Mathematical models of thrombin generation

Thrombin generation is a key step in the formation of a blood clot. It is the only enzyme able to cleave the protein fibrinogen into fibrin, which is vital to both the structure and stability of a clot. The formation of thrombin is the result of many positive and negative feedback loops, controlled by a series of proteins called coagulation factors, whose concentrations vary both between individuals and over time. It is the combined effects of all coagulation factors that regulate both the rate and amount of thrombin that is generated. Many models have been developed to predict the rate of thrombin generation and how it varies under differing conditions. An accurate and reliable model could prove to be a vital tool in drug development, such as for antithrombotics, and could aid in improving our understanding of both haemophilia and cardiovascular disease. However, while these models are validated qualitatively against variation in a few coagulation factors, they have rarely been validated quantitatively under variation in all factors, matching the variation seen in patient data. This sets up the key questions of this work; can any of these models accurately predict thrombin generation across variation in all coagulation factors, and if not, what changes need to be made to achieve this? In this work, we assess the accuracy of eight existing models against coagulation data from a large cohort of donors (n=348), showing none of these models are able to reliably reproduce thrombin generation. We then conduct multiple stages of exploratory analysis, identifying which reactions, reaction rates and coagulation factors control each of the model's predictions. Most notably, we observe a large amount of uncertainty in the reaction rates used to construct these models. We construct a new model of thrombin generation that quantifies the uncertainty in its reaction rates and addresses other issues seen in the current models. We use this new model to show that the uncertainty in these reaction rates results in high levels of uncertainty in model outputs and that the use of parameter inference methods significantly reduces this uncertainty. We conduct a simulation study, identifying improvements in the parameter inference methods we use and test assumptions made during model development. Finally, we outline future improvements and key next steps in the development of these models, most prominently, how to analyse and address model discrepancy and improve model specification

Mathematical models of thrombin generation

Thrombin generation is a key step in the formation of a blood clot. It is the only enzyme able to cleave the protein fibrinogen into fibrin, which is vital to both the structure and stability of a clot. The formation of thrombin is the result of many positive and negative feedback loops, controlled by a series of proteins called coagulation factors, whose concentrations vary both between individuals and over time. It is the combined effects of all coagulation factors that regulate both the rate and amount of thrombin that is generated. Many models have been developed to predict the rate of thrombin generation and how it varies under differing conditions. An accurate and reliable model could prove to be a vital tool in drug development, such as for antithrombotics, and could aid in improving our understanding of both haemophilia and cardiovascular disease. However, while these models are validated qualitatively against variation in a few coagulation factors, they have rarely been validated quantitatively under variation in all factors, matching the variation seen in patient data. This sets up the key questions of this work; can any of these models accurately predict thrombin generation across variation in all coagulation factors, and if not, what changes need to be made to achieve this? In this work, we assess the accuracy of eight existing models against coagulation data from a large cohort of donors (n=348), showing none of these models are able to reliably reproduce thrombin generation. We then conduct multiple stages of exploratory analysis, identifying which reactions, reaction rates and coagulation factors control each of the model's predictions. Most notably, we observe a large amount of uncertainty in the reaction rates used to construct these models. We construct a new model of thrombin generation that quantifies the uncertainty in its reaction rates and addresses other issues seen in the current models. We use this new model to show that the uncertainty in these reaction rates results in high levels of uncertainty in model outputs and that the use of parameter inference methods significantly reduces this uncertainty. We conduct a simulation study, identifying improvements in the parameter inference methods we use and test assumptions made during model development. Finally, we outline future improvements and key next steps in the development of these models, most prominently, how to analyse and address model discrepancy and improve model specification

