Coevolutionary immune system dynamics driving pathogen speciation

We introduce and analyze a within-host dynamical model of the coevolution between rapidly mutating pathogens and the adaptive immune response. Pathogen mutation and a homeostatic constraint on lymphocytes both play a role in allowing the development of chronic infection, rather than quick pathogen clearance. The dynamics of these chronic infections display emergent structure, including branching patterns corresponding to asexual pathogen speciation, which is fundamentally driven by the coevolutionary interaction. Over time, continued branching creates an increasingly fragile immune system, and leads to the eventual catastrophic loss of immune control.Comment: main article: 16 pages, 5 figures; supporting information: 3 page

The Suppression of Immune System Disorders by Passive Attrition

Exposure to infectious diseases has an unexpected benefit of inhibiting autoimmune diseases and allergies. This is one of many fundamental fitness tradeoffs associated with immune system architecture. The immune system attacks pathogens, but also may (inappropriately) attack the host. Exposure to pathogens can suppress the deleterious response, at the price of illness and the decay of immunity to previous diseases. This “hygiene hypothesis” has been associated with several possible underlying biological mechanisms. This study focuses on physiological constraints that lead to competition for survival between immune system cell types. Competition maintains a relatively constant total number of cells within each niche. The constraint implies that adding cells conferring new immunity requires loss (passive attrition) of some cells conferring previous immunities. We consider passive attrition as a mechanism to prevent the initial proliferation of autoreactive cells, thus preventing autoimmune disease. We see that this protection is a general property of homeostatic regulation and we look specifically at both the IL-15 and IL-7 regulated niches to make quantitative predictions using a mathematical model. This mathematical model yields insight into the dynamics of the “Hygiene Hypothesis,” and makes quantitative predictions for experiments testing the ability of passive attrition to suppress immune system disorders. The model also makes a prediction of an anti-correlation between prevalence of immune system disorders and passive attrition rates

The persistence of a chlorophyll spectral biosignature from Martian evaporite and spring analogues under Mars-like conditions

Spring and evaporite deposits are considered two of the most promising environments for past habitability on Mars and preservation of biosignatures. Manitoba, Canada hosts the East German Creek (EGC) hypersaline spring complex, and the post impact evaporite gypsum beds of the Lake St. Martin (LSM) impact. The EGC complex has microbial mats, sediments, algae and biofabrics, while endolithic communities are ubiquitous in the LSM gypsum beds. These communities are spectrally detectable based largely on the presence of a chlorophyll absorption band at 670 nm; however, the robustness of this feature under Martian surface conditions was unclear. Biological and biology-bearing samples from EGC and LSM were exposed to conditions similar to the surface of present day Mars (high UV flux, 100 mbar, anoxic, CO_2 rich) for up to 44 days, and preservation of the 670 nm chlorophyll feature and chlorophyll red-edge was observed. A decrease in band depth of the 670 nm band ranging from ∼16 to 80% resulted, with correlations seen in the degree of preservation and the spatial proximity of samples to the spring mound and mineral shielding effects. The spectra were deconvolved to Mars Exploration Rover (MER) Pancam and Mars Science Laboratory (MSL) Mastcam science filter bandpasses to investigate the detectability of the 670 nm feature and to compare with common mineral features. The red-edge and 670 nm feature associated with chlorophyll can be distinguished from the spectra of minerals with features below ∼1000 nm, such as hematite and jarosite. However, distinguishing goethite from samples with the chlorophyll feature is more problematic, and quantitative interpretation using band depth data makes little distinction between iron oxyhydroxides and the 670 nm chlorophyll feature. The chlorophyll spectral feature is observable in both Pancam and Mastcam, and we propose that of the proposed EXOMARS Pancam filters, the PHYLL filter is best suited for its detection

Gene expression patterns that predict sensitivity to epidermal growth factor receptor tyrosine kinase inhibitors in lung cancer cell lines and human lung tumors

