Biomedical subjects

G E Hatzakis

Publications and source records attributed to G E Hatzakis.

9 recordsLinked to original sources

PubMed2005

Selection of molecular descriptors with artificial intelligence for the understanding of HIV-1 protease peptidomimetic inhibitors-activity.

Quantitative Structure Activity Relationship (QSAR) techniques are used routinely by computational chemists in drug discovery and development to analyze datasets of compounds. Quantitative numerical methods like Partial Least Squares (PLS) and Artificial Neural Networks (ANN) have been used on QSAR to establish correlations between molecular properties and bioactivity. However, ANN may be advantageous over PLS because it considers the interrelations of the modeled variables. This study focused on the HIV-1 Protease (HIV-1 Pr) inhibitors belonging to the peptidomimetic class of compounds. The main objective was to select molecular descriptors with the best predictive value for antiviral potency (Ki). PLS and ANN were used to predict Ki activity of HIV-1 Pr inhibitors and the results were compared. To address the issue of dimensionality reduction, Genetic Algorithms (GA) were used for variable selection and their performance was compared against that of ANN. Finally, the structure of the optimum ANN achieving the highest Pearson's-R coefficient was determined. On the basis of Pearson's-R, PLS and ANN were compared to determine which exhibits maximum performance. Training and validation of models was performed on 15 random split sets of the master dataset consisted of 231 compounds. For each compound 192 molecular descriptors were considered. The molecular structure and constant of inhibition (Ki) were selected from the NIAID database. Study findings suggested that non-covalent interactions such as hydrophobicity, shape and hydrogen bonding describe well the antiviral activity of the HIV-1 Pr compounds. The significance of lipophilicity and relationship to HIV-1 associated hyperlipidemia and lipodystrophy syndrome warrant further investigation.

Algorithms↗

PubMed2003

Weaning infants with respiratory syncytial virus from mechanical ventilation through a fuzzy-logic controller.

We have previously developed a fuzzy logic controller for weaning adults with chronic obstructive pulmonary disease using pressure support ventilation (PSV). We used the core of our fuzzy logic-based weaning platform and further developed parametrizable components for weaning newborns of differing body size and disease-state. The controller was validated on neonates recovering from congenital heart disease (CHD) while receiving synchronous intermittent mandatory ventilation (SIMV). We wished to compare the efficacy of this controller versus the bedside weaning protocol in children with respiratory syncytial virus pneumonitis/bronchiolitis (RSV) in the pediatric intensive care unit (PICU). The fuzzy controller evaluated the "current" and "trend" weaning status of the newborn to quantitatively determine the change in the SIMV integrated ventilatory setting. For the "current" status it used heart rate (HR), respiratory rate (RR), tidal volume (VT) and oxygen saturation (SaO2), while for the "trend" status the differences of deltaRR/ deltat, deltaHR/ deltat, and deltaSaO2/ deltat recorded between two subsequent time points were utilized. The enumerated vital signs were fuzzified and then probability levels of occurrence were assigned. Individualized "golden" goals for SaO2 were set for each newborn. We retrospectively assessed the charts of 19 newborns, 113+/-128 days old, 5,546+/-2,321 gr body weight, weaning for 99+/-46 days, at 2-hour intervals. The SIMV levels proposed by the fuzzy controller were matched to those levels actually applied. In 60% of the time both values coincided. For the remaining 40%, the controller was more aggressive suggesting lower values of SIMV than the applied ones. The Area under the SIMV curves over time was 1,969+/-1,044 for the applied vs 1,886+/-978 for the suggested levels, respectively. The fuzzy controller adjusted for body size and disease-pattern can approximate the actual weaning course of newborns with RSV.

Female↗

PubMed2002

Fuzzy logic controller for weaning neonates from mechanical ventilation.

