pwc-archive/papers-with-abstracts huggingface dataset:
Dynamical properties of feedback signalling in B lymphopoiesis: A mathematical modelling approach
Authors: Salvador Chulián, Alvaro Martínez-Rubio, Anna Marciniak-Czochra, Thomas Stiehl, Cristina Blázquez Goñi, Juan Francisco Rodríguez Gutiérrez, Manuel Ramirez Orellana, Ana Castillo Robleda, Víctor M. Pérez-García, María Rosa
Date: 2020-07-08 00:00:00

Haematopoiesis is the process of generation of blood cells. Lymphopoiesis generates lymphocytes, the cells in charge of the adaptive immune response. Disruptions of this process are associated with diseases like leukaemia, which is especially incident in children. The characteristics of self-regulation of this process make them suitable for a mathematical study. In this paper we develop mathematical models of lymphopoiesis using currently available data. We do this by drawing inspiration from existing structured models of cell lineage development and integrating them with paediatric bone marrow data, with special focus on regulatory mechanisms. A formal analysis of the models is carried out, giving steady states and their stability conditions. We use this analysis to obtain biologically relevant regions of the parameter space and to understand the dynamical behaviour of B-cell renovation. Finally, we use numerical simulations to obtain further insight into the influence of proliferation and maturation rates on the reconstitution of the cells in the B line. We conclude that a model including feedback regulation of cell proliferation represents a biologically plausible depiction for B-cell reconstitution in bone marrow. Research into haematological disorders could benefit from a precise dynamical description of B lymphopoiesis.
Size-regulated symmetry breaking in reaction-diffusion models of developmental transitions
Authors: Jake Cornwall Scoones, Deb Sankar Banerjee, Shiladitya Banerjee
Date: 2020-07-07 00:00:00

The development of multicellular organisms proceeds through a series of morphogenetic and cell-state transitions, transforming homogeneous zygotes into complex adults by a process of self-organization. Many of these transitions are achieved by spontaneous symmetry breaking mechanisms, allowing cells and tissues to acquire pattern and polarity by virtue of local interactions without an upstream supply of information. The combined work of theory and experiment has elucidated how these systems break symmetry during developmental transitions. Given such transitions are multiple and their temporal ordering is crucial, an equally important question is how these developmental transitions are coordinated in time. Using a minimal mass-conserved substrate-depletion model for symmetry breaking as our case study, we elucidate mechanisms by which cells and tissues can couple reaction-diffusion driven symmetry breaking to the timing of developmental transitions, arguing that the dependence of patterning mode on system size may be a generic principle by which developing organisms measure time. By analyzing different regimes of our model, simulated on growing domains, we elaborate three distinct behaviours, allowing for clock-, timer-, or switch-like dynamics. By relating these behaviours to experimentally documented case studies of developmental timing, we provide a minimal conceptual framework to interrogate how developing organisms coordinate developmental transitions.
Large-volume intrathecal administrations: impact on CSF pressure and safety implications
Authors: Vasily Belov, Janine Appleton, Stephan Levin, Pilar Giffenig, Beata Durcanova, Mikhail Papisov
Date: 2020-06-09 00:00:00