BACKGROUND: Increased focus surrounds identifying patients with advanced non-small cell lung cancer (NSCLC) who will benefit from treatment with epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKI). EGFR mutation, gene copy number, coexpression of ErbB proteins and ligands, and epithelial to mesenchymal transition markers all correlate with EGFR TKI sensitivity, and while prediction of sensitivity using any one of the markers does identify responders, individual markers do not encompass all potential responders due to high levels of inter-patient and inter-tumor variability. We hypothesized that a multivariate predictor of EGFR TKI sensitivity based on gene expression data would offer a clinically useful method of accounting for the increased variability inherent in predicting response to EGFR TKI and for elucidation of mechanisms of aberrant EGFR signalling. Furthermore, we anticipated that this methodology would result in improved predictions compared to single parameters alone both in vitro and in vivo. RESULTS: Gene expression data derived from cell lines that demonstrate differential sensitivity to EGFR TKI, such as erlotinib, were used to generate models for a priori prediction of response. The gene expression signature of EGFR TKI sensitivity displays significant biological relevance in lung cancer biology in that pertinent signalling molecules and downstream effector molecules are present in the signature. Diagonal linear discriminant analysis using this gene signature was highly effective in classifying out-of-sample cancer cell lines by sensitivity to EGFR inhibition, and was more accurate than classifying by mutational status alone. Using the same predictor, we classified human lung adenocarcinomas and captured the majority of tumors with high levels of EGFR activation as well as those harbouring activating mutations in the kinase domain. We have demonstrated that predictive models of EGFR TKI sensitivity can classify both out-of-sample cell lines and lung adenocarcinomas. CONCLUSION: These data suggest that multivariate predictors of response to EGFR TKI have potential for clinical use and likely provide a robust and accurate predictor of EGFR TKI sensitivity that is not achieved with single biomarkers or clinical characteristics in non-small cell lung cancers

Zinc Ion-Dependent Peptide Nucleic Acid-Based Artificial Enzyme that Cleaves RNABulge Size and Sequence Dependence

In this report, we investigate the efficiency and selectivity of a Zn2+-dependent peptide nucleic acid-based artificial ribonuclease (PNAzyme) that cleaves RNA target sequences. The target RNAs are varied to form different sizes (3 and 4 nucleotides, nt) and sequences in the bulge formed upon binding to the PNAzyme. PNAzyme-promoted cleavage of the target RNAs was observed and variation of the substrate showed a clear dependence on the sequence and size of the bulge. For targets that form 4-nt bulges, we identified systems with an improved efficacy (an estimated half-life of ca 7-8 h as compared to 11-12 h for sequences studied earlier) as well as systems with an improved site selectivity (up to over 70% cleavage at a single site as compared to 50-60% with previous targets sequences). For targets forming 3-nt bulges, the enhancement compared to previous systems was even more pronounced. Compared to a starting point of targets forming 3-nt AAA bulges (half-lives of ca 21-24 h), we could identify target sequences that were cleaved with half-lives three times lower (ca 7-8 h), i.e., at rates similar to those found for the fastest 4-nt bulge system. In addition, with the 3-nt bulge RNA target site selectivity was improved even further to reach well over 80% cleavage at a specific site

Critical values for Lawshe's content validity ratio: revisiting the original methods of calculation

YesThe content validity ratio originally proposed by Lawshe is widely used to quantify content validity and yet methods used to calculate the original critical values were never reported. Methods for original calculation of critical values are suggested along with tables of exact binomial probabilities

Measuring and Modeling Behavioral Decision Dynamics in Collective Evacuation

Identifying and quantifying factors influencing human decision making remains an outstanding challenge, impacting the performance and predictability of social and technological systems. In many cases, system failures are traced to human factors including congestion, overload, miscommunication, and delays. Here we report results of a behavioral network science experiment, targeting decision making in a natural disaster. In each scenario, individuals are faced with a forced "go" versus "no go" evacuation decision, based on information available on competing broadcast and peer-to-peer sources. In this controlled setting, all actions and observations are recorded prior to the decision, enabling development of a quantitative decision making model that accounts for the disaster likelihood, severity, and temporal urgency, as well as competition between networked individuals for limited emergency resources. Individual differences in behavior within this social setting are correlated with individual differences in inherent risk attitudes, as measured by standard psychological assessments. Identification of robust methods for quantifying human decisions in the face of risk has implications for policy in disasters and other threat scenarios.Comment: Approved for public release; distribution is unlimite

Polymer-coated bioactive glass S53P4 increases VEGF and TNF expression in an induced membrane model in vivo

