Latency reversal agents affect differently the latent reservoir present in distinct CD4+ T subpopulations.

Latency reversal agents (LRAs) have proven to induce HIV-1 transcription in vivo but are ineffective at decreasing the size of the latent reservoir in antiretroviral treated patients. The capacity of the LRAs to perturb the viral reservoir present in distinct subpopulations of cells is currently unknown. Here, using a new RNA FISH/flow ex vivo viral reactivation assay, we performed a comprehensive assessment of the viral reactivation capacity of different families of LRAs, and their combinations, in different CD4+ T cell subsets. We observed that a median of 16.28% of the whole HIV-reservoir induced HIV-1 transcripts after viral reactivation, but only 10.10% of these HIV-1 RNA+ cells produced the viral protein p24. Moreover, none of the LRAs were powerful enough to reactivate HIV-1 transcription in all CD4+ T cell subpopulations. For instance, the combination of Romidepsin and Ingenol was identified as the best combination of drugs at increasing the proportion of HIV-1 RNA+ cells, in most, but not all, CD4+ T cell subsets. Importantly, memory stem cells were identified as highly resistant to HIV-1 reactivation, and only the combination of Panobinostat and Bryostatin-1 significantly increased the number of cells transcribing HIV within this subset. Overall, our results validate the use of the RNA FISH/flow technique to assess the potency of LRAs among different CD4+ T cell subsets, manifest the intrinsic differences between cells that encompass the latent HIV reservoir, and highlight the difficulty to significantly impact the latent infection with the currently available drugs. Thus, our results have important implications for the rational design of therapies aimed at reversing HIV latency from diverse cellular reservoirs.

Near-ground effect of height on pollen exposure.

The effect of height on pollen concentration is not well documented and little is known about the near-ground vertical profile of airborne pollen. This is important as most measuring stations are on roofs, but patient exposure is at ground level. Our study used a big data approach to estimate the near-ground vertical profile of pollen concentrations based on a global study of paired stations located at different heights. We analyzed paired sampling stations located at different heights between 1.5 and 50 m above ground level (AGL). This provided pollen data from 59 Hirst-type volumetric traps from 25 different areas, mainly in Europe, but also covering North America and Australia, resulting in about 2,000,000 daily pollen concentrations analyzed. The daily ratio of the amounts of pollen from different heights per location was used, and the values of the lower station were divided by the higher station. The lower station of paired traps recorded more pollen than the higher trap. However, while the effect of height on pollen concentration was clear, it was also limited (average ratio 1.3, range 0.7-2.2). The standard deviation of the pollen ratio was highly variable when the lower station was located close to the ground level (below 10 m AGL). We show that pollen concentrations measured at >10 m are representative for background near-ground levels.

Comprehensive analysis of different adhesives in aerobiological sampling using optical microscopy and high-throughput DNA sequencing.

The standardization and unification of the procedures to analyze and quantify the airborne pollen concentrations are very important topics. In this work, the effectiveness of the two most used adhesives in aerobiological sampling, silicone prepared with cyclohexane solvent (Silicone) and petroleum jelly (Vaseline), was compared under outdoor conditions. This comparison was carried out using the traditional method based on the identification and quantification by optical microscopy (OM) of the airborne pollen and the novel methodology by high-throughput sequencing analysis (HTS). Globally, the results from both methods of analysis (OM and HTS) showed a good agreement between the two adhesives tested regarding the abundance of the main pollen types present in the samples: Cupressaceae, Olea, Poaceae, Platanus, Quercus. We concluded that the results from both adhesives are comparable data. Furthermore, the comparisons between methodologies, OM vs. HTS, showed that both techniques can accurately identify the most abundant pollen types in the atmosphere for the studied periods, with a good agreement of their relative abundances especially when the airborne pollen diversity is low but showing some divergences as the number of pollen types increases.

Assessing allergenicity in urban parks: A nature-based solution to reduce the impact on public health.

