A computational model predicts sex-specific responses to calcium channel blockers in mammalian mesenteric vascular smooth muscle

The function of the smooth muscle cells lining the walls of mammalian systemic arteries and arterioles is to regulate the diameter of the vessels to control blood flow and blood pressure. Here, we describe an in silico model, which we call the 'Hernandez-Hernandez model', of electrical and Ca2+ signaling in arterial myocytes based on new experimental data indicating sex-specific differences in male and female arterial myocytes from murine resistance arteries. The model suggests the fundamental ionic mechanisms underlying membrane potential and intracellular Ca2+ signaling during the development of myogenic tone in arterial blood vessels. Although experimental data suggest that KV1.5 channel currents have similar amplitudes, kinetics, and voltage dependencies in male and female myocytes, simulations suggest that the KV1.5 current is the dominant current regulating membrane potential in male myocytes. In female cells, which have larger KV2.1 channel expression and longer time constants for activation than male myocytes, predictions from simulated female myocytes suggest that KV2.1 plays a primary role in the control of membrane potential. Over the physiological range of membrane potentials, the gating of a small number of voltage-gated K+ channels and L-type Ca2+ channels are predicted to drive sex-specific differences in intracellular Ca2+ and excitability. We also show that in an idealized computational model of a vessel, female arterial smooth muscle exhibits heightened sensitivity to commonly used Ca2+ channel blockers compared to male. In summary, we present a new model framework to investigate the potential sex-specific impact of antihypertensive drugs.

MIL-CELL: a tool for multi-scale simulation of yeast replication and prion transmission

The single-celled baker's yeast, Saccharomyces cerevisiae, can sustain a number of amyloid-based prions, the three most prominent examples being [URE3], [PSI+], and [PIN+]. In the laboratory, haploid S. cerevisiae cells of a single mating type can acquire an amyloid prion in one of two ways (i) spontaneous nucleation of the prion within the yeast cell, and (ii) receipt via mother-to-daughter transmission during the cell division cycle. Similarly, prions can be lost due to (i) dissolution of the prion amyloid by its breakage into non-amyloid monomeric units, or (ii) preferential donation/retention of prions between the mother and daughter during cell division. Here we present a computational tool (Monitoring Induction and Loss of prions in Cells; MIL-CELL) for modelling these four general processes using a multiscale approach describing both spatial and kinetic aspects of the yeast life cycle and the amyloid-prion behavior. We describe the workings of the model, assumptions upon which it is based and some interesting simulation results pertaining to the wave-like spread of the epigenetic prion elements through the yeast population. MIL-CELL is provided as a stand-alone GUI executable program for free download with the paper. MIL-CELL is equipped with a relational database allowing all simulated properties to be searched, collated and graphed. Its ability to incorporate variation in heritable properties means MIL-CELL is also capable of simulating loss of the isogenic nature of a cell population over time. The capability to monitor both chronological and reproductive age also makes MIL-CELL potentially useful in studies of cell aging.

Training-Induced Increase in V·O2max and Critical Power, and Acceleration of V·O2 on-Kinetics Result from Attenuated Pi Increase Caused by Elevated OXPHOS Activity

Computer simulations using a dynamic model of the skeletal muscle bioenergetic system, involving the Pi-double-threshold mechanism of muscle fatigue, demonstrate that the training-induced increase in V·O2max, increase in critical power (CP) and acceleration of primary phase II of the V·O2 on kinetics (decrease in t0.63) is caused by elevated OXPHOS activity acting through a decrease in and slowing of the Pi (inorganic phosphate) rise during the rest-to-work transition. This change leads to attenuation of the reaching by Pi of Pipeak, peak Pi at which exercise is terminated because of fatigue. The delayed (in time and in relation to V·O2 increase) Pi rise for a given power output (PO) in trained muscle causes Pi to reach Pipeak (in very heavy exercise) after a longer time and at a higher V·O2; thus, exercise duration is lengthened, and V·O2max is elevated compared to untrained muscle. The diminished Pi increase during exercise with a given PO can cause Pi to stabilize at a steady state less than Pipeak, and exercise can continue potentially ad infinitum (heavy exercise), instead of rising unceasingly and ultimately reaching Pipeak and causing exercise termination (very heavy exercise). This outcome means that CP rises, as the given PO is now less than, and not greater than CP. Finally, the diminished Pi increase (and other metabolite changes) results in, at a given PO (moderate exercise), the steady state of fluxes (including V·O2) and metabolites being reached faster; thus, t0.63 is shortened. This effect of elevated OXPHOS activity is possibly somewhat diminished by the training-induced decrease in Pipeak.

In silico analysis of the dynamic regulation of cardiac electrophysiology by Kv 11.1 ion-channel trafficking

Cardiac electrophysiology is regulated by continuous trafficking and internalization of ion channels occurring over minutes to hours. Kv 11.1 (also known as hERG) underlies the rapidly activating delayed-rectifier K+ current (IKr ), which plays a major role in cardiac ventricular repolarization. Experimental characterization of the distinct temporal effects of genetic and acquired modulators on channel trafficking and gating is challenging. Computer models are instrumental in elucidating these effects, but no currently available model incorporates ion-channel trafficking. Here, we present a novel computational model that reproduces the experimentally observed production, forward trafficking, internalization, recycling and degradation of Kv 11.1 channels, as well as their modulation by temperature, pentamidine, dofetilide and extracellular K+ . The acute effects of these modulators on channel gating were also incorporated and integrated with the trafficking model in the O'Hara-Rudy human ventricular cardiomyocyte model. Supraphysiological dofetilide concentrations substantially increased Kv 11.1 membrane levels while also producing a significant channel block. However, clinically relevant concentrations did not affect trafficking. Similarly, severe hypokalaemia reduced Kv 11.1 membrane levels based on long-term culture data, but had limited effect based on short-term data. By contrast, clinically relevant elevations in temperature acutely increased IKr due to faster kinetics, while after 24 h, IKr was decreased due to reduced Kv 11.1 membrane levels. The opposite was true for lower temperatures. Taken together, our model reveals a complex temporal regulation of cardiac electrophysiology by temperature, hypokalaemia, and dofetilide through competing effects on channel gating and trafficking, and provides a framework for future studies assessing the role of impaired trafficking in cardiac arrhythmias. KEY POINTS: Kv 11.1 channels underlying the rapidly activating delayed-rectifier K+ current are important for ventricular repolarization and are continuously shuttled from the cytoplasm to the plasma membrane and back over minutes to hours. Kv 11.1 gating and trafficking are modulated by temperature, drugs and extracellular K+ concentration but experimental characterization of their combined effects is challenging. Computer models may facilitate these analyses, but no currently available model incorporates ion-channel trafficking. We introduce a new two-state ion-channel trafficking model able to reproduce a wide range of experimental data, along with the effects of modulators of Kv 11.1 channel functioning and trafficking. The model reveals complex dynamic regulation of ventricular repolarization by temperature, extracellular K+ concentration and dofetilide through opposing acute (millisecond) effects on Kv 11.1 gating and long-term (hours) modulation of Kv 11.1 trafficking. This in silico trafficking framework provides a tool to investigate the roles of acute and long-term processes on arrhythmia promotion and maintenance.

Thalamic control of sensory processing and spindles in a biophysical somatosensory thalamoreticular circuit model of wakefulness and sleep

Thalamoreticular circuitry plays a key role in arousal, attention, cognition, and sleep spindles, and is linked to several brain disorders. A detailed computational model of mouse somatosensory thalamus and thalamic reticular nucleus has been developed to capture the properties of over 14,000 neurons connected by 6 million synapses. The model recreates the biological connectivity of these neurons, and simulations of the model reproduce multiple experimental findings in different brain states. The model shows that inhibitory rebound produces frequency-selective enhancement of thalamic responses during wakefulness. We find that thalamic interactions are responsible for the characteristic waxing and waning of spindle oscillations. In addition, we find that changes in thalamic excitability control spindle frequency and their incidence. The model is made openly available to provide a new tool for studying the function and dysfunction of the thalamoreticular circuitry in various brain states.

