Machine learning-directed electrical impedance tomography to predict metabolically vulnerable plaques.

The characterization of atherosclerotic plaques to predict their vulnerability to rupture remains a diagnostic challenge. Despite existing imaging modalities, none have proven their abilities to identify metabolically active oxidized low-density lipoprotein (oxLDL), a marker of plaque vulnerability. To this end, we developed a machine learning-directed electrochemical impedance spectroscopy (EIS) platform to analyze oxLDL-rich plaques, with immunohistology serving as the ground truth. We fabricated the EIS sensor by affixing a six-point microelectrode configuration onto a silicone balloon catheter and electroplating the surface with platinum black (PtB) to improve the charge transfer efficiency at the electrochemical interface. To demonstrate clinical translation, we deployed the EIS sensor to the coronary arteries of an explanted human heart from a patient undergoing heart transplant and interrogated the atherosclerotic lesions to reconstruct the 3D EIS profiles of oxLDL-rich atherosclerotic plaques in both right coronary and left descending coronary arteries. To establish effective generalization of our methods, we repeated the reconstruction and training process on the common carotid arteries of an unembalmed human cadaver specimen. Our findings indicated that our DenseNet model achieves the most reliable predictions for metabolically vulnerable plaque, yielding an accuracy of 92.59% after 100 epochs of training.

A study on computer vision for facial emotion recognition.

Artificial intelligence has been successfully applied in various fields, one of which is computer vision. In this study, a deep neural network (DNN) was adopted for Facial emotion recognition (FER). One of the objectives in this study is to identify the critical facial features on which the DNN model focuses for FER. In particular, we utilized a convolutional neural network (CNN), the combination of squeeze-and-excitation network and the residual neural network, for the task of FER. We utilized AffectNet and the Real-World Affective Faces Database (RAF-DB) as the facial expression databases that provide learning samples for the CNN. The feature maps were extracted from the residual blocks for further analysis. Our analysis shows that the features around the nose and mouth are critical facial landmarks for the neural networks. Cross-database validations were conducted between the databases. The network model trained on AffectNet achieved 77.37% accuracy when validated on the RAF-DB, while the network model pretrained on AffectNet and then transfer learned on the RAF-DB results in validation accuracy of 83.37%. The outcomes of this study would improve the understanding of neural networks and assist with improving computer vision accuracy.

An Ex Vivo Study of Outward Electrical Impedance Tomography (OEIT) for Intravascular Imaging.

OBJECTIVE: Atherosclerosis is a chronic immuno-inflammatory condition emerging in arteries and considered the cause of a myriad of cardiovascular diseases. Atherosclerotic lesion characterization through invasive imaging modalities is essential in disease evaluation and determining intervention strategy. Recently, electrical properties of the lesions have been utilized in assessing its vulnerability mainly owing to its capability to differentiate lipid content existing in the lesion, albeit with limited detection resolution. Electrical impedance tomography is the natural extension of conventional spectrometric measurement by incorporating larger number of interrogating electrodes and advanced algorithm to achieve imaging of target objects and thus provides significantly richer information. It is within this context that we develop Outward Electrical Impedance Tomography (OEIT), aimed at intravascular imaging for atherosclerotic lesion characterization. METHODS: We utilized flexible electronics to establish the 32-electrode OEIT device with outward facing configuration suitable for imaging of vessels. We conducted comprehensive studies through simulation model and ex vivo setup to demonstrate the functionality of OEIT. RESULTS: Quantitative characterization for OEIT regarding its proximity sensing and conductivity differentiation was achieved using well-controlled experimental conditions. Imaging capability for OEIT was further verified with phantom setup using porcine aorta to emulate in vivo environment. CONCLUSION: We have successfully demonstrated a novel tool for intravascular imaging, OEIT, with unique advantages for atherosclerosis detection. SIGNIFICANCE: This study demonstrates for the first time a novel electrical tomography-based platform for intravascular imaging, and we believe it paves the way for further adaptation of OEIT for intravascular detection in more translational settings and offers great potential as an alternative imaging tool for medical diagnosis.

Electrical impedance tomography for non-invasive identification of fatty liver infiltrate in overweight individuals.