Urban parks play a key role in the provision of ecosystem services, actively participating in improving the quality of life and welfare of local residents. This paper reports on the application of an index designed to quantify the allergenicity of urban parks in a number of Spanish cities. The index, which records biological and biometric parameters for the tree species growing there, classifies parks in terms of the risk they pose for allergy sufferers, graded as null, low, moderate or high. In this initial phase, the index was applied to 26 green areas in 24 Spanish cities; green areas varied in type (urban park, historical or modern garden, boulevard, square or urban forest), size 1-100 ha), geographical location, species richness, number of trees and tree density (number of trees / ha.). The data obtained were used to calculate the percentage of allergenic species in each park, which varied between 17-67%; density ranged from 100 to 300 trees/ha. The index values recorded ranged from a minimum of .07 to a maximum of .87; a significant correlation was found between index value and both number of trees and tree density. Taking an index value of .30 as the threshold considered sufficient to trigger allergy symptoms in the sensitive population, 12 of the parks studied may be regarded as unhealthy at any time of the year. Corrective measures to mitigate the impact of pollen emissions include the implementation of nature-based solutions at various levels: planning and design, handling and management, and strengthening of urban green-infrastructure elements. The index proved to be a useful tool for environmental analysis, and complies with the principles of portability and scalability central to current and horizon scientific research.

Modeling pollen time series using seasonal-trend decomposition procedure based on LOESS smoothing.

Analysis of airborne pollen concentrations provides valuable information on plant phenology and is thus a useful tool in agriculture-for predicting harvests in crops such as the olive and for deciding when to apply phytosanitary treatments-as well as in medicine and the environmental sciences. Variations in airborne pollen concentrations, moreover, are indicators of changing plant life cycles. By modeling pollen time series, we can not only identify the variables influencing pollen levels but also predict future pollen concentrations. In this study, airborne pollen time series were modeled using a seasonal-trend decomposition procedure based on LOcally wEighted Scatterplot Smoothing (LOESS) smoothing (STL). The data series-daily Poaceae pollen concentrations over the period 2006-2014-was broken up into seasonal and residual (stochastic) components. The seasonal component was compared with data on Poaceae flowering phenology obtained by field sampling. Residuals were fitted to a model generated from daily temperature and rainfall values, and daily pollen concentrations, using partial least squares regression (PLSR). This method was then applied to predict daily pollen concentrations for 2014 (independent validation data) using results for the seasonal component of the time series and estimates of the residual component for the period 2006-2013. Correlation between predicted and observed values was r = 0.79 (correlation coefficient) for the pre-peak period (i.e., the period prior to the peak pollen concentration) and r = 0.63 for the post-peak period. Separate analysis of each of the components of the pollen data series enables the sources of variability to be identified more accurately than by analysis of the original non-decomposed data series, and for this reason, this procedure has proved to be a suitable technique for analyzing the main environmental factors influencing airborne pollen concentrations.

Characterisation of the airborne pollen spectrum in Guadalajara (central Spain) and estimation of the potential allergy risk.

Aerobiological research into airborne pollen diversity and seasonal variations in pollen counts has become increasingly important over recent decades due to the growing incidence of asthma, rhinitis and other pollen-related allergic conditions. Airborne pollen in Guadalajara (Castilla-La Mancha, Spain) was studied over a 6-year period (2008-2013) using a Hirst-type volumetric spore trap. The highest pollen concentrations were recorded from February to June, coinciding with the pollen season of the pollen types that most contribute to the local airborne pollen spectrum: Cupressaceae (32.2%), Quercus (15.1%), Platanus (13.2%), Olea (8.3%), Populus (7.8%) and Poaceae (7.2%). These are therefore critical months for allergy sufferers. The pollen calendar was typically Mediterranean and comprised 25 pollen types. Between January and March, Cupressaceae pollen concentrations exceeded allergy risk thresholds on 38 days. Other woody species such as Olea and Platanus have a shorter pollen season, and airborne concentrations exceeded allergy risk thresholds on around 13 days in each case. Poaceae pollen concentrations attained allergy risk levels on 26 days between May and July. Other highly allergenic pollen types included Urticaceae and Chenopodiaceae-Amaranthaceae, though these are less abundant than other pollen types in Guadalajara and did not exceed risk thresholds on more than 3 and 5 days, respectively.

