Bacterial-derived RNA and DNA can function as ligands for intracellular receptor activation and induce downstream signaling to modulate the host response to bacterial infection. The mechanisms ...underlying the secretion of immunomodulatory RNA and DNA by pathogens such as Staphylococcus aureus and their delivery to intracellular host cell receptors are not well understood. Recently, extracellular membrane vesicle (MV) production has been proposed as a general secretion mechanism that could facilitate the delivery of functional bacterial nucleic acids into host cells. S. aureus produce membrane-bound, spherical, nano-sized, MVs packaged with a select array of bioactive macromolecules and they have been shown to play important roles in bacterial virulence and in immune modulation through the transmission of biologic signals to host cells. Here we show that S. aureus secretes RNA and DNA molecules that are mostly protected from degradation by their association with MVs. Importantly, we demonstrate that MVs can be delivered into cultured macrophage cells and subsequently stimulate a potent IFN-β response in recipient cells via activation of endosomal Toll-like receptors. These findings advance our understanding of the mechanisms by which bacterial nucleic acids traffic extracellularly to trigger the modulation of host immune responses.
•Active ageing is multidimensional: health-participation-lifelong learning-security.•There is no consensus on how to measure the construct and its different components.•Little care is paid to the ...role of active ageing in reducing mortality as people age.•We identified the factor structure of each active ageing domain using principal component analysis.•Promoting the physical health component of active ageing is key to enhance survival.
The World Health Organization’s active ageing model is based on the optimisation of four key “pillars”: health, lifelong learning, participation and security. It provides older people with a policy framework to develop their potential for well-being, which in turn, may facilitate longevity. We sought to assess the effect of active ageing on longer life expectancy by: i) operationalising the WHO active ageing framework, ii) testing the validity of the factors obtained by analysing the relationships between the pillars, and iii) exploring the impact of active ageing on survival through the health pillar.
Based on data from a sample of 801 community-dwelling older adults, we operationalised the active ageing model by taking each pillar as an individual construct using principal component analysis. The interrelationship between components and their association with survival was analysed using multiple regression models.
A three-factor structure was obtained for each pillar, except for lifelong learning with a single component. After adjustment for age, gender and marital status, survival was only significantly associated with the physical component of health (HR = 0.66; 95% CI = 0.47−0.93; p = 0.018). In turn, this component was loaded with representative variables of comorbidity and functionality, cognitive status and lifestyles, and correlated with components of lifelong learning, social activities and institutional support.
According to how the variables clustered into the components and how the components intertwined, results suggest that the variables loading on the biomedical component of the health pillar (e.g. cognitive function, health conditions or pain), may play a part on survival chances.
Aims.
We aim to perform consistent comparisons between observations and simulations on the mass dependence of the galaxy major merger fraction at low redshift over an unprecedentedly wide range of ...stellar masses (∼10
9
to 10
12
M
⊙
).
Methods.
We first carry out forward modelling of ideal synthetic images of major mergers and non-mergers selected from the Next Generation Illustris Simulations (IllustrisTNG) to include major observational effects. We then train deep convolutional neural networks (CNNs) using realistic mock observations of galaxy samples from the simulations. Subsequently, we apply the trained CNNs to real the Kilo-Degree Survey (KiDS) images of galaxies selected from the Galaxy And Mass Assembly (GAMA) survey. Based on the major merger samples, which are detected in a consistent manner in the observations and simulations, we determine the dependence of major merger fraction on stellar mass at
z
∼ 0.15 and make comparisons between the two.
Results.
The detected major merger fraction in the GAMA/KiDS observations has a fairly mild decreasing trend with increasing stellar mass over the mass range 10
9
M
⊙
<
M
*
< 10
11.5
M
⊙
. There is good agreement in the mass dependence of the major merger fraction in the GAMA/KiDS observations and the IllustrisTNG simulations over 10
9.5
M
⊙
<
M
*
< 10
10.5
M
⊙
. However, the observations and the simulations show some differences at
M
*
> 10
10.5
M
⊙
, possibly due to the supermassive blackhole feedback in its low-accretion state in the simulations which causes a sharp transition in the quenched fractions at this mass scale. The discrepancy could also be due to the relatively small volume of the simulations and/or differences in how stellar masses are measured in simulations and observations.
