Renin-Angiotensin System Blockade Associated with Statin Improves Endothelial Function in Diabetics

Abstract Background: Studies suggest that statins have pleiotropic effects, such as reduction in blood pressure, and improvement in endothelial function and vascular stiffness. Objective: To analyze if prior statin use influences the effect of renin-angiotensin-aldosterone system inhibitors on blood pressure, endothelial function, and vascular stiffness. Methods: Patients with diabetes and hypertension with office systolic blood pressure ≥ 130 mmHg and/or diastolic blood pressure ≥ 80 mmHg had their antihypertensive medications replaced by amlodipine during 6 weeks. They were then randomized to either benazepril or losartan for 12 additional weeks while continuing on amlodipine. Blood pressure (assessed with ambulatory blood pressure monitoring), endothelial function (brachial artery flow-mediated dilation), and vascular stiffness (pulse wave velocity) were evaluated before and after the combined treatment. In this study, a post hoc analysis was performed to compare patients who were or were not on statins (SU and NSU groups, respectively). Results: The SU group presented a greater reduction in the 24-hour systolic blood pressure (from 134 to 122 mmHg, p = 0.007), and in the brachial artery flow-mediated dilation (from 6.5 to 10.9%, p = 0.003) when compared with the NSU group (from 137 to 128 mmHg, p = 0.362, and from 7.5 to 8.3%, p = 0.820). There was no statistically significant difference in pulse wave velocity (SU group: from 9.95 to 9.90 m/s, p = 0.650; NSU group: from 10.65 to 11.05 m/s, p = 0.586). Conclusion: Combined use of statins, amlodipine, and renin-angiotensin-aldosterone system inhibitors improves the antihypertensive response and endothelial function in patients with hypertension and diabetes.

Methodological Gaps in Left Atrial Function Assessment by 2D Speckle Tracking Echocardiography

Abstract The assessment of left atrial (LA) function is used in various cardiovascular diseases. LA plays a complementary role in cardiac performance by modulating left ventricular (LV) function. Transthoracic two-dimensional (2D) phasic volumes and Doppler echocardiography can measure LA function non‑invasively. However, evaluation of LA deformation derived from 2D speckle tracking echocardiography (STE) is a new feasible and promising approach for assessment of LA mechanics. These parameters are able to detect subclinical LA dysfunction in different pathological condition. Normal ranges for LA deformation and cut-off values to diagnose LA dysfunction with different diseases have been reported, but data are still conflicting, probably because of some methodological and technical issues. This review highlights the importance of an unique standardized technique to assess the LA phasic functions by STE, and discusses recent studies on the most important clinical applications of this technique.

Advancing the understanding of brain function with multivariate pattern analysis

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2009

The Effect of Sleep Deprivation on Cardiac Function and Tolerance to Ischemia-Reperfusion Injury in Male Rats

Abstract Background: Sleep deprivation (SD) is strongly associated with elevated risk for cardiovascular disease. Objective: To determine the effect of SD on basal hemodynamic functions and tolerance to myocardial ischemia-reperfusion (IR) injury in male rats. Method: SD was induced by using the flowerpot method for 4 days. Isolated hearts were perfused with Langendorff setup, and the following parameters were measured at baseline and after IR: left ventricular developed pressure (LVDP); heart rate (HR); and the maximum rate of increase and decrease of left ventricular pressure (±dp/dt). Heart NOx level, infarct size and coronary flow CK-MB and LDH were measured after IR. Systolic blood pressure (SBP) was measured at start and end of study. Results: In the SD group, the baseline levels of LVDP (19%), +dp/dt (18%), and -dp/dt (21%) were significantly (p < 0.05) lower, and HR (32%) was significantly higher compared to the controls. After ischemia, hearts from SD group displayed a significant increase in HR together with a low hemodynamic function recovery compared to the controls. In the SD group, NOx level in heart, coronary flow CK-MB and LDH and infarct size significantly increased after IR; also SD rats had higher SBP after 4 days. Conclusion: Hearts from SD rats had lower basal cardiac function and less tolerance to IR injury, which may be linked to an increase in NO production following IR.

