Neurological manifestations of COVID-19 in patients: from path physiology to therapy

Coronavirus is a family of ARN positive single-stranded belonging to the family of Coronaviridae. There are several families of coronavirus that transmit more or less serious diseases. However, the so-called coronavirus-19 (SARS-CoV2) is the one that is currently causing most of the problems; in fact, biological dysfunctions that this virus causes provoke damage in various organs, from the lung to the heart, the kidney, the circulatory system, and even the brain. The neurological manifestations caused by viral infection, as well as the hypercoagulopathy and systemic inflammation, have been reported in several studies. In this review, we update the neurological mechanisms by which coronavirus-19 causes neurological manifestation in patients such as encephalomyelitis, Guillain-Barré syndrome, lacunars infarcts, neuropsychiatry disorders such as anxiety and depression, and vascular alterations. This review explains (a) the possible pathways by which coronavirus-19 can induce the different neurological manifestations, (b) the strategies used by the virus to cross the barrier system, (c) how the immune system responds to the infection, and (d) the treatment than can be administered to the COVID-19 patients.

Searching for a predictive peripherical biological model in parasuicidal behaviour

The aim of this study was to identify possible peripheral biological markers (both lipidic and hormonal) which can be easily used for the early detection of parasuicidal behaviour and to propose a predictive biological model of such behaviour. A case-control analytical study was undertaken at least 3 months after attempted suicide. Study was made of 128 patients who presented at the University General Hospital of Oviedo (Spain) with signs of self-intoxication. Lipidic and hormonal profiles were measured under basal conditions and comparison was made with a control group of healthy volunteer donors obtained from the Oviedo General Hospital blood bank. A discriminant analysis was later made with the aim of establishing a predictive biological model. This included the following variables: cholesterol, HDL-C, LDL-C and cortisol. Sensitivity and specificity were 62.5% and 65.6%, respectively. Replication and improvement of this model, through other prospective studies, could lead to the use of serum cholesterol and cortisol levels as inexpensive and readily available markers of suicide risk.

Response of Caligus rogercresseyi (Boxshall & Bravo, 2000) to treatment with Hydrogen Peroxide: Recovery of parasites, fish infestation and egg viability under experimental conditions

Hydrogen peroxide (HP) is used to remove C. rogercresseyi from fish but little is known about its effect on this species. This study determined EC₅₀ and concentration immobilizing 100% of specimens, capacity of parasites exposed to HP to recover and infest fish, and effect on survival into the copepodid stage. EC₅₀ and concentration immobilizing 100% of specimens were estimated by exposing parasites for 20 min to 11 concentrations and evaluating effect at 1 and 24 h post-exposure. Capacity to recover and infest fish, and survival into copepodid were evaluated by exposing parasites and eggs to HP for 20 min. Recovery and fish infestation were evaluated at 25 and 24 h post-exposure, respectively. Eggs were grown until control reached the copepodid stage and survival calculated. EC₅₀ was 709.8 ppm.100% immobilization was obtained at 825 ppm. Male and female recover 0.5 and 1 h post-exposure, respectively. Percentage of parasites exposed and not exposed to HP that were recovered on fish was not significantly different. Survival to copepodid was lower in those exposed to HP. HP effect is greater on copepodids, but 100% of the mobile stages are immobilized under 825 ppm causing detachment from fish and potentially driven away, reducing infestation risk.

Glutamate triggers neurosecretion and apoptosis in bovine chromaffin cells through a mechanism involving NO production by neuronal NO synthase activation

Previous work from our group stated that nitric oxide (NO), via cytokines, induces apoptosis in chromaffin cells by a mechanism involving iNOS, nNOS, and NF-κB. In this paper the involvement of glutamate as a possible intracellular trigger of neurosecretion and NO-mediated apoptosis has been evaluated. We show that chromaffin cells express different ionotropic and metabotropic glutamate receptors, this exerting different effects on the regulation of basal and glutamate-induced catecholamine secretion, via NO/cGMP. In addition, we studied the effects of endogenously generated NO, both basal and glutamate-stimulated, on apoptosis of chromaffin cells. Our results show that glutamate agonists are able to induce cell death and apoptosis in bovine chromaffin cells, parallel to an increase in NO production. Such effects were reversed by NOS inhibitors and glutamate receptor antagonists. Under basal conditions, iNOS inhibitors did not have any effect on apoptosis, whereas nNOS inhibitors induced apoptosis, indicating a neuroprotective effect of constitutive nNOS-generated NO. In contrast, glutamate-induced apoptosis was strongly reversed by nNOS inhibitors and weakly by iNOS inhibitors, thus indicating nNOS involvement in glutamate-mediated apoptosis. These results were confirmed by the fact that nNOS expression, but not iNOS, is specifically activated by glutamate. Finally, our results suggest the participation of PKG, PKA, PKC, and MAPK pathways in glutamate-mediated nNOS activation in chromaffin cells and point out the involvement of both PKA and PKC signaling pathways in the apoptotic effect of glutamate.

