RESUMO
A biomarker can be a metabolite, coming from a metabolic pathway or cell process, which might be employed in the diagnostic of diseases, predict patient response towards chemical therapies and/or monitor disease recurrences. Biomarkers, e.g. aldehydes or hydrocarbons, are often identified from different body fluids such as blood, urine, serum, saliva or from various tissues samples, and their concentration can vary from one sample to the other. However, the detection and the action of these biomarkers for diseases is a complicated process. Cancer is one of the main cause of death worldwide. The main characteristic of cancerous tumor is the uncontrolled growing of cells inside the organism. Likely, these uncontrolled growths are as consequence changes in the metabolism that could be analytically monitored. Depending on where the cancer cells are located, they provide different characteristics profiles. These profiles as fingerprints are used for differentiation in a comparison to normal cells. This critical study aimed at highlighting the latest progress in this area, especially in the employment of gas chromatography for the monitoring of volatile organic compounds (VOCs) and the identification of possible molecules used as biomarkers for cancer therapy.
Assuntos
Biomarcadores Tumorais/metabolismo , Cromatografia Gasosa-Espectrometria de Massas/métodos , Metabolômica , Neoplasias/metabolismo , Humanos , Neoplasias/patologia , Prognóstico , Compostos Orgânicos Voláteis/metabolismoRESUMO
Smelling is one of the five senses, which plays an important role in our everyday lives. Volatile compounds are, for example, characteristics of food where some of them can be perceivable by humans because of their aroma. They have a great influence on the decision making of consumers when they choose to use a product or not. In the case where a product has an offensive and strong aroma, many consumers might not appreciate it. On the contrary, soft and fresh natural aromas definitely increase the acceptance of a given product. These properties can drastically influence the economy; thus, it has been of great importance to manufacturers that the aroma of their food product is characterized by analytical means to provide a basis for further optimization processes. A lot of research has been devoted to this domain in order to link the quality of, e.g., a food to its aroma. By knowing the aromatic profile of a food, one can understand the nature of a given product leading to developing new products, which are more acceptable by consumers. There are two ways to analyze volatiles: one is to use human senses and/or sensory instruments, and the other is based on advanced analytical techniques. This work focuses on the latter. Although requirements are simple, low-cost technology is an attractive research target in this domain; most of the data are generated with very high-resolution analytical instruments. Such data gathered based on different analytical instruments normally have broad, overlapping sensitivity profiles and require substantial data analysis. In this review, we have addressed not only the question of the application of chemometrics for aroma analysis but also of the use of different analytical instruments in this field, highlighting the research needed for future focus.
Assuntos
Técnicas de Química Analítica/métodos , Informática/métodos , Compostos Orgânicos Voláteis/análise , Métodos Analíticos de Preparação de Amostras , Humanos , Metabolômica , Análise Multivariada , Compostos Orgânicos Voláteis/química , Compostos Orgânicos Voláteis/metabolismoRESUMO
ABSTRACT Bioflavonoid-containing diets have been reported to be beneficial in diabetes. In the current study, the effect of Biochanin A (BCA) on blood glucose, antioxidant enzyme activities and oxidative stress markers in diabetic rats were investigated. 30 male Wistar rats were divided into five groups. Two of them were selected as control; group1: control (receiving 0.5%DMSO), and group2: Control+BCA (receiving 10 mg/kg.bw BCA). Diabetes was induced in other rats with injection of (55 mg/kg.bw) streptozotocin; group3: diabetic control (receiving 0.5%DMSO), groups 4 and 5 were treated with 10 and 15 mg/kg.bw BCA respectively. After 6 weeks the following results were obtained. Fasting blood glucose (FBG), Triglyceride (TG), total cholesterol (TC), low density lipoprotein cholesterol (LDL-C), very low density lipoprotein cholesterol (VLDL-C) and malondialdehyde (MDA) levels significantly increased and body weight, high density lipoprotein cholesterol (HDL-C), superoxide dismutase (SOD) and catalase (CAT) activity and total antioxidant status (TAS) significantly decreased in diabetic rats as compared to control rats. Oral administration of BCA in 10 and 15 mg/kg.bw, FBG, TG, TC, LDL-C, VLDL-C were decreased significantly in all treated rats. MDA was decreased in all treated rats but it was significant just in 15 mg/kg.bw BCA. HDL, CAT, SOD, and TAS were significantly increased in treated group with 15 mg/kg.bw. The obtained results indicated hypoglycemic and hypolipidemic effect of BCA. Also BCA reduced oxidative stress in diabetic rats.
