Long-term assessment of didanosine, lamivudine, and efavirenz in antiretroviral-naive patients: 3-year follow-up.

The aim of this study was to evaluate the long-term efficacy and safety of didadosine (ddI), lamivudine (3TC), and efavirenz (EFV). This was a follow-up to the VESD study, a 12-month open-label, observational, multicenter study of adult patients with HIV infection who started antiretroviral treatment with the ddI-3TC-EFV once-daily regimen. Of the 167 patients originally included, 106 patients remained on the same triple therapy at the end of the study (1 year), and they were offered an extra 24 months of follow-up; 96 were enrolled in this study (VESD-2). Seventy patients out of the initial cohort were still on the same regimen at month 36, with 97% of them with plasma viral load <50 copies /ml. An intention-to-treat analysis showed that the percentage of patients with plasma viral load <50 copies/ml was 73% at 36 months. CD4 cell counts increased 344 cells/microl over the 36 months. Safety and tolerance were good with no unexpected long-term toxicity. After 3 years of treatment with ddI-3TC-EFV, more than 40% of the patients were still receiving the initial antiretroviral therapy with sustained, durable immunovirological benefit and good acceptance. Long-term toxicity and virological failure were low.

Nevirapine vs efavirenz in virologically supressed patients: Differences in lipoprotein subclasses and inflammatory biomarkers.

Background: The interaction between lipid disturbances and inflammatory markers is not well known in patients on antiretroviral therapy (ART). As nevirapine (NVP) is associated with a better lipid profile than efavirenz (EFV), we investigated the relationships between lipid profiles, lipoprotein subclasses and inflammatory biomarkers in patients with prolonged viral suppression with either NVP or EFV and no obvious clinical inflammation. Methods: 122 clinically stable HIV-infected patients with HIV-1 RNA <20 copies longer than 6 months on NNRTI therapy were studied. 72 (59%) were on EFV and 50 (41%) on NVP. Any potentially inflammatory co-morbid diseases (concurrent viral hepatitis, diabetes, hypertension, chronic liver or renal diseases), or statin treatment, were exclusion criteria. Inflammatory biomarkers included hsCRP, LpPLA2, sCD40L, IL-6, IL-8, t-PA, MCP-1, p-selectin and VCAM-1. Lipoprotein subclass measures (VLDL, LDL, IDL and HDL particle number and size) were obtained by the use of proton nuclear magnetic resonance spectroscopy. Results: 82% were male; median age 45 years. Median CD4 count 550/μL (IQR 324). Median time since HIV diagnosis 96 months (IQR 102) and accumulated time on ART 50 months (IQR 101). Patients on NVP had higher time since HIV diagnosis (126.9 [66.7] vs 91.3 [6.6] months, p=0.008) a prolonged time on ART (89.6 [54.6] vs 62.3 [52.2] months, p=0.01) and were older (47.7 vs 40.7 years, p=0.001) than those on EFV. NVP-treated patients presented increased HDL-c (55.8 [16] vs 48.8 [10.7] mg/dL, p=0.007) and apoA1 levels (153.4 [31.9] vs 141.5 [20.5] mg/dL, p=0.02), and reduced apoB/apoA1 ratio (0.68 [0.1] vs 0.61 [0.1], p=0.003) than EFV-treated patients. No differences in inflammatory markers or lipoprotein subclasses were found between NVP and EFV. In patients with extreme lipid values (less favorable: 75th percentiles of LDL, small/dense LDLp and small HDLp, or more favorable: HDL p75 and apoB/apoA1 ratio p25), no consistent differences in inflammatory biomarkers were found. Conclusions: Patients with prolonged viral suppression on NVP present significantly higher HDL and apoA1 levels and reduced apoB/apoA1 ratios than those on EFV, but no differences were found in lipoprotein particles nor inflammatory biomarkers. Relationships between lipid parameters and inflammatory biomarkers in NNRTItreated patients are complex and do not show a linear relationship in this study.

Clinical and Virological Efficacy of Etravirine Plus Two Active Nucleos(t)ide Analogs in an Heterogeneous HIV-Infected Population.

