The Experts below are selected from a list of 321 Experts worldwide ranked by ideXlab platform
Steve Goldband - One of the best experts on this subject based on the ideXlab platform.
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mathematical connection between short telomere induced senescence calculation and Mortality Rate data
International Journal of Molecular Sciences, 2020Co-Authors: J B Torrance, Steve GoldbandAbstract:The last 20 years have seen a surge in scientific activity and promising results in the study of aging and longevity. Many researchers have focused on telomeres, which are composed of a series of TTAGGG repeat nucleotide sequences at the ends of each chromosome. Measurements of the length of these telomere strands show that they decrease in length with increasing age, leading many authors to propose that when the length of these telomere strands decreases sufficiently, the cells enter into a state of replicative senescence, eventually leading to disease and death. These ideas are supported by evidence that short telomere length is correlated with increased Mortality. In this paper, we extend this idea to make an actual calculation of the predicted Mortality Rate caused by short telomere length induced senescence (STLIS). We derive a simple equation for the mathematical relationship between telomere length and Mortality Rate. Using only three parameters based on telomere length measurement data of Canadians, we have calculated both the magnitude and the age dependence of the Mortality Rate for both men and women. We show that these calculated data are in good quantitative agreement with the actual number of Canadians that die. This agreement demonstRates the quantitative correlation between the Mortality calculated by the STLIS model and the Mortality of the major diseases of aging (e.g., cardiovascular disease, many cancers and diabetes mellitus), which dominate human Mortality. This result represents significant progress in our understanding of the factors behind the cause of aging.
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mathematical connection between short telomere induced senescence calculation and Mortality Rate data
bioRxiv, 2020Co-Authors: J B Torrance, Steve GoldbandAbstract:The last 20 years have seen a surge in scientific activity and promising results in the study of aging and longevity. Many researchers have focused on telomeres, which are composed of a series of TTAGGG repeat nucleotide sequences at the ends of each chromosome. Measurements of the length of these telomere strands show that they decrease in length with increasing age, leading many authors to propose that when the length of these telomere strands decreases sufficiently, the cells enter into a state of replicative senescence, eventually leading to disease and death. These ideas are supported by evidence that short telomere length is correlated with increased Mortality. In this paper, we extend this idea to make an actual calculation of the predicted Mortality Rate caused by short telomere length induced senescence (STLIS). We derive a simple equation for the mathematical relationship between telomere length and Mortality Rate. Using only 3 parameters based on telomere length measurement data of Canadians, we have calculated both the magnitude and the age dependence of the Mortality Rate, for both men and women. We show that these calculated data are in good quantitative agreement with the actual number of Canadians that die. This agreement provides strong evidence (but not proof) that the mechanism of STLIS plays an important role in the major diseases of aging (e.g., cardiovascular disease, many cancers, and diabetes mellitus) which dominate human Mortality. This result represents significant progress in our understanding the factors behind the cause of aging.
J B Torrance - One of the best experts on this subject based on the ideXlab platform.
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mathematical connection between short telomere induced senescence calculation and Mortality Rate data
International Journal of Molecular Sciences, 2020Co-Authors: J B Torrance, Steve GoldbandAbstract:The last 20 years have seen a surge in scientific activity and promising results in the study of aging and longevity. Many researchers have focused on telomeres, which are composed of a series of TTAGGG repeat nucleotide sequences at the ends of each chromosome. Measurements of the length of these telomere strands show that they decrease in length with increasing age, leading many authors to propose that when the length of these telomere strands decreases sufficiently, the cells enter into a state of replicative senescence, eventually leading to disease and death. These ideas are supported by evidence that short telomere length is correlated with increased Mortality. In this paper, we extend this idea to make an actual calculation of the predicted Mortality Rate caused by short telomere length induced senescence (STLIS). We derive a simple equation for the mathematical relationship between telomere length and Mortality Rate. Using only three parameters based on telomere length measurement data of Canadians, we have calculated both the magnitude and the age dependence of the Mortality Rate for both men and women. We show that these calculated data are in good quantitative agreement with the actual number of Canadians that die. This agreement demonstRates the quantitative correlation between the Mortality calculated by the STLIS model and the Mortality of the major diseases of aging (e.g., cardiovascular disease, many cancers and diabetes mellitus), which dominate human Mortality. This result represents significant progress in our understanding of the factors behind the cause of aging.
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mathematical connection between short telomere induced senescence calculation and Mortality Rate data
bioRxiv, 2020Co-Authors: J B Torrance, Steve GoldbandAbstract:The last 20 years have seen a surge in scientific activity and promising results in the study of aging and longevity. Many researchers have focused on telomeres, which are composed of a series of TTAGGG repeat nucleotide sequences at the ends of each chromosome. Measurements of the length of these telomere strands show that they decrease in length with increasing age, leading many authors to propose that when the length of these telomere strands decreases sufficiently, the cells enter into a state of replicative senescence, eventually leading to disease and death. These ideas are supported by evidence that short telomere length is correlated with increased Mortality. In this paper, we extend this idea to make an actual calculation of the predicted Mortality Rate caused by short telomere length induced senescence (STLIS). We derive a simple equation for the mathematical relationship between telomere length and Mortality Rate. Using only 3 parameters based on telomere length measurement data of Canadians, we have calculated both the magnitude and the age dependence of the Mortality Rate, for both men and women. We show that these calculated data are in good quantitative agreement with the actual number of Canadians that die. This agreement provides strong evidence (but not proof) that the mechanism of STLIS plays an important role in the major diseases of aging (e.g., cardiovascular disease, many cancers, and diabetes mellitus) which dominate human Mortality. This result represents significant progress in our understanding the factors behind the cause of aging.