Physiological Fontan Procedure

© 2019 Corno, Owen, Cangiani, Hall and Rona. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. Objective: The conventional Fontan circulation deviates the superior vena cava (SVC = 1/3 of the systemic venous return) toward the right lung (3/5 of total lung volume) and the inferior vena cava (IVC = 2/3 of the systemic venous return) toward the left lung (2/5 of total lung volume). A “physiological” Fontan deviating the SVC toward the left lung and the IVC toward the right lung was compared with the conventional setting by computational fluid dynamics, studying whether this setting achieves a more favorable hemodynamics than the conventional Fontan circulation. Materials and Methods: An in-silico 3D parametric model of the Fontan procedure was developed using idealized vascular geometries with invariant sizes of SVC, IVC, right pulmonary artery (RPA), and left pulmonary artery (LPA), steady inflow velocities at IVC and SVC, and constant equal outflow pressures at RPA and LPA. These parameters were set to perform finite-volume incompressible steady flow simulations, assuming a single-phase, Newtonian, isothermal, laminar blood flow. Numerically converged finite-volume mass and momentum flow balances determined the inlet pressures and the outflow rates. Numerical closed-path integration of energy fluxes across domain boundaries determined the flow energy loss rate through the Fontan circulation. The comparison evaluated: (1) mean IVC pressure; (2) energy loss rate; (3) kinetic energy maximum value throughout the domain volume. Results: The comparison of the physiological vs. conventional Fontan provided these results: (1) mean IVC pressure 13.9 vs. 14.1 mmHg (= 0.2 mmHg reduction); (2) energy loss rate 5.55 vs. 6.61 mW (= 16% reduction); (3) maximum kinetic energy 283 vs. 396 J/m3 (= 29% reduction). Conclusions: A more physiological flow distribution is accompanied by a reduction of mean IVC pressure and by substantial reductions of energy loss rate and of peak kinetic energy. The potential clinical impact of these hemodynamic changes in reducing the incidence and severity of the adverse long-term effects of the Fontan circulation, in particular liver failure and protein-losing enteropathy, still remains to be assessed and will be the subject of future work

Linking haploinsufficiency of the autism- and schizophrenia-associated gene Cyfip1 with striatal-limbic-cortical network dysfunction and cognitive inflexibility

Impaired behavioural flexibility is a core feature of neuropsychiatric disorders and is associated with underlying dysfunction of fronto-striatal circuitry. Reduced dosage of Cyfip1 is a risk factor for neuropsychiatric disorder, as evidenced by its involvement in the 15q11.2 (BP1–BP2) copy number variant: deletion carriers are haploinsufficient for CYFIP1 and exhibit a two- to four-fold increased risk of schizophrenia, autism and/or intellectual disability. Here, we model the contributions of Cyfip1 to behavioural flexibility and related fronto-striatal neural network function using a recently developed haploinsufficient, heterozygous knockout rat line. Using multi-site local field potential (LFP) recordings during resting state, we show that Cyfip1 heterozygous rats (Cyfip1+/−) harbor disrupted network activity spanning medial prefrontal cortex, hippocampal CA1 and ventral striatum. In particular, Cyfip1+/− rats showed reduced influence of nucleus accumbens and increased dominance of prefrontal and hippocampal inputs, compared to wildtype controls. Adult Cyfip1+/− rats were able to learn a single cue-response association, yet unable to learn a conditional discrimination task that engages fronto-striatal interactions during flexible pairing of different levers and cue combinations. Together, these results implicate Cyfip1 in development or maintenance of cortico-limbic-striatal network integrity, further supporting the hypothesis that alterations in this circuitry contribute to behavioural inflexibility observed in neuropsychiatric diseases including schizophrenia and autism

Structural Basis for α-Conotoxin Potency and Selectivity

Parkinson\u27s disease is a debilitating movement disorder characterized by altered levels of α6β2* nicotinic acetylcholine receptors (nAChRs) localized on presynaptic striatal catecholaminergic neurons. α-Conotoxin MII (α-CTx MII) is a highly useful ligand to probe α6ß2 nAChRs structure and function, but it does not discriminate among closely related α6* nAChR subtypes. Modification of the α-CTx MII primary sequence led to the identification of α-CTx MII[E11A], an analog with 500-5300 fold discrimination between α6* subtypes found in both human and non-human primates. α-CTx MII[E11A] binds most strongly (femtomolar dissociation constant) to the high affinity α6* nAChR, a subtype that is selectively lost in Parkinson\u27s disease. Here we present the three-dimensional solution structure for α-CTx MII[E11A] as determined by two-dimensional 1H NMR spectroscopy to 0.13 +/- 0.09 Ǻ backbone and 0.45 +/- 0.08 Ǻ heavy atom root mean square deviation from mean structure. Structural comparisons suggest that the increased hydrophobic area of α-CTx MII[E11A] relative to other members of the α-CTx family may be responsible for its exceptionally high affinity for α6α4β2* nAChR as well as discrimination between α6ß2 and α3β2 containing nAChRs. This finding may enable the rational design of novel peptide analogs that demonstrate enhanced specificity for α6* nAChR subunit interfaces and provide a means to better understand nAChR structural determinants that modulate brain dopamine levels and the pathophysiology of Parkinson\u27s disease

