Analista/Sviluppatore Python Test Automation

Netcom Engineering, società del gruppo Metoda, specializzata nell'attività di consulenza ingegneristica

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Analista/Sviluppatore Python per attività di Test Automation.

Il candidato ideale ha conoscenza dei principali linguaggi di programmazione (in particolare Python, C, C++, Java, VisualBasic) ed un’esperienza pregressa di sviluppo di software applicativi in ambito tecnologico. Ha buone conoscenze nel campo delle telecomunicazioni e della televisione digitale ed una sufficiente padronanza dei più comuni tools software applicativi.

Le sue competenze gli consentono di valutare la fattibilità dell’automazione di un processo di test, di sviluppare il software per implementare le soluzioni trovate, di integrare propriamente tutti i componenti (HW/SW) coinvolti nella soluzioni proposta.

Sede di lavoro: Milano

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Left ventricular diastolic function evaluated with tissue Doppler imaging in children with familial Mediterranean fever.

The aim of this study was to assess the left ventricular diastolic function using conventional echocardiography and tissue Doppler imaging in children with familial Mediterranean fever. This study included 29 (13 males and 16 females) patients and 30 healthy subjects as controls. Body mass index was calculated and arterial blood pressure was monitored. After an overnight fast, venous blood samples were taken and serum amyloid A protein, C-reactive protein, serum-fasting glucose, total cholesterol, triglycerides, high-density lipoprotein cholesterol, very low density lipoprotein cholesterol, and serum low-density lipoprotein cholesterol levels were measured. A complete 2-dimensional, M-mode, pulse wave Doppler, and pulse wave tissue Doppler echocardiographic examination was performed. There were no significant differences between the groups regarding age, body mass index values, systolic and diastolic blood pressures, heart rates, serum-fasting glucose, total cholesterol, triglycerides, high-density lipoprotein cholesterol, very low density lipoprotein cholesterol, and serum low-density lipoprotein cholesterol. Serum levels of inflammatory markers were higher in patients' group (C-reactive protein and serum amyloid A protein levels were 10.84 mg/dl, 22.32 mg/l in patients' group, respectively, and 4.11 mg/dl, 3.65 mg/l, respectively, in the healthy controls.) Peak mitral A wave, E and A wave ratio differed significantly in both groups. There were statistically significant differences regarding parameters observed by tissue Doppler imaging such as E'm, A'm, E'm, and A'm ratio between patients' group and controls. Tissue Doppler imaging provided additional information on left ventricular diastolic function. While systolic functions were in normal range, some of the diastolic function parameters were impaired in patients with familial Mediterranean fever during childhood.

Diagnostic value of plasma fibronectin level in predicting the presence and severity of coronary artery disease.

The relation between fibronectin and coronary artery disease (CAD) according to previous study results is controversial. The aim of the present study is to investigate the predictive value of fibronectin in determining the presence and severity of CAD. Patients with stable angina (n = 62) who had angiographically documented CAD, and control patients (n = 31) who had normal coronary angiograms, were included in the study. Plasma fibronectin levels were determined in all patients. Plasma fibronectin level (milligrams per liter) in patients with CAD was higher than normal controls (364.2 +/- 171 vs 265.1 +/- 135.5, p = 0.006). The severity of CAD determined according to Gensini score and fibronectin level did not show any correlation (r = 0.13, p = 0.311). If fibronectin level 240 mg/l was determined as cutoff, it showed 76% sensitivity, 46% specificity, 46% negative predictive value, and 72.3% positive predictive value for predicting CAD. The present study showed that plasma fibronectin level in CAD is significantly higher than normal control subjects. However, it has no role in predicting the severity of CAD.

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