An in silico approach to understanding the interaction between cardiovascular and pulmonary lymphatic dysfunction

The lung is extremely sensitive to interstitial fluid balance, yet the role of pulmonary lymphatics in lung fluid homeostasis and its interaction with cardiovascular pressures is poorly understood. In health, there is a fine balance between fluid extravasated from the pulmonary capillaries into the interstitium and the return of fluid to the circulation via the lymphatic vessels. This balance is maintained by an extremely interdependent system governed by pressures in the fluids (air and blood) and tissue (interstitium), lung motion during breathing, and the permeability of the tissues. Chronic elevation in left atrial pressure (LAP) due to left heart disease increases the capillary blood pressure. The consequent fluid accumulation in the delicate lung tissue increases its weight, decreases its compliance, and impairs gas exchange. This interdependent system is difficult, if not impossible, to study experimentally. Computational modeling provides a unique perspective to analyze fluid movement in the cardiopulmonary vasculature in health and disease. We have developed an initial in silico model of pulmonary lymphatic function using an anatomically structured model to represent ventilation and perfusion and underlying biophysical laws governing fluid transfer at the interstitium. This novel model was tested against increased LAP and noncardiogenic effects (increased permeability). The model returned physiologically reasonable values for all applications, predicting pulmonary edema when LAP reached 25 mmHg and with increased permeability.NEW & NOTEWORTHY This model presents a novel approach to understanding the interaction between cardiac dysfunction and pulmonary lymphatic function, using anatomically structured models and biophysical equations to estimate regional variation in fluid transport from blood to interstitial and lymphatic flux. This fluid transport model brings together advanced models of ventilation, perfusion, and lung mechanics to produce a detailed model of fluid transport in health and various altered pathological conditions.

Understanding cingulotomy's therapeutic effect in OCD through computer models

Cingulotomy is therapeutic in OCD, but what are the possible mechanisms? Computer models that formalize cortical OCD abnormalities and anterior cingulate cortex (ACC) function can help answer this. At the neural dynamics level, cortical dynamics in OCD have been modeled using attractor networks, where activity patterns resistant to change denote the inability to switch to new patterns, which can reflect inflexible thinking patterns or behaviors. From that perspective, cingulotomy might reduce the influence of difficult-to-escape ACC attractor dynamics on other cortical areas. At the functional level, computer formulations based on model-free reinforcement learning (RL) have been used to describe the multitude of phenomena ACC is involved in, such as tracking the timing of expected outcomes and estimating the cost of exerting cognitive control and effort. Different elements of model-free RL models of ACC could be affected by the inflexible cortical dynamics, making it challenging to update their values. An agent can also use a world model, a representation of how the states of the world change, to plan its actions, through model-based RL. OCD has been hypothesized to be driven by reduced certainty of how the brain's world model describes changes. Cingulotomy might improve such uncertainties about the world and one's actions, making it possible to trust the outcomes of these actions more and thus reduce the urge to collect more sensory information in the form of compulsions. Connecting the neural dynamics models with the functional formulations can provide new ways of understanding the role of ACC in OCD, with potential therapeutic insights.

Modeling and simulation of vagal afferent input of the cough reflex

We employed computational modeling to investigate previously conducted experiments of the effect of vagal afferent modulation on the cough reflex in an anesthetized cat animal model. Specifically, we simulated unilateral cooling of the vagus nerve and analyzed characteristics of coughs produced by a computational model of brainstem cough/respiratory neuronal network. Unilateral vagal cooling was simulated by a reduction of cough afferent input (corresponding to unilateral vagal cooling) to the cough network. All these attempts resulted in only mild decreases in investigated cough characteristics such as cough number, amplitudes of inspiratory and expiratory cough efforts in comparison with experimental data. Multifactorial alterations of model characteristics during cough simulations were required to approximate cough motor patterns that were observed during unilateral vagal cooling in vivo. The results support the plausibility of a more complex NTS processing system for cough afferent information than has been proposed.

Stroke technique in C1 canoe slalom: a simulation study

Male C1 canoe slalom athletes traditionally used cross transitions to move their paddle to the other side of the boat and off-side strokes to paddle on their non-dominant side. Conversely, female athletes often use a switching transition and on-side strokes on their non-dominant side. The purpose of this study was to use a computer model to assess the relation between cross- or switching techniques, and the relative strength (symmetry) of non-dominant compared to dominant side strokes to race times in C1 canoe slalom. We created a forward dynamics model to predict race times using stroke forces (from an indoor ergometer), drag forces (measured on-water), and probability distributions for stroke and transition times (measured from international canoe slalom competitions). The main effects from an ANOVA (p<0.05) were (i) for a given transition number and strength symmetry the race times were faster when using cross-transitions than switch-transitions (ii) for a given strength symmetry the race times became slower as the number of switch transitions increased, but there was minimal effect of the number of cross-transitions, and (iii) the closer the strength of the strokes were between the dominant and non-dominant side (as symmetry factor approached 100 %), the faster the race times.

The biomechanical efficacy of a dressing with a soft cellulose fluff core in protecting prone surgical patients from chest injuries on the operating table

Pressure ulcers are soft‐tissue damage associated with tissue exposure to sustained deformations and stress concentrations. In patients who are proned for ventilation or surgery, such damage may occur in the superficial chest tissues that are compressed between the rib cage and the support surface. Prophylactic dressings have been previously proven as generally effective for pressure ulcer prevention. In this study, our goal was to develop a novel computational modelling framework to investigate the biomechanical efficacy of a dressing with a soft cellulose fluff core in protecting proned surgical patients from chest pressure ulcers occurring on the operating table, due to body fixation by the Relton‐Hall frame. We compared the levels of mechanical compressive stresses developing in the soft chest tissues, above the sternum and ribs, due to the trunk weight, whilst the body is supported by the Relton‐Hall frame pads, with versus without the prophylactically applied bilateral dressings. The protective efficacy index for the extremely high stresses, above the 95th‐percentile, were 40.5%, 25.6% and 24.2% for skin, adipose and muscle, respectively, indicating that the dressings dispersed elevated soft‐tissue stresses. The current results provide additional support for using soft cellulose fluff core dressings for pressure ulcer prophylaxis, including during surgery.

Selecting ideal drugs for encapsulation in thermosensitive liposomes and other triggered nanoparticles

OBJECTIVE

Thermosensitive liposomes (TSL) and other triggered drug delivery systems (DDS) are promising therapeutic strategies for targeted drug delivery. However, successful designs with candidate drugs depend on many variables, including nanoparticle formulation, drug properties, and cancer cell properties. We developed a computational model based on experimental data to predict the potential efficacies of drugs when used with triggered DDS, such as TSL.

METHODS

A computer model based on the Krogh cylinder was developed to predict uptake and cell survival with four anthracyclines when delivered by intravascular triggered DDS (e.g., TSL): doxorubicin (DOX), idarubicin (IDA), pirarubicin (PIR), and aclarubicin (ACLA). We simulated three tumor types derived from SVR angiosarcoma, LLC lung cancer, or SCC-1 oral carcinoma cells. In vitro cellular drug uptake and cytotoxicity data were obtained experimentally and incorporated into the model.

RESULTS

For all three cell lines, ACLA and IDA had the fastest cell uptake, with slower uptake for DOX and PIR. Cytotoxicity was highest for IDA and lowest for ACLA. The computer model predicted the highest tumor drug uptake for ACLA and IDA, resulting from their rapid cell uptake. Overall, IDA was most effective and produced the lowest tumor survival fraction, with DOX being the second best. Perivascular drug penetration was reduced for drugs with rapid cell uptake, potentially limiting delivery to cancer cells distant from the vasculature.

CONCLUSION

Combining simple in vitro experiments with a computer model could provide a powerful screening tool to evaluate the potential efficacy of candidate investigative drugs preceding TSL encapsulation and in vivo studies.

Models of Epidemiological Security Management in the Spread of the SARS-CoV-2 Virus

The task of managing epidemic security during COVID-19 is considered. The spread of the SARS-CoV-2 virus without and with vaccination is described by mathematical and computer models built on the basis of the epidemic control protocol adopted by the Georgian authorities. The mathematical model of the spread of the SARS-CoV-2 virus is described using the Cauchy problem for a system of ordinary differential equations. For the management of epidemiological safety, a objective function has been built, which takes into account: the financial consequences of introducing a lockdown in the country and the cost of treating the infected. Among the parameters of the model, the governing ones are highlighted. The control parameters are used to minimize the objective function. In the work, mainly theoretical research is given. However, computer simulation and a computational experiment on the proposed computer model with constant parameters allows us to answer the question: what is the number of infected citizens in the country, in which the economy does not need a lockdown, and the recovery prognosis of those infected with the SARS-CoV-2 virus is favorable.