Using citizen science image analysis to measure seabird phenology

Developing standardized methodology to allow efficient and cost-effective ecological data collection, particularly at scale, is of critical importance for understanding species' declines. Remote camera networks can enable monitoring across large spatiotemporal scales and at relatively low researcher cost, but manually analysing images and extracting biologically meaningful data is time-consuming. Citizen science image analysis could reduce researcher workload and increase output from large datasets, while actively raising awareness of ecological and conservation issues. Nevertheless, testing the validity of citizen science data collection and the retention of volunteers is essential before integrating these approaches into long-term monitoring programmes. In this study, we used data from a Zooniverse citizen science project, Seabird Watch, to investigate changes in breeding timing of a globally declining seabird species, the Black-legged Kittiwake Rissa tridactyla. Time-lapse cameras collected >200 000 images between 2014 and 2023 across 11 locations covering the species' North Atlantic range (51.7°N–78.9°N), with over 35 000 citizen science volunteers ‘tagging’ adult and juvenile Kittiwakes in images. Most volunteers (81%) classified images for only a single day, and each volunteer classified a median of five images, suggesting that high volunteer recruitment rates are important for the project's continued success. We developed a standardized method to extract colony arrival and departure dates from citizen science annotations, which did not significantly differ from manual analysis by a researcher. We found that Kittiwake colony arrival was 2.6 days later and departure was 1.2 days later per 1° increase in latitude, which was consistent with expectations. Year-round monitoring also showed that Kittiwakes visited one of the lowest latitude colonies, Skellig Michael (51.8°N), during winter, whereas birds from a colony at similar latitude, Skomer Island (51.7°N), did not. Our integrated time-lapse camera and citizen science system offers a cost-effective means of measuring changes in colony attendance and subsequent breeding timing in response to environmental change in cliff-nesting seabirds. This study is of wide relevance to a broad range of species that could be monitored using time-lapse photography, increasing the geographical reach and international scope of ecological monitoring against a background of rapidly changing ecosystems and challenging funding landscapes

The propensity of non-concussive and concussive head contacts during elite-level women's rugby league matches : A prospective analysis of over 14,000 tackle events

Objectives Identify the frequency, propensity, and factors related to tackle events which result in contact with the head in elite-level women's rugby league. Design Prospective video analysis study. Methods Video footage from 59 Women's Super League matches were analysed (n = 14,378 tackle events). All tackle events were coded as no head contact or head contact. Other independent variables included: area contacting head, impacted player, concussion outcome, penalty outcome, round of competition, time in match and team standard. Results There were 83.0 ± 20.0 (propensity 304.0/1000 tackle events) head contacts per match. The propensity of head contact was significantly greater for the tackler than ball-carrier (178.5 vs. 125.7/1000 tackle events; incident rate ratio 1.42, 95 % confidence interval 1.34 to 1.50). Head contacts occurring from an arm, shoulder, and head occurred significantly more than any other contact type. The propensity of concussions was 2.7/1000 head contacts. There was no significant influence of team standard or time in match on the propensity of head contacts. Conclusions The observed head contacts can inform interventions, primarily focusing on the tackler not contacting the ball-carrier's head. The tackler's head should also be appropriately positioned to avoid contact with the ball-carrier's knee (highest propensity for concussion). The findings are consistent with other research in men's rugby. Law modifications and/or enforcement (reducing the number of un-penalised head contacts), concurrent with coaching interventions (optimising head placement or reducing the head being contacted) may help minimise head contact risk factors for women's rugby league

A physicochemical perspective of aging from single-cell analysis of pH, macromolecular and organellar crowding in yeast

Cellular aging is a multifactorial process that is characterized by a decline in homeostatic capacity, best described at the molecular level. Physicochemical properties such as pH and macromolecular crowding are essential to all molecular processes in cells and require maintenance. Whether a drift in physicochemical properties contributes to the overall decline of homeostasis in aging is not known. Here we show that the cytosol of yeast cells acidifies modestly in early aging and sharply after senescence. Using a macromolecular crowding sensor optimized for long-term FRET measurements, we show that crowding is rather stable and that the stability of crowding is a stronger predictor for lifespan than the absolute crowding levels. Additionally, in aged cells we observe drastic changes in organellar volume, leading to crowding on the µm scale, which we term organellar crowding. Our measurements provide an initial framework of physicochemical parameters of replicatively aged yeast cells