Etravirine (ETV) is recommended in combination with a boosted protease inhibitor plus an optimized background regimen for salvage therapy, but there is limited experience with its use in combination with two nucleos(t)ide reverse-transcriptase inhibitors (NRTIs). This multicenter study aimed to assess the efficacy of this combination in two scenarios: group A) subjects without virologic failure on or no experience with non-nucleoside reverse-transcriptase inhibitors (NNRTIs) switched due to adverse events and group B) subjects switched after a virologic failure on an efavirenz- or nevirapine-based regimen. The primary endpoint was efficacy at 52 weeks analysed by intention-to-treat. Virologic failure was defined as the inability to suppress plasma HIV-RNA to <50 copies/mL after 24 weeks on treatment, or a confirmed viral load >200 copies/mL in patients who had previously achieved a viral suppression or had an undetectable viral load at inclusion. Two hundred eighty seven patients were included. Treatment efficacy rates in group A and B were 88.0% (CI95, 83.9-92.1%) and 77.4% (CI95, 65.0-89.7%), respectively; the rates reached 97.2% (CI95, 95.1-99.3%) and 90.5% (CI95, 81.7-99.3), by on-treatment analysis. The once-a-day ETV treatment was as effective as the twice daily dosing regimen. Grade 1-2 adverse events were observed motivating a treatment switch in 4.2% of the subjects. In conclusion, ETV (once- or twice daily) plus two analogs is a suitable, well-tolerated combination both as a switching strategy and after failure with first generation NNRTIs, ensuring full drug activity. TRIAL REGISTRATION ClinicalTrials.gov NCT01437241.

ACTG-HIV symptoms changes in patients switched to RPV/FTC/TDF due to previous intolerance to CART. Interim analysis of the PRO-STR study.

INTRODUCTION Tolerability and convenience are crucial aspects for the long-term success of combined antiretroviral therapy (cART). The aim of this study was to investigate the impact in routine clinical practice of switching to the single tablet regimen (STR) RPV/FTC/TDF in patients with intolerance to previous cART, in terms of patients' well-being, assessed by several validated measures. METHODS Prospective, multicenter study. Adult HIV-infected patients with viral load under 1.000 copies/mL while receiving a stable ART for at least the last three months and switched to RPV/FTC/TDF due to intolerance of previous regimen, were included. Analyses were performed by ITT. Presence/magnitude of symptoms (ACTG-HIV Symptom Index), quality of life (EQ-5D, EUROQoL & MOS-HIV), adherence (SMAQ), preference of treatment and perceived ease of medication (ESTAR) through 48 weeks were performed. RESULTS Interim analysis of 125 patients with 16 weeks of follow up was performed. 100 (80%) were male, mean age 46 years. Mean CD4 at baseline was 629.5±307.29 and 123 (98.4%) had viral load <50 copies/mL; 15% were HCV co-infected. Ninety two (73.6%) patients switched from a NNRTI (84.8% from EFV/FTC/TDF) and 33 (26.4%) from a PI/r. The most frequent reasons for switching were psychiatric disorders (51.2%), CNS adverse events (40.8%), gastrointestinal (19.2%) and metabolic disorders (19.2%). At the time of this analysis (week 16), four patients (3.2%) discontinued treatment: one due to adverse events, two virologic failures and one with no data. A total of 104 patients (83.2%) were virologically suppressed (<50 copies/mL). The average degree of discomfort in the ACTG-HIV Symptom Index significantly decreased from baseline (21±15.55) to week 4 (10.89±12.36) & week 16 (10.81±12.62), p<0.001. In all the patients, quality of life tools showed a significant benefit in well-being of the patients (Table 1). Adherence to therapy significantly and progressively increased (SMAQ) from baseline (54.4%) to week 4 (68%), p<0.001 and to week 16 (72.0%), p<0.001. CONCLUSIONS Switching to RPV/FTC/TDF from another ARV regimen due to toxicity, significantly improved the quality of life of HIV-infected patients, both in mental and physical components, and improved adherence to therapy while maintaining a good immune and virological response.