A determinação dos números de indivíduos mínimos necessários na experimentação genética

The main object of the present paper consists in giving formulas and methods which enable us to determine the minimum number of repetitions or of individuals necessary to garantee some extent the success of an experiment. The theoretical basis of all processes consists essentially in the following. Knowing the frequency of the desired p and of the non desired ovents q we may calculate the frequency of all possi- ble combinations, to be expected in n repetitions, by expanding the binomium (p-+q)n. Determining which of these combinations we want to avoid we calculate their total frequency, selecting the value of the exponent n of the binomium in such a way that this total frequency is equal or smaller than the accepted limit of precision n/pª{ 1/n1 (q/p)n + 1/(n-1)| (q/p)n-1 + 1/ 2!(n-2)| (q/p)n-2 + 1/3(n-3) (q/p)n-3... < Plim - -(1b) There does not exist an absolute limit of precision since its value depends not only upon psychological factors in our judgement, but is at the same sime a function of the number of repetitions For this reasen y have proposed (1,56) two relative values, one equal to 1-5n as the lowest value of probability and the other equal to 1-10n as the highest value of improbability, leaving between them what may be called the "region of doubt However these formulas cannot be applied in our case since this number n is just the unknown quantity. Thus we have to use, instead of the more exact values of these two formulas, the conventional limits of P.lim equal to 0,05 (Precision 5%), equal to 0,01 (Precision 1%, and to 0,001 (Precision P, 1%). The binominal formula as explained above (cf. formula 1, pg. 85), however is of rather limited applicability owing to the excessive calculus necessary, and we have thus to procure approximations as substitutes. We may use, without loss of precision, the following approximations: a) The normal or Gaussean distribution when the expected frequency p has any value between 0,1 and 0,9, and when n is at least superior to ten. b) The Poisson distribution when the expected frequecy p is smaller than 0,1. Tables V to VII show for some special cases that these approximations are very satisfactory. The praticai solution of the following problems, stated in the introduction can now be given: A) What is the minimum number of repititions necessary in order to avoid that any one of a treatments, varieties etc. may be accidentally always the best, on the best and second best, or the first, second, and third best or finally one of the n beat treatments, varieties etc. Using the first term of the binomium, we have the following equation for n: n = log Riim / log (m:) = log Riim / log.m - log a --------------(5) B) What is the minimun number of individuals necessary in 01der that a ceratin type, expected with the frequency p, may appaer at least in one, two, three or a=m+1 individuals. 1) For p between 0,1 and 0,9 and using the Gaussean approximation we have: on - ó. p (1-p) n - a -1.m b= δ. 1-p /p e c = m/p } -------------------(7) n = b + b² + 4 c/ 2 n´ = 1/p n cor = n + n' ---------- (8) We have to use the correction n' when p has a value between 0,25 and 0,75. The greek letters delta represents in the present esse the unilateral limits of the Gaussean distribution for the three conventional limits of precision : 1,64; 2,33; and 3,09 respectively. h we are only interested in having at least one individual, and m becomes equal to zero, the formula reduces to : c= m/p o para a = 1 a = { b + b²}² = b² = δ2 1- p /p }-----------------(9) n = 1/p n (cor) = n + n´ 2) If p is smaller than 0,1 we may use table 1 in order to find the mean m of a Poisson distribution and determine. n = m: p C) Which is the minimun number of individuals necessary for distinguishing two frequencies p1 and p2? 1) When pl and p2 are values between 0,1 and 0,9 we have: n = { δ p1 ( 1-pi) + p2) / p2 (1 - p2) n= 1/p1-p2 }------------ (13) n (cor) We have again to use the unilateral limits of the Gaussean distribution. The correction n' should be used if at least one of the valors pl or p2 has a value between 0,25 and 0,75. A more complicated formula may be used in cases where whe want to increase the precision : n (p1 - p2) δ { p1 (1- p2 ) / n= m δ = δ p1 ( 1 - p1) + p2 ( 1 - p2) c= m / p1 - p2 n = { b2 + 4 4 c }2 }--------- (14) n = 1/ p1 - p2 2) When both pl and p2 are smaller than 0,1 we determine the quocient (pl-r-p2) and procure the corresponding number m2 of a Poisson distribution in table 2. The value n is found by the equation : n = mg /p2 ------------- (15) D) What is the minimun number necessary for distinguishing three or more frequencies, p2 p1 p3. If the frequecies pl p2 p3 are values between 0,1 e 0,9 we have to solve the individual equations and sue the higest value of n thus determined : n 1.2 = {δ p1 (1 - p1) / p1 - p2 }² = Fiim n 1.2 = { δ p1 ( 1 - p1) + p1 ( 1 - p1) }² } -- (16) Delta represents now the bilateral limits of the : Gaussean distrioution : 1,96-2,58-3,29. 2) No table was prepared for the relatively rare cases of a comparison of threes or more frequencies below 0,1 and in such cases extremely high numbers would be required. E) A process is given which serves to solve two problemr of informatory nature : a) if a special type appears in n individuals with a frequency p(obs), what may be the corresponding ideal value of p(esp), or; b) if we study samples of n in diviuals and expect a certain type with a frequency p(esp) what may be the extreme limits of p(obs) in individual farmlies ? I.) If we are dealing with values between 0,1 and 0,9 we may use table 3. To solve the first question we select the respective horizontal line for p(obs) and determine which column corresponds to our value of n and find the respective value of p(esp) by interpolating between columns. In order to solve the second problem we start with the respective column for p(esp) and find the horizontal line for the given value of n either diretly or by approximation and by interpolation. 2) For frequencies smaller than 0,1 we have to use table 4 and transform the fractions p(esp) and p(obs) in numbers of Poisson series by multiplication with n. Tn order to solve the first broblem, we verify in which line the lower Poisson limit is equal to m(obs) and transform the corresponding value of m into frequecy p(esp) by dividing through n. The observed frequency may thus be a chance deviate of any value between 0,0... and the values given by dividing the value of m in the table by n. In the second case we transform first the expectation p(esp) into a value of m and procure in the horizontal line, corresponding to m(esp) the extreme values om m which than must be transformed, by dividing through n into values of p(obs). F) Partial and progressive tests may be recomended in all cases where there is lack of material or where the loss of time is less importent than the cost of large scale experiments since in many cases the minimun number necessary to garantee the results within the limits of precision is rather large. One should not forget that the minimun number really represents at the same time a maximun number, necessary only if one takes into consideration essentially the disfavorable variations, but smaller numbers may frequently already satisfactory results. For instance, by definition, we know that a frequecy of p means that we expect one individual in every total o(f1-p). If there were no chance variations, this number (1- p) will be suficient. and if there were favorable variations a smaller number still may yield one individual of the desired type. r.nus trusting to luck, one may start the experiment with numbers, smaller than the minimun calculated according to the formulas given above, and increase the total untill the desired result is obtained and this may well b ebefore the "minimum number" is reached. Some concrete examples of this partial or progressive procedure are given from our genetical experiments with maize.

