complex structure compared to previous published Machine Learning (ML) techniques. Our model is trained on a large number of complexes and on a significantly larger number of different structural- and evolutionary sequence-based features. In particular, we added interface size, type of interaction between residues at the interface of the complex, number of different types of residues at the interface and the Position-Specific Scoring Matrix (PSSM), for a total of 79 features. We used twenty-seven algorithms from a simple linear-based function to support-vector machine models with different cost functions. The best model was achieved by the use of the conditional inference random forest (c-forest) algorithm with a dataset pre-processed by the normalization of features and with up-sampling of the minor class. The method has an overall accuracy of 0.80, an F1-score of 0.73, a sensitivity of 0.76 and a specificity of 0.82 for the independent test set.

Science development study for the Atacama Large Aperture Submillimeter Telescope (AtLAST): Solar and stellar observations.

Observations at (sub-)millimeter wavelengths offer a complementary perspective on our Sun and other stars, offering significant insights into both the thermal and magnetic composition of their chromospheres. Despite the fundamental progress in (sub-)millimeter observations of the Sun, some important aspects require diagnostic capabilities that are not offered by existing observatories. In particular, simultaneously observations of the radiation continuum across an extended frequency range would facilitate the mapping of different layers and thus ultimately the 3D structure of the solar atmosphere. Mapping large regions on the Sun or even the whole solar disk at a very high temporal cadence would be crucial for systematically detecting and following the temporal evolution of flares, while synoptic observations, i.e., daily maps, over periods of years would provide an unprecedented view of the solar activity cycle in this wavelength regime. As our Sun is a fundamental reference for studying the atmospheres of active main sequence stars, observing the Sun and other stars with the same instrument would unlock the enormous diagnostic potential for understanding stellar activity and its impact on exoplanets. The Atacama Large Aperture Submillimeter Telescope (AtLAST), a single-dish telescope with 50m aperture proposed to be built in the Atacama desert in Chile, would be able to provide these observational capabilities. Equipped with a large number of detector elements for probing the radiation continuum across a wide frequency range, AtLAST would address a wide range of scientific topics including the thermal structure and heating of the solar chromosphere, flares and prominences, and the solar activity cycle. In this white paper, the key science cases and their technical requirements for AtLAST are discussed.

Observations of our Sun and other stars at wavelengths of around one millimeter, i.e. in the range between infrared and radio waves, present a valuable complementary perspective. Despite significant technological advancements, certain critical aspects necessitate diagnostic capabilities not offered by current observatories. The proposed Atacama Large Aperture Submillimeter Telescope (AtLAST), featuring a 50-meter aperture and slated for construction at a high altitude in Chile's Atacama desert, promises to address these observational needs. Equipped with novel detectors that would cover a wide frequency range, AtLAST could unlock a plethora of scientific studies contributing to a better understanding of our host star. Simultaneous observations over a broad frequency range at rapid succession would enable the imaging of different layers of the Sun, thus elucidating the three-dimensional thermal and magnetic structure of the solar atmosphere and providing important clues for many long-standing central questions such as how the outermost layers of the Sun are heated to very high temperatures, the nature of large-scale structures like prominences, and how flares and coronal mass ejections, i.e. enormous eruptions, are produced. The latter is of particular interest to modern society due to the potentially devastating impact on the technological infrastructure we depend on today. Another unique possibility would be to study the Sun's long-term evolution in this wavelength range, which would yield important insights into its activity cycle. Moreover, the Sun serves as a fundamental reference for other stars as, due to its proximity, it is the only star that can be investigated in such detail. The results for the Sun would therefore have direct implications for understanding other stars and their impact on exoplanets. This article outlines the key scientific objectives and technical requirements for solar observations with AtLAST.

The dual effect of abscisic acid on stomata.

