pwc-archive/papers-with-abstracts huggingface dataset:
Modelling and Optimal Control of Multi Strain Epidemics, with Application to COVID-19
Authors: Edilson F. Arruda, Dayse H. Pastore, Clauda M. Dias, Shyam S. Das
Date: 2021-01-19 00:00:00

This work introduces a novel epidemiological model that simultaneously considers multiple viral strains, reinfections due to waning immunity response over time and an optimal control formulation. This enables us to derive optimal mitigation strategies over a prescribed time horizon under a more realistic framework that does not imply perennial immunity and a single strain, although these can also be derived as particular cases of our formulation. The model also allows estimation of the number of infections over time in the absence of mitigation strategies under any number of viral strains. We validate our approach in the light of the COVID-19 epidemic and present a number of experiments to shed light on the overall behaviour under one or two strains in the absence of sufficient mitigation measures. We also derive optimal control strategies for distinct mitigation costs and evaluate the effect of these costs on the optimal mitigation measures over a two-year horizon. The results show that relaxations in the mitigation measures cause a rapid increase in the number of cases, which then demand more restrictive measures in the future.
Clustering Future Scenarios Based on Predicted Range Maps
Authors: Matthew Davidow, Cory Merow, Judy Che-Castaldo, Toryn Schafer, Marie-Christine Duker, Derek Corcoran, David Matteson
Date: 2021-01-19 00:00:00
Tasks: Clustering, Diversity

Predictions of biodiversity trajectories under climate change are crucial in order to act effectively in maintaining the diversity of species. In many ecological applications, future predictions are made under various global warming scenarios as described by a range of different climate models. The outputs of these various predictions call for a reliable interpretation. We propose a interpretable and flexible two step methodology to measure the similarity between predicted species range maps and cluster the future scenario predictions utilizing a spectral clustering technique. We find that clustering based on ecological impact (predicted species range maps) is mainly driven by the amount of warming. We contrast this with clustering based only on predicted climate features, which is driven mainly by climate models. The differences between these clusterings illustrate that it is crucial to incorporate ecological information to understand the relevant differences between climate models. The findings of this work can be used to better synthesize forecasts of biodiversity loss under the wide spectrum of results that emerge when considering potential future biodiversity loss.
Parameter inference in a computational model of hemodynamics in pulmonary hypertension
Authors: Amanda L. Colunga, Mitchel J. Colebank, REU Program, Mette S. Olufsen
Date: 2021-01-15 00:00:00
Tasks: Clinical Knowledge, Time Series, Time Series Analysis, Uncertainty Quantification

Pulmonary hypertension (PH), defined by a mean pulmonary arterial pressure (mPAP) $>$ 20 mmHg, is characterized by increased pulmonary vascular resistance and decreased pulmonary arterial compliance. There are few measurable biomarkers of PH progression, but a conclusive diagnosis of the disease requires invasive right heart catheterization (RHC). Patient-specific computational models of the cardiovascular system are a potential noninvasive tool for determining additional indicators of disease severity. Using computational modeling, this study quantifies physiological parameters indicative of disease severity in nine PH patients. The model includes all four heart chambers and the pulmonary and systemic circulations. We consider two sets of calibration data: static (systolic \& diastolic values) RHC data and a combination of static and continuous, time-series waveform data. We determine a subset of identifiable parameters for model calibration using sensitivity analyses and multistart inference, and carry out uncertainty quantification post-inference. Results show that additional waveform data enables accurate calibration of the right atrial reservoir and pump function across the PH cohort. Model outcomes, including stroke work and pulmonary resistance-compliance relations, reflect typical right heart dynamics in PH phenotypes. Lastly, we show that estimated parameters agree with previous, non-modeling studies, supporting this type of analysis in translational PH research.
Modeling Oyster Reef Reproductive Sustainability: Analyzing Gamete Viability, Hydrodynamics, and Reef Structure to Facilitate Restoration of $\textit{Crassostrea virginica}$
Authors: Justin Weissberg, Vinny Pagano
Date: 2021-01-13 00:00:00

