Nodulocystic Acne: Oral Gugulipid versus Tetracycline

Twenty patients with nodulocystic acne were randomly allocated to one of two treatment schedules: 1) Tetracycline 500 mg or 2) Tab. Gugulipid (equivalent to 25 mg guggulsterone). Both were taken twice daily for 3 months, and both produced a progressive reduction in the lesions in the majority of patients. With tetracycline, the percentage reduction in the inflammatory lesions was 65.2% as compared to 68% with gugulipid; on comparison, this difference was statistically insignificant (P>0.05). Follow-up at 3 months showed a relapse in 4 cases on tetracyline and 2 cases on gugulipid. An interesting observation was that the patients with oily faces responded remarkably better to gugulipid.     

Norepinephrine triggers release of glial ATP to increase postsynaptic efficacy

Glial cells actively participate in synaptic transmission. They clear molecules from the synaptic cleft, receive signals from neurons and, in turn, release molecules that can modulate signaling between neuronal elements. Whether glial-derived transmitters can contribute to enduring changes in postsynaptic efficacy, however, remains to be established. In rat hypothalamic paraventricular nucleus, we demonstrate an increase in the amplitude of miniature excitatory postsynaptic currents in response to norepinephrine that requires the release of ATP from glial cells. The increase in quantal efficacy, which likely results from an insertion of AMPA receptors, is secondary to the activation of P2X(7) receptors, an increase in postsynaptic calcium and the activation of phosphatidylinositol 3-kinase. The gliotransmitter ATP, therefore, contributes directly to the regulation of postsynaptic efficacy at glutamatergic synapses in the CNS.     

Neurological and humoral control of blood pressure

There is a relationship between arterial blood pressure, cardiac output and vascular resistance which can be described mathematically, and helps us to understand the short-term control of blood pressure in the terms of a hydraulic system. The sensors in this system are the arterial baroreceptors which mediate changes in the hydraulic system though control of the autonomic nervous system, which in turn influences heart rate, inotropy and vascular tone. Altering the distribution of blood between the arterial and venous systems compensates for acute changes in total blood volume. The total blood volume is controlled predominantly by the kidney, with the renin–angiotensin–aldosterone system acting as both the ‘sensor’ of blood pressure/volume (via renin release in the juxtaglomerular apparatus) and the ‘effector’ of blood pressure/volume (via aldosterone secretion by the adrenal cortex). Overall control is shared; the baroreceptors being responsible for mediating short-term changes, and renal mechanisms determining the long-term control of blood pressure. These systems have to be adaptable in order to deal with physiological variation in the delivery of blood to tissues from rest to exercise, and with the large shifts in blood volume seen in acute haemorrhage. Pathophysiological changes in these systems lead to maladaptive responses, with systemic hypertension the most commonly seen.     

Biostatistics Series Module 3: Comparing Groups: Numerical Variables

Numerical data that are normally distributed can be analyzed with parametric tests, that is, tests which are based on the parameters that define a normal distribution curve. If the distribution is uncertain, the data can be plotted as a normal probability plot and visually inspected, or tested for normality using one of a number of goodness of fit tests, such as the Kolmogorov–Smirnov test. The widely used Student''s t-test has three variants. The one-sample t-test is used to assess if a sample mean (as an estimate of the population mean) differs significantly from a given population mean. The means of two independent samples may be compared for a statistically significant difference by the unpaired or independent samples t-test. If the data sets are related in some way, their means may be compared by the paired or dependent samples t-test. The t-test should not be used to compare the means of more than two groups. Although it is possible to compare groups in pairs, when there are more than two groups, this will increase the probability of a Type I error. The one-way analysis of variance (ANOVA) is employed to compare the means of three or more independent data sets that are normally distributed. Multiple measurements from the same set of subjects cannot be treated as separate, unrelated data sets. Comparison of means in such a situation requires repeated measures ANOVA. It is to be noted that while a multiple group comparison test such as ANOVA can point to a significant difference, it does not identify exactly between which two groups the difference lies. To do this, multiple group comparison needs to be followed up by an appropriate post hoc test. An example is the Tukey''s honestly significant difference test following ANOVA. If the assumptions for parametric tests are not met, there are nonparametric alternatives for comparing data sets. These include Mann–Whitney U-test as the nonparametric counterpart of the unpaired Student''s t-test, Wilcoxon signed-rank test as the counterpart of the paired Student''s t-test, Kruskal–Wallis test as the nonparametric equivalent of ANOVA and the Friedman''s test as the counterpart of repeated measures ANOVA.