The classical view that the drought-related hormone ABA simply acts locally at the guard cell level to induce stomatal closure is questioned by differences between isolated epidermis and intact leaves in stomatal response to several stimuli. We tested the hypothesis that ABA mediates, in addition to a local effect, a remote effect in planta by changing hydraulic regulation in the leaf upstream of the stomata. By gravimetry, porometry to water vapour and argon, and psychrometry, we investigated the effect of exogenous ABA on transpiration, stomatal conductance and leaf hydraulic conductance of mutants described as ABA-insensitive at the guard cell level. We show that foliar transpiration of several ABA-insensitive mutants decreases in response to ABA. We demonstrate that ABA decreases stomatal conductance and down-regulates leaf hydraulic conductance in both the wildtype Col-0 and the ABA-insensitive mutant ost2-2. We propose that ABA promotes stomatal closure in a dual way via its already known biochemical effect on guard cells and a novel, indirect hydraulic effect through a decrease in water permeability within leaf vascular tissues. Variability in sensitivity of leaf hydraulic conductance to ABA among species could provide a physiological basis to the isohydric or anisohydric behaviour.

Deep learning framework for epidemiological forecasting: A study on COVID-19 cases and deaths in the Amazon state of Pará, Brazil.

Modeling time series has been a particularly challenging aspect due to the need for constant adjustments in a rapidly changing environment, data uncertainty, dependencies between variables, volatile fluctuations, and the need to identify ideal hyperparameters. The present study presents a Framework capable of making projections from time series related to cases and deaths by COVID-19 in the Amazonian state of Pará, in Brazil. For the first time, deep learning models such as TCN, TRANSFORMER, TFT, N-BEATS, and N-HiTS were assessed for this purpose. The ARIMA statistical model was also used in post-processing for residual adjustment and short-term smoothing of the generated forecasts. The Framework generates probabilistic forecasts, with multivariate support, considering the following variables: daily cases per day of the first symptom, cases published daily, the occurrence of deaths, deaths published daily, and percentage of daily vaccination. The generated predictions are statistically evaluated by determining the best model for 7-day moving average projections using evaluating metrics such as MSE, RMSE, MAPE, sMAPE, r2, Coefficient of Variation, and residual analysis. As a result, the generated projections showed an average error of 5.4% for Cases Publication, 8.0% for Cases Symptoms, 11.12% for Deaths Publication, and 4.6% for Deaths Occurrence, with the N-HiTS and N-BEATS models obtaining better results. In general terms, the use of deep learning models to predict cases and deaths from COVID-19 has proven to be a valuable practice for analyzing the spread of the virus, which allows health managers to better understand and respond to this kind of pandemic outbreak.

General practitioners' knowledge, attitudes, beliefs, and practices in the management of sexual dysfunction-results of the Portuguese SEXOS study.

INTRODUCTION: Evidence shows that sexual dysfunctions (SDs) are very prevalent in both sexes and that they share risk factors with many other conditions. It is known that only a minority of people experiencing sexual problems seek treatment, but the role of the general practitioner (GP) in SD diagnosis and treatment is relatively unexplored. No study has been conducted in Portugal in order to identify GPs' knowledge, attitudes, beliefs, and practices regarding SD and only a small amount of similar studies from other countries have been published. AIM: To characterize GPs' knowledge, attitudes, and beliefs concerning SD; practices of SD management in daily practice; self-perceived competence in discussing and treating SD; and need for training. METHODS: Cross-sectional study using confidential self-administered questionnaires applied to GPs working in Primary Health Care Units in the Lisbon region. MAIN OUTCOME MEASURES: The questionnaire collected information concerning GPs' knowledge and perceptions regarding SD, training and practice in sexual health, criteria for initiating discussion and treatment, and the adoption of guidelines. RESULTS: A total of 50 questionnaires (30 females) were obtained (73.5% response rate). On average, the 50 participants were 52±8.6 years old, had 21±8.2 years of family practice, and followed 1,613±364 patients. The degree in medicine was never considered as an extremely adequate source of information both for male and female SD. Lack of time to obtain relevant information for clinical practice and to deal with sexual health issues were perceived as important barriers in initiating a discussion with the patient, as well as lack of academic training and experience in this area. CONCLUSIONS: GPs expressed a high need for continuous training in this area and more than half considered that their degree was not an adequate source of training. These results indicate that there is a need for both pregraduate and postgraduate training in this area.

A restricted mixture model for dietary pattern analysis in small samples.

