Ammoniacal Carbonate Leaching: Effect of Dissolved Sulfur in the Distillation Operation.

The distillation process in the Ammoniacal Carbonate Leaching technology was studied at bench-scale and on industrial scale. The dissolved sulfur effect in the Product-liquor that feeds to the columns, on the Basic Nickel Carbonate (BNC) properties and the operation expenses was determined. When increasing the sulfur in the liquor, we augment the selectivity towards the sulfate formation in the BNC molecule; therefore the energy consumption to the BNC thermal decomposition in the calcination process increases.

Diagnostic benefits of adding EspC, EspF and Rv2348-B to the QuantiFERON Gold In-tube antigen combination.

Interferon (IFN)-γ release assays (IGRAs) are used to diagnose latent tuberculosis (TB) infection (LTBI). To improve the accuracy of these tests, different approaches, such as alternative cytokine detection and using different antigens, are considered. Following this purpose, this study aims to evaluate the addition of EspC, EspF and Rv2348-B to those present in the QuantiFERON-TB Gold In-Tube (QFN-G-IT).

Diagnostic Accuracy of Interferon Gamma-Induced Protein 10 mRNA Release Assay for Tuberculosis.

Interferon gamma (IFN-γ) release assays (IGRAs) are increasingly used to test for latent tuberculosis (TB) infection. Although highly specific, IGRAs have a relatively high false-negative rate in active TB patients. A more sensitive assay is needed.

Use of IP-10 detection in dried plasma spots for latent tuberculosis infection diagnosis in contacts via mail.

The aim of this study was to test the use of IP-10 detection in dried plasma from contact studies individuals (contacts of smear positive patients), by comparing it with IP-10 and IFN-γ detection in direct plasma, to establish IP-10 detection in DPS as a useful assay for LTBI diagnosis. Whole blood samples were collected from 80 subjects: 12 with active tuberculosis (TB), and 68 from contact studies. The amount of IFN-γ produced by sensitized T cells was determined in direct plasma by QuantiFERON Gold In-Tube test.

Study of CD27 and CCR4 Markers on Specific CD4 T-Cells as Immune Tools for Active and Latent Tuberculosis Management.

The immunological characterization of different cell markers has opened the possibility of considering them as immune tools for tuberculosis (TB) management, as they could correlate with TB latency/disease status and outcome. CD4 T-cells producing IFN-γ with a low expression of CD27 have been described as an active TB marker. In addition, there are unknown homing receptors related to TB, such as CCR4, which might be useful for understanding TB pathogenesis.

Assessment of the influence of direct tobacco smoke on infection and active TB management.

Background: Smoking is a risk factor for tuberculosis (TB) infection and disease progression. Tobacco smoking increases susceptibility to TB in a variety of ways, one of which is due to a reduction of the IFN-γ response. Consequently, an impaired immune response could affect performance of IFN-γ Release Assays (IGRAs).

Proteomics, networks and connectivity indices.

Describing the connectivity of chemical and/or biological systems using networks is a straight gate for the introduction of mathematical tools in proteomics. Networks, in some cases even very large ones, are simple objects that are composed at least by nodes and edges. The nodes represent the parts of the system and the edges geometric and/or functional relationships between parts.

Computational chemistry approach to protein kinase recognition using 3D stochastic van der Waals spectral moments.

Three-dimensional (3D) protein structures now frequently lack functional annotations because of the increase in the rate at which chemical structures are solved with respect to experimental knowledge of biological activity. As a result, predicting structure-function relationships for proteins is an active research field in computational chemistry and has implications in medicinal chemistry, biochemistry and proteomics. In previous studies stochastic spectral moments were used to predict protein stability or function (González-Díaz, H.

QSAR study of anticoccidial activity for diverse chemical compounds: prediction and experimental assay of trans-2-(2-nitrovinyl)furan.

In this work we report a QSAR model that discriminates between chemically heterogeneous classes of anticoccidial and non-anticoccidial compounds. For this purpose we used the Markovian Chemicals in silico Design (MARCH-INSIDE) approach J. Mol.

Simple stochastic fingerprints towards mathematical modeling in biology and medicine. 3. Ocular irritability classification model.

MARCH-INSIDE methodology and a statistical classification method--linear discriminant analysis (LDA)--is proposed as an alternative method to the Draize eye irritation test. This methodology has been successfully applied to a set of 46 neutral organic chemicals, which have been defined as ocular irritant or nonirritant. The model allow to categorize correctly 37 out of 46 compounds, showing an accuracy of 80.

3D-QSAR study for DNA cleavage proteins with a potential anti-tumor ATCUN-like motif.

Genomics projects have elucidated several genes that encode protein sequences. Subsequently, the advent of the proteomics age has enabled the synthesis and 3D structure determination for these protein sequences. Some of these proteins incorporate metal atoms but it is often not known whether they are metal-binding proteins and the nature of the biological activity is not understood.

Novel 2D maps and coupling numbers for protein sequences. The first QSAR study of polygalacturonases; isolation and prediction of a novel sequence from Psidium guajava L.

The development of 2D graph-theoretic representations for DNA sequences was very important for qualitative and quantitative comparison of sequences. Calculation of numeric features for these representations is useful for DNA-QSAR studies. Most of all graph-theoretic representations identify each one of the four bases with a unitary walk in one axe direction in the 2D space.

QSAR study for mycobacterial promoters with low sequence homology.

The general belief is that quantitative structure-activity relationship (QSAR) techniques work only for small molecules and, protein sequences or, more recently, DNA sequences. However, with non-branched graph for proteins and DNA sequences the QSAR often have to be based on powerful non-linear techniques such as support vector machines. In our opinion, linear QSAR models based on RNA could be useful to assign biological activity when alignment techniques fail due to low sequence homology.