Genetic approaches for the identification of apoptotic components

Jun amino-terminal kinase (JNK) mediates a physiological stress signal that leads to cell death. However, the role of the JNK pathway in intrinsic cell death execution mechanisms is largely unknown. In a genetic screen for dominant suppressors of Reaper (Rpr)-induced cell death, we identified Drosophila chromosomal regions that contain genes which are homologous to apoptosis signal-regulating kinase (ASK1) and Drosophila tumor necrosis factor receptor-associated factor 1 (DTRAF1). We present evidence that the killer signal initiates the JNK pathway via proteasome-mediated degradation of Drosophila inhibitor of apoptosis protein 1 (DIAP1) to promote cell death.     

Glucocorticoid interaction with bone marrow lymphoblast receptors in acute leukemia

Translated fromByulleten' Eksperimental'noi Biologii i Meditsiny, Vol. 115, N ^o 4, pp. 164–165, February, 1993.     

Long-term observation (8-10 years) of patients with mild forms of arterial hypertension

The nature of a course of "mild" arterial hypertension was studied in 126 patients for 8-10 yrs. It was shown that in 13.2% of the cases arterial pressure returned to normal values during a "natural" course of disease; border-line arterial hypertension was revealed in 9.4%. Stage II hypertension was diagnosed in 77.4% of the cases after 7-10 yrs. Progression of arterial hypertension was noted in this group in 1/3 of the cases (30.2%). Aggravated heredity and an initial morphological state of the kidneys (according to the results of intravital morphological investigation) were shown to be predictors of prognosis of arterial hypertension. The initial picture of the fundus of the eye and electrocardiographic signs of myocardial hypertrophy reflected the nature of a course of hypertension being not factors determining prognosis of arterial hypertension stabilization.     

Induction of radioresistance to accelerated carbon-ion beams in recipient cells by nitric oxide excreted from irradiated donor cells of human glioblastoma

PURPOSE: To investigate whether nitric oxide excreted from cells irradiated with accelerated carbon-ion beams modulates cellular radiosensitivity against irradiation in human glioblastoma A-172 and T98G cells. MATERIALS AND METHODS: Western-blot analysis of inducible nitric oxide synthase, hsp72 and p53, the concentration assay of nitrite in medium and cell survival assay after irradiation with accelerated carbon-ion beams were performed. RESULTS: The accumulation of inducible nitric oxide synthase was caused by accelerated carbon-ion beam irradiation of T98G cells but not of A-172 cells. The accumulation of hsp72 and p53 was observed in A-172 cells after exposure to the conditioned medium of the T98G cells irradiated with accelerated carbon-ion beams, and the accumulation was abolished by the addition of an inhibitor for inducible nitric oxide synthase to the medium. The radiosensitivity of A-172 cells was reduced in the conditioned medium of the T98G cells irradiated with accelerated carbon-ion beams compared with conventional fresh growth medium, and the reduction of radiosensitivity was abolished by the addition of an inducible nitric oxide synthase inhibitor to the conditioned medium. CONCLUSIONS: Nitric oxide excreted from the irradiated donor cells with accelerated carbon-ion beams could modulate the radiosensitivity of recipient cells. These findings indicate the importance of an intercellular signal transduction pathway initiated by nitric oxide in the cellular response to accelerated heavy ions.     

Automated Continuous Acute Kidney Injury Prediction and Surveillance: A Random Forest Model

ObjectiveTo develop and validate a prediction model of acute kidney injury (AKI) of any severity that could be used for AKI surveillance and management to improve clinical outcomes.Patients and MethodsThis retrospective cohort study was conducted in medical, surgical, and mixed intensive care units (ICUs) at Mayo Clinic in Rochester, Minnesota, including adult (≥18 years of age) ICU-unique patients admitted between October 1, 2004, and April 30, 2011. Our primary objective was prediction of AKI using extant clinical data following ICU admission. We used random forest classification to provide continuous AKI risk score.ResultsWe included 4572 and 1958 patients in the training and validation mutually exclusive cohorts, respectively. Acute kidney injury occurred in 1355 patients (30%) in the training cohort and 580 (30%) in the validation cohort. We incorporated known AKI risk factors and routinely measured vital characteristics and laboratory results. The model was run throughout ICU admission every 15 minutes and achieved an area under the receiver operating characteristic curve of 0.88 on validation. It was 92% sensitive and 68% specific and detected 30% of AKI cases at least 6 hours before the criterion standard time (AKI stages 1-3). For discrimination of AKI stages 2 to 3, the model had 91% sensitivity, 71% specificity, and 53% detection of AKI cases at least 6 hours before AKI onset.ConclusionWe developed and validated an AKI prediction model using random forest for continuous monitoring of ICU patients. This model could be used to identify high-risk patients for preventive measures or identifying patients of prospective interventional trials.