The two-stage induced-membrane technique for treatment of large bone defects has become popular among orthopedic surgeons. In the first operation, the bone defect is filled with poly(methyl methacrylate) (PMMA), which is intended to produce a membrane around the implant. In the second operation, PMMA is replaced with autograft or allograft bone. Bioactive glasses (BAGs) are bone substitutes with bone-stimulating and angiogenetic properties. The aim of our study was to evaluate the inductive vascular capacity of BAG-S53P4 and poly(lactide-co-glycolide) (PLGA)-coated BAG-S53P4 for potential use as bone substitutes in a single-stage induced-membrane technique. Sintered porous rods of BAG-S53P4, PLGA-coated BAG-S53P4 and PMMA were implanted in the femur of 36 rabbits for 2, 4 and 8 weeks. The expression of vascular endothelial growth factor (VEGF) and tumor necrosis factor alpha (TNF) in the induced membranes of implanted materials was analyzed with real-time quantitative polymerase chain reaction and compared with histology. Both uncoated BAG-S53P4 and PLGA-coated BAG-S53P4 increase expression of VEGF and TNF, resulting in higher amounts of capillary beds, compared with the lower expression of VEGF and less capillary beads observed for negative control and PMMA samples. A significantly higher expression of VEGF was observed for PLGA-coated BAG-S53P4 than for PMMA at 8 weeks (p <0.036). VEGF and TNF expression in the induced membrane of BAG-S53P4 and PLGA-coated BAG-S53P4 is equal or superior to PMMA, the "gold standard" material used in the induced-membrane technique. Furthermore, the VEGF and TNF expression for PLGA-coated BAG-S53P4 increased during follow-up.Peer reviewe

Considerations for Studying Sex as a Biological Variable in Spinal Cord Injury

In response to NIH initiatives to investigate sex as a biological variable in preclinical animal studies, researchers have increased their focus on male and female differences in neurotrauma. Inclusion of both sexes when modeling neurotrauma is leading to the identification of novel areas for therapeutic and scientific exploitation. Here, we review the organizational and activational effects of sex hormones on recovery from injury and how these changes impact the long-term health of spinal cord injury (SCI) patients. When determining how sex affects SCI it remains imperative to expand outcomes beyond locomotor recovery and consider other complications plaguing the quality of life of patients with SCI. Interestingly, the SCI field predominately utilizes female rodents for basic science research which contrasts most other male-biased research fields. We discuss the unique caveats this creates to the translatability of preclinical research in the SCI field. We also review current clinical and preclinical data examining sex as biological variable in SCI. Further, we report how technical considerations such as housing, size, care management, and age, confound the interpretation of sex-specific effects in animal studies of SCI. We have uncovered novel findings regarding how age differentially affects mortality and injury-induced anemia in males and females after SCI, and further identified estrus cycle dysfunction in mice after injury. Emerging concepts underlying sexually dimorphic responses to therapy are also discussed. Through a combination of literature review and primary research observations we present a practical guide for considering and incorporating sex as biological variable in preclinical neurotrauma studies

Expression divergence measured by transcriptome sequencing of four yeast species

<p>Abstract</p> <p>Background</p> <p>The evolution of gene expression is a challenging problem in evolutionary biology, for which accurate, well-calibrated measurements and methods are crucial.</p> <p>Results</p> <p>We quantified gene expression with whole-transcriptome sequencing in four diploid, prototrophic strains of <it>Saccharomyces </it>species grown under the same condition to investigate the evolution of gene expression. We found that variation in expression is gene-dependent with large variations in each gene's expression between replicates of the same species. This confounds the identification of genes differentially expressed across species. To address this, we developed a statistical approach to establish significance bounds for inter-species differential expression in RNA-Seq data based on the variance measured across biological replicates. This metric estimates the combined effects of technical and environmental variance, as well as Poisson sampling noise by isolating each component. Despite a paucity of large expression changes, we found a strong correlation between the variance of gene expression change and species divergence (R²= 0.90).</p> <p>Conclusion</p> <p>We provide an improved methodology for measuring gene expression changes in evolutionary diverged species using RNA Seq, where experimental artifacts can mimic evolutionary effects.</p> <p>GEO Accession Number: GSE32679</p