The increasing number of studies demonstrates the high potency of the intrathecal (IT) route for the delivery of biopharmaceuticals to the central nervous system (CNS). Our earlier data exhibited that both the infused volume and the infusion rate can regulate the initial disposition of the administered solute within the cerebrospinal fluid (CSF). On the other hand, fast additions of large volumes of liquid to the CSF inevitably raise the intracranial pressure (ICP), which may in turn lead to adverse reactions if the physiologically delimited threshold is exceeded. While long-term biological effects of elevated ICP (hydrocephalus) are known, the safety thresholds pertaining to short-term ICP elevations caused by IT infusions have not yet been characterized. This study aimed to investigate the dynamics of ICP in rats and non-human primates (NHPs) with respect to IT infusion rates and volumes. The data revealed that the addition of a liquid to the CSF raised the ICP in a rate and volume-dependent manner. At low infusion rates (<0.12 ml/min in rats and <2 ml/min in NHPs), NHPs and rats displayed similar tolerance patterns for extended durations. Specifically, safe accommodations of such added volumes were mainly facilitated by the accelerated pressure-dependent CSF drainage into the blood, with ICPs stabilizing at different levels below the safety threshold of 28+/-4 mm Hg in rats and 50+/-5 mm Hg in NHPs. High infusion rates caused uncompensated ICP elevations rapidly exceeding the safety thresholds. Their tolerance was species-dependent and was facilitated by the compensatory role of the varied components of craniospinal compliance while not excluding the possibility of other contributing factors. In conclusion, large volumes of liquids can safely be delivered via IT routes provided that ICP is monitored as a safety factor and cross-species physiological differences are accounted for.
A mechanistic framework for a priori pharmacokinetic predictions of orally inhaled drugs
Authors: Niklas Hartung, Jens Borghardt
Date: 2020-06-09 00:00:00
Tasks: parameter estimation

The fate of orally inhaled drugs is determined by pulmonary pharmacokinetic (PK) processes such as particle deposition, pulmonary drug dissolution, and mucociliary clearance. Although each single process has been systematically investigated, a quantitative understanding on their interaction remains limited and hence identifying optimal drug and formulation characteristics for orally inhaled drugs is still challenging. To investigate this complex interplay, the pulmonary processes can be integrated into mathematical models. However, existing modeling attempts considerably simplify these processes or are not systematically evaluated against (clinical) data. In this work, we developed a mathematical framework based on physiologically-structured population equations to integrate all relevant pulmonary processes mechanistically. A tailored numerical resolution strategy was chosen and the mechanistic model was evaluated systematically against different clinical datasets. Without any parameter estimation based on individual study data, the developed model simultaneously predicted (1) lung retention profiles of inhaled insoluble particles, (2) particle size-dependent PK of inhaled monodisperse particles, (3) PK differences between inhaled fluticasone propionate and budesonide, and (4) PK differences between healthy volunteers and asthmatic patients. Finally, to identify the most impactful optimization criteria for orally inhaled drugs, we investigated the impact of input parameters on both pulmonary and systemic exposure. Solubility of the inhaled drug did not have any relevant impact on local and systemic PK. Instead, pulmonary dissolution rate, particle size, tissue affinity, and systemic clearance were impactful potential optimization parameters. In the future, the developed prediction framework should be considered a powerful tool to identify optimal drug and formulation characteristics.
Reduced model for female endocrine dynamics: Validation and functional variations
Authors: E. J. Graham, N. Elhadad, D. Albers
Date: 2020-06-09 00:00:00

A normally functioning menstrual cycle requires significant crosstalk between hormones originating in ovarian and brain tissues. Reproductive hormone dysregulation may cause abnormal function and sometimes infertility. The inherent complexity in this endocrine system is a challenge to identifying mechanisms of cycle disruption, particularly given the large number of unknown parameters in existing mathematical models. We develop a new endocrine model to limit model complexity and use simulated distributions of unknown parameters for model analysis. By employing a comprehensive model evaluation, we identify a collection of mechanisms that differentiate normal and abnormal phenotypes. We also discover an intermediate phenotype--displaying relatively normal hormone levels and cycle dynamics--that is grouped statistically with the irregular phenotype. Results provide insight into how clinical symptoms associated with ovulatory disruption may not be detected through hormone measurements alone.
Relationship between blood pressure and flow rate in arteries using a modified Windkessel model
Authors: Nam Lyong Kang
Date: 2020-06-03 00:00:00

