Climate Variability and Ross River Virus Transmission in Townsville Region, Australia 1985 to 1996

Background How climate variability affects the transmission of infectious diseases at a regional level remains unclear. In this paper, we assessed the impact of climate variation on the Ross River virus (RRv) transmission in the Townsville region, Queensland, north-east Australia. Methods Population-based information was obtained on monthly variations in RRv cases, climatic factors, sea level, and population growth between 1985 and 1996. Cross-correlations were computed for a series of associations between climate variables (rainfall, maximum temperature, minimum temperature, relative humidity and high tide) and the monthly incidence of RRv disease over a range of time lags. The impact of climate variability on RRv transmission was assessed using the seasonal auto-regressive integrated moving average (SARIMA) model. Results There were significant correlations of the monthly incidence of RRv to rainfall, maximum temperature, minimum temperature and relative humidity, all at a lag of 2 months, and high tide in the current month. The results of SARIMA models show that monthly average rainfall (β=0.0012, p=0.04) and high tide (β=0.0262, p=0.01) were significantly associated with RRv transmission, although temperature and relative humidity did not seem to have played an important role in the Townsville region. Conclusions Rainfall, and high tide were likely to be key determinants of RRv transmission in the Townsville region

Religiosity and decreased risk of substance use disorders: is the effect mediated by social support or mental health status?

The negative association between religiosity (religious beliefs and church attendance) and the likelihood of substance use disorders is well established, but the mechanism(s) remain poorly understood. We investigated whether this association was mediated by social support or mental health status. We utilized cross-sectional data from the 2002 National Survey on Drug Use and Health (n = 36,370). We first used logistic regression to regress any alcohol use in the past year on sociodemographic and religiosity variables. Then, among individuals who drank in the past year, we regressed past year alcohol abuse/dependence on sociodemographic and religiosity variables. To investigate whether social support mediated the association between religiosity and alcohol use and alcohol abuse/dependence we repeated the above models, adding the social support variables. To the extent that these added predictors modified the magnitude of the effect of the religiosity variables, we interpreted social support as a possible mediator. We also formally tested for mediation using path analysis. We investigated the possible mediating role of mental health status analogously. Parallel sets of analyses were conducted for any drug use, and drug abuse/dependence among those using any drugs as the dependent variables. The addition of social support and mental health status variables to logistic regression models had little effect on the magnitude of the religiosity coefficients in any of the models. While some of the tests of mediation were significant in the path analyses, the results were not always in the expected direction, and the magnitude of the effects was small. The association between religiosity and decreased likelihood of a substance use disorder does not appear to be substantively mediated by either social support or mental health status

Effects of Hypericum Perforatum, in a rodent model of periodontitis

<p>Abstract</p> <p>Background</p> <p><it>Hypericum perforatum </it>is a medicinal plant species containing many polyphenolic compounds, namely flavonoids and phenolic acids. In this study we evaluate the effect of <it>Hypericum perforatum </it>in animal model of periodontitis.</p> <p>Methods</p> <p>Periodontitis was induced in adult male Sprague-Dawley rats by placing a nylon thread ligature around the lower 1st molars. Hypericum perforatum was administered at the dose of 2 mg/kg os, daily for eight days. At day 8, the gingivomucosal tissue encircling the mandibular first molar was removed.</p> <p>Results</p> <p>Periodontitis in rats resulted in an inflammatory process characterized by edema, neutrophil infiltration and cytokine production that was followed by the recruitment of other inflammatory cells, production of a range of inflammatory mediators such as NF-κB and iNOS expression, the nitration of tyrosine residues and activation of the nuclear enzyme poly (ADP-ribose) polymerase; apoptosis and the degree of gingivomucosal tissues injury. We report here that Hypericum perforatum exerts potent anti-inflammatory effects significantly reducing all of the parameters of inflammation as described above.</p> <p>Conclusions</p> <p>Taken together, our results clearly demonstrate that treatment with Hypericum reduces the development of inflammation and tissue injury, events associated with periodontitis.</p

Orientation-dependent backbone-only residue pair scoring functions for fixed backbone protein design