Design, Synthesis, and Evaluation of Antineoplastic Activity of Novel Carbocyclic Nucleosides

Cancer is the leading cause of death among men and women under age 85. Every year, millions of individuals are diagnosed with cancer. But finding new drugs is a complex, expensive, and very time-consuming task. Over the past decade, the cancer research community has begun to address the in silico modeling approaches, such as Quantitative Structure-Activity Relationships (QSAR), as an important alternative tool for targeting potential anticancer drugs. With the compilation of a large dataset of nucleosides synthesized in our laboratories, or elsewhere, and tested in a single cytotoxic assay under the same experimental conditions, we recognized a unique opportunity to attempt to build predictive QSAR models. Early efforts with 2D classification models built from part of this dataset were very encouraging. Here we report a further detailed evaluation of classification models to flag potential anticancer activities derived from a variety of 3D molecular representations. A quantitative 3D-model model that discriminates anticancer compounds from the inactive ones was attained, which allowed the correct classification of 82 % of compounds in such a large and diverse dataset, with only 5 % of false inactives and 11 % of false actives. The model developed here was then used to select and design a new series of nucleosides, by classifying beforehand them as active/inactive anticancer compounds. From the compounds so designed, 22 were synthesized and evaluated for their inhibitory effects on the proliferation of murine leukemia cells (L1210/0), of which 86 % were well-classified as active or inactive, and only two were false actives, corroborating the good predictive ability of the present discriminant model. The results of this study thus provide a valuable tool for the design of novel potent anticancer nucleoside analogues.

[Recommendations for the management of influenza in pediatrics (2009-2010).]

Specific action plans from various institutions, governments and scientific societies have been identified and implemented to combat the A H1N1 2009 influenza virus pandemic. This document sets out the recommendations of the Spanish Association of Pediatrics for the management of influenza in children for influenza season 2009-2010. The risk factors for influenza A H1N1 2009 in pediatric patients, the clinical course, severity and complications are similar to seasonal influenza. In most cases, the diagnosis of influenza will be based on clinical suspicion, without viral subtype differentiation. In a patient with influenza virus infection, the criteria for referral and hospital admission will be based broadly on the signs of clinical severity or complications, regardless of the causative virus. Children with influenza but with no signs of clinical severity or complications do not require antiviral treatment. Physical measures of hygiene and isolation are essential to reduce the transmissibility of the disease. The influenza vaccines in infancy, for both seasonal influenza and for influenza A H1N1 2009, should be directed primarily at patients with risk factors.

Variable selection methods in QSAR: an overview

Variable selection is a procedure used to select the most important features to obtain as much information as possible from a reduced amount of features. The selection stage is crucial. The subsequent design of a quantitative structure-activity relationship (QSAR) model (regression or discriminant) would lead to poor performance if little significant features are selected. In drug design modern era, by the means of combinatorial chemistry and high throughput screening, an unprecedented amount of experimental information has been generated. In addition, many molecular descriptors have been defined in the last two decays. All this information can be analyzed by QSAR techniques using adequate statistical procedures. These techniques and procedures should be fast, automated, and applicable to large data sets of structurally diverse compounds. For that reason, the identification of the best one seems to be a very difficult task in view of the large variable selection techniques existing nowadays. The intention of this review is to summarize some of the present knowledge concerning to variable selection methods applied to some well-known statistical techniques such as linear regression, PLS, kNN, Artificial Neural Networks, etc, with the aim to disseminate the advances of this important stage of the QSAR building model.

Search for new antagonist ligands for adenosine receptors from QSAR point of view. How close are we?

In view of the large libraries of nucleoside analogues that are now being handled in organic synthesis, the identification of drug biological activity is advisable prior to synthesis and this can be achieved by employing predictive biological property methods. In this sense, Quantitative Structure-Activity Relationships (QSAR) or docking approaches have emerged as promising tools. Although a large number of in silico approaches have been described in the literature for the prediction of different biological activities, the use of QSAR applications to develop adenosine receptor (AR) antagonists is not common as for the case of the antibiotics and anticancer compounds for instance. The intention of this review is to summarize the present knowledge concerning computational predictions of new molecules as adenosine receptor antagonists.

Quantitative structure carcinogenicity relationship for detecting structural alerts in nitroso-compounds

Prevention of environmentally induced cancers is a major health problem of which solutions depend on the rapid and accurate screening of potential chemical hazards. Lately, theoretical approaches such as the one proposed here - Quantitative Structure-Activity Relationship (QSAR) - are increasingly used for assessing the risks of environmental chemicals, since they can markedly reduce costs, avoid animal testing, and speed up policy decisions. This paper reports a QSAR study based on the Topological Substructural Molecular Design (TOPS-MODE) approach, aiming at predicting the rodent carcinogenicity of a set of nitroso-compounds selected from the Carcinogenic Potency Data Base (CPDB). The set comprises nitrosoureas (14 chemicals), N-nitrosamines (18 chemicals) C-nitroso-compounds (1 chemical), nitrosourethane (1 chemical) and nitrosoguanidine (1 chemical), which have been bioassayed in male rat using gavage as the route of administration. Here we are especially concerned in gathering the role of both parameters on the carcinogenic activity of this family of compounds. First, the regression model was derived, upon removal of one identified nitrosamine outlier, and was able to account for more than 84% of the variance in the experimental activity. Second, the TOPS-MODE approach afforded the bond contributions -- expressed as fragment contributions to the carcinogenic activity -- that can be interpreted and provide tools for better understanding the mechanisms of carcinogenesis. Finally, and most importantly, we demonstrate the potentialities of this approach towards the recognition of structural alerts for carcinogenicity predictions.