Non-alcoholic fatty liver disease (NAFLD) is one of the most common causes of cardiometabolic diseases in overweight individuals. While liver biopsy is the current gold standard to diagnose NAFLD and magnetic resonance imaging (MRI) is a non-invasive alternative still under clinical trials, the former is invasive and the latter costly. We demonstrate electrical impedance tomography (EIT) as a portable method for detecting fatty infiltrate. We enrolled 19 overweight subjects to undergo liver MRI scans, followed by EIT measurements. The MRI images provided the a priori knowledge of the liver boundary conditions for EIT reconstruction, and the multi-echo MRI data quantified liver proton-density fat fraction (PDFF%) to validate fat infiltrate. Using the EIT electrode belts, we circumferentially injected pairwise current to the upper abdomen, followed by acquiring the resulting surface-voltage to reconstruct the liver conductivity. Pearson's correlation analyses compared EIT conductivity or MRI PDFF with body mass index, age, waist circumference, height, and weight variables. We reveal that the correlation between liver EIT conductivity or MRI PDFF with demographics is statistically insignificant, whereas liver EIT conductivity is inversely correlated with MRI PDFF (R = -0.69, p = 0.003, n = 16). As a pilot study, EIT conductivity provides a portable method for operator-independent and cost-effective detection of hepatic steatosis.

Using the phase change of a reflected microwave to detect a human subject behind a barrier.

In a pulsed radar system, the amplitude and sign of the echo from a particular target will depend on the phase of the echo signal relative to that of the local oscillator signal. If the wavelength of the radar signal is very short, the phase of the echo can change greatly if the target moves even slightly. Based on this physical behavior, the pulsed radar system can serve as a life-detection system to detect a human subject's movements, which include breathing and heartbeat. In this paper, a pulsed microwave life-detection system was developed from a pulsed training radar system to successfully detect the presence of human subjects behind a simulated earthquake rubble wall. The sampled echo signals from the background noise, a dummy, and a female human subject are presented directly in the time domain without being transferred into the frequency domain, differentiating this work from recent works by other authors. Furthermore, we also demonstrate several superiorities of a pulsed system over and above the original continuous-wave approach with the experimental results.

Generation of clade- and symbiont-specific antibodies to characterize marker molecules during Cnidaria-Symbiodinium endosymbiosis.

The endosymbiosis between cnidarians and dinoflagellates is responsible for the formation of coral reefs. Changes in molecules have been identified during the process of cnidaria-Symbiodinium endosymbiosis. However, the complexity of the molecular interaction has prevented the establishment of a mechanistic explanation of cellular regulation in this mutualistic symbiosis. To date, no marker molecules have been identified to specifically represent the symbiotic status. Because the endosymbiotic association occurs in the symbiotic gastrodermal cells (SGCs), whole cells of isolated SGCs were used as an antigen to generate monoclonal antibodies (mAb) to screen possible molecular candidates of symbiotic markers. The results showed that one of the generated monoclonal antibodies, 2-6F, specifically recognized clade C symbiotic Symbiodinium but not its free-living counterpart or other Symbiodinium clades. The expression levels of 2-6F mAb-recognized proteins are highly correlated with the symbiotic status, and these proteins were characterized as N-linked glycoproteins via treatment with peptide N-glycosidase F. Furthermore, their glycan moieties were markedly different from those of free-living Symbiodinium, potentially suggesting host regulation of post-translational modification. Consequently, the 2-6F mAb can be used to detect the symbiotic state of corals and investigate the complex molecular interactions in cnidaria-Symbiodinium endosymbiosis.

Membrane labeling of coral gastrodermal cells by biotinylation: the proteomic identification of surface proteins involving cnidaria-dinoflagellate endosymbiosis.

The cellular and molecular-scale processes underlying the stability of coral-Symbiodinium endosymbioses remain unclear despite decades of investigation. As the coral gastroderm is the only tissue layer characterized by this unique symbiotic association, the membranes of these symbiotic gastrodermal cells (SGCs) may play important roles in the initiation and maintenance of the endosymbiosis. In order to elucidate the interactions between the endosymbiotic dinoflagellates and their coral hosts, a thorough characterization of SGC membranes is therefore required. Cell surface proteins of isolated SGCs were biotinylated herein by a cell impermeant agent, biotin-XX sulfosuccinimidyl ester. The in situ distribution of these biotinylated proteins was uncovered by both fluorescence and transmission electron microscopic imaging of proteins bound to Alexa Fluor® 488-conjugated streptavidin. The identity of these proteins was then determined by two-dimensional gel electrophoresis followed by liquid chromatography-tandem mass spectrometry. Nineteen (19) proteins were identified, and they are known to be involved in the molecular chaperone/stress response, cytoskeletal remodeling, and energy metabolism. These results not only reveal the molecular characters of the host SGC membrane, but also provide critical insight into understanding the possible role of host membranes in this ecologically important endosymbiotic association.