Serum uric acid level independently predicted metabolic syndrome in non-diabetic hypertensive patients

Background: Arterial hypertension may accompany metabolic syndrome (MetS) which is strongly associated with cardiovascular diseases. Determining high-risk groups concerning MetS development is crucial to prevent this undesirable clinic. Serum uric acid level was demonstrated to be associated with development of hypertension and MetS in normal population. It was aimed to investigate the role of serum uric acid for the prediction of MetS in non-diabetic hypertensive individuals. Material and methods: Patients who were diagnosed with arterial hypertension between January 2021 and June 2021 were included in the study. Diabetes mellitus was determined as an exclusion criteria. Metabolic syndrome was considered as the clustering of high blood pressure, elevated glucose level, abnormal cholesterol levels, and abdominal obesity conditions according to the National Cholesterol Education Program (NCEP) definition. Patients were divided into two groups by the presence of MetS. Results: The mean age of 107 non-diabetic hypertensive patients was 48.5 ± 8.6 years and 50 (46.7%) of them were female. A total of 56 patients (52%) had MetS. Waist circumference (101.2 ± 11.3 vs. 106.7 ± 10.1 cm, p = 0.020), body mass index (30.6 ± 4.9 vs. 32.8 ± 4.1, p = 0.016), E/e’ ratio [9.2 (7.3–11.1) vs. 10.6 (9.1–13.4), p = 0.003], EAT [5.9 (4.8–8) vs. 7.9 (6–9.6), p = 0.006], and serum uric acid level (4.75 ± 1.10 vs. 5.82 ± 1.21 mg/dL, p < 0.001) were higher in MetS (+) group. Multivariable regression demonstrated that serum uric acid [(odds ratio) OR = 2.217, 95% confidence interval (CI): 1.300–3.783, p = 0.003] and body mass index (OR = 1.214, 95% CI: 1.032–1.428, p = 0.019) were independent predictors of MetS presence. Conclusion: Serum uric acid level predicted MetS presence in non-diabetic hypertensive individuals independently. This practical blood parameter can be used to evaluate those who are at risk of MetS development.

The relationship of serum asymmetric dimethylarginine concentrations and lung involvement in patients with COVID-19 infection

Aim: COVID-19 infections the tissue through angiotensin converting enzyme 2 receptor, which is also expressed on endothelial cells. Endothelial dysfunction may be associated with lung involvement. Asymmetric dimethylarginine (ADMA) is an indirect marker of endothelial dysfunction. The aim of our study was to evaluate ADMA concentrations and to identify its association with lung involvement in patients with COVID19 disease. Methods: We included 42 patients with COVID-19 infection and lung involvement (Group 1). Forty-two age and sex matched patients without pneumonia acted as the control group (Group 2). All patients gave blood samples for ADMA at the 1st month control visit after discharge. We compared C-reactive protein (CRP) and ADMA concentrations in addition to routine biochemical parameters between groups. Results: Patients with lung involvement had higher admission glucose, CRP, and ADMA concentrations, and displayed lower hemoglobin concentration and lymphocyte count compared to patients without lung involvement. Although patients with lung involvement had higher ADMA concentrations with respect to those without; plasma ADMA levels were also higher than normal values in control group. Multivariate analysis identified log CRP concentration (OR= 3.047, 95% CI=1.881-5.023, p<0.001) as the independent predictor for lung involvement. And, there was a correlation between ADMA and CRP (r: 0.318, p: 0.003). Conclusion: We revealed elevated ADMA concentrations as the surrogate of endothelial dysfunction in COVID-19 patients whether they have pneumonia or not

Efficient computation of quadratic-phase integrals in optics

We present a fast N log N time algorithm for computing quadratic-phase integrals. This three-parameter class of integrals models propagation in free space in the Fresnel approximation, passage through thin lenses, and propagation in quadratic graded-index media as well as any combination of any number of these and is therefore of importance in optics. By carefully managing the sampling rate, one need not choose N much larger than the space–bandwidth product of the signals, despite the highly oscillatory integral kernel. The only deviation from exactness arises from the approximation of a continuous Fourier transform with the discrete Fourier transform. Thus the algorithm computes quadratic-phase integrals with a performance similar to that of the fast-Fourier-transform algorithm in computing the Fourier transform, in terms of both speed and accuracy. © 2006 Optical Society of America OCIS codes: 070.2580, 350.6980, 070.2590. A quadratic-phase system is a unitary system whose output g�u � is related to its input f�u � through a quadratic-phase integral: g�u � = � � exp� − i�/4

Digital Computation of Linear Canonical Transforms

We deal with the problem of efficient and accurate digital computation of the samples of the linear canonical transform (LCT) of a function, from the samples of the original function. Two approaches are presented and compared. The first is based on decomposition of the LCT into chirp multiplication, Fourier transformation, and scaling operations. The second is based on decomposition of the LCT into a fractional Fourier transform followed by scaling and chirp multiplication. Both algorithms take log time, where is the time-bandwidth product of the signals. The only essential deviation from exactness arises from the approximation of a continuous Fourier transform with the discrete Fourier transform. Thus, the algorithms compute LCTs with a performance similar to that of the fast Fourier transform algorithm in computing the Fourier transform, both in terms of speed and accuracy