Multicomponent ionic liquid CMC prediction.

We created a model to predict CMC of ILs based on 704 experimental values published in 43 publications since 2000. Our model was able to predict CMC of variety of ILs in binary or ternary system in a presence of salt or alcohol. The molecular volume of IL (Vm), solvent-accessible surface (S), solvation enthalpy (ΔsolvG∞), concentration of salt (Cs) or alcohol (Ca) and their molecular volumes (Vms and Vma, respectively) were chosen as descriptors, and Kernel Support Vector Machine (KSVM) and Evolutionary Algorithm (EA) as regression methodologies to create the models. Data was split into training and validation set (80/20) and subjected to bootstrap aggregation. KSVM provided better fit with average R2 of 0.843, and MSE of 0.608, whereas EA resulted in R2 of 0.794 and MSE of 0.973. From the sensitivity analysis it was shown that Vm and S have the highest impact on ILs micellization in both binary and ternary systems, however surprisingly in the presence of alcohol the Vm becomes insignificant/irrelevant. Micelle stabilizing or destabilizing influence of the descriptors depends upon the additives. Previous attempts at modelling the CMC of ILs was generally limited to small number of ILs in simplified (binary) systems. We however showed successful prediction of the CMC over a range of different systems (binary and ternary).

IL-17C mediates the recruitment of tumor-associated neutrophils and lung tumor growth.

Chronic obstructive pulmonary disease (COPD) is associated with an increased risk for lung cancer and an aberrant microbiota of the lung. Microbial colonization contributes to chronic neutrophilic inflammation in COPD. Nontypeable Haemophilus influenzae (NTHi) is frequently found in lungs of stable COPD patients and is the major pathogen triggering exacerbations. The epithelial cytokine interleukin-17C (IL-17C) promotes the recruitment of neutrophils into inflamed tissues. The purpose of this study was to investigate the function of IL-17C in the pulmonary tumor microenvironment. We subjected mice deficient for IL-17C (IL-17C-/-) and mice double deficient for Toll-like receptor 2 and 4 (TLR-2/4-/-) to a metastatic lung cancer model. Tumor proliferation and growth as well as the number of tumor-associated neutrophils was significantly decreased in IL-17C-/- and TLR-2/4-/- mice exposed to NTHi. The NTHi-induced pulmonary expression of IL-17C was dependent on TLR-2/4. In vitro, IL-17C increased the NTHi- and tumor necrosis factor-α-induced expression of the neutrophil chemokines keratinocyte-derived chemokine and macrophage inflammatory protein 2 in lung cancer cells but did not affect proliferation. Human lung cancer samples stained positive for IL-17C, and in non-small cell lung cancer patients with lymph node metastasis, IL-17C was identified as a negative prognostic factor. Our data indicate that epithelial IL-17C promotes neutrophilic inflammation in the tumor microenvironment and suggest that IL-17C links a pathologic microbiota, as present in COPD patients, with enhanced tumor growth.

Rhamnolipid CMC prediction.

Relationships between the purity, pH, hydrophobicity (logKow) of the carbon substrate, and the critical micelle concentration (CMC) of rhamnolipid type biosurfactants (RL) were investigated using a quantitative structure-property relationship (QSPR) approach and are presented here for the first time. Measured and literature CMC values of 97 RLs, representing biosurfactants at different stages of purification, were considered. An arbitrary scale for RLs purity was proposed and used in the modelling. A modified evolutionary algorithm was used to create clusters of equations to optimally describe the relationship between CMC and logKow, pH and purity (the optimal equation had an R2 of 0.8366). It was found that hydrophobicity of the carbon substrate used for the biosynthesis of the RL had the most significant influence on the final CMC of the RL. Purity of the RLs was also found to have a significant impact, where generally the less pure the RL the higher the CMC. These results were in accordance with our experimental data. Therefore, our model equation may be used for controlling the biosynthesis of biosurfactants with properties targeted for specific applications.

Cigarette smoke-induced disruption of pulmonary barrier and bacterial translocation drive tumor-associated inflammation and growth.

Microorganisms have an important role in tumorgenesis by the induction of inflammation and by a direct impact on tumor cells. Chronic obstructive pulmonary disease (COPD) is associated with an increased risk for lung cancer and microbial colonization. We asked whether bacterial pathogens act as tumor promoters during CS-induced pulmonary inflammation. In a metastatic lung cancer (LC) model, Lewis lung carcinoma (LLC) cells were injected in mice to initiate the growth of tumors in the lung. Exposure to the combination of cigarette smoke (CS) and nontypeable Haemophilus influenzae (NTHi) synergistically increased metastatic growth. Lung levels of albumin and LDH, translocation of bacterial factors into tumor tissue, tumor inflammation, and tumor proliferation were significantly increased in mice exposed to CS in combination with NTHi. Bacterial pathogens increased the proliferation of cultured LLC cells and human cancer cell lines. Metastatic growth induced by the exposure to CS in combination with NTHi was reduced in mice deficient for IL-17. Our data provide evidence that CS-induced loss of pulmonary barrier integrity allows bacterial factors to translocate into tumor tissue and to regulate tumor-associated inflammation and tumor proliferation. Translocation of bacterial factors in tumor tissue links CS-induced inflammation with tumor proliferation.

