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The region of southern Africa (SAF) is among the most exposed climate change hotspots and is projected to experience severe impacts across multiple economical and societal sectors. For this reason, producing reliable projections of the expected impacts of climate change is key for local communities. In this work we use an ensemble of 19 regional climate model (RCM) simulations performed in the context of the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa and a set of 10 global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5) that were used as the driving GCMs in the RCM simulations. We are concerned about the degree to which RCM simulations are influenced by their driving GCMs, with regards to monthly precipitation climatologies, precipitation biases and precipitation change signal, according to the Representative Concentration Pathway (RCP) 8.5 for the end of the 21st century. We investigate the degree to which RCMs and GCMs are able to reproduce specific climatic features over SAF and over three sub-regions, namely the greater Angola region, the greater Mozambique region, and the greater South Africa region. We identify that during the beginning of the rainy season, when regional processes are largely dependent on the coupling between the surface and the atmosphere, the impact of the driving GCMs on the RCMs is smaller compared to the core of the rainy season, when precipitation is mainly controlled by the large-scale circulation. In addition, we show that RCMs are able to counteract the bias received by their driving GCMs; hence, we claim that the cascade of uncertainty over SAF is not additive, but indeed the RCMs do provide improved precipitation climatologies. The fact that certain bias patterns during the historical period (1985–2005) identified in GCMs are resolved in RCMs provides evidence that RCMs are reliable tools for climate change impact studies over SAF. [ABSTRACT FROM AUTHOR]

The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modeling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behavior of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) – Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (October–March), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensembles exhibited improved performance compared to their forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher-resolution regional climate simulations. The CMIP6 ensemble displayed a similar behavior to CMIP5, but reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angola Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic processes that take place. Improvements in observational networks (both in situ and satellite) as well as continued advancements in high-resolution modeling will be critical, in order to develop a robust assessment of climate change for southern Africa. [ABSTRACT FROM AUTHOR]

The region of southern Africa (SAF) is among the most exposed climate change hotspots and is projected to experience severe impacts on multiple economical and societal sectors. For this reason, producing reliable projections of the expected impacts of climate change is key for local communities. In this work we use a set of 19 regional climate models (RCMs) performed in the context of the Coordinated Regional Climate Downscaling Experiment (CORDEX) - Africa and a set of 10 global climate models (GCMs) participating in the Coupled Model Intercomparison Project Phase 5 (CMIP5), that were used as the driving GCMs in the RCM simulations. We are concerned about the degree to which RCM simulations are influenced by their driving GCMs, with regards to monthly precipitation climatologies, precipitation biases and precipitation change signal, according to the Representative Concentration Pathway (RCP) 8.5 for the end of the 21st century. We investigate the degree to which RCMs and GCMs are able to reproduce specific climatic features over SAF and over three sub-regions, namely the greater Angola region, the greater Mozambique region and the greater South Africa region. We identify that during the beginning of the rainy season, when regional processes are largely dependent on the coupling between the surface and the atmosphere, the impact of the driving GCMs on the RCMs is smaller, compared to the core of the rainy season, when precipitation is mainly controlled by the large-scale circulation. In addition, we show that RCMs are able to counteract the bias received by their driving GCMs, hence, we claim that the cascade of uncertainty over SAF is not additive, but indeed the RCMs do provide improved precipitation climatologies. The fact that certain bias patterns over the historical period (1985-2005) identified in GCMs are resolved in RCMs, provides evidence that RCMs are reliable tools for climate change impact studies over SAF. [ABSTRACT FROM AUTHOR]

The region of southern Africa (SAF) is highly vulnerable to the impacts of climate change and is projected to experience severe precipitation shortages in the coming decades. Ensuring that our modelling tools are fit for the purpose of assessing these changes is critical. In this work we compare a range of satellite products along with gauge-based datasets. Additionally, we investigate the behaviour of regional climate simulations from the Coordinated Regional Climate Downscaling Experiment (CORDEX) - Africa domain, along with simulations from the Coupled Model Intercomparison Project Phase 5 (CMIP5) and Phase 6 (CMIP6). We identify considerable variability in the standard deviation of precipitation between satellite products that merge with rain gauges and satellite products that do not, during the rainy season (Oct-Mar), indicating high observational uncertainty for specific regions over SAF. Good agreement both in spatial pattern and the strength of the calculated trends is found between satellite and gauge-based products, however. Both CORDEX-Africa and CMIP5 ensembles underestimate the observed trends during the analysis period. The CMIP6 ensemble displayed persistent drying trends, in direct contrast to the observations. The regional ensemble exhibited improved performance compared to its forcing (CMIP5), when the annual cycle and the extreme precipitation indices were examined, confirming the added value of the higher resolution regional climate simulations. The CMIP6 ensemble displayed a similar behaviour to CMIP5, however reducing slightly the ensemble spread. However, we show that reproduction of some key SAF phenomena, like the Angolan Low (which exerts a strong influence on regional precipitation), still poses a challenge for the global and regional models. This is likely a result of the complex climatic process that take place. Improvements in observational networks (both in-situ and satellite), as well as continued advancements in high-resolution modelling will be critical, in order to develop a robust assessment of climate change for southern Africa. [ABSTRACT FROM AUTHOR]

