A Novel Embedded Feature Selection and Dimensionality Reduction Method for an SVM Type Classifier to Predict Periventricular Leukomalacia (PVL) in Neonates.

This paper is concerned with the prediction of the occurrence of periventricular leukomalacia (PVL) in neonates after heart surgery. Our prior work shows that the Support Vector Machine (SVM) classifier can be a powerful tool in predicting clinical outcomes of such complicated and uncommon diseases, even when the number of data samples is low. In the presented work, we first illustrate and discuss the shortcomings of the traditional automatic machine learning (aML) approach. Consequently, we describe our methodology for addressing these shortcomings, while utilizing the designed interactive ML (iML) algorithm. Finally, we conclude with a discussion of the developed method and the results obtained. In sum, by adding an additional (Genetic Algorithm) optimization step in the SVM learning framework, we were able to (a) reduce the dimensionality of an SVM model from 248 to 53 features, (b) increase generalization that was confirmed by a 100% accuracy assessed on an unseen testing set, and (c) improve the overall SVM model's performance from 65% to 100% testing accuracy, utilizing the proposed iML method.

Automatic Detection of Endotracheal Intubation During the Anesthesia Procedure.

This paper is concerned with the mathematical modeling and detection of endotracheal (ET) intubation in children under general anesthesia during surgery. In major pediatric surgeries, the airway is often secured with an endotracheal tube (ETT) followed by initiation of mechanical ventilation. Clinicians utilize auscultation of breath sounds and capnography to verify correct ETT placement. However, anesthesia providers often delay timely charting of ET intubation. This latency in event documentation results in decreased efficacy of clinical decision support systems. In order to target this problem, we collected real inpatient data and designed an algorithm to accurately detect the intubation time within the clinically valid range; the results show that we are able to achieve high accuracy in more than 96% of the cases. Automatic detection of ET intubation time would thus enhance better real-time data capture to support future improvement in clinical decision support systems.

Application of Mathematical Modeling for Simulation and Analysis of Hypoplastic Left Heart Syndrome (HLHS) in Pre- and Postsurgery Conditions.

This paper is concerned with the mathematical modeling of a severe and common congenital defect called hypoplastic left heart syndrome (HLHS). Surgical approaches are utilized for palliating this heart condition; however, a brain white matter injury called periventricular leukomalacia (PVL) occurs with high prevalence at or around the time of surgery, the exact cause of which is not known presently. Our main goal in this paper is to study the hemodynamic conditions under which HLHS physiology may lead to the occurrence of PVL. A lumped parameter model of the HLHS circulation has been developed integrating diffusion modeling of oxygen and carbon dioxide concentrations in order to study hemodynamic variables such as pressure, flow, and blood gas concentration. Results presented include calculations of blood pressures and flow rates in different parts of the circulation. Simulations also show changes in the ratio of pulmonary to systemic blood flow rates when the sizes of the patent ductus arteriosus and atrial septal defect are varied. These changes lead to unbalanced blood circulations and, when combined with low oxygen and carbon dioxide concentrations in arteries, result in poor oxygen delivery to the brain. We stipulate that PVL occurs as a consequence.

Prediction of periventricular leukomalacia occurrence in neonates after heart surgery.

This paper is concerned with predicting the occurrence of periventricular leukomalacia (PVL) using vital and blood gas data which are collected over a period of 12 h after the neonatal cardiac surgery. A data mining approach has been employed to generate a set of rules for classification of subjects as healthy or PVL affected. In view of the fact that blood gas and vital data have different sampling rates, in this study we have divided the data into two categories: 1) high resolution (vital), and 2) low resolution (blood gas), and designed a separate classifier based on each data category. The developed algorithm is composed of several stages; first, a feature pool has been extracted from each data category and the extracted features have been ranked based on the data reliability and their mutual information content with the output. An optimal feature subset with the highest discriminative capability has been formed using simultaneous maximization of the class separability measure and mutual information of a set. Two separate decision trees (DTs) have been developed for the classification purpose and more importantly to discover hidden relationships that exist among the data to help us better understand PVL pathophysiology. The DT result shows that high amplitude 20 min variations and low sample entropy in the vital data and the defined out of range index as well as maximum rate of change in blood gas data are important factors for PVL prediction. Low sample entropy represents lack of variability in hemodynamic measurement, and constant blood pressure with small fluctuations is an important indicator of PVL occurrence. Finally, using the different time frames of data collection, we show that the first 6 h of data contain sufficient information for PVL occurrence prediction.

