Neuronal modeling of patch-clamp data is based on approximations which are valid under specific assumptions regarding cell properties and morphology. Certain cells, which show a biexponential capacitance transient decay, can be modeled with a two-compartment model. However, for parameter-extraction in such a model, approximations are required regarding the relative sizes of the various model parameters. These approximations apply to certain cell types or experimental conditions and are not valid in the general case. In this paper, we present a general method for the extraction of the parameters in a two-compartment model without assumptions regarding the relative size of the parameters. All the passive electrical parameters of the two-compartment model are derived in terms of the available experimental data.
Ultrasonic transducers are a key element that governs the performances of both generating and receiving ultrasound in an ultrasonic measurement system. Electrical impedance is a parameter sensitive to the environment of the transducer; it contains information about the transducer but also on the medium in which it is immersed. Several practical applications exploit this property. For this study, the model is implemented with the VHDL-AMS behavioral language. The simulations approaches presented in this work are based on the electrical Redwood model and its parameters are deduced from the transducer electroacoustic characteristics.
POWER SYSTEM PROBLEMS IN TEACHING CONTROL THEORY ON SIMULINKijctcm
This experiment demonstrates to engineering students that control system and power system theory are not orthogonal, but highly interrelated. It introduces a real-world power system problem to enhance time domain State Space Modelling (SSM) skills of students. It also shows how power quality is affected with real-world scenarios. Power system was modeled in State Space by following its circuit topology in a bottom-up fashion. At two different time instances of the power generator sinusoidal wave, the transmission line was switched on. Fourier transform was used to analyze resulting line currents. It validated the harmonic components, as expected, from power system theory. Students understood the effects of switching transients at various times on supply voltage sinusoid within control theory and learned time domain analysis. They were surveyed to gauge their perception of the project. Results from a before/after assessment analyzed usingT-Tests showed a statistically significant enhanced learning in SSM.
Power System Problems in Teaching Control Theory on Simulinkijctcm
This experiment demonstrates to engineering students that control system and power system theory are not orthogonal, but highly interrelated. It introduces a real-world power system problem to enhance time domain State Space Modelling (SSM) skills of students. It also shows how power quality is affected with real-world scenarios. Power system was modeled in State Space by following its circuit topology in a bottom-up fashion. At two different time instances of the power generator sinusoidal wave, the transmission line was switched on. Fourier transform was used to analyze resulting line currents. It validated the harmonic components, as expected, from power system theory. Students understood the effects of switching transients at various times on supply voltage sinusoid within control theory and learned time domain analysis. They were surveyed to gauge their perception of the project. Results from a before/after assessment analyzed usingT-Tests showed a statistically significant enhanced learning in SSM.
Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm Yayah Zakaria
The objective of this paper is the PEM fuel cell impedance model parameters identification. This work is a part of a larger work which is the diagnosis of the fuel cell which deals with the optimization and the parameters identification of the impedance complex model of the Nexa Ballard 1200 PEM fuel cell. The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands. In fact, the frequency spectrum is divided into bands according to the behavior of the fuel cell. So, this work is considered a first in the field of impedance spectroscopy So, this work is considered a first in the field of impedance spectroscopy. Indeed, the identification using genetic algorithm requires experimental measures of the fuel cell impedance to optimize and identify the impedance model parameters values. This method is characterized by a good precision compared to the numeric methods. The obtained results prove the effectiveness of this approach.
Fuel Cell Impedance Model Parameters Optimization using a Genetic AlgorithmIJECEIAES
The objective of this paper is the PEM fuel cell impedance model parameters identification. This work is a part of a larger work which is the diagnosis of the fuel cell which deals with the optimization and the parameters identification of the impedance complex model of the Nexa Ballard 1200 W PEM fuel cell. The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands. In fact, the frequency spectrum is divided into bands according to the behavior of the fuel cell. So, this work is considered a first in the field of impedance spectroscopy So, this work is considered a first in the field of impedance spectroscopy. Indeed, the identification using genetic algorithm requires experimental measures of the fuel cell impedance to optimize and identify the impedance model parameters values. This method is characterized by a good precision compared to the numeric methods. The obtained results prove the effectiveness of this approach.
Ultrasonic transducers are a key element that governs the performances of both generating and receiving ultrasound in an ultrasonic measurement system. Electrical impedance is a parameter sensitive to the environment of the transducer; it contains information about the transducer but also on the medium in which it is immersed. Several practical applications exploit this property. For this study, the model is implemented with the VHDL-AMS behavioral language. The simulations approaches presented in this work are based on the electrical Redwood model and its parameters are deduced from the transducer electroacoustic characteristics.
POWER SYSTEM PROBLEMS IN TEACHING CONTROL THEORY ON SIMULINKijctcm
This experiment demonstrates to engineering students that control system and power system theory are not orthogonal, but highly interrelated. It introduces a real-world power system problem to enhance time domain State Space Modelling (SSM) skills of students. It also shows how power quality is affected with real-world scenarios. Power system was modeled in State Space by following its circuit topology in a bottom-up fashion. At two different time instances of the power generator sinusoidal wave, the transmission line was switched on. Fourier transform was used to analyze resulting line currents. It validated the harmonic components, as expected, from power system theory. Students understood the effects of switching transients at various times on supply voltage sinusoid within control theory and learned time domain analysis. They were surveyed to gauge their perception of the project. Results from a before/after assessment analyzed usingT-Tests showed a statistically significant enhanced learning in SSM.
Power System Problems in Teaching Control Theory on Simulinkijctcm
This experiment demonstrates to engineering students that control system and power system theory are not orthogonal, but highly interrelated. It introduces a real-world power system problem to enhance time domain State Space Modelling (SSM) skills of students. It also shows how power quality is affected with real-world scenarios. Power system was modeled in State Space by following its circuit topology in a bottom-up fashion. At two different time instances of the power generator sinusoidal wave, the transmission line was switched on. Fourier transform was used to analyze resulting line currents. It validated the harmonic components, as expected, from power system theory. Students understood the effects of switching transients at various times on supply voltage sinusoid within control theory and learned time domain analysis. They were surveyed to gauge their perception of the project. Results from a before/after assessment analyzed usingT-Tests showed a statistically significant enhanced learning in SSM.
Fuel Cell Impedance Model Parameters Optimization using a Genetic Algorithm Yayah Zakaria
The objective of this paper is the PEM fuel cell impedance model parameters identification. This work is a part of a larger work which is the diagnosis of the fuel cell which deals with the optimization and the parameters identification of the impedance complex model of the Nexa Ballard 1200 PEM fuel cell. The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands. In fact, the frequency spectrum is divided into bands according to the behavior of the fuel cell. So, this work is considered a first in the field of impedance spectroscopy So, this work is considered a first in the field of impedance spectroscopy. Indeed, the identification using genetic algorithm requires experimental measures of the fuel cell impedance to optimize and identify the impedance model parameters values. This method is characterized by a good precision compared to the numeric methods. The obtained results prove the effectiveness of this approach.
Fuel Cell Impedance Model Parameters Optimization using a Genetic AlgorithmIJECEIAES
The objective of this paper is the PEM fuel cell impedance model parameters identification. This work is a part of a larger work which is the diagnosis of the fuel cell which deals with the optimization and the parameters identification of the impedance complex model of the Nexa Ballard 1200 W PEM fuel cell. The method used for the identification is a sample genetic algorithm and the proposed impedance model is based on electric parameters, which will be found from a sweeping of well determined frequency bands. In fact, the frequency spectrum is divided into bands according to the behavior of the fuel cell. So, this work is considered a first in the field of impedance spectroscopy So, this work is considered a first in the field of impedance spectroscopy. Indeed, the identification using genetic algorithm requires experimental measures of the fuel cell impedance to optimize and identify the impedance model parameters values. This method is characterized by a good precision compared to the numeric methods. The obtained results prove the effectiveness of this approach.
The Need for Enhanced Power System Modelling Techniques & Simulation Tools Power System Operation
The Need for Enhanced Power System Modelling Techniques & Simulation Tools The Need for Enhanced Power System Modelling Techniques The Need for Enhanced Power System Modelling Techniques & Simulation Tools The Need for Enhanced Power System Modelling Techniques & Simulation Tools & Simulation Tools
Fault identification in transformer windingeSAT Journals
Abstract Transformer fault detection during impulse tests has always been an important topic in power engineering. Transformers connected to overhead lines are often prone to lightning strikes and resulting winding damage. For assessment of their insulation strength against such impulse stresses they are usually subjected to lightning impulse tests after assembly. In the case of a fault inside the winding, the shape of the winding current changes as compared to that of a healthy winding. The pattern of the fault current depends on the type of fault and its location along the length of the winding. This paper investigates Conventional procedures of fault diagnosis involved visual examination of the oscillographic records in time-domain and also applying the Fast Fourier Transform (FFT) algorithm to analyze the transformer ‘fingerprint’ in the frequency-domain. Actually, this method is straight forward technique for interpretation of minor impulse faults in transformers. Also Simulation results obtained for a range of distribution transformer digital models are presented to illustrate the ability of this approach to classify insulation failures during impulse testing. The proposed method has been applied for impulse fault analysis of a analog model of a 12kVA single phase transformer. Keywords: transformer; Impulse test; Fault; FFT
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
EFFECTIVE PEEC MODELING OF TRANSMISSION LINES STRUCTURES USING A SELECTIVE ME...EEIJ journal
The transmission lines structures are quite common in the system of electromagnetic compatibility (EMC)
analysis. The increasing complexities of physical structures make electromagnetic modeling an
increasingly tough task, and computational efficiency is desirable. In this paper, a novel selective mesh
approach is presented for partial element equivalent circuit (PEEC) modeling where intense coupling parts
are meshed while the remaining parts are eliminated. With the proposed approach, the meshed ground
plane is dependent on the length and height of the above transmission lines. Relevant compact formulae for
determining mesh boundaries are deduced, and a procedure of general mesh generation is also given. A
numerical example is presented, and a validation check is accomplished, showing that the approach leads
to a significant reduction in unknowns and thus computation time and consumed memories, while
preserving the sufficient precision. This approach is especially useful for modeling the electromagnetic
coupling of transmission lines and reference ground, and it may also be beneficial for other equivalent
circuit modeling techniques.
Dynamic Performance of Distance Relayson Series Compensated Transmission Line...Premier Publishers
Series compensation is installed in power system networks to increase power transfer capacity, improve the system stability, reduce system losses, improve voltage regulation and for achieving flexible power flow control. Distance relays are widely used as main or backup protection of transmission lines including series-compensated transmission lines. The performance of conventional distance relays is affected by series capacitors and cause certain protection issues. This paper briefly discusses the problems like voltage inversion, current inversion, overreach and under reach during the fault conditions specific to series compensated lines. The behavior of capacitor protection techniques is discussed with simulations performed using Real Time Digital Simulator (RTDS) simulator for a typical 400 kV system having series compensation. The analysis is based on Transmission Line fault simulations, internal and external to the 400-transmission line where the Fixed Series Compensation (FSC)is installed.