Computational Prediction and Experimental Values of Mechanical Properties of Carbon Nanotube Reinforced Cement

The main objective of this study is to create a rigorous computer model of carbon nanotube composites to predict their mechanical properties before they are manufactured and to reduce the number of physical tests. A detailed comparison between experimental and computational results of a cement-based composite is made to match data and find the most significant parameters. It is also shown how the properties of the nanotubes (Young's modulus, aspect ratio, quantity, directionality, clustering) and the cement (Young's modulus) affect the composite properties. This paper tries to focus on the problem of modeling carbon nanotube composites computationally, and further study proposals are given.

A computer model for professional competence assessment according to ISO 15189

Background As defined by ISO 15189 competence is the "demonstrated ability to apply knowledge and skills" thus, its assessment is fundamental for ensuring the quality of the total testing process in order to reduce the risk for the patient. We have developed a functional software for the measurement of professional competences in order to standardize the procedure and to collect all the data in a single platform, avoiding redundancy and dispersion. Methods Our model objectively assesses the skills, as they become measurable and comparable with appropriate standards and involves both managers and operators, to increase their active engagement. The assessment concerns everyone, but the standards to be met (numerical values) can vary according to the responsibilities. Several subjective and objective criteria are evaluated: each parameter can contribute in a variable proportion to the total skills measured according to the needs of the organization. Results The data are automatically analyzed and can be easily monitored in real time in the form of indicators, thanks to dashboards. The comparison between the skills required and those measured allows highlighting the gap useful for planning personalized training paths. Conclusions Our tool is reliable and highly adaptable to laboratories about competences to track criteria, standards and monitored indicators. The computerized management is a strategic action as it fulfills the requirements of registration, traceability, communication, data analysis and indicators development, which are the tenets of continuous improvement, and allows planning to be made on the basis of the actual training needs.

Effect of intracardiac blood flow pulsatility during radiofrequency cardiac ablation: computer modeling study

PURPOSE

To assess the effect of intracardiac blood flow pulsatility on tissue and blood distributions during radiofrequency (RF) cardiac ablation (RFCA).

METHODS

A three-dimensional computer model was used to simulate constant power ablations with an irrigated-tip electrode and three possible catheter orientations (perpendicular, parallel and 45°). Continuous flow and three different pulsatile flow profiles were considered, with four average blood velocity values: 3, 5.5, 8.5 and 24.4 cm/s. The 50 °C contour was used to assess thermal lesion size.

RESULTS

The differences in lesion size between continuous flow and the different pulsatile flow profiles were always less than 1 mm. As regards maximum tissue temperature, the differences between continuous and pulsatile flow were always less than 1 °C, with slightly higher differences in maximum blood temperature, but never over 6 °C. While the progress of maximum tissue temperature was identical for continuous and pulsatile flow, maximum blood temperature with the pulsatile profile showed small amplitude oscillations associated with blood flow pulsatility.

CONCLUSIONS

The findings show that intracardiac blood pulsatility has a negligible effect on lesion size and a very limited impact on maximum tissue and blood temperatures, which suggests that future experimental studies based on ex vivo or in silico models can ignore pulsatility in intracardiac blood flow.

Scaffold-Dependent Mechanical and Architectural Cues Guide Osteochondral Defect Healing in silico

Osteochondral defects in joints require surgical intervention to relieve pain and restore function. However, no current treatment enables a complete reconstitution of the articular surface. It is known that both mechanical and biological factors play a key role on osteochondral defect healing, however the underlying principles and how they can be used in the design of treatment strategies remain largely unknown. To unravel the underlying principles of mechanobiology in osteochondral defect healing, i.e., how mechanical stimuli can guide biological tissue formation, we employed a computational approach investigating the scaffold-associated mechanical and architectural properties that would enable a guided defect healing. A previous computer model of the knee joint was further developed to simulate healing of an empty osteochondral defect. Then, scaffolds were implanted in the defect and their architectures and material properties were systematically varied to identify their relevance in osteochondral defect healing. Scaffold mechanical and architectural properties were capable of influencing osteochondral defect healing. Specifically, scaffold material elastic modulus values in the range of cancellous bone (low GPa range) and a scaffold architecture that provided stability, i.e., resistance against displacement, in both the main loading direction and perpendicular to it supported the repair process. The here presented model, despite its simplifications, is regarded as a powerful tool to screen for promising properties of novel scaffold candidates fostering osteochondral defect regeneration prior to their implementation in vivo.

Achieving functional neuronal dendrite structure through sequential stochastic growth and retraction

Class I ventral posterior dendritic arborisation (c1vpda) proprioceptive sensory neurons respond to contractions in the Drosophila larval body wall during crawling. Their dendritic branches run along the direction of contraction, possibly a functional requirement to maximise membrane curvature during crawling contractions. Although the molecular machinery of dendritic patterning in c1vpda has been extensively studied, the process leading to the precise elaboration of their comb-like shapes remains elusive. Here, to link dendrite shape with its proprioceptive role, we performed long-term, non-invasive, in vivo time-lapse imaging of c1vpda embryonic and larval morphogenesis to reveal a sequence of differentiation stages. We combined computer models and dendritic branch dynamics tracking to propose that distinct sequential phases of stochastic growth and retraction achieve efficient dendritic trees both in terms of wire and function. Our study shows how dendrite growth balances structure-function requirements, shedding new light on general principles of self-organisation in functionally specialised dendrites.

Investigation of femur fracture potential in common pediatric falls using finite element analysis

A finite element (FE) model of an 11-month-old child's femur was developed to evaluate fracture risk in short-distance feet-first falls and bed falls. Pediatric material properties were applied to the FE model. Femur loading was derived from previously conducted fall experiments using a child surrogate where fall conditions (e.g., fall height, impact surface) were varied. Fracture thresholds based on principal stress and strain were used to examine potential for fracture. Peak stress/strain were significantly greater for feet-first falls from greater heights and onto harder impact surfaces. Feet-first falls exceeded some, but not all fracture thresholds. Bed falls did not exceed any fracture thresholds.

Research on the Methods and Algorithms Improving the Measurements Precision and Market Competitive Advantages of Fiber Optic Current Sensors

An electromagnetic instrument transformer is a common device used to measure large current values in high-voltage electrical networks; it has been in use for more than a century. However, the optical current transformer, a promising technology also known as a fiber optic current sensor (FOCS), offers increased safety and ease of operation, as well as the absence of errors caused by the magnetic circuit of legacy transformers. Although the FOCS scheme is well known and has been actively developed for over a quarter century, it has certain disadvantages that limit its use. This paper describes the authors' efforts to solve these problems in order to make FOCS technology competitive and widely adopted. We upgraded the FOCS optical circuit, expanded the frequency band of the captured current signal, and reduced the solution's cost. We designed new signal processing algorithms to compensate for errors caused by internal factors in the measurement circuit, as well as those caused by environmental influences. We developed an FOCS computer model based on the Jones matrix formalism to enhance the experimental debugging. It allowed us to define the requirements for elements of the optical circuit and its production accuracy.

Patient-Specific Blood Flow Analysis for Cerebral Arteriovenous Malformation Based on Digital Subtraction Angiography Images

Real-time digital subtraction angiography (DSA) is capable of revealing the cerebral vascular morphology and blood flow perfusion patterns of arterial venous malformations (AVMs). In this study, we analyze the DSA images of a subject-specific left posterior AVM case and customize a generic electric analog model for cerebral circulation accordingly. The generic model consists of electronic components representing 49 major cerebral arteries and veins, and yields their blood pressure and flow rate profiles. The model was adapted by incorporating the supplying and draining patterns of the AVM to simulate some typical AVM features such as the blood "steal" syndrome, where the flow rate in the left posterior artery increases by almost three times (∼300 ml/min vs 100 ml/min) compared with the healthy case. Meanwhile, the flow rate to the right posterior artery is reduced to ∼30 ml/min from 100 ml/min despite the presence of an autoregulation mechanism in the model. In addition, the blood pressure in the draining veins is increased from 9 to 22 mmHg, and the blood pressure in the feeding arteries is reduced from 85 to 30 mmHg due to the fistula effects of the AVM. In summary, a first DSA-based AVM model has been developed. More subject-specific AVM cases are required to apply the presented in silico model, and in vivo data are used to validate the simulation results.

