Ontogeny of Toll-like receptor mediated cytokine responses of human blood mononuclear cells

Newborns and young infants suffer increased infectious morbidity and mortality as compared to older children and adults. Morbidity and mortality due to infection are highest during the first weeks of life, decreasing over several years. Furthermore, most vaccines are not administered around birth, but over the first few years of life. A more complete understanding of the ontogeny of the immune system over the first years of life is thus urgently needed. Here, we applied the most comprehensive analysis focused on the innate immune response following TLR stimulation over the first 2 years of life in the largest such longitudinal cohort studied to-date (35 subjects). We found that innate TLR responses (i) known to support Th17 adaptive immune responses (IL-23, IL-6) peaked around birth and declined over the following 2 years only to increase again by adulthood; (ii) potentially supporting antiviral defense (IFN-α) reached adult level function by 1 year of age; (iii) known to support Th1 type immunity (IL-12p70, IFN-γ) slowly rose from a low at birth but remained far below adult responses even at 2 years of age; (iv) inducing IL-10 production steadily declined from a high around birth to adult levels by 1 or 2 years of age, and; (v) leading to production of TNF-α or IL-1β varied by stimuli. Our data contradict the notion of a linear progression from an 'immature' neonatal to a 'mature' adult pattern, but instead indicate the existence of qualitative and quantitative age-specific changes in innate immune reactivity in response to TLR stimulation.     

The response of human bacteria to static magnetic field and radiofrequency electromagnetic field

Cell phones and electronic appliances and devices are inseparable from most people in modern society and the electromagnetic field (EMF) from the devices is a potential health threat. Although the direct health effect of a cell phone and its radiofrequency (RF) EMF to human is still elusive, the effect to unicellular organisms is rather apparent. Human microbiota, including skin microbiota, has been linked to a very significant role in the health of a host human body. It is important to understand the response of human skin microbiota to the RF-EMF from cell phones and personal electronic devices, since this may be one of the potential mechanisms of a human health threat brought about by the disruption of the intimate and balanced host-microbiota relationship. Here, we investigated the response of both laboratory culture strains and isolates of skin bacteria under static magnetic field (SMF) and RF-EMF. The growth patterns of laboratory cultures of Escherichia coli, Pseudomonas aeruginosa, and Staphylococcus epidermidis under SMF were variable per different species. The bacterial isolates of skin microbiota from 4 subjects with different cell phone usage history also showed inconsistent growth responses. These findings led us to hypothesize that cell phone level RF-EMF disrupts human skin microbiota. Thus, the results from the current study lay ground for more comprehensive research on the effect of RF-EMF on human health through the human-microbiota relationship.     

An Iterative Leave-One-Out Approach to Outlier Detection in RNA-Seq Data

The discrete data structure and large sequencing depth of RNA sequencing (RNA-seq) experiments can often generate outlier read counts in one or more RNA samples within a homogeneous group. Thus, how to identify and manage outlier observations in RNA-seq data is an emerging topic of interest. One of the main objectives in these research efforts is to develop statistical methodology that effectively balances the impact of outlier observations and achieves maximal power for statistical testing. To reach that goal, strengthening the accuracy of outlier detection is an important precursor. Current outlier detection algorithms for RNA-seq data are executed within a testing framework and may be sensitive to sparse data and heavy-tailed distributions. Therefore, we propose a univariate algorithm that utilizes a probabilistic approach to measure the deviation between an observation and the distribution generating the remaining data and implement it within in an iterative leave-one-out design strategy. Analyses of real and simulated RNA-seq data show that the proposed methodology has higher outlier detection rates for both non-normalized and normalized negative binomial distributed data.     

The rat fibrinogen genes. Linkage of the A alpha and gamma chain genes

We have utilized cDNA probes for the alpha, beta, and gamma chains of rat fibrinogen to isolate the corresponding genes from two rat genomic libraries constructed in bacteriophage Charon 4A. There is a single copy of each gene. Mapping of greater than 92 kilobase pairs of rat genomic DNA has shown that the gamma and alpha chain genes are directly linked in a 5'-3' direction in vivo.