Estimating the Acid-Base Properties and Electrical Charge of Organic Matter Using Spectrophotometry.

Spectrophotometric acid-base titration is a simple and powerful technique to evaluate the properties of proton binding sites of natural organic matter (NOM) at environmentally relevant concentrations. However, it is challenging to quantify the chemical charges (Q) carried by NOM at these concentrations. Based on a previous work, which relates the variation of Q with the specific UV-vis differential absorbance (ΔAλ,pH) at a given wavelength (λ) and pH of a dissolved NOM sample, the present work proposes a method to investigate any NOM sample. It determines specific features in the absorbance spectra attributed to proton-inert chromophores (A0,λ) and to the deprotonation processes of carboxylic (A1,λ) and phenolic groups (A2,λ). It enables to select sample-specific wavelength (λmid), where both these functional groups significantly contribute to the variation of absorbance with pH. The linear regression analysis of Aλmid,pH vs Q for various NOM reference samples evidenced that the sample-specific slope (SNOM) and intercept (INOM) were related to the intrinsic spectroscopic properties of the sample (A0,λmid, A1,λmid, and A2,λmid). This approach can thus be used to approximate the Q values of the NOM samples at environmentally relevant concentrations: a pre-requisite for predicting the fate and behavior of metal ions in natural systems.

A Multi-Skilled Mathematical Model of Bacterial Attachment in Initiation of Biofilms.

The initial step of biofilm formation is bacteria attachment to biotic or abiotic surfaces and other bacteria through intra or interspecies interactions. Adhesion can be influenced by physicochemical conditions of the environment, such as iron. There is no available mathematical model of bacterial attachment giving realistic initiation rather than random adhesion. We describe a simple stochastic attachment model, from the simplest case in two dimensions with one bacterial species attaching on a homogeneous flat surface to more complex situations, with either several bacterial species, inhomogeneous or non-flat surfaces, or in three dimensions. The model depends on attachment probabilities (on the surface, laterally, or vertically on bacteria). Effects of each of these parameters were analyzed. This mathematical model is then applied to experimental oral microcolonies of Porphyromonas gingivalis, Streptococcus gordonii, and Treponema denticola, either as mono-, two, or three species, under different iron concentrations. The model allows to characterize the adhesion of three bacterial species and explore the effect of iron on attachment. This model appears as a powerful tool for initial attachment analysis of bacterial species. It will enable further modeling of biofilm formation in later steps with biofilm initialization more relevant to real-life subgingival biofilms.

C-ECi: a CUBIC-ECi combined clearing method for three-dimensional follicular content analysis in the fish ovary†.

Deciphering mechanisms of oocyte development in the fish ovary still remain challenging, and a comprehensive overview of this process at the level of the organ is still needed. The recent development of optical tissue clearing methods has tremendously boosted the three-dimensional (3D) imaging of large size biological samples that are naturally opaque. However, no attempt of clearing on fish ovary that accumulates extremely high concentration of lipids within oocytes has been reported to date. To face with this ovarian-specific challenge, we combined two existing clearing methods, the nontoxic solvent-based ethyl cinnamate (ECi) method for efficient clearing and the Clear Unobstructed Brain Imaging Cocktails and Computational (CUBIC) method to enhance lipid removal and reduce nonspecific staining. The methyl green fluorescent dye was used to stain nuclei and delineate the follicular structures that include oocytes. Using this procedure (named CUBIC-ECi [C-ECi]), ovaries of both medaka and trout could be imaged in 3D and follicles analyzed. To our knowledge, this is the first procedure elaborated for clearing and imaging fish ovary in 3D. The C-ECi method thus provides an interesting tool for getting precise quantitative data on follicular content in fish ovary and promises to be useful for further developmental and morphological studies.

Cathodoluminescence hyperspectral analysis of whispering gallery modes in active semiconductor wedge resonators.

Whispering gallery mode resonators are key devices for integrated photonics. Despite their generalization in fundamental and applied science, information on spatial confinement of light in these structures is mostly retrieved from purely spectral analysis. In this work, we present a detailed spectral and spatial characterization of whispering gallery modes in active semiconductor microdisk resonators by use of hyperspectral cathodoluminescence. By comparing our experimental findings to finite element simulations, we demonstrate that the combination of spectral and spatial measurements enables unique identification of the modes and even reveals specific features of the microresonator geometry, such as a wedge profile.

The pVHL172 isoform is not a tumor suppressor and up-regulates a subset of pro-tumorigenic genes including TGFB1 and MMP13.

The von Hippel-Lindau (VHL) tumor suppressor gene is often deleted or mutated in ccRCC (clear cell renal cell carcinoma) producing a non-functional protein. The gene encodes two mRNA, and three protein isoforms (pVHL213, pVHL160 and pVHL172). The pVHL protein is part of an E3 ligase complex involved in the ubiquitination and proteasomal degradation of different proteins, particularly hypoxia inducible factors (HIF) that drive the transcription of genes involved in the regulation of cell proliferation, angiogenesis or extracellular matrix remodelling. Other non-canonical (HIF-independent) pVHL functions have been described. A recent work reported the expression of the uncharacterized protein isoform pVHL172 which is translated from the variant 2 by alternative splicing of the exon 2. This splice variant is sometimes enriched in the ccRCCs and the protein has been identified in the respective samples of ccRCCs and different renal cell lines. Functional studies on pVHL have only concerned the pVHL213 and pVHL160 isoforms, but no function was assigned to pVHL172. Here we show that pVHL172 stable expression in renal cancer cells does not regulate the level of HIF, exacerbates tumorigenicity when 786-O-pVHL172 cells were xenografted in mice. The pVHL172-induced tumors developed a sarcomatoid phenotype. Moreover, pVHL172 expression was shown to up regulate a subset of pro-tumorigenic genes including TGFB1, MMP1 and MMP13. In summary we identified that pVHL172 is not a tumor suppressor. Furthermore our findings suggest an antagonistic function of this pVHL isoform in the HIF-independent aggressiveness of renal tumors compared to pVHL213.

A new mathematical model of bacterial interactions in two-species oral biofilms.

Periodontitis are bacterial inflammatory diseases, where the bacterial biofilms present on the tooth-supporting tissues switch from a healthy state towards a pathogenic state. Among bacterial species involved in the disease, Porphyromonas gingivalis has been shown to induce dysbiosis, and to induce virulence of otherwise healthy bacteria like Streptococcus gordonii. During biofilm development, primary colonizers such as S. gordonii first attach to the surface and allow the subsequent adhesion of periodontal pathogens such as P. gingivalis. Interactions between those two bacteria have been extensively studied during the adhesion step of the biofilm. The aim of the study was to understand interactions of both species during the growing phase of the biofilm, for which little knowledge is available, using a mathematical model. This two-species biofilm model was based on a substrate-dependent growth, implemented with damage parameters, and validated thanks to data obtained on experimental biofilms. Three different hypothesis of interactions were proposed and assayed using this model: independence, competition between both bacteria species, or induction of toxicity by one species for the other species. Adequacy between experimental and simulated biofilms were found with the last hypothetic mathematical model. This new mathematical model of two species bacteria biofilms, dependent on different substrates for growing, can be applied to any bacteria species, environmental conditions, or steps of biofilm development. It will be of great interest for exploring bacterial interactions in biofilm conditions.