Lipid changes in HIV-patients switching to the coformulated single tablet FTC/RPV/TDF (Eviplera®). Efficacy and safety analysis. GeSida Study 8114.

INTRODUCTION Rilpivirine (RPV) has a better lipid profile than efavirenz (EFV) in naïve patients (1). Switching to RPV may be convenient for many patients, while maintaining a good immunovirological control (2). The aim of this study was to analyze lipid changes in HIV-patients at 24 weeks after switching to Eviplera® (emtricitabine/RPV/tenofovir disoproxil fumarate [FTC/RPV/TDF]). MATERIALS AND METHODS Retrospective, multicentre study of a cohort of asymptomatic HIV-patients who switched from a regimen based on 2 nucleoside reverse transcriptase inhibitors (NRTI)+protease inhibitor (PI)/non nucleoside reverse transcriptase inhibitor (NNRTI) or ritonavir boosted PI monotherapy to Eviplera® during February-December, 2013; all had undetectable HIV viral load for ≥3 months prior to switching. Patients with previous failures on antiretroviral therapy (ART) including TDF and/or FTC/3TC, with genotype tests showing resistance to components of Eviplera®, or who had changed the third drug of the ART during the study period were excluded. Changes in lipid profile and cardiovascular risk (CVR), and efficacy and safety at 24 weeks were analyzed. RESULTS Among 305 patients included in the study, 298 were analyzed (7 cases were excluded due to lack of data). Men 81.2%, mean age 44.5 years, 75.8% of HIV sexually transmitted. 233 (78.2%) patients switched from a regimen based on 2 NRTI+NNRTI (90.5% EFV/FTC/TDF). The most frequent reasons for switching were central nervous system (CNS) adverse events (31.0%), convenience (27.6%) and metabolic disorders (23.2%). At this time, 293 patients have reached 24 weeks: 281 (95.9%) have continued Eviplera®, 6 stopped it (3 adverse events, 2 virologic failures, 1 discontinuation) and 6 have been lost to follow up. Lipid profiles of 283 cases were available at 24 weeks and mean (mg/dL) baseline vs 24 weeks are: total cholesterol (193 vs 169; p=0.0001), HDL-c (49 vs 45; p=0.0001), LDL-c (114 vs 103; p=0.001), tryglycerides (158 vs 115; p=0.0001), total cholesterol to HDL-c ratio (4.2 vs 4.1; p=0.3). CVR decreased (8.7 vs 7.5%; p= 0.0001). CD4 counts were similar to baseline (653 vs 674 cells/µL; p=0.08), and 274 (96.8%) patients maintained viral suppression. CONCLUSIONS At 24 weeks after switching to Eviplera®, lipid profile and CVR improved while maintaining a good immunovirological control. Most subjects switched to Eviplera® from a regimen based on NNRTI, mainly EFV/FTC/TDF. CNS adverse events, convenience and metabolic disorders were the most frequent reasons for switching.

Multi-dimensional classification using Bayesian networks for stationary and evolving streaming data

Hoy en día, con la evolución continua y rápida de las tecnologías de la información y los dispositivos de computación, se recogen y almacenan continuamente grandes volúmenes de datos en distintos dominios y a través de diversas aplicaciones del mundo real. La extracción de conocimiento útil de una cantidad tan enorme de datos no se puede realizar habitualmente de forma manual, y requiere el uso de técnicas adecuadas de aprendizaje automático y de minería de datos. La clasificación es una de las técnicas más importantes que ha sido aplicada con éxito a varias áreas. En general, la clasificación se compone de dos pasos principales: en primer lugar, aprender un modelo de clasificación o clasificador a partir de un conjunto de datos de entrenamiento, y en segundo lugar, clasificar las nuevas instancias de datos utilizando el clasificador aprendido. La clasificación es supervisada cuando todas las etiquetas están presentes en los datos de entrenamiento (es decir, datos completamente etiquetados), semi-supervisada cuando sólo algunas etiquetas son conocidas (es decir, datos parcialmente etiquetados), y no supervisada cuando todas las etiquetas están ausentes en los datos de entrenamiento (es decir, datos no etiquetados). Además, aparte de esta taxonomía, el problema de clasificación se puede categorizar en unidimensional o multidimensional en función del número de variables clase, una o más, respectivamente; o también puede ser categorizado en estacionario o cambiante con el tiempo en función de las características de los datos y de la tasa de cambio subyacente. A lo largo de esta tesis, tratamos el problema de clasificación desde tres perspectivas diferentes, a saber, clasificación supervisada multidimensional estacionaria, clasificación semisupervisada unidimensional cambiante con el tiempo, y clasificación supervisada multidimensional cambiante con el tiempo. Para llevar a cabo esta tarea, hemos usado básicamente los clasificadores Bayesianos como modelos. La primera contribución, dirigiéndose al problema de clasificación supervisada multidimensional estacionaria, se compone de dos nuevos métodos de aprendizaje de clasificadores Bayesianos multidimensionales a partir de datos estacionarios. Los métodos se proponen desde dos puntos de vista diferentes. El primer método, denominado CB-MBC, se basa en una estrategia de envoltura de selección de variables que es voraz y hacia delante, mientras que el segundo, denominado MB-MBC, es una estrategia de filtrado de variables con una aproximación basada en restricciones y en el manto de Markov. Ambos métodos han sido aplicados a dos problemas reales importantes, a saber, la predicción de los inhibidores de la transcriptasa inversa y de la proteasa para el problema de infección por el virus de la inmunodeficiencia humana tipo 1 (HIV-1), y la predicción del European Quality of Life-5 Dimensions (EQ-5D) a partir de los cuestionarios de la enfermedad de Parkinson con 39 ítems (PDQ-39). El estudio experimental incluye comparaciones de CB-MBC y MB-MBC con los métodos del estado del arte de la clasificación multidimensional, así como con métodos comúnmente utilizados para resolver el problema de predicción de la enfermedad de Parkinson, a saber, la regresión logística multinomial, mínimos cuadrados ordinarios, y mínimas desviaciones absolutas censuradas. En ambas aplicaciones, los resultados han sido prometedores con respecto a la precisión de la clasificación, así como en relación al análisis de las estructuras gráficas que identifican interacciones conocidas y novedosas entre las variables. La segunda contribución, referida al problema de clasificación semi-supervisada unidimensional cambiante con el tiempo, consiste en un método nuevo (CPL-DS) para clasificar flujos de datos parcialmente etiquetados. Los flujos de datos difieren de los conjuntos de datos estacionarios en su proceso de generación muy rápido y en su aspecto de cambio de concepto. Es decir, los conceptos aprendidos y/o la distribución subyacente están probablemente cambiando y evolucionando en el tiempo, lo que hace que el modelo de clasificación actual sea obsoleto y deba ser actualizado. CPL-DS utiliza la divergencia de Kullback-Leibler y el método de bootstrapping para cuantificar y detectar tres tipos posibles de cambio: en las predictoras, en la a posteriori de la clase o en ambas. Después, si se detecta cualquier cambio, un nuevo modelo de clasificación se aprende usando el algoritmo EM; si no, el modelo de clasificación actual se mantiene sin modificaciones. CPL-DS es general, ya que puede ser aplicado a varios modelos de clasificación. Usando dos modelos diferentes, el clasificador naive Bayes y la regresión logística, CPL-DS se ha probado con flujos de datos sintéticos y también se ha aplicado al problema real de la detección de código malware, en el cual los nuevos ficheros recibidos deben ser continuamente clasificados en malware o goodware. Los resultados experimentales muestran que nuestro método es efectivo para la detección de diferentes tipos de cambio a partir de los flujos de datos parcialmente etiquetados y también tiene una buena precisión de la clasificación. Finalmente, la tercera contribución, sobre el problema de clasificación supervisada multidimensional cambiante con el tiempo, consiste en dos métodos adaptativos, a saber, Locally Adpative-MB-MBC (LA-MB-MBC) y Globally Adpative-MB-MBC (GA-MB-MBC). Ambos métodos monitorizan el cambio de concepto a lo largo del tiempo utilizando la log-verosimilitud media como métrica y el test de Page-Hinkley. Luego, si se detecta un cambio de concepto, LA-MB-MBC adapta el actual clasificador Bayesiano multidimensional localmente alrededor de cada nodo cambiado, mientras que GA-MB-MBC aprende un nuevo clasificador Bayesiano multidimensional. El estudio experimental realizado usando flujos de datos sintéticos multidimensionales indica los méritos de los métodos adaptativos propuestos. ABSTRACT Nowadays, with the ongoing and rapid evolution of information technology and computing devices, large volumes of data are continuously collected and stored in different domains and through various real-world applications. Extracting useful knowledge from such a huge amount of data usually cannot be performed manually, and requires the use of adequate machine learning and data mining techniques. Classification is one of the most important techniques that has been successfully applied to several areas. Roughly speaking, classification consists of two main steps: first, learn a classification model or classifier from an available training data, and secondly, classify the new incoming unseen data instances using the learned classifier. Classification is supervised when the whole class values are present in the training data (i.e., fully labeled data), semi-supervised when only some class values are known (i.e., partially labeled data), and unsupervised when the whole class values are missing in the training data (i.e., unlabeled data). In addition, besides this taxonomy, the classification problem can be categorized into uni-dimensional or multi-dimensional depending on the number of class variables, one or more, respectively; or can be also categorized into stationary or streaming depending on the characteristics of the data and the rate of change underlying it. Through this thesis, we deal with the classification problem under three different settings, namely, supervised multi-dimensional stationary classification, semi-supervised unidimensional streaming classification, and supervised multi-dimensional streaming classification. To accomplish this task, we basically used Bayesian network classifiers as models. The first contribution, addressing the supervised multi-dimensional stationary classification problem, consists of two new methods for learning multi-dimensional Bayesian network classifiers from stationary data. They are proposed from two different points of view. The first method, named CB-MBC, is based on a wrapper greedy forward selection approach, while the second one, named MB-MBC, is a filter constraint-based approach based on Markov blankets. Both methods are applied to two important real-world problems, namely, the prediction of the human immunodeficiency virus type 1 (HIV-1) reverse transcriptase and protease inhibitors, and the prediction of the European Quality of Life-5 Dimensions (EQ-5D) from 39-item Parkinson’s Disease Questionnaire (PDQ-39). The experimental study includes comparisons of CB-MBC and MB-MBC against state-of-the-art multi-dimensional classification methods, as well as against commonly used methods for solving the Parkinson’s disease prediction problem, namely, multinomial logistic regression, ordinary least squares, and censored least absolute deviations. For both considered case studies, results are promising in terms of classification accuracy as well as regarding the analysis of the learned MBC graphical structures identifying known and novel interactions among variables. The second contribution, addressing the semi-supervised uni-dimensional streaming classification problem, consists of a novel method (CPL-DS) for classifying partially labeled data streams. Data streams differ from the stationary data sets by their highly rapid generation process and their concept-drifting aspect. That is, the learned concepts and/or the underlying distribution are likely changing and evolving over time, which makes the current classification model out-of-date requiring to be updated. CPL-DS uses the Kullback-Leibler divergence and bootstrapping method to quantify and detect three possible kinds of drift: feature, conditional or dual. Then, if any occurs, a new classification model is learned using the expectation-maximization algorithm; otherwise, the current classification model is kept unchanged. CPL-DS is general as it can be applied to several classification models. Using two different models, namely, naive Bayes classifier and logistic regression, CPL-DS is tested with synthetic data streams and applied to the real-world problem of malware detection, where the new received files should be continuously classified into malware or goodware. Experimental results show that our approach is effective for detecting different kinds of drift from partially labeled data streams, as well as having a good classification performance. Finally, the third contribution, addressing the supervised multi-dimensional streaming classification problem, consists of two adaptive methods, namely, Locally Adaptive-MB-MBC (LA-MB-MBC) and Globally Adaptive-MB-MBC (GA-MB-MBC). Both methods monitor the concept drift over time using the average log-likelihood score and the Page-Hinkley test. Then, if a drift is detected, LA-MB-MBC adapts the current multi-dimensional Bayesian network classifier locally around each changed node, whereas GA-MB-MBC learns a new multi-dimensional Bayesian network classifier from scratch. Experimental study carried out using synthetic multi-dimensional data streams shows the merits of both proposed adaptive methods.

