Idalia Garza-Veloz

Analyses of chondrogenic induction of adipose mesenchymal stem cells by combined co-stimulation mediated by adenoviral gene transfer.

IntroductionAdipose-derived stem cells (ASCs) have the potential to differentiate into cartilage under stimulation with some reported growth and transcriptional factors, which may constitute an alternative for cartilage replacement approaches. In this study, we analyzed the in vitro chondrogenesis of ASCs transduced with adenoviral vectors encoding insulin-like growth factor-1 (IGF-1), transforming growth factor beta-1 (TGF-β1), fibroblast growth factor-2 (FGF-2), and sex-determining region Y-box 9 (SOX9) either alone or in combinations.MethodsAggregate cultures of characterized ovine ASCs were transduced with 100 multiplicity of infections of Ad.IGF-1, Ad.TGF-β1, Ad.FGF-2, and Ad.SOX9 alone or in combination. These were harvested at various time points for detection of cartilage-specific genes expression by quantitative real-time PCR or after 14 and 28 days for histologic and biochemical analyses detecting proteoglycans, collagens (II, I and X), and total sulfated glycosaminoglycan and collagen content, respectively.ResultsExpression analyses showed that co-expression of IGF-1 and FGF-2 resulted in higher significant expression levels of aggrecan, biglycan, cartilage matrix, proteoglycan, and collagen II (all P ≤0.001 at 28 days). Aggregates co-transduced with Ad.IGF-1/Ad.FGF-2 showed a selective expression of proteoglycans and collagen II, with limited expression of collagens I and × demonstrated by histological analyses, and had significantly greater glycosaminoglycan and collagen production than the positive control (P ≤0.001). Western blot analyses for this combination also demonstrated increased expression of collagen II, while expression of collagens I and × was undetectable and limited, respectively.ConclusionCombined overexpression of IGF-1/FGF-2 within ASCs enhances their chondrogenic differentiation inducing the expression of chondrogenic markers, suggesting that this combination is more beneficial than the other factors tested for the development of cell-based therapies for cartilage repair.

No association between polymorphisms/haplotypes of the vascular endothelial growth factor gene and preeclampsia

BackgroundPreeclampsia (PE) is the first worldwide cause of death in pregnant women, intra-uterine growth retardation, and fetal prematurity. Some vascular endothelial grown factor gene (VEGF) polymorphisms have been associated to PE and other pregnancy disturbances. We evaluated the associations between VEGF genotypes/haplotypes and PE in Mexican women.Methods164 pregnant women were enrolled in a case-control study (78 cases and 86 normotensive pregnant controls). The rs699947 (-2578C/A), rs1570360 (-1154G/A), rs2010963 (+405G/C), and rs25648 (-7C/T), VEGF variants were discriminated using Polymerase Chain Reaction - Restriction Fragment Length Polymorphism (PCR-RFLP) methods or Taqman single nucleotide polymorphism (SNP) assays.ResultsThe proportions of the minor allele for rs699947, rs1570360, rs2010963, and rs25648 VEGF SNPs were 0.33, 0.2, 0.39, and 0.17 in controls, and 0.39, 0.23, 0.41, and 0.15 in cases, respectively (P values > 0.05). The most frequent haplotypes of rs699947, rs1570360, rs2010963, and rs25648 VEGF SNPs, were C-G-C-C and C-G-G-C with frequencies of 0.39, 0.21 in cases and 0.37, 0.25 in controls, respectively (P values > 0.05)ConclusionThere was no evidence of an association between VEGF alleles, genotypes, or haplotypes frequencies and PE in our study.

CYP2D6 gene polymorphisms and predicted phenotypes in eight indigenous groups from northwestern Mexico

AIM Polymorphisms in CYP2D6 impact the interindividual and interethnic variability of drug efficiency; therefore, we determined the CYP2D6 allele distribution in eight Amerindian groups from northwestern Mexico and compared them with the frequencies in Mexican Mestizos. MATERIALS & METHODS A total of 508 Amerindians were studied. Genotyping of CYP2D6*5 and multiplication alleles was performed by long-range PCR, while CYP2D6*2, *3, *4, *6, *10, *17, *29, *35, *41 and copy number were evaluated by real-time PCR. RESULTS The most frequent alleles were CYP2D6*2 (0.05-0.28), CYP2D6*4 (0.003-0.21) and multiplications (0.043-0.107). CYP2D6*5, *6, * 10 and *41 were not observed in the majority of Amerindians, and CYP2D6*3, *17, *35 and *29 were not detected. The poor metabolizer genotype ( *4/*5) was lower (0.2%) in Amerindians than in Mestizos (5%); conversely, the ultrarapid metabolizer genotype was higher (12.6%) in indigenous groups than in Mestizos (7%). CONCLUSION Our data show a lower frequency of CYP2D6 inactive alleles and a higher frequency of duplication/multiplication of CYP2D6 active alleles in indigenous populations that in Mestizos. Original submitted 14 August 2013; Revision submitted 7 October 2013.