Giuseppe Simini - One of the best experts on this subject based on the ideXlab platform.
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acute renal failure in the patient undergoing cardiac operation prevalence Mortality Rate and main risk factors
The Journal of Thoracic and Cardiovascular Surgery, 1994Co-Authors: Giorgio Zanardo, Paolo Michielon, Agostino Paccagnella, Paolo Rosi, Mauro Calo, Valeria Salandin, Antonia Da Ros, Federica Michieletto, Giuseppe SiminiAbstract:A total of 775 consecutive patients who survived the first 24 hours after cardiac operation were prospectively studied to assess the prevalence, Mortality Rate, and main risk factors for development of new acute renal failure. Normal renal function before operation (serum creatinine level less than 1.5 mg/dl) was registered in 734 (94.7 %) patients. Of these, 111 (15.1 %) showed a postoperative renal complication including 84 (11.4%) classified as renal dysfunction (serum creatinine level between 1.5 and 2.5 mg/dl) and 27 (3.7%) as acute renal failure (serum creatinine level higher than 2.5 mg/dl). The Mortality Rate was 0.8 % in normal patients, 9.5 % in patients with renal dysfunction, and 44.4 % when acute renal failure developed (p
Yundai Chen - One of the best experts on this subject based on the ideXlab platform.
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application of arima model in prediction of Mortality Rate of suicide in hainan province
Chinese journal of epidemiology, 2018Co-Authors: Yunning Liu, Yundai ChenAbstract:Objective To analyze the trend of suicide Mortality in residents of Hainan province, and explore the application of time sequence model in the prediction of the Mortality of suicide. Methods The Mortality data of suicide in residents of Hainan province between January, 2014 and December, 2016 were collected and analyzed with time sequence model and the Mortality Rate of suicide during January-June, 2017 in Hainan was predicted with the model. Results During January, 2014 to June 2017, a total of 576 suicide cases were reported in Hainan, the Mortality Rate was 1.5/100 000. The established ARIMA model had good fitting for the suicide Mortality in previous times and the prediction result was quite similar to the actual Mortality, the predicted Mortality Rate was within the 95% confidence interval of the actual Rate. Conclusion The time sequence model for the prediction of suicide Mortality in Hainan was "ARIMA (0, 1, 0) (0, 0, 0) 12" , and the prediction effect of the model was better, which can be used to predict the suicide Mortality in Hainan. Key words: Suicide; Injury; Time sequence
Kevin B. Weiss - One of the best experts on this subject based on the ideXlab platform.
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Mortality Rate in veterans with multiple chronic conditions
Journal of General Internal Medicine, 2007Co-Authors: Todd A. Lee, Alexandra E. Shields, Christine Vogeli, Teresa B. Gibson, Min Woong-sohn, William D. Marder, David Blumenthal, Kevin B. WeissAbstract:Background Among patients with multiple chronic conditions, there is increasing appreciation of the complex interrelatedness of diseases. Previous studies have focused on the prevalence and economic burden associated with multiple chronic conditions, much less is known about the Mortality Rate associated with specific combinations of multiple diseases.
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Mortality Rate in veterans with multiple chronic conditions.
Journal of general internal medicine, 2007Co-Authors: Todd A. Lee, Alexandra E. Shields, Christine Vogeli, Teresa B. Gibson, Min Woong-sohn, William D. Marder, David Blumenthal, Kevin B. WeissAbstract:Among patients with multiple chronic conditions, there is increasing appreciation of the complex interrelatedness of diseases. Previous studies have focused on the prevalence and economic burden associated with multiple chronic conditions, much less is known about the Mortality Rate associated with specific combinations of multiple diseases. Measure the Mortality Rate in combinations of 11 chronic conditions. Cohort study of veteran health care users. Veterans between 55 and 64 years that used Veterans Health Administration health care services between October 1999 and September 2000. Patients were identified as having one or more of the following: COPD, diabetes, hypertension, rheumatoid arthritis, osteoarthritis, asthma, depression, ischemic heart disease, dementia, stroke, and cancer. Mutually exclusive combinations of disease based on these conditions were created, and 5-year Mortality Rates were determined. There were 741,847 persons included. The number in each group by a count of conditions was: none = 217,944 (29.34%); 1 = 221,111 (29.8%); 2 = 175,228 (23.6%); 3 = 86,447 (11.7%); and 4+ = 41,117 (5.5%). The 5-year Mortality Rate by the number of conditions was: none = 4.1%; 1 = 6.0%; 2 = 7.8%; 3 = 11.2%; 4+ = 16.7%. Among combinations with the same number of conditions, there was significant variability in Mortality Rates. Patients with multiple chronic conditions have higher Mortality Rates. Because there was significant variation in Mortality across clusters with the same number of conditions, when studying patients with multiple coexisting illnesses, it is important to understand not only that several conditions may be present but that specific conditions can differentially impact the risk of Mortality.