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Previous studies suggested a significant relationship between alpha- amylase and caries formation. This study was implemented in order to investigate the interrelation between level of salivary and serum alpha- amylase, and dental caries. Methods: In this cross-sectional study, un-stimulated whole saliva and serum samples were collected from 118 high school students who were divided into four groups: caries free females (N = 28), caries active females (N = 35), caries free males (N = 28) and caries active males (N =27). Mean levels of salivary and serum alpha-amylase was evaluated by spectrophotometric methods to assayenzyme kinetics. Data were analyzed using studentst-tests and chi-square tests. Results: Salivary alpha amylase was significantly higher in caries active groups as compared to caries free groups (P = 0.002). The mean salivary alpha -amylase was significantly higherin caries active males (P = 0.002). Also, serum alpha-amylase was significantly higher in caries active groups as compared to caries free groups (P = 0.001). In bothsexes the mean serum alpha- amylase levels were statistically significant higher in caries active compared to caries free groups (P = 0.02 and 0.01 respectively). Conclusion: A significant association was found between salivary and serum alpha- amylase and dental caries in adolescents. More research to demonstrate there al relation between alpha amylase and dental caries is recommended...
Objetivo: Alguns estudos anteriores sugeriram uma relação significativa entre a alfa-amilase e a formação de cárie. Este estudo foi realizado com o objetivo de investigar a interrelação entre o nível de alfa-amilase na saliva e no soro e a cárie. Material e Métodos: Neste estudo transversal, amostras de saliva não-estimulada e soro foram coletadas de 118 estudantes do ensino médio que foram divididos em quatro grupos: mulheres livres de cárie (n = 28), mulheres com cárie ativa (n = 35), homens livres de cárie (n = 28) e homens com cárie ativa (n = 27). O nível de alfa-amilase da saliva e soro foi avaliado por espectrofotometria para ensaios de cinética enzimática. Os dados foram analisados pelos testes te Qui-quadrado. Resultados: A alfa-amilase salivar foi significativamente maior nos grupos com cárie ativa em comparação com os grupos livres de cárie (p = 0,002). A alfa amilase salivar foi significativamente maior nos homens com cáries ativa (p = 0,002). Além disso, a alfa amilase sérica foi significativamente maior nos grupos de cárie ativa, em comparação com os grupos livres de cárie(p = 0,001). Em ambos os sexos a média da alfa-amilase sérica foi estatisticamente superior nos grupos de cárie ativa, em comparação com livres de cárie (p = 0,02 e 0,01, respectivamente). Conclusão: Foi encontrada uma associação significativa entre a alfa-amilase salivar e sérica em indivíduos com a cárie dentária na adolescência. São recomendadas mais investigações para demonstrar real relação entre os níveis de alfa-amilase e cárie dentária...
Assuntos
Humanos , alfa-Amilases , Cárie Dentária , Saliva , SoroRESUMO
In order to minimize the high attrition rate that usually characterizes drug research and development projects, current medicinal chemists aim to characterize both pharmacological and ADME profiles at the beginning of drug R&D initiatives. Thus, the development of ADME High-Throughput Screening in vitro and in silico ADME models has become an important growing research area. Here we present new linear and non-linear predictive QSPR models to predict the human intestinal absorption rate, which are derived from a medium sized, balanced and diverse training set of organic compounds. The structure-property relationships so obtained involve only 4 molecular descriptors, and display an excellent ratio of number of cases to number of descriptors. Their adjustment of the training set data together with the performance achieved during the internal and external validation procedures are comparable to previously reported modeling efforts.
