Multiparametric cell cycle analysis by automated microscopy

Cell cycle analysis using flow cytometry (FC) to measure cellular DNA content is a common procedure in drug mechanism of action studies. Although this technique lends itself readily to cell lines that grow in suspension, adherent cell cultures must be resuspended in a cumbersome and potentially invasive procedure that normally involves trypsinization and mechanical agitation of monolayer cultures. High-content analysis (HCA), an automated microscopy-based technology, is well suited to analysis of monolayer cell cultures but provides intrinsically less accurate determination of cellular DNA content than does FC and thus is not the method of choice for cell cycle analysis. Using Cellomics's ArrayScan reader, the authors have developed a 4-color multiparametric HCA approach for cell cycle analysis of adherent cells based on detection of DNA content (4,6-diamidino-2-phenylindole [DAPI] fluorescence), together with the known cell cycle markers bromo-2-deoxyuridine (BrdU) incorporation, cyclin B1 expression, and histone H3 (Ser28) phosphorylation within a single cell population. Considering all 4 markers together, a reliable and accurate quantification of cell cycle phases was possible, as compared with flow cytometric analysis. Using this assay, specific cell cycle blocks induced by treatment with thymidine, paclitaxel, or nocodazole as test drugs were easily monitored in adherent cultures of U-2 OS osteosarcoma cells.     

Evolving public perceptions and stability in vaccine uptake

Recent vaccine scares and sudden spikes in vaccine demand remind us that the effectiveness of mass vaccination programs is governed by the public perception of vaccination. Previous work has shown that the tendency of individuals to optimize self-interest can lead to vaccination levels that are suboptimal for a community. We use game theory to relate population-level demand for vaccines to decision-making by individuals with varied beliefs about the costs of infection and vaccination. In contrast to previous work proposing that universal vaccination is impossible in a game theoretic context, we show that optimal individual behavior can vary between universal vaccination and no vaccination, depending on the relative costs and benefits to individuals. By coupling game models and epidemic models, we demonstrate that the pursuit of self-interest often leads to stable dynamics but can lead to oscillations in vaccine uptake over time. The instability is exacerbated in populations that are more homogeneous with respect to their perceptions of vaccine and infection risks. This research illustrates the importance of applying temporal models to an inherently temporal situation, namely, the time evolution of vaccine coverage in an informed population with a voluntary vaccination policy.     

Evaluating Paratransgenesis as a Potential Control Strategy for African Trypanosomiasis

Genetic-modification strategies are currently being developed to reduce the transmission of vector-borne diseases, including African trypanosomiasis. For tsetse, the vector of African trypanosomiasis, a paratransgenic strategy is being considered: this approach involves modification of the commensal symbiotic bacteria Sodalis to express trypanosome-resistance-conferring products. Modified Sodalis can then be driven into the tsetse population by cytoplasmic incompatibility (CI) from Wolbachia bacteria. To evaluate the effectiveness of this paratransgenic strategy in controlling African trypanosomiasis, we developed a three-species mathematical model of trypanosomiasis transmission among tsetse, humans, and animal reservoir hosts. Using empirical estimates of CI parameters, we found that paratransgenic tsetse have the potential to eliminate trypanosomiasis, provided that any extra mortality caused by Wolbachia colonization is low, that the paratransgene is effective at protecting against trypanosome transmission, and that the target tsetse species comprises a large majority of the tsetse population in the release location.     

Free-Riding Behavior in Vaccination Decisions: An Experimental Study

Individual decision-making regarding vaccination may be affected by the vaccination choices of others. As vaccination produces externalities reducing transmission of a disease, it can provide an incentive for individuals to be free-riders who benefit from the vaccination of others while avoiding the cost of vaccination. This study examined an individual''s decision about vaccination in a group setting for a hypothetical disease that is called “influenza” using a computerized experimental game. In the game, interactions with others are allowed. We found that higher observed vaccination rate within the group during the previous round of the game decreased the likelihood of an individual''s vaccination acceptance, indicating the existence of free-riding behavior. The free-riding behavior was observed regardless of parameter conditions on the characteristics of the influenza and vaccine. We also found that other predictors of vaccination uptake included an individual''s own influenza exposure in previous rounds increasing the likelihood of vaccination acceptance, consistent with existing empirical studies. Influenza prevalence among other group members during the previous round did not have a statistically significant effect on vaccination acceptance in the current round once vaccination rate in the previous round was controlled for.     