The eastern oyster is a keystone species and ecosystem engineer. However, restoration efforts of wild oysters are often unsuccessful, in that they do not produce a robust population of oysters that are able to successfully reproduce. Furthermore, the dynamics of wild oyster fertilization is not yet well understood. Through conducting an experiment predicated on quantifying the influence of elementary aspects of fertilization kinetics--sperm concentration, gamete age, and success rate--we found that, as stochastic as the mating process may seem, there are correlations which fundamentally serve as the framework for assessing long-term sustainability, reef structure, and hydrodynamic parameters in relation to fertilization. We then focused on mathematically defining a procedure which simulated a concentration distribution of a single sperm and egg release where there existed conditions necessary for breeding to take place. We found a very significant impact of both gamete age and sperm concentration on fertilization rate ($p < 0.0001$). Our hydrodynamic model demonstrates that distance can also drastically influence broadcast spawning. This could be used as a foundation for developing a flexible model for wild oyster fertilization based on placement, initial seawater conditions, and size of the starting population. The results of this research could be implemented into a more user-friendly program which would accept multiple variables as inputs and output the probability of fertilization given arbitrary values. By accounting for environmental deviations, this generalization would increase its compatibility with the public and actualize the project's intended purpose: enhance the planning of oyster reef restoration projects.
Detecting seasonal episodic-like spatiotemporal memory patterns using animal movement modelling
Authors: Peter R. Thompson, Andrew E. Derocher, Mark A. Edwards, Mark A. Lewis
Date: 2021-01-11 00:00:00
Tasks: Model Selection, parameter estimation

1. Spatial memory plays a role in the way animals perceive their environments, resulting in memory-informed movement patterns that are observable to ecologists. Developing mathematical techniques to understand how animals use memory in their environments allows for an increased understanding of animal cognition. 2. Here we describe a model that accounts for the memory of seasonal or ephemeral qualities of an animal's environment. The model captures multiple behaviors at once by allowing for resource selection in the present time as well as long-distance navigations to previously visited locations within an animal's home range. 3. We performed a set of analyses on simulated data to test our model, determining that it can provide informative results from as little as one year of discrete-time location data. We also show that the accuracy of model selection and parameter estimation increases with more location data. 4. This model has potential to identify a specific mechanism in which animals use memory to optimize their foraging, by revisiting temporally and predictably variable resources at consistent time lags.
The pathway elaboration method for mean first passage time estimation in large continuous-time Markov chains with applications to nucleic acid kinetics
Authors: Sedigheh Zolaktaf, Frits Dannenberg, Mark Schmidt, Anne Condon, Erik Winfree
Date: 2021-01-11 00:00:00

For predicting the kinetics of nucleic acid reactions, continuous-time Markov chains (CTMCs) are widely used. The rate of a reaction can be obtained through the mean first passage time (MFPT) of its CTMC. However, a typical issue in CTMCs is that the number of states could be large, making MFPT estimation challenging, particularly for events that happen on a long time scale (rare events). We propose the pathway elaboration method, a time-efficient probabilistic truncation-based approach for detailed-balance CTMCs. It can be used for estimating the MFPT for rare events in addition to rapidly evaluating perturbed parameters without expensive recomputations. We demonstrate that pathway elaboration is suitable for predicting nucleic acid kinetics by conducting computational experiments on 267 measurements that cover a wide range of rates for different types of reactions. We utilize pathway elaboration to gain insight on the kinetics of two contrasting reactions, one being a rare event. We then compare the performance of pathway elaboration with the stochastic simulation algorithm (SSA) for MFPT estimation on 237 of the reactions for which SSA is feasible. We further build truncated CTMCs with SSA and transition path sampling (TPS) to compare with pathway elaboration. Finally, we use pathway elaboration to rapidly evaluate perturbed model parameters during optimization with respect to experimentally measured rates for these 237 reactions. The testing error on the remaining 30 reactions, which involved rare events and were not feasible to simulate with SSA, improved comparably with the training error. Our framework and dataset are available at https://github.com/ DNA-and-Natural-Algorithms-Group/PathwayElaboration.
Using excess deaths and testing statistics to improve estimates of COVID-19 mortalities
Authors: Lucas Böttcher, Maria D'Orsogna, Tom Chou
Date: 2021-01-10 00:00:00