Rituximab is known to affect T cell immune responses. We and others have reported expansions of T large granular lymphocytes (T-LGLs) in lymphoma patients after Rituximab. We report here the immunogenetic profiling of the T cell receptor (TR) gene repertoire in 14 patients who received Rituximab post allo-HCT and explore clinicobiological correlations. All experienced antigenic triggers, CMV, EBV re-activation and chronic GvHD and had been treated with Rituximab. Skewing of TRBV genes was observed: 3 TRBV genes accounted for half of the repertoire. Oligoclonal pattern with expanded clonotypes was common. Patients with oligoclonality exhibited frequently cGvHD. Longitudinal samples in one revealed distinct clonotypes, suggesting clonal drift. T-LGL leukemia of donor origin with mixed chimerism eventually developed. In conclusion, we report development of oligoclonal T-LGLs after Rituximab post allo-HCT, alluding to antigen selection. Persistence of this phenomenon likely reflects strong antigenic stimulation by viruses and/or cGVHD aggravated by Rituximab. [ABSTRACT FROM AUTHOR]

Simple Summary: Climate change is one of the major threats to plant diversity and is expected to force species distributions into latitudinal or altitudinal shifts. The complex biology of orchids, and their many interactions with other organisms, increases their vulnerability in a changing climate. This study focuses on how climatic alterations will affect the distribution of the fly orchid (Ophrys insectifera L.), one of the most well-known and distinctive Ophrys species in Europe, using models that predict the species range changes in the future, based on environmental factors. The orchid's environmentally suitable area is projected to shift northwards but downhill in the future, experiencing a moderate overall range contraction. More specifically in near- and long-term future, it is expected to be lost in South Europe, especially from the Balkans, while it will gain areas in North Europe, with the UK, Scandinavia, and the Baltic countries being among the winners. These results, although conservative since they are based only on abiotic variables, provide useful insights on the fly orchid's response to future climatic change, and can serve as a basis for further studies on a finer scale. Numerous orchid species around the world have already been affected by the ongoing climate change, displaying phenological alterations and considerable changes to their distributions. The fly orchid (Ophrys insectifera L.) is a well-known and distinctive Ophrys species in Europe, with a broad distribution across the continent. This study explores the effects of climate change on the range of O. insectifera, using a species distribution models (SDMs) framework that encompasses different climatic models and scenarios for the near- and long-term future. The species' environmentally suitable area is projected to shift northwards (as expected) but downhill (contrary to usual expectations) in the future. In addition, an overall range contraction is predicted under all investigated combinations of climatic models and scenarios. While this is moderate overall, it includes some regions of severe loss and other areas with major gains. Specifically, O. insectifera is projected to experience major area loss in its southern reaches (the Balkans, Italy and Spain), while it will expand its northern limits to North Europe, with the UK, Scandinavia, and the Baltic countries exhibiting the largest gains. [ABSTRACT FROM AUTHOR]

Background: Wearing facemasks is of proven efficacy as a public health protective measure against COVID-19. Currently there are no observational data concerning the wearing of facemasks and the adherence to guidelines concerning their handling. Methods: Registration of the way passers-by were wearing facemasks at 26 different locations of five major cities in Greece. The results were correlated with the rate of COVID-19 deaths in the region. Results: In total, 119,433 passers-by were registered, 57,043 females (47.8%) and 62,390 males (52.2%). From the total sample, 81.1% were wearing the mask properly, 10.8% had their nose out, 6.2% were wearing it under the jaw, and 1.9% had no mask at all. There was a significant difference between males and females concerning any use of mask. Inappropriate use of was correlated with COVID-19 death rate in the studied region. Conclusion: Our findings suggest that under conditions of mandatory wearing and in central locations of major cities, during walking, proper use of masks is suboptimal, but still contributes with some protection. Fear and risk perception seem to be strong factors contributing to adherence to proper mask wearing. [ABSTRACT FROM AUTHOR]

Erythropotamos is a tributary of river Evros and during the last decade its drainage basin flooded many times, causing extensive damage on properties. In order to assess flood susceptibility in the aforementioned study area, the inundated areas of floods that occurred in 2010, 2017 and 2018 were initially delineated with the aid of SAR (Synthetic Aperture Radar) imagery by applying an established flood delineation methodology. Subsequently, flood susceptibility mapping was conducted for the study area by applying the Analytical Hierarchy Process (AHP). Topographical, hydrological and meteorological factors were used and each one of them was classified into three (3) flood susceptibility categories (low, medium and high). The determination of the importance for each factor over the others, which is the main objective of this research, was decided according to the proportion of the 2010 inundated area, captured by ENVISAT/ASAR imagery, which intersected with each factor's high susceptibility class. Finally, the resulting flood susceptibility map was validated according with the inundated areas of the 2017 and 2018 flood events, captured by SENTINEL - 1 A/B imagery, indicating that approximately 60% of both of these areas intersected with the map's high susceptibility zone. [ABSTRACT FROM AUTHOR]

Chronic idiopathic neutropenia (CIN) is an acquired disorder of granulopoiesis characterized by female predominance and mostly uncomplicated course. Crucial to CIN pathophysiology is the presence of activated T lymphocytes with myelosuppressive properties in both peripheral blood (PB) and bone marrow (BM). We systematically profiled the T cell receptor beta chain (TRB) gene repertoire in CD8+ cells of 34 CIN patients through subcloning/Sanger sequencing analysis of TRBV–TRBD–TRBJ gene rearrangements. Remarkable repertoire skewing and oligoclonality were observed, along with shared clonotypes between different patients, alluding to antigen selection. Cross-comparison of our sequence dataset with public TRB sequence databases revealed that CIN may rarely share common immunogenetic features with other entities, however, the CIN TRB repertoire is largely disease-biased. Overall, these findings suggest that CIN may be driven by long-term exposure to a restricted set of specific CIN-associated antigens. [ABSTRACT FROM AUTHOR]

A letter to the editor is presented discussing a study on impact of Tp53 gene p72R polymorphism in chronic lymphocytic leukemia (CLL) cases with unmutated immunoglobulin receptors.