PubMed · 13523207
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D C McPHAIL, J A CAMPBELL. 1958-04-12. Acute appendicitis.. https://doi.org/10.1136/bmj.1.5075.852
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Programmed cell death or apoptosis is a physiologically important process in neurogenesis wherein approximately 50% of the neurons apoptose during maturation of the nervous system. However, premature apoptosis and/or aberrations in apoptosis control contribute to the pathogenesis of a variety of neurological disorders including acute brain injury such as trauma, spinal cord injury, ischemic stroke and ischemia/reperfusion as well as chronic disease states such as Alzheimer's, Parkinson's, Huntington's, amyotrophic lateral sclerosis, spinal muscular atrophy, and diabetic neuropathy. The current review will focus on two major topics, namely, the general concepts of our current understanding of the apoptosis death machinery, its mediators and regulation, and the relationship between aberrant apoptosis and genesis of neurodegenerative disorders. This knowledge of apoptosis mechanisms will underpin the basis for development of novel therapeutic strategies and treatment modalities that are directed at control of the neuronal apoptotic death program.
Programmed cell death and survival are controlled by complex pathways, with the anti-apoptotic proteins Bcl-2 and Bcl-X(L) and the pro-apoptotic proteins Bax and Bcl-X(S) being major regulators. Variations in the expression of Bcl-X(S) have been observed in leukemic cells from acute myeloid leukemia (AML) patients and correlated with clinical outcome, but the impact of Bcl-X(S) on molecular pathophysiological mechanisms and the potential role of Bcl-X(S) as a therapeutic target in AML are not yet defined. In order to analyze the functional relevance of Bcl-X(S) in AML, Bcl-X(S) was moderately (2-3 fold) overexpressed in the AML cell lines HL-60 and MO7e by transfection with a tetracycline-regulatable Bcl-X(S) expression system. Increased Bcl-X(S) did not change the rate of spontaneous apoptosis, chemosensitivity to ara-C, or cell cycle kinetics. Further analysis of this unexpected result revealed a compensatory transcriptional upregulation of endogenous anti-apoptotic Bcl-X(L) in MO7e and HL-60, and Bcl-2 in HL-60 cells resulting in increased protein levels. Bax levels were unchanged. Bcl-X(L) and Bcl-2 were found to heterodimerize with Bcl-X(S), thereby providing a possible explanation for the abrogation of its pro-apoptotic function. These results suggest the existence of a regulatory mechanism aimed to protect leukemic cells from pro-apoptotic stimuli.
This study compares a typical heuristic algorithm with classical and Bayesian regression models in ascertaining the presence of acute bronchopulmonary disease events in lung transplant recipients. These models attempt to predict whether an epoch will end in an event, based on the preceding two weeks of data. The data consist of 150 two-week epochs of daily to biweekly spirometry and symptom covariates for 30 subjects over 60 subject-years. Seventy-five 'event' epochs end on a day when an acute bronchopulmonary disease event is documented in the medical record; 75 randomly selected 'non-event' epochs end on a day when no event is documented. The data are partitioned by randomly assigning 15 subjects for training and the remaining 15 subjects for testing. For cross-validation, a second random partition is generated from the same data set. The statistical models are trained and tested on both partitions. For the heuristic algorithm, its historical event classifications on the same test cases are used. Classification performance on both partitions of all models is compared using receiver operating characteristic curves, sensitivity and specificity, and a Shannon information score. Data partition did not appreciably affect statistical model performance. All statistical models, unlike the heuristic algorithm, performed significantly different than chance (family significance < 0.05, Pearson independence chi-square, Bonferroni multiple correction), and better than the heuristic algorithm. The best models were Bayesian changepoint models. Through a clinically oriented discussion, a case classified by all of these algorithms is presented, suggesting the clinical usefulness of the Bayesian approach compared with the classical and heuristic approaches.