Models for forecasting the flowering of Cornicabra olive groves.

This study examined the impact of weather-related variables on flowering phenology in the Cornicabra olive tree and constructed models based on linear and Poisson regression to forecast the onset and length of the pre-flowering and flowering phenophases. Spain is the world's leading olive oil producer, and the Cornicabra variety is the second largest Spanish variety in terms of surface area. However, there has been little phenological research into this variety. Phenological observations were made over a 5-year period (2009-2013) at four sampling sites in the province of Toledo (central Spain). Results showed that the onset of the pre-flowering phase is governed largely by temperature, which displayed a positive correlation with the temperature in the start of dormancy (November) and a negative correlation during the months prior to budburst (January, February and March). A similar relationship was recorded for the onset of flowering. Other weather-related variables, including solar radiation and rainfall, also influenced the succession of olive flowering phenophases. Linear models proved the most suitable for forecasting the onset and length of the pre-flowering period and the onset of flowering. The onset and length of pre-flowering can be predicted up to 1 or 2 months prior to budburst, whilst the onset of flowering can be forecast up to 3 months beforehand. By contrast, a nonlinear model using Poisson regression was best suited to predict the length of the flowering period.

Airborne pollen of allergenic herb species in Toledo (Spain).

This study analysed airborne pollen counts for allergenic herb taxa in Toledo (central Spain), a major tourist city receiving over 2 million visitors per year, located in the region of Castilla-La Mancha. The taxa selected were Chenopodiaceae-Amaranthaceae, Plantago, Poaceae and Urticaceae, all of which produce allergenic pollen giving rise to serious symptoms in pollen-allergy sufferers. Aerobiological data were recorded over a 6-year period (2005 to 2010) using the sampling and analysis procedures recommended by the Spanish Aerobiology Network. The abundance and the temporal (annual, daily and intradiurnal) distribution of these pollen types were analysed, and the influence of weather-related factors on airborne pollen counts was assessed. Pollen from herbaceous species accounted for 20.9% of total airborne pollen in Toledo, the largest contributor being Poaceae, with 8.5% of the total pollen count; this family was also the leading cause of respiratory allergies. Examination of intradiurnal variation revealed three distinct distribution patterns: (1) peak daily counts for Chenopodiaceae-Amaranthaceae and Plantago were recorded during the hottest part of the day, i.e. from 1400 to 1600 hours; (2) Urticaceae displayed two peaks (1400-1600 and 2200 hours); and (3) Poaceae counts remained fairly stable throughout the day. Two main risk periods were identified for allergies: spring, with allergies caused by Urticaceae, Plantago and Poaceae pollen, and summer, due to Chenopodiaceae-Amaranthaceae pollen.

Atmospheric pollen allergen load and environmental patterns in central and southwestern Iberian Peninsula.

Over one quarter of the population in industrialised countries suffers from some type of allergy and inhaled aeroallergens from pollen are the primary cause of allergic ailments. The networks for monitoring biological air quality measure the airborne pollen concentrations that characterize periods of exposure to major airborne aeroallergens but there are certain discrepancies in relation to the allergen-pollen dynamic. In this paper we analyse the airborne allergens Ole e 1, Phl p 1, Phl p 5 and Pla a 1, and interpreted the adjustments and mismatches in their concentrations in relation to airborne pollen. The influence of main environmental patterns was considered. The study was conducted in two urban areas of the centre and southwest of the Iberian Peninsula (Toledo in Spain and Évora in Portugal). Monitoring for pollen followed the standard protocol using Hirst volumetric spore traps and allergenic particles were quantified by ELISA assay. The results indicate that the discrepancies in this relationship were affected by the weather conditions up to 6 days prior. Precipitation and humidity above normal values caused a higher concentration of the allergen Pla a 1. This effect occurred in reverse in the case of humidity for the allergens Ole e 1 and Phl p 1. Humidity and precipitation generated the same pattern in the allergen-pollen relationship in both Phl p 1 and Phl p 5. Our findings show consistent results that allow to interpret the rate of discrepancy between allergen and pollen, and it can be used to improve allergy risk prediction models generated from atmospheric pollen.