Discovering hidden relationships in physiological signals for prediction of Periventricular Leukomalacia.

This paper is concerned with predicting the occurrence of Periventricular Leukomalacia (PVL) using vital data which are collected over a period of twelve hours after neonatal cardiac surgery. The vital data contain heart rate (HR), mean arterial pressure (MAP), right atrium pressure (RAP), and oxygen saturation (SpO2). Various features are extracted from the data and are then ranked so that an optimal subset of features that have the highest discriminative capabilities can be selected. A decision tree (DT) is then developed for the vital data in order to identify the most important vital measurements. The DT result shows that high amplitude 20 minutes variations and low sample entropy in the data is an important factor for prediction of PVL. Low sample entropy represents lack of variability in hemodynamic measurement, and constant blood pressure with small fluctuations is an important indicator of PVL occurrence. Finally, using the different time frames of the collected data, we show that the first six hours of data contain sufficient information for PVL occurrence prediction.

Application of decision tree in the prediction of periventricular leukomalacia (PVL) occurrence in neonates after heart surgery.

This paper is concerned with the prediction of the occurrence of periventricular leukomalacia (PVL) that occurs in neonates after heart surgery. The data which is collected over a period of 12 hours after cardiac surgery contains vital measurements as well as blood gas measurements with different resolutions. Vital data measured using near-inferred spectroscopy (NIRS) at the sampling rate of 0.25 Hz and blood gas measurement up to 12 times with irregular time intervals for 35 patients collected at Children's Hospital of Philadelphia (CHOP) are used for this study. Features derived from the data include statistical moments (mean, variance, skewness and kurtosis), trend and minimum and maximum values of the vital data and rate of change, time weighted mean and a custom defined out of range index (ORI) for the blood gas data. A decision tree is developed for the vital data in order to identify the most important vital measurements. In addition, a decision tree is developed for blood gas data to find important factors for the prediction of PVL occurrence. Results show that in the blood gas data, maximum rate of change of concentration of bicarbonate ions in blood (HCO(3)) and minimum rate of change of partial pressure of dissolved CO(2) in the blood (PaCO(2)) are the two most important factors for prediction of the PVL. Also important are the kurtosis of heart rate and hemoglobin values.

Receptors for prostaglandin E(2) that regulate cellular immune responses in the mouse.

Production of prostaglandin E(2) (PGE(2)) is enhanced during inflammation, and this lipid mediator can dramatically modulate immune responses. There are four receptors for PGE(2) (EP1-EP4) with unique patterns of expression and different coupling to intracellular signaling pathways. To identify the EP receptors that regulate cellular immune responses, we used mouse lines in which the genes encoding each of the four EP receptors were disrupted by gene targeting. Using the mixed lymphocyte response (MLR) as a model cellular immune response, we confirmed that PGE(2) has potent antiproliferative effects on wild-type responder cells. The absence of either the EP1 or EP3 receptors did not alter the inhibitory response to PGE(2) in the MLR. In contrast, when responder cells lacked the EP2 receptor, PGE(2) had little effect on proliferation. Modest resistance to PGE(2) was also observed in EP4-/- responder cells. Reconstitution experiments suggest that EP2 receptors primarily inhibit the MLR through direct actions on T cells. Furthermore, PGE(2) modulates macrophage function by activating the EP4 receptor and thereby inhibiting cytokine release. Thus, PGE(2) regulates cellular immune responses through distinct EP receptors on different immune cell populations: EP2 receptors directly inhibit T cell proliferation while EP2 and EP4 receptors regulate antigen presenting cells functions.

A role for fractalkine and its receptor (CX3CR1) in cardiac allograft rejection.