Folate status and S-adenosylmethionine/S-adenosylhomocysteine ratio in colorectal adenocarcinoma in humans

OBJECTIVES

This study reports the influence of colorectal neoplasia on methylation intermediates and folate concentrations in human colonic mucosa, as well as systemic measures of folate status, to examine biomarkers and possible mechanisms of folate-related carcinogenesis.

SUBJECTS

A total of 47 patients were selected from those previously diagnosed with adenocarcinoma of the colorectum undergoing surgery. For each individual, we obtained a biopsy of the adenocarcinoma and a biopsy of normal appearing mucosa, to perform an intra-individual comparison.

RESULTS

The 'methylation' ratio (S-adenosylmethionine/S-adenosylhomocysteine (SAH)) was lower in pathological tissue vs normal mucosa (P=0.08), mainly due to a much higher SAH concentration (P<0.005). Colonic folate concentration was significantly diminished in malignant tissue (P<0.0001). Plasma homocysteine concentration was within the normal to high range, and folate and vitamin B12 plasma concentrations were within the low to normal range as compared with normative values.

CONCLUSION

Our results contribute to the hypothesis that altered DNA methylation and methyl metabolism is associated with colorectal neoplasia.

2D-autocorrelation descriptors for predicting cytotoxicity of naphthoquinone ester derivatives against oral human epidermoid carcinoma

A QSAR study was developed, employing 2D-autocorrelation descriptors and a set of 37 naphthoquinone ester derivatives, in order to model the cytotoxicity of these compounds against oral human epidermoid carcinoma (KB). A comparison with other approaches such as the BCUT, Galvez topological charge indexes, Randić molecular profile, Geometrical, and RDF descriptors was carried out. Mathematical models were obtained by means of the multiple regression analysis (MRA) and the variables were selected using genetic algorithm. Based on the statistical results the 2D-autocorrelation descriptors were considered the best and were able to describe more than 84.2% of the variance in the experimental activity once we controlled for outliers.

Quantitative structure–activity relationship studies of HIV-1 integrase inhibition. 1. GETAWAY descriptors

The GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) approach has been applied to the study of the HIV-1 integrase inhibition of 172 compounds that belong to 11 different chemistry families. A model able to describe more than 68.5% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, none of the five different approaches, including the use of Randić Molecular Profiles, Geometrical, RDF, 3D-MORSE and WHIM descriptors was able to explain more than 62.4% of the variance in the mentioned property with the same number of variables in the equation. Finally, after extracting five compounds considered by us as outliers the model was able to describe more than 72.5% of the variance in the experimental activity.

Quantitative structure–activity relationship studies for the prediction of antifungal activity of N-arylbenzenesulfonamides against Botrytis cinerea

The Botrytis cinerea is one of the most interesting fungal pathogens. It can infect almost every plant and plant part and cause early latent infections which damage the fruit before ripening. The QSAR is an alternative method for the research of new and better fungicides against B. cinerea. This paper describes the results of applying a topological sub-structural molecular design (TOPS-MODE) approach for predicting the antifungal activity of 28 N-arylbenzenesulfonamides. The model described 86.1% of the experimental variance, with a standard deviation of 0.223. Leave-one-out and leave-group-out cross validation was carried out with the aim of evaluating the predictive power of the model. The values of their respective squared correlations coefficients were 0.754 and 0.741. The TOPS-MODE approach was compared with three other predictive models, but none of these could explain more than 72.8% of the variance with the same number of variables. In addition, this approach enabled the assessment of the contribution of different bonds to antifungal activity, thereby making the relationships between structure and biological activity more transparent. It was found that the fungicidal activity of the chemicals analyzed was increased by the presence of a sulfonamide group bonded to two aromatics rings, making this group the most important of the molecule. The majority of the substituents present in the aromatic rings have an electron withdrawing effect and they contribute to a smaller degree than the sulfonamide group to the property under study. The aromatic moiety plays an important role in this activity; its contribution changes with different substituents. Generally, the nitro group has a positive and great contribution to the biological property but when this group is involved in some compounds in ortho effect with the SO2 moiety of the sulfonamide group a lower value of contribution is observed for both groups.

QSAR Studies Using Radial Distribution Function for Predicting A1 Adenosine Receptors Agonists

The radial distribution function (RDF) approach has been applied to the study of the A(1) adenosine receptors agonist effect of 32 adenosine analogues. A model able to describe more than 79% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, none of the three different approaches, including the use of 2D autocorrelations, BCUT and 3D-MORSE descriptors were able to explain more than 72% of the variance in the mentioned property with the same number of variables in the equation. In addition, we established a comparison with other models reported by us for this receptor subtype using this data set, and the RDF descriptors continue getting the best results.

QSAR studies about cytotoxicity of benzophenazines with dual inhibition toward both topoisomerases I and II: 3D-MoRSE descriptors and statistical considerations about variable selection

Deoxyribonucleic acid (DNA) topoisomerases are involved in diverse cellular processes, such as replication, transcription, recombination, and chromosome segregation. Searching new compounds that inhibit both topoisomerases I and II is very important due to the deficiency of the specific inhibitors to overcome multidrug resistance (MDR). A QSAR study was developed, employing the 3D-MoRSE descriptors and a set of 64 benzophenazines in order to model the inhibition of the topoisomerases I and II, expressed by the cytotoxicity of these compounds (IC(50)) versus drug-resistant human small cell lung carcinoma line cell H69/LX4. A comparison with other approaches such as the Topological, BCUT, Galvez topological charge indexes, 2D autocorrelations, Randić molecular profile, Geometrical, RDF, and WHIM descriptors was carried out. The mathematical models were obtained by means of the multiple regression analysis (MRA) and the variables were selected using the genetic algorithm. The model relative to the 3D-MoRSE descriptors was considered as the best, taking into account its statistical parameters. It was able to describe more than 82.2% of the variance in the experimental activity once the outliers were extracted.