Ion Channel Simulations for Potassium, Sodium, Calcium, and Chloride Channels...Iowa State University
Computer simulations of realistic ion channel structures have always been challenging and a subject of rigorous study. Simulations based on continuum electrostatics have proven to be computationally cheap and reasonably accurate in predicting a channel's behavior. In this paper we discuss the use of a device simulator, SILVACO, to build a solid-state model for KcsA channel and study its steady-state response. SILVACO is a well-established program, typically used by electrical engineers to simulate the process flow and electrical characteristics of solid-state devices. By employing this simulation program, we have presented an alternative computing platform for performing ion channel simulations, besides the known methods of writing codes in programming languages. With the ease of varying the different parameters in the channel's vestibule and the ability of incorporating surface charges, we have shown the wide-ranging possibilities of using a device simulator for ion channel simulations. Our simulated results closely agree with the experimental data, validating our model.
https://www.sciencedirect.com/science/article/abs/pii/S0169260706002276
In this paper a novel control technique for switching-frequency-modulated switch-mode power converters (SMPC) operating in discontinuous conduction mode is proposed. The use of the technique leads to significant reduction in peak-to-peak output voltage and peak currents increased due to straightforward application of switching frequency modulation (SFM). The technique is based on hybrid modulation scheme in which both switching frequency and duty ratio are modulated simultaneously by the same modulation signal. Theoretical analysis and experimental verification of the proposed technique are presented in details. Both computer simulations and experiments show that switching-frequency-modulated SMPC with the proposed control technique in comparison to SMPC without SFM has appreaciably lower conducted electromagnetic emissions, at the cost of slightly increased peak-to-peak output voltage and peak currents.
Permanent Fault Location in Distribution System Using Phasor Measurement Unit...IJECEIAES
This paper proposes a new method for locating high impedance fault in distribution systems using phasor measurement units (PMUs) installed at certain locations of the system. To implement this algorithm, at first a new method is suggested for the placement of PMUs. Taking information from the units, voltage and current of the entire distribution system are calculated. Then, the two buses in which the fault has been occurred is determined, and location and type of the fault are identified. The main characteristics of the proposed method are: the use of distributed parameter line model in phase domain, considering the presence of literals, and high precision in calculating the high impedance fault location. The results obtained from simulations in EMTP-RV and MATLAB software indicate high accuracy and independence of the proposed method from the fault type, fault location and fault resistance compared to previous methods, so that the maximum observed error was less than 0.15%.
In this review, we focus on the hardware and software technologies used for the purpose of gastrointestinal tract monitoring in a safe and comfortable manner. We review the FDA guidelines for ingestible wireless telemetric medical devices, and the features incorporated in capsule systems such as microrobotics, closed-loop feedback, physiological sensing, nerve stimulation, sampling and delivery, panoramic imaging and rapid reading software. Both experimental and commercialized capsule systems with their sensors, devices, and circuits are discussed. Furthermore, the advances in biocompatible materials and batteries, edible electronics and alternative energy sources for ingestible capsule systems are presented. The clinical studies are reviewed to examine the safety and effectiveness of capsule procedures and the current challenges and outlook are summarized.
Dylan Miley*, Leonardo Bertoncello Machado*, Calvin Condo, Albert E. Jergens, Kyoung-Jin Yoon, Santosh Pandey, “Video Capsule Endoscopy and Ingestible Electronics: Emerging Trends in Sensors, Circuits, Materials, Telemetry, Optics, and Rapid Reading Software“, Advanced Devices & Instrumentation, (Science Partner Journal), Volume 2021, Article ID 9854040, 2021. https://spj.science.org/doi/10.34133/2021/9854040?permanently=true
https://doi.org/10.34133/2021/9854040
Antimicrobial resistance studies in low-cost microfluidic chipsIowa State University
By utilizing a low-cost engineering tool, we have created a microfluidic platform to study bacteria at the single cell level, allowing us to unlock insights into microbial physiology and genetics that would otherwise not be possible. The platform is composed of 3D devices made of adhesive tapes, an agarose membrane as the resting substrate, a temperature-controlled environmental chamber, and an autofocusing module. With this technology, we have been able to observe Escherichia coli morphological changes during ampicillin exposure and measure the minimum inhibitory concentration of the antibiotic. Additionally, we have been able to use CRISPR interference (CRISPRi) to evaluate gene regulation in a concentration gradient. Overall, our microfluidic platform provides a powerful, low-cost tool to uncover new genetic determinants of antibiotic susceptibility and assess the long-term effectiveness of antibiotics in bacterial cultures.
Adhesive Tape Microfluidics with an Autofocusing Module That Incorporates CRISPR Interference: Applications to Long-Term Bacterial Antibiotic Studies, Taejoon Kong, Nicholas Backes, Upender Kalwa, Christopher Legner, Gregory J. Phillips, and Santosh Pandey, ACS Sensors 2019 4 (10), 2638-2645
https://doi.org/10.1021/acssensors.9b01031
https://pubs.acs.org/doi/full/10.1021/acssensors.9b01031
The Need for Enhanced Power System Modelling Techniques & Simulation Tools Power System Operation
The Need for Enhanced Power System Modelling Techniques & Simulation Tools The Need for Enhanced Power System Modelling Techniques The Need for Enhanced Power System Modelling Techniques & Simulation Tools The Need for Enhanced Power System Modelling Techniques & Simulation Tools & Simulation Tools
Fault identification in transformer windingeSAT Journals
Abstract Transformer fault detection during impulse tests has always been an important topic in power engineering. Transformers connected to overhead lines are often prone to lightning strikes and resulting winding damage. For assessment of their insulation strength against such impulse stresses they are usually subjected to lightning impulse tests after assembly. In the case of a fault inside the winding, the shape of the winding current changes as compared to that of a healthy winding. The pattern of the fault current depends on the type of fault and its location along the length of the winding. This paper investigates Conventional procedures of fault diagnosis involved visual examination of the oscillographic records in time-domain and also applying the Fast Fourier Transform (FFT) algorithm to analyze the transformer ‘fingerprint’ in the frequency-domain. Actually, this method is straight forward technique for interpretation of minor impulse faults in transformers. Also Simulation results obtained for a range of distribution transformer digital models are presented to illustrate the ability of this approach to classify insulation failures during impulse testing. The proposed method has been applied for impulse fault analysis of a analog model of a 12kVA single phase transformer. Keywords: transformer; Impulse test; Fault; FFT
IJRET : International Journal of Research in Engineering and Technology is an international peer reviewed, online journal published by eSAT Publishing House for the enhancement of research in various disciplines of Engineering and Technology. The aim and scope of the journal is to provide an academic medium and an important reference for the advancement and dissemination of research results that support high-level learning, teaching and research in the fields of Engineering and Technology. We bring together Scientists, Academician, Field Engineers, Scholars and Students of related fields of Engineering and Technology.
EFFECTIVE PEEC MODELING OF TRANSMISSION LINES STRUCTURES USING A SELECTIVE ME...EEIJ journal
The transmission lines structures are quite common in the system of electromagnetic compatibility (EMC)
analysis. The increasing complexities of physical structures make electromagnetic modeling an
increasingly tough task, and computational efficiency is desirable. In this paper, a novel selective mesh
approach is presented for partial element equivalent circuit (PEEC) modeling where intense coupling parts
are meshed while the remaining parts are eliminated. With the proposed approach, the meshed ground
plane is dependent on the length and height of the above transmission lines. Relevant compact formulae for
determining mesh boundaries are deduced, and a procedure of general mesh generation is also given. A
numerical example is presented, and a validation check is accomplished, showing that the approach leads
to a significant reduction in unknowns and thus computation time and consumed memories, while
preserving the sufficient precision. This approach is especially useful for modeling the electromagnetic
coupling of transmission lines and reference ground, and it may also be beneficial for other equivalent
circuit modeling techniques.
Dynamic Performance of Distance Relayson Series Compensated Transmission Line...Premier Publishers
Series compensation is installed in power system networks to increase power transfer capacity, improve the system stability, reduce system losses, improve voltage regulation and for achieving flexible power flow control. Distance relays are widely used as main or backup protection of transmission lines including series-compensated transmission lines. The performance of conventional distance relays is affected by series capacitors and cause certain protection issues. This paper briefly discusses the problems like voltage inversion, current inversion, overreach and under reach during the fault conditions specific to series compensated lines. The behavior of capacitor protection techniques is discussed with simulations performed using Real Time Digital Simulator (RTDS) simulator for a typical 400 kV system having series compensation. The analysis is based on Transmission Line fault simulations, internal and external to the 400-transmission line where the Fixed Series Compensation (FSC)is installed.
Ion Channel Simulations for Potassium, Sodium, Calcium, and Chloride Channels...Iowa State University
Computer simulations of realistic ion channel structures have always been challenging and a subject of rigorous study. Simulations based on continuum electrostatics have proven to be computationally cheap and reasonably accurate in predicting a channel's behavior. In this paper we discuss the use of a device simulator, SILVACO, to build a solid-state model for KcsA channel and study its steady-state response. SILVACO is a well-established program, typically used by electrical engineers to simulate the process flow and electrical characteristics of solid-state devices. By employing this simulation program, we have presented an alternative computing platform for performing ion channel simulations, besides the known methods of writing codes in programming languages. With the ease of varying the different parameters in the channel's vestibule and the ability of incorporating surface charges, we have shown the wide-ranging possibilities of using a device simulator for ion channel simulations. Our simulated results closely agree with the experimental data, validating our model.
https://www.sciencedirect.com/science/article/abs/pii/S0169260706002276
In this paper a novel control technique for switching-frequency-modulated switch-mode power converters (SMPC) operating in discontinuous conduction mode is proposed. The use of the technique leads to significant reduction in peak-to-peak output voltage and peak currents increased due to straightforward application of switching frequency modulation (SFM). The technique is based on hybrid modulation scheme in which both switching frequency and duty ratio are modulated simultaneously by the same modulation signal. Theoretical analysis and experimental verification of the proposed technique are presented in details. Both computer simulations and experiments show that switching-frequency-modulated SMPC with the proposed control technique in comparison to SMPC without SFM has appreaciably lower conducted electromagnetic emissions, at the cost of slightly increased peak-to-peak output voltage and peak currents.
Permanent Fault Location in Distribution System Using Phasor Measurement Unit...IJECEIAES
This paper proposes a new method for locating high impedance fault in distribution systems using phasor measurement units (PMUs) installed at certain locations of the system. To implement this algorithm, at first a new method is suggested for the placement of PMUs. Taking information from the units, voltage and current of the entire distribution system are calculated. Then, the two buses in which the fault has been occurred is determined, and location and type of the fault are identified. The main characteristics of the proposed method are: the use of distributed parameter line model in phase domain, considering the presence of literals, and high precision in calculating the high impedance fault location. The results obtained from simulations in EMTP-RV and MATLAB software indicate high accuracy and independence of the proposed method from the fault type, fault location and fault resistance compared to previous methods, so that the maximum observed error was less than 0.15%.
Similar to Two compartment model for Patch Clamp (20)
In this review, we focus on the hardware and software technologies used for the purpose of gastrointestinal tract monitoring in a safe and comfortable manner. We review the FDA guidelines for ingestible wireless telemetric medical devices, and the features incorporated in capsule systems such as microrobotics, closed-loop feedback, physiological sensing, nerve stimulation, sampling and delivery, panoramic imaging and rapid reading software. Both experimental and commercialized capsule systems with their sensors, devices, and circuits are discussed. Furthermore, the advances in biocompatible materials and batteries, edible electronics and alternative energy sources for ingestible capsule systems are presented. The clinical studies are reviewed to examine the safety and effectiveness of capsule procedures and the current challenges and outlook are summarized.
