Realistic Computational Model Research Articles

EXTH-37. A NOVEL TRANSDUCER ARRAY LAYOUT FOR DELIVERING TUMOR TREATING FIELDS TO THE SPINE

Abstract Tumor Treating Fields (TTFields) are an antimitotic technology utilising electric fields to disrupt mitosis in cancer cells. TTFields are currently approved by the FDA for the treatment of Glioblastoma Multiforme (GBM) and Malignant Pleural Mesothelioma (MPM). TTFields are delivered through 2 pairs of transducer arrays placed on the patient’s skin. Each pair delivers TTFields in a single direction, and the pairs are placed to provide perpendicular field. Preclinical studies show that 1V/cm is the clinical threshold for the treatment to be effective. Some types of cancers send metastases to the spinal cord and CSF, i.e. leptomeningeal disease. The purpose of this study was to find transducer array layouts that deliver TTFields to the spine at therapeutic intensities of above 1 V/cm. Computational simulations testing the delivery of TTFields to the spine were performed using the Sim4Life 4.0 (ZMT Zurich) computational platform, and the Duke 3.1 and Ella 3.0 (ITI’S, Zurich) realistic computational models of a male and female respectively. “Standard” layouts in which a pair of arrays are placed on the front and back of the patient and second pair on the lateral aspects of the patient failed to deliver TTFields at therapeutic intensities to the spinal cord. This is probably because the spinal cord is surrounded by the CSF and spine, which shunt the electric fields from reaching the spinal cord. However, field intensities above 1 V/cm were observed when delivering TTFields when both arrays were placed on the patients back, with a first array placed close to the neck, and second array placed towards the thighs. In this case, the spinal cord and surrounding CSF act as a conductive cable, directing the electric field along the spine. This novel layout opens the possibility for treating cancerous disease along the spine.

Morphology Evolution during Lithium-Based Vertically Aligned Nanocomposite Growth.

Ceramic-based nanocomposites are a rapidly evolving research area as they are currently being used in a wide range of applications. Epitaxial vertically aligned nanocomposites (VANs) offer promising advantages over conventional planar multilayers as key functionalities are tailored by the strong coupling at their vertical interfaces. However, limited knowledge exists of which material systems are compatible in composite films and which types of structures are optimal for a given functionality. No lithium-based VANs have yet been explored for energy storage, while 3D solid-state batteries offer great promise for enhanced energy and power densities. Although solid-on-solid kinetic Monte Carlo simulation (KMCS) models of VAN growth have previously been developed, phase separation was forced into the systems by limiting hopping directions and/or tuning the activation energies for hopping. Here, we study the influence of the temperature and deposition rate on the morphology evolution of lithium-based VANs, consisting of a promising LiMn2O4 cathode and a Li0.5La0.5TiO3 electrolyte, by applying a KMCS model with activation energies for hopping obtained experimentally and with minimum restrictions for hopping directions. Although the model considers only the kinetic processes away from thermodynamic equilibrium, which would determine the final shape of the pillars within the matrix, the trends in pillar size and distribution within the simulated VANs are in good agreement with experiments. This provides an elegant tool to predict the growth of VAN materials as the experimental activation energies and higher degrees of freedom for hopping result in a more realistic and low computational cost model to obtain accurate simulations of VAN materials.

Towards the realistic computer model of precipitation polymerization microgels

In this paper we propose a new method of coarse-grained computer simulations of the microgel formation in course of free radical precipitation polymerization. For the first time, we simulate the precipitation polymerization process from a dilute solution of initial components to a final microgel particle with coarse grained molecular dynamics, and compare it to the experimental data. We expect that our simulation studies of PNIPA-like microgels will be able to elucidate the subject of nucleation and growth kinetics and to describe in detail the network topology and structure. Performed computer simulations help to determine the characteristic phases of the growth process and show the necessity of prolongated synthesis for the formation of stable microgel particles. We demonstrate the important role of dangling ends in microgels, which occupy as much as 50% of its molecular mass and have previously unattended influence on the swelling behavior. The verification of the model is made by the comparison of collapse curves and structure factors between simulated and experimental systems, and high quality matching is achieved. This work could help to open new horizons in studies that require the knowledge of detailed and realistic structures of the microgel networks.

