Microbiology is the study of microorganisms, which are unicellular or cell-cluster microscopic organisms. This includes eukaryotes (with a nucleus) such as fungi and protists, and prokaryotes (without a nucleus) such as bacteria and viruses (though viruses are not strictly classed as living organisms).

Although much is now known in the field of microbiology, advances are being made regularly. In actual fact, the most common estimates suggest that we have studied only about 1% of all of the microbes in any given environment. Thus, despite the fact that over three hundred years have passed since the discovery of microbes, the field of microbiology is clearly in its infancy relative to other biological disciplines such as zoology, botany or even entomology.

History

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Bacteria were first observed by Anton van Leeuwenhoek in 1676 using a single-lens microscope of his own design. The name "bacterium" was introduced much later, by Ehrenberg in 1828, derived from the Greek word βακτηριον meaning "small stick". While Antony van Leeuwenhoek is often cited as the first microbiologist, the first recorded microbiological observation, that of the fruiting bodies of molds, was made earlier in 1665 by Robert Hooke.

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American Journal of Epidemiology - current issue

Cover
Fri, 03 Feb 2012 07:15:44 -0800

Editorial Board
Fri, 03 Feb 2012 07:15:44 -0800

Subscriptions
Fri, 03 Feb 2012 07:15:44 -0800

Table of contents
Fri, 03 Feb 2012 07:15:45 -0800

Anti-Mullerian Hormone: A Potential New Tool in Epidemiologic Studies of Female Fecundability
Baird, D. D., Steiner, A. Z. Fri, 03 Feb 2012 07:15:45 -0800
The objective of the present commentary is to suggest that epidemiologists explore the use of anti-Müllerian hormone (AMH) as a new measurement tool in fecundability studies. The authors briefly summarize the advantages and limitations of the 3 current approaches to studies of fecundability. All 3 approaches involve the collection of time-to-pregnancy or attempt-time data, and most are limited to participants who plan their pregnancies. AMH is produced by ovarian follicles during their early growth stages and is measured clinically to assess ovarian reserve (the number of remaining oocytes). Unlike time to pregnancy, serum AMH level can be assessed regardless of pregnancy-attempt status. Measurements are not significantly affected by phase of the menstrual cycle, oral contraceptive use, or early pregnancy. The authors suggest that AMH measurement can be a valuable addition to traditionally designed fecundability studies. In addition, this hormone should be investigated as an independent measure of fecundability in studies that focus on exposures hypothesized to target the ovary.
Bias in Observational Studies of Prevalent Users: Lessons for Comparative Effectiveness Research From a Meta-Analysis of Statins
Danaei, G., Tavakkoli, M., Hernan, M. A. Fri, 03 Feb 2012 07:15:45 -0800
Randomized clinical trials (RCTs) are usually the preferred strategy with which to generate evidence of comparative effectiveness, but conducting an RCT is not always feasible. Though observational studies and RCTs often provide comparable estimates, the questioning of observational analyses has recently intensified because of randomized-observational discrepancies regarding the effect of postmenopausal hormone replacement therapy on coronary heart disease. Reanalyses of observational data that excluded prevalent users of hormone replacement therapy led to attenuated discrepancies, which begs the question of whether exclusion of prevalent users should be generally recommended. In the current study, the authors evaluated the effect of excluding prevalent users of statins in a meta-analysis of observational studies of persons with cardiovascular disease. The pooled, multivariate-adjusted mortality hazard ratio for statin use was 0.77 (95% confidence interval (CI): 0.65, 0.91) in 4 studies that compared incident users with nonusers, 0.70 (95% CI: 0.64, 0.78) in 13 studies that compared a combination of prevalent and incident users with nonusers, and 0.54 (95% CI: 0.45, 0.66) in 13 studies that compared prevalent users with nonusers. The corresponding hazard ratio from 18 RCTs was 0.84 (95% CI: 0.77, 0.91). It appears that the greater the proportion of prevalent statin users in observational studies, the larger the discrepancy between observational and randomized estimates.

