Evolution of size-dependent flowering in a variable environment: construction and analysis of a stochastic integral projection model

Understanding why individuals delay reproduction is a classic problem in evolutionary biology. In plants, the study of reproductive delays is complicated because growth and survival can be size and age dependent, individuals of the same size can grow by different amounts and there is temporal variation in the environment. We extend the recently developed integral projection approach to include size- and age-dependent demography and temporal variation. The technique is then applied to a long-term individually structured dataset for Carlina vulgaris, a monocarpic thistle. The parameterized model has excellent descriptive properties in terms of both the population size and the distributions of sizes within each age class. In Carlina, the probability of flowering depends on both plant size and age. We use the parameterized model to predict this relationship, using the evolutionarily stable strategy approach. Considering each year separately, we show that both the direction and the magnitude of selection on the flowering strategy vary from year to year. Provided the flowering strategy is constrained, so it cannot be a step function, the model accurately predicts the average size at flowering. Elasticity analysis is used to partition the size- and age-specific contributions to the stochastic growth rate, λs. We use λs to construct fitness landscapes and show how different forms of stochasticity influence its topography. We prove the existence of a unique stochastic growth rate, λs, which is independent of the initial population vector, and show that Tuljapurkar's perturbation analysis for log(λs) can be used to calculate elasticities

Evaluation of a cheap ultrasonic stage for light source coherence function measurement, optical coherence tomography and dynamic focusing

We evaluate the performance of a cheap ultrasonic stage in setups related to optical coherence tomography. The stage was used in several configurations: (1) optical delay line in an optical coherence tomography (OCT) setup; (2) as a delay line measuring coherence function of a low coherence source (e. g. superluminescent diode) and (3) in a dynamic focusing arrangement. The results are as follows: the stage is suitable for coherence function measurement (coherence length up to 70 mu m) of the light source and dynamic focusing. We found it unsuitable for OCT due to an unstable velocity profile. Despite this, the velocity profile has a repeatable shape (4% over 1000 A-scans) and slight modifications to the stage promise wider applications

Promoting creativity and innovation in biotechnology

Accepted versio

Plasma polymerised nanoscale coatings of controlled thickness for efficient solid-phase presentation of growth factors

The engineering of biomaterial surfaces and scaffolds for specific biomedical and clinical application is of growing interest. Certain functionalised surfaces can capture and deliver bioactive molecules, such as growth factors (GF), enhancing the clinical efficacy of such systems. With a custom-made plasma polymerisation reactor described here we have developed bioactive polymer coatings based on poly(ethyl acrylate) (PEA). This remarkable polymer unfolds fibronectin (FN) upon adsorption to allow the GF binding region of FN to sequester and present GFs with high efficiency. We systematically evaluate process conditions and their impact on plasma polymerised PEA coatings and characterise the effect of plasma power and deposition time on thickness, wettability and chemical composition of the coatings. We demonstrate that functional substrate roughness can be maintained after deposition of the polymer coatings. Importantly, we show that coatings deposited at different conditions all maintain a similar or better bioactivity than spin coated PEA references. We show that in PEA plasma polymerised coatings FN assembles into nanonetworks with high availability of integrin and GF binding regions that sequester bone morphogenetic protein-2 (BMP-2). We also report similar mesenchymal stem cell adhesion behaviour, as characterised by focal adhesions, and differentiation potential on BMP-2 coated surfaces, regardless of plasma deposition conditions. This is a potent and versatile technology that can help facilitate the use of GFs in clinical applications

Ectrodactyly-ectodermal dysplasia-clefting syndrome presenting with bilateral choanal atresia and rectal stenosis

We present the case of a male who shortly after birth developed acute respiratory distress due to bilateral choanal atresia, following which he was found to have rectal stenosis. Genetic testing for CHARGE syndrome was negative, but whole genome sequencing identified heterozygosity for a pathogenic missense variant in TP63 (c.727C > T, p.(Arg243Trp). He also has partial cutaneous syndactyly of the third and fourth fingers of the right hand, and bilateral lacrimal duct stenosis/aplasia. A later maxillofacial review identified a palpable submucousal cleft and his scalp hair is blond and slightly sparse. Choanal atresia and rectal stenosis are recognized features of ectrodactyly-ectodermal dysplasia-clefting syndrome, but we believe this is the first report of a case presenting with these features in the absence of the cardinal features.This article is freely available via Open Access. Click on the Publisher URL to access it via the publisher's site.published version, accepted version (12 month embargo), submitted versio

