Прецеденты снижения распространенности немецкого языка в Бразилии во второй половине XX вв. (на примере опроса учащихся школ штата Санта-Катарина)

Although functional magnetic resonance imaging (fMRI) has gained increasing importance in investigating neural substrates of anxiety disorders, less is known about the stress eliciting properties of the scanner environment itself. The aim of the study was to investigate feasibility, self-reported distress and anxiety management strategies during an fMRI experiment in a comprehensive sample of patients with panic disorder and agoraphobia (PD/AG). Within the national research network PANIC-NET, n = 89 patients and n = 90 controls participated in a multicenter fMRI study. Subjects completed a retrospective questionnaire on self-reported distress, including a habituation profile and exploratory questions about helpful strategies. Drop-out rates and fMRI quality parameters were employed as markers of study feasibility. Different anxiety measures were used to identify patients particularly vulnerable to increased scanner anxiety and impaired data quality. Three (3.5%) patients terminated the session prematurely. While drop-out rates were comparable for patients and controls, data quality was moderately impaired in patients. Distress was significantly elevated in patients compared to controls; claustrophobic anxiety was furthermore associated with pronounced distress and lower fMRI data quality in patients. Patients reported helpful strategies, including motivational factors and cognitive coping strategies. The feasibility of large-scale fMRI studies on PD/AG patients could be proved. Study designs should nevertheless acknowledge that the MRI setting may enhance stress reactions. Future studies are needed to investigate the relationship between self-reported distress and fMRI data in patient groups that are subject to neuroimaging research

The Impact of Interventions to Prevent Neonatal Healthcare-associated Infections in Low- and Middle-income Countries: A Systematic Review.

BACKGROUND: Clinically suspected and laboratory-confirmed bloodstream infections are frequent causes of morbidity and mortality during neonatal care. The most effective infection prevention and control interventions for neonates in low- and middle-income countries (LMIC) are unknown. AIM: To identify effective interventions in the prevention of hospital-acquired bloodstream infections in LMIC neonatal units. METHODS: Medline, PUBMED, the Cochrane Database of Systematic Reviews, EMBASE and PsychInfo (January 2003 to October 2020) were searched to identify studies reporting single or bundled interventions for prevention of bloodstream infections in LMIC neonatal units. RESULTS: Our initial search identified 5206 articles; following application of filters, 27 publications met the inclusion and Integrated Quality Criteria for the Review of Multiple Study Designs assessment criteria and were summarized in the final analysis. No studies were carried out in low-income countries, only 1 in Sub-Saharan Africa and just 2 in multiple countries. Of the 18 single-intervention studies, most targeted skin (n = 4) and gastrointestinal mucosal integrity (n = 5). Whereas emollient therapy and lactoferrin achieved significant reductions in proven neonatal infection, glutamine and mixed probiotics showed no benefit. Chlorhexidine gluconate for cord care and kangaroo mother care reduced infection in individual single-center studies. Of the 9 studies evaluating bundles, most focused on prevention of device-associated infections and achieved significant reductions in catheter- and ventilator-associated infections. CONCLUSIONS: There is a limited evidence base for the effectiveness of infection prevention and control interventions in LMIC neonatal units; bundled interventions targeting device-associated infections were most effective. More multisite studies with robust study designs are needed to inform infection prevention and control intervention strategies in low-resource neonatal units

Abelhas-sem-ferrão amazônicas defendem meliponários contra saques de outras abelhas

Entre as abelhas eussociais, dois gêneros apresentam estratégia de vida cleptobiótica, obtendo recursos alimentares de ninhos de outras abelhas ao invés de coletá-los em flores. Entre as espécies atacadas existe um gradiente de suscetibilidade ao roubo variando desde espécies vulneráveis até altamente resistentes. Neste trabalho nós descrevemos um ataque de Lestrimelitta rufipes a um ninho de Scaptotrigona sp. em um meliponário na Amazônia central (Amazonas, Brazil). O ninho atacado foi transferido para um meliponário com espécies resistentes (Duckeola ghilianii e Melipona fulva) e as interações foram descritas. As abelhas resistentes contra-atacaram e afugentaram as ladras protegendo o ninho de Scaptotrigona sp.. A presença de comportamento defensivo em gêneros não proximamente relacionados sugere que ele tenha evoluído mais de uma vez entre os Meliponini. Considerando o comportamento descrito, sugerimos a criação de espécies nativas resistentes em meliponários de regiões onde elas forem nativas, devido ao potencial que elas tem na proteção

Evidence for Reductive Genome Evolution and Lateral Acquisition of Virulence Functions in Two Corynebacterium pseudotuberculosis Strains