American Journal of Epidemiology - recent issues

Cover
Fri, 03 Feb 2012 07:15:44 -0800

Editorial Board
Fri, 03 Feb 2012 07:15:44 -0800

Subscriptions
Fri, 03 Feb 2012 07:15:44 -0800

Table of contents
Fri, 03 Feb 2012 07:15:45 -0800

Anti-Mullerian Hormone: A Potential New Tool in Epidemiologic Studies of Female Fecundability
Baird, D. D., Steiner, A. Z. Fri, 03 Feb 2012 07:15:45 -0800
The objective of the present commentary is to suggest that epidemiologists explore the use of anti-Müllerian hormone (AMH) as a new measurement tool in fecundability studies. The authors briefly summarize the advantages and limitations of the 3 current approaches to studies of fecundability. All 3 approaches involve the collection of time-to-pregnancy or attempt-time data, and most are limited to participants who plan their pregnancies. AMH is produced by ovarian follicles during their early growth stages and is measured clinically to assess ovarian reserve (the number of remaining oocytes). Unlike time to pregnancy, serum AMH level can be assessed regardless of pregnancy-attempt status. Measurements are not significantly affected by phase of the menstrual cycle, oral contraceptive use, or early pregnancy. The authors suggest that AMH measurement can be a valuable addition to traditionally designed fecundability studies. In addition, this hormone should be investigated as an independent measure of fecundability in studies that focus on exposures hypothesized to target the ovary.
Bias in Observational Studies of Prevalent Users: Lessons for Comparative Effectiveness Research From a Meta-Analysis of Statins
Danaei, G., Tavakkoli, M., Hernan, M. A. Fri, 03 Feb 2012 07:15:45 -0800
Randomized clinical trials (RCTs) are usually the preferred strategy with which to generate evidence of comparative effectiveness, but conducting an RCT is not always feasible. Though observational studies and RCTs often provide comparable estimates, the questioning of observational analyses has recently intensified because of randomized-observational discrepancies regarding the effect of postmenopausal hormone replacement therapy on coronary heart disease. Reanalyses of observational data that excluded prevalent users of hormone replacement therapy led to attenuated discrepancies, which begs the question of whether exclusion of prevalent users should be generally recommended. In the current study, the authors evaluated the effect of excluding prevalent users of statins in a meta-analysis of observational studies of persons with cardiovascular disease. The pooled, multivariate-adjusted mortality hazard ratio for statin use was 0.77 (95% confidence interval (CI): 0.65, 0.91) in 4 studies that compared incident users with nonusers, 0.70 (95% CI: 0.64, 0.78) in 13 studies that compared a combination of prevalent and incident users with nonusers, and 0.54 (95% CI: 0.45, 0.66) in 13 studies that compared prevalent users with nonusers. The corresponding hazard ratio from 18 RCTs was 0.84 (95% CI: 0.77, 0.91). It appears that the greater the proportion of prevalent statin users in observational studies, the larger the discrepancy between observational and randomized estimates.

Epidemiology & Infection - Current Issue

Volume 140 Issue 03
Thu, 01 Mar 2012 00:00:00 -0000
Epidemiology Infection, Volume 140 Issue 03 Epidemiology Infection publishes original reports and reviews on all aspects of infection in humans and animals. Particular emphasis is given to the epidemiology, prevention and control of infectious diseases. The scope includes the zoonoses, tropical infections, food hygiene, vaccine studies, statistics and the clinical, social and public-health aspects of infectious disease. It has become the key international periodical in which to find the latest reports on recently discovered infections and new technology. For those concerned with policy and planning for the control of infections, the papers on mathematical modelling of epidemics caused by historical, current and emergent infections will be of particular value.
HYG volume 140 issue 3 Cover and Front matter
Miscellaneous Epidemiology & Infection, Volume 140 Issue 03, pp f1-f2Abstract

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