Arteriosclerosis carotídea subclínica en pacientes con infección por VIH: relación con el tratamiento antirretroviral

La infección por VIH asocia un riesgo cardiovascular elevado por elevada prevalencia de factores de riesgo cardiovascular en esta población, por la propia infección por VIH y por las alteraciones metabólicas asociadas a la propia infección por VIH y al tratamiento antirretroviral (TAR). La arteriosclerosis carotídea subclínica es un reconocido marcador de riesgo cardiovascular. Material y métodos: Se realizó un estudio transversal incluyendo varones no diabéticos con infección por VIH a partir de 18 años, clasificados de acuerdo al grupo de tratamiento: grupo Naïve y grupo en TAR. Los pacientes del grupo TAR se dividían en grupo IP, tratado con inhibidores de la proteasa (IP) y grupo NN, grupo tratado con inhibidores de la transcriptasa inversa no análogos de nucleósidos que nunca estuvo expuesto a IP. Los dos grupos en TAR estaban en tratamiento con inhibidores de la transcriptasa inversa análogos de nucleósidos. Se evaluó por ecografía la presencia de arteriosclerosis carotídea subclínica, como aumento del grosor de íntima media (GIM) y presencia de placa carotídea, y se observó la relación con los factores de riesgo cardiovascular y metabólicos y su relación con el TAR. Resultados: Se incluyeron 93 varones con edad media 42,2 ± 8,2 años, mediana de tiempo de infección por VIH 6,6[2,9-12,4] años, mediana del tiempo total de exposición a TAR 59 [33-104,5] meses. El grupo naïve lo constituían 16 pacientes y el grupo en TAR 77 pacientes: 37 en el grupo NN y 40 en el grupo IP. Las variables asociadas de forma significativa a GIM máximo y medio en ACC fueron la edad, los años/paquete, la obesidad, la hiperglucemia basal en ayunas, HbA1c, los índices de insulinresistencia, la escala de Framingham, los años de evolución de la infección por VIH. El GIM medio se asoció de forma proporcional a presencia de síndrome metabólico, niveles de proteína C reactiva ultrasensible e insuficiencia de vitamina D e inversamente proporcional a la carga viral...

Development and Preliminary Evaluation of a Rapid Oligochromatographic Assay for Specific Detection of New Human Influenza A H1N1 Virus

A new oligochromatographic assay, Speed-Oligo Novel Influenza A H1N1, was designed and optimized for the specific detection of the 2009 influenza A H1N1 virus. The assay is based on a PCR method coupled to detection of PCR products by means of a dipstick device. The target sequence is a 103-bp fragment within the hemagglutinin gene. The analytical sensitivity of the new assay was measured with serial dilutions of a plasmid that contained the target sequence, and we determined that down to one copy per reaction of the plasmid was reliably detected. Diagnostic performance was assessed with 103 RNAs from suspected cases (40 positive and 63 negative results) previously analyzed with a reference real-time PCR technique. All positive cases were confirmed, and no false-positive results were detected with the new assay. No cross-reactions were observed when other viral strains or clinical samples with other respiratory viruses were tested. According to these results, this new assay has 100% sensitivity and specificity. The turnaround time for the whole procedure was 140 min. The assay may be especially useful for the specific detection of 2009 H1N1 virus in laboratories not equipped with real-time PCR instruments

Adipose tissue gene expression of factors related to lipid processing in obesity.