Ruiz JC, D'Afonseca V, Silva A, et al. Evidence for Reductive Genome Evolution and Lateral Acquisition of Virulence Functions in Two Corynebacterium pseudotuberculosis Strains. PLoS ONE. 2011;6(4): e18551.Background: Corynebacterium pseudotuberculosis, a Gram-positive, facultative intracellular pathogen, is the etiologic agent of the disease known as caseous lymphadenitis (CL). CL mainly affects small ruminants, such as goats and sheep; it also causes infections in humans, though rarely. This species is distributed worldwide, but it has the most serious economic impact in Oceania, Africa and South America. Although C. pseudotuberculosis causes major health and productivity problems for livestock, little is known about the molecular basis of its pathogenicity. Methodology and Findings: We characterized two C. pseudotuberculosis genomes (Cp1002, isolated from goats; and CpC231, isolated from sheep). Analysis of the predicted genomes showed high similarity in genomic architecture, gene content and genetic order. When C. pseudotuberculosis was compared with other Corynebacterium species, it became evident that this pathogenic species has lost numerous genes, resulting in one of the smallest genomes in the genus. Other differences that could be part of the adaptation to pathogenicity include a lower GC content, of about 52%, and a reduced gene repertoire. The C. pseudotuberculosis genome also includes seven putative pathogenicity islands, which contain several classical virulence factors, including genes for fimbrial subunits, adhesion factors, iron uptake and secreted toxins. Additionally, all of the virulence factors in the islands have characteristics that indicate horizontal transfer. Conclusions: These particular genome characteristics of C. pseudotuberculosis, as well as its acquired virulence factors in pathogenicity islands, provide evidence of its lifestyle and of the pathogenicity pathways used by this pathogen in the infection process. All genomes cited in this study are available in the NCBI Genbank database (http://www.ncbi.nlm.nih.gov/genbank/) under accession numbers CP001809 and CP001829

A Rescorla-Wagner Drift-Diffusion Model of Conditioning and Timing

Computational models of classical conditioning have made significant contributions to the theoretic understanding of associative learning, yet they still struggle when the temporal aspects of conditioning are taken into account. Interval timing models have contributed a rich variety of time representations and provided accurate predictions for the timing of responses, but they usually have little to say about associative learning. In this article we present a unified model of conditioning and timing that is based on the influential Rescorla-Wagner conditioning model and the more recently developed Timing Drift-Diffusion model. We test the model by simulating 10 experimental phenomena and show that it can provide an adequate account for 8, and a partial account for the other 2. We argue that the model can account for more phenomena in the chosen set than these other similar in scope models: CSC-TD, MS-TD, Learning to Time and Modular Theory. A comparison and analysis of the mechanisms in these models is provided, with a focus on the types of time representation and associative learning rule used

The Blursday database as a resource to study subjective temporalities during COVID-19

The COVID-19 pandemic and associated lockdowns triggered worldwide changes in the daily routines of human experience. The Blursday database provides repeated measures of subjective time and related processes from participants in nine countries tested on 14 questionnaires and 15 behavioural tasks during the COVID-19 pandemic. A total of 2,840 participants completed at least one task, and 439 participants completed all tasks in the first session. The database and all data collection tools are accessible to researchers for studying the effects of social isolation on temporal information processing, time perspective, decision-making, sleep, metacognition, attention, memory, self-perception and mindfulness. Blursday includes quantitative statistics such as sleep patterns, personality traits, psychological well-being and lockdown indices. The database provides quantitative insights on the effects of lockdown (stringency and mobility) and subjective confinement on time perception (duration, passage of time and temporal distances). Perceived isolation affects time perception, and we report an inter-individual central tendency effect in retrospective duration estimation

Native diversity buffers against severity of non-native tree invasions

Determining the drivers of non-native plant invasions is critical for managing native ecosystems and limiting the spread of invasive species$^{1,2}$. Tree invasions in particular have been relatively overlooked, even though they have the potential to transform ecosystems and economies$^{3,4}$. Here, leveraging global tree databases$^{5,6,7}$, we explore how the phylogenetic and functional diversity of native tree communities, human pressure and the environment influence the establishment of non-native tree species and the subsequent invasion severity. We find that anthropogenic factors are key to predicting whether a location is invaded, but that invasion severity is underpinned by native diversity, with higher diversity predicting lower invasion severity. Temperature and precipitation emerge as strong predictors of invasion strategy, with non-native species invading successfully when they are similar to the native community in cold or dry extremes. Yet, despite the influence of these ecological forces in determining invasion strategy, we find evidence that these patterns can be obscured by human activity, with lower ecological signal in areas with higher proximity to shipping ports. Our global perspective of non-native tree invasion highlights that human drivers influence non-native tree presence, and that native phylogenetic and functional diversity have a critical role in the establishment and spread of subsequent invasions

The global biogeography of tree leaf form and habit

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling

The global biogeography of tree leaf form and habit.

Understanding what controls global leaf type variation in trees is crucial for comprehending their role in terrestrial ecosystems, including carbon, water and nutrient dynamics. Yet our understanding of the factors influencing forest leaf types remains incomplete, leaving us uncertain about the global proportions of needle-leaved, broadleaved, evergreen and deciduous trees. To address these gaps, we conducted a global, ground-sourced assessment of forest leaf-type variation by integrating forest inventory data with comprehensive leaf form (broadleaf vs needle-leaf) and habit (evergreen vs deciduous) records. We found that global variation in leaf habit is primarily driven by isothermality and soil characteristics, while leaf form is predominantly driven by temperature. Given these relationships, we estimate that 38% of global tree individuals are needle-leaved evergreen, 29% are broadleaved evergreen, 27% are broadleaved deciduous and 5% are needle-leaved deciduous. The aboveground biomass distribution among these tree types is approximately 21% (126.4 Gt), 54% (335.7 Gt), 22% (136.2 Gt) and 3% (18.7 Gt), respectively. We further project that, depending on future emissions pathways, 17-34% of forested areas will experience climate conditions by the end of the century that currently support a different forest type, highlighting the intensification of climatic stress on existing forests. By quantifying the distribution of tree leaf types and their corresponding biomass, and identifying regions where climate change will exert greatest pressure on current leaf types, our results can help improve predictions of future terrestrial ecosystem functioning and carbon cycling