Outdoor airborne allergens: Characterization, behavior and monitoring in Europe.

Aeroallergens or inhalant allergens, are proteins dispersed through the air and have the potential to induce allergic conditions such as rhinitis, conjunctivitis, and asthma. Outdoor aeroallergens are found predominantly in pollen grains and fungal spores, which are allergen carriers. Aeroallergens from pollen and fungi have seasonal emission patterns that correlate with plant pollination and fungal sporulation and are strongly associated with atmospheric weather conditions. They are released when allergen carriers come in contact with the respiratory system, e.g. the nasal mucosa. In addition, due to the rupture of allergen carriers, airborne allergen molecules may be released directly into the air in the form of micronic and submicronic particles (cytoplasmic debris, cell wall fragments, droplets etc.) or adhered onto other airborne particulate matter. Therefore, aeroallergen detection strategies must consider, in addition to the allergen carriers, the allergen molecules themselves. This review article aims to present the current knowledge on inhalant allergens in the outdoor environment, their structure, localization, and factors affecting their production, transformation, release or degradation. In addition, methods for collecting and quantifying aeroallergens are listed and thoroughly discussed. Finally, the knowledge gaps, challenges and implications associated with aeroallergen analysis are described.

Co-exposure to highly allergenic airborne pollen and fungal spores in Europe.

The study is aimed at determining the potential spatiotemporal risk of the co-occurrence of airborne pollen and fungal spores high concentrations in different bio-climatic zones in Europe. Birch, grass, mugwort, ragweed, olive pollen and Alternaria and Cladosporium fungal spores were investigated at 16 sites in Europe, in 2005-2019. In Central and northern Europe, pollen and fungal spore seasons mainly overlap in June and July, while in South Europe, the highest pollen concentrations occur frequently outside of the spore seasons. In the coldest climate, no allergy thresholds were exceeded simultaneously by two spore or pollen taxa, while in the warmest climate most of the days with at least two pollen taxa exceeding threshold values were observed. The annual air temperature amplitude seems to be the main bioclimatic factor influencing the accumulation of days in which Alternaria and Cladosporium spores simultaneously exceed allergy thresholds. The phenomenon of co-occurrence of airborne allergen concentrations gets increasingly common in Europe and is proposed to be present on other continents, especially in temperate climate.

Models for forecasting airborne Cupressaceae pollen levels in central Spain.

The influence of meteorological variables on airborne Cupressaceae pollen levels in central Spain was analyzed, and prediction models based on polynomial and multiple regressions were used to predict pollen counts throughout the pollen season. The Cupressaceae pollen type was selected in view of both its abundance in the atmosphere of the central Iberian Peninsula (particularly from January to March) and its allergenic importance. Sampling was performed uninterruptedly over a 5-year period, using a Hirst volumetric sampler and the sampling method established by the Spanish Aerobiology Network. Temperature displayed the strongest (positive) correlation with Cupressaceae pollen counts. Polynomial and multiple regression analysis showed that maximum temperature was the most influential variable included in prediction models. The prediction equations obtained for the study period were reasonably satisfactory, accounting for 48% and 59% of the variation in airborne pollen levels.

DDS: integrating data analytics transformations in task-based workflows.

High-performance data analytics (HPDA) is a current trend in e-science research that aims to integrate traditional HPC with recent data analytic frameworks. Most of the work done in this field has focused on improving data analytic frameworks by implementing their engines on top of HPC technologies such as Message Passing Interface. However, there is a lack of integration from an application development perspective. HPC workflows have their own parallel programming models, while data analytic (DA) algorithms are mainly implemented using data transformations and executed with frameworks like Spark. Task-based programming models (TBPMs) are a very efficient approach for implementing HPC workflows. Data analytic transformations can also be decomposed as a set of tasks and implemented with a task-based programming model. In this paper, we present a methodology to develop HPDA applications on top of TBPMs that allow developers to combine HPC workflows and data analytic transformations seamlessly. A prototype of this approach has been implemented on top of the PyCOMPSs task-based programming model to validate two aspects: HPDA applications can be seamlessly developed and have better performance than Spark. We compare our results using different programs. Finally, we conclude with the idea of integrating DA into HPC applications and evaluation of our method against Spark.