P11.18 Tumor treating fields (TTFields) treatment of spinal cord metastases

Abstract BACKGROUND Tumor Treating Fields (TTFields) is an anti-mitotic cancer treatment approved for the treatment of Glioblastoma multiforme (GBM) and is currently also investigated in a phase III trial in 1–10 brain metastases from non-small cell lung cancer (METIS). Apart from spread to the brain, some cancer types, such as breast cancer, lung cancer, and melanoma, may lead to metastatic spread to the spinal cord. Previous studies have shown that reported transducer array layouts for the treatment of abdominal/pelvic tumors (e.g. pancreatic cancer), with one pair of arrays positioned on the anterior and posterior of the patient, and the second pair of arrays placed on each side of the thorax, yield therapeutically insufficient field intensities of <1 V/cm in the spinal cord. This finding probably results from the anatomical structure of the spine, consisting of the cerebrospinal fluid as a highly conductive layer, encased by a resistive bone structure that shunts the current delivered across the body by the arrays away from the spine. This simulation-based study aimed at resolving this challenge by identifying novel array layouts on the body that effectively deliver TTFields to the spine. MATERIAL AND METHODS For the simulations of the TTFields delivery to the spine, a human male 34 years old realistic computational model (DUKE v3.1 by ITI’S, Zurich) and the ZMT’s Sim4Life v4.0 electro-quasi-static solver was utilized. TTFields were simulated by imposing an alternating current with a current density of 200 mA/disk and a frequency of 150 kHz on the outer surfaces of the disks of each pair of arrays. RESULTS For one of the tested array layouts, a high electric field was shown to be induced within the spinal cord and surrounding CSF: Our calculations of mean field intensity within the spine and nerves from vertebrae T8-T9 at the top to L3-L4 at the bottom added up to 1.77 V/cm. This layout consisted of the placement of a pair of arrays on the back of the patient, with one array positioned above the section in the spine to which treatment would be delivered, and the other array positioned below the target section. Notably, the resulting electric field is directed along the spine in this setting (ie, vertically). CONCLUSION Our results demonstrate that treatment of the whole spinal cord and nerves in a single direction can be achieved by placing a pair of transducer arrays on the patient’s back: one array on the neck, and one at the bottom of the spine. For the development of an active treatment in the perpendicular direction, further studies need to be conducted.

P11.21 Treating numerous secondary tumors in the brain with tumor treating fields: Simulation study to identify optimal transducer array layout

Abstract BACKGROUND Tumor Treating Fields (TTFields) use alternating electric fields for the treatment of solid tumors. The therapy is approved for glioblastoma multiforme (GBM), and a phase III trial in 1–10 brain metastases from non-small cell lung cancer (METIS) is currently enrolling patients. In GBM, the layout of the transducer arrays delivering the TTFields to the tumor is optimized for high field intensity in the tumor, while the dose in other regions is decreased. In the setting of secondary brain tumors, as they manifest as brain metastases in 10–30 % of adult cancer patients - especially in melanoma, lung, breast, colon, and kidney cancer - a high TTFields dose in the entire brain would be beneficial. Thus, numerous tumors instead of only one lesion should receive therapeutic TTFields doses. In this study, transducer array layouts aiming for a homogeneous TTFields distribution in the whole brain were investigated. MATERIAL AND METHODS We used computer simulations in a realistic computational head model of a 40+ years old man, constructed in-house from a T1 MRI series, to compute the field distributions obtained with various transducer array layouts. The distribution of TTFields delivered by pairs of transducer arrays at different positions on the head and neck was simulated using Sim4Life v3.0 (ZMT Zürich). For each layout, we determined and compared the mean and median field intensities in five pre-determined sections of the brain: (1) the cerebellum and brain stem together with other infra-tentorial anatomical regions; and (2–5) the four cerebral quadrants. RESULTS One array layout could be identified yielding median intensities between 1.5 V/cm to 1.7 V/cm in all areas and a homogeneous distribution within the brain. This layout is composed of one pair of arrays positioned on the right temple and left scapula, and the other pair positioned on the left temple and right scapula. CONCLUSION This study was able to determine a novel TTFields transducer array layout that might be used for treatment of the entire brain with therapeutic intensities, as would be beneficial in patients with brain metastases.