This study examined the flow rate in arteries using the modified Windkessel model, considering various models for blood pressure. An exact solution was derived using a Laplace transform method and the effects of blood pressure on the flow rate in an artery were examined. The effects of the flow resistance, arterial compliance, and inertia of blood on the flow rate were also investigated. The flow rate decreased with increasing inertia of the blood and flow resistance and decreasing arterial compliance. The height and position of the secondary peak were determined by a combination of the flow resistance, arterial compliance, and blood inertance. The results suggest that the risk of hypertension may increase with age because decreases in flow rate due to an increase in flow resistance and a decrease in arterial compliance were more substantial than the increase in flow rate caused by a decrease in blood inertance. The proposed method can provide information to examine how factors, such as aging, disease, and exercise, affect the flow rate in blood vessels.
Heart rate variability code: Does it exist and can we hack it?
Authors: Martin G. Frasch
Date: 2020-01-22 00:00:00
Tasks: Heart Rate Variability

Heart rate variability (HRV) has been studied for over 50 years, yet an integrative concept is missing on what HRV's mathematical properties represent physiologically. Here I introduce the notion of HRV code as an attempt to address this challenge systematically. I review the existing evidence from physiological studies in various species to support this concept and propose experiments to help validate and expand this notion further.
In Silico Trial to test COVID-19 candidate vaccines: a case study with UISS platform
Authors: Giulia Russo, Marzio Pennisi, Marco Viceconti, Francesco Pappalardo
Date: 2020-05-05 00:00:00

SARS-CoV-2 is a severe respiratory infection that infects humans. Its outburst entitled it as a pandemic emergence. To get a grip on this, outbreak specific preventive and therapeutic interventions are urgently needed. It must be said that, until now, there are no existing vaccines for coronaviruses. To promptly and rapidly respond to pandemic events, the application of in silico trials can be used for designing and testing medicines against SARS-CoV-2 and speed-up the vaccine discovery pipeline, predicting any therapeutic failure and minimizing undesired effects. Here, we present an in silico platform that showed to be in very good agreement with the latest literature in predicting SARS- CoV-2 dynamics and related immune system host response. Moreover, it has been used to predict the outcome of one of the latest suggested approach to design an effective vaccine, based on monoclonal antibody. UISS is then potentially ready to be used as an in silico trial platform to predict the outcome of vaccination strategy against SARS-CoV-2.
Prediction of repurposed drugs for treating lung injury in COVID-19
Authors: Bing He, Lana Garmire
Date: 2020-03-30 00:00:00
Tasks: Respiratory Failure

Coronavirus disease (COVID-19) is an infectious disease discovered in 2019 and currently in outbreak across the world. Lung injury with severe respiratory failure is the leading cause of death in COVID-19, brought by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). However, there still lacks efficient treatment for COVID-19 induced lung injury and acute respiratory failure. Inhibition of Angiotensin-converting enzyme 2 (ACE2) caused by spike protein of SARS-CoV-2 is the most plausible mechanism of lung injury in COVID-19. We propose two candidate drugs, COL-3 (a chemically modified tetracycline) and CGP-60474 (a cyclin-dependent kinase inhibitor), for treating lung injuries in COVID-19, based on their abilities to reverse the gene expression patterns in HCC515 cells treated with ACE2 inhibitor and in human COVID-19 patient lung tissues. Further bioinformatics analysis shows that twelve significantly enriched pathways (P-value <0.05) overlap between HCC515 cells treated with ACE2 inhibitor and human COVID-19 patient lung tissues, including signaling pathways known to be associated with lung injury such as TNF signaling, MAPK signaling and Chemokine signaling pathways. All these twelve pathways are targeted in COL-3 treated HCC515 cells, in which genes such as RHOA, RAC2, FAS, CDC42 have reduced expression. CGP-60474 shares eleven of twelve pathways with COL-3 with common target genes such as RHOA. It also uniquely targets genes related to lung injury, such as CALR and MMP14. In summary, this study shows that ACE2 inhibition is likely part of the mechanisms leading to lung injury in COVID-19, and that compounds such as COL-3 and CGP-60474 have the potential as repurposed drugs for its treatment.
Electrostatic precipitation of exhaled particles for tensiometric examination of pulmonary surfactant
Authors: Andrey Shmyrov, Alexey Mizev, Irina Mizeva, Anastasia Shmyrova
Date: 2020-04-03 00:00:00