Pre-exascale HPC approaches for molecular dynamics simulations. Covid-19 research: A use case.

Exascale computing has been a dream for ages and is close to becoming a reality that will impact how molecular simulations are being performed, as well as the quantity and quality of the information derived for them. We review how the biomolecular simulations field is anticipating these new architectures, making emphasis on recent work from groups in the BioExcel Center of Excellence for High Performance Computing. We exemplified the power of these simulation strategies with the work done by the HPC simulation community to fight Covid-19 pandemics. This article is categorized under:Data Science > Computer Algorithms and ProgrammingData Science > Databases and Expert SystemsMolecular and Statistical Mechanics > Molecular Dynamics and Monte-Carlo Methods.

Environmental drivers of the seasonal exposure to airborne Alternaria spores in Spain.

Alternaria conidia have high allergenic potential and they can trigger important respiratory diseases. Due to that and to their extensive detection period, airborne Alternaria spores are considered as a relevant airborne allergenic particle. Several studies have been developed in order to predict the human exposure to this aeroallergen and to prevent their negative effects on sensitive population. These studies revealed that some sampling locations usually have just one single Alternaria spore season while other locations generally have two seasons within the same year. However, the reasons of these two different seasonal patterns remain unclear. To understand them better, the present study was carried out in order to determine if there are any weather conditions that influence these different behaviours at different sampling locations. With this purpose, the airborne Alternaria spore concentrations of 18 sampling locations in a wide range of latitudinal, altitudinal and climate ranges of Spain were studied. The aerobiological samples were obtained by means of Hirst-Type volumetric pollen traps, and the seasonality of the airborne Alternaria spores were analysed. The optimal weather conditions for spore production were studied, and the main weather factor affecting Alternaria spore seasonality were analysed by means of random forests and regression trees. The results showed that the temperature was the most relevant variable for the Alternaria spore dispersion and it influenced both the spore integrals and their seasonality. The water availability was also a very significant variable. Warmer sampling locations generally have a longer period of Alternaria spore detection. However, the spore production declines during the summer when the temperatures are extremely warm, what splits the favourable period for Alternaria spore production and dispersion into two separate ones, detected as two Alternaria spore seasons within the same year.

The impact of non-additive genetic associations on age-related complex diseases.

Genome-wide association studies (GWAS) are not fully comprehensive, as current strategies typically test only the additive model, exclude the X chromosome, and use only one reference panel for genotype imputation. We implement an extensive GWAS strategy, GUIDANCE, which improves genotype imputation by using multiple reference panels and includes the analysis of the X chromosome and non-additive models to test for association. We apply this methodology to 62,281 subjects across 22 age-related diseases and identify 94 genome-wide associated loci, including 26 previously unreported. Moreover, we observe that 27.7% of the 94 loci are missed if we use standard imputation strategies with a single reference panel, such as HRC, and only test the additive model. Among the new findings, we identify three novel low-frequency recessive variants with odds ratios larger than 4, which need at least a three-fold larger sample size to be detected under the additive model. This study highlights the benefits of applying innovative strategies to better uncover the genetic architecture of complex diseases.

Causes of increased pollen exposure during Saharan-Sahel dust intrusions.

