Prevalence of asymptomatic bacteriuria in type 2 diabetic subjects with and without microalbuminuria

<p>Abstract</p> <p>Background</p> <p>Diabetic subjects, especially women, show high prevalence of asymptomatic bacteriuria (ASB). The aim of the present study was to evaluate the prevalence of ASB in subjects with type 2 diabetes mellitus (T2D) with and without microalbuminuria (MA).</p> <p>Findings</p> <p>A hundred diabetic subjects with MA (53 males/47 females, mean age ± standard deviation: 65.5 ± 11.1 years) and 100 diabetic subjects without MA (52 males/48 females, mean age ± standard deviation: 65.4 ± 11.3 years), consecutively attending the outpatient diabetes clinic of our hospital were recruited in the study. Subjects with overt diabetic nephropathy or nephropathy from other causes were excluded. In addition, subjects with symptoms of urinary track infection or use of antimicrobial drugs in the last 14 days were excluded by the study.</p> <p>Diabetic subjects with MA showed increased prevalence of ASB compared to diabetic subjects without MA (21% versus 8%, P < 0.001, respectively). <it>Escherichia coli </it>was the most prevalent pathogen isolated in diabetic subjects with and without MA (12% versus 3.0%, P = 0.01, respectively) followed by <it>Proteus mirabilis </it>(6% versus 5%, P = 0.75, respectively) and <it>Klebsiella </it>spp (5% versus 1%, P = 0.09, respectively). Univariate logistic analysis showed that ASB was associated with the presence of coronary artery disease [odds ratio (OR): 0.29, 95% Confidence Intervals (95% CI): 0.09-0.95, P = 0.04] and gender (OR: 0.09, 95% CI: 0.02-0.35, P < 0.001) in the diabetic study group with MA.</p> <p>Conclusions</p> <p>ASB is more prevalent among T2D subjects with MA. Screening for ASB is warranted in diabetic patients especially if pyuria is detected in urine analysis since ASB has been found to be a risk factor for developing symptomatic urinary tract infection.</p

Predictive modelling of soils’ hydraulic conductivity using artificial neural network and multiple linear regression

As a result of heterogeneity nature of soils and variation in its hydraulic conductivity over several orders of magnitude for various soil types from fine-grained to coarse-grained soils, predictive methods to estimate hydraulic conductivity of soils from properties considered more easily obtainable have now been given an appropriate consideration. This study evaluates the performance of artificial neural network (ANN) being one of the popular computational intelligence techniques in predicting hydraulic conductivity of wide range of soil types and compared with the traditional multiple linear regression (MLR). ANN and MLR models were developed using six input variables. Results revealed that only three input variables were statistically significant in MLR model development. Performance evaluations of the developed models using determination coefficient and mean square error show that the prediction capability of ANN is far better than MLR. In addition, comparative study with available existing models shows that the developed ANN and MLR in this study performed relatively better

T-138C and A-7G polymorphisms in the MGP gene and the association with coronary arthery disease: Iranian patients

&quot;n Normal 0 false false false EN-GB X-NONE AR-SA MicrosoftInternetExplorer4 /* Style Definitions */ table.MsoNormalTable {mso-style-name:"Table Normal"; mso-tstyle-rowband-size:0; mso-tstyle-colband-size:0; mso-style-noshow:yes; mso-style-priority:99; mso-style-qformat:yes; mso-style-parent:""; mso-padding-alt:0cm 5.4pt 0cm 5.4pt; mso-para-margin:0cm; mso-para-margin-bottom:.0001pt; mso-pagination:widow-orphan; font-size:11.0pt; font-family:"Calibri","sans-serif"; mso-ascii-font-family:Calibri; mso-ascii-theme-font:minor-latin; mso-fareast-font-family:"Times New Roman"; mso-fareast-theme-font:minor-fareast; mso-hansi-font-family:Calibri; mso-hansi-theme-font:minor-latin; mso-bidi-font-family:Arial; mso-bidi-theme-font:minor-bidi;} Background: Coronary Artery Disease (CAD) is a major cause of death worldwide including Iran.&amp;nbsp; The risk of developing disease in patients without symptoms is assessed in part by factors that are associated with disease. Among these factors family history points to the significance of genetic component in the risk of CAD. The identification of the genetic variants that confer risk for CAD is essential for detecting high-risk individuals, so preventative life style and therapeutic action can be taken before overt disease develops. So far more than 100 genes have been reported with possible role in developing risk for CAD. Matrix- Gla Protein (MGP) is one of these genes that association of its single nucleotide polymorphism (SNP) with CAD has been reported.&amp;nbsp; Among the polymorphisms, there are two promoter SNPs at position -7 &amp;amp; -138 that their association with CAD has been reported before. Here we investigated the association of these SNPs with CAD in Iranian population. &quot;n&quot;n Methods: 150 cases and 150 controls were selected on the basis of their clinical assessments and angiographic reports. DNA was extracted from blood samples. The genotypes for both SNPs were determined using Polymerase Chain Reaction-Restriction Fragment Length Polymorphism (PCR-RFLP) method with size fractionation on Polyacrylamide gel. &quot;n&quot;n Results: The comparison of allele &amp;amp; genotype frequencies between patients and controls showed that there is an excess of A allele at position -7 and T allele at position -138 among patients, although these differences were not significant (p&amp;lt;0.2, and p&amp;lt;0.5 respectively).&quot;n&quot;n Conclusions: This study suggests no association of these SNPs with CAD in Iranian population. Confirmation of this finding needs independent repeat of similar studies.&quot;n&quot;n Keywords: Coronary Artery Disease (CAD), Matrix Gla Protein (MGP), Single Nucleotide Polymorphism (SNP)

Evaluation of Antimicrobial Resistance of Acinetobacter baumannii to Imipenem, Ciporofloxacin and Ceftazidime using E Test

&quot;nBackground: Resistance patterns among nosocomial bacterial pathogens in hospitals may vary widely from country to coun&amp;shy;try at any given point and within the same country over time. Acinetobacter baumannii is one of the most important bacte&amp;shy;rium causes hospital acquired infections. Therefore, surveillance of antibiotic resistance of A. baumannii is necessary, espe&amp;shy;cially in our country which there is no have much data in this field.&quot;nMethods: In a prospective study, strain comprised of a total of 191 recent clinical isolates selected consecutively from clini&amp;shy;cal infections of separate patients from three University hospitals in Tehran. Minimum inhibitory concentration (MIC) of these organisms for imipenem, ciprofloxacin and ceftazidime was determined using E test method according to CLSI guide&amp;shy;line. Also, MIC50 and MIC90 percent was calculated for each of these antibiotics.&quot;nResults: The percentages of Acinetobacter baumannii isolates susceptible to ciprofloxacin and ceftazidime by E test were 55.5% and 44.5%, respectively. The percentage of bacterium susceptible to imipenem by E test was 72.8%. MIC50 and MIC90 of imipenem in E test were 1.5 and &amp;gt;32, respectively.&quot;nConclusion: High antimicrobial resistance against A. baumannii species has been seen in Iran; therefore, it is necessary to imple&amp;shy;ment some approaches for prevention of bacterial spread