Sleep is traditionally constituted of two global behavioral states, non-rapid eye movement (NREM) and rapid eye movement (REM), characterized by quiescence and reduced responsiveness to sensory ...stimuli 1. NREM sleep is distinguished by slow waves and spindles throughout the cerebral cortex and REM sleep by an “activated,” low-voltage fast electroencephalogram (EEG) paradoxically similar to that of wake, accompanied by rapid eye movements and muscle atonia. However, recent evidence has shown that cortical activity patterns during wake and NREM sleep are not as global as previously thought. Local slow waves can appear in various cortical regions in both awake humans 2 and rodents 3–5. Intracranial recordings in humans 6 and rodents 4, 7 have shown that NREM sleep slow waves most often involve only a subset of brain regions that varies from wave to wave rather than occurring near synchronously across all cortical areas. Moreover, some cortical areas can transiently “wake up” 8 in an otherwise sleeping brain. Yet until now, cortical activity during REM sleep was thought to be homogenously wake-like. We show here, using local laminar recordings in freely moving mice, that slow waves occur regularly during REM sleep, but only in primary sensory and motor areas and mostly in layer 4, the main target of relay thalamic inputs, and layer 3. This finding may help explain why, during REM sleep, we remain disconnected from the environment even though the bulk of the cortex shows wake-like, paradoxical activation.
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•Slow waves with neuronal OFF periods, typical of NREM sleep, occur in REM sleep•REM slow waves mainly occur in layers 3 and 4 of primary sensory and motor cortex•REM slow waves may partly account for sensory disconnection during REM sleep
During REM sleep, the scalp EEG shows low-voltage fast activity as in wake, yet subjects do not respond to mild stimuli. Funk et al. show that slow waves, a hallmark of NREM sleep, also occur during REM sleep in middle and superficial layers of primary cortices. These slow waves may partly explain the sensory disconnection of REM sleep.
A Random Forest (RF) classifier was applied to spectral as well as mono- and multi-seasonal textural features extracted from Landsat TM imagery to increase the accuracy of land cover classification ...over a complex Mediterranean landscape, with a large number of land cover categories and low inter-class separability. Five different types of geostatistical textural measure for three different window sizes and three different lags were applied creating a total of 972 potential input variables. Madograms, rodograms and direct variograms for the univariate case and cross- and pseudo-cross variograms for the multivariate case, together with multi-seasonal spectral information, were used in a RF classifier to map the land cover types. The pseudo-cross and cross variograms were used specifically to incorporate important seasonal/temporal information. Incorporating multi-scale textural features into the RF models led to an increase in the overall index of 10.71% and, for the most accurate classification, the increase was up to 30% in some classes. The differences in the kappa coefficient for the textural classification models were evaluated statistically using a pairwise Z-test, revealing a significant increase in per-class classification accuracy compared to GLCM-based texture measures. The pseudo-cross variogram between the visible and near-infrared bands was the most important textural features for general classification, and the multi-seasonal pseudo-cross variogram had an outstanding importance for agricultural classes. Overall, the RF classifier applied to a reduced subset of input variables composed of the most informative textural features led to the highest accuracy. Highly reliable classification results were obtained when the 16 most important textural features calculated at single scales (window sizes) were selected and used in the classification. The proposed methodology significantly increased the classification accuracy achieved with a spectral maximum likelihood classifier (ML). The kappa values for the textural RF and ML classifications were equal to 0.92 and 0.83, respectively.
► We assess the increase in accuracy that can be achieved by incorporating geostatistical texture in Random Forest classifiers. ► The proposed method is based on the analysis of mono- and multi-seasonal textural features. ► Pseudo-cross and cross variograms were used to incorporate the seasonal/temporal dimension. ► Our approach outperforms GLCM-based approaches. ► Random Forest classification system was utilised to determine and select the most important textural features.
Nocardia, a Gram-positive bacterium, is responsible for rare and severe infections. Accurate microbiological data are essential to guide antibiotic treatment. Our primary objective was to describe ...species identification and results of antimicrobial susceptibility testing (AST) for Nocardia isolates analysed over a 6-year period. Secondary objectives were to study temporal trends in species distribution and AST results.
We retrospectively analysed results from Nocardia isolates sent between January 2010 and December 2015 to a French laboratory dedicated to Nocardia (Observatoire Français des Nocardioses). Species identification was obtained by amplification and sequencing of a 600-bp fragment of the 16S rRNA gene (for all isolates) and of hsp65 (when required). AST was performed using disk diffusion.
We included 793 Nocardia isolates, mostly from the lungs (53.8%). The most frequent species were Nocardia farcinica (20.2%), Nocardia abscessus complex (19.9%) and Nocardia nova complex (19.5%). The proportion of N. farcinica increased significantly over time from 13% in 2010 to 27.6% in 2014. Linezolid, amikacin, trimethoprim-sulfamethoxazole, minocycline and imipenem were the most frequently identified active antibiotics with, respectively, 0% (0/734), 2.9% (21/730), 5.4% (40/734), 9.4% (69/734) and 19.5% (143/732) of isolates not susceptible. Nocardia farcinica was frequently not susceptible to cefotaxime (118/148, 79.7% of the isolates), but only about 5% of Nocardia cyriacigeorgica and N. abscessus complex isolates were not susceptible to cefotaxime.
In this first epidemiological study of Nocardia isolated from human samples in France, N. farcinica was the species most frequently identified and its prevalence increased over time.