A Proof of Concept Study for Simulating Heat Transfer in Patients Treated with Tumor-Treating Fields

Tumor Treating Fields are alternating electric fields that inhibit cancer cell growth. TTFields are delivered non-invasively through transducer arrays placed on the skin in close proximity to the tumor. Preclinical studies have shown that the efficacy of TTFields increases with field intensity, with a therapeutic threshold of 1V/cm. However, delivering higher field intensities could result in temperature increases within the body, possibly leading to thermal damage to tissue. In practice, devices designed to deliver TTFields incorporate temperature sensors in the transducer arrays that enable temperature control at the skin, thereby preventing thermal damage to tissues. Heating (at the skin) is the main factor limiting the intensity at which TTFields is delivered. Therefore, accurate models describing tissue heating due to TTFields therapy could provide important insight, ultimately enabling improved TTFields delivery. Measuring the spatial distribution of temperature within a patient’s body is extremely challenging and therefore numerical simulations of the heat flow within the head during treatment are a more practical approach. Here we present initial results from a study aimed to develop a valid computational model of heat transfer in the body during TTFields therapy. A realistic computational head model of a healthy male was used for this study. Virtual transducer arrays were placed on the head, and delivery of TTFields to the brain, was simulated using the Sim4Life v4.0 (ZMT Zürich) electro-quasi-static solver. The results of the electric field simulation were incorporated into the Sim4Life thermal solver to yield the temperature distribution within the head during TTFields therapy. Maximal temperatures occurred in the external tissue layers, below the transducer arrays as expected. Average temperatures within the brain were well below 38°C. Temperature distributions within the brain were sensitive to the perfusion coefficient assigned to the cerebrospinal fluid as well as other tissues. A framework for investigating heat transfer in patients treated with TTFields has been established. Future work combining experiments and simulations is needed to validate the models and establish accurate thermal properties for tissues. In the future, the ability to model heat transfer is expected to lead to improvements in TTFields delivery.

Weak biases emerging from vocal tract anatomy shape the repeated transmission of vowels.

Linguistic diversity is affected by multiple factors, but it is usually assumed that variation in the anatomy of our speech organs plays no explanatory role. Here we use realistic computer models of the human speech organs to test whether inter-individual and inter-group variation in the shape of the hard palate (the bony roof of the mouth) affects acoustics of speech sounds. Based on 107 midsagittal MRI scans of the hard palate of human participants, we modelled with high accuracy the articulation of a set of five cross-linguistically representative vowels by agents learning to produce speech sounds. We found that different hard palate shapes result in subtle differences in the acoustics and articulatory strategies of the produced vowels, and that these individual-level speech idiosyncrasies are amplified by the repeated transmission of language across generations. Therefore, we suggest that, besides culture and environment, quantitative biological variation can be amplified, also influencing language.

Computational procedure to an accurate DFT simulation to solid state systems

The density functional theory has become increasingly common as a methodology to explain the properties of crystalline materials because of the improvement in computational infrastructure and software development to perform such computational simulations. Although several studies have shown that the characteristics of certain classes of materials can be represented with great precision, it is still necessary to improve the methods and strategies in order to achieve more realistic computational modeling. In the present work, strategies are reported in a systematic way for the accurate representation of crystalline systems. The crystalline compound chosen for the study as a case test was BaMoO4, both because of its potential technological application and because of the low accuracy of the simulations previously reported in the literature. The computational models were carried out with the B3LYP and WC1LYP functionals selected from an initial set containing eight hybrid functionals in conjunction with an all-electron basis set. Two different strategies were applied for improving the description of the initial models, both involving atomic basis set optimization and Hartree-Fock exchange percentage adjustment. The results obtained with the two strategies show a precision of structural parameters, band gap energy, and vibrational properties never before presented in theoretical studies of BaMoO4. Finally, a flowchart of good calculation practices is elaborated. This can be of great value for the organization and conduction of calculations in new research.

Abstract 4430: Simulating delivery of TTFields to the infratentorium in patients with brainstem gliomas