Predicting brain organization with a computational model: 50-year perspective on lateral inhibition and oscillatory gating by dendrodendritic synapses

The first compartmental computer models of brain neurons using the Rall method predicted novel and unexpected dendrodendritic interactions between mitral and granule cells in the olfactory bulb. We review the models from a 50-year perspective on the work that has challenged, supported, and extended the original proposal that these interactions mediate both lateral inhibition and oscillatory activity, essential steps in the neural basis of olfactory processing and perception. We highlight strategies behind the neurophysiological experiments and the Rall methods that enhance the ability of detailed compartmental modeling to give counterintuitive predictions that lead to deeper insights into neural organization at the synaptic and circuit level. The application of these methods to mechanisms of neurogenesis and plasticity are exciting challenges for the future.

Application of a Mathematical Model in Determining the Spread of the Rabies Virus: Simulation Study

Background

Rabies is an acute infectious disease of the central nervous system caused by the rabies virus. The mortality rate of rabies is almost 100%. For some countries with poor sanitation, the spread of rabies among dogs is very serious.

Objective

The objective of this paper was to study the ecological transmission mode of rabies to make theoretical contributions to the suppression of rabies in China.

Methods

A mathematical model of the transmission mode of rabies was constructed using relevant data from the literature and officially published figures in China. Using this model, we fitted the data of the number of patients with rabies and predicted the future number of patients with rabies. In addition, we studied the effectiveness of different rabies suppression measures.

Results

The results of the study indicated that the number of people infected with rabies will rise in the first stage, and then decrease. The model forecasted that in about 10 years, the number of rabies cases will be controlled within a relatively stable range. According to the prediction results of the model reported in this paper, the number of rabies cases will eventually plateau at approximately 500 people every year. Relatively effective rabies suppression measures include controlling the birth rate of domestic and wild dogs as well as increasing the level of rabies immunity in domestic dogs.

Conclusions

The basic reproductive number of rabies in China is still greater than 1. That is, China currently has insufficient measures to control rabies. The research on the transmission mode of rabies and control measures in this paper can provide theoretical support for rabies control in China.

Development of a Canine Rigid Body Musculoskeletal Computer Model to Evaluate Gait

Background

Kinematic and kinetic analysis have been used to gain an understanding of canine movement and joint loading during gait. By non-invasively predicting muscle activation patterns and forces during gait, musculoskeletal models can further our understanding of normal variability and muscle activation patterns and force profiles characteristic of gait.

Methods

Pelvic limb kinematics and kinetics were measured for a 2 year old healthy female Dachshund (5.4 kg) during gait using 3-D motion capture and force platforms. A computed tomography scan was conducted to acquire pelvis and pelvic limb morphology. Using the OpenSim modeling platform, a bilateral pelvic limb subject-specific rigid body musculoskeletal computer model was developed. This model predicted muscle activation patterns, muscle forces, and angular kinematics and joint moments during walking.

Results

Gait kinematics determined from motion capture matched those predicted by the model, verifying model accuracy. Primary muscles involved in generating joint moments during stance and swing were predicted by the model: at mid-stance the adductor magnus et brevis (peak activation 53.2%, peak force 64.7 N) extended the hip, and stifle flexor muscles (biceps femoris tibial and calcaneal portions) flexed the stifle. Countering vertical ground reaction forces, the iliopsoas (peak activation 37.9%, peak force 68.7 N) stabilized the hip in mid-stance, while the biceps femoris patellar portion stabilized the stifle in mid-stance and the plantar flexors (gastrocnemius and flexor digitorum muscles) stabilized the tarsal joint during early stance. Transitioning to swing, the iliopsoas, rectus femoris and tensor fascia lata flexed the hip, while in late swing the adductor magnus et brevis impeded further flexion as biceps femoris tibial and calcaneal portions stabilized the stifle for ground contact.

Conclusion

The musculoskeletal computer model accurately replicated experimental canine angular kinematics associated with gait and was used to predict muscle activation patterns and forces. Thus, musculoskeletal modeling allows for quantification of measures such as muscle forces that are difficult or impossible to measure in vivo.

Use of a Virtual Mock Loop model to evaluate a new left ventricular assist device for transapical insertion

We are developing a novel type of miniaturized left ventricular assist device that is configured for transapical insertion. The aim of this study was to assess the performance and function of a new pump by using a Virtual Mock Loop system for device characterization and mapping. The results, such as pressure-flow performance curves, from pump testing in a physical mock circulatory loop were used to analyze its function as a left ventricular assist device. The Virtual Mock Loop system was programmed to mimic the normal heart condition, systolic heart failure, diastolic heart failure, and both systolic and diastolic heart failure, and to provide hemodynamic pressure values before and after the activation of several left ventricular assist device pump speeds (12,000, 14,000, and 16,000 r/min). With pump support, systemic flow and mean aortic pressure increased, and mean left atrial pressure and pulmonary artery pressure decreased for all heart conditions. Regarding high pump-speed support, the systemic flow, aortic pressure, left atrial pressure, and pulmonary artery pressure returned to the level of the normal heart condition. Based on the test results from the Virtual Mock Loop system, the new left ventricular assist device for transapical insertion may be able to ease the symptoms of patients with various types of heart failure. The Virtual Mock Loop system could be helpful to assess pump performance before in vitro bench testing.

How personalized heart modeling can help treatment of lethal arrhythmias: A focus on ventricular tachycardia ablation strategies in post-infarction patients

Precision Cardiology is a targeted strategy for cardiovascular disease prevention and treatment that accounts for individual variability. Computational heart modeling is one of the novel approaches that have been developed under the umbrella of Precision Cardiology. Personalized computational modeling of patient hearts has made strides in the development of models that incorporate the individual geometry and structure of the heart as well as other patient-specific information. Of these developments, one of the potentially most impactful is the research aimed at noninvasively predicting the targets of ablation of lethal arrhythmia, ventricular tachycardia (VT), using patient-specific models. The approach has been successfully applied to patients with ischemic cardiomyopathy in proof-of-concept studies. The goal of this paper is to review the strategies for computational VT ablation guidance in ischemic cardiomyopathy patients, from model developments to the intricacies of the actual clinical application. To provide context in describing the road these computational modeling applications have undertaken, we first review the state of the art in VT ablation in the clinic, emphasizing the benefits that personalized computational prediction of ablation targets could bring to the clinical electrophysiology practice. This article is characterized under: Analytical and Computational Methods > Computational Methods Models of Systems Properties and Processes > Organ, Tissue, and Physiological Models Translational, Genomic, and Systems Medicine > Translational Medicine.

Arterial Hypertension and Unusual Ascending Aortic Dilatation in a Neonate With Acute Kidney Injury: Mechanistic Computer Modeling

Background

Neonatal asphyxia caused kidney injury and severe hypertension in a newborn. An unusually dilatated ascending aorta developed. Dialysis and pharmacological treatment led to partial recovery of the ascending aortic diameters. It was hypothesized that the aortic dilatation may be associated with aortic stiffening, peripheral resistance, and cardiovascular changes. Mathematical modeling was used to better understand the potential causes of the hypertension, and to confirm our clinical treatment within the confines of the model's capabilities.

Methods

The patient's systolic arterial blood pressure showed hypertension. Echocardiographic exams showed ascending aorta dilatation during hypertension, which partially normalized upon antihypertensive treatment. To explore the underlying mechanisms of the aortic dilatation and hypertension, an existing lumped parameter hemodynamics model was deployed. Hypertension was simulated using realistic literature informed parameter values. It was also simulated using large parameter perturbations to demonstrate effects. Simulations were designed to permit examination of causal mechanisms. The hypertension inducing effects of aortic stiffnesses, vascular resistances, and cardiac hypertrophy on blood flow and pressure were simulated. Sensitivity analysis was used to stratify causes.

