Transcriptional Errors in Human Immunodeficiency Virus Type 1 Generate Targets for T-Cell Responses

We measured T-cell responses to human immunodeficiency virus type 1 (HIV-1) cryptic epitopes encoded by regions of the viral genome not normally translated into viral proteins. T-cell responses to cryptic epitopes and to regions normally spliced out of the HIV-1 viral proteins Rev and Tat were detected in HIV-1-infected subjects.

Suicide behavior and neuropsychological assessment of type I bipolar patients

Background: Neuropsychological deficits are often described in patients with bipolar disorder (BID). Some symptoms and/or associated characteristics of BD can be more closely associated to those cognitive impairments. We aimed to explore cognitive neuropsychological characteristics of type I bipolar patients (BPI) in terms Of lifetime Suicide attempt history. Method: We studied 39 BPI Outpatients compared with 53 healthy controls (HC) matched by age, educational and intellectual level. All Subjects were submitted to a neuropsychological assessment of executive functions, decision-making and declarative episodic memory. Results: When comparing BD1 patients, regardless of suicide attempt history or HC, we observed that bipolar patients performed worse than controls oil measures of memory, attention, executive functions and decision-making, Patients with a history of suicide attempt performed worse than non-attempters on measures of decision-making and there were a significant negative correlation between the number of suicide attempts and decision-making results (block 3 and net score). We also found significant Positive correlation between the number Of Suicide attempts and amount Of errors in Stroop Color Word Test (part 3). Limitations: The sample Studied call be considered small and a potentially confounding variable - medication status - were not controlled. Conclusion: Our results show the presence of neuropsychological deficits in memory, executive functions, attention and decision-making in BPI patients. Suicide attempts BPI scored worse than non-suicide attempt Bill oil measures of decision-making. More suicide attempts were associated with a worse decision-making process. Future research should explore the relationship between the association between this specific cognitive deficits in BPIs, serotonergic function and suicide behavior in bipolar patients as well other diagnostic groups. (C) 2009 Elsevier B.V. All rights reserved.

A decision support system to facilitate management of patients with acute gastrointestinal bleeding

Objective: To develop a model to predict the bleeding source and identify the cohort amongst patients with acute gastrointestinal bleeding (GIB) who require urgent intervention, including endoscopy. Patients with acute GIB, an unpredictable event, are most commonly evaluated and managed by non-gastroenterologists. Rapid and consistently reliable risk stratification of patients with acute GIB for urgent endoscopy may potentially improve outcomes amongst such patients by targeting scarce health-care resources to those who need it the most. Design and methods: Using ICD-9 codes for acute GIB, 189 patients with acute GIB and all. available data variables required to develop and test models were identified from a hospital medical records database. Data on 122 patients was utilized for development of the model and on 67 patients utilized to perform comparative analysis of the models. Clinical data such as presenting signs and symptoms, demographic data, presence of co-morbidities, laboratory data and corresponding endoscopic diagnosis and outcomes were collected. Clinical data and endoscopic diagnosis collected for each patient was utilized to retrospectively ascertain optimal management for each patient. Clinical presentations and corresponding treatment was utilized as training examples. Eight mathematical models including artificial neural network (ANN), support vector machine (SVM), k-nearest neighbor, linear discriminant analysis (LDA), shrunken centroid (SC), random forest (RF), logistic regression, and boosting were trained and tested. The performance of these models was compared using standard statistical analysis and ROC curves. Results: Overall the random forest model best predicted the source, need for resuscitation, and disposition with accuracies of approximately 80% or higher (accuracy for endoscopy was greater than 75%). The area under ROC curve for RF was greater than 0.85, indicating excellent performance by the random forest model Conclusion: While most mathematical models are effective as a decision support system for evaluation and management of patients with acute GIB, in our testing, the RF model consistently demonstrated the best performance. Amongst patients presenting with acute GIB, mathematical models may facilitate the identification of the source of GIB, need for intervention and allow optimization of care and healthcare resource allocation; these however require further validation. (c) 2007 Elsevier B.V. All rights reserved.