The Typical Flight Performance of Blowflies: Measuring the Normal Performance Envelope of Calliphora vicina Using a Novel Corner-Cube Arena

Despite a wealth of evidence demonstrating extraordinary maximal performance, little is known about the routine flight performance of insects. We present a set of techniques for benchmarking performance characteristics of insects in free flight, demonstrated using a model species, and comment on the significance of the performance observed. Free-flying blowflies (Calliphora vicina) were filmed inside a novel mirrored arena comprising a large (1.6 m1.6 m1.6 m) corner-cube reflector using a single high-speed digital video camera (250 or 500 fps). This arrangement permitted accurate reconstruction of the flies' 3-dimensional trajectories without the need for synchronisation hardware, by virtue of the multiple reflections of a subject within the arena. Image sequences were analysed using custom-written automated tracking software, and processed using a self-calibrating bundle adjustment procedure to determine the subject's instantaneous 3-dimensional position. We illustrate our method by using these trajectory data to benchmark the routine flight performance envelope of our flies. Flight speeds were most commonly observed between 1.2 ms−1 and 2.3 ms−1, with a maximum of 2.5 ms−1. Our flies tended to dive faster than they climbed, with a maximum descent rate (−2.4 ms−1) almost double the maximum climb rate (1.2 ms−1). Modal turn rate was around 240°s−1, with maximal rates in excess of 1700°s−1. We used the maximal flight performance we observed during normal flight to construct notional physical limits on the blowfly flight envelope, and used the distribution of observations within that notional envelope to postulate behavioural preferences or physiological and anatomical constraints. The flight trajectories we recorded were never steady: rather they were constantly accelerating or decelerating, with maximum tangential accelerations and maximum centripetal accelerations on the order of 3 g

Modelling pathogen load dynamics to elucidate mechanistic determinants of host-Plasmodium falciparum interactions

During infection, increasing pathogen load stimulates both protective and harmful aspects of the host response. The dynamics of this interaction are hard to quantify in humans, but doing so could improve understanding of mechanisms of disease and protection. We sought to model the contributions of parasite multiplication rate and host response to observed parasite load in individual subjects with Plasmodium falciparum malaria, using only data obtained at the time of clinical presentation, and then to identify their mechanistic correlates. We predicted higher parasite multiplication rates and lower host responsiveness in severe malaria cases, with severe anemia being more insidious than cerebral malaria. We predicted that parasite growth-inhibition was associated with platelet consumption, lower expression of CXCL10 and type-1 interferon-associated genes, but increased cathepsin G and matrix metallopeptidase 9 expression. We found that cathepsin G and matrix metallopeptidase 9 directly inhibit parasite invasion into erythrocytes. Parasite multiplication rate was associated with host iron availability and higher complement factor H levels, lower expression of gametocyte-associated genes but higher expression of translation-associated genes in the parasite. Our findings demonstrate the potential of using explicit modelling of pathogen load dynamics to deepen understanding of host-pathogen interactions and identify mechanistic correlates of protection

Considering Intra-individual Genetic Heterogeneity to Understand Biodiversity

In this chapter, I am concerned with the concept of Intra-individual Genetic Hetereogeneity (IGH) and its potential influence on biodiversity estimates. Definitions of biological individuality are often indirectly dependent on genetic sampling -and vice versa. Genetic sampling typically focuses on a particular locus or set of loci, found in the the mitochondrial, chloroplast or nuclear genome. If ecological function or evolutionary individuality can be defined on the level of multiple divergent genomes, as I shall argue is the case in IGH, our current genetic sampling strategies and analytic approaches may miss out on relevant biodiversity. Now that more and more examples of IGH are available, it is becoming possible to investigate the positive and negative effects of IGH on the functioning and evolution of multicellular individuals more systematically. I consider some examples and argue that studying diversity through the lens of IGH facilitates thinking not in terms of units, but in terms of interactions between biological entities. This, in turn, enables a fresh take on the ecological and evolutionary significance of biological diversity

Health-related quality of life of children with attention-deficit/hyperactivity disorder versus children with diabetes and healthy controls

The impact of attention-deficit/hyperactivity disorder (ADHD) on health-related quality of life (HRQoL) is reported to be similar to that of other mental health and physical disorders. In this cross-sectional study, we hypothesized that children with ADHD and children with type 1 diabetes mellitus (T1DM) would have significantly worse HRQoL compared with healthy children, and that better clinical status in ADHD and T1DM would be associated with better HRQoL. Children were recruited from three outpatient services in Scotland. Responses to two frequently used validated HRQoL instruments, the Paediatric Quality of Life Inventory (PedsQL) and Child Health and Illness Profile-child edition (CHIP-CE), were obtained from parents/carers and children (6–16 years) with/without ADHD or T1DM. Child and parent/carer-completed HRQoL measurements were evaluated for 213 children with ADHD, 58 children with T1DM and 117 healthy children (control group). Significantly lower self and parent/carer ratings were observed across most PedsQL (P < 0.001) and CHIP-CE (P < 0.05) domains (indicating reduced HRQoL) for the ADHD group compared with the T1DM and control groups. Parent/carer and child ratings were significantly correlated for both measures of HRQoL (PedsQL total score: P < 0.001; CHIP-CE all domains: P < 0.001), but only with low-to-moderate strength. Correlation between ADHD severity and HRQoL was significant with both PedsQL and CHIP-CE for all parent/carer (P < 0.01) and most child (P < 0.05) ratings; more ADHD symptoms were associated with poorer HRQoL. These data demonstrate that ADHD has a significant impact on HRQoL (as observed in both parent/carer and child ratings), which seems to be greater than that for children with T1DM