Dylan Miley*, Leonardo Bertoncello Machado*, Calvin Condo, Albert E. Jergens, Kyoung-Jin Yoon, Santosh Pandey, “Video Capsule Endoscopy and Ingestible Electronics: Emerging Trends in Sensors, Circuits, Materials, Telemetry, Optics, and Rapid Reading Software“, Advanced Devices & Instrumentation, (Science Partner Journal), Volume 2021, Article ID 9854040, 2021. https://spj.science.org/doi/10.34133/2021/9854040?permanently=true
https://doi.org/10.34133/2021/9854040
Antimicrobial resistance studies in low-cost microfluidic chipsIowa State University
By utilizing a low-cost engineering tool, we have created a microfluidic platform to study bacteria at the single cell level, allowing us to unlock insights into microbial physiology and genetics that would otherwise not be possible. The platform is composed of 3D devices made of adhesive tapes, an agarose membrane as the resting substrate, a temperature-controlled environmental chamber, and an autofocusing module. With this technology, we have been able to observe Escherichia coli morphological changes during ampicillin exposure and measure the minimum inhibitory concentration of the antibiotic. Additionally, we have been able to use CRISPR interference (CRISPRi) to evaluate gene regulation in a concentration gradient. Overall, our microfluidic platform provides a powerful, low-cost tool to uncover new genetic determinants of antibiotic susceptibility and assess the long-term effectiveness of antibiotics in bacterial cultures.
Adhesive Tape Microfluidics with an Autofocusing Module That Incorporates CRISPR Interference: Applications to Long-Term Bacterial Antibiotic Studies, Taejoon Kong, Nicholas Backes, Upender Kalwa, Christopher Legner, Gregory J. Phillips, and Santosh Pandey, ACS Sensors 2019 4 (10), 2638-2645
https://doi.org/10.1021/acssensors.9b01031
https://pubs.acs.org/doi/full/10.1021/acssensors.9b01031
Flexible chip for long-term antimicrobial resistance experimentsIowa State University
By creating a low-cost, three-dimensional microfluidic platform, we have improved our ability to study bacterial cells at the single cell level. This technology allows for prolonged culturing of bacteria in a controlled environment, as well as high resolution observation and imaging of cells. We have used this platform to examine morphological changes in Escherichia coli exposed to ampicillin and to quantify the minimum inhibitory concentration of the antibiotic. Additionally, we demonstrated the potential for precise gene regulation using CRISPR interference (CRISPRi) in a concentration gradient. Ultimately, this engineering tool should be useful for uncovering new genetic factors that influence antibiotic susceptibility and evaluating the long-term effectiveness of antibiotics.
Adhesive Tape Microfluidics with an Autofocusing Module That Incorporates CRISPR Interference: Applications to Long-Term Bacterial Antibiotic Studies, Taejoon Kong, Nicholas Backes, Upender Kalwa, Christopher Legner, Gregory J. Phillips, and Santosh Pandey, ACS Sensors 2019 4 (10), 2638-2645
https://doi.org/10.1021/acssensors.9b01031
https://pubs.acs.org/doi/full/10.1021/acssensors.9b01031
In this paper, we explore the use of microfluidic paper-based analytical devices (PADs) to study the behavior of Caenorhabditis elegans. We show how these devices can be fabricated on paper and plastic substrates, as well as how to load, visualize, and transfer single and multiple nematodes. We also demonstrate the use of anthelmintic drug, levamisole, to perform chemical testing on C. elegans. Furthermore, we provide a custom program that is able to recognize individual worms on the PADs in real-time and extract their locomotion parameters. This combination of PADs and the nematode tracking program creates a low-cost, easy-to-fabricate imaging and screening assay that is superior to standard agarose plates or polymeric microfluidic devices for non-microfluidic, nematode laboratories.
Zach Njus, Taejoon Kong, Upender Kalwa, Christopher Legner, Matthew Weinstein, Shawn Flanigan, Jenifer Saldanha, and Santosh Pandey, "Flexible and disposable paper- and plastic-based gel micropads for nematode handling, imaging, and chemical testing", APL Bioengineering 1, 016102 (2017)
https://doi.org/10.1063/1.5005829
https://aip.scitation.org/doi/10.1063/1.5005829
The resistance of parasites to existing drugs and the availability of better technology platforms has driven the discovery of new drugs. Microfluidic devices have been used to facilitate faster screening of compounds, controlled sampling/sorting of whole animals, and automated behavioral pattern recognition. In most cases, drug effects on small creatures (e.g., Caenorhabditis elegans) are measuredelegant by a single parameter such as worm velocity or stroke frequency. We present a multi-parameter extraction method to characterize modes of paralysis in C. elegans over a longer duration. This was done using a microfluidic device featuring real-time imaging, exposing worms to four anthelmintic drugs at EC75, where 75% of the worm population is affected. We monitored the worms' behavior with metrics such as curls per second, types of paralyzation, mode frequency, and number/duration of active/immobilization periods. Differences were observed in how the worms paralyzed in the various drug environments at equivalent concentrations. This study highlights the importance of assessing drug effects on small animals with multiple parameters, measured at regular intervals over a prolonged period, to accurately detect resistance and adaptability in chemical environments.
Roy Lycke, Archana Parashar, and Santosh Pandey, "Microfluidics-enabled method to identify modes of Caenorhabditis elegans paralysis in four anthelmintics", Biomicrofluidics 7, 064103 (2013).
https://doi.org/10.1063/1.4829777
https://aip.scitation.org/doi/10.1063/1.4829777
Melanoma is a particularly dangerous type of skin cancer and is hard to treat in its later stages. Therefore, early detection is key in reducing mortality rates. In order to assist dermatologists in doing this, computer-aided systems have been designed for desktop computers. However, there is a desire for the development of mobile, at-home diagnostics for melanoma risk assessment. Here, we introduce a smartphone application that captures images and extracts ABCD features to classify skin lesions as either malignant or benign. The algorithms used are adaptive to make the process light and user-friendly, as well as reliable in diagnosis. Images can be taken with the phone's camera or imported from public datasets. The entire process of taking the image, performing preprocessing, segmentation and classification is completed on an Android smartphone in a short time. Our application is evaluated on a dataset of 200 images, and achieved either comparable or better performance metrics than other methods. Additionally, it is easy-to-download and easy-to-navigate for the user, which is important for the widespread use of such diagnostics.
Kalwa, U.; Legner, C.; Kong, T.; Pandey, S. Skin Cancer Diagnostics with an All-Inclusive Smartphone Application. Symmetry 2019, 11, 790. https://doi.org/10.3390/sym11060790
https://www.mdpi.com/2073-8994/11/6/790
A CMOS biosensor with a folded floating-gate is created to detect charged biochemical molecules. It contains a FET, a control-gate and a sensing area. The floating-gate spans the whole device, allowing the sensing area to be placed on top of the FET, resulting in a decrease of the device's total area. The device is sensitive to the polarity and quantity of charged poly amino acids and could be used for electronic recognition of temporal and spatial migration of charges, such as in biological phenomena.
B. Chen, A. Parashar and S. Pandey, "Folded Floating-Gate CMOS Biosensor for the Detection of Charged Biochemical Molecules," IEEE Sensors Journal, vol. 11, no. 11, pp. 2906-2910, Nov. 2011, doi: 10.1109/JSEN.2011.2149514.
https://ieeexplore.ieee.org/document/5762313
We attempt to offer an innovative solution to the issues of long response times, large volumes of actuation fluid, and external control circuitry that have been associated with past approaches in creating switches in paper microfluidics. Our method consists of a device created from chromatography paper and featuring folds which, when selectively wetted with an actuation fluid, will either raise or lower the actuator's tip and thus engage or break the desired fluidic connections. As a result, response time is drastically reduced (2 seconds) and the volume of actuation fluid consumed is extremely small (4 microliters). We have tested this approach with six switch configurations, ranging from single-pole single-throw (normally OFF and normally ON) to single-pole double-throw (with single and double break). We further demonstrate its potential with a colorimetric assay involving six actuators in parallel, which can detect the presence of three analytes (glucose, protein, and nitrite) in artificial saliva. Finally, this work brings in the concept of origami to paper microfluidics, combining multiple-fold geometries for programmable switching of fluidic connections.
"A fast, reconfigurable flow switch for paper
microfluidics based on selective wetting of folded
paper actuator strips",
Lab on Chip, 2017, 17, 3621
A method to create smart and flexible switches for the regulation of liquid flow across multiple channels is essential in paper microfluidics. Prior approaches are hampered by long response times, high actuation fluid volumes, and external control circuitry. To diminish these problems, we designed a distinctive actuator device fashioned entirely from chromatography paper and featuring folds. The fold can be selectively wetted by an actuation fluid at either the crest or trough, resulting in the raising or lowering of the actuator's tip and thus bringing about the connection or severance of fluidic channels. This actuation principle reduces the response time to only two seconds and the amount of fluid used to merely four microliters. We have also added six switch arrangements which can be divided into single-pole single-throw (normally OFF and normally ON) and single-pole double-throw (with single and double break). The utilization of six actuators in a parallel system allowed us to construct an autonomous colorimetric assay for the detection of three analytes - glucose, protein, and nitrite - in artificial saliva. This study has brought the concept of origami to paper microfluidics, allowing the use of multiple-fold geometries for the programmable switching of fluidic connections.
Taejoon Kong et al, "A fast, reconfigurable flow switch for paper
microfluidics based on selective wetting of folded
paper actuator strips", Lab on Chip, 2017, 17, 3621
The transmembrane proteins known as ion channels play a role in controlling and preserving the ionic concentrations across the cell membrane. Modeling the flux of ions in and out of these channels on an atomic level is essential for understanding several neurological diseases and related pharmaceutical discoveries. Recent experimental research has provided information on the channel's physical structure which can be used to create realistic ion transport models. Different trajectories exist for the ions entering the channel, each having its own probability of occurrence. Variables that measure these trajectories are the translocation and return probabilities, average lifetime, and spectral density of the ion number fluctuations. Theoretical analysis of ion transport has been restricted to low-resolution continuum diffusion-based or kinetic-based models which do not consider important factors that have an effect on ionic conduction. This paper extends previous models by an electro-diffusion model which takes into account the effects of electric fields, energy barriers, and rate-limited association/dissociation of ions with surface charges present inside the channel. Derived from the analytical model are the survival probability and spectral density.
:Analytical Modeling of the Ion Number Fluctuations in Biological Ion Channels"
Journal of Nanoscience and Nanotechnology; Vol. 12, 2489–2495, 2012
Ion Channel Fluctuations in Transmemembrane Proteins within Cell MembranesIowa State University
The transmembrane proteins known as ion channels play a role in controlling and preserving the ionic concentrations across the cell membrane. Modeling the flux of ions in and out of these channels on an atomic level is essential for understanding several neurological diseases and related pharmaceutical discoveries. Recent experimental research has provided information on the channel's physical structure which can be used to create realistic ion transport models. Different trajectories exist for the ions entering the channel, each having its own probability of occurrence. Variables that measure these trajectories are the translocation and return probabilities, average lifetime, and spectral density of the ion number fluctuations. Theoretical analysis of ion transport has been restricted to low-resolution continuum diffusion-based or kinetic-based models which do not consider important factors that have an effect on ionic conduction. This paper extends previous models by an electro-diffusion model which takes into account the effects of electric fields, energy barriers, and rate-limited association/dissociation of ions with surface charges present inside the channel. Derived from the analytical model are the survival probability and spectral density.