Multivariate finite mixture models have been applied to the identification of dietary patterns. These models are known to have many parameters, and consequently large samples are usually required. We present a special case of a multivariate mixture model that reduces the number of parameters to be estimated and seems adequate for small to moderately sized samples. We illustrate our approach with an analysis of Portuguese data from a food-frequency questionnaire and with a simulation study.

New confinement index and new perspective for comparing countries - COVID-19.

BACKGROUND AND OBJECTIVE: In the difficult problem of comparing countries regarding their lockdown measures or deaths caused by the COVID-19, there is still no agreement on what is the best strategy to follow. Thus, we propose a new way of comparison countries that avoids the main difficulties in the comparison by using three-dimensional trajectories for this type of data. METHODS: We introduce a new index to analyze the level of confinement that each country was subject to overtime, based on the Community Mobility Reports published by Google resorting to Principal Component Analysis. Subsequently, by using longitudinal clustering, we divide the European countries into similar groups according to the COVID-19 obits and also to the confinement index. However, to make the most out of the clustering methods we resort to artificial longitudinal data to evaluate both the methods and the indices. RESULTS: By using artificial data, we discover that Calinski-Harabasz outperformed other internal indices in indicating the real number of clusters. The tests also suggested that K-means with Euclidean distance was the best method among the ones studied. With the application to both the mobility and fatalities datasets, we found two groups in each one. CONCLUSIONS: Our analysis enables us to discover that European northern countries had more mobility during the first confinement and that the deaths caused by COVID-19 started to drop around the 40th day since the first death.

Staff detection with stable paths.

The preservation of musical works produced in the past requires their digitalization and transformation into a machine-readable format. The processing of handwritten musical scores by computers remains far from ideal. One of the fundamental stages to carry out this task is the staff line detection. We investigate a general-purpose, knowledge-free method for the automatic detection of music staff lines based on a stable path approach. Lines affected by curvature, discontinuities, and inclination are robustly detected. Experimental results show that the proposed technique consistently outperforms well-established algorithms.

Averse Deep Semantic Segmentation.

Semantic segmentation consists in predicting whether any given pixel is part of the object of interest or not. Two types of errors are therefore possible: false positives and false negatives. For visualization and emphasis purposes, we might want to put special effort into reducing one type of error in detriment of the other. A common practice is to define the two types of errors as a relative trade-off using a cost matrix. However, it might be more natural for humans to define the trade-off in terms of an absolute constraint on one type of errors while trying to minimize the other. Previously, we suggested possible approaches to introduce this absolute trade-off in binary classifiers. Extending to semantic segmentation, we propose a threshold on the sigmoid layer and modifications to gradient descent such as adding a new term to the loss function and training in two phases. The latter produced the more resilient results, with a simple threshold being sufficient in most cases.

Opportunities and Limitations of Crop Phenotyping in Southern European Countries.

The Mediterranean climate is characterized by hot dry summers and frequent droughts. Mediterranean crops are frequently subjected to high evapotranspiration demands, soil water deficits, high temperatures, and photo-oxidative stress. These conditions will become more severe due to global warming which poses major challenges to the sustainability of the agricultural sector in Mediterranean countries. Selection of crop varieties adapted to future climatic conditions and more tolerant to extreme climatic events is urgently required. Plant phenotyping is a crucial approach to address these challenges. High-throughput plant phenotyping (HTPP) helps to monitor the performance of improved genotypes and is one of the most effective strategies to improve the sustainability of agricultural production. In spite of the remarkable progress in basic knowledge and technology of plant phenotyping, there are still several practical, financial, and political constraints to implement HTPP approaches in field and controlled conditions across the Mediterranean. The European panorama of phenotyping is heterogeneous and integration of phenotyping data across different scales and translation of "phytotron research" to the field, and from model species to crops, remain major challenges. Moreover, solutions specifically tailored to Mediterranean agriculture (e.g., crops and environmental stresses) are in high demand, as the region is vulnerable to climate change and to desertification processes. The specific phenotyping requirements of Mediterranean crops have not yet been fully identified. The high cost of HTPP infrastructures is a major limiting factor, though the limited availability of skilled personnel may also impair its implementation in Mediterranean countries. We propose that the lack of suitable phenotyping infrastructures is hindering the development of new Mediterranean agricultural varieties and will negatively affect future competitiveness of the agricultural sector. We provide an overview of the heterogeneous panorama of phenotyping within Mediterranean countries, describing the state of the art of agricultural production, breeding initiatives, and phenotyping capabilities in five countries: Italy, Greece, Portugal, Spain, and Turkey. We characterize some of the main impediments for development of plant phenotyping in those countries and identify strategies to overcome barriers and maximize the benefits of phenotyping and modeling approaches to Mediterranean agriculture and related sustainability.