Quantitative Structure Activity Relationships as Useful Tools for the Design of New Adenosine Receptor Ligands. 1. Agonist

In order to minimize expensive drug failures it is essential to determine the potential biological activity of new candidates as early as possible. In view of the large libraries of nucleoside analogues that are now being handled in organic synthesis, the identification of a drugs biological activity is advisable even before synthesis and this can be achieved using predictive biological activity methods. In this sense, computer aided rational drug design strategies like Quantitative Structure Activity Relationships (QSAR) or docking approaches have emerged as promising tools. Although a large number of in silico approaches have been described in the literature for the prediction of different biological activities, the use of traditional QSAR applications in the development of new agonist molecules with affinity toward adenosine receptors is scarce. This review attempts to summarize the current level of knowledge concerning computational affinity predictions for adenosine receptors using QSAR models based on knowledge of the agonist ligands. Several computational protocols and different 2D and 3D descriptors have been described in the literature for these targets, but more effort is still required in this area.

In silico studies using Radial Distribution Function approach for predicting affinity of 1 alpha,25-dihydroxyvitamin D(3) analogues for Vitamin D receptor

The Radial Distribution Function (RDF) approach has been applied to the study of the chick intestinal VDR affinity of 49 Vitamin D analogues. A model able to describe more than 77.5% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, none of four different approaches, including the use of Topological, BCUT, Randić molecular profiles and Geometrical descriptors were able to explain more than 55% of the variance in the mentioned property, with the same number of variables in the equation.

Mitochondrial involvement in nitric oxide-induced cellular death in cortical neurons in culture

Nitric oxide (NO) is an unstable molecule with physiological and pathological properties. In brain, NO acts as a modulator of neurotransmission as well as a protector against neuronal death from several death stimuli. However, beside this protector effect, high NO concentrations produce neuronal death by a mechanism in which the caspase pathway is implicated. In this work, we demonstrate that in cortical neurons the NO toxicity is mediated by mitochondrial dysfunction. SNAP, an NO donor, induces apoptosis in these cells because it 1) increases the p53 and 2) induces cytochrome c release and activation of caspase-9 and caspase-3. SNAP also induces necrosis, through 1) breakdown of the mitochondrial membrane potential, 2) ATP decrease, 3) ROS formation, and 4) LDH and ATP release, indicative of oxidative stress and death by necrosis. To sum up, in cortical neurons, high NO concentrations produced cellular death by both an apoptotic and a necrotic mechanism in which the mitochondria are implicated.

A topological substructural molecular design to predict soil sorption coefficients for pesticides

A TOPological Sub-structural MOlecular DEsign (TOPS-MODE) approach was used to predict the soil sorption coefficients for a set of pesticide compounds. The obtained model accounted for more than 85% of the data variance and demonstrated the importance of the dipole moment, the standard distance, the polarizability, and the hydrophobicity in describing the property under study. In addition, we compared this new model to a previous one using different descriptors such as WHIM and molecular connectivity indices. Finally, the TOPS-MODE was used to calculate the contribution of different fragments to the soil sorption coefficient of the compounds studied. The present approximation proved to be a good method for studying the soil sorption coefficient for pesticides, but it could also be extended to other series of chemicals.

2D autocorrelation modelling of the inhibitory activity of cytokinin-derived cyclin-dependent kinase inhibitors

The inhibitory activity towards p34(cdc2)/cyclin b kinase (CBK) enzyme of 30 cytokinin-derived compounds has been successfully modelled using 2D spatial autocorrelation vectors. Predictive linear and non-linear models were obtained by forward stepwise multi-linear regression analysis (MRA) and artificial neural network (ANN) approaches respectively. A variable selection routine that selected relevant non-linear information from the data set was employed prior to networks training. The best ANN with three input variables was able to explain about 87% data variance in comparison with 80% by the linear equation using the same number of descriptors. Similarly, the neural network had higher predictive power. The MRA model showed a linear dependence between the inhibitory activities and the spatial distributions of masses, electronegativities and van der Waals volumes on the inhibitors molecules. Meanwhile, ANN model evidenced the occurrence of non-linear relationships between the inhibitory activity and the mass distribution at different topological distance on the cytokinin-derived compounds. Furthermore, inhibitors were well distributed regarding its activity levels in a Kohonen self-organizing map (SOM) built using the input variables of the best neural network.

Cadmium induces reactive oxygen species generation and lipid peroxidation in cortical neurons in culture

Cadmium is a toxic agent that it is also an environmental contaminant. Cadmium exposure may be implicated in some humans disorders related to hyperactivity and increased aggressiveness. This study presents data indicating that cadmium induces cellular death in cortical neurons in culture. This death could be mediated by an apoptotic and a necrotic mechanism. The apoptotic death may be mediated by oxidative stress with reactive oxygen species (ROS) formation which could be induced by mitochondrial membrane dysfunction since this cation produces: (a) depletion of mitochondrial membrane potential and (b) diminution of ATP levels with ATP release. Necrotic death could be mediated by lipid peroxidation induced by cadmium through an indirect mechanism (ROS formation). On the other hand, 40% of the cells survive cadmium action. This survival seems to be mediated by the ability of these cells to activate antioxidant defense systems, since cadmium reduced the intracellular glutathione levels and induced catalase and SOD activation in these cells.