This paper presents a remote monitoring tool for the objective measurement of behavioral indicators that can help in assessing the health and welfare of pigs in precision swine production. The multiparameter electronic sensor board can measure posture, gait, vocalization, and external temperature, and has been characterized through laboratory measurements and animal tests. Machine learning algorithms and decision support tools can be implemented to detect animal lameness, lethargy, pain, injury, and distress. The adoption of this technology could lead to more efficient management of farm animals, better targeting of sick animals, lower medical costs, and fewer antibiotics being used. Challenges and a road map for technology adoption are discussed, along with suggestions for future improvements.
Animals 2021, 11(9), 2665; https://doi.org/10.3390/ani11092665
We propose a remote monitoring device for measuring behavioral indicators like posture, gait, vocalization, and external temperature which can help in evaluating the health and welfare of pigs. The multiparameter electronic sensor board was tested in a laboratory and on animals. Machine learning algorithms and decision support tools can be used to detect lameness, lethargy, pain, injury, and distress. The roadmap for technology adoption, potential benefits, and further challenges are discussed. This technology could help in efficient management of farm animals, providing targeted attention to sick animals, saving medical costs, and reducing the use of antibiotics.
"Behavioral Monitoring Tool for Pig Farmers: Ear Tag Sensors,
Machine Intelligence, and Technology Adoption Roadmap",
Animals 2021, 11, 2665.
https://doi.org/10.3390/ani11092665
In this study, two sets of experiments were conducted in order to investigate the impact of static magnetic fields on the growth and ethanol production of Saccharomyces cerevisiae. The first experiment ran for 25 hours with a 2% dextrose loading rate, while the second ran for 30 hours with a 6% dextrose loading rate. The magnetic fields used were homogeneous and non-homogeneous, with strengths of 100 mT and 200 mT, respectively. The results showed that the homogenous magnetic field had no significant effect on cell growth, whilst the non-homogeneous field yielded an increase of approximately 8% in peak ethanol concentration compared to the control.
Deutmeyer, A. , Raman, R. , Murphy, P. and Pandey, S. (2011) Effect of magnetic field on the fermentation kinetics of Saccharomyces cerevisiae. Advances in Bioscience and Biotechnology, 2, 207-213.
doi: 10.4236/abb.2011.24031.
https://www.scirp.org/journal/paperinformation.aspx?paperid=6857
Magnetic field to improve fermentation kinetics for ethanol production Iowa State University
Two experiments were conducted to analyze the influence that magnetic fields have on cell growth and ethanol production during fermentation. The first experiment was conducted for 25 hours at a 2% dextrose loading rate with a homogeneous and non-homogeneous static magnetic field of 100 mT and 200 mT, respectively. The second experiment was conducted for 30 hours at a 6% dextrose loading rate with a non-homogeneous static magnetic field of 200 mT. The results indicated that homogeneous magnetic fields did not have a significant effect on the yeast cell growth. However, the non-homogeneous static magnetic field resulted in about 8% more peak ethanol concentration than the control for the 2% dextrose loading rate.
To evaluate the severity of SCN infections in the field, population densities of nematode eggs must be calculated. A method utilizing OptiPrep as a density gradient medium has been shown to provide more effective separation and recovery of extracted eggs compared to sucrose centrifugation. Furthermore, computerized processes have been established to facilitate the discernment and enumeration of eggs from processed samples. A high-resolution scanner was employed to capture static images of eggs and debris on filter papers, and a deep learning network was trained to distinguish and count the eggs from the debris. Additionally, a lensless imaging setup was established using standard components, and the egg samples were allowed to pass through a microfluidic flow chip created from double-sided adhesive tape. Holographic videos were then recorded of the eggs and debris as they moved through, which were reconstructed and processed by a custom software program to obtain the egg counts. The software programs' efficacy for egg counting was validated using soil samples obtained from two farms, and the results were compared to those obtained through manual counting.
Kalwa U, Legner C, Wlezien E, Tylka G, Pandey S (2019) New methods of removing debris and high-throughput counting of cyst nematode eggs extracted from field soil. PLOS ONE 14(10): e0223386.
https://doi.org/10.1371/journal.pone.0223386
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223386
To evaluate the level of infestation of the soybean cyst nematode (SCN), Heterodera glycines, in the field, egg population densities are determined from soil samples. Sucrose centrifugation is a common technique for separating debris from the extracted SCN eggs. We have developed a procedure, however, that employs OptiPrep as a density gradient medium, with improved extraction and recovery of the eggs compared to the sucrose centrifugation technique. Also, we have built computerized methods to automate the identification and counting of the nematode eggs from the processed samples. One approach uses a high-resolution scanner to capture static images of the eggs and debris on filter papers and a deep learning network is trained to detect and count the eggs. The second approach utilizes a lensless imaging setup with off-the-shelf components and the egg samples flow through a microfluidic flowchip. Holographic videos are taken of the passing eggs and debris, which are then reconstructed and processed by a custom software program to calculate egg counts. To evaluate the performance of the software programs, SCN-infested soils were collected from two farms and the results were compared with manual counts.
Kalwa U, Legner C, Wlezien E, Tylka G, Pandey S (2019), New methods of removing debris and high-throughput counting of cyst nematode eggs extracted from field soil. PLOS ONE 14(10): e0223386.
https://doi.org/10.1371/journal.pone.0223386
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0223386
Effect of Static Magnetic Field on Parasitic Worms in MicroChipsIowa State University
This study uses the model organism, C. elegans, to investigate its sensitivity and response to static magnetic fields. Wild-type C. elegans are put into microfluidic channels and exposed to permanent magnets for five cycles of thirty-second time intervals at field strengths ranging from 5 milli Tesla to 120 milli Tesla. Recorded and analyzed with custom software, the results of the worm's movement - the average velocity, turning and curling percentage - were compared to control experiments. Surprisingly, the results did not show any significant difference, indicating that C. elegans may not be able to sense static magnetic fields at the range of field strengths tested.
Njus, Z. , Feldmann, D. , Brien, R. , Kong, T. , Kalwa, U. and Pandey, S. (2015) Characterizing the Effect of Static Magnetic Fields on C. elegans Using Microfluidics. Advances in Bioscience and Biotechnology, 6, 583-591.
doi: 10.4236/abb.2015.69061.
https://www.scirp.org/journal/paperinformation.aspx?paperid=59434
The integration of physical and chemical sensing mechanisms found in nature has been harnessed to enable the development of wearable devices that can track the biochemical and physiological signals of the human body. Numerous consumer electronics have been developed to measure activity, posture, heart rate, respiration rate, and blood oxygen level. Sweat sampling provides a source of biomarkers that is accessible in a continuous, on-the-go, and non-invasive way, allowing for unique developments in wearable sweat sensing. This review focuses on recent trends in material science, device development, sensing mechanisms, power generation, and data management related to these devices. Additionally, exemplary wearable sweat sensors and commercialization efforts in this area are discussed, with an emphasis on the multifunctional sensing platforms that integrate data from both physical and biochemical sweat sensors.
Recent developments in wearable physical sensors have enabled the development of a number of consumer electronics products which measure parameters related to activity, posture, heart rate, respiration rate, and blood oxygen level. However, progress in the development of wearable chemical sensors has been slower due to the inherent challenges in retrieving and processing bodily fluids. Sweat is a valuable source of biomarkers which can be accessed continuously, on-the-go, and non-invasively. This review provides an overview of recent trends in the area of wearable sweat sensing, looking at topics such as material science, device development, sensing mechanisms, power generation, and data management. Examples of wearable sweat sensors published in recent years, as well as commercialization efforts in this field are also presented. The review highlights the trends in multifunctional sensing platforms which incorporate flexible electronics to integrate data from both physical and biochemical sensors.
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Title: Sense of Taste
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Explore natural remedies for syphilis treatment in Singapore. Discover alternative therapies, herbal remedies, and lifestyle changes that may complement conventional treatments. Learn about holistic approaches to managing syphilis symptoms and supporting overall health.
These simplified slides by Dr. Sidra Arshad present an overview of the non-respiratory functions of the respiratory tract.
Learning objectives:
1. Enlist the non-respiratory functions of the respiratory tract
2. Briefly explain how these functions are carried out
3. Discuss the significance of dead space
4. Differentiate between minute ventilation and alveolar ventilation
5. Describe the cough and sneeze reflexes
Study Resources:
1. Chapter 39, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 34, Ganong’s Review of Medical Physiology, 26th edition
3. Chapter 17, Human Physiology by Lauralee Sherwood, 9th edition
4. Non-respiratory functions of the lungs https://academic.oup.com/bjaed/article/13/3/98/278874
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Ve...kevinkariuki227
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
TEST BANK for Operations Management, 14th Edition by William J. Stevenson, Verified Chapters 1 - 19, Complete Newest Version.pdf
ARTIFICIAL INTELLIGENCE IN HEALTHCARE.pdfAnujkumaranit
Artificial intelligence (AI) refers to the simulation of human intelligence processes by machines, especially computer systems. It encompasses tasks such as learning, reasoning, problem-solving, perception, and language understanding. AI technologies are revolutionizing various fields, from healthcare to finance, by enabling machines to perform tasks that typically require human intelligence.
New Directions in Targeted Therapeutic Approaches for Older Adults With Mantl...i3 Health
i3 Health is pleased to make the speaker slides from this activity available for use as a non-accredited self-study or teaching resource.
This slide deck presented by Dr. Kami Maddocks, Professor-Clinical in the Division of Hematology and
Associate Division Director for Ambulatory Operations
The Ohio State University Comprehensive Cancer Center, will provide insight into new directions in targeted therapeutic approaches for older adults with mantle cell lymphoma.
STATEMENT OF NEED
Mantle cell lymphoma (MCL) is a rare, aggressive B-cell non-Hodgkin lymphoma (NHL) accounting for 5% to 7% of all lymphomas. Its prognosis ranges from indolent disease that does not require treatment for years to very aggressive disease, which is associated with poor survival (Silkenstedt et al, 2021). Typically, MCL is diagnosed at advanced stage and in older patients who cannot tolerate intensive therapy (NCCN, 2022). Although recent advances have slightly increased remission rates, recurrence and relapse remain very common, leading to a median overall survival between 3 and 6 years (LLS, 2021). Though there are several effective options, progress is still needed towards establishing an accepted frontline approach for MCL (Castellino et al, 2022). Treatment selection and management of MCL are complicated by the heterogeneity of prognosis, advanced age and comorbidities of patients, and lack of an established standard approach for treatment, making it vital that clinicians be familiar with the latest research and advances in this area. In this activity chaired by Michael Wang, MD, Professor in the Department of Lymphoma & Myeloma at MD Anderson Cancer Center, expert faculty will discuss prognostic factors informing treatment, the promising results of recent trials in new therapeutic approaches, and the implications of treatment resistance in therapeutic selection for MCL.
Target Audience
Hematology/oncology fellows, attending faculty, and other health care professionals involved in the treatment of patients with mantle cell lymphoma (MCL).