Circulating microRNA expression profile in B-cell acute lymphoblastic leukemia

BACKGROUND Acute lymphoblastic leukemia (ALL) is a highly diverse disease characterized by cytogenetic and molecular abnormalities, including altered microRNA (miRNA) expression signatures. AIM We perform and validate a plasma miRNA expression profiling to identify potential miRNA involved in leukemogenesis METHODS MiRNA expression profiling assay was realized in 39 B-ALL and 7 normal control plasma samples using TaqMan Low Density Array (TLDA) plates on Applied Biosystems 7900 HT Fast Real-Time PCR System. MiRNA validation was done for six miRNA differentially expressed by quantitative real-time PCR. RESULTS Seventy-seven circulating miRNA differentially expressed: hsa-miR-511, -222, and -34a were overexpressed, whereas hsa-miR-199a-3p, -223, -221, and -26a were underexpressed (p values < 0.005 for both sets). According to operating characteristic curve analysis, hsa-miR-511 was the most valuable biomarker for distinguishing B-ALL from normal controls, with an area under curve value of 1 and 100% for sensitivity, and specificity respectively. CONCLUSIONS Measuring circulating levels of specific miRNA implicated in regulation of cell differentiation and/or cell proliferation such as hsa-miRNA-511, offers high sensitivity and specificity in B-ALL detection and may be potentially useful for detection of disease progression, as indicator of therapeutic response, and in the assessment of biological and/or therapeutic targets for patients with B-ALL.

Positive association between vascular endothelial growth factor (VEGF) -2578 C/A variant and prostate cancer

BACKGROUND Vascular endothelial growth factor (VEGF) gene is an important angiogenesis regulator related to cancer development and progression. We evaluated the association between -2578 C/A (rs699947) VEGF polymorphism and PCa in Mexican subjects, to contribute to knowledge of VEGF role in genetic epidemiology of prostate cancer (PCa). OBJECTIVE The aim of this study was to evaluate the association between -2578 C/A VEGF variant and PCa in Mexican population. METHODS A total of 249 men (77 PCa cases and 172 controls) from the Northwestern region of Mexico were screened for the -2578 C/A VEGF variant. The polymorphism was determined by polymerase chain reaction-based restriction analysis. RESULTS Genotype frequencies for C/C, C/A, and A/A, were 0.48, 0.49, 0.03 for cases and 0.41, 0.45, 0.14 for controls respectively. Genotype A/A of -2578 VEGF variant reduces the risk of PCa in an 84% among studied population (Odds Ratio 0.16; 95% CI: 0.04-0.71, P=0.007). C/C carriers showed an increased PCa risk of 6.1 times among the study population. CONCLUSIONS Inheritance of -2578 A/A genotype of VEGF gene may modify PCa susceptibility risk in Mexican population.

Expression levels of seven candidate genes in human peripheral blood mononuclear cells and their association with preeclampsia

Objective: To evaluate the peripheral blood mononuclear cell (PBMC) expression levels of hemeoxygenase 1 (HMOX-1), superoxide dismutase 1 (SOD-1), vascular endothelial growth factor A (VEGF-A), transforming growth factor beta 1 (TGF-β1), interleukin (IL)-6, IL-15 and AdipoQ genes to study their association with preeclampsia (PE). Methods: A total of 177 pregnant women were recruited: 108 cases and 69 controls. Quantification of gene expression was measured by quantitative real-time polymerase chain reaction (PCR) using TaqMan probes. Results: Underexpression of VEGF-A and TGF-β1 was a constant in most of the cases (80.91% and 76.36%, respectively) and their expression was associated with onset and/or severity of disease (p values < 0.05). IL-6, IL-15 and AdipoQ, showed low or no expression in PBMC samples evaluated. Conclusion: PBMC underexpression of VEGF-A and TGF-β1 is a hallmark of PE in the study population.