Antioxidant, anti-inflammatory and cytotoxic/antitumoral bioactives from the phylum Basidiomycota and their possible mechanisms of action.

Biologically active compounds from species of the phylum Basidiomycota have been shown a wide range of pharmacological activities and provide a vast reservoir of potential innovational drugs. The aim of this review is to discuss some mechanisms of action involved in antioxidant, anti-inflammatory and cytotoxic/antitumoral activities attributed to the bioactive compounds from species of the phylum Basidiomycota. We show that isolated compounds from extracts, secondary metabolites and polysaccharides that presented antioxidant properties have mechanisms of action involved in the elimination/capture of free radicals and reduction of lipid peroxidation. Also, some bioactives with anti-inflammatory activity were reported to enhance innate and cell-mediated immune responses. Finally, compounds that presented cytotoxic/antitumoral activity induces increased free radical production, collapse of the mitochondrial membrane potential and increased expression of proteins responsible for cell cycle arrest and apoptosis. Investigating the mechanisms of action of biologically active compounds will facilitate further efforts to accelerate the discovery of novel therapeutic strategies.

Prevalence, severity, and risk factors for erectile dysfunction in a representative sample of 3,548 portuguese men aged 40 to 69 years attending primary healthcare centers: results of the Portuguese erectile dysfunction study.

INTRODUCTION: Many studies of the prevalence of erectile dysfunction have been conducted in several countries. This is the first Portuguese study that provides current and comparative data on the prevalence of erectile dysfunction. AIM: The main objective was to estimate the prevalence of erectile dysfunction in men aged 40 to 69 years and correlate erectile dysfunction to certain risk factors. MAIN OUTCOME MEASURES: Evaluation of erectile dysfunction was achieved using the International Index of Erectile Function (IIEF), a 15-item questionnaire that has been developed and validated as a brief and reliable self-administered scale for accessing erectile function. METHODS: The Portuguese Erectile Dysfunction Study was based on a questionnaire that included socio-demographic variables, information on lifestyle and risk factors, and the IIEF. In total, 3,548 questionnaires were administered to men aged 40 to 69 years in 50 primary healthcare centers between July 2004 and January 2005 in a combination of both self-administration and interviews. Erectile dysfunction was defined as the inability to achieve and maintain an erection sufficient to permit satisfactory sexual intercourse. RESULTS: The response rate was 81.3%. The total prevalence of erectile dysfunction was 48.1% (age-adjusted). Prevalence increases with age: 29%, 50%, and 74% in men aged 40 to 49 years, 50 to 59 years, and 60 to 69 years, respectively. Severity of erectile dysfunction also increases with age: 1%, 2%, and 10% of complete erectile dysfunction in men aged 40 to 49 years, 50 to 59 years, and 60 to 69 years, respectively. CONCLUSIONS: The prevalence of erectile dysfunction is strongly related to age. There is also a correlation with the health status of participants.

The unimodal model for the classification of ordinal data.