<p>Abstract</p> <p>Background</p> <p>Empirical scoring functions have proven useful in protein structure modeling. Most such scoring functions depend on protein side chain conformations. However, backbone-only scoring functions do not require computationally intensive structure optimization and so are well suited to protein design, which requires fast score evaluation. Furthermore, scoring functions that account for the distinctive relative position and orientation preferences of residue pairs are expected to be more accurate than those that depend only on the separation distance.</p> <p>Results</p> <p>Residue pair scoring functions for fixed backbone protein design were derived using only backbone geometry. Unlike previous studies that used spherical harmonics to fit 2D angular distributions, Gaussian Mixture Models were used to fit the full 3D (position only) and 6D (position and orientation) distributions of residue pairs. The performance of the 1D (residue separation only), 3D, and 6D scoring functions were compared by their ability to identify correct threading solutions for a non-redundant benchmark set of protein backbone structures. The threading accuracy was found to steadily increase with increasing dimension, with the 6D scoring function achieving the highest accuracy. Furthermore, the 3D and 6D scoring functions were shown to outperform side chain-dependent empirical potentials from three other studies. Next, two computational methods that take advantage of the speed and pairwise form of these new backbone-only scoring functions were investigated. The first is a procedure that exploits available sequence data by averaging scores over threading solutions for homologs. This was evaluated by applying it to the challenging problem of identifying interacting transmembrane alpha-helices and found to further improve prediction accuracy. The second is a protein design method for determining the optimal sequence for a backbone structure by applying Belief Propagation optimization using the 6D scoring functions. The sensitivity of this method to backbone structure perturbations was compared with that of fixed-backbone all-atom modeling by determining the similarities between optimal sequences for two different backbone structures within the same protein family. The results showed that the design method using 6D scoring functions was more robust to small variations in backbone structure than the all-atom design method.</p> <p>Conclusions</p> <p>Backbone-only residue pair scoring functions that account for all six relative degrees of freedom are the most accurate and including the scores of homologs further improves the accuracy in threading applications. The 6D scoring function outperformed several side chain-dependent potentials while avoiding time-consuming and error prone side chain structure prediction. These scoring functions are particularly useful as an initial filter in protein design problems before applying all-atom modeling.</p

Using Structure to Explore the Sequence Alignment Space of Remote Homologs

Protein structure modeling by homology requires an accurate sequence alignment between the query protein and its structural template. However, sequence alignment methods based on dynamic programming (DP) are typically unable to generate accurate alignments for remote sequence homologs, thus limiting the applicability of modeling methods. A central problem is that the alignment that is “optimal” in terms of the DP score does not necessarily correspond to the alignment that produces the most accurate structural model. That is, the correct alignment based on structural superposition will generally have a lower score than the optimal alignment obtained from sequence. Variations of the DP algorithm have been developed that generate alternative alignments that are “suboptimal” in terms of the DP score, but these still encounter difficulties in detecting the correct structural alignment. We present here a new alternative sequence alignment method that relies heavily on the structure of the template. By initially aligning the query sequence to individual fragments in secondary structure elements and combining high-scoring fragments that pass basic tests for “modelability”, we can generate accurate alignments within a small ensemble. Our results suggest that the set of sequences that can currently be modeled by homology can be greatly extended

Fibroblasts Express Immune Relevant Genes and Are Important Sentinel Cells during Tissue Damage in Rainbow Trout (Oncorhynchus mykiss)

Fibroblasts have shown to be an immune competent cell type in mammals. However, little is known about the immunological functions of this cell-type in lower vertebrates. A rainbow trout hypodermal fibroblast cell-line (RTHDF) was shown to be responsive to PAMPs and DAMPs after stimulation with LPS from E. coli, supernatant and debris from sonicated RTHDF cells. LPS was overall the strongest inducer of IL-1β, IL-8, IL-10, TLR-3 and TLR-9. IL-1β and IL-8 were already highly up regulated after 1 hour of LPS stimulation. Supernatant stimuli significantly increased the expression of IL-1β, TLR-3 and TLR-9, whereas the debris stimuli only increased expression of IL-1β. Consequently, an in vivo experiment was further set up. By mechanically damaging the muscle tissue of rainbow trout, it was shown that fibroblasts in the muscle tissue of rainbow trout contribute to electing a highly local inflammatory response following tissue injury. The damaged muscle tissue showed a strong increase in the expression of the immune genes IL-1β, IL-8 and TGF-β already 4 hours post injury at the site of injury while the expression in non-damaged muscle tissue was not influenced. A weaker, but significant response was also seen for TLR-9 and TLR-22. Rainbow trout fibroblasts were found to be highly immune competent with a significant ability to express cytokines and immune receptors. Thus fish fibroblasts are believed to contribute significantly to local inflammatory reactions in concert with the traditional immune cells

