Food Quality in Producer-Grazer Models: A Generalized Analysis

Stoichiometric constraints play a role in the dynamics of natural populations, but are not explicitly considered in most mathematical models. Recent theoretical works suggest that these constraints can have a significant impact and should not be neglected. However, it is not yet resolved how stoichiometry should be integrated in population dynamical models, as different modeling approaches are found to yield qualitatively different results. Here we investigate a unifying framework that reveals the differences and commonalities between previously proposed models for producer-grazer systems. Our analysis reveals that stoichiometric constraints affect the dynamics mainly by increasing the intraspecific competition between producers and by introducing a variable biomass conversion efficiency. The intraspecific competition has a strongly stabilizing effect on the system, whereas the variable conversion efficiency resulting from a variable food quality is the main determinant for the nature of the instability once destabilization occurs. Only if the food quality is high an oscillatory instability, as in the classical paradox of enrichment, can occur. While the generalized model reveals that the generic insights remain valid in a large class of models, we show that other details such as the specific sequence of bifurcations encountered in enrichment scenarios can depend sensitively on assumptions made in modeling stoichiometric constraints.Comment: Online appendixes include

Automatic Segmentation of the Left Ventricle in Cardiac CT Angiography Using Convolutional Neural Network

Accurate delineation of the left ventricle (LV) is an important step in evaluation of cardiac function. In this paper, we present an automatic method for segmentation of the LV in cardiac CT angiography (CCTA) scans. Segmentation is performed in two stages. First, a bounding box around the LV is detected using a combination of three convolutional neural networks (CNNs). Subsequently, to obtain the segmentation of the LV, voxel classification is performed within the defined bounding box using a CNN. The study included CCTA scans of sixty patients, fifty scans were used to train the CNNs for the LV localization, five scans were used to train LV segmentation and the remaining five scans were used for testing the method. Automatic segmentation resulted in the average Dice coefficient of 0.85 and mean absolute surface distance of 1.1 mm. The results demonstrate that automatic segmentation of the LV in CCTA scans using voxel classification with convolutional neural networks is feasible.Comment: This work has been published as: Zreik, M., Leiner, T., de Vos, B. D., van Hamersvelt, R. W., Viergever, M. A., I\v{s}gum, I. (2016, April). Automatic segmentation of the left ventricle in cardiac CT angiography using convolutional neural networks. In Biomedical Imaging (ISBI), 2016 IEEE 13th International Symposium on (pp. 40-43). IEE

Designing synthetic networks in silico : A generalised evolutionary algorithm approach

Background: Evolution has led to the development of biological networks that are shaped by environmental signals. Elucidating, understanding and then reconstructing important network motifs is one of the principal aims of Systems & Synthetic Biology. Consequently, previous research has focused on finding optimal network structures and reaction rates that respond to pulses or produce stable oscillations. In this work we present a generalised in silico evolutionary algorithm that simultaneously finds network structures and reaction rates (genotypes) that can satisfy multiple defined objectives (phenotypes). Results: The key step to our approach is to translate a schema/binary-based description of biological networks into systems of ordinary differential equations (ODEs). The ODEs can then be solved numerically to provide dynamic information about an evolved networks functionality. Initially we benchmark algorithm performance by finding optimal networks that can recapitulate concentration time-series data and perform parameter optimisation on oscillatory dynamics of the Repressilator. We go on to show the utility of our algorithm by finding new designs for robust synthetic oscillators, and by performing multi-objective optimisation to find a set of oscillators and feed-forward loops that are optimal at balancing different system properties. In sum, our results not only confirm and build on previous observations but we also provide new designs of synthetic oscillators for experimental construction. Conclusions: In this work we have presented and tested an evolutionary algorithm that can design a biological network to produce desired output. Given that previous designs of synthetic networks have been limited to subregions of network- and parameter-space, the use of our evolutionary optimisation algorithm will enable Synthetic Biologists to construct new systems with the potential to display a wider range of complex responses

ICARES: a real-time automated detection tool for clusters of infectious diseases in the Netherlands.

Clusters of infectious diseases are frequently detected late. Real-time, detailed information about an evolving cluster and possible associated conditions is essential for local policy makers, travelers planning to visit the area, and the local population. This is currently illustrated in the Zika virus outbreak

Visions, Values, and Videos: Revisiting Envisionings in Service of UbiComp Design for the Home

UbiComp has been envisioned to bring about a future dominated by calm computing technologies making our everyday lives ever more convenient. Yet the same vision has also attracted criticism for encouraging a solitary and passive lifestyle. The aim of this paper is to explore and elaborate these tensions further by examining the human values surrounding future domestic UbiComp solutions. Drawing on envisioning and contravisioning, we probe members of the public (N=28) through the presentation and focus group discussion of two contrasting animated video scenarios, where one is inspired by "calm" and the other by "engaging" visions of future UbiComp technology. By analysing the reasoning of our participants, we identify and elaborate a number of relevant values involved in balancing the two perspectives. In conclusion, we articulate practically applicable takeaways in the form of a set of key design questions and challenges.Comment: DIS'20, July 6-10, 2020, Eindhoven, Netherland

