Mass Media and the Contagion of Fear: The Case of Ebola in America

Background

In the weeks following the first imported case of Ebola in the U. S. on September 29, 2014, coverage of the very limited outbreak dominated the news media, in a manner quite disproportionate to the actual threat to national public health; by the end of October, 2014, there were only four laboratory confirmed cases of Ebola in the entire nation. Public interest in these events was high, as reflected in the millions of Ebola-related Internet searches and tweets performed in the month following the first confirmed case. Use of trending Internet searches and tweets has been proposed in the past for real-time prediction of outbreaks (a field referred to as “digital epidemiology”), but accounting for the biases of public panic has been problematic. In the case of the limited U. S. Ebola outbreak, we know that the Ebola-related searches and tweets originating the U. S. during the outbreak were due only to public interest or panic, providing an unprecedented means to determine how these dynamics affect such data, and how news media may be driving these trends.

Methodology

We examine daily Ebola-related Internet search and Twitter data in the U. S. during the six week period ending Oct 31, 2014. TV news coverage data were obtained from the daily number of Ebola-related news videos appearing on two major news networks. We fit the parameters of a mathematical contagion model to the data to determine if the news coverage was a significant factor in the temporal patterns in Ebola-related Internet and Twitter data.

Conclusions

We find significant evidence of contagion, with each Ebola-related news video inspiring tens of thousands of Ebola-related tweets and Internet searches. Between 65% to 76% of the variance in all samples is described by the news media contagion model.     

Functionality of Dengue Virus Specific Memory T Cell Responses in Individuals Who Were Hospitalized or Who Had Mild or Subclinical Dengue Infection

Background

Although antibody responses to dengue virus (DENV) in naturally infected individuals have been extensively studied, the functionality of DENV specific memory T cell responses in relation to clinical disease severity is incompletely understood.

Methodology/Principal findings

Using ex vivo IFNγ ELISpot assays, and by determining cytokines produced in ELISpot supernatants, we investigated the functionality of DENV-specific memory T cell responses in a large cohort of individuals from Sri Lanka (n=338), who were naturally infected and were either hospitalized due to dengue or had mild or sub clinical dengue infection. We found that T cells of individuals with both past mild or sub clinical dengue infection and who were hospitalized produced multiple cytokines when stimulated with DENV-NS3 peptides. However, while DENV-NS3 specific T cells of those with mild/sub clinical dengue infection were more likely to produce only granzyme B (p=0.02), those who were hospitalized were more likely to produce both TNFα and IFNγ (p=0.03) or TNFα alone.We have also investigated the usefulness of a novel T cell based assay, which can be used to determine the past infecting DENV serotype. 92.4% of DENV seropositive individuals responded to at least one DENV serotype of this assay and none of the seronegatives responded. Individuals who were seronegative, but had received the Japanese encephalitis vaccine too made no responses, suggesting that the peptides used in this assay did not cross react with the Japanese encephalitis virus.

Conclusions/significance

The types of cytokines produced by DENV-specific memory T cells appear to influence the outcome of clinical disease severity. The novel T cell based assay, is likely to be useful in determining the past infecting DENV serotype in immune-epidemiological studies and also in dengue vaccine trials.     

Trend of Cardio-Metabolic Risk Factors in Polycystic Ovary Syndrome: A Population-Based Prospective Cohort Study

Objective

To see the changes of cardio-metabolic risk factors overtime in polycystic ovary syndrome vs. control women.

Methods

This study was conducted on 637 participants (85 PCOS and 552 control reproductive aged, 18–45 years) of Tehran Lipid and Glucose Study (TLGS), an ongoing population-based cohort study with 12 years of follow-up. The cardiovascular risk factors of these groups were assessed in three-year intervals using standard questionnaires, history taking, anthropometric measures, and metabolic/endocrine evaluation. Generalized estimating equation was used to analyze the data.

Results

Overall mean of insulin (3.55, CI: 0.66–6.45), HOMA-IR (0.63, CI: 0.08–1.18), and HOMA-β (45.90, CI: 0.86–90.93) were significantly higher in PCOS than in healthy women after adjustment for age, BMI, and baseline levels. However, the negative interaction (follow-up years × PCOS status) of PCOS and normal women converged overtime. Comparing third follow-up with first, insulin and HOMA-IR decreased 10.6% and 5%, respectively in PCOS women; and increased 6.7% and 14.6%, respectively in controls (P<0.05). The results did not show any significant result for other cardio-metabolic variables including WC, lipid profile, FPG, 2-h PG, SBP, and DBP.

Conclusion

While the insulin level and insulin resistance rate were higher in reproductive aged PCOS than in healthy women, the difference of these risk factors decreased overtime. Thus, the metabolic consequences of PCOS women in later life may be lower than those initially anticipated.     

The Link between Microbial Diversity and Nitrogen Cycling in Marine Sediments Is Modulated by Macrofaunal Bioturbation

Objectives

The marine benthic nitrogen cycle is affected by both the presence and activity of macrofauna and the diversity of N-cycling microbes. However, integrated research simultaneously investigating macrofauna, microbes and N-cycling is lacking. We investigated spatio-temporal patterns in microbial community composition and diversity, macrofaunal abundance and their sediment reworking activity, and N-cycling in seven subtidal stations in the Southern North Sea.

Spatio-Temporal Patterns of the Microbial Communities

Our results indicated that bacteria (total and β-AOB) showed more spatio-temporal variation than archaea (total and AOA) as sedimentation of organic matter and the subsequent changes in the environment had a stronger impact on their community composition and diversity indices in our study area. However, spatio-temporal patterns of total bacterial and β-AOB communities were different and related to the availability of ammonium for the autotrophic β-AOB. Highest bacterial richness and diversity were observed in June at the timing of the phytoplankton bloom deposition, while richness of β-AOB as well as AOA peaked in September. Total archaeal community showed no temporal variation in diversity indices.

Macrofauna, Microbes and the Benthic N-Cycle

Distance based linear models revealed that, independent from the effect of grain size and the quality and quantity of sediment organic matter, nitrification and N-mineralization were affected by respectively the diversity of metabolically active β-AOB and AOA, and the total bacteria, near the sediment-water interface. Separate models demonstrated a significant and independent effect of macrofaunal activities on community composition and richness of total bacteria, and diversity indices of metabolically active AOA. Diversity of β-AOB was significantly affected by macrofaunal abundance. Our results support the link between microbial biodiversity and ecosystem functioning in marine sediments, and provided broad correlative support for the hypothesis that this relationship is modulated by macrofaunal activity. We hypothesized that the latter effect can be explained by their bioturbating and bio-irrigating activities, increasing the spatial complexity of the biogeochemical environment.     

Robust and stable feature selection by integrating ranking methods and wrapper technique in genetic data classification

High dimensional data increase the dimension of space and consequently the computational complexity and result in lower generalization. From these types of classification problems microarray data classification can be mentioned. Microarrays contain genetic and biological data which can be used to diagnose diseases including various types of cancers and tumors. Having intractable dimensions, dimension reduction process is necessary on these data. The main goal of this paper is to provide a method for dimension reduction and classification of genetic data sets. The proposed approach includes different stages. In the first stage, several feature ranking methods are fused for enhancing the robustness and stability of feature selection process. Wrapper method is combined with the proposed hybrid ranking method to embed the interaction between genes. Afterwards, the classification process is applied using support vector machine. Before feeding the data to the SVM classifier the problem of imbalance classes of data in the training phase should be overcame. The experimental results of the proposed approach on five microarray databases show that the robustness metric of the feature selection process is in the interval of [0.70, 0.88]. Also the classification accuracy is in the range of [91%, 96%].     