Learning Objectives
1.) Identify clinical and biological prognostic factors that can guide treatment decision making for older adults with MCL
2.) Evaluate emerging data on targeted therapeutic approaches for treatment-naive and relapsed/refractory MCL and their applicability to older adults
3.) Assess mechanisms of resistance to targeted therapies for MCL and their implications for treatment selection
Report Back from SGO 2024: What’s the Latest in Cervical Cancer?bkling
Are you curious about what’s new in cervical cancer research or unsure what the findings mean? Join Dr. Emily Ko, a gynecologic oncologist at Penn Medicine, to learn about the latest updates from the Society of Gynecologic Oncology (SGO) 2024 Annual Meeting on Women’s Cancer. Dr. Ko will discuss what the research presented at the conference means for you and answer your questions about the new developments.
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
micro teaching on communication m.sc nursing.pdfAnurag Sharma
Microteaching is a unique model of practice teaching. It is a viable instrument for the. desired change in the teaching behavior or the behavior potential which, in specified types of real. classroom situations, tends to facilitate the achievement of specified types of objectives.
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
1. Parameter-extraction of a two-compartment model for whole-cell
data analysis
Santosh Pandey *, Marvin H. White
Sherman Fairchild Center, Lehigh University, Bethlehem, PA 18015, USA
Received 10 April 2002; received in revised form 2 July 2002; accepted 3 July 2002
Abstract
Neuronal modeling of patch-clamp data is based on approximations which are valid under specific assumptions regarding cell
properties and morphology. Certain cells, which show a biexponential capacitance transient decay, can be modeled with a two-
compartment model. However, for parameter-extraction in such a model, approximations are required regarding the relative sizes of
the various model parameters. These approximations apply to certain cell types or experimental conditions and are not valid in the
general case. In this paper, we present a general method for the extraction of the parameters in a two-compartment model without
assumptions regarding the relative size of the parameters. All the passive electrical parameters of the two-compartment model are
derived in terms of the available experimental data. The experimental data is obtained from a DC measurement (where the
command potential is a hyperpolarizing DC voltage) and an AC measurement (where the command potential is a sinusoidal
stimulus on a hyperpolarized DC potential) performed on the cell under test. Computer simulations are performed with a circuit
simulator, XSPICE, to observe the effects of varying the two-compartment model parameters on the capacitive transients of the
current response. Our general solution for the parameter-estimation of a two-compartment model may be used to model any
neuron, which has a biexponential capacitive current decay. In addition, our model avoids the need for simplifying and perhaps
erroneous approximations. Our equations may be easily implemented in hardware/software compensation schemes to correct the
recorded currents for any series resistance or capacitive transient errors. Our general solution reduces to the results of previous
researchers under their approximations. # 2002 Elsevier Science B.V. All rights reserved.
Keywords: Patch-clamping; Two-compartment; Whole-cell; Parameter-extraction; Modeling
* Corresponding author. Tel.: /1-610-758-4518; fax: /1-610-758-4561
E-mail addresses: skp3@lehigh.edu (S. Pandey), mhw0@lehigh.edu (M.H. White).
Nomenclature
t single-compartment time constant (s)
tO CDRCRD/(RC/RD) (s)
t1 [(1/CD)(1/RM/1/RC/1/RS)]1
(s)
t2 see Eq. (14) (s)
t3 two-compartment time constant (slow) (s)
t4 two-compartment time constant (fast) (s)
RS pipette resistance (ohm)
RM resistance of compartment M (ohm)
CM capacitance of compartment M (farad)
RD resistance of compartment D (ohm)
CD capacitance of compartment D (farad)
RC resistance connecting compartments M and D (ohm)
VO command potential (volts)
Journal of Neuroscience Methods 120 (2002) 131/143
www.elsevier.com/locate/jneumeth
0165-0270/02/$ - see front matter # 2002 Elsevier Science B.V. All rights reserved.
PII: S 0 1 6 5 - 0 2 7 0 ( 0 2 ) 0 0 1 9 8 - X
2. 1. Introduction
In most electrophysiological studies, whole-cell vol-
tage-clamp techniques are an established method to
measure ionic currents from single cells. An ideal
voltage clamp has two functions: first, it imposes a
command potential on the membrane such that the cell
membrane potential is equal to the command potential
and second, it measures the ionic current. In reality,
there is considerable resistance to the flow of current
through the pipette to the cytoplasm. As a result of this
current flow, the membrane potential is not equal to the
applied command potential. The signal response time
(time constant) is essentially a function of the pipette
resistance, the membrane resistance and capacitance. An
estimation of these electrical components is needed to
compensate for the series resistance and capacitive
transient errors in a voltage-clamp experiment.
Compartmental models are often used to represent a
cell’s passive electrical properties, which provide a useful
insight into the different cell conduction mechanisms. In
the simplest case, a single-compartment model (Fig. 1)
can be used to represent the electrical characteristics of
small cells (longest dimension B/100 mm). Here, the
capacitive transient of the current response to a hyper-
polarized voltage step (i.e. a negative step voltage
relative to the intracellular medium) has a single-
exponential decay time constant. Also, the membrane
resistance is usually 50/100 times larger than the pipette
resistance (5/10 MV). As such, the method of para-
meter-estimation in a single-compartment model be-
comes quite trivial and, over time, numerous methods
have evolved for the extraction of these parameters. If
we assume the membrane resistance is much larger than
the pipette resistance, then all single-compartment
model parameters can be estimated within reasonable
accuracy (Sakmann and Neher, 1994). A more exact
method of parameter-estimation involves admittance
measurements (Lindau and Neher, 1988), where the
model parameters can be expressed in terms of the real
and imaginary components of the measured admittance.
Also, the dynamic changes in passive cellular character-
istics may be measured with phase-tracking techniques
(Fidler and Fernandez, 1989) or by other dual-frequency
measurement approaches (Donnelly, 1994). Computer
simulations have been performed by Sala et al. to
examine the sources of errors introduced by the single-
compartment model parameters in single-electrode vol-
tage-clamp experiments (Sala and Sala, 1994). Recently
a method, which employs planar pipettes in silicon, was
suggested to reduce noise sources in patch-clamping and
for high-throughput screening (Pandey and White,
2001).
A single-compartment model cannot describe some
cells. In neurons, such as the cerebellar Purkinje cells,
the capacitive current response to a hyperpolarizing
voltage pulse is a sum of two exponentials. These cells
can be modeled satisfactorily with a two-compartment
equivalent circuit. In a two-compartment model, the
equivalent electrical circuit consists of two main com-
partments (soma and proximal dendrites on the one
hand, distal dendrites on the other) connected by a
resistance. In hippocampal pyramidal cells, three ex-
ponentials are needed to model the capacitive decay. In
these instances, and many more complex cases, a cable
analysis may be more appropriate than a multi-com-
partment model (Koch and Segev, 1989). The cable
method for analyzing passive electrical data from
neurons consists of decomposing the voltage response
V1(t) potential at compartment M (volts)
V2(t) potential at compartment D (volts)
VP steady-state voltage component of V2(t) (s)
i1(t) total input current through the pipette (ampere)
iSS steady-state component of i1(t) (ampere)
AO single-compartment exponential-decay coefficient (ampere)
A1 two-compartment current exponential-decay (slow) coefficient (ampere)
A2 two-compartment current exponential-decay (fast) coefficient (ampere)
j see Eq. (28) (s2
)
v operating frequency of the sinusoidal stimulus (radians/s)
Y(v) single-compartment admittance at a frequency v (ohm1
)
AR(v) real part of Y(v) (ohm1
)
BR(v) imaginary part of Y(v) (ohm1
)
RTOTAL single-compartment thevenin equivalent resistance (ohm)
RTOT two-compartment thevenin equivalent resistance (ohm)
YTOT(v) two-compartment admittance at a frequency v (ohm1
)
ZTOT(v) two-compartment impedance at a frequency v (ohm)
a(v) real part of YTOT(v) (ohm1
)
b(v) imaginary part of YTOT(v) (ohm1
)
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143
132
3. of the cell into a series of exponential functions and
substituting the time constants of these exponential
functions into equations derived from cable theory
(Rall et al., 1992). As an alternative to this traditional
method of cable analysis, the method of ‘integrals of
transients’ has been employed to analyze the passive
electrical data from neurons (Engelhardt et al., 1998).
Yet, the simpler the compartmental model, the easier
it becomes to estimate its model parameters (Roth and
Hausser, 2001). Unfortunately, even in a two-compart-
ment model, some approximations need to be made to
simplify the model and thereby, ease the method of
parameter-extraction. Llano et al. (1991) employed a
two-compartment model to fit the capacitive transients
of the excitatory currents from Purkinje cells as a sum of
two exponentials. Llano et al. (1991) assumed the
resistances in the proximal and distal compartments
were very large compared with the other resistances in
the equivalent circuit. The biexponential decay of
capacitive transients from hippocampal cells was de-
scribed using a two-compartment model by Mennerick
et al. (1995) assuming the resistance of the distal
compartment is very large. In another work, a simplified
two-compartment model was used to extract the mem-
brane properties of bipolar neurons, assuming very high
resistances in the proximal and distal compartments
(Mennerick et al., 1997). A recent work compared the
various approximations made by previous authors while
using a two-compartment model, summarizing the
validity and limits of these approximations under
different conditions (Nadeau and Lester, 2000).
The reliability of any parameter-extraction technique
depends on the approximations made while extracting
the model parameters and on the validation of such
approximations for the given cell and the bandwidth of
operation. Compensation circuitry, either included in
the software/hardware of the patch-clamp setup, relies
on the accuracy of these parameter-extraction techni-
ques to compensate for the errors introduced by the
circuit resistance and capacitance (Traynelis, 1998). In
some cases, certain simplifying approximations regard-
ing the size of the model parameters can be justified. But
in other cases, especially when dealing with complex and
larger cells, a more exact model for the estimation of the
parameters is required. This points out the need for a
general method of parameter-estimation in a two-
compartment model, which is not subjected to over-
simplifying approximations.
In this work, we present an exact, analytical method
for the parameter-estimation of a two-compartment
model. All the passive electrical parameters of the two-
compartment model are derived based on the DC
measurements (where the command potential is a DC
hyperpolarizing voltage) and on AC measurements
(where the command potential is a sinusoidal stimulus
resting upon a DC hyperpolarizing voltage). Our
equations are compared to those derived by previous
authors and, under approximations used by these
authors, we obtain the same results. Computer simula-
tions are performed on a circuit simulator, XSPICE, to
demonstrate the contributions of varying each model
parameter on the capacitive transients of the current
response.