Preliminary tests on nisin and pediocin production using waste protein sources. Factorial and kinetic studies

Lactic acid bacteria, the object of current interest as bacteriocin producers, are microorganisms with complex requirements for peptidic sources, making them appropriate indicators for testing the suitability of formulations based on proteinaceous wastes for use as microbiological media. Different peptones obtained from visceral and fish muscle residues promoted growth of lactic acid bacteria when applied individually or in combination. Kinetic parameters and bacteriocin production were similar and, in some cases (pediocin), far superior (>500%) to those obtained with bactopeptones and commercial media specifically recommended for lactic acid bacteria growth. Visceral residues, especially when subjected to a brief process of autohydrolysis at 20 degrees C, were more efficient for bacterial growth than muscle, even when muscle was treated with pepsin.

Quantitative structure activity relationship for the computational prediction of nitrocompounds carcinogenicity

Several nitrocompounds have been screened for carcinogenicity in rodents, but this is a lengthy and expensive process, taking two years and typically costing 2.5 million dollars, and uses large numbers of animals. There is, therefore, much impetus to develop suitable alternative methods. One possible way of predicting carcinogenicity is to use quantitative structure-activity relationships (QSARs). QSARs have been widely utilized for toxicity testing, thereby contributing to a reduction in the need for experimental animals. This paper describes the results of applying a TOPological substructural molecular design (TOPS-MODE) approach for predicting the rodent carcinogenicity of nitrocompounds. The model described 79.10% of the experimental variance, with a standard deviation of 0.424. The predictive power of the model was validated by leave-one-out validation, with a determination coefficient of 0.666. In addition, this approach enabled the contribution of different fragments to carcinogenic potency to be assessed, thereby making the relationships between structure and carcinogenicity to be transparent. It was found that the carcinogenic activity of the chemicals analysed was increased by the presence of a primary amine group bonded to the aromatic ring, a manner that was proportional to the ring aromaticity. The nitro group bonded to an aromatic carbon atom is a more important determinant of carcinogenicity than the nitro group bonded to an aliphatic carbon. Finally, the TOPS-MODE approach was compared with four other predictive models, but none of these could explain more than 66% of the variance in the carcinogenic potency with the same number of variables.

Proteases production by two Vibrio species on residuals marine media

A comparative study was carried out on the growth and production of alkaline proteases by two Vibrio species using different marine peptones from fish viscera residues. The bacteria tested, Vibrio anguillarum and Vibrio splendidus, are producers of high levels of proteolytic enzymes which act as factors of virulence in fish cultures, causing high mortality rates. The kinetic assays and subsequent comparison with the parameters obtained from the adjustment to various mathematical models, highlighted the potential interest of the media formulated, for their possible production on an industrial scale, particularly the production of proteases by V. anguillarum growing in rainbow trout and squid peptones.

A radial-distribution-function approach for predicting rodent carcinogenicity

Carcinogenic activity has been investigated using the Radial-Distribution-Function (RDF) approach. A discriminant model was developed to predict the carcinogenic and non-carcinogenic activity on a data set of 188 compounds. The percentage of overall classification was 76.4% for the carcinogenic chemicals and 72.5% for the non-carcinogenic chemicals. The predictive power of the model was validated by two tests: a cross-validation by the resubstitution technique and a test set (compounds not used in the development of the model) with 79.3 and 72.5% good classification, respectively. The RDF descriptors were compared with eight other methodologies; Constitutional, Molecular walks counts, Galvez topological charge indices, 2D autocorrelations, Randić molecular profiles, Geometrical, 3D-MORSE, and WHIM, demonstrating that the RDF descriptors are better to the rest of the approaches used.

Nitric oxide and peroxynitrite induce cellular death in bovine chromaffin cells: Evidence for a mixed necrotic and apoptotic mechanism with caspases activation

Treatment of chromaffin cells with nitric oxide (NO) donors (SNP and SNAP) and peroxynitrite produces a time- and dose-dependent necrotic and apoptotic cell death. Necrotic cell death was characterized by both an increase in lactate dehydrogenase and ATP release and changes in nuclei and cell morphology (as seen with fluorescence microscopy analysis with propidium iodide and Hoechst 33342). Apoptotic cell death was characterized by nuclear fragmentation and presence of apoptotic cell bodies, by a decrease in DNA content, and by an increase in DNA fragmentation. Treatment of chromaffin cells with lipopolysaccharide (LPS) or cytokines (interferon-gamma, tumor necrosis factor-alpha) resulted only in apoptotic cell death. Apoptotic effects of NO-inducing compounds were specifically reversed, depending on the stimuli, by the NO scavenger carboxy-PTIO (CPTio) or by the NOS inhibitors L-NMA and thiocitrulline. NO-induced apoptotic death in chromaffin cells was concomitant to a cell cycle arrest in G0G1 phase and a decrease in the number of chromaffin cells in the G2M and S phases of cell cycle. All NO-producing compounds were able to induce activation of caspase 3 and cytochrome c release, and specific inhibitors of caspase 3 and 9, such as Ac-DEVD-CHO (CPP32) and Ac-Z-LEHD-FMK, respectively, prevented NO-induced apoptosis in chromaffin cells. These results suggest that chromaffin cells could be good models for investigating the molecular basis of degeneration in diseases showing death of catecholaminergic neurons, phenomenon in which NO plays an important role.

