Dataset Information

Comparative and alternative approaches and novel animal models for aging research: introduction to special issue.

ABSTRACT: This special issue of AGE showcases powerful alternative or unconventional approaches to basic aging research, including the use of exceptionally long-lived animal model species and comparative methods from evolutionary biology. In this opening paper, we introduce several of these alternative aging research themes, including the comparative phylogenetic approach. This approach applies modern inferential methods for dissecting basic physiological and biochemical mechanisms correlated with phenotypic traits including longevity, slow aging, sustained somatic maintenance, and repair of molecular damage. Comparative methods can be used to assess the general relevance of specific aging mechanisms--including oxidative processes--to diverse animal species, as well as to assess their potential clinical relevance to humans and other mammals. We also introduce several other novel, underexploited approaches with particular relevance to biogerontology, including the use of model animal species or strains that retain natural genetic heterogeneity, studies of effects of infectious disease and parasites on aging and responses to caloric restriction, studies of reproductive aging, and naturally occurring sex differences in aging. We emphasize the importance of drawing inferences from aging phenomena in laboratory studies that can be applied to clinically relevant aging syndromes in long-lived, outbred animals, including humans.

SUBMITTER: Holmes DJ

PROVIDER: S-EPMC2527630 | biostudies-other | 2008 Sep

REPOSITORIES: biostudies-other

ACCESS DATA

Similar Datasets

Project description:The severity of the overdose epidemic underscores the urgent need for innovative and high impact interventions that promote the rapid penetration and scale up of evidence-based practices (EBPs) in communities profoundly affected by fatal opioid overdose. This special issue shares scientific advancements in implementation research design and evaluation of a novel data-driven community-based intervention. The HEALing (Helping End Addiction Long-Term) Communities Study (HCS) is a four-year study that is designed to examine the effectiveness of the Communities That HEAL (CTH) intervention. The CTH intervention supports the dissemination of EBPs in 67 communities across four high-burdened states-Kentucky, Massachusetts, New York, and Ohio. The diversity in these communities in terms of rural-urban status, race-ethnicity and other social determinants of health facilitates generalizability of results to other communities across the US. The nine papers in this special issue describe critical elements that constitute the HCS framework and design. This includes the implementation of EBPs that have a substantial impact on fatal and non-fatal opioid overdose, the Opioid-overdose Reduction Continuum of Care Approach, communication campaigns to increase awareness and demand for EBPs and reduce stigma against people with OUD and MOUD interventions, and the process of community engagement. This includes how to form community coalitions and gain their commitment, and steps taken to mobilize coalitions to pursue EBP implementation and ensure EBPs are adapted for community needs. The collective papers in this issue demonstrate that the design of any complex study must adapt to unanticipated temporal events, including the rapidly emerging COVID-19 crisis. Readers will learn about the scientific process of the design and implementation of a community-engaged intervention, its methodologies, guiding conceptual models, and research implementation strategies that can be applied to address other health issues.

Project description:Background In order to track progress towards the target of universal access to sexual and reproductive health care services of the post-2015 Sustainable Development Goals (SDGs), a measure (demand for family planning satisfied with modern contraceptive methods) and a benchmark (at least 75% by 2030 in all countries) have been recommended. Objectives The goal of this study was to assess the prospects of reaching the benchmark at the country level. Such information can facilitate strategic planning, including resource allocation at global and country levels. Design We selected 63 countries based on their status as least developed according to the United Nations or as a priority country in global family planning initiatives. Using United Nations estimates and projections of family planning indicators between 1970 and 2030, we calculated percent demand for family planning satisfied with modern contraceptive methods for each year and country. We then calculated the annual percentage point changes between 2014 and 2030 required to meet the benchmark. The required rates of change were compared to current projections as well as estimates between 1970 and 2010. Results To reach the benchmark on average across the 63 countries, demand satisfied with modern methods must increase by 2.2 percentage points per year between 2014 and 2030 – more than double current projections. Between 1970 and 2010, such rapid progress was observed in 24 study countries but typically spanning 5–10 years. At currently projected rates, only 9 of the 63 study countries will reach the benchmark. Meanwhile, the gap between projected and required changes is largest in the Central and West African regions, 0.9 and 3.0 percentage points per year, respectively. If the benchmark is achieved, 334 million women across the study countries will use a modern contraceptive method in 2030, compared to 226 million women in 2014. Conclusions In order to achieve the component of the SDGs calling for universal access to sexual and reproductive health services, substantial effort is needed to accelerate rates of progress by a factor of 2 in most study countries and by a factor of 3 in Central and West African countries.

Dataset Information

Comparative and alternative approaches and novel animal models for aging research: introduction to special issue.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets