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.     

SDF2XYZ2SDF: how to exploit TINKER power in cheminformatics projects

An open-source tool capable of converting SD files (and virtually any other format through OpenBabel) into MMFF-typed XYZ coordinate files to be used with TINKER is described. SDF2XYZ2SDF allows including the power of TINKER molecular mechanics computations in automated cheminformatics workflows, such as conformational searches and virtual screening protocols.     

Antibacterial activity and chemical composition of the essential oil of Grammosciadium platycarpum Boiss. from Iran

The chemical composition of the essential oils obtained from two samples (GP1 and GP2) of Grammosciadium platycarpum Boiss. was analyzed by GC and GC-MS. The analysis of the oils resulted in the identification of twenty-two constituents. Linalool (79.0%-GP1, 81.8%-GP2) and limonene (10.0%, 5.8%) were found to be the major components, respectively. The in vitro antibacterial activities of these oils and their main compounds against seven Gram-positive and Gram-negative bacteria were investigated. The results exhibited that the total oils and their major components possess strong to moderate activities against all the tested bacteria except for Pseudomonas aeruginosa.     

The influence of peroxisome proliferator-activated receptor γ(1) during differentiation of mouse embryonic stem cells to neural cells

Peroxisome proliferator activated receptor γ, belongs to PPARs, which exerts various metabolic functions including differentiation process. To testify the importance of PPARγ in neural differentiation of mouse embryonic stem cells (mESCs), its expression level was assessed. Data revealed an elevation in expression level of PPARγ when neural precursors (NPs) are formed upon retinoic acid treatment. Thus, involvement of PPARγ in two stages of neural differentiation of mESCs, during and post-NPs formation was examined by application of its agonist and antagonist. Our results indicated that PPARγ inactivation via treatment with GW9662 during NPs formation, reduced expression of neural precursor and neural (neuronal and astrocytes) markers. However, PPARγ inactivation by antagonist treatment post-NPs formation stage only decreased the expression of mature astrocyte marker (Gfap) suggesting that inactivation of PPARγ by antagonist decreased astrocyte differentiation. Here, we have demonstrated the stage dependent role of PPARγ modulation on neural differentiation of mESCs by retinoic acid treatment for the first time.     

Effects of the Addition of Humic Substances on Soil Protease Activities in Andosols in the Presence of Cadmium

Cadmium extraction, sorption, and immobilization seem to be the effective mechanisms in detoxification of Cd-contaminated soil. Humic substances present in soils may play an important role both in controlling the negative effects of pollution with Cd and in stabilizing soil enzymes. In this context, we have compared the effects of humic substances on soil protease activities in the presence and absence of Cd in forest and cultivated field soil samples. The samples were taken from surface soils of Andosols in a single upland area of the Kanto district in Japan. Humic substances extracted from the two soils showed differences in elemental composition, the degree of condensation of aromatic groups, and the proportions of major functional groups. Compared with the control soil samples, those with added humic substances showed a significant increase in protease activities, even in the presence of Cd (10 and 50 mg Cd kg^?1 soil). However, the addition of Cd decreased the protease activities, protein contents, and soil pH in both soil samples at each of the two levels of humic substance fortification (+5% and +10%). Moreover, protease activities showed significant negative correlation with exchangeable Cd, but adding humic substances did not lead to a reduction in either sample. Thus, although the addition of humic substances increased and stabilized protease activities, it did not lead to a clear reversal of enzyme inhibition by Cd. The obtained results indicate that in both soil samples the humic substances used in this study did not have sufficient affinity to adsorb Cd, and the impact on enzyme activities depends on the difference in chemical characteristics of the added organic matter, as suggested by the difference in enhancement of protease activities between forest and cultivated field soil samples.     

An explorative study on potent Gram-negative specific LpxC inhibitors: CoMFA,CoMSIA, HQSAR and molecular docking

Pathogenic Gram-negative bacteria are responsible for nearly half of the serious human infections. Hologram quantitative structure–activity relationships (HQSAR), comparative molecular field analysis (CoMFA), and comparative molecular similarity index analysis (CoMSIA) were implemented on a group of 32 of potent Gram-negative LpxC inhibitors. The most effective HQSAR model was obtained using atoms, bonds, donor, and acceptor as fragment distinction. The cross-validated correlation coefficient (q²), non-cross-validated correlation coefficient (r²), and predictive correlation coefficient (r²_Pred) for test set of HQSAR model were 0.937, 0.993, and 0.892, respectively. The generated models were found to be statistically significant as the CoMFA model had (r²?=?0.967, q²?=?0.804, r²_Pred?=?0.827); the CoMSIA model had (r²?=?0.963, q²?=?0.752, r²_Pred?=?0.857). Molecular docking was employed to validate the results of the HQSAR, CoMFA, and CoMSIA models. Based on the obtained information, six new LpxC inhibitors have been designed.