2. Single-compartment model (a review)
We assume a reasonably small cell (B/100 mm) with a
membrane resistance RM and a membrane capacitance
CM. The command voltage VO is applied to the cell
through a pipette with a series resistance of RS. Fig. 1
shows the electrical equivalent circuit of the small cell,
along with the voltage and current waveforms asso-
ciated with the circuit. This equivalent circuit represen-
tation of a small cell is often used with patch-clamp
techniques in electrophysiological experiments. We
assume the cell membrane is isopotential and there are
no voltage-dependent, active conductances. In small
cells, the typical values of the single-compartment model
parameters are RS/10 MV, RM /1 GV and CM /15/
100 pF. In such cases, the assumption of RM / /RS is
valid and simplifies the model. We will describe briefly
the standard equations of this single-compartment
model, estimating the model parameters by making the
assumption of RM / /RS. Next, we will review a more
Fig. 1. (A) A single-compartment model showing the passive electrical
equivalent circuit of a small cell. (B) The typical waveforms of the
command voltage VO and the recorded current i1(t) versus time.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143 133
4. accurate method for the estimation of the single-
compartment model parameters based on admittance
measurements with no simplifying assumptions. We will
extend this approach to a two-compartment model,
which will provide a technique for the extraction of the
two compartment model parameters. From Fig. 1(A),
we derive the equations
V1(t)
VOt
RSCM
1exp
t
t
(1)
where
tCM
RMRS
RM RS
is the circuit time constant and the current is
i1(t)
VO
RS
1
t
RSCM
VOt
R2
SCM
exp
t
t
(2)
The experimentally recorded current i1(t) has the form
i1(t)iSS AO exp(t=t) (3)
where iSS is the steady state component of i1(t).
Comparing Eq. (1) and Eq. (3) we have
iSS
VO
RS
1
t
RSCM
and AO
VOt
R2
SCM
(4)
With the assumption RM / /RS, the model parameters
can be written as (Sakmann and Neher, 1994)
RM
VO
iSS
; RS
VO
i1(0)
; CM
t
RS
(5)
Computer simulations of the single-compartment
equivalent circuit are performed on XSPICE, a circuit
simulator. Fig. 2(A) shows the effect of varying the
series resistance on the capacitive transient of the
current i1(t) under the application of a 10 mV command
voltage step. The values of the model parameters are
chosen as RM /100 MV, CM /20 pF and RS /2, 3.5
and 5 MV. We see the series resistance compensation is
increased (i.e. as RS is decreased), the time constant t
decreases and the value of i1(0) or AO increases
(according to Eq. (2)). In Fig. 2(B), the amplitude of
the command voltage step is varied and its effect on the
capacitive transient of the current i1(t) is observed. The
values of the model parameters are RM /100 MV,
CM /20 pF and RS/2 MV. In Fig. 2(B), we observe
that even though the time constant is fixed (t/39 ms),
the current i1(0) or AO increases with increasing
magnitude of the command voltage VO (according to
Eq. (2)).
We now review a method of parameter estimation for
a single-compartment model, which gives an exact
solution for the model parameters, without simplifying
assumptions (Lindau and Neher, 1988). In this techni-
que, a sinusoidal voltage stimulus resting upon a
hyperpolarized DC potential is applied as the command
voltage. The magnitude and phase-shift of the resulting
current sinusoid are analyzed with a phase-sensitive
detector to give the real and imaginary current compo-
nents. These current components divided by the stimu-
lus voltage amplitude give the real and imaginary
admittance values. Using this information, along with
the information from the measured DC current, all the
parameters of a single-compartment model can be
exactly determined.
From Fig. 1(A), the net admittance is
Y(v)AR(v)jBR(v)
(1 v2
RMRPC2
M) jvR2
MCM
RT(1 v2R2
PC2
M)
(6)
Fig. 2. (A) The effect of series resistance compensation on the
capacitive transient of the current i1(t). The model parameters are
RM/100 MV, CM/20 pF and RS /2, 3.5 and 5 MV. The fitting
parameters for the single-exponential decay of the capacitive transients
are: (a) for RS/2 MV, t/39 ms, AO/4.9 nA, iSS/0.098 nA; (b) for
RS/3.5 MV, t/68 ms, AO/2.7 nA, iSS/0.096 nA; (c) for RS/5
MV, t/96 ms, AO/1.9 nA, iSS /0.095 nA. (B) The effect of varying
the command step voltage VO on the capacitive transient of the current
i1(t). The model parameters are RM/100 MV, CM/20 pF and RS/
2 MV. The fitting parameters for the single-exponential decay of the
capacitive transients are: t/39 ms (a) for VO//10 mV, AO/4.9 nA,
iSS /0.098 nA; (b) for VO//30 mV, AO/14.7 nA, iSS /0.29 nA; (c)
for VO//60 mV, AO/29.4 nA, iSS/0.59 nA.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143
134
5. where
RT RM RS
VO
IDC
and RP
RMRS
RM RS
(7)
With the experimental values of RT, AR and BR, Eq. (6)
and Eq. (7) give the model parameters as
RS
AR R1
T
A2
R B2
R ARR1
T
;
RM
RTf(AR R1
T )2
B2
Rg
A2
R B2
R ARR1
T
;
CM
1
vCBR
(A2
R B2
R ARR1
T )2
(AR R1
T )2
B2
R
(8)
where fC/vC/2p is the frequency of the applied
sinusoid.
To estimate the three parameters RS, RM and CM of
the single-compartment model, at least three equations
are needed. In the Lindau/Neher technique, the admit-
tance measurement provides two equations and the DC
current measurement provides the third equation needed
to estimate all the model parameters. We use a similar
methodology in the parameter-extraction of the two-
compartment model. The current response i1(t) to a DC
command voltage, together with the admittance mea-
surements, will provide all the information needed to
exactly estimate all the six parameters of the two-
compartment model, as shown in the next section.
3. Two compartment model (DC measurements)
In this analysis, we assume a cell that can be modeled
by an electrical equivalent circuit shown in Fig. 3. The
DC step command voltage VO is applied to the cell
through a pipette with a series resistance RS. The actual
cell can be represented by two compartments: compart-
ment M (for the soma and proximal dendrites) and
compartment D (for the distal dendrites). A series
resistance RC connects the two compartments. Assum-
ing the pipette capacitance is fully compensated, the
following equations can be derived for the two-compart-
ment model:
i1 (VO V1)=RS; i2 (V1 V2)=RC; i3 V1=RM;
i5 V2=RD; i4 CMdV1=dt; i6 CDdV2=dt;
i1 i2 i3 i4; i2 i5 i6
(9)
From the above set of equations, we obtain two first-
order differential equations
CM
dV1(t)
dt
V1(t)
1
RM
1
RC
1
RS
V2(t)
RC
VO
RS
(10)
CD
dV2(t)
dt
V2(t)
1
RC
1
RD
V1(t)
RC
(11)
Eliminating V1(t) from these two differential equations
gives a second-order non-homogeneous differential
equation in V2(t) as
d2
V2(t)
dt2
dV2(t)
dt
1
tO
1
t1
V2(t)
1
tOt1
1
CMCDR2
C
VO
CMCDRCRS
(12)
where
1
tO
1
CD
1
RC
1
RD
and
1
t1
1
CM
1
RM
1
RC
1
RS
(13)
The solution of such a differential equation is of the
form: V(t)/c1 exp(/t/t3)/c2 exp(/t/t4)/VP, where
VP is the particular solution of the above differential
equation and the exponential terms are the solutions of
the homogeneous differential equation. The constants c1
and c2 can be determined from the given initial condi-
tions. For Eq. (12), the particular solution VP is
VP
VORMt2
CD(RMRS RMRC RCRS)
where
t2 CD
1
RD
(RS RM)
RMRS RMRC RCRS
1
(14)
The homogeneous solution of the differential Eq. (12)
gives the two circuit time constants as
1
t3
1
tOt1
1
R2
CCMCD
=
1
tO
1
t1
(15)
1
t4
1
tO
1
t1
2
1
tOt1
1
R2
CCMCD
=
1
tO
1
t1
(16)
Fig. 3. Two-compartment model showing the two compartments:
compartment M (for the soma and proximal dendrites) and compart-
ment D (for the distal dendrites) connected by a resistance RC. The
pipette resistance is RS and the command voltage stimulus is VO.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143 135
6. We also have a relation between the two time constants
as
1
t4
1
t3
1
tO
1
t1
(17)
The initial conditions of V2(0)/0 and V1(0)/0 give the
general solutions of V1(t) and V2(t) as
V2(t)
VORMt2
CD(RMRC RMRS RCRS)
1
t3
t4 t3
exp
t
t3
t4
t4 t3
exp
t
t4
(18)
V1(t)
VORMRCt2
tO(RMRC RMRS RCRS)
1
t3 tO
t4 t3
exp
t
t3
t4 tO
t4 t3
exp
t
t4
(19)
In the approximation of CM /0 (Nadeau and Lester,
2000), we observe the time constants in Eq. (15) and Eq.
(16) reduce to t3 /t2 and t4/0. If we place the values
of these time constants into Eq. (18), then we will have
the same result obtained by Nadeau and Lester (2000).
The next section will provide additional validation of
the above set of equations for the two-compartment
model. Now, the experimentally recorded current i1(t)
has the form
i1(t)iSS A1 exp
t
t3
A2 exp
t
t4
(20)
where iSS is the steady-state current component of i1(t),
while t3 (slow) and t4 (fast) are the two time constants of
the biexponential capacitive transient. Fitting the ex-
perimental plot of i1(t) with Eq. (20) will provide the
values of all the equation unknowns (iSS, t3, t4, A1, A2).
From the experimental plot of i1(t), the following
parameters can be determined:
RTOT
VO
iSS
; RS
VO
i1(0)
VO
A1 A2 iSS
;
CM
VO
R2
S(di1(0)=dt)
t3t4(A1 A2 iSS)2
VO(A1t4 A2t3)
(21)
Eq. (21) allows us to estimate the parameters RS and CM
from the known values of the current parameters (iSS, t3,
t4, A1, A2) in Eq. (20). Also, from Fig. 3 and Eq. (21),
RM can be expressed in terms of RTOT, RS, RC and RD as
1
RTOT RS
1
RM
1
RC RD
iSS(A1 A2 iSS)
VO(A1 A2)
(22)
Using the form of i1(t) from Eq. (20), the voltage V1(t)
can be expressed as
V1(t)VO RS
iSS A1 exp
t
t3
A2 exp
t
t4
(23)
Comparing the two forms of voltage V1(t) from Eq. (19)
and Eq. (23) gives the values of tO, t1 and t2 in terms of
the known parameters as
tO
CDRCRD
RC RD
A1t4 A2t3
A1 A2
(24)
t1
1
t4
1
t3
1
tO
1
(25)
t2
RSCMtO
VOt1
(VO iSSRS) (26)
Now, from the expression of t3, the model parameter
CD can be expressed as
C1
D R2
CCMj
where
j
1
tOt1
1
t3
1
t4
1
t3
(27)
The relation between RC and RD can be found from Eq.
(13) and Eq. (22) as
RD
RC RD
RC
CM
t1
1
RS
1
RTOT RS
(28)
We have shown the derivations of a two-compartment
model based on DC measurements. Our objective is to
express the model unknowns (RS, RM, RC, RD
¯
, CM, CD)
in terms of the known parameters (iSS, t3, t4, A1, A2) of
the experimentally recorded current (Eq. (20)). We are
able to extract some parameters (RS, RTOT, CM, to, t1,
t2) in this process, but the other model unknowns (RC,
RD, RM, CD) may only be expressed in terms of some
interdependent equations. In the next section, we will
continue with our derivations for the parameter-extrac-
tion of a two-compartment model, to express the ‘still-
unknown’ model parameters in the form of independent
equations.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143
136
7. 4. Comparison with previous work
In our derivations until now, we have avoided making
simplifying assumptions or approximations regarding
the relative sizes of the circuit components. At this
point, it is interesting to review the previous work on the
two-compartment modeling. In these works, simplifying
assumptions are made, which provides a unique solution
to the equivalent circuit model based on DC measure-
ments. If we apply these assumptions to our general set
of equations, then our equations reduce to previous
reported work.