Ca2+ Permeable AMPA Receptor Induced Long-Term Potentiation Requires PI3/MAP Kinases but Not Ca/CaM-Dependent Kinase II

Ca2+ influx via GluR2-lacking Ca2+-permeable AMPA glutamate receptors (CP-AMPARs) can trigger changes in synaptic efficacy in both interneurons and principle neurons, but the underlying mechanisms remain unknown. We took advantage of genetically altered mice with no or reduced GluR2, thus allowing the expression of synaptic CP-AMPARs, to investigate the molecular signaling process during CP-AMPAR-induced synaptic plasticity at CA1 synapses in the hippocampus. Utilizing electrophysiological techniques, we demonstrated that these receptors were capable of inducing numerous forms of long-term potentiation (referred to as CP-AMPAR dependent LTP) through a number of different induction protocols, including high-frequency stimulation (HFS) and theta-burst stimulation (TBS). This included a previously undemonstrated form of protein-synthesis dependent late-LTP (L-LTP) at CA1 synapses that is NMDA-receptor independent. This form of plasticity was completely blocked by the selective CP-AMPAR inhibitor IEM-1460, and found to be dependent on postsynaptic Ca2+ ions through calcium chelator (BAPTA) studies. Surprisingly, Ca/CaM-dependent kinase II (CaMKII), the key protein kinase that is indispensable for NMDA-receptor dependent LTP at CA1 synapses appeared to be not required for the induction of CP-AMPAR dependent LTP due to the lack of effect of two separate pharmacological inhibitors (KN-62 and staurosporine) on this form of potentiation. Both KN-62 and staurosporine strongly inhibited NMDA-receptor dependent LTP in control studies. In contrast, inhibitors for PI3-kinase (LY294002 and wortmannin) or the MAPK cascade (PD98059 and U0126) significantly attenuated this CP-AMPAR-dependent LTP. Similarly, postsynaptic infusion of tetanus toxin (TeTx) light chain, an inhibitor of exocytosis, also had a significant inhibitory effect on this form of LTP. These results suggest that distinct synaptic signaling underlies GluR2-lacking CP-AMPAR-dependent LTP, and reinforces the recent notions that CP-AMPARs are important facilitators of synaptic plasticity in the brain

Optimizing Preprocessing and Analysis Pipelines for Single-Subject fMRI: 2. Interactions with ICA, PCA, Task Contrast and Inter-Subject Heterogeneity

A variety of preprocessing techniques are available to correct subject-dependant artifacts in fMRI, caused by head motion and physiological noise. Although it has been established that the chosen preprocessing steps (or “pipeline”) may significantly affect fMRI results, it is not well understood how preprocessing choices interact with other parts of the fMRI experimental design. In this study, we examine how two experimental factors interact with preprocessing: between-subject heterogeneity, and strength of task contrast. Two levels of cognitive contrast were examined in an fMRI adaptation of the Trail-Making Test, with data from young, healthy adults. The importance of standard preprocessing with motion correction, physiological noise correction, motion parameter regression and temporal detrending were examined for the two task contrasts. We also tested subspace estimation using Principal Component Analysis (PCA), and Independent Component Analysis (ICA). Results were obtained for Penalized Discriminant Analysis, and model performance quantified with reproducibility (R) and prediction metrics (P). Simulation methods were also used to test for potential biases from individual-subject optimization. Our results demonstrate that (1) individual pipeline optimization is not significantly more biased than fixed preprocessing. In addition, (2) when applying a fixed pipeline across all subjects, the task contrast significantly affects pipeline performance; in particular, the effects of PCA and ICA models vary with contrast, and are not by themselves optimal preprocessing steps. Also, (3) selecting the optimal pipeline for each subject improves within-subject (P,R) and between-subject overlap, with the weaker cognitive contrast being more sensitive to pipeline optimization. These results demonstrate that sensitivity of fMRI results is influenced not only by preprocessing choices, but also by interactions with other experimental design factors. This paper outlines a quantitative procedure to denoise data that would otherwise be discarded due to artifact; this is particularly relevant for weak signal contrasts in single-subject, small-sample and clinical datasets