Steady state pig dendritic cells migrating in skin draining pseudo-afferent lymph are semi-mature

Dendritic cells (DC) in peripheral tissues are considered as immature cells that mature and migrate towards lymph nodes upon stimulation with pathogens. This commonly accepted paradigm is challenged by the fact that tolerance to peripheral self antigen is controlled by mature DC and that DC collected from afferent lymph draining different tissues from several species, in the absence of pathogen signaling, were inconsistently found to be either at a mature or semi-mature state. In order to better define the maturation state of DC that migrate in lymph in absence of pathogen stimulation, we compared skin lymph DC to resident and LPS (lipopolysaccharide)-activated skin DC thanks to the establishment of a mini-pig model of lymph duct cannulation. Based on their co-stimulatory molecules expression and endocytotic capacities, pig lymph skin DC were found at an intermediate state of maturation between resident and LPS-activated skin DC and were fully capable of allogeneic T cell stimulation. Furthermore, lymph skin DC could be further matured by LPS or influenza stimulation. Thus, using the pig skin model which is relevant to human, we show that skin-derived DC constantly migrate at an intermediate state of maturation that can be further enhanced upon appropriate stimulation.     

Assessing the effects of climate change on the phenology of European temperate trees

Modelling phenology is crucial to assess the impact of climate change on the length of the canopy duration and the productivity of terrestrial ecosystems. Focusing on six dominant European tree species, the aims of this study were (i) to examine the accuracy of different leaf phenology models to simulate the onset and ending of the leafy season, with particular emphasis on the putative role of chilling to release winter bud dormancy and (ii) to predict seasonal shifts for the 21st century in response to climate warming.Models testing and validation were done for each species considering 2 or 3 years of phenological observations acquired over a large elevational gradient (1500 m range, 57 populations). Flushing models were either based solely on forcing temperatures (1-phase models) or both on chilling and forcing temperatures (2-phases models). Leaf senescence models were based on both temperature and photoperiod.We show that most flushing models are able to predict accurately the observed flushing dates. The 1-phase models are as efficient as 2-phases models for most species suggesting that chilling temperatures are currently sufficient to fully release bud dormancy. However, our predictions for the 21st century highlight that chilling temperature could be insufficient for some species at low elevation. Overall, flushing is expected to advance in the next decades but this trend substantially differed between species (from 0 to 2.4 days per decade). The prediction of leaf senescence appears more challenging, as the proposed models work properly for only two out of four deciduous species, for which senescence is expected to be delayed in the future (from 1.4 to 2.3 days per decade). These trends to earlier spring leafing and later autumn senescence are likely to affect the competitive balance between species. For instance, simulations over the 21st century predict a stronger lengthening of the canopy duration for Quercus petraea than for Fagus sylvatica, suggesting that shifts in the elevational distributions of these species might occur.     

Combining Cattle Activity and Progesterone Measurements Using Hidden Semi-Markov Models

Hourly pedometer counts and irregularly measured concentration of the hormone progesterone were available for a large number of dairy cattle. A hidden semi-Markov was applied to this bivariate time-series data for the purposes of monitoring the reproductive status of cattle. In particular, the ability to identify oestrus is investigated as this is of great importance to farm management. Progesterone concentration is a more accurate but more expensive method than pedometer counts, and we evaluate the added benefits of a model that includes this variable. The resulting model is biologically sensible, but validation is difficult. We utilize some auxiliary data to demonstrate the model’s performance.     

Mapping soil Pb stocks and availability in mainland France combining regression trees with robust geostatistics

Maps of lead (Pb) stocks in soils and estimates of its availability are needed to assess risks of contamination. Stocks in soils of total and ethylenediamine tetraacetic acid (EDTA) extractable Pb, as well as Pb availability, assessed by EDTA/total Pb ratio, were measured and calculated to a depth of 30 cm with the French soil monitoring network at sites defined by a regular 16 × 16 km grid. Setting aside punctual anomalies by winsorizing, these properties were mapped using linear mixed models (LMM). LMMs combined conditional partitioning trees upon 5 predictors (pH, texture, parent material, land use, population density) with robust geostatistics to avoid distortion due to outlying values. Rather than selecting the fixed effects according to expert-knowledge, regression trees were used to account for explanatory variables in a single classification. This original method stressed both the necessity for a geostatistical component to complement regression tree models when spatial correlation is evident, and the usefulness of these trees to interpret maps. Pb stocks varied widely with peak concentrations and availability in densely populated areas. Lithology, texture and forestation also affected total Pb stocks. With regards to availability, forestation and pH appeared as key factors.     