Llano et al. (1991) uses the assumption of RM /,
RD / /RC, RS and CD / /CM for modeling the
currents of Purkinje cells. This simplifying assumption
works well for determining the passive properties of
Purkinje neurons. As will be shown below, the results in
the reference (Llano et al., 1991) can be obtained from
the general set of equations we have already derived for
the two-compartment model. If we use the above
assumption, then Eq. (13), Eq. (15) and Eq. (16) yield
tO CDRC;
1
t1
1
t4
1
CM
1
RC
1
RS
;
t2 t3 CD(RC RS)
(29)
Inserting Eq. (29) into Eq. (19) provides
V1(t)VO
1
RS
RC RS
exp
t
t3
RC
RC RS
exp
t
t4
(30)
Comparing Eq. (23) with Eq. (31) gives
A1
VO
RC RS
and A2
VORC
R2
S RSRC
(31)
Eq. (29) and Eq. (31) are sufficient to extract the model
parameters as
CD
t3A1
VO
CM
t4(A1 A2)2
A2VO
RS
VO
A1 A2
RC
A2VO
A1(A1 A2)
(32)
The results obtained by Llano et al. (1991) are the
same as those shown in Eq. (32). Computer simulations
are performed on a two-compartment model with the
assumption that RD / /RS, RC; RM / and CD / /
CM and the results are shown in Fig. 4. A 10 mV
command potential is applied as the voltage stimulus
VO. Fig. 4(A) shows the effect of series resistance
compensation on the capacitive transient of the current
i1(t). The model parameters chosen are CM /5 pF,
CD /100 pF, RC/30 MV and RS/5, 10 and 15 MV.
From Eq. (31), we see the amplitude of A2 (fast) is RC/
RS times the amplitude of A1 (slow). As the ratio of RC/
RS is increased, the amplitude of A2 also increases
(evident from Fig. 4A). The amplitude of A1, on the
other hand, does not change significantly. Increasing the
series resistance compensation decreases both the fast
(t4) and the slow (t3) time constants. Fig. 4(B) shows the
effect of varying RC on the capacitive transient of the
current i1(t) under the same assumption. The model
parameters chosen are CM /5 pF, CD /100 pF, RS/
10 MV and RC /10, 30 and 60 MV. In this case also,
decreasing the value of RC decreases both the fast (t4)
and the slow (t3) time constants. However, the value of
i1(0) is constant for varying values of RC.
Mennerick et al. (1995) use the assumption RD / /
RM for modeling the passive properties of hippocampal
Fig. 4. (A) The effect of series resistance compensation on the
capacitive transient of the current i1(t) under the assumption RD /
/RS, RC; RM/ and CD / /CM. A 10 mV command potential
was applied as the voltage stimulus VO. The model parameters chosen
are CM/5 pF, CD /100 pF, RC /30 MV and RS/5, 10 and 15 MV.
The fitting parameters for the biexponential decay of the capacitive
transients are (a) for RS/5 MV, t3/3.5 ms, t4 /21.4 ms, A1 /0.28
nA, A2/1.7 nA; (b) for RS/10 MV, t3 /4 ms, t4/37.5 ms, A1/
0.25 nA, A2 /0.75 nA; (c) for RS/15 MV, t3/4.5 ms, t4 /50 ms,
A1 /0.22 nA, A2/0.44 nA. (B) The effect of varying RC on the
capacitive transient of the current i1(t) under the same assumption.
The model parameters chosen are CM/5 pF, CD /100 pF, RS/10
MV and RC /10, 30 and 60 MV. The fitting parameters for the
biexponential decay of the capacitive transients are (a) for RC /10
MV, t3/2 ms, t4 /25 ms, A1 /0.5 nA, A2 /0.5 nA; (b) for RC /30
MV, t3 /4 ms, t4 /37.5 ms, A1/0.25 nA, A2 /0.75 nA; (c) for RC/
60 MV, t3 /7 ms, t4/43 ms, A1 /0.14 nA, A2/0.86 nA.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143 137
8. neurons. Single-exponential fits are usually inadequate
to describe the decay of current transients from these
hippocampal neurons, but biexponential decays pro-
vided an adequate description of the data. The biexpo-
nential decay of capacitive transients indicates the
passive membrane properties may be described ade-
quately with a two-compartment equivalent circuit
model. As shown below, with this assumption in our
general set of equations, we obtain the same results as
reported in the literature (Mennerick et al., 1995).
From Eq. (13) and Eq. (24) we have
tO RCCD
A1t4 A2t3
A1 A2
(33)
and with Eq. (21) and Eq. (22),
RS
VO
A1 A2 iSS
;
1
RM
iSS(A1 A2 iSS)
VO(A1 A2)
;
CM
t3t4(A1 A2 iSS)2
VO(A1t4 A2t3)
(34)
Also, with Eq. (28) and Eq. (34),
RC
(A1 A2)(A1t4 A2t3)2
VO
A1A2(A1 A2 iSS)2
(t4 t3)2
and
CD
1
RC
A1t4 A2t3
A1 A2
(35)
5. Two-compartment model (admittance measurements)
A common method for measuring changes in mem-
brane capacitances of small cells utilizes a sinusoidal
voltage stimulus. The membrane capacitance is mea-
sured as a function of the real and imaginary admittance
of the cell for the case of a single-compartment model.
In this instance, this scheme is extended for a two-
compartment model to help extract the remaining model
parameters. If the AC admittance of the two-compart-
ment model is YTOT(v)/1/ZTOT(v)/a(v)/jb(v),
then from Fig. 3 we have
1
ZTOT(v) RS
1
RM
jvCM
1 jvCDRD
RC RD jvCDRCRD
(36)
which can be written as
fa RS(a2
b2
)g jb
f(1 aRS)2
(bRS)2
g
1
RM
jvCM
RC jvtO(RC RD)
RC(RC RD)(1 jvtO)
(37)
Equating the real parts of the Eq. (37) and using Eq.
(13), we find
1
(RC RD)(1 v2t2
O)
1
RC(1 v2t2
O)
1
RS
CM
t1
fa RS(a2
b2
)g
f(1 aRS)2
(bRS)2
g
(38)
Inserting Eq. (13), Eq. (27) and Eq. (38) into Eq. (28)
gives
1
RC
(1v2
t2
O)
1
RS
CM
t1
fa RS(a2
b2
)g
f(1 aRS)2
(bRS)2
g
1
tOCMRCj
1
CM
t1
1
RS
1
RTOT RS
(39)
From Eq. (39), RC can be expressed as
1
RC
(1 v2
t2
O)fa RS(a2
b2
)g
f(1 aRS)2
(bRS)2
g
v2
t2
O
CM
t1
1
RS
1
RTOT RS
1
tOCMj
CM
t1
1
RS
1
RTOT RS
1
(40)
And from the expression C1
D R2
CCMj; we have
1
CD
1
tO
ffiffiffiffiffiffiffiffiffiffi
CMj
p
CM
t1
1
RS
1
RTOT RS
ffiffiffiffiffiffiffiffiffiffi
CMj
p
(1 v2
t2
O)fa RS(a2
b2
)g
f(1 aRS)2
(bRS)2
g
v2
t2
O
CM
t1
1
RS
1
RTOT RS
2
(41)
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143
138
9. Finally, we have
1
RD
1
RC
1
RCCMjtO
1
and
1
RM
1
RTOT RS
1
RC RD
(42)
From the results obtained in previous sections, all the
six two-compartment model parameters (RC, RD, RM,
RS, CM, CD) are independently expressed in terms of the
known parameters (iSS, t3, t4, A1, A2) of the current i1(t)
expression (Eq. (20)) and the known parameters (a(v),
b(v), v) of the admittance measurements. A flowchart
summarizing the steps for the extraction of the model
parameters is shown at the end of the next section as
Fig. 11. Such an algorithm can be easily implemented in
software, which takes (as input) the DC and AC
measurement results and gives (as output) the values
of the model parameters.
6. Two-compartment model (simulation results)
Computer simulations of the two-compartment
model, based on our general parameter-extraction
method, were performed on XSPICE. The effect of
varying the series resistance compensation on the two-
compartment model current response is shown in Fig. 5.
The model parameters chosen are CM /25 pF, CD /25
pF, RC /20 MV, RM /RD /200 MV and RS/1, 5 and
10 MV. Fig. 5(A) shows the effect of series resistance
compensation on the capacitive transient of the current
i1(t) in a two-compartment model. From RS /1 MV to
Fig. 5. (A) The effect of series resistance compensation on the
capacitive transient of the current i1(t) in a two-compartment model
(with no approximations). The model parameters chosen are CM/25
pF, CD/25 pF, RC /20 MV, RM/RD/200 MV and RS/1, 5 and
10 MV. The fitting parameters for the biexponential decay of the
capacitive transients are (a) for RS /1 MV, t3 /0.5 ms, t4/21.5 ms,
A1 /0.94 nA, A2 /9 nA, iSS/0.095 nA; (b) for RS /5 MV, t3 /0.67
ms, t4 /72 ms, A1 /0.7 nA, A2 /1.2 nA, iSS/0.091 nA; (c) for RS/
10 MV, t3/0.87 ms, t4/104 ms, A1/0.5 nA, A2 /0.42 nA, iSS/
0.087 nA. (B) Plots the various values of tO, t1, t2, t3 and t4 (as defined
by Eqs. (13)/(16)) as a function of the series resistance compensation.
The model parameters are chosen as CM/25 pF, CD /25 pF, RC /20
MV and RM/RD/200 MV. The range of the values of the other
fitting parameters are A1 /0.5/0.94 nA, A2/0.42/9.0 nA, iSS/
0.087/0.095 nA.
Fig. 6. (A) The effect of varying RC on the capacitive transient of the
current i1(t) in a two-compartment model (with no approximations).
The model parameters chosen are CM/25 pF, CD/25 pF, RS/5
MV, RM/RD /200 MV and RC /2, 20 and 100 MV. The fitting
parameters for the biexponential decay of the capacitive transients are
(a) for RC /2 MV, t3/0.3 ms, t4/19.3 ms, A1 /1.7 nA, A2 /0.22
nA, iSS/0.095 nA; (b) for RC/20 MV, t3 /0.67 ms, t4 /72 ms, A1/
0.69 nA, A2 /1.22 nA, iSS /0.09 nA; (c) for RC /100 MV, t3 /1.84
ms, t4 /103 ms, A1/0.19 nA, A2 /1.73 nA, iSS/0.08 nA. (B) Plots
the various values of tO, t1, t2, t3 and t4 (as defined by Eqs. (13)/(16))
as a function of RC. The model parameters are chosen as CM/25 pF,
CD /25 pF, RS/5 MV and RM /RD /200 MV. The range of the
values of the other fitting parameters A1 /0.12/1.7 nA, A2 /0.22/1.8
nA, iSS/0.073/0.095 nA.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143 139
10. RS/10 MV, the increase in t3 (slow) is not so
significant (0.5/0.87 ms) compared to the increase in
t4 (fast) (21.5/104 ms). Also, the value of i1(0) is very
sensitive to changes in RS. Fig. 5(B) plots the various
values of tO, t1, t2, t3 and t4 (as defined by Eqs. (13)/
(16)) as a function of the series resistance compensation.