Belowground DNA-based techniques: untangling the network of plant root interactions

Contains fulltext : 91591.pdf (publisher's version ) (Closed access)7 p

Dynamics of multi-stage infections on networks

This paper investigates the dynamics of infectious diseases with a nonexponentially distributed infectious period. This is achieved by considering a multistage infection model on networks. Using pairwise approximation with a standard closure, a number of important characteristics of disease dynamics are derived analytically, including the final size of an epidemic and a threshold for epidemic outbreaks, and it is shown how these quantities depend on disease characteristics, as well as the number of disease stages. Stochastic simulations of dynamics on networks are performed and compared to output of pairwise models for several realistic examples of infectious diseases to illustrate the role played by the number of stages in the disease dynamics. These results show that a higher number of disease stages results in faster epidemic outbreaks with a higher peak prevalence and a larger final size of the epidemic. The agreement between the pairwise and simulation models is excellent in the cases we consider

Controlling infectious disease outbreaks: Lessons from mathematical modelling.

Accepted versio

ZNF804a Regulates Expression of the Schizophrenia-Associated Genes PRSS16, COMT, PDE4B, and DRD2

ZNF804a was identified by a genome-wide association study (GWAS) in which a single nucleotide polymorphism (SNP rs1344706) in ZNF804a reached genome-wide statistical significance for association with a combined diagnosis of schizophrenia (SZ) and bipolar disorder. Although the molecular function of ZNF804a is unknown, the amino acid sequence is predicted to contain a C2H2-type zinc-finger domain and suggests ZNF804a plays a role in DNA binding and transcription. Here, we confirm that ZNF804a directly contributes to transcriptional control by regulating the expression of several SZ associated genes and directly interacts with chromatin proximal to the promoter regions of PRSS16 and COMT, the two genes we find upregulated by ZNF804a. Using immunochemistry we establish that ZNF804a is localized to the nucleus of rat neural progenitor cells in culture and in vivo. We demonstrate that expression of ZNF804a results in a significant increase in transcript levels of PRSS16 and COMT, relative to GFP transfected controls, and a statistically significant decrease in transcript levels of PDE4B and DRD2. Furthermore, we show using chromatin immunoprecipitation assays (ChIP) that both epitope-tagged and endogenous ZNF804a directly interacts with the promoter regions of PRSS16 and COMT, suggesting a direct upregulation of transcription by ZNF804a on the expression of these genes. These results are the first to confirm that ZNF804a regulates transcription levels of four SZ associated genes, and binds to chromatin proximal to promoters of two SZ genes. These results suggest a model where ZNF804a may modulate a transcriptional network of SZ associated genes

An optimal control theory approach to non-pharmaceutical interventions

<p>Abstract</p> <p>Background</p> <p>Non-pharmaceutical interventions (NPI) are the first line of defense against pandemic influenza. These interventions dampen virus spread by reducing contact between infected and susceptible persons. Because they curtail essential societal activities, they must be applied judiciously. Optimal control theory is an approach for modeling and balancing competing objectives such as epidemic spread and NPI cost.</p> <p>Methods</p> <p>We apply optimal control on an epidemiologic compartmental model to develop triggers for NPI implementation. The objective is to minimize expected person-days lost from influenza related deaths and NPI implementations for the model. We perform a multivariate sensitivity analysis based on Latin Hypercube Sampling to study the effects of input parameters on the optimal control policy. Additional studies investigated the effects of departures from the modeling assumptions, including exponential terminal time and linear NPI implementation cost.</p> <p>Results</p> <p>An optimal policy is derived for the control model using a linear NPI implementation cost. Linear cost leads to a "bang-bang" policy in which NPIs are applied at maximum strength when certain state criteria are met. Multivariate sensitivity analyses are presented which indicate that NPI cost, death rate, and recovery rate are influential in determining the policy structure. Further death rate, basic reproductive number and recovery rate are the most influential in determining the expected cumulative death. When applying the NPI policy, the cumulative deaths under exponential and gamma terminal times are close, which implies that the outcome of applying the "bang-bang" policy is insensitive to the exponential assumption. Quadratic cost leads to a multi-level policy in which NPIs are applied at varying strength levels, again based on certain state criteria. Results indicate that linear cost leads to more costly implementation resulting in fewer deaths.</p> <p>Conclusions</p> <p>The application of optimal control theory can provide valuable insight to developing effective control strategies for pandemic. Our findings highlight the importance of establishing a sensitive and timely surveillance system for pandemic preparedness.</p