The hallmark of acute allograft rejection is infiltration of the inflamed graft by circulating leukocytes. We studied the role of fractalkine (FKN) and its receptor, CX(3)CR1, in allograft rejection. FKN expression was negligible in nonrejecting cardiac isografts but was significantly enhanced in rejecting allografts. At early time points, FKN expression was particularly prominent on vascular tissues and endothelium. As rejection progressed, FKN expression was further increased, with prominent anti-FKN staining seen around vessels and on cardiac myocytes. To determine the capacity of FKN on endothelial cells to promote leukocyte adhesion, we performed adhesion assays with PBMC and monolayers of TNF-alpha-activated murine endothelial cells under low-shear conditions. Treatment with either anti-FKN or anti-CX(3)CR1-blocking Ab significantly inhibited PBMC binding, indicating that a large proportion of leukocyte binding to murine endothelium occurs via the FKN and CX(3)CR1 adhesion receptors. To determine the functional significance of FKN in rejection, we treated cardiac allograft recipients with daily injections of anti-CX(3)CR1 Ab. Treatment with the anti-CX(3)CR1 Ab significantly prolonged allograft survival from 7 +/- 1 to 49 +/- 30 days (p < 0.0008). These studies identify a critical role for FKN in the pathogenesis of acute rejection and suggest that FKN may be a useful therapeutic target in rejection.

The adjacent flanking region plays a critical role in facilitating the presentation of the Listeria monocytogenes product lemA to H2 M3wt-restricted, peptide-specific murine CD8 cells.

Mice infected with Listeria monocytogenes (LM) generate CD8 effectors specific for f-MIGWII, the amino terminus of the bacterial product lemA presented by the class Ib MHC molecule H2 M3wt. lemA has several distinctive properties: 1) it is readily presented as an exogenous Ag in the absence of bacterial infection; 2) it is processed by a TAP-independent pathway, which is sensitive to chloroquine, pepstatin, and brefeldin; and 3) the immunogenic portion of the molecule is extremely resistant to proteolytic degradation even by proteinase K. To assess the structural basis for these findings, we expressed a truncated variant (t-lemA) containing the amino-terminal hexapeptide and the subsequent 27 amino acids linked to a histidine tail in Escherichia coli, and purified the product by affinity chromatography. Purified t-lemA could be presented to f-MIGWII-specific effectors by macrophages and fibroblasts at 1-10 nM. Unlike f-MIGWII, which binds directly to H2 M3wt, t-lemA required processing by a chloroquine-, pepstatin-, and brefeldin-sensitive pathway. Brefeldin sensitivity often implies endogenous processing in the cytoplasm, but several lines of evidence suggest translocation to the cytoplasm and proteosomal degradation are not critical for t-lemA presentation. Unlike f-MIGWII, t-lemA was profoundly resistant to proteinase K, and, using 35S-labeled t-lemA, we could identify the region from position 1 to approximately 30 as the protease-resistant element. Thus, the hydrophobic peptide sequence following f-MIGWII can account for the unusual properties of lemA noted above. Analogous modification could be used to alter the properties of other peptide Ags presented by class I MHC products.

Intraperitoneal immunity and pneumoperitoneum.

BACKGROUND: Carbon dioxide (CO(2)) pneumoperitoneum has been implicated as a possible factor in depressed intraperitoneal immunity. Using in vitro functional assays, CO(2) has been shown to decrease the function of peritoneal macrophages harvested from insufflated mice. However, an effective in vivo assessment is lacking. Listeria monocytogenes (LM), an intracellular pathogen, has served as a well-established in vivo model to study cell-mediated immune responses in mice. This study examines the immune competence of mice based on their ability to clear intraperitoneally administered LM following CO(2) vs helium (He) insufflation. METHODS: Eighty-five mice (C57Bl/6, males, 4-6 weeks old) were divided between the following four treatment groups: CO(2) insufflation, He insufflation, abdominal laparotomy (Lap), and control (anesthesia only). Immediately postoperatively, each group was inoculated percutaneously and intraperitoneally with a sublethal dose (.015 x 10(6) org) of virulent LM (EGD strain). Half of the animals were killed on postoperative day 3 and half on day 5. Spleens and livers (sites of bacterial predilection) were harvested, homogenized, and plated on TSB agar. The amount of bacteria (1 x 10(6) LM/spleen and liver) from each group was then compared. Statistical significance was set at p

H2M3wt-restricted, Listeria monocytogenes-immune CD8 T cells respond to multiple formylated peptides and to a variety of gram-positive and gram-negative bacteria.