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Absorção Intestinal , Dinâmica não Linear , Preparações Farmacêuticas/metabolismo , Relação Quantitativa Estrutura-Atividade , Humanos , Modelos Lineares , Conformação Molecular , Permeabilidade , Preparações Farmacêuticas/química , Probabilidade , TermodinâmicaRESUMO
The objective of the article was to perform a predictive analysis, based on quantitative structure-property relationships, of the dissociation constants (pK(a)) of different medicinal compounds (e.g., salicylic acid, salbutamol, lidocaine). Given the importance of this property in medicinal chemistry, it is of interest to develop theoretical methods for its prediction. The descriptors selection from a pool containing more than a thousand geometrical, topological, quantum-mechanical, and electronic types of descriptors was performed using the enhanced replacement method. Genetic algorithm and the replacement method (RM) techniques were used as reference points. A new methodology for the selection of the optimal number of descriptors to include in a model was presented and successfully used, showing that the best model should contain four descriptors. The best quantitative structure-property relationships linear model constructed using 62 molecular structures not previously used in this type of quantitative structure-property study showed good predictive attributes. The root mean squared error of the 26 molecules test set was 0.5600. The analysis of the quantitative structure-property relationships model suggests that the dissociation constants depend significantly on the number of acceptor atoms for H-bonds and on the number of carboxylic acids present in the molecules.
Assuntos
Preparações Farmacêuticas/química , Relação Quantitativa Estrutura-Atividade , Albuterol/química , Algoritmos , Ligação de Hidrogênio , Cinética , Lidocaína/química , Modelos Moleculares , Ácido Salicílico/químicaRESUMO
Leishmaniasis is a neglected disease transmitted in many tropical and sub-tropical countries, with few studies devoted to its treatment. In this work, the activities of two antileishmanial compound classes were modeled using Dragon descriptors, and multiple linear (MLR) and support vector machines (SVM) as linear and nonlinear regression methods, respectively. Both models were highly predictive, with calibration, leave-one-out validation and external validation R(2) of 0.79, 0.72 and 0.78, respectively, for the MLR-based model, improving significantly to 0.98, 0.93 and 0.90 when using SVM modeling. Therefore, novel compounds were proposed using the QSAR models built by combining the substructures of the main active compounds of both classes. The most promising structures were docked into the active site of Leishmania donovani α,ß tubulin (Ld-Tub), demonstrating the high affinity of some new structures when compared to existing antileishmanial compounds.
Assuntos
Antiprotozoários/química , Antiprotozoários/farmacologia , Leishmania/efeitos dos fármacos , Sulfetos/química , Sulfetos/farmacologia , Sulfonamidas/química , Sulfonamidas/farmacologia , Sequência de Aminoácidos , Animais , Leishmania donovani/química , Leishmania donovani/efeitos dos fármacos , Modelos Moleculares , Dados de Sequência Molecular , Relação Quantitativa Estrutura-Atividade , Homologia de Sequência de AminoácidosRESUMO
We establish useful models that relate experimentally measured biological activities of compounds to their molecular structure. The pED(50) feeding inhibition on Spodoptera litura species exhibited by aurones, chromones, 3-coumarones and flavones is analyzed in this work through the hypothesis encompassed in the Quantitative Structure-Activity Relationships (QSAR) Theory. This constitutes a first necessary computationally based step during the design of more bio-friendly repellents that could lead to insights for improving the insecticidal activities of the investigated compounds. After optimizing the molecular structure of each furane and pyrane benzoderivative with the semiempirical molecular orbitals method PM3, more than a thousand of constitutional, topological, geometrical and electronic descriptors are calculated and multiparametric linear regression models are established on the antifeedant potencies. The feature selection method employed in this study is the Replacement Method, which has proven to be successful in previous analyzes. We establish the QSAR both for the complete molecular set of compounds and also for each chemical class, so that acceptably describing the variation of the inhibitory activities from the knowledge of their structure and thus achieving useful predictive results. The main interest of developing trustful QSAR models is that these enable the prediction of compounds having no experimentally measured activities for any reason. Therefore, the structure-activity relationships are further employed for investigating the antifeedant activity on previously synthesized 2-,7-substituted benzopyranes, which do not pose any measured values on the biological expression. One of them, 2-(alpha-naphtyl)-4H-1-benzopyran-4-one, results in a promising structure to be experimentally analyzed as it has predicted pED(50)=1.162.
