5 resultados para Biochemical analysis


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INTRODUCTION: The metabolic syndrome (MS) consists of a set of clinical and biochemical changes. It is very common among chronic hemodialysis patients, being the leading cause of death in these patients, 44% of all patients undergoing this therapy. AIMS: The aim of this study was to investigate the prevalence of MS and risk factors associated with its development, as well as the prevalence of obesity in HD patients. METHODS: This study has followed 90 patients of both sexes with chronic renal failure (CRF) who were treated with hemodialysis periodically in our unit for ten years. All patients were performed quarterly measurements of plasma albumin (A1b) and other biochemical analysis; besides, they underwent some anthropometric measurements like weight, height and body mass index (BMI). This was calculated using weight / size2 formula and grouped in BMI values according to WHO criteria. The data concerning hypertension and glucose were also considered. RESULTS: The prevalence of MS was 25% and obesity was presented as follows: 45% with type I overweight; 30.8% with type II overweight and 12 patients (2%) were obese. Being statistically significant as risk factors, BMI, overweight, triglycerides, total cholesterol, HDL cholesterol as well as hypertension and elevated glucose levels were obtained. CONCLUSIONS: The metabolic syndrome compromises the patient survival causing a high prevalence in these patients. The principal risk factors in MS are monitoring weight, BMI, triglycerides, HDL cholesterol, hypertension and diabetes.

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Background. Urotensin II (UII) is a potent vasoconstrictor peptide, which signals through a G-protein coupled receptor (GPCR) known as GPR14 or urotensin receptor (UTR). UII exerts a broad spectrum of actions in several systems such as vascular cell, heart muscle or pancreas, where it inhibits insulin release. Objective. Given the reported role of UII in insulin secretion, we have performed a genetic association analysis of the UTS2 gene and flanking regions with biochemical parameters related to insulin resistance (fasting glucose, glucose 2 hours after a glucose overload, fasting insulin and insulin resistance estimated as HOMA). Results and Conclusions. We have identified several polymorphisms associated with the analysed clinical traits, not only at the UTS2 gene, but also in thePER3 gene, located upstream from UTS2. Our results are compatible with a role for UII in glucose homeostasis and diabetes although we cannot rule out the possibility that PER3 gene may underlie the reported associations.

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Aquaporin-1 (AQP1) is a water channel that is highly expressed in tissues with rapid O(2) transport. It has been reported that this protein contributes to gas permeation (CO(2), NO and O(2)) through the plasma membrane. We show that hypoxia increases Aqp1 mRNA and protein levels in tissues, namely mouse brain and lung, and in cultured cells, the 9L glioma cell line. Stopped-flow light-scattering experiments confirmed an increase in the water permeability of 9L cells exposed to hypoxia, supporting the view that hypoxic Aqp1 up-regulation has a functional role. To investigate the molecular mechanisms underlying this regulatory process, transcriptional regulation was studied by transient transfections of mouse endothelial cells with a 1297 bp 5' proximal Aqp1 promoter-luciferase construct. Incubation in hypoxia produced a dose- and time-dependent induction of luciferase activity that was also obtained after treatments with hypoxia mimetics (DMOG and CoCl(2)) and by overexpressing stabilized mutated forms of HIF-1α. Single mutations or full deletions of the three putative HIF binding domains present in the Aqp1 promoter partially reduced its responsiveness to hypoxia, and transfection with Hif-1α siRNA decreased the in vitro hypoxia induction of Aqp1 mRNA and protein levels. Our results indicate that HIF-1α participates in the hypoxic induction of AQP1. However, we also demonstrate that the activation of Aqp1 promoter by hypoxia is complex and multifactorial and suggest that besides HIF-1α other transcription factors might contribute to this regulatory process. These data provide a conceptual framework to support future research on the involvement of AQP1 in a range of pathophysiological conditions, including edema, tumor growth, and respiratory diseases.

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BACKGROUND The role of genes involved in the control of progression from the G1 to the S phase of the cell cycle in melanoma tumors in not fully known. The aim of our study was to analyse mutations in TP53, CDKN1A, CDKN2A, and CDKN2B genes in melanoma tumors and melanoma cell lines METHODS We analysed 39 primary and metastatic melanomas and 9 melanoma cell lines by single-stranded conformational polymorphism (SSCP). RESULTS The single-stranded technique showed heterozygous defects in the TP53 gene in 8 of 39 (20.5%) melanoma tumors: three new single point mutations in intronic sequences (introns 1 and 2) and exon 10, and three new single nucleotide polymorphisms located in introns 1 and 2 (C to T transition at position 11701 in intron 1; C insertion at position 11818 in intron 2; and C insertion at position 11875 in intron 2). One melanoma tumor exhibited two heterozygous alterations in the CDKN2A exon 1 one of which was novel (stop codon, and missense mutation). No defects were found in the remaining genes. CONCLUSION These results suggest that these genes are involved in melanoma tumorigenesis, although they may be not the major targets. Other suppressor genes that may be informative of the mechanism of tumorigenesis in skin melanomas should be studied.

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There is limited information on the role of penicillin-binding proteins (PBPs) in the resistance of Acinetobacter baumannii to β-lactams. This study presents an analysis of the allelic variations of PBP genes in A. baumannii isolates. Twenty-six A. baumannii clinical isolates (susceptible or resistant to carbapenems) from three teaching hospitals in Spain were included. The antimicrobial susceptibility profile, clonal pattern, and genomic species identification were also evaluated. Based on the six complete genomes of A. baumannii, the PBP genes were identified, and primers were designed for each gene. The nucleotide sequences of the genes identified that encode PBPs and the corresponding amino acid sequences were compared with those of ATCC 17978. Seven PBP genes and one monofunctional transglycosylase (MGT) gene were identified in the six genomes, encoding (i) four high-molecular-mass proteins (two of class A, PBP1a [ponA] and PBP1b [mrcB], and two of class B, PBP2 [pbpA or mrdA] and PBP3 [ftsI]), (ii) three low-molecular-mass proteins (two of type 5, PBP5/6 [dacC] and PBP6b [dacD], and one of type 7 (PBP7/8 [pbpG]), and (iii) a monofunctional enzyme (MtgA [mtgA]). Hot spot mutation regions were observed, although most of the allelic changes found translated into silent mutations. The amino acid consensus sequences corresponding to the PBP genes in the genomes and the clinical isolates were highly conserved. The changes found in amino acid sequences were associated with concrete clonal patterns but were not directly related to susceptibility or resistance to β-lactams. An insertion sequence disrupting the gene encoding PBP6b was identified in an endemic carbapenem-resistant clone in one of the participant hospitals.