Periodontal Treatment Reduces Circulating Pro-Inflammatory Cytokine and Chemokine Levels in African American HIV+ Individuals with Virological Suppression

Introduction

Periodontal Disease (PD), a chronic inflammatory disease, is highly prevalent among Persons Living With HIV (PLWH) and is characterized by microbial symbiosis and oxidative stress. Our hypothesis stipulates that periodontal therapy attenuates systemic inflammatory and bacterial burden while improving periodontal status in PLWH.

Methods

Sixteen African Americans (AA) with suppressed HIV viremia on long-term Antiretroviral Therapy (ART) were recruited to this study. Participants were placed into two groups, based on their dental care status: group 1 (In-Care, IC) and group 2 (Out of Care, OC). Periodontal health was investigated at baseline, 3 months, 6 months, and 12 months. Cytokine/chemokines, microbial phyla, and Asymmetric Dimethylarginine (ADMA, a marker for endothelial cell dysfunction) levels were assessed in the serum. Statistical comparisons between groups and at different visits were performed using multiple comparison tests.

Results

Across longitudinal visits, periodontal treatment significantly reduced the levels of several cytokines and chemokines. At baseline, the out of care group had significantly higher blood levels of ADMA and actinobacteria than the IC group. Periodontal treatment significantly altered the abundance of circulating genomic bacterial DNA for various phyla in out of care group.

Conclusions

Periodontal treatment interventions effectively attenuated circulating pro-inflammatory cytokines and altered microbial translocation, both critical drivers of systemic inflammation in PLWH.

A New Robust Method for Nonlinear Regression

BACKGROUND

When outliers are present, the least squares method of nonlinear regression performs poorly. The main purpose of this paper is to provide a robust alternative technique to the Ordinary Least Squares nonlinear regression method. This new robust nonlinear regression method can provide accurate parameter estimates when outliers and/or influential observations are present.

METHOD

Real and simulated data for drug concentration and tumor size-metastasis are used to assess the performance of this new estimator. Monte Carlo simulations are performed to evaluate the robustness of our new method in comparison with the Ordinary Least Squares method.

RESULTS

In simulated data with outliers, this new estimator of regression parameters seems to outperform the Ordinary Least Squares with respect to bias, mean squared errors, and mean estimated parameters. Two algorithms have been proposed. Additionally and for the sake of computational ease and illustration, a Mathematica program has been provided in the Appendix.

CONCLUSION

The accuracy of our robust technique is superior to that of the Ordinary Least Squares. The robustness and simplicity of computations make this new technique more appropriate and useful tool for the analysis of nonlinear regressions.

Robust Logistic and Probit Methods for Binary and Multinomial Regression

In this paper we introduce new robust estimators for the logistic and probit regressions for binary, multinomial, nominal and ordinal data and apply these models to estimate the parameters when outliers or inluential observations are present. Maximum likelihood estimates don't behave well when outliers or inluential observations are present. One remedy is to remove inluential observations from the data and then apply the maximum likelihood technique on the deleted data. Another approach is to employ a robust technique that can handle outliers and inluential observations without removing any observations from the data sets. The robustness of the method is tested using real and simulated data sets.

Oscillabolastic model, a new model for oscillatory dynamics, applied to the analysis of Hes1 gene expression and Ehrlich ascites tumor growth

This paper introduces a new dynamical model, called the oscillabolastic model, to analyze the dynamical behavior of biomedical data when one observes oscillatory behavior. The proposed oscillabolastic model is sufficiently flexible to represent various types of oscillatory behavior. The oscillabolastic model is applied to two sets of data. The first data set deals with the oscillabolastic modeling of Ehrlich ascites tumor cells and the second one is the oscillabolastic modeling of the mean signal intensity of Hes1 gene expression in response to serum stimulation. A generalized oscillabolastic model is also suggested to accommodate cases in which predictor variables other than time are also involved.

Heavy metals distribution in an Iowa suburban landscape

This study investigated the degree to which human activities through urbanization influence heavy metal concentrations in a suburban landscape in Ankeny, IA. Residential areas from different years in nine time periods of development were identified from aerial photos. Soil cores were collected from the center of the front yard of 10 randomly selected homes. Cores were subdivided into 0- to 5-, 5- to 10-, and 10- to 20-cm increments from a composite of five cores. The soils were analyzed for organic C, pH, and total Cd, Co, Cr, Cu, Ni, Pb, and Zn. Results showed that organic C increased and pH decreased with time, and that there was a general decreasing trend in heavy metal concentrations from the pre-1939 period until 1983-1990, after which there was a sharp increase in the concentrations of most of the metals. The mean Cu concentration ranged from 21 mg kg(-1) for the pre-1939 time period of development to 14.9 mg kg(-1) for the recent period of development (2003-2005). Nickel concentrations increased significantly with depth with means of 21.3 mg kg(-1) at depth 0 to 5 cm, 22.5 mg kg(-1) at depth 5 to 10 cm, and 23.0 mg kg(-1) at depth 10 to 20 cm. The concentrations of heavy metals were significantly intercorrelated, except Zn, suggesting their coexistence as mineral constituents or common contamination source. The concentrations of Cu and Pb in some locations could be due to anthropogenic inputs or higher organic matter content in soils adjacent to older homes. There appears to have been a source that caused an increase in Cd, Cr, Co, Cu, Pb, and Ni concentrations in soil adjacent to homes built between 1983 and 1990.