Factors such as non-uniform definitions of mortality, uncertainty in disease prevalence, and biased sampling complicate the quantification of fatality during an epidemic. Regardless of the employed fatality measure, the infected population and the number of infection-caused deaths need to be consistently estimated for comparing mortality across regions. We combine historical and current mortality data, a statistical testing model, and an SIR epidemic model, to improve estimation of mortality. We find that the average excess death across the entire US is 13$\%$ higher than the number of reported COVID-19 deaths. In some areas, such as New York City, the number of weekly deaths is about eight times higher than in previous years. Other countries such as Peru, Ecuador, Mexico, and Spain exhibit excess deaths significantly higher than their reported COVID-19 deaths. Conversely, we find negligible or negative excess deaths for part and all of 2020 for Denmark, Germany, and Norway.
A Cloud connected NO2 and Ozone Sensor System for Personalized Pediatric Asthma Research and Management
Authors: Quan Dong, Baichen Li, R. Scott Downen, Nam Tran, Elizabeth Chorvinsky, Dinesh K. Pillai, Mona E. Zaghloul, Zhenyu Li
Date: 2021-01-08 00:00:00
Tasks: Management

This paper presents a cloud-connected indoor air quality sensor system that can be deployed to patients' homes to study personal microenvironmental exposure for asthma research and management. The system consists of multiple compact sensor units that can measure residential NO2, ozone, humidity, and temperature at one minute resolution and a cloud based informatic system that acquires, stores, and visualizes the microenvironmental data in real time. The sensor hardware can measure NO2 as low as 10 ppb and ozone at 15 ppb. The cloud informatic system is implemented using open-source software on Amazon Web Service for easy deployment and scalability. This system was successfully deployed to pediatric asthma patients' homes in a pilot study. In this study, we discovered that some families can have short term NO2 exposure higher than EPA's one hour exposure limit (100 ppb), and NO2 micropollution episodes often arise from natural gas appliance usage such as gas stove burning during cooking. By combining the personalized air pollutant exposure measurements with the physiological responses from a patient diary and medical record, this system can enable novel asthma research and personalized asthma management.
Transmission of droplet-conveyed infectious agents such as SARS-CoV-2 by speech and vocal exercises during speech therapy: preliminary experiment concerning airflow velocity
Authors: Antoine Giovanni, Thomas Radulesco, Gilles Bouchet, Alexia Mattei, Joana Révis, Estelle Bogdanski, Justin Michel
Date: 2021-01-06 00:00:00

Purpose Infectious agents, such as SARS-CoV-2, can be carried by droplets expelled during breathing. The spatial dissemination of droplets varies according to their initial velocity. After a short literature review, our goal was to determine the velocity of the exhaled air during vocal exercises. Methods A propylene glycol cloud produced by 2 e-cigarettes' users allowed visualization of the exhaled air emitted during vocal exercises. Airflow velocities were measured during the first 200 ms of a long exhalation, a sustained vowel /a/ and varied vocal exercises. For the long exhalation and the sustained vowel /a/, the decrease of airflow velocity was measured until 3 s. Results were compared with a Computational Fluid Dynamics (CFD) study using boundary conditions consistent with our experimental study. Results Regarding the production of vowels, higher velocities were found in loud and whispered voices than in normal voice. Voiced consonants like /3/ or /v/ generated higher velocities than vowels. Some voiceless consonants, e.g., /t/ generated high velocities, but long exhalation had the highest velocities. Semi-occluded vocal tract exercises generated faster airflow velocities than loud speech, with a decreased velocity during voicing. The initial velocity quickly decreased as was shown during a long exhalation or a sustained vowel /a/. Velocities were consistent with the CFD data. Conclusion Initial velocity of the exhaled air is a key factor influencing droplets trajectory. Our study revealed that vocal exercises produce a slower airflow than long exhalation. Speech therapy should, therefore, not be associated with an increased risk of contamination when implementing standard recommendations.
A promising approach for the real-time quantification of cytosolic protein-protein interactions in living cells
Authors: Ilaria Incaviglia, Andreas Frutiger, Yves Blickenstorfer, Fridolin Treindl, Giulia Ammirati, Ines Lüchtefeld, Birgit Dreier, Andreas Plückthun, Janos Vörös, Andreas M Reichmuth
Date: 2020-11-26 00:00:00
Tasks: Specificity