Abstract Purpose/Objective(s): TTFields are FDA-approved for the treatment of recurrent and newly diagnosed Glioblastoma (GBM) in the supratentorial brain. The EF-14 trial showed that combining TTFields with adjuvant chemo-radiation leads to a significant increase in overall survival compared to adjuvant chemo-radiation alone. High-grade gliomas also occur in the infratentorium and brainstem of pediatric and adult patients. Brainstem gliomas have a median survival of 9 to 11 months, necessitating the exploration of novel treatment combinations, such as delivering TTFields to the infratentorial brain. We recently showed in a simulation-based study that TTFields can be successfully delivered to the infratentorium. Effective delivery was achieved by placement of the arrays on the vertex, bilateral posterolateral occiput, and superior-posterior neck; the array placement results in TTFields at therapeutic intensities throughout the brainstem and cerebellum of realistic computational head models. The previous simulation-based study was performed using realistic computational models of healthy individuals; it did not provide detailed insight into field distributions within tumor tissue located in the infratentorium. Here, we aim to expand the results of this previous study, by simulating the delivery of TTFields to the infratentorium of adult and pediatric patients with high-grade brainstem gliomas. Materials/Methods: A realistic computational model was created using MRI data of adult and pediatric patients with high-grade brainstem gliomas. Transducer arrays were placed on the model and the delivery of TTFields to the infratentorial brain was then simulated using a commercial numerical solver. The electric field distribution in the supratentorium, infratentorium, and within the tumor were derived from the simulations, and the dose in the tumor analyzed. Results: The distribution of calculated isofield lines demonstrates effective delivery of TTFields to infratentorial brain tumors. Conclusion: Our results provides rationale for clinically investigating the utility of TTFields in treating infratentorial high-grade gliomas. Citation Format: Marigdalia K. Ramirez-Fort, Brittany Cross, Ariel Naveh, Shearwood McClelland III, Melissa Mendez, Roberto Santiago, Sean S. Mahase, Jaime Matta, Ze'ev Bomzon, Christopher S. Lange. Simulating delivery of TTFields to the infratentorium in patients with brainstem gliomas [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4430.

Abstract CT204: Increasing Tumor Treating Fields dose at the tumor bed improves survival: Setting a framework for TTFields dosimetry based on analysis of the EF-14 Phase III trial in newly diagnosed glioblastoma

Abstract Introduction: Tumor Treating Fields (TTFields) are low intensity, intermediate frequency, anti-mitotic alternating electric fields that are delivered via transducer arrays placed on the shaved scalp. TTFields are approved for Glioblastoma (GBM) based on improved overall survival (OS) and progression free survival (PFS) in the Phase III EF-14 [NCT00916409] trial in newly diagnosed GBM patients. To test the hypothesis if increasing TTFields dose at the tumor bed improves patient outcomes, we performed a simulation-based study investigating the association between TTFields dose and overall survival (OS) and progression free survival (PFS) in EF-14 TTFields-treated patients. Methods: EF-14 patients cases (N=340) were included. Realistic computational head models of the patients were derived from T1-contrast images captured at baseline. Patients who were on treatment for less than two months, or for whom MRI image quality was insufficient for the creation of a realistic head model were excluded from the analysis (N=126). The transducer array layout on each patient was obtained from EF-14 records; average compliance (fraction of time patient was on active treatment), and average electrical current delivered to the patient were derived from log files of the TTFields devices used by patients. TTFields intensity distributions and power loss densities were calculated for each patient using a Finite Elements Method. Local Minimum Dose Density (LMiDD) was defined as the product of TTFields power loss density and the average patient compliance. The average LMiDD within a tumor bed comprising the Gross Tumor Volume and the Peritumoral Boundary Zone 3 mm wide was calculated. Results: The median OS and PFS were significantly longer when average LMiDD in the tumor bed was >0.77 MmW/cm3: OS (25.2 vs. 20.4 months, p=0.003, HR=0.611) and PFS (8.5 vs 6.7 months, p=0.02, HR=0.699). The median OS and PFS were longer when average TTFields intensity was >1.06 V/cm OS (24.3 vs. 21.6 months, p=0.03, HR=0.705) and PFS (8.1 vs 7.9 months, p=0.03, HR=0.721). Conclusions: In this study we present the first reported analysis demonstrating patient-level dose responses to TTFields. Increasing Tumor Treating Fields dose at the tumor bed improves survival (OS and PFS) in newly diagnosed GBM. We provide a rigorous definition for TTFields dose, and set a conceptual framework for future work on TTFields dosimetry and treatment planning. Citation Format: Matthew T. Ballo, Noa Urman, Ze'ev Bomzon, Gitit Lavy-Shahaf, Steven Toms. Increasing Tumor Treating Fields dose at the tumor bed improves survival: Setting a framework for TTFields dosimetry based on analysis of the EF-14 Phase III trial in newly diagnosed glioblastoma [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr CT204.

