Adherence to host extracellular matrix and serum components by Enterococcus faecium isolates of diverse origin.

Enterococcus faecium has emerged as an important cause of nosocomial infections over the last two decades. We recently demonstrated collagen type I (CI) as a common adherence target for some E. faecium isolates and a significant correlation was found to exist between acm-mediated CI adherence and clinical origin. Here, we evaluated 60 diverse E. faecium isolates for their adherence to up to 15 immobilized host extracellular matrix and serum components. Adherence phenotypes were most commonly observed to fibronectin (Fn) (20% of the 60 isolates), fibrinogen (17%) and laminin (Ln) (13%), while only one or two of the isolates adhered to collagen type V (CV), transferrin or lactoferrin and none to the other host components tested. Adherence to Fn and Ln was almost exclusively restricted to clinical isolates, especially the endocarditis-enriched nosocomial genogroup clonal complex 17 (CC17). Thus, the ability to adhere to Fn and Ln, in addition to CI, may have contributed to the emergence and adaptation of E. faecium, in particular CC17, as a nosocomial pathogen.

Mechanism of dendritic epidermal T cell-mediated tolerance induction and inhibition of proliferation

Dendritic epidermal T cells (DETC) comprise a unique population of T cells that reside in mouse epidermis and whose function remains unclear. Most DETC express a $\gamma\delta$ TCR, although some, including our DETC line, AU16, express an $\alpha\beta$ TCR. Additionally, AU16 cells express CD3, Thy-1, CD45, CD28, B7, and AsGM-1. Previous studies in our laboratory demonstrated that hapten-conjugated AU16 could induce specific immunologic tolerance in vivo and inhibit T cell proliferation in vitro. Both these activities are antigen-specific, and the induction of tolerance is non-MHC-restricted. In addition, AU16 cells are cytotoxic to a number of tumor cell lines in vitro. These studies suggested a role for these cells in immune surveillance. The purpose of my studies was to test the hypothesis that these functions of DETC (tolerance induction, inhibition of T cell proliferation, and tumor cell killing) were mediated by a cytotoxic mechanism. My specific aims were (1) to determine whether AU16 could prevent or delay tumor growth in vivo; and (2) to determine the mechanism whereby AU16 induce tolerance, using an in vitro proliferation assay. I first showed that AU16 cells killed a variety of skin tumor cell lines in vitro. I then demonstrated that they prevented melanoma growth in C3H mice when both cell types were mixed immediately prior to intradermal (i.d.) injection. Studies using the in vitro proliferation assay confirmed that DETC inhibit proliferation of T cells stimulated by hapten-bearing, antigen-presenting cells (FITC-APC). To determine which cell was the target, $\gamma$-irradiated, hapten-conjugated AU16 were added to the proliferation assay on d 4. They profoundly inhibited the proliferation of naive T cells to $\gamma$-irradiated, FITC-APC, as measured by ($\sp3$H) TdR uptake. This result strongly suggested that the T cell was the target of the AU16 activity because no APC were present by d 4 of the in vitro culture. In contrast, the addition of FITC-conjugated splenic T cells (SP-T) or lymph node T cells (LN-T) was less inhibitory. Preincubation of the T cells with FITC-AU16 cells for 24 h, followed by removal of the AU16 cells, completely inhibited the ability of the T cells to proliferate in response to FITC-APC, further supporting the conclusion that the T cell was the target of the AU16. Finally, AU16 cells were capable of killing a variety of activated T cells and T cell lines, arguing that the mechanism of proliferation inhibition, and possibly tolerance induction is one of cytotoxicity. Importantly, $\gamma\delta$ TCR$\sp+$ DETC behaved, both in vivo and in vitro like AU16, whereas other T cells did not. Therefore, these results are consistent with the hypothesis that AU16 cells are true DETC and that they induce tolerance by killing T cells that are antigen-activated in vivo. ^

Statistical characterization and development of summary measures of non-normal distributions of nuclear morphometry data from prostate cancer cells for use as prognostic indicators