Internalization of Flax Rust Avirulence Proteins into Flax and Tobacco Cells Can Occur in the Absence of the Pathogen

Translocation of pathogen effector proteins into the host cell cytoplasm is a key determinant for the pathogenicity of many bacterial and oomycete plant pathogens. A number of secreted fungal avirulence (Avr) proteins are also inferred to be delivered into host cells, based on their intracellular recognition by host resistance proteins, including those of flax rust (Melampsora lini). Here, we show by immunolocalization that the flax rust AvrM protein is secreted from haustoria during infection and accumulates in the haustorial wall. Five days after inoculation, the AvrM protein was also detected within the cytoplasm of a proportion of plant cells containing haustoria, confirming its delivery into host cells during infection. Transient expression of secreted AvrL567 and AvrM proteins fused to cerulean fluorescent protein in tobacco (Nicotiana tabacum) and flax cells resulted in intracellular accumulation of the fusion proteins. The rust Avr protein signal peptides were functional in plants and efficiently directed fused cerulean into the secretory pathway. Thus, these secreted effectors are internalized into the plant cell cytosol in the absence of the pathogen, suggesting that they do not require a pathogen-encoded transport mechanism. Uptake of these proteins is dependent on signals in their N-terminal regions, but the primary sequence features of these uptake regions are not conserved between different rust effectors.     

Contribution to the cytotaxonomy of Oryzopsis (Poaceae)

Meiotic studies were performed in twelve populations of four Oryzopsis species (O. pubiflora, O. lateralis, O. holciformis var. longiglomis and O. barbellata) to obtain data on the ploidy level and cytological evolution of the genus. The chromosome number 2n=2x=24 was revealed in all the species and populations studied. The present and other studies show the occurrence of two basic chromosome numbers in the genus, i.e. x=11 and x=12. Although Oryzopsis species and populations studied are diploid and are expected to form only bivalents in metaphase of meiosis‐I, quadrivalents were observed in O. pubiflora and O. lateralis, possibly due to the occurrence of heterozygote translocations. B‐chromosomes of 0–2 were observed in all species and populations studied. This is the first report of the occurrence of B‐chromosomes in the genus Oryzopsis. Several meiocytes showed the presence of double chromosome number in O. lateralis, and multipolar cells were observed in populations of O. barbellata, O. lateralis and O. holciformis var. longiglomis. The occurrence of large pollen grains (possibly unreduced) was observed along with smaller (normal) pollen grains in these species. Significant differences observed in chiasma frequency and distribution among studied species may be of use in species delimitation. The Kakan population differed significantly from the other populations of O. lateralis in meiotic characteristics. If such cytological differences are accompanied by morphological variation (under investigation), we may consider this population as a new variety or subspecies.     

Optimizing a Proteomics Platform for Urine Biomarker Discovery

Biomarker discovery approaches in urine have been hindered by concerns for reproducibility and inadequate standardization of proteomics protocols. In this study, we describe an optimized quantitative proteomics strategy for urine biomarker discovery, which is applicable to fresh or long frozen samples. We used urine from healthy controls to standardize iTRAQ (isobaric tags for relative and absolute quantitation) for variation induced by protease inhibitors, starting protein and iTRAQ label quantities, protein extraction methods, and depletion of albumin and immunoglobulin G (IgG). We observed the following: (a) Absence of protease inhibitors did not affect the number or identity of the high confidence proteins. (b) Use of less than 20 μg of protein per sample led to a significant drop in the number of identified proteins. (c) Use of as little as a quarter unit of an iTRAQ label did not affect the number or identity of the identified proteins. (d) Protein extraction by methanol precipitation led to the highest protein yields and the most reproducible spectra. (e) Depletion of albumin and IgG did not increase the number of identified proteins or deepen the proteome coverage. Applying this optimized protocol to four pairs of long frozen urine samples from diabetic Pima Indians with or without nephropathy, we observed patterns suggesting segregation of cases and controls by iTRAQ spectra. We also identified several previously reported candidate biomarkers that showed trends toward differential expression, albeit not reaching statistical significance in this small sample set.With ongoing advances in mass spectrometry (MS) and proteomics technology, proteomics analysis is progressively occupying a central position in biomarker discovery platforms. Biofluids such as urine and blood are the preferred media for proteomics analysis because of their ease of collection and extensive history of use in clinical laboratory practice. Urine, in particular, is an information-rich fluid that can be collected non-invasively and in large quantities. Many urine proteins are produced or shed in the kidney and urogenital tract (1), making urine a promising proximal source of biomarkers for diseases affecting these structures.However, proteomics-based biomarker discovery in urine faces multiple challenges. Urine proteomics is complicated by low urine protein concentration, variations in pH, and high concentrations of salts and urea or other urine components that interfere with sample processing. The urine proteome can also change with individual variables such as hydration, diurnal change, diet, and physical activity as well as variation in sample collection, processing, and storage. In addition, urine proteomics shares the usual challenges of biomarker discovery in other biofluids such as throughput, cost, and the need for a reproducible and quantitative work flow.Isotopic or isobaric labeling methods to reduce variation, increase throughput, and enable quantitative analysis have been developed to address some of these challenges. One such method, isobaric tags for relative and absolute quantitation (iTRAQ)¹ (2), combines relative and absolute peptide quantification with multiplexing ability to enable an increased throughput as well as simultaneous comparison of up to eight samples within one experimental run. Variations induced by urine sample processing have been systematically evaluated for proteomics analyses using two-dimensional gel electrophoresis (3–6), differential gel electrophoresis (7), and liquid chromatography-coupled mass spectrometry (LC-MS) (5, 8, 9). However, no systematic analyses of urine sample collection and processing have been reported for iTRAQ.Before utilizing iTRAQ-based quantitative proteomics for urine biomarker discovery, we evaluated the impact of variation in several processing steps (addition of protease inhibitors, the starting protein quantities, quantity of the iTRAQ label, protein extraction methods, and depletion of abundant proteins) on iTRAQ protein identification and quantitation. Applying this optimized biomarker discovery protocol to small quantities of long frozen urine samples from the Pima longitudinal study of diabetic nephropathy, we observed patterns suggestive of segregation of cases and controls by iTRAQ spectra. We also observed trends toward differential expression in several proteins that had been identified as putative biomarkers in previous studies. However, given the small sample size, none of these proteins retained statistical significance after multiple testing correction.     