BACKGROUND Adipose tissue lipid storage and processing capacity can be a key factor for obesity-related metabolic disorders such as insulin resistance and diabetes. Lipid uptake is the first step to adipose tissue lipid storage. The aim of this study was to analyze the gene expression of factors involved in lipid uptake and processing in subcutaneous (SAT) and visceral (VAT) adipose tissue according to body mass index (BMI) and the degree of insulin resistance (IR). METHODS AND PRINCIPAL FINDINGS VLDL receptor (VLDLR), lipoprotein lipase (LPL), acylation stimulating protein (ASP), LDL receptor-related protein 1 (LRP1) and fatty acid binding protein 4 (FABP4) gene expression was measured in VAT and SAT from 28 morbidly obese patients with Type 2 Diabetes Mellitus (T2DM) or high IR, 10 morbidly obese patients with low IR, 10 obese patients with low IR and 12 lean healthy controls. LPL, FABP4, LRP1 and ASP expression in VAT was higher in lean controls. In SAT, LPL and FABP4 expression were also higher in lean controls. BMI, plasma insulin levels and HOMA-IR correlated negatively with LPL expression in both VAT and SAT as well as with FABP4 expression in VAT. FABP4 gene expression in SAT correlated inversely with BMI and HOMA-IR. However, multiple regression analysis showed that BMI was the main variable contributing to LPL and FABP4 gene expression in both VAT and SAT. CONCLUSIONS Morbidly obese patients have a lower gene expression of factors related with lipid uptake and processing in comparison with healthy lean persons.

Identification of reference genes for quantitative RT-PCR in ascending aortic aneurysms.

Hypertension and congenital aortic valve malformations are frequent causes of ascending aortic aneurysms. The molecular mechanisms of aneurysm formation under these circumstances are not well understood. Reference genes for gene activity studies in aortic tissue that are not influenced by aortic valve morphology and its hemodynamic consequences, aortic dilatation, hypertension, or antihypertensive medication are not available so far. This study determines genes in ascending aortic tissue that are independent of these parameters. Tissue specimens from dilated and undilated ascending aortas were obtained from 60 patients (age ≤70 years) with different morphologies of the aortic valve (tricuspid undilated n = 24, dilated n = 11; bicuspid undilated n = 6, dilated n = 15; unicuspid dilated n = 4). Of the studied individuals, 36 had hypertension, and 31 received ACE inhibitors or AT1 receptor antagonists. The specimens were obtained intraoperatively from the wall of the ascending aorta. We analyzed the expression levels of 32 candidate reference genes by quantitative RT-PCR (RT-qPCR). Differential expression levels were assessed by parametric statistics. The expression analysis of these 32 genes by RT-qPCR showed that EIF2B1, ELF1, and PPIA remained constant in their expression levels in the different specimen groups, thus being insensitive to aortic valve morphology, aortic dilatation, hypertension, and medication with ACE inhibitors or AT1 receptor antagonists. Unlike many other commonly used reference genes, the genes EIF2B1, ELF1, and PPIA are neither confounded by aortic comorbidities nor by antihypertensive medication and therefore are most suitable for gene expression analysis of ascending aortic tissue.

Rab18 dynamics in adipocytes in relation to lipogenesis, lipolysis and obesity.

Lipid droplets (LDs) are organelles that coordinate lipid storage and mobilization, both processes being especially important in cells specialized in managing fat, the adipocytes. Proteomic analyses of LDs have consistently identified the small GTPase Rab18 as a component of the LD coat. However, the specific contribution of Rab18 to adipocyte function remains to be elucidated. Herein, we have analyzed Rab18 expression, intracellular localization and function in relation to the metabolic status of adipocytes. We show that Rab18 production increases during adipogenic differentiation of 3T3-L1 cells. In addition, our data show that insulin induces, via phosphatidylinositol 3-kinase (PI3K), the recruitment of Rab18 to the surface of LDs. Furthermore, Rab18 overexpression increased basal lipogenesis and Rab18 silencing impaired the lipogenic response to insulin, thereby suggesting that this GTPase promotes fat accumulation in adipocytes. On the other hand, studies of the β-adrenergic receptor agonist isoproterenol confirmed and extended previous evidence for the participation of Rab18 in lipolysis. Together, our data support the view that Rab18 is a common mediator of lipolysis and lipogenesis and suggests that the endoplasmic reticulum (ER) is the link that enables Rab18 action on these two processes. Finally, we describe, for the first time, the presence of Rab18 in human adipose tissue, wherein the expression of this GTPase exhibits sex- and depot-specific differences and is correlated to obesity. Taken together, these findings indicate that Rab18 is involved in insulin-mediated lipogenesis, as well as in β-adrenergic-induced lipolysis, likely facilitating interaction of LDs with ER membranes and the exchange of lipids between these compartments. A role for Rab18 in the regulation of adipocyte biology under both normal and pathological conditions is proposed.