Abstract 688: Safety and efficacy of TTFields delivery to the lungs: A computational study

Abstract Objective: This study investigates the efficacy and safety of Tumor Treating Fields (TTFields) delivery to the lungs utilizing computational simulations. Introduction: Recent results of a phase 2 clinical trial STELLAR (NCT02397928) demonstrated a significant extension in median overall survival among patients with mesothelioma treated with TTFields plus standard of care chemotherapy compared to historical control data of patients who received standard of care chemotherapy alone. A phase 3 clinical trial (NCT02973789) is currently investigating the efficacy of TTFields therapy for the treatment of Non-Small-Cell lung cancer (NSCLC). The efficacy of TTFields therapy in disrupting tumor cells depends on the frequency of the field (150kHz optimal frequency for NSCLC and mesothelioma) and the field intensity. The higher the field intensity, the larger the therapeutic effect, with a therapeutic threshold of 0.7 V/cm above which TTFields begin to exert a significant anti-mitotic effect on cells. Delivery of an electric field to the body unavoidably leads to deposition of heat in the tissue through Joule heating. The rate at which electrical energy is absorbed and converted to heat, depends on field’s frequency and tissue’s properties. Since Joule heating may cause thermal damage, it is important to ensure that TTFields intensity in the body is below the thermal damage threshold. In this study we performed numerical simulations to evaluate the thermal safety and the efficacy of the NovoTTF-100L when delivering Tumor Treating Fields to the torso. Thermal safety threshold levels were determined by current density and specific absorption rate (SAR) and TTFields therapeutic threshold was determined by field intensity. Methods: We investigated field intensity, current density and SAR values that developed within 3 different realistic human computational models in which a virtual representation of the NovoTTF-100L (150kHz) was used to deliver TTFields to the lungs. The models used in this study include: a female model, male model and an obese male model (Virtual Population, IT’IS foundation) with a range of BMI values from normal to obese. Numerical simulations were performed using Sim4life (v3.0, ZMT Zurich). Results: The simulations show that for all models, the NovoTTF-100L delivers therapeutic intensities of over 0.7 V/cm RMS to over at least 76% of the lungs. Current density within the models is well below the safety threshold of 100 mA/cm^2. SAR values within the internal organs are below the levels at which thermal damage occurs. In the superficial body layers, higher SAR values are observed. However, the NovoTTF-100L incorporates temperature control that prevents the skin from heating to levels at which thermal damage can occur. Conclusions: Results of this study support the observations that the NovoTTF-100L delivers TTFields to the lungs at therapeutic levels and that the device is safe for use in the entire patient population. Citation Format: Hadas Sara Hershkovich, Noa Urman, Ariel Naveh, Zeev Bomzon. Safety and efficacy of TTFields delivery to the lungs: A computational study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 688.

Abstract 691: Simulating TTFields-induced temperature changes within a patient’s brain - a proof of concept study

Abstract Introduction: TTFields is an antimitotic cancer treatment that utilizes low intensity (1-3 V/cm) alternating electric fields in the intermediate frequency (100-300 kHz) that are delivered in two orthogonal directions using 2 pairs of transducer arrays. TTFields are currently approved for Glioblastoma Multiforme (GBM). Preclinical studies show that the effect of TTFields is intensity-dependent with a therapeutic threshold of 1 V/cm, and that as the intensity rises so does the efficacy. However, delivery of high field intensities could result in temperature increases within the body that lead to thermal damage to tissue. In practice, during treatment with TTFields, tissue heating is limited by a closed loop that adjusts the delivery of TTFields to ensure that skin temperature remains within the safety limits. Since heating limits the intensity at which TTFields is delivered, accurate models of tissue heating during TTFields therapy could provide insights into new approaches for the delivery of TTFields. Since measuring the temperature spatial distribution within a patient’s brain is extremely challenging, simulating the heat flow within the head during treatment is a more practical approach. Here, we present preliminary results from a study aimed at developing a valid computational model of heat transfer in the head during TTFields therapy. Method: A realistic computational head model of a healthy male was used in this study. Virtual transducer arrays were placed on the head. To simulate the delivery of TTFields to the brain, we used ZMT's Sim4Life v4.0 electro-quasi-static solver. The results of the electric field simulation were then used as heat source for the heat simulation. The heat simulation solves the Pennes bio-heat model, taking into account tissue heat capacity and conductivity, and also accounting for heat convection through blood perfusion. Sensitivity analysis was performed to establish the sensitivity of the temperature distribution within the brain to the thermal properties of the various tissue types. Results: Average temperatures within the brain tissue were well below 38° C for all simulations. Temperature distributions within the brain were highly sensitive to the perfusion coefficient assigned to the cerebrospinal fluid as well as other tissues.Conclusions: We have established a computational framework for investigating heat transfer in the brain during TTFields therapy. Further work is needed to correctly establish the thermal properties of the various tissue types. This may require experimental measurements in which the heat transfer model is fine-tuned and validated. Citation Format: Ariel Naveh, Ze'ev Bomzon. Simulating TTFields-induced temperature changes within a patient’s brain - a proof of concept study [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 691.