Results

In agreement with our clinical diagnosis, the model showed that an increase of aortic stiffness followed by augmentation of peripheral resistance are the prime causes of realistic hypertension. Increased left ventricular elastance may also cause hypertension. Ascending aortic pressure and flow increased in the simultaneous presence of left ventricle hypertrophy and augmented small vessel resistance, which indicate a plausible condition for ascending aorta dilatation. In case of realistic hypertension, sensitivity analysis showed that the treatment of both the large vessel stiffness and small vessel resistance are more important in comparison to cardiac hypertrophy.

Conclusion and Discussion

Large vessel stiffness was found to be the prime factor in arterial hypertension, which confirmed the clinical treatment. Treatment of cardiac hypertrophy appears to provide significant benefit but may be secondary to treatment of large vessel stiffness. The quantitative grading of pathophysiological mechanisms provided by the modeling may contribute to treatment recommendations. The model was limited due to a lack of data suitable to permit model identification.

Predicting early risk of chronic kidney disease in cats using routine clinical laboratory tests and machine learning

Background

Advanced machine learning methods combined with large sets of health screening data provide opportunities for diagnostic value in human and veterinary medicine.

Hypothesis/Objectives

To derive a model to predict the risk of cats developing chronic kidney disease (CKD) using data from electronic health records (EHRs) collected during routine veterinary practice.

Animals

A total of 106 251 cats that attended Banfield Pet Hospitals between January 1, 1995, and December 31, 2017.

Methods

Longitudinal EHRs from Banfield Pet Hospitals were extracted and randomly split into 2 parts. The first 67% of the data were used to build a prediction model, which included feature selection and identification of the optimal neural network type and architecture. The remaining unseen EHRs were used to evaluate the model performance.

Results

The final model was a recurrent neural network (RNN) with 4 features (creatinine, blood urea nitrogen, urine specific gravity, and age). When predicting CKD near the point of diagnosis, the model displayed a sensitivity of 90.7% and a specificity of 98.9%. Model sensitivity decreased when predicting the risk of CKD with a longer horizon, having 63.0% sensitivity 1 year before diagnosis and 44.2% 2 years before diagnosis, but with specificity remaining around 99%.

Conclusions and clinical importance

The use of models based on machine learning can support veterinary decision making by improving early identification of CKD.

Regulation of gamma-frequency oscillation by feedforward inhibition: A computational modeling study

Throughout the brain, reciprocally connected excitatory and inhibitory neurons interact to produce gamma-frequency oscillations. The emergent gamma rhythm synchronizes local neural activity and helps to select which cells should fire in each cycle. We previously found that such excitation-inhibition microcircuits, however, have a potentially significant caveat: the frequency of the gamma oscillation and the level of selection (i.e., the percentage of cells that are allowed to fire) vary with the magnitude of the input signal. In networks with varying levels of brain activity, such a feature may produce undesirable instability on the time and spatial structure of the neural signal with a potential for adversely impacting important neural processing mechanisms. Here we propose that feedforward inhibition solves the latter instability problem of the excitation-inhibition microcircuit. Using computer simulations, we show that the feedforward inhibitory signal reduces the dependence of both the frequency of population oscillation and the level of selection on the magnitude of the input excitation. Such a mechanism can produce stable gamma oscillations with its frequency determined only by the properties of the feedforward network, as observed in the hippocampus. As feedforward and feedback inhibition motifs commonly appear together in the brain, we hypothesize that their interaction underlies a robust implementation of general computational principles of neural processing involved in several cognitive tasks, including the formation of cell assemblies and the routing of information between brain areas.

Slow sinusoidal tilt movements demonstrate the contribution to orthostatic tolerance of cerebrospinal fluid movement to and from the spinal dural space

Standing up elicits a host of cardiovascular changes which all affect the cerebral circulation. Lowered mean arterial blood pressure (ABP) at brain level, change in the cerebral venous outflow path, lowered end-tidal PCO2 (PET CO2 ), and intracranial pressure (ICP) modify cerebral blood flow (CBF). The question we undertook to answer is whether gravity-induced blood pressure (BP) changes are compensated in CBF with the same dynamics as are spontaneous or induced ABP changes in a stable position. Twenty-two healthy subjects (18/4 m/f, 40 ± 8 years) were subjected to 30° and 70° head-up tilt (HUT) and sinusoidal tilts (SinTilt, 0°↨60° around 30° at 2.5-10 tilts/min). Additionally, at those three tilt levels, they performed paced breathing at 6-15 breaths/min to induce larger than spontaneous cardiovascular oscillations. We measured continuous finger BP and cerebral blood flow velocity (CBFv) in the middle cerebral artery by transcranial Doppler to compute transfer functions (TFs) from ABP- to CBFv oscillations. SinTilt induces the largest ABP oscillations at brain level with CBFv gains strikingly lower than for paced breathing or spontaneous variations. This would imply better autoregulation for dynamic gravitational changes. We demonstrate in a mathematical model that this difference is explained by ICP changes due to movement of cerebrospinal fluid (CSF) into and out of the spinal dural sack. Dynamic cerebrovascular autoregulation seems insensitive to how BP oscillations originate if the effect of ICP is factored in. CSF-movement in-and-out of the spinal dural space contributes importantly to orthostatic tolerance by its effect on cerebral perfusion pressure.

Image Analysis Software as a Strategy to Improve the Radiographic Determination of Fracture Healing

OBJECTIVES

To develop and validate an unbiased, accurate, convenient, and inexpensive means of determining when an osseous defect has healed and recovered sufficient strength to allow weight bearing.

METHODS

A novel image processing software algorithm was created to analyze the radiographic images and produce a metric designed to reflect the bone strength. We used a rat femoral segmental defect model that provides a range of healing responses from complete union to nonunion. Femora were examined by x-ray, micro-computed tomography and mechanical testing. Accurate simulated radiographic images at different incident x-ray beam angles were produced from the micro-computed tomography data files.

RESULTS

The software-generated metric (SC) showed high levels of correlation with both the mechanical strength (τMech) and the polar moment of inertia (pMOI), with the mechanical testing data having the highest association. The optimization analysis yielded optimal oblique angles θB of 125 degrees for τMech and 50 degrees for pMOI. The Pearson R values for the optimized model were 0.71 and 0.64 for τMech and pMOI, respectively. Further validation using true radiographs also demonstrated that the metric was accurate and that the simulations were realistic.

CONCLUSIONS

The preliminary findings suggest a very promising methodology to assess bone fracture healing using conventional radiography. With radiographs acquired at appropriate incident angles, it proved possible to accurately calculate the degree of healing and the mechanical strength of the bone. Further research is necessary to refine this approach and determine whether it translates to the human clinical setting.

Dispersion of Recovery and Vulnerability to Re-entry in a Model of Human Atrial Tissue With Simulated Diffuse and Focal Patterns of Fibrosis

Fibrosis in atrial tissue can act as a substrate for persistent atrial fibrillation, and can be focal or diffuse. Regions of fibrosis are associated with slowed or blocked conduction, and several approaches have been used to model these effects. In this study a computational model of 2D atrial tissue was used to investigate how the spatial scale of regions of simulated fibrosis influenced the dispersion of action potential duration (APD) and vulnerability to re-entry in simulated normal human atrial tissue, and human tissue that has undergone remodeling as a result of persistent atrial fibrillation. Electrical activity was simulated in a 10 × 10 cm square 2D domain, with a spatially varying diffusion coefficient as described below. Cellular electrophysiology was represented by the Courtemanche model for human atrial cells, with the model parameters set for normal and remodeled cells. The effect of fibrosis was modeled with a smoothly varying diffusion coefficient, obtained from sampling a Gaussian random field (GRF) with length scales of between 1.25 and 10.0 mm. Twenty samples were drawn from each field, and used to allocate a value of diffusion coefficient between 0.05 and 0.2 mm²/ms. Dispersion of APD was assessed in each sample by pacing at a cycle length of 1,000 ms, followed by a premature beat with a coupling interval of 400 ms. Vulnerability to re-entry was assessed with an aggressive pacing protocol with pacing cycle lengths decreasing from 450 to 250 ms in 25 ms intervals for normal tissue and 300–150 ms for remodeled tissue. Simulated fibrosis at smaller spatial scales tended to lengthen APD, increase APD dispersion, and increase vulnerability to sustained re-entry relative to fibrosis at larger spatial scales. This study shows that when fibrosis is represented by smoothly varying tissue diffusion, the spatial scale of fibrosis has important effects on both dispersion of recovery and vulnerability to re-entry.

