Activated carbon adsorption of cyanide complexes and thiocyanate ion from petrochemical wastewaters

Experimental isotherms indicate that thiocyanate and nickel cyanide complex (tetracyanonicklate (II)) adsorb to an equal extent from synthetic and actual waste solutions at loadings below 10 mg/g carbon. Loading of nickel hexammine complex is an order of magnitude less. Adsorption of the divalent nickel cation is strongly pH dependent and is believed to be a chemisorption by precipitation or reaction on the carbon surface. In pure solution, ferrocyanide (hexacyanoferrate (II)) adsorption was comparable to that of thiocyanate or nickelocyanide, but adsorption from the waste liquor tested was negligible. This difference may be due to solvation of ferrocyanide with methanol in the wastewater to form a species with entirely different adsorption characteristics. Chemical oxygen demand (COD) values were obtained for several of the pure materials (SCN^?, 1.1; Fe(CN)₆^?4, 0.5; Ni(CN)₄^?2, 0.4 mg $\text{COD}\text{mg}$ ion) and the wastewater to monitor adsorption of organic background materials.     

Novel Simple Conjugation Chemistries for Decoration of GMMA with Heterologous Antigens

Outer Membrane Vesicles (OMV) constitute a promising platform for the development of efficient vaccines. OMV can be decorated with heterologous antigens (proteins or polysaccharides), becoming attractive novel carriers for the development of multicomponent vaccines. Chemical conjugation represents a tool for linking antigens, also from phylogenetically distant pathogens, to OMV. Here we develop two simple and widely applicable conjugation chemistries targeting proteins or lipopolysaccharides on the surface of Generalized Modules for Membrane Antigens (GMMA), OMV spontaneously released from Gram-negative bacteria mutated to increase vesicle yield and reduce potential reactogenicity. A Design of Experiment approach was used to identify optimal conditions for GMMA activation before conjugation, resulting in consistent processes and ensuring conjugation efficiency. Conjugates produced by both chemistries induced strong humoral response against the heterologous antigen and GMMA. Additionally, the use of the two orthogonal chemistries allowed to control the linkage of two different antigens on the same GMMA particle. This work supports the further advancement of this novel platform with great potential for the design of effective vaccines.     

Direct and Indirect Effect of TGFβ on Treg Transendothelial Recruitment in HCC Tissue Microenvironment

The balance between anti-tumor and tumor-promoting immune cells, such as CD4+ Th1 and regulatory T cells (Tregs), respectively, is assumed to dictate the progression of hepatocellular carcinoma (HCC). The transforming growth factor beta (TGFβ) markedly shapes the HCC microenvironment, regulating the activation state of multiple leukocyte subsets and driving the differentiation of cancer associated fibroblasts (CAFs). The fibrotic (desmoplastic) reaction in HCC tissue strongly depends on CAFs activity. In this study, we attempted to assess the role of TGFβ on transendothelial migration of Th1-oriented and Treg-oriented CD4+ T cells via a direct or indirect, CAF-mediated mechanisms, respectively. We found that the blockage of TGFβ receptor I-dependent signaling in Tregs resulted in impaired transendothelial migration (TEM) of these cells. Interestingly, the secretome of TGFβ-treated CAFs inhibited the TEM of Tregs but not Th1 cells, in comparison to the secretome of untreated CAFs. In addition, we found a significant inverse correlation between alpha-SMA and FoxP3 (marker of Tregs) mRNA expression in a microarray analysis involving 78 HCCs, thus suggesting that TGFβ-activated stromal cells may counteract the trafficking of Tregs into the tumor. The apparent dual behavior of TGFβ as both pro- and anti-tumorigenic cytokines may add a further level of complexity to the mechanisms that regulate the interactions among cancerous, stromal, and immune cells within HCC, as well as other solid tumors, and contribute to better manipulation of the TGFβ signaling as a therapeutic target in HCC patients.     