Objective: Collecting exhaled particles that represent small droplets of the alveolar lining fluid shows great promise as a tool for pulmonary surfactant (PS) sampling. For this purpose, we present a setup consisting of two modules, namely, a module for droplet collecting, called an electrostatic aerosol trapping (ESAT) system, and a measurement module for studying PS properties. We suggest the way how to extract numerical values from the experimental data associated with PS properties. Methods: The operating principle of ESAT is based on the electrostatic precipitation of exhaled particles. The native material was collected directly on the water surface, where an accumulated adsorbed film of PS was examined with tensiometric method. The modified capillary waves method adapted to study small volume samples was utilized. The efficiency of the setup was verified in the experiments with healthy subjects. Conclusion: The accumulation of PS components on the water surface in an amount sufficient for tensiometric study was reported. It was shown how to extract the numerical values from the experimental data characterizing PS properties. Significance: The idea underlying the new concept used in this study may give impetus to further development of point-of-care facilities for collecting PS samples and for their express analysis.
A Computational Model of Levodopa-Induced Toxicity in Substantia Nigra Pars Compacta in Parkinson's Disease
Authors: Vignayanandam R. Muddapu, Karthik Vijayakumar, Keerthiga Ramakrishnan, V Srinivasa Chakravarthy
Date: 2020-04-01 00:00:00

Parkinson's disease (PD) is caused by the progressive loss of dopaminergic cells in substantia nigra pars compacta (SNc). The root cause of this cell loss in PD is still not decisively elucidated. A recent line of thinking traces the cause of PD neurodegeneration to metabolic deficiency. Due to exceptionally high energy demand, SNc neurons exhibit a higher basal metabolic rate and higher oxygen consumption rate, which results in oxidative stress. Recently, we have suggested that the excitotoxic loss of SNc cells might be due to energy deficiency occurring at different levels of neural hierarchy. Levodopa (LDOPA), a precursor of dopamine, which is used as a symptom-relieving treatment for PD, leads to outcomes that are both positive and negative. Several researchers suggested that LDOPA might be harmful to SNc cells due to oxidative stress. The role of LDOPA in the course of PD pathogenesis is still debatable. We hypothesize that energy deficiency can lead to LDOPA-induced toxicity (LIT) in two ways: by promoting dopamine-induced oxidative stress and by exacerbating excitotoxicity in SNc. We present a multiscale computational model of SNc-striatum system, which will help us in understanding the mechanism behind neurodegeneration postulated above and provides insights for developing disease-modifying therapeutics. It was observed that SNc terminals are more vulnerable to energy deficiency than SNc somas. During LDOPA therapy, it was observed that higher LDOPA dosage results in increased loss of somas and terminals in SNc. It was also observed that co-administration of LDOPA and glutathione (antioxidant) evades LDOPA-induced toxicity in SNc neurons. We show that our proposed model was able to capture LDOPA-induced toxicity in SNc, caused by energy deficiency.
Effects of fixatives on myelin molecular order probed with RP-CARS microscopy
Authors: Giuseppe de Vito, Paola Parlanti, Roberta Cecchi, Stefano Luin, Valentina Cappello, Ilaria Tonazzini, Vincenzo Piazza
Date: 2020-03-09 00:00:00

When live imaging is not feasible, sample fixation allows preserving the ultrastructure of biological samples for subsequent microscopy analysis. This process could be performed with various methods, each one affecting differently the biological structure of the sample. While these alterations were well-characterized using traditional microscopy, little information is available about the effects of the fixatives on the spatial molecular orientation of the biological tissue. We tackled this issue by employing Rotating-Polarization Coherent Anti-Stokes Raman Scattering (RP-CARS) microscopy to study the effects of different fixatives on the myelin sub-micrometric molecular order and micrometric morphology. RP-CARS is a novel technique derived from CARS microscopy that allows probing spatial orientation of molecular bonds while maintaining the intrinsic chemical selectivity of CARS microscopy. By characterizing the effects of the fixation procedures, the present work represents a useful guide for the choice of the best fixation technique(s), in particular for polarisation-resolved CARS microscopy. Finally, we show that the combination of paraformaldehyde and glutaraldehyde can be effectively employed as a fixative for RP-CARS microscopy, as long as the effects on the molecular spatial distribution, here characterized, are taken into account.
RP-CARS reveals molecular spatial order anomalies in myelin of an animal model of Krabbe disease
Authors: Giuseppe de Vito, Valentina Cappello, Ilaria Tonazzini, Marco Cecchini, Vincenzo Piazza
Date: 2020-03-08 00:00:00

