A ‘membrane-on-chip’ device allows researchers to quickly and easily see what’s going on at the molecular level of a cell membrane.

Dr. Anna-Maria Pappa, Assistant Professor, Department of Biomedical Engineering in collaboration with researchers from Cambridge and Stanford Universities has been investigating the use of bioelectronics to understand how viruses and drugs interact with cell membranes.

Dr. Pappa’s most recent work details the mechanism behind this device. The researchers provide a mechanistic understanding of the device, using experiments and simulations to provide insight about how their device works and in turn provide design criteria to enhance its sensitivity. Their results were published in.

The research team includes investigators from the Department of Chemical Engineering and Biotechnology at the University of Cambridge and the Department of Materials Science and Engineering at Stanford University.

The cell membrane separates the interior of the cell from its external environment. It is a semipermeable lipid bilayer that regulates the transport of materials entering and exiting the cell.

Supported lipid bilayers (SLBs) of varying biological complexity can be produced using extracellular material that can be harvested from simple cell culture. Those models can be used to mimic any cell from the human body — all in a lab, without the time and effort needed to keep an actual cell alive.

“These SLBs can be formed on solid surfaces and used to characterize the properties of the plasma membrane or to study membrane interactions at the molecular level,” Dr. Pappa said. “More than half of all currently approved drugs target the cell membrane, but the complexity and slow turnaround of traditional cell-based assays make the study of molecular interactions with the cell membrane quite challenging. SLBs are a simple and representative cell membrane model that we can use to more quickly and easily see what’s going on at the molecular level.”

This is a non-invasive technique. In vitro is Latin for ‘within the glass’ and refers to work that is performed outside of a living organism, providing a controlled environment for an experiment.

A ‘membrane-on-chip’ device allows researchers to isolate the cell membrane and measure events at the membrane level. This could be the entry of a drug to the cell, the interaction between a virus and the membrane, or the way ion channels work, to name a few examples.

“We can culture the cells we want to investigate in the lab,” Dr. Pappa said. “Cells secrete extracellular substances, which give us information about the cell membrane, proteins, and lipid components. We can isolate the particles, put them on the device, fuse them with the substrate and create a lipid bilayer.”

The device uses conducting polymer electrodes and transistors. Integrating electrical components offers an opportunity to noninvasively interface with these biological models for more accurate and quantifiable information.

Interfacing can be a powerful means of investigating biological systems when used carefully, but the polymer and the tissue must not damage each other. Organic bioelectronics are devices containing carbon, which can seamlessly integrate with complex biological systems. They also demonstrate superior performance compared with inorganic counterparts when it comes to interfacing and transducing biological signals.

“Electronic signatures give insight to what’s going on, but the signals are complicated. They need decoupling and analyzing to understand what’s happening at the molecular level for meaningful biological data.” Dr. Pappa said.

To infer the properties of the cell membrane, the researchers use electrochemical impedance spectroscopy, a powerful technique used to analyze biological events occurring at the electrode surface. Depending on the voltage frequency, the SLBs will act in different ways, which researchers can extrapolate to infer information about how the cell membrane is interacting with its environment.

While complicated, using electrochemical impedance spectroscopy is a better alternative to microscopy, which uses microscopes to physically view objects and areas of objects. Witnessing the interactions between the cell membrane and a target drug, for example, is possible and widely used, but doesn’t offer portability or high throughput. Integrating electronics with a ‘membrane-on-chip’ device offers the speed and ease researchers need for identifying new drug candidates or how an unknown virus enters cells, for example.��

Jade Sterling
Science Writer
25 July 2022

The post Mimicking the Cell Membrane on a Chip appeared first on Khalifa University.

Pressure sensors are used in electronic devices across all industries and making them as accurate as possible means making them as thin as possible. Researchers from Khalifa University have developed a method to use a novel 2D material for highly-sensitive and tunable flexible pressure sensors.��

Compared with conventional rigid silicon-based electronics, thin, flexible electronics can withstand various deformations such as tension, compression, bending and twisting. Pressure sensors that can transform external pressure into electrical signals are an indispensable application of flexible electronics, particularly for biomedical applications.

A team of researchers from Khalifa University has investigated how to develop a pressure sensor using a novel 2-Dimensional (2D) material, which is a single sheet of material that is just one atom thick, and 3D printing. They published their results in The research team includes Jing Fu, Research Associate, Somayya Taher, PhD candidate, Prof. Rashid Abu Al-Rub, Director of the Advanced Digital and Additive Manufacturing Group and Professor of Mechanical Engineering, Prof. TJ Zhang, Professor of Mechanical Engineering, Prof. Vincent Chan, Professor of Biomedical Engineering, and Prof. Kin Liao, Professor of Aerospace Engineering.

“Pressure sensors can be divided into various categories, including piezoelectric pressure sensors and piezoresistive pressure sensors,” Dr. Kin explained. “The working principle of a piezoresistive pressure sensor capitalizes on the change in the electrical resistance of the sensor against applied pressure. Such sensors have a simple structure, high sensitivity, fast-frequency response and low-energy consumption, making them popular candidates for various applications.”

An effective pressure sensor needs to be sufficiently thin. A sensor that is too thick may give erroneous readings as the sensor would press into a soft material, decreasing the load between the objects and increasing the measured pressure. To be as accurate as possible, researchers have turned to 2D materials to achieve sensors that are thin as possible.

“The engineering performance and robustness of a piezoresistive sensor mainly hinge on the sensor’s embedded active material,” Dr. Kin explained. “So far, different kinds of conductive materials have been used, such as metal nanoparticles, conductive polymers, graphene, and transition metal compounds. More recently, 2D materials have captured researchers’ attention worldwide, particularly transition metal carbides and nitrides or MXenes.”

MXenes are a family of 2D materials comprised of a pretransition metal, such as titanium (Ti), zirconium (Zr) or hafnium (Hf), with carbon and/or nitrogen, and hydroxyl, oxygen or fluorine surface functional group. These combinations give MXenes excellent electrical conductivity and hydrophilicity, making them promising candidates for applications such as piezoresistive sensors.��

As a 2D material, MXenes can be used as sheets and stacked on top of each other via van der Waals forces or hydrogen bonding between the functional groups. This way, MXenes can be formed into flexible and stable films, although the resulting material shows a very weak piezoresistive effect because when compressed, the structure of the sheet doesn’t allow for much deformation. Using MXenes in a 3D structure with similar length scales in all three dimensions would overcome this issue and make best use of the novel MXene material.

The Khalifa University team used additive manufacturing to develop the 3D structures. Traditional methods use templates upon which MXene layers are deposited before the templates are removed. While this does work, it does not allow for precise control of the internal structure of the resulting 3D scaffold. 3D printing overcomes this, with the technology able to fabricate flexible pressure-sensitive sensors with a high dynamic range through an easy to manipulate and large-scale manufacturing method.

“There are enormous possibilities in the design of internal structures that could be produced by 3D printing, but the triply periodic minimal surface (TPMS) structure is one of the more interesting,” Dr. Kin said. “The TPMS structure is known for possessing characteristics of surface area, mechanical robustness and thermal conductivity with an edge-free structure. Fabrication of 2D MXenes into the periodic, porous TPMS structure will lead to the development of novel 3D scaffolds with excellent electrical conductivity and mechanical properties.”

The team developed a simple and efficient method to combine MXene with a uniquely designed TPMS gyroid structure to create a 3D MXene-based gyroidal structure for use as a piezoresistive sensor with extremely high sensitivity, good response time and improvable durability. This method can be used to fabricate 3D MXene structures with any size, shape and internal structure.

More recently, Prof. Liao’s group has been working on constructing 3D structures of heterogenous 2D materials – different types of 2D materials organized in layered manner – for applications such as sensors, electromagnetic interference shielding, as well as energy-related applications.

Jade Sterling
Science Writer
25 May 2022

The post Advances in Flexible Pressure Sensors Using 3D Printing and 2D Materials appeared first on Khalifa University.

The takeAbreath facemask combines sophisticated machine learning with advanced sensors and gamification to address the stress and anxiety levels brought to the surface by the Covid-19 pandemic.

Not only does their facemask help monitor stress, it is linked to a smartphone app that offers breathing games to help reduce stress levels.

Dr. Anna-Maria Pappa, Assistant Professor, Dr. Sofia Dias, Research Scientist, and Prof. Leontios Hadjileontiadis, Biomedical Engineering Department Chair, collaborated with Dr. Sahika Inal, King Abdullaziz University of Science and Technology, to develop a smart mask that monitors stress and offers intervention techniques, including games and breathing exercises, to the user. Out of 314 applications from all over the world, the innovative mask won third place in the.

The Women to Impact Resilience Challenge, organized by the King Abdullah University of Science and Technology (KAUST), is aimed at individuals and teams from around the world with technology-based solutions that help local ecosystems build resilience to real-world challenges such as climate change, disasters, epidemics, food insecurity, and environmental degradation. The Khalifa University team entered the Health track which required their solution tackle ‘the prevention, detection and treatment of diseases and pandemics.’

The takeAbreath team received a prize of USD 5,000 for their solution in an award ceremony held on the 20th of January.

“Covid-19 exacerbated the psychosocial effects that put adults at high risk for chronic depression and anxiety,” Dr. Pappa explained. “The need for continuous stress monitoring and stress management is timelier than ever. But emotional expression is hampered by the face mask that became a necessary protective accessory during the pandemic. Our takeAbreath solution transforms a simple mask to a smart ‘Lab-on-Facemask’.”

Sensors in the facemask recognize physiological signals related to stress and anxiety, including breathing patterns and variations in the electrical conductance of the skin, known as electrodermal activity (EDA). Research shows that both breathing and EDA signals can be indicative of the intensity of our emotional state.

“When physiological signals are transferred to a smartphone app via Bluetooth, our algorithms perform deep data analysis using trained deep learning models to identify the stress or anxiety levels of the user,” Dr. Dias explained. “Once this has been determined, the app offers personalized breathing games and exercises to the user, controlled by the users’ breathing sounds.”

“Recent work published in the Lancet revealed that in 2020, cases of major depressive and anxiety disorders increased by 28 percent and 26 percent respectively, notably in countries with high Covid-19 infection rates,” Prof. Inal said. “With the social distancing requirements preventing traditional doctor’s office visits and diagnoses, we need technological advancements to help support mental health. Our smart facemask concept with its integrated real-time stress-sensing capabilities offers that support.”

Beyond the pandemic however, as facemasks seem likely to remain an accessory to everyday life, continuous monitoring of stress and anxiety can help users maintain better mental health throughout their lives.

“Overall, our approach builds on existing studies where respiratory patterns and electrodermal activity have been successfully employed, either separately or in combination, in assessing the mental state of individuals and proposing suitable intervention strategies,” Dr. Pappa said. “We incorporated a sensing framework into a wearable facemask linked to a smartphone for real-time continuous measurements and to provide stress management through breathing games and exercises.”

Breathing exercises have long been recommended for reducing stress levels as they increase oxygen exchange, which reduces blood pressure, slows the heart, and releases any tension held in the abdomen. These physical changes also benefit the mental state as focusing on breathing can bring patients back to the present and to a state of mindfulness. While breathing exercises may not be a full stress management technique, they are clinically proven to lessen the symptoms of stress and anxiety and can be employed whenever and wherever needed.

“takeAbreath showcases the skills of the KU Department of Biomedical Engineering faculty to approach health problems by normalizing the technology to the user’s everyday living customs and turning simple means, such as a mask, to a smart health monitoring sensor. This line of research, by involving gamified interventions, exemplifies to the young students the way they could think in order to provide innovative solutions to GLocal problems, such as stress, anxiety and Covid-19 pandemic” Prof. Hadjileontiadis, Chair of BME, ��ݮ��Ƶ.

Jade Sterling
Science Writer
6 April 2022

The post Success for Khalifa University Team at Women to Impact 2022 Resilience Challenge for takeAbreath Stress Monitoring Facemask appeared first on Khalifa University.