In recent years, cell-based assays have been frequently used in molecular interaction analysis. Cell-based assays complement traditional biochemical and biophysical methods, as they allow for molecular interaction analysis, mode of action studies and even drug screening processes to be performed under physiologically relevant conditions. In most cellular assays, biomolecules are usually labeled to achieve specificity. In order to overcome some of the drawbacks associated with label-based assays, we have recently introduced cell-based molography as a biosensor for the analysis of specific molecular interactions involving native membrane receptors in living cells. Here, we expand this assay to cytosolic protein-protein interactions. First, we created a biomimetic membrane receptor by tethering one cytosolic interaction partner to the plasma membrane. The artificial construct is then coherently arranged into a two-dimensional pattern within the cytosol of living cells. Thanks to the molographic sensor, the specific interactions between the coherently arranged protein and its endogenous interaction partners become visible in real-time without the use of a fluorescent label. This method turns out to be an important extension of cell-based molography because it expands the range of interactions that can be analyzed by molography to those in the cytosol of living cells.
Modeling tau transport in the axon initial segment
Authors: Ivan A. Kuznetsov, Andrey V. Kuznetsov
Date: 2020-06-30 00:00:00

By assuming that tau protein can be in seven kinetic states, we developed a model of tau protein transport in the axon and in the axon initial segment (AIS). Two separate sets of kinetic constants were determined, one in the axon and the other in the AIS. This was done by fitting the model predictions in the axon with experimental results and by fitting the model predictions in the AIS with the assumed linear increase of the total tau concentration in the AIS. The calibrated model was used to make predictions about tau transport in the axon and in the AIS. To the best of our knowledge, this is the first paper that presents a mathematical model of tau transport in the AIS. Our modeling results suggest that binding of free tau to MTs creates a negative gradient of free tau in the AIS. This leads to diffusion-driven tau transport from the soma into the AIS. The model further suggests that slow axonal transport and diffusion-driven transport of tau work together in the AIS, moving tau anterogradely. Our numerical results predict an interplay between these two mechanisms: as the distance from the soma increases, the diffusion-driven transport decreases, while motor-driven transport becomes larger. Thus, the machinery in the AIS works as a pump, moving tau into the axon.
ATP-driven separation of liquid phase condensates in bacteria
Authors: B. Guilhas, J. C. Walter, J. Rech, G. David, N. -O. Walliser, J. Palmeri, C. Mathieu-Demaziere, A. Parmeggiani, J. Y. Bouet, A. Le Gall, M. Nollmann
Date: 2020-10-01 00:00:00

Liquid-liquid phase separated (LLPS) states are key to compartmentalise components in the absence of membranes, however it is unclear whether LLPS condensates are actively and specifically organized in the sub-cellular space and by which mechanisms. Here, we address this question by focusing on the ParABS DNA segregation system, composed of a centromeric-like sequence (parS), a DNA-binding protein (ParB) and a motor (ParA). We show that parS-ParB associate to form nanometer-sized, round condensates. ParB molecules diffuse rapidly within the nucleoid volume, but display confined motions when trapped inside ParB condensates. Single ParB molecules are able to rapidly diffuse between different condensates, and nucleation is strongly favoured by parS. Notably, the ParA motor is required to prevent the fusion of ParB condensates. These results describe a novel active mechanism that splits, segregates and localises non-canonical LLPS condensates in the sub-cellular space.
Nanoelectrodes for intracellular measurements of reactive oxygen and nitrogen species in single living cells
Authors: Keke Hu, Yan-Ling Liu, Alexander Oleinick, Michael Mirkin, Wei-Hua Huang, Christian Amatore
Date: 2020-07-07 00:00:00