Neutral glenoid alignment in reverse shoulder arthroplasty does not guarantee decreased risk of impingement

Reverse Shoulder Arthroplasty (RSA) has gained popularity over the recent years, but impingement concerns are still present. Surgeons aim to correct pre-operative glenoid deformities to reduce impingement but it can be challenging without assistance like patient specific guides. However, it is unclear how accurate glenoid correction affects the impingement. The main objective of this study was to determine whether accurate glenoid correction to neutral version and tilt can reduce the risk of impingement. Two types of virtual surgeries were performed on 22 pre-operative arthritic shoulders: (i) "Interactive," the glenoid baseplate could be placed with accuracy, and (ii) "Blind," surgeons placed the RSA baseplate while they could only visualize the glenoid. The virtual models were then used in an RSA biomechanical model which recorded impingement for (i) four Range of Motion (ROM) tasks, (ii) ten Activities of Daily Living (ADL). The "Blind" method resulted in more variable glenoid placement (version and tilt) than the "Interactive" method (p = 0.001). However, both methods showed similar ROM and impingement occurrence in ADLs. The results suggest it is challenging for surgeons to accurately correct version and tilt on arthritic glenoids when only referencing off of the face of the glenoid. However, the variable glenosphere placement observed in the "Blind" method did not result in worse impingement compared to the accurate "Interactive" method. This was because both methods had similar inferior baseplate positioning which is more important than correcting version or tilt. Implantation accuracy remains important in RSA, but pre-operative planning should not just target at correcting version and tilt. © 2017 Orthopaedic Research Society. Published by Wiley Periodicals, Inc. J Orthop Res 36:1213-1219, 2018.

A Comparative Assessment of Implant Site Viability in Humans and Rats

Our long-term objective is to devise methods to improve osteotomy site preparation and, in doing so, facilitate implant osseointegration. As a first step in this process, we developed a standardized oral osteotomy model in ovariectomized rats. There were 2 unique features to this model: first, the rats exhibited an osteopenic phenotype, reminiscent of the bone health that has been reported for the average dental implant patient population. Second, osteotomies were produced in healed tooth extraction sites and therefore represented the placement of most implants in patients. Commercially available drills were then used to produce osteotomies in a patient cohort and in the rat model. Molecular, cellular, and histologic analyses demonstrated a close alignment between the responses of human and rodent alveolar bone to osteotomy site preparation. Most notably in both patients and rats, all drilling tools created a zone of dead and dying osteocytes around the osteotomy. In rat tissues, which could be collected at multiple time points after osteotomy, the fate of the dead alveolar bone was followed. Over the course of a week, osteoclast activity was responsible for resorbing the necrotic bone, which in turn stimulated the deposition of a new bone matrix by osteoblasts. Collectively, these analyses support the use of an ovariectomy surgery rat model to gain insights into the response of human bone to osteotomy site preparation. The data also suggest that reducing the zone of osteocyte death will improve osteotomy site viability, leading to faster new bone formation around implants.

Neuronal Mechanism for Compensation of Longitudinal Chromatic Aberration-Derived Algorithm

The human visual system faces many challenges, among them the need to overcome the imperfections of its optics, which degrade the retinal image. One of the most dominant limitations is longitudinal chromatic aberration (LCA), which causes short wavelengths (blue light) to be focused in front of the retina with consequent blurring of the retinal chromatic image. The perceived visual appearance, however, does not display such chromatic distortions. The intriguing question, therefore, is how the perceived visual appearance of a sharp and clear chromatic image is achieved despite the imperfections of the ocular optics. To address this issue, we propose a neural mechanism and computational model, based on the unique properties of the S-cone pathway. The model suggests that the visual system overcomes LCA through two known properties of the S channel: (1) omitting the contribution of the S channel from the high-spatial resolution pathway (utilizing only the L and M channels). (b) Having large and coextensive receptive fields that correspond to the small bistratified cells. Here, we use computational simulations of our model on real images to show how integrating these two basic principles can provide a significant compensation for LCA. Further support for the proposed neuronal mechanism is given by the ability of the model to predict an enigmatic visual phenomenon of large color shifts as part of the assimilation effect.

A Comparison of Phenomenologic Growth Laws for Myocardial Hypertrophy

The heart grows in response to changes in hemodynamic loading during normal development and in response to valve disease, hypertension, and other pathologies. In general, a left ventricle subjected to increased afterload (pressure overloading) exhibits concentric growth characterized by thickening of individual myocytes and the heart wall, while one experiencing increased preload (volume overloading) exhibits eccentric growth characterized by lengthening of myocytes and dilation of the cavity. Predictive models of cardiac growth could be important tools in evaluating treatments, guiding clinical decision making, and designing novel therapies for a range of diseases. Thus, in the past 20 years there has been considerable effort to simulate growth within the left ventricle. While a number of published equations or systems of equations (often termed "growth laws") can capture some aspects of experimentally observed growth patterns, no direct comparisons of the various published models have been performed. Here we examine eight of these laws and compare them in a simple test-bed in which we imposed stretches measured during in vivo pressure and volume overload. Laws were compared based on their ability to predict experimentally measured patterns of growth in the myocardial fiber and radial directions as well as the ratio of fiber-to-radial growth. Three of the eight laws were able to reproduce most key aspects of growth following both pressure and volume overload. Although these three growth laws utilized different approaches to predict hypertrophy, they all employed multiple inputs that were weakly correlated during in vivo overload and therefore provided independent information about mechanics.

Relation between denaturation time measured by optical coherence reflectometry and thermal lesion depth during radiofrequency cardiac ablation: Feasibility numerical study

BACKGROUND/OBJECTIVE

Radiofrequency (RF) catheter ablation is a minimally invasive medical procedure used to thermally destroy the focus of cardiac arrhythmias. Novel optical techniques are now being integrated into RF catheters in order to detect the changes in tissue properties. Loss of birefringence due to fiber denaturation at around 70°C is related to changes in accumulated phase retardation and can be measured by polarization-sensitive optical coherence reflectometry (PS-OCR). Since irreversible thermal lesions are produced when the tissue reaches 50°C, our goal was to seek the mathematical relationship between both isotherms.

MATERIALS AND METHODS

A two-dimensional model based on a coupled electric-thermal problem was built and solved using the finite element method. The model consisted of cardiac tissue, blood, and a non-irrigated electrode with a sensor embedded in its tip to maintain a specific target electrode temperature. Computer simulations were conducted by varying the tissue characteristics. Lesion depth was estimated by the 50°C isotherm, while the denaturation time (TD) was taken as the time at which the 70°C isotherm reached a depth of 0.75 mm (which corresponds to the optical depth reached by PS-OCR technology).

RESULTS

A strong correlation (R²  > 0.83) was found between TD and lesion depth and an even stronger correlation (R² > 0.96) was found between TD and the time required to achieve a specific lesion depth. For instance, the ablation time required to ensure a minimum lesion depth of 3 mm was 1.33 × TD + 3.93 × seconds.

CONCLUSIONS

The computer results confirmed the strong relationship between denaturation time and lesion depth and suggest that measuring denaturation time by PS-OCR could provide information on the ablation time required to reach a specific lesion depth. Lasers Surg. Med. 50:222-229, 2018. © 2017 Wiley Periodicals, Inc.

Fibrosis and Atrial Fibrillation: Computerized and Optical Mapping; A View into the Human Atria at Submillimeter Resolution

Recent studies strongly suggest that the majority of atrial fibrillation (AF) patients with diagnosed or subclinical cardiac diseases have established or even pre-existing fibrotic structural remodeling, which may lead to conduction abnormalities and reentrant activity that sustain AF. As conventional treatments fail to treat AF in far too many cases, an urgent need exists to identify specific structural arrhythmogenic fibrosis patterns, which may maintain AF, in order to identify effective ablation targets for AF treatment. However, the existing challenge is to define what exact structural remodeling within the complex 3D human atrial wall is arrhythmogenic, as well as linking arrhythmogenic fibrosis to an underlying mechanism of AF maintenance in the clinical setting. This review is focused on the role of 3D fibrosis architecture in the mechanisms of AF maintenance revealed by submillimeter, high-resolution ex-vivo imaging modalities directly of human atria, as well as from in-silico 3D computational techniques that can be able to overcome in-vivo clinical limitations. The systematic integration of functional and structural imaging ex-vivo may inform the necessary integration of electrode and structural mapping in-vivo. A holistic view of AF driver mechanisms may begin to identify the defining characteristics or "fingerprints" of reentrant AF drivers, such as 3D fibrotic architecture, in order to design optimal patient-specific ablation strategies.

