Characterization of a Cutibacterium acnes Camp Factor 1-Related Peptide as a New TLR-2 Modulator in In Vitro and Ex Vivo Models of Inflammation

Cutibacterium acnes (C. acnes) has been implicated in inflammatory acne where highly mutated Christie–Atkins–Munch–Petersen factor (CAMP)1 displays strong toll like receptor (TLR)-2 binding activity. Using specific antibodies, we showed that CAMP1 production was independent of C. acnes phylotype and involved in the induction of inflammation. We confirmed that TLR-2 bound both mutated and non-mutated recombinant CAMP1, and peptide array analysis showed that seven peptides (A14, A15, B1, B2, B3, C1 and C3) were involved in TLR-2 binding, located on the same side of the three-dimensional structure of CAMP1. Both mutated and non-mutated recombinant CAMP1 proteins induced the production of C-X-C motif chemokine ligand interleukin (CXCL)8/(IL)-8 in vitro in keratinocytes and that of granulocyte macrophage-colony stimulating factor (GM-CSF), tumor necrosis factor (TNF)-α, IL-1β and IL-10 in ex vivo human skin explants. Only A14, B1 and B2 inhibited the production of CXCL8/IL-8 by keratinocytes and that of (GM-CSF), TNF-α, IL-1β and IL-10 in human skin explants stimulated with rCAMP1 and C. acnes. Following pretreatment with B2, RNA sequencing on skin explants identified the 10 genes displaying the strongest differential expression as IL6, TNF, CXCL1, CXCL2, CXCL3, CXCL8, IL-1β, chemokine ligand (CCL)2, CCL4 and colony stimulating factor (CSF)2. We, thus, identified a new CAMP1-derived peptide as a TLR-2 modulator likely to be a good candidate for clinical evaluation.     

Preparation of H-bar cross-sectional specimen for in situ TEM straining experiments: A FIB-based method applied to a nitrided Ti-6Al-4V alloy

The in situ tensile straining of cross-sectional specimens inside a TEM is intrinsically very difficult to perform despite its obvious interest to study interfaces of surface treated materials. We have combined a FIB-based method to produce H-bar specimens of a nitrided Ti-6Al-4V alloy and in situ TEM straining stage, to successfully study the plastic deformation mechanisms that are activated close to the nitrided surface in the Ti-based alloy.     

The three Rs of river ecosystem resilience: Resources,recruitment, and refugia

Resilience in river ecosystems requires that organisms must persist in the face of highly dynamic hydrological and geomorphological variations. Disturbance events such as floods and droughts are postulated to shape life history traits that support resilience, but river management and conservation would benefit from greater understanding of the emergent effects in communities of river organisms. We unify current knowledge of taxonomic‐, phylogenetic‐, and trait‐based aspects of river communities that might aid the identification and quantification of resilience mechanisms. Temporal variations in river productivity, physical connectivity, and environmental heterogeneity resulting from floods and droughts are highlighted as key characteristics that promote resilience in these dynamic ecosystems. Three community‐wide mechanisms that underlie resilience are (a) partitioning (competition/facilitation) of dynamically varying resources, (b) dispersal, recolonization, and recruitment promoted by connectivity, and (c) functional redundancy in communities promoted by resource heterogeneity and refugia. Along with taxonomic and phylogenetic identity, biological traits related to feeding specialization, dispersal ability, and habitat specialization mediate organism responses to disturbance. Measures of these factors might also enable assessment of the relative contributions of different mechanisms to community resilience. Interactions between abiotic drivers and biotic aspects of resource use, dispersal, and persistence have clear implications for river conservation and management. To support these management needs, we propose a set of taxonomic, phylogenetic, and life‐history trait metrics that might be used to measure resilience mechanisms. By identifying such indicators, our proposed framework can enable targeted management strategies to adapt river ecosystems to global change.     

Comparison between five stochastic global search algorithms for optimizing thermoelectric generator designs

In this study, the best settings of five heuristics are determined for solving a mixed-integer non-linear multi-objective optimization problem. The algorithms treated in the article are: ant colony optimization, genetic algorithm, particle swarm optimization, differential evolution, and teaching-learning basic algorithm. The optimization problem consists in optimizing the design of a thermoelectric device, based on a model available in literature. Results showed that the inner settings can have different effects on the algorithm performance criteria depending on the algorithm. A formulation based on the weighted sum method is introduced for solving the multiobjective optimization problem with optimal settings. It was found that the five heuristic algorithms have comparable performances. Differential evolution generated the highest number of non-dominated solutions in comparison with the other algorithms.     

