University of Alabama

About: University of Alabama is a education organization based out in Tuscaloosa, Alabama, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 27323 authors who have published 48609 publications receiving 1565337 citations. The organization is also known as: Alabama & Bama.

Mapping and predicting mortality from systemic sclerosis

Abstract: Objectives To determine the causes of death and risk factors in systemic sclerosis (SSc). Methods Between 2000 and 2011, we examined the death certificates of all French patients with SSc to determine causes of death. Then we examined causes of death and developed a score associated with all-cause mortality from the international European Scleroderma Trials and Research (EUSTAR) database. Candidate prognostic factors were tested by Cox proportional hazards regression model by single variable analysis, followed by a multiple variable model stratified by centres. The bootstrapping technique was used for internal validation. Results We identified 2719 French certificates of deaths related to SSc, mainly from cardiac (31%) and respiratory (18%) causes, and an increase in SSc-specific mortality over time. Over a median follow-up of 2.3 years, 1072 (9.6%) of 11 193 patients from the EUSTAR sample died, from cardiac disease in 27% and respiratory causes in 17%. By multiple variable analysis, a risk score was developed, which accurately predicted the 3-year mortality, with an area under the curve of 0.82. The 3-year survival of patients in the upper quartile was 53%, in contrast with 98% in the first quartile. Conclusion Combining two complementary and detailed databases enabled the collection of an unprecedented 3700 deaths, revealing the major contribution of the cardiopulmonary system to SSc mortality. We also developed a robust score to risk-stratify these patients and estimate their 3-year survival. With the emergence of new therapies, these important observations should help caregivers plan and refine the monitoring and management to prolong these patients’ survival.

Alternative Hierarchies of the Attitude-Behavior Relationship: The Impact of Brand Commitment and Habit

Abstract: The theory of reasoned action and the low-involvement hierarchy model were tested using cross-lagged panel correlation. It was proposed that the low-involvement hierarchy model would more accurately reflect the behavior of low-brand-committed individuals and that the theory of reasoned action would more accurately reflect the behavior of high-brand-committed individuals. Although the findings did not completely support these hypotheses, the general thrusts of the hypotheses appear to be supported. Additionally, behavior was hypothesized and shown to influence habit for all individuals.

Death, detritus, and energy flow in aquatic ecosystems

Abstract: SUMMARY 1. Pelagic trophic structure and energy fluxes are evaluated predominantly on the basis of ingestion of particulate organic matter by living organisms and the effects of consumption on the population dynamics of trophic levels. 2. Population fluxes are not representative of the material and energy fluxes of either the composite pelagic region or the lake ecosystem. Metabolism of particulate and especially dissolved organic detritus from many pelagic and non-pelagic autochthonous and from allochthonous sources dominates both material and energy fluxes. Because of the very large magnitudes and relative chemical recalcitrance of these detrital sources, the large but slow metabolism of detritus provides an inherent ecosystem stability that energetically dampens the ephemeral, volatile fluctuations of higher trophic levels. 3. The annual time period is the only meaningful interval in comparative quantitative analyses of material and energy fluxes at population, community, and ecosystem levels. 4. Non-predatory death and metabolism by prokaryotic and protistian heterotrophs dominate. Continued application of animal-orientated relationships to the integrated, process-driven couplings of the aquatic ecosystems impedes understanding of quantitative ecosystem pathways and control mechanisms.