Estimation of the radiation dose in pregnancy: an automated patient-specific model using convolutional neural networks.

The conceptus dose during diagnostic imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. The aim of this work is to develop a methodology for automated construction of patient-specific computational phantoms based on actual patient CT images to enable accurate estimation of conceptus dose. We developed a 3D deep convolutional network algorithm for automated segmentation of CT images to build realistic computational phantoms. The neural network architecture consists of analysis and synthesis paths with four resolution levels each, trained on manually labeled CT scans of six identified anatomical structures. Thirty-two CT exams were augmented to 128 datasets and randomly split into 80%/20% for training/testing. The absorbed doses for six segmented organs/tissues from abdominal CT scans were estimated using Monte Carlo calculations. The resulting radiation doses were then compared between the computational models generated using automated segmentation and manual segmentation, serving as reference. The Dice similarity coefficient for identified internal organs between manual segmentation and automated segmentation results varies from 0.92 to 0.98 while the mean Hausdorff distance for the uterus is 16.1mm. The mean absorbed dose for the uterus is 2.9mGy whereas the mean organ dose differences between manual and automated segmentation techniques are 0.07%, - 0.45%, - 1.55%, - 0.48%, - 0.12%, and 0.28% for the kidney, liver, lung, skeleton, uterus, and total body, respectively. The proposed methodology allows automated construction of realistic computational models that can be exploited to estimate patient-specific organ radiation doses from radiological imaging procedures. • The conceptus dose during diagnostic radiology and nuclear medicine imaging procedures for pregnant patients raises health concerns owing to the high radiosensitivity of the developing embryo/fetus. • The proposed methodology allows automated construction of realistic computational models that can be exploited to estimate patient-specific organ radiation doses from radiological imaging procedures. • The dosimetric results can be used for the risk-benefit analysis of radiation hazards to conceptus from diagnostic imaging procedures, thus guiding the decision-making process.

Intracellular calcium stores mediate metaplasticity at hippocampal dendritic spines.

Key points Calcium (Ca2+) entry mediated by NMDA receptors is considered central to the induction of activity‐dependent synaptic plasticity in hippocampal area CA1; this description does not, however, take into account the potential contribution of endoplasmic reticulum (ER) Ca2+ stores.The ER has a heterogeneous distribution in CA1 dendritic spines, and may introduce localized functional differences in Ca2+ signalling between synapses, as suggested by experiments on metabotropic receptor‐dependent long‐term depression.A physiologically detailed computational model of Ca2+ dynamics at a CA3–CA1 excitatory synapse characterizes the contribution of spine ER via metabotropic signalling during plasticity induction protocols.ER Ca2+ release via IP3 receptors modulates NMDA receptor‐dependent plasticity in a graded manner, to selectively promote synaptic depression with relatively diminished effect on LTP induction; this may temper further strengthening at the stronger synapses which are preferentially associated with ER‐containing spines.Acquisition of spine ER may thus represent a local, biophysically plausible ‘metaplastic switch’ at potentiated CA1 synapses, contributing to the plasticity–stability balance in neural circuits. Long‐term plasticity mediated by NMDA receptors supports input‐specific, Hebbian forms of learning at excitatory CA3–CA1 connections in the hippocampus. There exists an additional layer of stabilizing mechanisms that act globally as well as locally over multiple time scales to ensure that plasticity occurs in a constrained manner. Here, we investigated the role of calcium (Ca2+) stores associated with the endoplasmic reticulum (ER) in the local regulation of plasticity at individual CA1 synapses. Our study was spurred by (1) the curious observation that ER is sparsely distributed in dendritic spines, but over‐represented in larger spines that are likely to have undergone activity‐dependent strengthening, and (2) evidence suggesting that ER motility at synapses can be rapid, and accompany activity‐regulated spine remodelling. We constructed a physiologically realistic computational model of an ER‐bearing CA1 spine, and examined how IP3‐sensitive Ca2+ stores affect spine Ca2+ dynamics during activity patterns mimicking the induction of long‐term potentiation and long‐term depression (LTD). Our results suggest that the presence of ER modulates NMDA receptor‐dependent plasticity in a graded manner that selectively enhances LTD induction. We propose that ER may locally tune Ca2+‐based plasticity, providing a braking mechanism to mitigate runaway strengthening at potentiated synapses. Our study provides a biophysically accurate description of postsynaptic Ca2+ regulation, and suggests that ER in the spine may promote the re‐use of hippocampal synapses with saturated strengths.