Weaning from mechanical ventilation is the gradual detachment from any ventilatory support till normal spontaneous breathing can be fully resumed. To date, we have developed a fuzzy logic controller for weaning COPD adults using pressure support ventilation (PS). However, adults and newborns differ in the pathophysiology of lung disease. We therefore used our fuzzy logic-based weaning platform to develop modularized components for weaning newborns with lung disease. Our controller uses the heart rate (HR), respiratory rate (RR), tidal volume (VT) and oxygen saturation (SaO2) and their trends deltaHR/deltat, deltaVT/deltat and deltaSaO2/deltat to evaluate, respectively, the Current and Trend weaning status of the newborn. Through appropriate fuzzification of these vital signs, Current and Trend weaning status can quantitatively determine the increase/decrease in the synchronized intermittent mandatory ventilation (SIMV) setting. The post-operative weaning courses of 10 newborns, 82+/-162 days old, were assessed at 2-hour intervals for 68+/-39 days. The SIMV levels, proposed by our algorithm, were matched to those levels actually applied. For 60% of the time both values coincided. For the remaining 40%, our algorithm suggested lower SIMV support than what was applied. The Area Under the Curve for integrated ventilatory support over time was 1203+/-846 for standard ventilatory strategies and 1152+/-802 for fuzzy controller. This suggests that the algorithm, approximates the actual weaning progression, and may advocate a more aggressive strategy. Moreover, the core of the fuzzy controller facilitates adaptation for body size and diversified disease patterns and sets the premises as an infant-weaning tool.

Area Under Curve↗

PubMed2002

Neural networks morbidity and mortality modeling during loss of HIV T-cell homeostasis.

Despite the proven clinical benefits of HAART, mortality may still occur; particularly in those with less than 50 CD4+ cells/mL and, in some cases, with a viral burden below detectable plasma levels of HIV-1 RNA. Multiple factors may predict mortality including initial response to therapy, viral factors and host immune parameters. Due to the complexity of this problem, we developed Artificial Intelligence based tools/Neural Network (NN) to optimally evaluate outcomes of therapy and predict morbidity and mortality. To further validate the accuracy of these tools, we challenged their performance with that of Cox regression modeling (RM). Our study population involved 116 HIV+ individuals who consistently maintained CD4+ count < 50 cells/mL for over 6 months. All patients were treated with antiretrovirals. To assess clinical outcomes, we developed a feedforward back-propagation Neural Network. We then compared the performance of this network to a Cox regression model. The Neural Network outscored the Cox regression model in the ROC curve areas: 0.888 vs 0.760 (HIV+ first Seropositivity to AIDS), 0.901 vs 0.758 (HIV+ first Seropositivity to Last Assessment incl. death) and 0.832 vs 0.799 (AIDS to Last Assessment incl. death), for the NN & Cox, respectively. In patients with a history of AIDS defining events and with severe T-Cell depletion, mortality occurs despite therapy. Although Neural Networks and Cox modeling were successful in predicting mortality, the Neural Network was superior in assessing risk in this population.

Biomarkers↗

PubMed2001

Improvement of HIV-specific immunity in HIV-infected twins treated with highly active antiretroviral therapy, interleukin 2, and syngeneic adoptively transferred cells.

Five HIV-seropositive twins were treated with HAART and given cycles of treatment consisting of adoptive cellular therapy from their HIV-seronegative identical twins followed by a 5-day course of intravenous IL-2. Changes in absolute and percent CD4(+) and CD8(+) cell count were monitored and compared with changes in these parameters occurring in seven age-, sex-, and disease stage-matched HIV-infected patients treated with HAART alone. Increase in the magnitude and breadth of HIV-specific immune responses was monitored in three twin subjects who received multiple treatment cycles. Absolute and percent CD4(+) cell counts rose dramatically and to significantly higher levels in the recipient twins than in control subjects treated with HAART only. The subjects who received multiple cycles of treatment developed new and increased levels of HIV-specific activated and memory cytotoxic T lymphocyte responses, and interferon gamma-secreting effector cells. Treatment consisting of HAART, adoptive cellular therapy, and IL-2 was superior to treatment with HAART alone for improving absolute and percent CD4(+) cell counts and inducing new, or increasing the magnitude of, HIV-specific immune responses in HIV infected patients.