Validation of a Lab-on-Chip Assay for Measuring Sorafenib Effectiveness on HCC Cell Proliferation

Hepatocellular carcinoma (HCC) is a highly lethal cancer, and although a few drugs are available for treatment, therapeutic effectiveness is still unsatisfactory. New drugs are urgently needed for hepatocellular carcinoma (HCC) patients. In this context, reliable preclinical assays are of paramount importance to screen the effectiveness of new drugs and, in particular, measure their effects on HCC cell proliferation. However, cell proliferation measurement is a time-consuming and operator-dependent procedure. The aim of this study was to validate an engineered miniaturized on-chip platform for real-time, non-destructive cell proliferation assays and drug screening. The effectiveness of Sorafenib, the first-line drug mainly used for patients with advanced HCC, was tested in parallel, comparing the gold standard 96-well-plate assay and our new lab-on-chip platform. Results from the lab-on-chip are consistent in intra-assay replicates and comparable to the output of standard crystal violet proliferation assays for assessing Sorafenib effectiveness on HCC cell proliferation. The miniaturized platform presents several advantages in terms of lesser reagents consumption, operator time, and costs, as well as overcoming a number of technical and operator-dependent pitfalls. Moreover, the number of cells required is lower, a relevant issue when primary cell cultures are used. In conclusion, the availability of inexpensive on-chip assays can speed up drug development, especially by using patient-derived samples to take into account disease heterogeneity and patient-specific characteristics.     

Multiple clusterings of heterogeneous information networks

Machine Learning - Traditional clustering algorithms focus on a single clustering result; as such, they cannot explore potential diverse patterns of complex real world data. To deal with this...     

Iodine Value and Fatty Acids Determination on Pig Fat Samples by FT-NIR Spectroscopy: Benefits of Variable Selection in the Perspective of Industrial Applications

In this work, FT-NIR spectroscopy was employed to determine iodine value (IV) and fatty acids (FA) content of pig fat samples, through the combined use of signal preprocessing, multivariate calibration, and variable selection methods. In particular, the main focus was on the use of variable selection methods, both in order to improve the predictive performance of the calibration models, and to identify relevant wavelengths that could be subsequently used for the development of simple, fast, and cheap hand-held devices, able to measure IV and FA content directly on the fat without the need of any sample pretreatment. Firstly, for each property of interest, partial least squares (PLS) multivariate calibration models were calculated considering the whole spectral range and testing different signal preprocessing methods. Then, once chosen the optimal signal preprocessing method, a two-step variable selection procedure was applied. In the first step, the interval-PLS variable selection algorithm was used to calculate a set of calibration models, whose outcomes were considered altogether in the second step, in order to select the optimal calibration model. The variable selection procedure allowed to lower the number of spectral variables retained by the model, and often led to an increase of the performance in prediction of the external test set samples.     

Mesoporous carbons supported non-noble metal Fe–N X electrocatalysts for PEM fuel cell oxygen reduction reaction

Three types of iron–nitrogen-containing non-noble metal catalysts, supported on an ultrasonic spray pyrolysis mesoporous carbon (USPMC), a hollow core mesoporous shell carbon (HCMSC), and a standard carbon (Ketjen Black CJ600, KB), respectively, are synthesized using a wet-impregnation method. The morphologies and structure as well as composition of the synthesized carbon supports and their corresponding supported Fe–N _X catalysts (namely Fe–N _X /USPMC, Fe–N _X /HCMSC, and Fe–N _X /KB, respectively) are physically characterized using EDX, SEM, FESEM, and BET analysis, respectively. The catalytic activities of these three electrocatalysts toward oxygen reduction reaction (ORR) are measured using rotating disk electrode technique in O₂-saturated 0.5 M H₂SO₄ solution. The catalyzed ORR exchange current densities are also obtained using the Tafel method based on the measured data. Among these three electrocatalysts, Fe–N _X /HCMSC can give the best ORR performance, which is correlated to its higher nitrogen, mesopore, and micropore contents, compared to the other electrocatalysts. It is rationalized that the performance improvement of these electrocatalysts may be achieved as long as an optimal relationship among mesopores, micropores, and even macropores for increasing both ORR kinetics and reactant gases accessibility to the active sites can be found.