Disease Surveillance on Complex Social Networks

As infectious disease surveillance systems expand to include digital, crowd-sourced, and social network data, public health agencies are gaining unprecedented access to high-resolution data and have an opportunity to selectively monitor informative individuals. Contact networks, which are the webs of interaction through which diseases spread, determine whether and when individuals become infected, and thus who might serve as early and accurate surveillance sensors. Here, we evaluate three strategies for selecting sensors—sampling the most connected, random, and friends of random individuals—in three complex social networks—a simple scale-free network, an empirical Venezuelan college student network, and an empirical Montreal wireless hotspot usage network. Across five different surveillance goals—early and accurate detection of epidemic emergence and peak, and general situational awareness—we find that the optimal choice of sensors depends on the public health goal, the underlying network and the reproduction number of the disease (R₀). For diseases with a low R₀, the most connected individuals provide the earliest and most accurate information about both the onset and peak of an outbreak. However, identifying network hubs is often impractical, and they can be misleading if monitored for general situational awareness, if the underlying network has significant community structure, or if R₀ is high or unknown. Taking a theoretical approach, we also derive the optimal surveillance system for early outbreak detection but find that real-world identification of such sensors would be nearly impossible. By contrast, the friends-of-random strategy offers a more practical and robust alternative. It can be readily implemented without prior knowledge of the network, and by identifying sensors with higher than average, but not the highest, epidemiological risk, it provides reasonably early and accurate information.     

Optimal Timing of Disease Transmission in an Age-Structured Population

It is a common medical folk-practice for parents to encourage their children to contract certain infectious diseases while they are young. This folk-practice is controversial, in part, because it contradicts the long-term public health goal of minimizing disease incidence. We study an epidemiological model of infectious disease in an age-structured population where virulence is age-dependent and show that, in some cases, the optimal behavior will increase disease transmission. This provides a rigorous justification of the concept of “endemic stability,” and demonstrates that folk-practices may have been historically justified.     

Disease Severity and Mortality Can Be Independently Regulated in a Mouse Model of Experimental Graft versus Host Disease

Graft versus host disease (GVHD) is the major limitation of allogeneic hematopoietic stem cell transplantation (HSCT) presenting high mortality and morbidity rates. However, the exact cause of death is not completely understood and does not correlate with specific clinical and histological parameters of disease. Here we show, by using a semi-allogeneic mouse model of GVHD, that mortality and morbidity can be experimentally separated. We injected bone marrow-derived dendritic cells (BMDC) from NOD2/CARD15-deficient donors into semi-allogeneic irradiated chimaeras and observed that recipients were protected from death. However, no protection was observed regarding clinical or pathological scores up to 20 days after transplantation. Protection from death was associated with decreased bacterial translocation, faster hematologic recovery and epithelial integrity maintenance despite mononuclear infiltration at day 20 post-GVHD induction with no skew towards different T helper phenotypes. The protected mice recovered from aGVHD and progressively reached scores compatible with healthy animals. Altogether, our data indicate that severity and mortality can be separate events providing a model to study transplant-related mortality.     

Spatial and Temporal Clustering of Chikungunya Virus Transmission in Dominica

Using geo-referenced case data, we present spatial and spatio-temporal cluster analyses of the early spread of the 2013–2015 chikungunya virus (CHIKV) in Dominica, an island in the Caribbean. Spatial coordinates of the locations of the first 417 reported cases observed between December 15^th, 2013 and March 11^th, 2014, were captured using the Global Positioning System (GPS). We observed a preponderance of female cases, which has been reported for CHIKV outbreaks in other regions. We also noted statistically significant spatial and spatio-temporal clusters in highly populated areas and observed major clusters prior to implementation of intensive vector control programs suggesting early vector control measures, and education had an impact on the spread of the CHIKV epidemic in Dominica. A dynamical identification of clusters can lead to local assessment of risk and provide opportunities for targeted control efforts for nations experiencing CHIKV outbreaks.