According to Eq. (13), tO is relatively independent of
RS, as shown in Fig. 5. It should be noted here that fast
exponential decay time constant of the capacitive
transient is t4, while the slow exponential decay time
constant is t3. The variables t1 (fast) and t2 (slow)
represent the two time constants for a two-compartment
model under the approximation of RM /, RD / /
RC, RS and CD / /CM (Llano et al., 1991). As seen
in Fig. 5(B), the time constants t1 and t4 are close to
each other, but the difference between the time constants
t2 and t3 increases with increasing values of RS. This
shows the limitation of using an approximated two-
compartment model with a high series resistance. In
addition, the difference between the time constants t2
and t3 increases with an increasing value of the
connecting resistance RC. Finally, both time constants
of the general two-compartment model, t3 and t4,
depend and change with varying values of RS. This is
in contrast to the finite-cable model, where changing RS
affects only the first, faster time constant and leaves the
slower one unchanged.
Fig. 6 shows the effect of varying RC on the current
response of a two-compartment model. Fig. 6(A) shows
the effect of varying RC on the capacitive transient of the
current i1(t). The model parameters chosen are CM /25
Fig. 7. (A) The effect of varying RD on the capacitive transient of the
current i1(t) in a two-compartment model (with no approximations).
The model parameters chosen are CM/25 pF, CD /25 pF, RS/5
MV, RM/200 MV, RC /20 MV and RD /20, 100 and 400 MV. The
fitting parameters for the biexponential decay of the capacitive
transients are (a) for RD /20 MV, t3 /0.39 ms, t4 /60 ms, A1 /
0.725 nA, A2 /1.02 nA, iSS/0.26 nA; (b) for RD /100 MV, t3 /
0.615 ms, t4/70.3 ms, A1 /0.68 nA, A2 /1.2 nA, iSS/0.125 nA; (c)
for RD /400 MV, t3/0.71 ms, t4 /73 ms, A1 /0.7 nA, A2/1.23 nA,
iSS/0.07 nA. (B) Plots the various values of tO, t1, t2, t3 and t4 (as
defined by Eqs. (13)/(16)) as a function of RD. The model parameters
are chosen as CM/25 pF, CD/25 pF, RS/5 MV and RM /200
MV. The range of the values of the other fitting parameters A1 /0.7/
0.76 nA, A2 /0.95/1.23 nA, iSS/0.07/0.3 nA.
Fig. 8. (A) The effect of varying RM on the capacitive transient of the
current i1(t) in a two-compartment model (with no approximations).
The model parameters chosen are CM/25 pF, CD/25 pF, RS/5
MV, RD/200 MV, RC /20 MV and RM/10, 50 and 200 MV. The
fitting parameters for the biexponential decay of the capacitive
transients are (a) for RM/10 MV, t3 /0.6 ms, t4 /56 ms, A1 /0.46
nA, A2 /1.05 nA, iSS/0.7 nA; (b) for RM/50 MV, t3 /0.66 ms,
t4 /69 ms, A1/0.62 nA, A2/1.2 nA, iSS /0.22 nA; (c) for RM/200
MV, t3/0.67 ms, t4 /72 ms, A1 /0.7 nA, A2 /1.22 nA, iSS/0.09
nA. (B) Plots the various values of tO, t1, t2, t3 and t4 (as defined by
Eqs. (13)/(16)) as a function of RM. The model parameters are chosen
as CM/25 pF, CD/25 pF, RS/5 MV and RD/200 MV. The range
of the values of the other fitting parameters A1 /0.44/0.71 nA, A2/
1.03/1.23 nA, iSS/0.07/0.53 nA.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143
140
11. pF, CD /25 pF, RS/5 MV, RM /RD /200 MV and
RC/2, 20 and 100 MV. Fig. 6(B) plots the various
values of tO, t1, t2, t3 and t4 (as defined by Eqs. (13)/
(16)) as a function of RC. The model parameters chosen
in this case are the same as those for Fig. 6(A). From
both the plots, the slow time constant t3 is very sensitive
to increases in the value of RC, whereas the other time
constant t4 is relatively constant with any changes in the
value of RC. Also, the difference between t2 and t3
becomes smaller with increasing values of RC. This
shows that the approximation of CM /0 by Nadeau and
Lester (2000) is valid only for larger values of RC where
the difference between the two time constants, t3 and t4,
is large.
Fig. 7 shows the effect of varying RD on the current
response of a two-compartment model. The model
parameters chosen are CM /25 pF, CD /25 pF, RS/5
MV, RM /200 MV, RC /20 MV and RD /20, 100 and
400 MV. Fig. 7(A) shows the effect of varying RD on the
capacitive transient of the current i1(t). Fig. 7(B) plots
the various values of tO, t1, t2, t3 and t4 as a function of
RD, choosing the same values of the model parameters.
Similar to Fig. 6, we see a strong dependence of the slow
time constant t3 on the varying values of RD, while the
fast time constant t4 is relatively independent of such
changes in RD. The difference between t2 and t3 is more
pronounced for smaller values of RC.
Fig. 8 shows the effect of varying RM on the current
response of a two-compartment model. The model
parameters chosen are CM /25 pF, CD /25 pF, RS/
5 MV, RD /200 MV, RC/20 MV and RM /10, 50 and
200 MV. Fig. 8(A) shows how the capacitive transient of
Fig. 9. (A) The effect of varying CM on the capacitive transient of the
current i1(t) in a two-compartment model (with no approximations).
The model parameters chosen are CD /25 pF, RS /5 MV, RM/
RD/200 MV, RC /20 MV and CM /5, 25 and 100 pF. The fitting
parameters for the biexponential decay of the capacitive transients are
(a) for CM/5 pF, t3 /0.6 ms, t4 /18 ms, A1 /0.42 nA, A2 /1.5 nA,
iSS/0.09 nA; (b) for CM /25 pF, t3/0.67 ms, t4 /72 ms, A1 /0.7
nA, A2 /1.22 nA, iSS/0.09 nA; (c) for CM/100 pF, t3 /1.03 ms,
t4 /175 ms, A1/1.3 nA, A2/0.63 nA, iSS/0.09 nA. (B) Plots the
various values of tO, t1, t2, t3 and t4 (as defined by Eqs. (13)/(16)) as a
function of CM. The model parameters are chosen as CD /25 pF,
RS/5 MV and RM/RD /200 MV. The range of the values of the
other fitting parameters are A1 /0.42/1.6 nA, A2/0.35/1.5 nA,
iSS/0.09 nA.
Fig. 10. (A) The effect of varying CD on the capacitive transient of the
current i1(t) in a two-compartment model (with no approximations).
The model parameters chosen are CM/25 pF, RS/5 MV, RM/
RD /200 MV, RC /20 MV and CD/5, 25 and 100 pF. The fitting
parameters for the biexponential decay of the capacitive transients are
(a) for CD /5 pF, t3 /0.23 ms, t4 /39 ms, A1/1.4 nA, A2 /0.52 nA,
iSS /0.09 nA; (b) for CD/25 pF, t3 /0.67 ms, t4/72 ms, A1 /0.7
nA, A2 /1.22 nA, iSS /0.09 nA; (c) for CD/100 pF, t3 /2.33 ms,
t4 /90 ms, A1 /0.44 nA, A2/1.47 nA, iSS/0.09 nA. (B) Plots the
various values of tO, t1, t2, t3 and t4 (as defined by Eqs. (13)/(16)) as a
function of CD. The model parameters are chosen as CM/25 pF,
RS/5 MV, RM/RD /200 MV and RC /20 MV. The range of the
values of the other fitting parameters are A1/0.39/1.39 nA, A2 /
0.52/1.52 nA, iSS/0.09 nA.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143 141
12. the current i1(t) varies with changing RM. Fig. 8(B) plots
the various values of tO, t1, t2, t3 and t4 as a function of
RM, choosing the same values of the model parameters.
As seen in Fig. 8, the time constants t1, t2, t3 and t4
exhibit less dependence on the varying values of RM.
Yet, there is significant difference between the curves of
t2 and t3, suggesting that for relatively smaller values of
RC, the more accurate time constant (slow) is t3 and not
t2 (which is the slow time constant under the approx-
imation made by Llano et al. (1991)).
Fig. 9 shows the effect of varying CM on the current
response of a two-compartment model. The model
parameters chosen are CD /25 pF, RS/5 MV, RM /
RD /200 MV, RC /20 MV and CM /5, 25 and 100 pF.
Fig. 9(A) shows the effect of varying CM on the
capacitive transient of the current i1(t). Fig. 9(B) plots
the various values of tO, t1, t2, t3 and t4 as a function of
CM, choosing the same values of the model parameters.
As seen in Fig. 9, both the time constants t3 and t4 vary
with changing values of CM; the dependence of the slow
time constant t3 on such changes being much more
significant. The curve of t2 is relatively independent of
varying CM because it was the slow time constant for the
case where CM /0 in a two-compartment model (Llano
et al., 1991; Nadeau and Lester, 2000). In this case, there
is noticeable error involved in the computation of the
time constants if approximations are made in the two-
compartment model. This error becomes more and more
significant as the value of CM increases.
Fig. 10 shows the effect of varying CD on the current
response of a two-compartment model. The model
parameters chosen are CM /25 pF, RS/5 MV, RM /
RD /200 MV, RC/20 MV and CD /5, 25 and 100 pF.
Fig. 10(A) shows the effect of varying CD on the
capacitive transient of the current i1(t). Fig. 10(B) plots
the various values of tO, t1, t2, t3 and t4 as a function of
CD, choosing the same values of the model parameters.
As seen from Fig. 10, the fast time constant t4 is
relatively constant with changing values of CD, while the
slow time constant t3 shows a sharp, linear increase with
increasing values of CD. The curves of t2 and t3 follow
each other closely and so does the curves of t1 and t4. As
such, making an approximation about the relative size
of CD does not introduce any significant error in the
computation of the time constants.
7. Conclusion
In summary, we have derived a general solution for
the parameter-estimation of a two-compartment model.
With simplifying approximations, used by previous
authors, our derivations are consistent with their results.
The computer simulation results of the general two-
compartment model give valuable insight into the role of
each model parameter in the current response of such an
equivalent circuit. We have compared the various time
constants (those from approximated models and those
from our general model) under the effects of varying
model parameters. The difference between the time
constants (related to the approximated models and our
general model) increases with decreasing values of the
connecting resistance RC. As seen from the simulations,
each of the model parameters has a unique effect on the
variation of the different time constants. Employing an
approximated model may not reveal the exact values of
the model parameters, which are calculated from these
time constants. The general method for the extraction of
parameters is not limited by any simplifying approxima-
tions and so gives an exact solution of the two-
compartment model.
Acknowledgements
The funding for this project was provided by National
Science Foundation (ECS-0086178; Electronic DNA
Sequencing with Ion Channel Research). S. Pandey is
Fig. 11. A flowchart to summarize the steps for the parameter-
extraction of a two-compartment model using the algorithm described
in this work.
S. Pandey, M.H. White / Journal of Neuroscience Methods 120 (2002) 131/143
142
13. also supported by a Sherman Fairchild Graduate
Fellowship.
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