Modeling of farnesyltransferase inhibition by some thiol and non-thiol peptidomimetic inhibitors using genetic neural networks and RDF approaches

Inhibition of farnesyltransferase (FT) enzyme by a set of 78 thiol and non-thiol peptidomimetic inhibitors was successfully modeled by a genetic neural network (GNN) approach, using radial distribution function descriptors. A linear model was unable to successfully fit the whole data set; however, the optimum Bayesian regularized neural network model described about 87% inhibitory activity variance with a relevant predictive power measured by q2 values of leave-one-out and leave-group-out cross-validations of about 0.7. According to their activity levels, thiol and non-thiol inhibitors were well-distributed in a topological map, built with the inputs of the optimum non-linear predictor. Furthermore, descriptors in the GNN model suggested the occurrence of a strong dependence of FT inhibition on the molecular shape and size rather than on electronegativity or polarizability characteristics of the studied compounds.

Radial distribution function descriptors: an alternative for predicting A2 A adenosine receptors agonists

The Radial Distribution Function approach has been applied to the study of the A2 A adenosine receptors agonist effect of 29 adenosine analogues: N6- arylcarbamoyl, 2-arylalkynyl-N6 -arylcarbamoyl, and N6 -carboxamido derivatives. A model able to describe around 85% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, no one of nine different approaches, including the use of Galvez Topological Charges indexes, BCUT, Geometrical, 2D autocorrelations, Topological, Randić Molecular profile, WHIM, 3D-MORSE and GETAWAY descriptors were able to explain more than 78% of the variance in the mentioned property with the same number of variables in the equation. Finally, the model support that the bulkiness and stereoselectivity play an important role in the affinity for this receptor in this kind of compounds.

A topological function based on spectral moments for predicting affinity toward A3 adenosine receptors

The spectral moment descriptors have been applied to the study of affinity for A(3) adenosine receptors of 32 adenosine analogues. A model, able to describe more than 95% of the variance in the experimental activity, was developed with the use of the above-mentioned approach. The fragment contributions to the activity carried out show that the sulfonamido moiety at the N(6) position and hydrogen bonding play an important role in the interaction with the receptor.

GETAWAY descriptors to predicting A2A adenosine receptors agonists

The GEometry, Topology and Atom-Weights AssemblY approach has been applied to the study of the A(2A) adenosine receptors agonist effect of 29 adenosine analogues: N(6)-arylcarbamoyl, 2-arylalkynyl-N(6)-arylcarbamoyl, and N(6)-carboxamido derivatives. A model able to describe more than 77% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, no one of four different approaches, including the use of Topological, Galvez Topological Charges indexes, Geometrical and WHIM descriptors were able to explain more than 70% of the variance in the mentioned property with the same number of variables in the equation.

Quantitative structure-activity relationship studies of vitamin D receptor affinity for analogues of 1alpha,25-dihydroxyvitamin D3. 1: WHIM descriptors

The weighted holistic invariant molecular (WHIM) approach has been applied to the study of the VDR affinity of 86 vitamin D analogues. A model able to describe more than 71% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, none of three different approaches, including the use of BCUT, Galvez topological charge indices, and 2D autocorrelations descriptors, was able to explain more than 38% of the variance in the mentioned property, even with more variables in the equation.

A topological substructural approach applied to the computational prediction of rodent carcinogenicity

The carcinogenic activity has been investigated by using a topological substructural molecular design approach (TOPS-MODE). A discriminant model was developed to predict the carcinogenic and noncarcinogenic activity on a data set of 189 compounds. The percentage of correct classification was 76.32%. The predictive power of the model was validated by three test: an external test set (compounds not used in the develop of the model, with a 72.97% of good classification), a leave-group-out cross-validation procedure (4-fold full cross-validation, removing 20% of compounds in each cycle, with a good prediction of 76.31%) and two external prediction sets (the first and second exercises of the National Toxicology Program). This methodology evidenced that the hydrophobicity increase the carcinogenic activity and the dipole moment of the molecule decrease it; suggesting the capacity of the TOPS-MODE descriptors to estimate this property for new drug candidates. Finally, the positive and negative fragment contributions to the carcinogenic activity were identified (structural alerts) and their potentialities in the lead generation process and in the design of 'safer' chemicals were evaluated.

BCUT descriptors to predicting affinity toward A3 adenosine receptors

The BCUT descriptors have been applied to the study of the A(3) adenosine receptor agonist effect of 32 adenosine analogues. A model, able to describe more than 80% of the variance in the experimental activity was developed with the use of the above-mentioned approach. Four different approaches (topological, Galvez topological charges indexes, Randić molecular profiles, and geometrical descriptors) failed to give satisfactory models for this property with the same number of variables in the equation. Although statistically significant models were derived containing descriptors other than BCUT, the best fitted model was still found with these descriptors.

Quantitative structure-activity relationship to predict toxicological properties of benzene derivative compounds

TOPological Sub-structural MOlecular DEsign (TOPS-MODE) was used to assess acute aquatic toxicity of a series of 69 benzene derivatives. The obtained model was able to explain more than 88% of data variance, stressing the importance of molecule hydrophobicity and its dipolar moment, as well as the distance between their bonds to describe the property under study. On the other hand, this model was better than those obtained with Dragon software (Constitutional, Galvez topological charges indices and BCUT) using the same number of variables. This approach proved to be a very good method to assess acute aquatic toxicity of these king of compounds, which could be applied to other series of substances.