Imaging beyond structure : novel noninvasive tools for neuroimaging of stem cell function and differentiation

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2013

In vivo and in vitro studies on the expression and function of TFF peptides in the gastrointestinal tract and the central nervous system

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2014

Breakage probability of repeated stressing of granules by configuring the stressing points

Magdeburg, Univ., Fak. für Verfahrens- und Systemtechnik, Diss., 2014

Dominance of positivity of the Green's function associated to a perturbed polyharmonic dirichlet boundary value problem by pointwise estimates

Magdeburg, Univ., Fak. für Mathematik, Diss., 2015

The status (quo) of VET in Brazil : an empirical study about its function, meaning and impingements from the perspective of former dual system apprentices

Magdeburg, Univ., Fak. für Humanwiss., Diss., 2015

Astrocyte-specific function of A20 and FasL in experimental autoimmune encephalomyelitis

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2015

role of NMDA-receptors (NMDARs) and NMDAR antagonists in murine T- and B-lymphocyte function

Magdeburg, Univ., Fak. für Naturwiss., Diss., 2015

Interneuron function in pathological memory processes : relevance for posttraumatic stress disorder

Otto-von-Guericke-Universität Magdeburg, Fakultät für Naturwissenschaften, Univ., Dissertation, 2015

effect of the extracellular environment on the composition and function of synapses

Otto-von-Guericke-Universität magdeburg, Fakultät für Naturwissenschaften, Dissertation, 2015

General function of the gall bladder from the evolutionary standpoint, by Frank W. Gorham and Andrew Conway Ivy.

v.22:no.3(1938)