Integrating cross-frequency and within band functional networks in resting-state MEG: A multi-layer network approach

Neuronal oscillations exist across a broad frequency spectrum, and are thought to provide a mechanism of interaction between spatially separated brain regions. Since ongoing mental activity necessitates the simultaneous formation of multiple networks, it seems likely that the brain employs interactions within multiple frequency bands, as well as cross-frequency coupling, to support such networks. Here, we propose a multi-layer network framework that elucidates this pan-spectral picture of network interactions. Our network consists of multiple layers (frequency-band specific networks) that influence each other via inter-layer (cross-frequency) coupling. Applying this model to MEG resting-state data and using envelope correlations as connectivity metric, we demonstrate strong dependency between within layer structure and inter-layer coupling, indicating that networks obtained in different frequency bands do not act as independent entities. More specifically, our results suggest that frequency band specific networks are characterised by a common structure seen across all layers, superimposed by layer specific connectivity, and inter-layer coupling is most strongly associated with this common mode. Finally, using a biophysical model, we demonstrate that there are two regimes of multi-layer network behaviour; one in which different layers are independent and a second in which they operate highly dependent. Results suggest that the healthy human brain operates at the transition point between these regimes, allowing for integration and segregation between layers. Overall, our observations show that a complete picture of global brain network connectivity requires integration of connectivity patterns across the full frequency spectrum

Single-shot, high-dose rabbit ATG for rejection prophylaxis after kidney transplantation

We studied the effects of a single intravenous injection of rabbit ATG (RIVM, Bilthoven, The Netherlands) in a dose of 8 mg/kg body weight administered 6 h after kidney transplantation on graft survival, rejection incidence, T-cell subsets, and cost-effectiveness. A total of 58 (37 male/21 female) consecutive renal allograft recipients were entered in this trial. Treatment results were compared with 56 patients treated with intravenous cyclosporin (CyA). In all patients concomitant medication consisted of steroids and azathioprine, followed by oral CyA. Following rabbit ATG, T cells (WT31) quickly disappeared from the peripheral blood and a return to greater than 100/mm3 was observed at a median of 7 (range 3–21) days. Graft survival was the same in both groups, as was the incidence of primary nonfunction. The rate of acute rejection was significantly lower in the rabbit ATG-treated patients (12 % vs 50%). We conclude that a single shot of rabbit ATG is an attractive, easy, and cost-effective induction scheme with a low incidence of delayed graft function and acute rejection episodes. A relatively high incidence of vascular thrombosis of the graft, however, warrants further study before this treatment regimen can be generally applied

Better early functional outcome after short stem total hip arthroplasty? A prospective blinded randomised controlled multicentre trial comparing the Collum Femoris Preserving stem with a Zweymuller straight cementless stem total hip replacement for the treatment of primary osteoarthritis of the hip

Objectives Primary aim was to compare the functional results at 3 months and 2 years between short and conventional cementless stem total hip arthroplasty (THA). Secondary aim was to determine the feasibility of a double-blind implant-related trial. Design A prospective blinded randomised controlled multicentre trial in patients with osteoarthritis of the hip. All patients, research assistants, clinical assessors, investigators and data analysts were blinded to the type of prosthesis. Population: 150 patients between 18 and 70 years with osteoarthritis of the hip, 75 in the short stem and 75 in the conventional stem group. Mean age: 60 years (SD 7). Interventions: The Collum Femoris Preserving short stem versus the Zweymuller Alloclassic conventional stem. Main outcome measures The Dutch version of the Hip Disability and Osteoarthritis Outcome Score (HOOS). Secondary outcomes measures: Harris Hip Score, the Physical Component Scale of the SF12, the Timed Up and Go test, Pain and the EQ-5D. Feasibility outcomes: continued blinding, protocol adherence and follow-up success rate. Results No significant difference between the two groups. Mean HOOS total score in the short stem group increased 32.7 points from 36.6 (95% CI 32.9 to 40.2) preoperatively to 69.3 (95% CI 66.4 to 72.1) at 3 months follow-up. Mean HOOS total score in the conventional straight stem group increased 36.3 points from 37.1 (95% CI 33.9 to 40.3) preoperatively to 73.4 (95% CI 70.3 to 76.4) at 3 months follow-up. 91.2% of patients remained blinded at 2 years follow-up. Both protocol adherence and follow-up success rate were 98%. Conclusions Functional result at 3 months and 2 years after short stem THA is not superior to conventional cementless THA. There were more perioperative and postoperative complications in the short stem group. Direct comparison of two hip implants in a double-blinded randomised controlled trial is feasible. Trial registration number NTR1560