Reactive oxygen and nitrogen species (ROS and RNS) play important roles in various physiological processes (e.g., phagocytosis) and pathological conditions (e.g., cancer). The primary ROS/RNS, viz., hydrogen peroxide, peroxynitrite ion, nitric oxide, and nitrite ion, can be oxidized at different electrode potentials and therefore detected and quantified by electroanalytical techniques. Nanometer-sized electrochemical probes are especially suitable for measuring ROS/RNS in single cells and cellular organelles. In this article, we survey recent advances in localized measurements of ROS/RNS inside single cells and discuss several methodological issues, including optimization of nanoelectrode geometry, precise positioning of an electrochemical probe inside a cell, and interpretation of electroanalytical data.
Amperometric Measurements and Dynamic Models Reveal a Mechanism for How Zinc Alters Neurotransmitter Release
Authors: Lin Ren, Alexander Oleinick, Irina Svir, Christian Amatore, Andrew Ewing
Date: 2020-07-07 00:00:00

Zinc, a suspected potentiator of learning and memory, is shown to affect exocytotic release and storage in neurotransmitter-containing vesicles. Structural and size analysis of the vesicular dense core and halo using transmission electron microscopy was combined with single-cell amperometry to study the vesicle size changes induced after zinc treatment and to compare these changes to theoretical predictions based on the concept of partial release as opposed to full quantal release. This powerful combined analytical approach establishes the existence of an unsuspected strong link between vesicle structure and exocytotic dynamics which can be used to explain the mechanism of regulation of synaptic plasticity by Zn 2+ through modulation of neurotransmitter release.
Hindering loads prompt clustered configurations that enhance stability during cargo transport by multiple Kinesin-1
Authors: Shreyas Bhaban, Rachit Srivastava, James Melbourne, Saurav Talukdar, Murti V. Salapaka
Date: 2020-07-04 00:00:00

Transport of intracellular cargo is often mediated by teams of molecular motors that function in a chaotic environment under varying conditions. We show that the motors have unique steady state behavior which enables transport modalities that are robust. Under reduced ATP concentrations, multi-motor configurations are preferred over single motors. Higher load force drives motors to cluster, but very high loads compel them to separate in a manner that promotes immediate cargo movement once the load subsides. These inferences, backed by analytical guarantees, provide unique insights into the coordination strategies adopted by molecular motors to transport intracellular cargo.
Motor protein transport along inhomogeneous microtubules
Authors: Shawn D. Ryan, Zachary McCarthy, Mykhailo Potomkin
Date: 2020-05-05 00:00:00

Many cellular processes rely on the cell's ability to transport material to and from the nucleus. Networks consisting of many microtubules and actin filaments are key to this transport. Recently, the inhibition of intracellular transport has been implicated in neurodegenerative diseases such as Alzheimer's disease and Amyotrophic Lateral Sclerosis (ALS). Furthermore, microtubules may contain so-called defective regions where motor protein velocity is reduced due to accumulation of other motors and microtubule associated proteins. In this work, we propose a new mathematical model describing the motion of motor proteins on microtubules which incorporate a defective region. We take a mean-field approach derived from a first principle lattice model to study motor protein dynamics and density profiles. In particular, given a set of model parameters we obtain a closed-form expression for the equilibrium density profile along a given microtubule. We then verify the analytic results using mathematical analysis on the discrete model and Monte Carlo simulations. This work will contribute to the fundamental understanding of inhomogeneous microtubules providing insight into microscopic interactions that may result in the onset of neurodegenerative diseases. Our results for inhomogeneous microtubules are consistent with prior work studying the homogeneous case.