Adult↗

PubMed2001

Fuzzy logic and mechanical ventilation.

Closed-loop control can achieve appropriate ventilation of the lungs in a healthy person by involving the continuous interaction of three components: sensors, controllers, and effectors. The sensors are the chemo-mechanoreceptors, which continuously monitor key bodily functions affected by ventilation. This information is relayed to the controllers, the respiratory centers in the brain, allowing them to determine how actual ventilation compares with that needed by the body. Finally, the controllers direct the effectors, the muscles of respiration, to adjust the ventilation accordingly. When a patient is in respiratory failure, the effector's role is taken over by a mechanical ventilator. The issue that is considered in this article is how the physician might be taken out of the feedback loop.

Algorithms↗

PubMed1999

Automatic control of pressure support mechanical ventilation using fuzzy logic.

There is currently no universally accepted approach to weaning patients from mechanical ventilation, but there is clearly a feeling within the medical community that it may be possible to formulate the weaning process algorithmically in some manner. Fuzzy logic seems suited this task because of the way it so naturally represents the subjective human notions employed in much of medical decision-making. The purpose of the present study was to develop a fuzzy logic algorithm for controlling pressure support ventilation in patients in the intensive care unit, utilizing measurements of heart rate, tidal volume, breathing frequency, and arterial oxygen saturation. In this report we describe the fuzzy logic algorithm, and demonstrate its use retrospectively in 13 patients with severe chronic obstructive pulmonary disease, by comparing the decisions made by the algorithm with what actually transpired. The fuzzy logic recommendations agreed with the status quo to within 2 cm H(2)O an average of 76% of the time, and to within 4 cm H(2)O an average of 88% of the time (although in most of these instances no medical decisions were taken as to whether or not to change the level of ventilatory support). We also compared the predictions of our algorithm with those cases in which changes in pressure support level were actually made by an attending physician, and found that the physicians tended to reduce the support level somewhat more aggressively than the algorithm did. We conclude that our fuzzy algorithm has the potential to control the level of pressure support ventilation from ongoing measurements of a patient's vital signs.

Adult↗

PubMed1996

Short-time neutron activation gamma-ray spectroscopy.

Short-time instrumental neutron activation analysis, with high throughput, sensitivity and accuracy without matrix interferences, can be achieved in spite of the initial high count rate from both short and long-lived nuclide activation, if the experimental conditions are optimized by the combination of techniques. Thus the initial usually high counting rate can be faced by a loss-free counting system to avoid blocking or distortion of the system. The rapid radioactive decay and the consequent low counting statistics of short lived nuclides can be compensated by source-detector distance variation during the counting period and by cyclic and cumulative activation. Matrix spectral interferences can be reduced by ion exchange before activation for selective element preseparation and by neutron spectrum optimization such as epithermal neutron activation for selective element peak enhancement.

Journal Article↗

PubMedDate not supplied

The natural history of leukocyturia associated with indinavir treatment in HIV+ individuals.

Urinary complications observed during indinavir treatment of HIV disease are often attributed to indinavir crystalluria. In a prospective study of urinalysis during the first year of indinavir therapy, 5 of 54 asymptomatic HIV+ individuals presented severe leukocyturia (> or =100 cells/HPF) usually accompanying indinavir crystalluria. The clinical course of these 5 individuals, successfully treated for HIV and monitored for an second follow-up year, suggests that recurrence of severe leukocyturia may be an indicator of renal damage, likely tubulointerstitial disease caused by indinavir crystalluria. This is in contrast to the remaining 49 subjects, including those presenting mild leukocyturia, who did not demonstrate any evidence of renal disease. Regular urinalysis is therefore recommended in the clinical management of indinavir-treated individuals to detect early renal damage secondary to indinavir crystalluria and to prevent further renal impairment.

Adult↗