How Can We Show You, If You Can't See It? Trialing the Use of an Interactive Three-Dimensional Micro-CT Model in Medical Education.

Teaching internal structures obscured from direct view is a major challenge of anatomy education. High-fidelity interactive three-dimensional (3D) micro-computed tomography (CT) models with virtual dissection present a possible solution. However, their utility for teaching complex internal structures of the human body is unclear. The purpose of this study was to investigate the use of a realistic 3D micro-CT interactive visualization computer model to teach paranasal sinus anatomy in a laboratory setting during pre-clinical medical training. Year 1 (n=79) and Year 2 (n=59) medical students undertook self-directed activities focused on paranasal sinus anatomy in one of two laboratories (traditional laboratory and 3D model). All participants completed pre and posttests before and after the laboratory session. Results of regression analyses predicting post-laboratory knowledge indicate that, when students were inexperienced with the 3D computer technology, use of the model was detrimental to learning for students with greater prior knowledge of the relevant anatomy (P<0.05). For participants experienced with the 3D computer technology, however, the use of the model was detrimental for students with less prior knowledge of the relevant anatomy (P<0.001). These results emphasize that several factors need to be considered in the design and effective implementation of such models in the classroom. Under the right conditions, the 3D model is equal to traditional laboratory resources when used as a learning tool. This paper discusses the importance of preparatory training for students and the technical consideration necessary to successfully integrate such models into medical anatomical curricula.

A general approach to optimizing tumor treating fields therapy.

e14668 Background: Tumor Treating Fields (TTFields) are alternating electric fields used to non-invasively treat cancer. TTFields are delivered via transducer arrays placed on the skin close to the tumor. Post-hoc analysis [1] has shown that delivering higher field power to the tumor and increasing usage (percent of time patient is actively treated) improve patient survival. Thus, optimizing the position of arrays to maximize TTFields power at the tumor could improve survival. At the same time, minimizing the array area to maximize patient comfort and consequently maximizing usage is also likely to improve survival. However, optimizing TTFields delivery is non-trivial since the field distribution is influenced by array positioning and geometry, the anatomy of the patient and the heterogeneous electric properties of different tissues. Here we present a general approach to optimizing Tumor Treating Fields using numerical simulations. Methods: Delivery of TTFields to the brains, lungs and abdomens of realistic computational models was investigated. The effect of the transducer array size and position on the field distribution within the phantoms was analyzed, and an approach for optimizing TTFields delivery developed. Results: Field power is generally highest in the region between the arrays, with larger arrays generally delivering higher field power. Anatomical features such as bones, the spine or a resection cavity significantly influence the field within this region. A general approach to optimizing TTFields delivery is: Maximize field power by using the largest arrays possible. To maximize patient comfort, array size are chose so that significant portions of the skin in the region of disease are not covered by the arrays. Place virtual arrays on a realistic computational model of the patient such that the tumor is located between them and simulate TTFields delivery to the patient. Apply an iterative algorithm to shift the arrays around their initial positions until field power in the tumor bed is maximized. Conclusions: We have developed a general approach to optimizing delivery of TTFields to the tumor. Effective TTFields treatment planning is expected to improve patient outcome. [1] Ballo et. al., submitted to RED Journal 2018.