N-acetyltransferase polymorphism among northern Sudanese

Interindividual and interethnic differences in allele frequencies of N-acetyltransferase (NAT2) single nucleotide polymorphisms (SNPs) are responsible for phenotypic variability of adverse drug reactions and susceptibility to cancer. We genotyped the seven NAT2 common SNPs in 127 randomly selected unrelated northern Sudanese subjects using allele-specific and RFLP polymerase chain reaction (PCR) based methods. Molecular genotyping was enough to designate alleles for 41 individuals unambiguously, whereas 63 individuals' alleles were inferred from haplotypes previously described. In the remaining 23 individuals, however, the phase of the SNPs could not be decided because of multiple SNP heterozygotes. Using computational methods in the HAP and Phase programs, we confirmed the inferred alleles of the 62 individuals and predicted the remaining 23 ambiguous alleles. Twelve NAT2 alleles were identified. Four alleles coded for rapid acetylators (18%), and eight alleles coded for slow acetylators (82%). Two genotypes coded for rapid acetylation (3.9%), 10 for intermediate acetylation (27.6%), and 13 for slow acetylation (68.5%). The G191A African SNP and the G857A predominantly Asian SNP were each detected at a low frequency of 3.1%. The combination of molecular and computational analysis was useful in resolving ambiguous genotypes of NAT2 in multiple SNP heterozygotes. Among the northern Sudanese the SNPs associated with slow acetylation are more prevalent than in Caucasians and Asians. This and other African studies are suggestive of an African origin for NAT2-associated polymorphism.     

Evaluation of culture conditions for cellulase production by two Trichoderma reesei mutants under solid-state fermentation conditions

Response surface methodology (RSM) was used to evaluate the effects of fermentation parameters for cellulase production by Trichoderma reesei QM9414 and T. reesei MCG77 in solid-state fermentation using rice bran as substrate. Initial pH, moisture content and temperature were optimized using filter paper activity (FPA) as response. Statistical analysis of the results for T. reesei QM9414 showed that only moisture content had significant effect on cellulase activity and had a linear effect on enzyme activity (maximum enzyme activities were obtained at 70% moisture content). The results for T. reesei MCG77 showed that temperature and moisture content were the most significant parameters for cellulase activity. The optimum cellulase production was in the temperature range of 25-30 degrees C and moisture content between 55% and 70%. After the optimization, the FPA in T. reesei MCG77 was increased by 2.5 folds compared to that of T. reesei QM9414.