Many real life problems require the classification of items into naturally ordered classes. These problems are traditionally handled by conventional methods intended for the classification of nominal classes where the order relation is ignored. This paper introduces a new machine learning paradigm intended for multi-class classification problems where the classes are ordered. The theoretical development of this paradigm is carried out under the key idea that the random variable class associated with a given query should follow a unimodal distribution. In this context, two approaches are considered: a parametric, where the random variable class is assumed to follow a specific discrete distribution; a nonparametric, where the random variable class is assumed to be distribution-free. In either case, the unimodal model can be implemented in practice by means of feedforward neural networks and support vector machines, for instance. Nevertheless, our main focus is on feedforward neural networks. We also introduce a new coefficient, r(int), to measure the performance of ordinal data classifiers. An experimental study with artificial and real datasets is presented in order to illustrate the performances of both parametric and nonparametric approaches and compare them with the performances of other methods. The superiority of the parametric approach is suggested, namely when flexible discrete distributions, a new concept introduced here, are considered.

SpotOn: High Accuracy Identification of Protein-Protein Interface Hot-Spots.

We present SpotOn, a web server to identify and classify interfacial residues as Hot-Spots (HS) and Null-Spots (NS). SpotON implements a robust algorithm with a demonstrated accuracy of 0.95 and sensitivity of 0.98 on an independent test set. The predictor was developed using an ensemble machine learning approach with up-sampling of the minor class. It was trained on 53 complexes using various features, based on both protein 3D structure and sequence. The SpotOn web interface is freely available at: http://milou.science.uu.nl/services/SPOTON/ .

Modelling ordinal relations with SVMs: An application to objective aesthetic evaluation of breast cancer conservative treatment.

The cosmetic result is an important endpoint for breast cancer conservative treatment (BCCT), but the verification of this outcome remains without a standard. Objective assessment methods are preferred to overcome the drawbacks of subjective evaluation. In this paper a novel algorithm is proposed, based on support vector machines, for the classification of ordinal categorical data. This classifier is then applied as a new methodology for the objective assessment of the aesthetic result of BCCT. Based on the new classifier, a semi-objective score for quantification of the aesthetic results of BCCT was developed, allowing the discrimination of patients into four classes.

[Goiter and pregnancy]. / Bócio e gravidez.

The author refers to the changes occurred in thyroid dimensions during pregnancy, evaluated clinically and echographically. He also describes the changes in thyroid normal function on pregnant women and the different stages of the fetal thyroid maturation. Some complementary tests must be carried out, when there is a presence of a goitre nodule, which opportunity and relevance the need are discussed. The possibility of thyroid carcinoma is referred as its most adequate treatment.

Behavioral and neurochemical studies in mice pretreated with garcinielliptone FC in pilocarpine-induced seizures.

Garcinielliptone FC (GFC) isolated from hexanic fraction seed extract of species Platonia insignis Mart. It is widely used in folk medicine to treat skin diseases in both humans and animals as well as the seed decoction has been used to treat diarrheas and inflammatory diseases. However, there is no research on GFC effects in the central nervous system of rodents. The present study aimed to evaluate the GFC effects at doses of 25, 50 or 75 mg/kg on seizure parameters to determine their anticonvulsant activity and its effects on amino acid (γ-aminobutyric acid (GABA), glutamine, aspartate and glutathione) levels as well as on acetylcholinesterase (AChE) activity in mice hippocampus after seizures. GFC produced an increased latency to first seizure, at doses 25mg/kg (20.12 ± 2.20 min), 50mg/kg (20.95 ± 2.21 min) or 75 mg/kg (23.43 ± 1.99 min) when compared with seized mice. In addition, GABA content of mice hippocampus treated with GFC75 plus P400 showed an increase of 46.90% when compared with seized mice. In aspartate, glutamine and glutamate levels detected a decrease of 5.21%, 13.55% and 21.80%, respectively in mice hippocampus treated with GFC75 plus P400 when compared with seized mice. Hippocampus mice treated with GFC75 plus P400 showed an increase in AChE activity (63.30%) when compared with seized mice. The results indicate that GFC can exert anticonvulsant activity and reduce the frequency of installation of pilocarpine-induced status epilepticus, as demonstrated by increase in latency to first seizure and decrease in mortality rate of animals. In conclusion, our data suggest that GFC may influence in epileptogenesis and promote anticonvulsant actions in pilocarpine model by modulating the GABA and glutamate contents and of AChE activity in seized mice hippocampus. This compound may be useful to produce neuronal protection and it can be considered as an anticonvulsant agent.