An Approach for a Synthetic CTL Vaccine Design against Zika Flavivirus Using Class I and Class II Epitopes Identified by Computer Modeling

The threat posed by severe congenital abnormalities related to Zika virus (ZKV) infection during pregnancy has turned development of a ZKV vaccine into an emergency. Recent work suggests that the cytotoxic T lymphocyte (CTL) response to infection is an important defense mechanism in response to ZKV. Here, we develop the rationale and strategy for a new approach to developing cytotoxic T lymphocyte (CTL) vaccines for ZKV flavivirus infection. The proposed approach is based on recent studies using a protein structure computer model for HIV epitope selection designed to select epitopes for CTL attack optimized for viruses that exhibit antigenic drift. Because naturally processed and presented human ZKV T cell epitopes have not yet been described, we identified predicted class I peptide sequences on ZKV matching previously identified DNV (Dengue) class I epitopes and by using a Major Histocompatibility Complex (MHC) binding prediction tool. A subset of those met the criteria for optimal CD8+ attack based on physical chemistry parameters determined by analysis of the ZKV protein structure encoded in open source Protein Data File (PDB) format files. We also identified candidate ZKV epitopes predicted to bind promiscuously to multiple HLA class II molecules that could provide help to the CTL responses. This work suggests that a CTL vaccine for ZKV may be possible even if ZKV exhibits significant antigenic drift. We have previously described a microsphere-based CTL vaccine platform capable of eliciting an immune response for class I epitopes in mice and are currently working toward in vivo testing of class I and class II epitope delivery directed against ZKV epitopes using the same microsphere-based vaccine.

Plasticity in the Period of the Circadian Pacemaker Induced by Phase Dispersion of Its Constituent Cellular Clocks

The mammalian circadian pacemaker is commonly thought to be a rigid oscillator that generates output under a variety of circumstances that differ only in phase, period, and/or amplitude. Yet the pacemaker is composed of many cells that each can respond to varying circumstances in different ways. Computer simulations demonstrate that networks of such pacemaker cells behave differently under a light-dark cycle compared with constant darkness. The differences demonstrate that the circadian pacemaker is plastic: The pacemaker shapes its properties in response to the circumstances. A consequence is that properties of a pacemaker under a light-dark cycle cannot be derived from studies of the same system in constant darkness. In this paper we show that the dispersion of phase in a network of coupled oscillators can influence ensemble period: For the considered type of coupling, it is demonstrated that the more synchronous the cells are, the longer is the ensemble period. This is consistent with various data sets obtained in mammals, and even with a data set from fruit flies, in which circadian variation in behavior is regulated in a distinctly differently way from that in mammals. We conclude that environmental circumstances such as photoperiod and exposure to light pulses in otherwise darkness modify the phase distribution of the network and, thereby, the period of the ensemble. Our study supports the view that such properties as circadian period are not solely determined by clock genes but are also determined by the genes that regulate the communication in cellular networks.

A numerical strategy for finite element modeling of frictionless asymmetric vocal fold collision

Analysis of voice pathologies may require vocal fold models that include relevant features such as vocal fold asymmetric collision. The present study numerically addresses the problem of frictionless asymmetric collision in a self-sustained three-dimensional continuum model of the vocal folds. Theoretical background and numerical analysis of the finite-element position-based contact model are presented, along with validation. A novel contact detection mechanism capable to detect collision in asymmetric oscillations is developed. The effect of inexact contact constraint enforcement on vocal fold dynamics is examined by different variational methods for inequality constrained minimization problems, namely, the Lagrange multiplier method and the penalty method. In contrast to the penalty solution, which is related to classical spring-like contact forces, numerical examples show that the parameter-independent Lagrange multiplier solution is more robust and accurate in the estimation of dynamical and mechanical features at vocal fold contact. Furthermore, special attention is paid to the temporal integration schemes in relation to the contact problem, the results suggesting an advantage of highly diffusive schemes. Finally, vocal fold contact enforcement is shown to affect asymmetric oscillations. The present model may be adapted to existing vocal fold models, which may contribute to a better understanding of the effect of the nonlinear contact phenomenon on phonation. Copyright © 2016 John Wiley & Sons, Ltd.

Ionic mechanisms maintaining action potential conduction velocity at high firing frequencies in an unmyelinated axon

The descending contralateral movement detector (DCMD) is a high‐performance interneuron in locusts with an axon capable of transmitting action potentials (AP) at more than 500 Hz. We investigated biophysical mechanisms for fidelity of high‐frequency transmission in this axon. We measured conduction velocities (CVs) at room temperature during exposure to 10 mmol/L cadmium, a calcium current antagonist, and found significant reduction in CV with reduction at frequencies >200 Hz of ~10%. Higher temperatures induced greater CV reductions during exposure to cadmium across all frequencies of ~20–30%. Intracellular recordings during 15 min of exposure to cadmium or nickel, also a calcium current antagonist, revealed an increase in the magnitude of the afterhyperpolarization potential (AHP) and the time to recover to baseline after the AHP (Medians for Control: −19.8%; Nickel: 167.2%; Cadmium: 387.2%), that could be due to a T‐type calcium current. However, the removal of extracellular calcium did not mimic divalent cation exposure suggesting calcium currents are not the cause of the AHP increase. Computational modeling showed that the effects of the divalent cations could be modeled with a persistent sodium current which could be blocked by high concentrations of divalent cations. Persistent sodium current shortened the AHP duration in our models and increased CV for high‐frequency APs. We suggest that faithful, high‐frequency axonal conduction in the DCMD is enabled by a mechanism that shortens the AHP duration like a persistent or resurgent sodium current.

Complementary mechanisms create direction selectivity in the fly

How neurons become sensitive to the direction of visual motion represents a classic example of neural computation. Two alternative mechanisms have been discussed in the literature so far: preferred direction enhancement, by which responses are amplified when stimuli move along the preferred direction of the cell, and null direction suppression, where one signal inhibits the response to the subsequent one when stimuli move along the opposite, i.e. null direction. Along the processing chain in the Drosophila optic lobe, directional responses first appear in T4 and T5 cells. Visually stimulating sequences of individual columns in the optic lobe with a telescope while recording from single T4 neurons, we find both mechanisms at work implemented in different sub-regions of the receptive field. This finding explains the high degree of directional selectivity found already in the fly's primary motion-sensing neurons and marks an important step in our understanding of elementary motion detection.

Computational Analysis of the Hypothalamic Control of Food Intake

Food-intake control is mediated by a heterogeneous network of different neural subtypes, distributed over various hypothalamic nuclei and other brain structures, in which each subtype can release more than one neurotransmitter or neurohormone. The complexity of the interactions of these subtypes poses a challenge to understanding their specific contributions to food-intake control, and apparent consistencies in the dataset can be contradicted by new findings. For example, the growing consensus that arcuate nucleus neurons expressing Agouti-related peptide (AgRP neurons) promote feeding, while those expressing pro-opiomelanocortin (POMC neurons) suppress feeding, is contradicted by findings that low AgRP neuron activity and high POMC neuron activity can be associated with high levels of food intake. Similarly, the growing consensus that GABAergic neurons in the lateral hypothalamus suppress feeding is contradicted by findings suggesting the opposite. Yet the complexity of the food-intake control network admits many different network behaviors. It is possible that anomalous associations between the responses of certain neural subtypes and feeding are actually consistent with known interactions, but their effect on feeding depends on the responses of the other neural subtypes in the network. We explored this possibility through computational analysis. We made a computer model of the interactions between the hypothalamic and other neural subtypes known to be involved in food-intake control, and optimized its parameters so that model behavior matched observed behavior over an extensive test battery. We then used specialized computational techniques to search the entire model state space, where each state represents a different configuration of the responses of the units (model neural subtypes) in the network. We found that the anomalous associations between the responses of certain hypothalamic neural subtypes and feeding are actually consistent with the known structure of the food-intake control network, and we could specify the ways in which the anomalous configurations differed from the expected ones. By analyzing the temporal relationships between different states we identified the conditions under which the anomalous associations can occur, and these stand as model predictions.

