Age-specific metabolic rates and mortality rates in the genus Drosophila

Early theories of aging suggested that organisms with relatively high metabolic rates would live shorter lives. Despite widespread tests of this 'rate of living' theory of aging, there is little empirical evidence to support the idea. A more fine-grained approach that examined age-related changes in metabolic rate over the life span could provide valuable insight into the relationship between metabolic rate and aging. Here we compare age-related metabolic rate (measured as CO2 production per hour) and age-related mortality rate among five species in the genus Drosophila. We find no evidence that longer-lived species have lower metabolic rates. In all five species, there is no clear evidence of an age-related metabolic decline. Metabolic rates are strikingly constant throughout the life course, with the exception of females of D. hydei, in which metabolic rates show an increase over the first third of the life span and then decline. We argue that some physiological traits may have been shaped by such strong selection over evolutionary time that they are relatively resistant to the decline in the force of selection that occurs within the life time of a single individual. We suggest that comparisons of specific traits that do not show signs of aging with those traits that do decline with age could provide insight into the aging process.     

Demographic incidence rates

Demographers commonly interpret incidence rates (for first marriages, say, or for births of a given order), cumulated over age for a closed cohort, as prevalences of corresponding demographic statuses. Since one is hard put to find an explicit justification for this interpretation in the literature, this note offers a mathematical proof that it is correct if and only if there is nondifferential mortality, as well as an extension to incidences for events which can happen more than once to an individual. Mortality incidence rates are discussed as well, and some of the evidence that cumulative incidence rates may get absurd values when computed from period data is reviewed.     

Protein unfolding rates correlate as strongly as folding rates with native structure

Although the folding rates of proteins have been studied extensively, both experimentally and theoretically, and many native state topological parameters have been proposed to correlate with or predict these rates, unfolding rates have received much less attention. Moreover, unfolding rates have generally been thought either to not relate to native topology in the same manner as folding rates, perhaps depending on different topological parameters, or to be more difficult to predict. Using a dataset of 108 proteins including two-state and multistate folders, we find that both unfolding and folding rates correlate strongly, and comparably well, with well-established measures of native topology, the absolute contact order and the long range order, with correlation coefficient values of 0.75 or higher. In addition, compared to folding rates, the absolute values of unfolding rates vary more strongly with native topology, have a larger range of values, and correlate better with thermodynamic stability. Similar trends are observed for subsets of different protein structural classes. Taken together, these results suggest that choosing a scaffold for protein engineering may require a compromise between a simple topology that will fold sufficiently quickly but also unfold quickly, and a complex topology that will unfold slowly and hence have kinetic stability, but fold slowly. These observations, together with the established role of kinetic stability in determining resistance to thermal and chemical denaturation as well as proteases, have important implications for understanding fundamental aspects of protein unfolding and folding and for protein engineering and design.     

Measuring readmission rates.

OBJECTIVE--To assess the feasibility of extracting data on readmissions and readmission rates from Körner data for use as health service indicators. DESIGN--Retrospective analysis of inpatient Körner data for January 1988 to April 1989. SETTING--Three districts in North East Thames region. MAIN OUTCOME MEASURES--Number of readmissions after index discharge for all acute specialties combined and by specialty (general medicine, general surgery, gynaecology, trauma and orthopaedics, and geriatrics); readmission rates at 28 days after index discharge; and rates standardised for age group and sex by specialty and by consultant. RESULTS--All specialties showed an early peak in number of admissions, which levelled off by 28 days. Readmission rates at 28 days were appreciably lower in surgical specialties than in medical specialties (for example, general surgery 4.1% v geriatric medicine 15.1%). They were related to age and sex of the patient. Rates standardised for these variables did not significantly differ by district. Likewise, significant differences in standardised rates were not obtained for consultants within a specialty in one district. CONCLUSIONS--Readmission rates may be measured with Körner data. The pattern of readmissions with time means that readmission rates should be measured at not more than 28 days after the index discharge; the rates require standardisation for age and sex. Annual comparisons of standardised rates may be made among districts for combinations of specialties; those among individual consultants or specialties are unlikely to be statistically valid.     

Re-assessing current extinction rates

There is a widespread belief that we are experiencing a mass extinction event similar in severity to previous mass extinction events in the last 600 million years where up to 95% of species disappeared. This paper reviews evidence for current extinctions and different methods of assessing extinction rates including species–area relationships and loss of tropical forests, changing threat status of species, co-extinction rates and modelling the impact of climate change. For 30 years some have suggested that extinctions through tropical forest loss are occurring at a rate of up to 100 species a day and yet less than 1,200 extinctions have been recorded in the last 400 years. Reasons for low number of identified global extinctions are suggested here and include success in protecting many endangered species, poor monitoring of most of the rest of species and their level of threat, extinction debt where forests have been lost but species still survive, that regrowth forests may be important in retaining ‘old growth’ species, fewer co-extinctions of species than expected, and large differences in the vulnerability of different taxa to extinction threats. More recently, others have suggested similar rates of extinction to earlier estimates but with the key cause of extinction being climate change, and in particular rising temperatures, rather than deforestation alone. Here I suggest that climate change, rather than deforestation is likely to bring about such high levels of extinction since the impacts of climate change are local to global and that climate change is acting synergistically with a range of other threats to biodiversity including deforestation.     

Identifying site-specific substitution rates

A maximum likelihood framework for estimating site-specific substitution rates is presented that does not require any prior assumptions about the rate distribution. We show that, when the branching pattern of the underlying tree is known, the analysis of pairs of positions is sufficient to estimate site-specific rates. In the abscense of a known topology, we introduce an iterative procedure to estimate simultaneously the branching pattern, the branch lengths, and site-specific substitution rates. Simulations show that the evolutionary rate of fast-evolving sites can be reliably inferred and that the accuracy of rate estimates depends mainly on the number of sequences in the data set. Thus, large sets of aligned sequences are necessary for reliable site-specific rate estimates. The method is applied to the complete mitochondrial DNA sequence of 53 humans, providing a complete picture of the site-specific substitution rates in human mitochondrial DNA.