Plasma cancer biomarker multiplex screening and the risk of subsequent preeclampsia

a Molecular Medicine Laboratory, Unidad Academica de Medicina Humana y Ciencias de la Salud, Carretera Zacatecas-Guadalajara Km.6, Ejido la Escondida, Zacatecas, Mexico b Biomedical Research Laboratory, Unidad Academica de Odontologia, Carretera Zacatecas-Guadalajara Km.6, Ejido la Escondida, Zacatecas, Mexico c Hospital de la Mujer Zacatecana, Servicios de Salud de Zacatecas, Av. Programacion y Presupuesto 7, Zona Industrial, Zacatecas, Mexico d School of Medicine, University of Colima, Av. Universidad 333, Colonia las viboras, Colima, Mexico e Instituto Estatal de Cancerologia, Servicios de Salud del Estado de Colima, Mexico

Doppler ultrasound evaluation in preeclampsia.

BackgroundWorldwide preeclampsia (PE) is the leading cause of maternal death and affects 5 to 8% of pregnant women. PE is characterized by elevated blood pressure and proteinuria. Doppler Ultrasound (US) evaluation has been considered a useful method for prediction of PE; however, there is no complete data about the most frequently altered US parameters in the pathology. The aim of this study was to evaluate the uterine, umbilical, and the middle cerebral arteries using Doppler US parameters [resistance index (RI), pulsatility index (PI), notch (N), systolic peak (SP) and their combinations] in pregnant women, in order to make a global evaluation of hemodynamic repercussion caused by the established PE.ResultsA total of 102 pregnant Mexican women (65 PE women and 37 normotensive women) were recruited in a cases and controls study. Blood velocity waveforms from uterine, umbilical, and middle cerebral arteries, in pregnancies from 24 to 37 weeks of gestation were recorded by trans-abdominal examination with a Toshiba Ultrasound Power Vision 6000 SSA-370A, with a 3.5 MHz convex transducer. Abnormal general Doppler US profile showed a positive association with PE [odds ratio (OR) = 2.93, 95% confidence interval (CI) = 1.2 - 7.3, P = 0.021)], and a specificity and predictive positive value of 89.2% and 88.6%, respectively. Other parameters like N presence, RI and PI of umbilical artery, as well as the PI of middle cerebral artery, showed differences between groups (P values < 0.05).ConclusionGeneral Doppler US result, as well as N from uterine vessel, RI from umbilical artery, and PI from umbilical and middle cerebral arteries in their individual form, may be considered as tools to determine hemodynamic repercussion caused by PE.

A comparison of back propagation and Generalized Regression Neural Networks performance in neutron spectrometry.

The process of unfolding the neutron energy spectrum has been subject of research for many years. Monte Carlo, iterative methods, the bayesian theory, the principle of maximum entropy are some of the methods used. The drawbacks associated with traditional unfolding procedures have motivated the research of complementary approaches. Back Propagation Neural Networks (BPNN), have been applied with success in neutron spectrometry and dosimetry domains, however, the structure and learning parameters are factors that highly impact in the networks performance. In ANN domain, Generalized Regression Neural Network (GRNN) is one of the simplest neural networks in term of network architecture and learning algorithm. The learning is instantaneous, requiring no time for training. Opposite to BPNN, a GRNN would be formed instantly with just a 1-pass training on the development data. In the network development phase, the only hurdle is to optimize the hyper-parameter, which is known as sigma, governing the smoothness of the network. The aim of this work was to compare the performance of BPNN and GRNN in the solution of the neutron spectrometry problem. From results obtained it can be observed that despite the very similar results, GRNN performs better than BPNN.

Multivariate Feature Selection of Image Descriptors Data for Breast Cancer with Computer-Assisted Diagnosis

Breast cancer is an important global health problem, and the most common type of cancer among women. Late diagnosis significantly decreases the survival rate of the patient; however, using mammography for early detection has been demonstrated to be a very important tool increasing the survival rate. The purpose of this paper is to obtain a multivariate model to classify benign and malignant tumor lesions using a computer-assisted diagnosis with a genetic algorithm in training and test datasets from mammography image features. A multivariate search was conducted to obtain predictive models with different approaches, in order to compare and validate results. The multivariate models were constructed using: Random Forest, Nearest centroid, and K-Nearest Neighbor (K-NN) strategies as cost function in a genetic algorithm applied to the features in the BCDR public databases. Results suggest that the two texture descriptor features obtained in the multivariate model have a similar or better prediction capability to classify the data outcome compared with the multivariate model composed of all the features, according to their fitness value. This model can help to reduce the workload of radiologists and present a second opinion in the classification of tumor lesions.