During the southern summer of 2020, large phytoplankton blooms were detected using satellite technology in Chile (western Patagonia), where intensive salmonid aquaculture is carried out. Some ...harvesting sites recorded massive fish mortalities, which were associated with the presence of the dinoflagellate species Cochlodinium sp. The bloom included other phytoplankton species, as Lepidodinium chlorophorum, which persistently changed the colour of the ocean to green. These blooms coincided with the government-managed emergency lockdown due to the COVID-19 pandemic. Local in situ sampling was slowed down. However, imagery from the Copernicus programme allowed operational monitoring. This study shows the benefits of both Sentinel-3 and Sentinel-2 satellites in terms of their spectral, spatial and temporal capabilities for improved algal bloom monitoring. These novel tools, which can foster optimal decision-making, are available for delivering early alerts in situations of natural catastrophes and blockages, such as those occurred during the global COVID-19 lockdown.
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•Copernicus programme provides crucial data during the COVID-19 lockdown in Chile.•Sentinel-2/3 satellites allow monitoring an algal bloom harmful for the aquaculture.•A dinoflagellates bloom produces massive salmonid mortalities in the harvesting sites.•Mesoscale and high-resolution satellite data detect precise location of the HAB.•Early alarm during pandemic or catastrophic events can advance optimal decision-making.
•Landsystem science produced many empirical results but lacks progress in theory.•We review theories on causes of changes in land use extent and intensity.•We synthesize middle-range theories of ...systemic land system processes.•Theories of land-use spillovers (land sparing and rebound effects with intensification, leakage).•Theories of land-use transitions (structural non-linear changes, including forest transition).
Changes in land systems generate many sustainability challenges. Identifying more sustainable land-use alternatives requires solid theoretical foundations on the causes of land-use/cover changes. Land system science is a maturing field that has produced a wealth of methodological innovations and empirical observations on land-cover and land-use change, from patterns and processes to causes. We take stock of this knowledge by reviewing and synthesizing the theories that explain the causal mechanisms of land-use change, including systemic linkages between distant land-use changes, with a focus on agriculture and forestry processes. We first review theories explaining changes in land-use extent, such as agricultural expansion, deforestation, frontier development, and land abandonment, and changes in land-use intensity, such as agricultural intensification and disintensification. We then synthesize theories of higher-level land system change processes, focusing on: (i) land-use spillovers, including land sparing and rebound effects with intensification, leakage, indirect land-use change, and land-use displacement, and (ii) land-use transitions, defined as structural non-linear changes in land systems, including forest transitions. Theories focusing on the causes of land system changes span theoretically and epistemologically disparate knowledge domains and build from deductive, abductive, and inductive approaches. A grand, integrated theory of land system change remains elusive. Yet, we show that middle-range theories – defined here as contextual generalizations that describe chains of causal mechanisms explaining a well-bounded range of phenomena, as well as the conditions that trigger, enable, or prevent these causal chains –, provide a path towards generalized knowledge of land systems. This knowledge can support progress towards sustainable social-ecological systems.
Acidic oxidation methods have been widely reported as an effective method to purify and functionalize the surface of carbon nanotubes (CNTs). Although effective, the strong acids typically employed ...and the high sonication power used to disperse the nanotubes in the solution frequently cause nanotube damage, limiting their great potential as mechanical and electrical reinforcements. This work examines the use of HNO
3, H
2SO
4 and H
2O
2 at relatively low concentrations, short treatment times and low sonication power, in an attempt to achieve experimental conditions which efficiently functionalize the surface of multiwalled CNTs minimizing nanotube damage. A low power sonochemical treatment employing 3.0
M HNO
3 for 2
h followed by 2
h of identical treatment with H
2O
2 proved to be the most effective for this aim.
In the last decade, it has been revealed that androgens play a direct and important role in regulating female reproductive function. Androgens mediate their actions via the androgen receptor (AR), ...and global and cell-specific Ar-knockout mouse models have confirmed that AR-mediated androgen actions play a role in regulating female fertility and follicle health, development and ovulation. This knowledge, along with the clinical data reporting a beneficial effect of androgens or androgen-modulating agents in augmenting in vitro fertilization (IVF) stimulation in women termed poor responders, has supported the adoption of this concept in many IVF clinics worldwide. On the other hand, substantial evidence from human and animal studies now supports the hypothesis that androgens in excess, acting via the AR, play a key role in the origins of polycystic ovary syndrome (PCOS). The identification of the target sites of these AR actions and the molecular mechanisms involved in underpinning the development of PCOS is essential to provide the knowledge required for the future development of novel, mechanism-based therapies for the treatment of PCOS. This review will summarize the basic scientific discoveries that have enhanced our knowledge of the roles of androgens in female reproductive function, discuss the impact these findings have had in the clinic and how a greater understanding of the role androgens play in female physiology may shape the future development of effective strategies to improve IVF outcomes in poor responders and the amelioration of symptoms in patients with PCOS.
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