Nuclear morphometry (NM) uses image analysis to measure features of the cell nucleus which are classified as: bulk properties, shape or form, and DNA distribution. Studies have used these measurements as diagnostic and prognostic indicators of disease with inconclusive results. The distributional properties of these variables have not been systematically investigated although much of the medical data exhibit nonnormal distributions. Measurements are done on several hundred cells per patient so summary measurements reflecting the underlying distribution are needed.^ Distributional characteristics of 34 NM variables from prostate cancer cells were investigated using graphical and analytical techniques. Cells per sample ranged from 52 to 458. A small sample of patients with benign prostatic hyperplasia (BPH), representing non-cancer cells, was used for general comparison with the cancer cells.^ Data transformations such as log, square root and 1/x did not yield normality as measured by the Shapiro-Wilks test for normality. A modulus transformation, used for distributions having abnormal kurtosis values, also did not produce normality.^ Kernel density histograms of the 34 variables exhibited non-normality and 18 variables also exhibited bimodality. A bimodality coefficient was calculated and 3 variables: DNA concentration, shape and elongation, showed the strongest evidence of bimodality and were studied further.^ Two analytical approaches were used to obtain a summary measure for each variable for each patient: cluster analysis to determine significant clusters and a mixture model analysis using a two component model having a Gaussian distribution with equal variances. The mixture component parameters were used to bootstrap the log likelihood ratio to determine the significant number of components, 1 or 2. These summary measures were used as predictors of disease severity in several proportional odds logistic regression models. The disease severity scale had 5 levels and was constructed of 3 components: extracapsulary penetration (ECP), lymph node involvement (LN+) and seminal vesicle involvement (SV+) which represent surrogate measures of prognosis. The summary measures were not strong predictors of disease severity. There was some indication from the mixture model results that there were changes in mean levels and proportions of the components in the lower severity levels. ^

Body fat distribution and serum lipids in children and adolescents

Previous studies of normal children have linked body fat but not body fat distribution (BFD), to higher blood pressures, lipids, and insulin resistance (Berenson et al., 1988) BFD is a well-established risk factor for cardiovascular disease in adults (Björntorp, 1988). This study investigates the relation of BFD and serum lipids at baseline in children from Project HeartBeat!, a study of the growth and development of cardiovascular risk factors in 678 children in three cohorts measured initially at ages 8, 11, and 14 years. Initially, two of four indices of BFD were significantly related to the lipids: ratio of upper to lower body skinfolds (ln US:LS) and conicity (C Index). A factor analysis reduced the information in the serum lipids to two vectors: (1) total cholesterol + LDL-cholesterol and (2) HDL-cholesterol − triglycerides, which together accounted for 85% of the lipid variation. Using each serum lipid and vector as separate dependent variables, linear and quadratic regression models were constructed to examine the predictive ability of the two BFD variables, controlling for total body fat, gender, ethnicity (Black, non-Black) and maturation. Linear models provided an acceptable fit. Percent body fat (%BF) was a significant predictor in each and every lipid model, independent of age, maturation, or ethnicity (p ≤ 0.05). No BFD variable entered the equation for total or LDL-cholesterol, although there was a significant maturity by BFD interaction for LDL (ln US:LS was a significant predictor in more mature individuals). Both %BF and BFD (by way of Conicity) were significant predictors of HDL-cholesterol and triglycerides (p ≤ 0.01). All models were statistically significant at a high level (p ≤ 0.01), but adjusted R 2's for all models were low (0.05–0.15). Body fat distribution is a significant predictor of lipids in normal children, but secondarily to %BF, and for LDL-cholesterol in particular, the relation is dependent on maturity status. ^

POPULATION ASSESSMENTS OF INFECTION WITH SCHISTOSOMA MANSONI: EFFECTS OF BIAS CAUSED BY THE RELATIVE SENSITIVITY OF DIAGNOSTIC TECHNIQUES (PUERTO RICO)

This study establishes the extent and relevance of bias of population estimates of prevalence, incidence, and intensity of infection with Schistosoma mansoni caused by the relative sensitivity of stool examination techniques. The population studied was Parcelas de Boqueron in Las Piedras, Puerto Rico, where the Centers for Disease Control, had undertaken a prospective community-based study of infection with S. mansoni in 1972. During each January of the succeeding years stool specimens from this population were processed according to the modified Ritchie concentration (MRC) technique. During January 1979 additional stool specimens were collected from 30 individuals selected on the basis of their mean S. mansoni egg output during previous years. Each specimen was divided into ten 1-gm aliquots and three 42-mg aliquots. The relationship of egg counts obtained with the Kato-Katz (KK) thick smear technique as a function of the mean of ten counts obtained with the MRC technique was established by means of regression analysis. Additionally, the effect of fecal sample size and egg excretion level on technique sensitivity was evaluated during a blind assessment of single stool specimen samples, using both examination methods, from 125 residents with documented S. mansoni infections. The regression equation was: Ln KK = 2.3324 + 0.6319 Ln MRC, and the coefficient of determination (r('2)) was 0.73. The regression equation was then utilized to correct the term "m" for sample size in the expression P ((GREATERTHEQ) 1 egg) = 1 - e('-ms), which estimates the probability P of finding at least one egg as a function of the mean S. mansoni egg output "m" of the population and the effective stool sample size "s" utilized by the coprological technique. This algorithm closely approximated the observed sensitivity of the KK and MRC tests when these were utilized to blindly screen a population of known parasitologic status for infection with S. mansoni. In addition, the algorithm was utilized to adjust the apparent prevalence of infection for the degree of functional sensitivity exhibited by the diagnostic test. This permitted the estimation of true prevalence of infection and, hence, a means for correcting estimates of incidence of infection. ^