Variability of the particle size of suspended sediment during highly concentrated flood events in a small mountainous catchment

Purpose

There is a growing interest in the characterization of the particle size of sediment due to its impact on particle dynamics, especially for connectivity purpose. This study determined the particle size distribution of suspended sediment in a mountainous catchment, with the aim to evaluate the variability of particle size during floods, the main controlling factors, and if indirect information from hillslopes was useful for the interpretation of particle size measured at the catchment outlet. This work involved the development of a measurement protocol.

Material and methods

Samples were collected automatically from streamwater during flood events using an ISCO 3700 sampler. Five events were analyzed for their particle size distributions using a Malvern Mastersizer 2000. Because the samples were too concentrated, two different protocols were tested to address the errors made during the subsampling step: using a pipette and a home-made device with successive dilution phases.

Results and discussion

High errors occurred when using a pipette to extract particles within a stirred sample. The maximum errors were reduced from 1,600 to 30?% using the device described within this study. Particles were found to be aggregated at various levels regardless of the discharge they were sampled at. Their size was found to be either variable or stable at the event scale, and statistical analyses revealed that discharge was the factor that best correlated with particle size. The results obtained in this study are in agreement with the few other studies in comparable environments. Some hypothesis are put forward and discussed to explain the positive relationship between particle size and discharge. Input from hillslopes seems to have a measureable effect in this headwater catchment.

Conclusions

While the need for in situ measurements has long been stressed in lowland rivers, estuaries, and coastal environments, it was shown that the use of an accurate dilution protocol could provide some physically interpretable measurements on the particle size distributions of suspended sediment transported in a mountainous catchment. It also appears that hillslope information has to be considered when studying particle size measured at the catchment outlet.     

Antiproliferative Activity of Cyanophora paradoxa Pigments in Melanoma,Breast and Lung Cancer Cells

The glaucophyte Cyanophora paradoxa (Cp) was chemically investigated to identify pigments efficiently inhibiting malignant melanoma, mammary carcinoma and lung adenocarcinoma cells growth. Cp water and ethanol extracts significantly inhibited the growth of the three cancer cell lines in vitro, at 100 µg·mL⁻¹. Flash chromatography of the Cp ethanol extract, devoid of c-phycocyanin and allophycocyanin, enabled the collection of eight fractions, four of which strongly inhibited cancer cells growth at 100 µg·mL⁻¹. Particularly, two fractions inhibited more than 90% of the melanoma cells growth, one inducing apoptosis in the three cancer cells lines. The detailed analysis of Cp pigment composition resulted in the discrimination of 17 molecules, ten of which were unequivocally identified by high resolution mass spectrometry. Pheophorbide a, β-cryptoxanthin and zeaxanthin were the three main pigments or derivatives responsible for the strong cytotoxicity of Cp fractions in cancer cells. These data point to Cyanophora paradoxa as a new microalgal source to purify potent anticancer pigments, and demonstrate for the first time the strong antiproliferative activity of zeaxanthin and β-cryptoxanthin in melanoma cells.     

Cerebellar vascular hamartoma in a British Shorthair cat

Cerebellar vascular hamartoma was diagnosed in a 16-month-old cat following magnetic resonance imaging and incisional biopsy. The clinical features were consistent with the cerebellar site of the lesion accompanied by signs attributable to cerebellar herniation through the foramen magnum and increased intra-cranial pressure. A lesion of this type represents a previously unreported differential diagnosis for central nervous system lesions in young cats.     

Understanding the effect of repeated administration of meloxicam on feline renal cortex and medulla: A lipidomics and metabolomics approach

Repeated administration of meloxicam can cause kidney damage in cats by mechanisms that remain unclear. Metabolomics and lipidomics are powerful, noninvasive approaches used to investigate tissue response to drug exposure. Thus, the objective of this study was to assess the effects of meloxicam on the feline kidney using untargeted metabolomics and lipidomics approaches. Female young‐adult purpose‐breed cats were allocated into the control (n = 4) and meloxicam (n = 4) groups. Cats in the control and meloxicam groups were treated daily with saline and meloxicam at 0.3 mg/kg subcutaneously for 17 days, respectively. Renal cortices and medullas were collected at the end of the treatment period. Random forest and metabolic pathway analyses were used to identify metabolites that discriminate meloxicam‐treated from saline‐treated cats and to identify disturbed metabolic pathways in renal tissue. Our results revealed that the repeated administration of meloxicam to cats altered the kidney metabolome and lipidome and suggest that at least 40 metabolic pathways were altered in the renal cortex and medulla. These metabolic pathways included lipid, amino acid, carbohydrate, nucleotide and energy metabolisms, and metabolism of cofactors and vitamins. This is the first study using a pharmacometabonomics approach for studying the molecular effects of meloxicam on feline kidneys.