SNAP, a NO donor, induces cortical neuron death by a mechanism in which the caspase pathway is implicated

In this paper, we present data which demonstrate that, in cortical neurons, SNAP induces loss in cell viability as evaluated by the XTT test. This cell death started at 250 microM SNAP when the treatment was performed in a serum-free medium and at 10 microM when the treatment was given in the presence of serum. This death was mediated, at least in part, by an apoptotic mechanism detected by flow cytometry and DNA fractionation. The highest SNAP concentrations induced a dual behavior on caspase-3 activity. Concentrations of 250 microM in the absence of serum and 10 microM to 300 microM in the presence of serum produced caspase-3 activation. This indicates that NO induces neuronal death by an apoptotic mechanism in which the caspase pathway is implicated. Higher SNAP concentrations (500 microM to 1 mM) diminished the caspase-3 activity to levels similar or even lower than control values. This profile was observed in the absence as well as in the presence of serum in the medium. The caspase-3 inhibition mediated by the highest SNAP concentrations did not imply NO cellular protection since the caspase-3 inhibition mediated by these SNAP concentrations neither correlated with cellular viability nor with cellular apoptosis. The possible mechanism of caspase-3 inhibition at the highest SNAP concentrations used is discussed.

Nitric oxide donors induce calcium-mobilisation from internal stores but do not stimulate catecholamine secretion by bovine chromaffin cells in resting conditions

The potential role of nitric oxide (NO) donors and peroxynitrites on both basal catecholamine (CA) secretion and modulation of calcium levels has been investigated in primary cultures of bovine chromaffin cells. NO donors did not modulate catecholamine secretion, while peroxynitrites induced a time dose-dependent increase in basal CA secretion. Two facts may explain the lack of these compounds on basal CA secretion. NO donors induce, on the one hand, an increase in intracellular calcium levels by depletion of internal IP3-stores from endoplasmic reticulum. On the other hand, a small calcium influx through N-type voltage-dependent calcium channels (VDCC), which seem not to be coupled to exocytosis of adrenaline and noradrenaline in chromaffin cells. Both effects, calcium-mobilisation from internal stores and calcium entry through N-type VDCC are mediated by cGMP synthesis. In contrast, peroxynitrites induce an increase in basal CA secretion by both a decrease of intracellular catecholamine content and a toxic effect on cellular membrane. All these results, taken together, could explain contradictory results in the literature on the role of NO on basal catecholamine secretion and on modulation of intracellular calcium in chromaffin cells.

Geometry, topology, and atom-weights assembly descriptors to predicting A1 adenosine receptors agonists

The GEometry, Topology, and Atom-Weights AssemblY (GETAWAY) approach has been applied to the study of the A1 adenosine receptors agonist effect of 32 adenosine analogues: N6-arylcarbamoyl, 2-arylalkynyl-N6-arylcarbamoyl, and N6-carboxamido derivatives. A model, able to describe more than 77% of the variance in the experimental activity, was developed with the use of the above mentioned approach. Five different approaches (Topological, Galvez Topological Charges indexes, Randic Molecular Profiles, Geometrical, and WHIM descriptors) failed to give satisfactory models (R2=0.70) for this property with the same number of variables in the equation. Although statistically significant models were derived containing descriptors other than GETAWAY, the best fitted out model was still found with these descriptors.

Quantitative structure–activity relationship to predict differential inhibition of aldose reductase by flavonoid compounds

Inhibitory activity against aldose reductase enzyme of flavonoid derivatives were modelled using 11 kinds of molecular descriptors from Dragon software. Model with four Galvez Charge Indices described 67% of data variance and overtaken other models using the same number of variables. Galvez indices showed to contain important information on the relationship between the inhibitor structures and its activity by describing the molecular topology and charge transfer through the molecule. In addition, artificial neural networks were trained using charge indices from the linear models but the obtaining networks overfitted the data having low predictive power.

Stimulation of Bacteriocin Production by Dialyzed Culture Media from Different Lactic Acid Bacteria

The cross-effects of dialyzed postincubates (with a cut-off at 1000 Da) on the biomass and bacteriocin production of six strains of lactic acid bacteria were studied, and a predominance of stimulating responses was found, the characteristics of which suggested merely nutritional effects or the presence of precursor fragments of the bacteriocins. Additionally, cluster analysis of the detected responses provides an approach to define groups of highly compatible (potential consortia) or doubtfully compatible strains of lactic acid bacteria. Such a definition, which does not claim taxonomic value, has practical interest, however, in cases (e.g., silage production) in which it is convenient to use mixed inocula including strains able to establish positive interactions.

SNAP, a NO donor, induces cellular protection only when cortical neurons are submitted to some aggression process

Nitric oxide is a versatile molecule, which plays important physiological and pathological roles. Its protective and toxic actions have been already evidenced in several cell types. However, the protective effect in cortical neurons remains elusive. In this work, we demonstrate that the NO-donor SNAP may induce both neuroprotection and neurotoxicity in this sort of cells. The protective effect of NO was evidenced when cortical neurons were exposed to deleterious conditions, such as serum deprivation. Serum deprivation induces apoptotic cortical neuron death through a caspase-dependent mechanism. Under these conditions, SNAP was able to oppose cell death through both caspase-3 inhibition and/or increase of antiapoptotic protein levels (Bcl-2 and Bcl-x(L)). On the other hand, in a normally serum-supplemented medium, high dose of SNAP behaves as a neurotoxic agent, through a mechanism which involves caspase-3 activation.