A subset of H2M3wt-restricted, Listeria monocytogenes (LM)-immune CD8 effectors recognize antigen-presenting cells (APC) preincubated with heat-killed LM. The responsible product, which we have previously designated heat-killed Listeria-associated antigen (HAA), is extremely hydrophobic and resistant to proteolytic degradation. Despite the protease resistance of HAA, we now report that HAA-immune clones are uniformly responsive to fMIGWII, a formylated oligopeptide derived from the recently described LM product, lemA. While fMIGWII was by far the most potent peptide tested, over half our clones also responded to the LM-derived peptide fMIVII and cross-reactive responses to two other unrelated formylated peptides at concentrations of <1 microM were frequently observed. One of these peptides (fBlaZ) did not share any amino acid in common with fMIGWII except N-formyl methionine at position 1. Unformylated variants of the same peptides were inactive. HAA-immune CD8 cells also responded in an H2M3wt-restricted manner to APC pretreated with heat-killed or live preparations of other gram-positive and gram-negative bacteria such as Streptococcus pyogenes (SP) and Proteus vulgaris (PV). Unlike fMIGWII which is water soluble and protease sensitive, the native antigens extracted from SP and PV, like HAA, were very hydrophobic and proteinase K resistant, presumably reflecting in each case the association of cross-reactive polypeptides with bacterial lipid or phospholipid. Thus, HAA/lemA-immune, H2M3wt-restricted effectors can respond to a variety of formylated peptides and bacterial antigens in vitro. Similar cross-reactions in vivo might have physiologically significant implications.

H2-M3wt-restricted, Listeria monocytogenes-specific CD8 T cells recognize a novel, hydrophobic, protease-resistant, periodate-sensitive antigen.

Mice infected with Listeria monocytogenes (LM) generate H2-M3wt-restricted CD8 effectors which recognize a heat-killed LM-associated antigen (HAA) presented by macrophages. To characterize HAA, we extracted a bioactive component from LM using SDS or NaOH. Extracted HAA aggregated in hydrophilic solvents but dissociated in the presence of SDS into a smaller subunit which migrated in Sephadex G-200 between chymotrypsinogen (25 kDa) and cytochrome c (12.5 kDa). HAA bioactivity and size was unaffected by proteinase K under conditions which degraded virtually all detectable protein. HAA was also unaffected by other proteases, RNase and DNase, but HAA bioactivity was destroyed by periodate, an agent that degrades carbohydrates. These studies demonstrate that H2-M3wt can present a hydrophobic, non-peptide, microbial antigen, probably glycolipid in origin, to CD8 T cells.

Bovine x murine T-cell hybridomas specific for bovine herpesvirus 1 (BHV-1) glycoproteins.

Difficulties in the isolation and long-term maintenance of bovine herpesvirus-1 (BHV-1) specific T-cell clones have hindered the analysis of bovine cell-mediated immune response to this virus. In an effort to identify the T-cell epitopes of the virus, bovine murine T-cell hybridomas specific for BHV-1 were generated as an alternative to T-cell clones. Peripheral blood lymphocytes from a calf immunized with BHV-1 were restimulated in vitro with the virus to generate bulk T-cell cultures. The antigen-specific T-cell-enriched bulk culture lymphocytes were fused with the T-cell receptor-deficient mutant of the murine thymoma cell line BW 5147. T-cell hybridomas were screened for their ability to produce interferon-gamma in response to BHV-1 stimulation. Hybridomas with various specificities were obtained. One of them was specific for the BHV-1 glycoprotein gI, two were specific for gIV, while three other hybridomas were specific for gIII. One hybridoma responded to stimulation with BHV-1, but not to any of the glycoproteins gI, gIII, or gIV, suggesting that proteins other than these major glycoproteins may be involved in the bovine T-cell response to BHV-1. Of these hybridomas, one was MHC Class I restricted, while all the others were Class II restricted.