Almost uniform sampling via quantum walks

Many classical randomized algorithms (e.g., approximation algorithms for #P-complete problems) utilize the following random walk algorithm for {\em almost uniform sampling} from a state space $S$ of cardinality $N$: run a symmetric ergodic Markov chain $P$ on $S$ for long enough to obtain a random state from within $\epsilon$ total variation distance of the uniform distribution over $S$. The running time of this algorithm, the so-called {\em mixing time} of $P$, is $O(\delta^{-1} (\log N + \log \epsilon^{-1}))$, where $\delta$ is the spectral gap of $P$. We present a natural quantum version of this algorithm based on repeated measurements of the {\em quantum walk} $U_t = e^{-iPt}$. We show that it samples almost uniformly from $S$ with logarithmic dependence on $\epsilon^{-1}$ just as the classical walk $P$ does; previously, no such quantum walk algorithm was known. We then outline a framework for analyzing its running time and formulate two plausible conjectures which together would imply that it runs in time $O(\delta^{-1/2} \log N \log \epsilon^{-1})$ when $P$ is the standard transition matrix of a constant-degree graph. We prove each conjecture for a subclass of Cayley graphs.Comment: 13 pages; v2 added NSF grant info; v3 incorporated feedbac

Hurdles to uptake of mesenchymal stem cells and their progenitors in therapeutic products

Twenty-five years have passed since the first clinical trial utilising mesenchymal stomal/stem cells (MSCs) in 1995. In this time academic research has grown our understanding of MSC biochemistry and our ability to manipulate these cells in vitro using chemical, biomaterial, and mechanical methods. Research has been emboldened by the promise that MSCs can treat illness and repair damaged tissues through their capacity for immunomodulation and differentiation. Since 1995, 31 therapeutic products containing MSCs and/or progenitors have reached the market with the level of in vitro manipulation varying significantly. In this review, we summarise existing therapeutic products containing MSCs or mesenchymal progenitor cells and examine the challenges faced when developing new therapeutic products. Successful progression to clinical trial, and ultimately market, requires a thorough understanding of these hurdles at the earliest stages of in vitro pre-clinical development. It is beneficial to understand the health economic benefit for a new product and the reimbursement potential within various healthcare systems. Pre-clinical studies should be selected to demonstrate efficacy and safety for the specific clinical indication in humans, to avoid duplication of effort and minimise animal usage. Early consideration should also be given to manufacturing: how cell manipulation methods will integrate into highly controlled workflows and how they will be scaled up to produce clinically relevant quantities of cells. Finally, we summarise the main regulatory pathways for these clinical products, which can help shape early therapeutic design and testing

A Longitudinal Cline Characterizes the Genetic Structure of Human Populations in the Tibetan Plateau

Indigenous populations of the Tibetan plateau have attracted much attention for their good performance at extreme high altitude. Most genetic studies of Tibetan adaptations have used genetic variation data at the genome scale, while genetic inferences about their de- mography and population structure are largely based on uniparental markers. To provide genome-wide information on population structure, we analyzed new and published data of 338 individuals from indigenous populations across the plateau in conjunction with world- wide genetic variation data. We found a clear signal of genetic stratification across the east- west axis within Tibetan samples. Samples from more eastern locations tend to have higher genetic affinity with lowland East Asians, which can be explained by more gene flow from lowland East Asia onto the plateau. Our findings corroborate a previous report of admixture signals in Tibetans, which were based on a subset of the samples analyzed here, but add evidence for isolation by distance in a broader geospatial context

Quantum teleportation on a photonic chip

Quantum teleportation is a fundamental concept in quantum physics which now finds important applications at the heart of quantum technology including quantum relays, quantum repeaters and linear optics quantum computing (LOQC). Photonic implementations have largely focussed on achieving long distance teleportation due to its suitability for decoherence-free communication. Teleportation also plays a vital role in the scalability of photonic quantum computing, for which large linear optical networks will likely require an integrated architecture. Here we report the first demonstration of quantum teleportation in which all key parts - entanglement preparation, Bell-state analysis and quantum state tomography - are performed on a reconfigurable integrated photonic chip. We also show that a novel element-wise characterisation method is critical to mitigate component errors, a key technique which will become increasingly important as integrated circuits reach higher complexities necessary for quantum enhanced operation.Comment: Originally submitted version - refer to online journal for accepted manuscript; Nature Photonics (2014

Do individual differences in face recognition ability moderate the other ethnicity effect?

Individuals are better at recognizing faces from their own ethnic group compared with other ethnicity faces—the other-ethnicity effect (OEE). This finding is said to reflect differences in experience and familiarity to faces from other ethnicities relative to faces corresponding with the viewers' ethnicity. However, own-ethnicity face recognition performance ranges considerably within a population, from very poor to extremely good. In addition, within-population recognition performance on other-ethnicity faces can also vary considerably with some individuals being classed as “other ethnicity face blind” (Wan et al., 2017). Despite evidence for considerable variation in performance within population for faces of both types, it is currently unclear whether the magnitude of the OEE changes as a function of this variability. By recruiting large-scale multinational samples, we investigated the size of the OEE across the full range of own and other ethnicity face performance while considering measures of social contact. We find that the magnitude of the OEE is remarkably consistent across all levels of within-population own- and other-ethnicity face recognition ability, and this pattern was unaffected by social contact measures. These findings suggest that the OEE is a persistent feature of face recognition performance, with consequences for models built around very poor, and very good face recognizers