Modeling of individual differences in driver behavior

Computational transportation is a scientific discipline which uses traffic flow simulation for intervention design and analysis. Realistic traffic flow simulation depends on realistic computational modeling of individual agents such as drivers. Whereas, realistic agent model relies on realistic modeling of microscopic driver behaviors. IDM and MOBIL are considered de-facto car-following and lane change models respectively. All the prominent microscopic models have been developed with engineering perspective i.e. to reproduce perfect driving behavior. Whereas human driving behavior exhibit individual difference and is prone to risks and errors. This study focuses on development of a personality-based model of driver behavior. The parameters that have been modeled to represent driving preferences have been identified. In their existing forms, model parameters could be assigned arbitrary values from a prescribed range to define different driver profiles. This way, theoretically, infinite driver profiles could be created, many of which does not exist in real. Whereas, literature of traffic psychology suggests that there are few prevalent classes of drivers which exhibit certain behavioral patterns. These classes are characterized with the help of human personality. In proposed study, a relationship between personality traits and model parameters have been modeled. This enhancement may reproduce individual differences in driving behaviors.

VoroMQA web server for assessing three-dimensional structures of proteins and protein complexes.

The VoroMQA (Voronoi tessellation-based Model Quality Assessment) web server is dedicated to the estimation of protein structure quality, a common step in selecting realistic and most accurate computational models and in validating experimental structures. As an input, the VoroMQA web server accepts one or more protein structures in PDB format. Input structures may be either monomeric proteins or multimeric protein complexes. For every input structure, the server provides both global and local (per-residue) scores. Visualization of the local scores along the protein chain is enhanced by providing secondary structure assignment and information on solvent accessibility. A unique feature of the VoroMQA server is the ability to directly assess protein-protein interaction interfaces. If this type of assessment is requested, the web server provides interface quality scores, interface energy estimates, and local scores for residues involved in inter-chain interfaces. VoroMQA, the underlying method of the web server, was extensively tested in recent community-wide CASP and CAPRI experiments. During these experiments VoroMQA showed outstanding performance both in model selection and in estimation of accuracy of local structural regions. The VoroMQA web server is available at http://bioinformatics.ibt.lt/wtsam/voromqa.

Quasiperiodic rhythms of the inferior olive.

Inferior olivary activity causes both short-term and long-term changes in cerebellar output underlying motor performance and motor learning. Many of its neurons engage in coherent subthreshold oscillations and are extensively coupled via gap junctions. Studies in reduced preparations suggest that these properties promote rhythmic, synchronized output. However, the interaction of these properties with torrential synaptic inputs in awake behaving animals is not well understood. Here we combine electrophysiological recordings in awake mice with a realistic tissue-scale computational model of the inferior olive to study the relative impact of intrinsic and extrinsic mechanisms governing its activity. Our data and model suggest that if subthreshold oscillations are present in the awake state, the period of these oscillations will be transient and variable. Accordingly, by using different temporal patterns of sensory stimulation, we found that complex spike rhythmicity was readily evoked but limited to short intervals of no more than a few hundred milliseconds and that the periodicity of this rhythmic activity was not fixed but dynamically related to the synaptic input to the inferior olive as well as to motor output. In contrast, in the long-term, the average olivary spiking activity was not affected by the strength and duration of the sensory stimulation, while the level of gap junctional coupling determined the stiffness of the rhythmic activity in the olivary network during its dynamic response to sensory modulation. Thus, interactions between intrinsic properties and extrinsic inputs can explain the variations of spiking activity of olivary neurons, providing a temporal framework for the creation of both the short-term and long-term changes in cerebellar output.

Black hole as a model of computation

Abstract This paper focuses on an alternative, more physically realistic model of computation than Etesi and Nemeti’s relativistic computer in a Malament-Hogarth spacetime (2002) that uses the black hole itself combined with an external observer equipped with a source and some method of measurement of gamma-rays, as opposed to sending a classical computer into a black hole and exploiting the properties of the spacetime to achieve hypercomputation. The source of output, Hawking radiation, is considered along with the constraints imposed by the holographic principle which limit the number of degrees of freedom in the system and consequently the maximum usable information. The Bekenstein-Hawking entropy is converted from the traditional form in terms of the horizon area to that of the Shannon entropy, establishing an analogy between the physical and computational perspectives of the system. Next examples are considered to establish the approximate order of the necessary excitation energy and the resulting gamma-ray interactions which form the input from the observer. Finally, the Turing completeness of the language for this model is considered through a simulation of the Turing machine. The goal is to introduce a model of computation that can later be used to study the relationship between computability and physical systems.