Two Khalifa University student papers have been accepted at the 43rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

The and will cover diverse topics of cutting-edge research and innovation in biomedical engineering and healthcare technology.

Fitting the theme of ‘Changing Global Healthcare in the Twenty-First Century’, Dahlia Hassan investigated the efficacy of a model in determining how to help patients suffering from fainting, while Feryal Alskafi, MSc in Biomedical Engineering student, developed a model to identify emotions from bodily responses. Dahlia is currently a Teacher’s Assistant for Dr. Herbert Jelinek, Associate Professor of Biomedical Engineering, and will begin her Master’s degree in Spring 2022.

Heart Rate Model to Help Reduce Fainting

Vasovagal syncope is a medical condition that can lead to fainting. This is caused by a temporary drop in the amount of blood that flows to the brain from a sudden drop in blood pressure or a drop in heart rate. It is considered to be the most common cause of fainting that becomes even more common with age.

Patients with vasovagal syncope often undergo a self-training program at home to improve their condition. In the training program, the patients are asked to stand against a wall without moving, twice a day for up to 30 minutes. After a few weeks of doing this daily, the patients are given the ‘head-up tilt test’ to determine whether the standing practice helped decrease their symptoms.

In a head-up tilt test, the patient begins lying flat in bed and the bed is gradually tilted to a maximum angle of 80 degrees. Gravity causes blood to pool in the legs, resulting in a blood pressure drop above the patient’s center of gravity. Baroreceptors sense the decrease in blood pressure and cause an increase in heart rate. In healthy individuals, although the blood pressure initially increases, the heart rate quickly returns to normal. In syncope patients, the heart rate remains high. While useful for diagnosis, the head-up tilt test is time-consuming, not available in all clinics, and carries the risk of inducing cardiac arrest.

As an alternative to the head-up tilt test, Hassan proposed a new way of determining whether the self-training program can help patients with syncope. She developed a model that uses a patient’s electrocardiogram (ECG) data, which are electrical signals from the heart, to predict heart rate changes and determine the efficacy of the home-based training program.

The data from her model can be used by clinicians to assess whether extended periods of standing can help decrease the amount of fainting episodes the patient experiences based on subsequent five-minute heart rate recordings, without the need to perform a head-up tilt test.

While the model can be used to determine heart rate changes at any time of day, relying only on the heart rate as an input is limiting. Hassan plans to further her work by including blood pressure as a parameter for the model.����

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Monitoring Our Emotions

Wearable sensors are already used to monitor health—heart rate sensors are commonly used to keep an eye on heart health and predict any adverse events. Further advances in sensors have also been used to recognize emotions using physiological signals. However, there is no universally accepted model for emotions, which Alskafi set out to change.

Emotions play a vital role in human behavior and psychology, exerting a powerful influence on processes such as perception, attention, decision-making, and learning. Emotions can be categorized by how they are felt, using valence, arousal and dominance. Valence is the positivity or negativity of an emotion; arousal is the level of excitement different emotions elicit; and dominance relates to feeling in or out of control in our response.

In healthcare, an individual profile that recognizes sources of stress, anxiety, depression or chronic diseases can be built by tracking emotions using wearable trackers. Alskafi recognized that while emotions are usually conveyed through body language and facial expressions, physiological manifestations of emotions could provide a more accurate representation. These are much harder to conceal and more difficult to manipulate when compared to body language, but some conditions cause people to present emotions differently. The physiological responses should be the same among all people as expression of emotions is shown through changes in heart rate, temperature and breathing patterns.

Alskafi fed these parameters into her model to classify physiological responses into different emotions. Anger and joy tend to be high arousal emotions, while sadness and reflection have low arousal levels. Fear and anger tend to be negative valence emotions, while joy has positive valence.

Her results found that the model performed best when it had fewer emotions to choose between, showing that the study can be used as a basis for further research in machine learning classification and algorithm development.

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Jade Sterling
Science Writer
20 September 2021

The post Student Biomedical Engineering Papers Accepted at EMBC appeared first on Khalifa University.