Object-based fusion for urban tree species classification from hyperspectral,panchromatic and nDSM data

This study aims at identifying the best object-based fusion strategy that takes advantage of the complementarity of several heterogeneous airborne data sources for improving the classification of 15 tree species in an urban area (Toulouse, France). The airborne data sources are: hyperspectral Visible Near-Infrared (160 spectral bands, spatial resolution of 0.4 m) and Short-Wavelength Infrared (256 spectral bands, 1.6 m), panchromatic (14 cm), and a normalized Digital Surface Model (12.5 cm). Object-based feature and decision level fusion strategies are proposed and compared when applied to a reference site where the species are previously identified during ground truth collection. This allows the best fusion strategy to be selected with a view to introducing the method in an automatic process (tree crown delineation and species classification) on a test site, independent of the reference site used for learning. In particular, a decision level fusion is selected: based on the Support Vector Machine algorithm, Visible Near-Infrared and Short-Wavelength Infrared classifications use Minimum Noise Fraction components at the original spatial resolution, whereas panchromatic and normalized Digital Surface Model classifications use, respectively, Haralick’s and structural features computed at the object scale. After the computation of a decision profile for each source at the object level based on the classification algorithms’ membership probabilities, these decision profiles are combined and a decision rule is applied to predict the species. Focusing on the reference site, the Visible Near-Infrared exhibits the best performances with F-score values higher than 60% for 13 species out of 15. The Short-Wavelength Infrared is the most powerful for three species with F-score greater than 60% for seven common species with the Visible Near-Infrared. The panchromatic and normalized Digital Surface Model contribute marginally. The best fusion strategy (decision fusion) does not improve significantly the overall accuracy with 77% (kappa = 74%) against 75% (kappa = 72%) for the Visible Near-Infrared but in general, it improves the results for cases where complementarities have been observed. When applied to the test site and assessed for the two majority species (Tilia tomentosa and Platanus x hispanica), the selected approach gives consistent results with an overall accuracy of 63% against 55% for the Visible Near-Infrared.     

Lesser in vitro anaerobic cecal isoflavone disappearance was associated with greater apparent absorption of daidzein and genistein in Golden Syrian hamsters

Our hypothesis in this study was that in vitro disappearance of isoflavones from fecal or cecal contents of Golden Syrian hamsters paralleled the apparent absorption of these compounds, comparable with previous findings from in vitro human fecal incubations. Two studies were conducted to test this idea: one on in vitro fecal (study 1, n = 20/sex) and the other on in vitro cecal contents (study 2, n = 10/sex) ability to degrade isoflavones. According to HPLC analysis, urinary isoflavone excretion was significantly less by 2-4 fold in males compared with females in both studies. Fecal isoflavone excretion was not significantly different between sexes or isoflavones (study 1) and was <0.5% of ingested dose. In vitro anaerobic fecal isoflavone degradation rate constants from study 1 were minimal with no significant correlation between urinary and fecal isoflavone excretion. However, in vitro anaerobic cecal isoflavone degradation rate constants (study 2) were greater and significantly correlated with urinary excretion of daidzein (R = 0.90; p = 0.01) and genistein (R = 0.93; p = 0.004), but not glycitein (R = 0.50; p = 0.3). Both male and female hamsters showed a pattern of urinary isoflavone excretion similar to that found in humans (daidzein > genistein). Hamster in vitro cecal isoflavone degradation rate constants seemed to be analogous to human in vitro fecal isoflavone degradation rate constants for genistein and daidzein. The sex difference in isoflavone excretion in hamsters and the instability in glycitein excretion across studies coupled with the paucity of human data on this isoflavone deserve further investigation.     

Structural dependence of chemical durability in modified aluminoborate glasses

Alkali and alkaline earth aluminoborate glasses feature high resistance to cracking under sharp contact loading compared to other oxide glasses. However, due to the high content of hygroscopic B₂O₃, it is expected that applications of these glasses could be hindered by poor chemical durability in aqueous solutions. Indeed, the compositional and structural dependence of their dissolution kinetics remains unexplored. In this work, we correlate the dissolution rates of aluminoborate glasses in acidic, neutral, and basic solutions with the structural changes induced by varying the aluminum-to-boron ratio. In detail, we investigate a total of seventeen magnesium, lithium, and sodium aluminoborate glasses with fixed modifier content of 25 mol%. We show that the structural changes induced by alumina depend on the network modifier. We also demonstrate a correlation between the chemical durability at various pH values and the structural changes in Mg-, Li- and Na-aluminoborate glasses. The substitution of alumina by boron oxide leads to a general decrease in chemical corrosion in neutral and acidic solutions. The lowest dissolution rate value is observed in Mg-aluminoborate glasses, as a consequence of the intermediate character of magnesium which can increase the network cross-linking. For basic solutions, the chemical durability is almost constant for the different amount of alumina in the three series, likely because B₂O₃ is susceptible to nucleophilic attack, which is favored in high-OH⁻ solutions.