A radial distribution function approach to predict A2B agonist effect of adenosine analogues

The radial distribution function (RDF) approach has been applied to the study of the A(2B) agonist effect of a set of 89 adenosine analogues reported with this activity. A model able to describe more than 70% of the variance in the experimental activity was developed with the use of the mentioned approach. In contrast, none of the eleven different approaches including the use of Constitutional, Topological, Molecular walk count, BCUT, Galvez topological charge indices, 2D autocorrelations, Randić molecular profiles, Geometrical, 3D Morse, WHIM and GETAWAY descriptors was able to explain more than 47% of the variance in the mentioned property with the same number of descriptors.

A TOPS-MODE approach to predict adenosine kinase inhibition

The TOPological Sub-Structural Molecular Design (TOPS-MODE) approach has been applied to the study of the adenosine kinase inhibitory activity of pyrrolo[2,3-d]pyrimidine nucleoside analogues. A model capable of describing around 77% of the variance in the experimental activity of 32 analogues of these compounds was developed with the use of the mentioned approach. In contrast, no one of nine different approaches, including the use of Constitutional, Topological, BCUT, 2D autocorrelations, geometrical, RDF, 3D Morse, WHIM, and GETAWAY descriptors were able to explain more than 70% of the variance in the mentioned property with the same number of descriptors. Although, statistically significant models were derived containing other descriptors than spectral moments still the best one fitted out model was find with these variables.

Effects of Aeration on Growth and on Production of Bacteriocins and Other Metabolites in Cultures of Eight Strains of Lactic Acid Bacteria

In general, it is accepted that the production of bacteriocins in lactic acid bacteria cultures implies moderately to highly restrictive conditions regarding the availability of oxygen. However, the situation appears to be more complex, probably owing to the facultative anaerobic character of these microorganisms. By studying the culture of eight strains of lactic acid bacteria carried out in vessels with different loads of medium within an interval that determines linearly the minimum availability of oxygen, the existence of three types of behavior was highlighted: production increases (1) with the availability of oxygen, (2) with the restriction of this availability, and (3) toward both extremes of these conditions, diminishing in intermediate situations. These behaviors affected not only the production of bacteriocins, but also their metabolic character (in the Luedeking and Piret sense), as well as the production of other characteristic metabolites, such as lactic acid, acetic acid, and ethanol.

QSPR calculation of normal boiling points of organic molecules based on the use of correlation weighting of atomic orbitals with extended connectivity of zero- and first-order graphs of atomic orbitals

We report the results of a calculation of the normal boiling points of a representative set of 200 organic molecules through the application of QSPR theory. For this purpose we have used a particular set of flexible molecular descriptors, the so called Correlation Weighting of Atomic Orbitals with Extended Connectivity of Zero- and First-Order Graphs of Atomic Orbitals. Although in general the results show suitable behavior to predict this physical chemistry property, the existence of some deviant behaviors points to a need to complement this index with some other sort of molecular descriptors. Some possible extensions of this study are discussed.

Peptones from autohydrolysed fish viscera for nisin and pediocin production

Various peptones obtained from hydrolysed visceral homogenates of four fishery residues showed their suitability for promoting the growth of lactic acid bacteria, micro-organisms with particularly complex requirements regarding peptidic nutrients. The assay of several treatments with two bacterial species, producers of the two main bacteriocins (nisin and pediocin) demostrated that optimum conditions only imply a brief autohydrolysis at natural pH and room temperature, with subsequent steam-flow stabilisation. Later kinetic analysis of the cultures of both bacteria in the best media provided parameters which, for production of both biomass and bacteriocins (the latter behaved in the majority of cases as a mixed metabolite), indicate comparable or superior results to those found in costly commercial media, specifically recommended for culture of lactic acid bacteria.

Therapeutic efficacy and safety of multiple intravenous infusions of infliximab in refractory ankylosing spondylitis patients with axial involvement

OBJECTIVE

To evaluate the clinical response and safety profile of infliximab in refractory ankylosing spondylitis patients.

METHODS

Patients with active ankylosing spondylitis, despite methotrexate therapy, were included in an open-label, single-centre study. Patients were given 3-5 mg/kg infliximab infusions at Weeks 0, 2, 6, and q8 etc up to Week 30, together with methotrexate at the dosage taken prior to study inclusion, and were followed-up for a 34-week period.

RESULTS

Nine patients with mean age 43 years and mean disease duration 7 years, diagnosed with pure axial ankylosing spondylitis were included. Erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), duration of morning stiffness, physician's global assessment of disease activity (PhGADA), visual analogue scale (VAS) pain, enthesis index, occiput-to-wall test, Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), and Bath Ankylosing Spondylitis Functional Index (BASFI) significantly improved by Week 6. No adverse events related with the drug were recorded during the 34-week follow-up period.

CONCLUSION

Efficacy results are similar to those previously published. No adverse events were seen during therapy, and antinuclear antibody profiles were negative. The association of methotrexate with infliximab can improve the safety profile.