Airborne particulate matter such as mineral dust comes mainly from natural sources, and the African regions of Sahara and Sahel originate large amounts of the aerosols dispersed worldwide. There is little knowledge about the influence of dust episodes on airborne pollen concentrations, and although the centre and southeast of the Iberian Peninsula are frequently affected by dust intrusions, until now, no specific works have analysed the effect of these episodes on airborne pollen concentrations in these areas. The aims of this study were to analyse the simultaneous occurrence of airborne pollen peaks and Saharan-Sahel dust intrusions in the central and south-eastern Iberian Peninsula, and to study the weather conditions - air mass pathways and conditions of air temperature, relative humidity and atmospheric pressure - that influence the airborne pollen concentrations during dust episodes. The results showed that the rise in airborne pollen concentrations during dust episodes is apparent in inland Iberian areas, although not in coastal areas in the southeast where pollen concentrations are even observed to decrease, coinciding with prevailing easterly winds from the sea. Total pollen concentrations and specific pollen types such as Olea, Poaceae and Quercus showed an increase in the central Iberian Peninsula during dust episodes when two meteorological phenomena concur: 1) prevailing winds from extensive areas of major wind-pollinated pollen sources over a medium or short distance (mainly from western and southwestern areas); and 2) optimal meteorological conditions that favour pollen release and dispersal into the atmosphere (mainly high temperatures and subsequently low humidity in central areas). Both conditions often occur during the Saharan-Sahel dust intrusions in the centre. Maximum pollen peaks are therefore most likely to occur during dust episodes in the central Iberian Peninsula, thus dramatically increasing the risk of outbreaks of pollinosis and other respiratory diseases in the population.

BioExcel Building Blocks, a software library for interoperable biomolecular simulation workflows.

In the recent years, the improvement of software and hardware performance has made biomolecular simulations a mature tool for the study of biological processes. Simulation length and the size and complexity of the analyzed systems make simulations both complementary and compatible with other bioinformatics disciplines. However, the characteristics of the software packages used for simulation have prevented the adoption of the technologies accepted in other bioinformatics fields like automated deployment systems, workflow orchestration, or the use of software containers. We present here a comprehensive exercise to bring biomolecular simulations to the "bioinformatics way of working". The exercise has led to the development of the BioExcel Building Blocks (BioBB) library. BioBB's are built as Python wrappers to provide an interoperable architecture. BioBB's have been integrated in a chain of usual software management tools to generate data ontologies, documentation, installation packages, software containers and ways of integration with workflow managers, that make them usable in most computational environments.

Expression of CD20 after viral reactivation renders HIV-reservoir cells susceptible to Rituximab.

The identification of exclusive markers to target HIV-reservoir cells will represent a significant advance in the search for therapies to cure HIV. Here, we identify the B lymphocyte antigen CD20 as a marker for HIV-infected cells in vitro and in vivo. The CD20 molecule is dimly expressed in a subpopulation of CD4-positive (CD4+) T lymphocytes from blood, with high levels of cell activation and heterogeneous memory phenotypes. In lymph node samples from infected patients, CD20 is present in productively HIV-infected cells, and ex vivo viral infection selectively upregulates the expression of CD20 during early infection. In samples from patients on antiretroviral therapy (ART) this subpopulation is significantly enriched in HIV transcripts, and the anti-CD20 monoclonal antibody Rituximab induces cell killing, which reduces the pool of HIV-expressing cells when combined with latency reversal agents. We provide a tool for targeting this active HIV-reservoir after viral reactivation in patients while on ART.

Standardised index for measuring atmospheric grass-pollen emission.

Grass pollen is the main cause of pollen allergy in Europe, and-given its marked allergenic potential and elevated airborne concentrations-constitutes a major public health risk. This study sought to identify the grass species triggering allergies during the highest-risk periods, and to measure the contribution of each species to airborne grass pollen concentrations. This type of research is particularly useful with a view to optimising the prevention and diagnosis of pollen allergies and developing the most effective immunological treatments. To that end, a total of 28 species potentially responsible for allergies were analysed. In order to assess the potential contribution of these species to overall airborne pollen concentrations, an index was designed (Pollen Contribution Index) based on the following parameters for each species: flowering phenology, pollen grain size (polar and equatorial axes), abundance of the species in the area and pollen production. The species contributing most to airborne pollen concentrations were, in order: Dactylis glomerata subsp. hispanica, Lolium rigidum, Trisetum paniceum and Arrhenatherum album. These species all shared certain features: small grain size (and thus greater buoyancy in air), high pollen production and considerable abundance. This Index was applied to a case study in a Mediterranean-climate area of the central Iberian Peninsula, but could equally be applied to other areas and other allergenic pollens. Findings showed that a small number of species were responsible for most airborne grass pollen.