Estimating the extrinsic incubation period of malaria using a mechanistic model of sporogony

During sporogony, malaria-causing parasites infect a mosquito, reproduce and migrate to the mosquito salivary glands where they can be transmitted the next time blood feeding occurs. The time required for sporogony, known as the extrinsic incubation period (EIP), is an important determinant of malaria transmission intensity. The EIP is typically estimated as the time for a given percentile, x, of infected mosquitoes to develop salivary gland sporozoites (the infectious parasite life stage), which is denoted by EIP_x. Many mechanisms, however, affect the observed sporozoite prevalence including the human-to-mosquito transmission probability and possibly differences in mosquito mortality according to infection status. To account for these various mechanisms, we present a mechanistic mathematical model, which explicitly models key processes at the parasite, mosquito and observational scales. Fitting this model to experimental data, we find greater variation in the EIP than previously thought: we estimated the range between EIP₁₀ and EIP₉₀ (at 27°C) as 4.5 days compared to 0.9 days using existing statistical methods. This pattern holds over the range of study temperatures included in the dataset. Increasing temperature from 21°C to 34°C decreased the EIP₅₀ from 16.1 to 8.8 days. Our work highlights the importance of mechanistic modelling of sporogony to (1) improve estimates of malaria transmission under different environmental conditions or disease control programs and (2) evaluate novel interventions that target the mosquito life stages of the parasite.     

Application of Statistical Thermodynamics to the Olfaction Mechanism

The application of the grand canonical ensemble in statisticalthermodynamics to the stimulus adsorption on the olfactory receptorsites, assuming some simplifying hypotheses, leads us to anexpression of the olfactory response R, which is a functionof various physico-chemical parameters involved in the olfactionmechanism, e.g. the stimulus concentration, the saturated vaporpressure, the power law exponent and the partition coefficient.This expression of R is in agreement with the olfactory responseof the Hill model, but is more explicit. Stevens' law and theolfactory threshold expression are easily deduced from R. Theexpression of the threshold we established from R enabled usto explain some empirical relations in the literature betweenthe parameters quoted above. The use of the grand canonicalensemble with the chemical potential notion gave us an interpretationof Stevens' law and a better understanding of the role of someparameters involved in the olfaction mechanism, such as saturatedvapor pressure and power law exponent. Chem. Senses 22: 67–75,1997.     

Predictors of Weight Loss in Adults with Topiramate‐Treated Epilepsy

Objective: We examined predictors of weight loss with topiramate, an anticonvulsant associated with weight loss in adults. Research Methods and Procedures: In this uncontrolled, prospective clinical trial, topiramate was added to existing anticonvulsants in adults (40 to 110 kg) with partial‐onset seizures. Primary measurements were change from baseline weight after 3 months and 1 year in patients completing 1 year of topiramate treatment (N = 38). Physiological and metabolic measures were analyzed for correlation with weight loss during topiramate treatment. Results: In patients who completed 1 year of topiramate treatment, baseline weight was reduced in 82% at 3 months and in 86% at 1 year. Mean body weight was reduced 3.0 kg (3.9% of baseline) at 3 months and 5.9 kg (7.3%) at 1 year. In obese patients [body mass index (BMI) ≥ 30 kg/m²], mean weight loss was 4.2 kg (4.3%) at 3 months and 10.9 kg (11.0%) at 1 year. Weight loss was primarily caused by reduction in body fat mass. For all patients, weight loss at 3 months correlated most strongly with reduced caloric intake (p = 0.02). At 1 year, caloric intake had returned to baseline levels; weight loss correlated most strongly with higher baseline BMI (p = 0.0007). Discussion: Our results suggest that weight loss occurs in most adults treated with topiramate and is sustained for at least 1 year. Reduced caloric intake may account, in part, for weight loss during early treatment. The pattern of weight loss differs according to baseline BMI, with obese patients experiencing greater weight loss during continued therapy.     

Fibrillation of transferrin

BackgroundThe nature of fibrillar deposits from aqueous solutions of human serum and recombinant human transferrin on mica and carbon-coated formvar surfaces has been investigated.Methods and ResultsAtomic force microscopy showed that the deposition of recombinant transferrin onto the hydrophilic surface of mica resulted in the formation of a monolayer-thick film composed of conformationally-strained flattened protein molecules. Elongated fibres developed on top of this layer and appeared to be composed of single proteins or small clusters thereof. Monomeric and dimeric transferrins were separated by gel permeation chromatography and their states of aggregation confirmed by mass spectrometry and dynamic light scattering. Transmission electron-microscopy showed that dimeric transferrin, but not monomeric transferrin, deposited on carbon-coated formvar grids forms rounded (circular) structures ca. 250 nm in diameter. Small transferrin fibrils ca. 250 nm long appeared to be composed of smaller rounded sub-units. Synchrotron radiation-circular dichroism and, Congo red and thioflavin-T dye-binding experiments suggested that transferrin aggregation in solution does not involve major structural changes to the protein or formation of classical β-sheet amyloid structures. Collisional cross sections determined via ion mobility–mass spectrometry showed little difference between the overall protein shapes of apo- and holo-transferrin in the gas phase.General significanceThe possibility that transferrin deformation and aggregation are involved in neurological disorders such as Parkinson's and Alzheimer's disease is discussed. This article is part of a Special Issue entitled Transferrins: Molecular mechanisms of iron transport and disorders.     

What it Takes to Get Passed On: Message Content,Style, and Structure as Predictors of Retransmission in the Boston Marathon Bombing Response

Message retransmission is a central aspect of information diffusion. In a disaster context, the passing on of official warning messages by members of the public also serves as a behavioral indicator of message salience, suggesting that particular messages are (or are not) perceived by the public to be both noteworthy and valuable enough to share with others. This study provides the first examination of terse message retransmission of official warning messages in response to a domestic terrorist attack, the Boston Marathon Bombing in 2013. Using messages posted from public officials’ Twitter accounts that were active during the period of the Boston Marathon bombing and manhunt, we examine the features of messages that are associated with their retransmission. We focus on message content, style, and structure, as well as the networked relationships of message senders to answer the question: what characteristics of a terse message sent under conditions of imminent threat predict its retransmission among members of the public? We employ a negative binomial model to examine how message characteristics affect message retransmission. We find that, rather than any single effect dominating the process, retransmission of official Tweets during the Boston bombing response was jointly influenced by various message content, style, and sender characteristics. These findings suggest the need for more work that investigates impact of multiple factors on the allocation of attention and on message retransmission during hazard events.     

A Forensically Sound Adversary Model for Mobile Devices

In this paper, we propose an adversary model to facilitate forensic investigations of mobile devices (e.g. Android, iOS and Windows smartphones) that can be readily adapted to the latest mobile device technologies. This is essential given the ongoing and rapidly changing nature of mobile device technologies. An integral principle and significant constraint upon forensic practitioners is that of forensic soundness. Our adversary model specifically considers and integrates the constraints of forensic soundness on the adversary, in our case, a forensic practitioner. One construction of the adversary model is an evidence collection and analysis methodology for Android devices. Using the methodology with six popular cloud apps, we were successful in extracting various information of forensic interest in both the external and internal storage of the mobile device.