Krabbe disease (KD) is a rare demyelinating sphingolipidosis, often fatal in the first years of life. It is caused by the inactivation of the galactocerebrosidase (GALC) enzyme that causes an increase in the cellular levels of psychosine considered to be at the origin of the tissue-level effects. GALC is inactivated also in the Twitcher (TWI) mouse: a genetic model of KD that is providing important insights into the understating of the pathogenetic process and the development of possible treatments. In this article an innovative optical technique, RP-CARS, is proposed as a tool to study the degree of order of the CH2 bonds inside the myelin sheaths of TWI-mice sciatic-nerve fibres. RP-CARS, a recently developed variation of CARS microscopy, is able to combine the intrinsic chemical selectivity of CARS microscopy with molecular-bond-spatial-orientation sensibility. This is the first time RP-CARS is applied to the study of a genetic model of a pathology, leading to the demonstration of a post-onset progressive spatial disorganization of the myelin CH2 bonds. The presented result could be of great interest for a deeper understanding of the pathogenic mechanisms underlying the human KD and, moreover, it is an additional proof of the experimental validity of this microscopy technique.
Parameter estimation and treatment optimization in a stochastic model for immunotherapy of cancer
Authors: Modibo Diabate, Loren Coquille, Adeline Samson
Date: 2018-06-05 00:00:00
Tasks: parameter estimation

Adoptive Cell Transfer therapy of cancer is currently in full development and mathematical modeling is playing a critical role in this area. We study a stochastic model developed by Baar et al. in 2015 for modeling immunotherapy against melanoma skin cancer. First, we estimate the parameters of the deterministic limit of the model based on biological data of tumor growth in mice. A Nonlinear Mixed Effects Model is estimated by the Stochastic Approximation Expectation Maximization algorithm. With the estimated parameters, we head back to the stochastic model and calculate the probability that the T cells all get exhausted during the treatment. We show that for some relevant parameter values, an early relapse is due to stochastic fluctuations (complete T cells exhaustion) with a non negligible probability. Then, focusing on the relapse related to the T cell exhaustion, we propose to optimize the treatment plan (treatment doses and restimulation times) by minimizing the T cell exhaustion probability in the parameter estimation ranges.
Emerging classes of antioxidant to cancer therapy: a review of clinical and experimental studies
Authors: Qurat-ul-Ain, M. Iqbal Choudhary
Date: 2020-03-06 00:00:00

This review mainly focuses on the relation between antioxidants with cancer therapy. Antioxidants have been reported to play an essential role to reduce free radical species. Free radicals commonly cause oxidative damage which is a common factor in the aging process, and also the vital factor of formation, and development of major disease specially cancer. Although, since last many decades several antioxidants belong to natural and synthetic origin have been tested in clinical trials against oxidative stress, however these clinical trials end up with undesirable effects. This review also complied with the most recent findings of oxidative stress, highlighting of free racial production, and its related oxidative damage at cellular and molecular level, with the new and existing natural and synthetic classes of free radical scavenger and their related clinical trials.
Mathematical Model of ingested glucose in Glucose-Insulin Regulation
Authors: Sourav Chowdhury, Sourabh Kumar Manna, Suparna Roychowdhury, Indranath Chaudhuri
Date: 2020-03-05 00:00:00

Here, we develop a mathematical model for glucose-insulin regulatory system. The model includes a new parameter which is the amount of ingested glucose. Ingested glucose is an external glucose source coming from digested food. We assume that the external glucose or ingested glucose decays exponentially with time. We establish a system of three linear ordinary differential equations with this new parameter, derive stability analysis and the solution of this model.