Mobility and biodegradability of an imidazolium based ionic liquid in soil and soil amended with waste sewage sludge.

Sorption on solids and biodegradation are main phenomena that can mitigate the pollution of soil and water by ionic liquids (ILs). ILs sorbed on soil particles become immobilized (temporarily or permanently) which prevents them from spreading into deeper layers of soil or groundwater but which also makes them less bioavailable. In this study we attempt to examine if amendment of soil with waste sludge has a potential to mitigate the transport and enhance biodegradation of ILs using 1-methyl-3-octylimidazolium chloride ([OMIM][Cl]) as an example. We present the results of adsorption test (batch and column) and ultimate biodegradation of [OMIM][Cl] using microbial communities derived from soil. Finally, we combine all of these processes together to examine the fate of [OMIM][Cl] in a continuous column flow-through system in soil amended with waste sewage sludge. Addition of sludge serves two purposes: firstly increasing soil organic matter (formerly proved to facilitate retardation), and secondly augmenting soil with versatile microbial communities previously shown to successfully degrade ILs.

In silico modelling for predicting the cationic hydrophobicity and cytotoxicity of ionic liquids towards the Leukemia rat cell line, Vibrio fischeri and Scenedesmus vacuolatus based on molecular interaction potentials of ions.

In this study we present prediction models for estimating in silico the cationic hydrophobicity and the cytotoxicity (log [1/EC50]) of ionic liquids (ILs) towards the Leukemia rat cell line (IPC-81), the marine bacterium Vibrio fischeri and the limnic green algae Scenedesmus vacuolatus using linear free energy relationship (LFER) descriptors computed by COSMO calculations. The LFER descriptors used for the prediction model (i.e. excess molar refraction (E), dipolarity/polarizability (S), hydrogen-bonding acidity (A), hydrogen-bonding basicity (B) and McGowan volume (V)) were calculated using sub-descriptors (sig2, sig3, HBD3, HBA4, MR, and volume) derived from COSMO-RS, COSMO and OBPROP. With the combination of two solute descriptors (B, V) of the cation we were able to predict cationic hydrophobicity values (log ko ) with r (2) = 0.987 and standard error (SE) = 0.139 log units. By using the calculated log k o values, we were able to deduce a linear toxicity prediction model. In the second prediction study for the cytotoxicity of ILs, analysis of descriptor sensitivity helped us to determine that the McGowan volume (V) terms of the cation was the most important predictor of cytotoxicity and to simplify prediction models for cytotoxicity of ILs towards the IPC-81 (r (2) of 0.778, SE of 0.450 log units), Vibrio fischeri (r (2) of 0.762, SE of 0.529 log units) and Scenedesmus vacuolatus (r (2) of 0.776, SE of 0.825 log units). The robustness and predictivity of the two models for IPC-81 and Vibrio fischeri were checked by comparing the calculated SE and r (2) (coefficient of determination) values of the test set.

Predicting the critical micelle concentrations of aqueous solutions of ionic liquids and other ionic surfactants.

Some ionic liquids (ILs) are structurally analogous to surfactants, especially those that consist of a combination of organic and inorganic ions. The critical micelle concentration (CMC) is a basic parameter of surface chemistry and colloid science. A significant amount of research has already been carried out to determine the CMCs of ILs. However, because of the many varied cation/anion combinations, it is a daunting task to measure the CMCs of all possible ILs. Herein we suggest a general rule for predicting the CMCs of ionic surfactants in water based on data from COSMO-RS calculations. In accordance with the Stauff-Klevens rule, the molecular volume (V(m)) is sufficient to describe similar homologous series of cationic surfactants such as imidazolium- and ammonium-based ionic liquids with varying side-chain lengths. However, to also include anionic surfactants like Na[C(n)SO(4)] in a more general correlation, V(m) has to be exchanged by the cubed molecular radius (r3(m)) and the molecular surface has to be used as an additional descriptor. Furthermore, to describe double amphiphilic compounds like [C(4)MIm][C(8)SO(4)], the enthalpies of mixtures calculated by COSMO-RS have to be taken into account. The resulting equation had allowed us to predict the CMCs of all of the 36 tested surfactants with an error similar to or smaller than the usual experimental errors (18 different cations, 10 different anions: root mean squared error (rmse)=0.191 logarithmic units; R(2)=0.994). We discuss the factors governing micelle formation on the basis of our calculations and show that the structure of our equation can be related to Gibbs' theory of crystallization.