MicroRNA expression profiling in Imatinib-resistant Chronic Myeloid Leukemia patients without clinically significant ABL1-mutations.

The development of Imatinib Mesylate (IM), the first specific inhibitor of BCR-ABL1, has had a major impact in patients with Chronic Myeloid Leukemia (CML), establishing IM as the standard therapy for CML. Despite the clinical success obtained with the use of IM, primary resistance to IM and molecular evidence of persistent disease has been observed in 20-25% of IM treated patients. The existence of second generation TK inhibitors, which are effective in patients with IM resistance, makes identification of predictors of resistance to IM an important goal in CML. In this study, we have identified a group of 19 miRNAs that may predict clinical resistance to IM in patients with newly diagnosed CML.

Novel (60%) and recurrent (40%) androgen receptor gene mutations in a series of 59 patients with a 46,XY disorder of sex development.

BACKGROUND Androgen receptor (AR) gene mutations are the most frequent cause of 46,XY disorders of sex development (DSD) and are associated with a variety of phenotypes, ranging from phenotypic women [complete androgen insensitivity syndrome (CAIS)] to milder degrees of undervirilization (partial form or PAIS) or men with only infertility (mild form or MAIS). OBJECTIVE The aim of the study was to characterize the contribution of the AR gene to the molecular cause of 46,XY DSD in a series of Spanish patients. SETTING We studied a series of 133 index patients with 46,XY DSD in whom gonads were differentiated as testes, with phenotypes including varying degrees of undervirilization, and in whom the AR gene was the first candidate for a molecular analysis. METHODS The AR gene was sequenced (exons 1 to 8 with intronic flanking regions) in all patients and in family members of 61% of AR-mutated gene patients. RESULTS AR gene mutations were found in 59 individuals (44.4% of index patients), of whom 46 (78%) were CAIS and 13 (22%) PAIS. Fifty-seven different mutations were found: 21.0% located in exon 1, 15.8% in exons 2 and 3, 57.9% in exons 4-8, and 5.3% intronic. Twenty-three mutations (40.4%) had been previously described and 34 (59.6%) were novel. CONCLUSIONS AR gene mutation is the most frequent cause of 46,XY DSD, with a clearly higher frequency in the complete phenotype. Mutations spread along the whole coding sequence, including exon 1. This series shows that 60% of mutations detected during the period 2002-2009 were novel.

Differences in osteogenic and apoptotic genes between osteoporotic and osteoarthritic patients.

BACKGROUND Osteoporosis is a metabolic disorder characterized by a reduction in bone mass and deterioration in the microarchitectural structure of the bone, leading to a higher risk for spontaneous and fragility fractures.The main aim was to study the differences between human bone from osteoporotic and osteoarthritic patients about gene expression (osteogenesis and apoptosis), bone mineral density, microstructural and biomechanic parameters. METHODS We analyzed data from 12 subjects: 6 with osteoporotic hip fracture (OP) and 6 with hip osteoarthritis (OA), as the control group. All subjects underwent medical history, analytical determinations, densitometry, histomorphometric and biochemical study. The expression of 86 genes of osteogenesis and 86 genes of apoptosis was studied in pool of bone samples from patients with OP and OA by PCR array. RESULTS We observed that most of the genes of apoptosis and osteogenesis show a decrease in gene expression in the osteoporotic group in comparison with the osteoarthritic group. The histomorphometric study shows a lower bone quality in the group of patients with hip fractures compared to the osteoarthritic group. CONCLUSIONS The bone tissue of osteoporotic fracture patients is more fragile than the bone of OA patients. Our results showed an osteoporotic bone with a lower capacities for differentiation and osteoblastic activity as well as a lower rate of apoptosis than osteoarthritic bone. These results are related with structural and biochemical parameters.