Inhalation Study of Mycobacteriophage D29 Aerosol for Mice by Endotracheal Route and Nose-Only Exposure

BACKGROUND

Lytic mycobacteriophage D29 has the potential for tuberculosis treatment including multidrug-resistant strains. The aims of this study are to investigate deposition and distribution of aerosolized phage D29 particles in naive Balb/C mice, together with pharmacokinetics and evaluation of acute lung injury.

METHODS

Pharmacokinetics and BALF (bronchoalveolar lavage fluids) were analyzed after administration of phage D29 aerosols by endotracheal route using Penn-century aerosolizer; Collison 6-jet and Spinning top aerosol nebulizers (STAG) were used to generate phage aerosols with different particle size distributions in nose-only inhalation experiments. After exposure, deposited amounts of phage D29 particles in respiratory tracts were measured, and deposition efficiencies were calculated. A typical path deposition model for mice was developed, and then comparisons were made between predictions and experimentally measured results.

RESULTS

Approximately 10% of aerosolized phages D29 reached lung of mouse for pulmonary delivery, and were completely eliminated until 72 h after administration. In contrast, about 0.1% of intraperitoneal injected phages reached the lung, and were almost eliminated at 12 h time point. The inflammation was hardly observed in lung according to the results of BALF analysis. The CMADs (count median aerodynamic diameters) of generated aerosol by Collison and STAG nebulizer were 0.8 μm and 1.5 μm, respectively. After nose-only exposure, measured deposition efficiencies in whole respiratory tract for 0.8 and 1.5 μm phage particles were below 1% and 10%, respectively. Predictions of the computer deposition model compared fairly well with experimentally measured results.

CONCLUSIONS

This is the first systematic study of phage D29 aerosol respiratory challenge in laboratory animals. It provides evidence that aerosol delivery of phage D29 is an effective way for treating pulmonary infections caused by Mycobacterium tuberculosis. This research will also provide important data for future inhalation experiments.

A computer model for the simulation of nanoparticle deposition in the alveolar structures of the human lungs

BACKGROUND

According to epidemiological and experimental studies, inhalation of nanoparticles is commonly believed as a main trigger for several pulmonary dysfunctions and lung diseases. Concerning the transport and deposition of such nano-scale particles in the different structures of the human lungs, some essential questions are still in need of a clarification. Therefore, main objective of the study was the simulation of nanoparticle deposition in the alveolar region of the human respiratory tract (HRT).

METHODS

Respective factors describing the aerodynamic behavior of spherical and non-spherical particles in the inhaled air stream (i.e., Cunningham slip correction factors, dynamic shape factors, equivalent-volume diameters, aerodynamic diameters) were computed. Alveolar deposition of diverse nanomaterials according to several known mechanisms, among which Brownian diffusion and sedimentation play a superior role, was approximated by the use of empirical and analytical formulae. Deposition calculations were conducted with a currently developed program, termed NANODEP, which allows the variation of numerous input parameters with regard to particle geometry, lung morphometry, and aerosol inhalation.

RESULTS

Generally, alveolar deposition of nanoparticles concerned for this study varies between 0.1% and 12.4% during sitting breathing and between 2.0% and 20.1% during heavy-exercise breathing. Prolate particles (e.g., nanotubes) exhibit a significant increase in deposition, when their aspect ratio is enhanced. In contrast, deposition of oblate particles (e.g., nanoplatelets) is remarkably declined with any reduction of the aspect ratio.

CONCLUSIONS

The study clearly demonstrates that alveolar deposition of nanoparticles represents a topic certainly being of superior interest for physicists and respiratory physicians in future.

A model model: a commentary on DiFrancesco and Noble (1985) 'A model of cardiac electrical activity incorporating ionic pumps and concentration changes'

This paper summarizes the advances made by the DiFrancesco and Noble (DFN) model of cardiac cellular electrophysiology, which was published in Philosophical Transactions B in 1985. This model was developed at a time when the introduction of new techniques and provision of experimental data had resulted in an explosion of knowledge about the cellular and biophysical properties of the heart. It advanced the cardiac modelling field from a period when computer models considered only the voltage-dependent channels in the surface membrane. In particular, it included a consideration of changes of both intra- and extracellular ionic concentrations. In this paper, we summarize the most important contributions of the DiFrancesco and Noble paper. We also describe how computer modelling has developed subsequently with the extension from the single cell to the whole heart as well as its use in understanding disease and predicting the effects of pharmaceutical interventions. This commentary was written to celebrate the 350th anniversary of the journal Philosophical Transactions of the Royal Society.

Spike propagation through the dorsal root ganglia in an unmyelinated sensory neuron: a modeling study

Unmyelinated C-fibers are a major type of sensory neurons conveying pain information. Action potential conduction is regulated by the bifurcation (T-junction) of sensory neuron axons within the dorsal root ganglia (DRG). Understanding how C-fiber signaling is influenced by the morphology of the T-junction and the local expression of ion channels is important for understanding pain signaling. In this study we used biophysical computer modeling to investigate the influence of axon morphology within the DRG and various membrane conductances on the reliability of spike propagation. As expected, calculated input impedance and the amplitude of propagating action potentials were both lowest at the T-junction. Propagation reliability for single spikes was highly sensitive to the diameter of the stem axon and the density of voltage-gated Na⁺ channels. A model containing only fast voltage-gated Na⁺ and delayed-rectifier K⁺ channels conducted trains of spikes up to frequencies of 110 Hz. The addition of slowly activating KCNQ channels (i.e., K_V7 or M-channels) to the model reduced the following frequency to 30 Hz. Hyperpolarization produced by addition of a much slower conductance, such as a Ca²⁺-dependent K⁺ current, was needed to reduce the following frequency to 6 Hz. Attenuation of driving force due to ion accumulation or hyperpolarization produced by a Na⁺-K⁺ pump had no effect on following frequency but could influence the reliability of spike propagation mutually with the voltage shift generated by a Ca²⁺-dependent K⁺ current. These simulations suggest how specific ion channels within the DRG may contribute toward therapeutic treatments for chronic pain.

Optimization of catheter ablation of atrial fibrillation: insights gained from clinically-derived computer models

Atrial fibrillation (AF) is the most common heart rhythm disturbance, and its treatment is an increasing economic burden on the health care system. Despite recent intense clinical, experimental and basic research activity, the treatment of AF with current antiarrhythmic drugs and catheter/surgical therapies remains limited. Radiofrequency catheter ablation (RFCA) is widely used to treat patients with AF. Current clinical ablation strategies are largely based on atrial anatomy and/or substrate detected using different approaches, and they vary from one clinical center to another. The nature of clinical ablation leads to ambiguity regarding the optimal patient personalization of the therapy partly due to the fact that each empirical configuration of ablation lines made in a patient is irreversible during one ablation procedure. To investigate optimized ablation lesion line sets, in silico experimentation is an ideal solution. 3D computer models give us a unique advantage to plan and assess the effectiveness of different ablation strategies before and during RFCA. Reliability of in silico assessment is ensured by inclusion of accurate 3D atrial geometry, realistic fiber orientation, accurate fibrosis distribution and cellular kinetics; however, most of this detailed information in the current computer models is extrapolated from animal models and not from the human heart. The predictive power of computer models will increase as they are validated with human experimental and clinical data. To make the most from a computer model, one needs to develop 3D computer models based on the same functionally and structurally mapped intact human atria with high spatial resolution. The purpose of this review paper is to summarize recent developments in clinically-derived computer models and the clinical insights they provide for catheter ablation.

Patient-specific computer model of dynamic squatting after total knee arthroplasty

Knee forces are highly relevant to performance after total knee arthroplasty especially during high flexion activities such as squatting. We constructed subject-specific models of two patients implanted with instrumented knee prostheses that measured knee forces in vivo. In vivo peak forces ranged from 2.2 to 2.3 times bodyweight but peaked at different flexion angles based on the type of squatting activity. Our model predicted tibiofemoral contact force with reasonable accuracy in both subjects. This model can be a very useful tool to predict the effect of surgical techniques and component alignment on contact forces. In addition, this model could be used for implant design development, to enhance knee function, to predict forces generated during other activities, and for predicting clinical outcomes.