Assuntos
Comportamento Alimentar/efeitos dos fármacos , Flavonas/química , Flavonas/farmacologia , Repelentes de Insetos/farmacologia , Spodoptera/efeitos dos fármacos , Animais , Benzofuranos/química , Benzofuranos/farmacologia , Cromonas/química , Cromonas/farmacologia , Relação Quantitativa Estrutura-AtividadeRESUMO
Several studies were conducted in past years which used the evolutionary process of Genetic Algorithms for optimizing the Support Vector Regression parameter values although, however, few of them were devoted to the simultaneously optimization of the type of kernel function involved in the established model. The present work introduces a new hybrid genetic-based Support Vector Regression approach, whose statistical quality and predictive capability is afterward analyzed and compared to other standard chemometric techniques, such as Partial Least Squares, Back-Propagation Artificial Neural Networks, and Support Vector Machines based on Cross-Validation. For this purpose, we employ a data set of experimentally determined binding affinity constants toward the benzodiazepine binding site of the GABA (A) receptor complex on 78 flavonoid ligands.
Assuntos
Inteligência Artificial , Flavonoides/química , Flavonoides/metabolismo , Genética , Relação Quantitativa Estrutura-Atividade , Receptores de GABA-A/química , Receptores de GABA-A/metabolismo , Algoritmos , Dinâmica não Linear , Ligação Proteica , Análise de RegressãoRESUMO
A spectrophotometric method for the simultaneous determination of Al(III), Co(II) and Ni(II) using Alizarin Red S as a chelating agent was developed. The parameters controlling the behavior of the system were investigated and optimum conditions were selected. The presence of non-linearities was checked using Mallows augmented partial residual plots. To take into account these non-linearities, a principal component analysis-adaptive neuro-fuzzy inference systems (PC-ANFISs) method was used for the analysis of ternary mixtures of Al(III), Co(II) and Ni(II) over the range of 0.05-0.90, 0.05-4.05 and 0.05-0.95 microg mL(-1), respectively. Absorbance data were collected between 370 and 700 nm. The method was applied to accurately and simultaneously determines the content of metal ions in several synthetic mixtures.
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Alumínio/análise , Cobalto/análise , Níquel/análise , Espectrofotometria/métodos , Água/análise , Algoritmos , Antraquinonas , Calibragem , Quelantes , Análise de Componente Principal , Sensibilidade e EspecificidadeRESUMO
Inhibition of tyrosine kinase enzyme WEE1 is an important step for the treatment of cancer. The bioactivities of a series of WEE1 inhibitors have been previously modeled through comparative molecular field analyses (CoMFA and CoMSIA), but a two-dimensional image-based quantitative structure-activity relationship approach has shown to be highly predictive for other compound classes. This method, called multivariate image analysis applied to quantitative structure-activity relationship, was applied here to derive quantitative structure-activity relationship models. Whilst the well-known bilinear and multilinear partial least squares regressions (PLS and N-PLS, respectively) correlated multivariate image analysis descriptors with the corresponding dependent variables only reasonably well, the use of wavelet and principal component ranking as variable selection methods, together with least-squares support vector machine, improved significantly the prediction statistics. These recently implemented mathematical tools, particularly novel in quantitative structure-activity relationship studies, represent an important advance for the development of more predictive quantitative structure-activity relationship models and, consequently, new drugs.