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An ingestible bioimpedance sensing device for wireless monitoring of epithelial barriers

Existing gastrointestinal (GI) diagnostic tools are unable to non-invasively monitor mucosal tight junction integrity in vivo beyond the esophagus. In the GI tract, local inflammatory processes induce alterations in tight junction proteins, enhancing paracellular ion permeability. Although transepithelial electrical resistance (TEER) may be used in the laboratory to assess mucosal barrier integrity, there are no existing methodologies for characterizing tight junction dilation in vivo. Addressing this technology gap, intraluminal bioimpedance sensing may be employed as a localized, non-invasive surrogate to TEER electrodes used in cell cultures. Thus far, bioimpedance has only been implemented in esophagogastroduodenoscopy (EGD) due to the need for external electronics connections. In this work, we develop a novel, noise-resilient Bluetooth-enabled ingestible device for the continuous, non-invasive measurement of intestinal mucosal “leakiness.” As a proof-of-concept, we validate wireless impedance readout on excised porcine tissues in motion. Through an animal study, we demonstrate how the device exhibits altered impedance response to tight junction dilation induced on mice colonic tissue through calcium-chelator exposure. Device measurements are validated using standard benchtop methods for assessing mucosal permeability.

Evaluation of electrical impedance spectroscopy of bovine eyes for early detection of uveal melanoma

Uveal melanoma is the most common primary intraocular cancer in adults and is an aggressive malignancy with risk to vision and survival. Early detection and timely management of tumors may help preserve vision and reduce mortality rate but is challenging as many tumors are asymptomatic until they become large. Here, we studied the electrical properties of eyes to investigate a novel method for potentially detecting small intraocular tumors. We used finite element analysis to simulate the impact of uveal melanoma tumors on electrical impedance and current density in eye models. We also measured the impedance and current flow in the presence of inserted tissue simulating an intraocular tumor in enucleated bovine eyes and eyes in bovine head ex vivo. Our results showed that a 5 mm-diameter mass was detected inside a 32-mm diameter bovine eye by the impedance analyzer.

Acoustic impedance-based surface acoustic wave chip for gas leak detection and respiratory monitoring

Acoustic impedance enables many interesting acoustic applications. However, acoustic impedance for gas sensing is rare and difficult. Here we introduce a micro-nano surface acoustic wave (SAW) chip based on the acoustic impedance effect to achieve ultra-fast and wide-range gas sensing. We theoretically established the relationship between surface load acoustic impedance and SAW attenuation, and analyzed the influence of acoustic impedance on acoustic propagation loss under different gas/humidity media. Experimental measurements reveal that the differences in acoustic impedance generated by different gases trigger different acoustic attenuation, and can achieve wide-range (0–100 v/v%) gas monitoring, with ultra-fast response and recovery speeds reaching sub-second levels (t90 < 1 s, t10 < 0.5 s) and detection limit of ~1 v/v%. This capability can also be perfectly utilized for human respiratory monitoring, accurately reflecting respiratory status, frequency, and intensity. Consequently, the SAW chip based on the acoustic impedance effect provides a new solution for in-situ detection of gas leaks and precise monitoring of human respiration.

Image-based impedance spectroscopy for printed electronics

The field of printed electronics has been extensively researched for its versatility and scalability in flexible and large-area applications. Impedance is of great importance for the performance and reliability of electronics. However, its measurement requires electrical contacts, which makes it difficult on complex or bio-interfaces. Although the printing process is accessible, impedance characterization may be cumbersome, which can create a bottleneck during the manufacturing process. This paper reports the first effort at developing a convolutional neural network (CNN) based image regression model to replace impedance spectroscopy (IS). In our study, the CNN model learned the features of inkjet-printed electrode images that are dependent on the printing and sintering of nanomaterials and quantitatively predicted the resistance and capacitance of the equivalent circuit of the inkjet-printed lines. The image-based impedance spectroscopy (IIS) is expected to be the cornerstone as a revolutionary approach to electronics research and development enabled by deep neural networks.

Holistic AI analysis of hybrid cardiac perfusion images for mortality prediction

Low-dose computed tomography attenuation correction (CTAC) scans are used in hybrid myocardial perfusion imaging (MPI) for attenuation correction and coronary calcium scoring, and contain additional anatomic and pathologic information not utilized in clinical assessment. We seek to uncover the full potential of these scans utilizing a holistic artificial intelligence (AI) approach. A multi-structure model segmented 33 structures and quantified 15 radiomics features in each organ in 10,480 patients from 4 sites. Coronary calcium and epicardial fat measures were obtained from separate AI models. The area under the receiver-operating characteristic curves (AUC) for all-cause mortality prediction of the model utilizing MPI, CT, stress test, and clinical features was 0.80 (95% confidence interval [0.74–0.87]), which was higher than for coronary calcium (0.64 [0.57–0.71]) or perfusion (0.62 [0.55–0.70]), with p < 0.001 for both. A comprehensive multimodality approach can significantly improve mortality prediction compared to MPI information alone in patients undergoing hybrid MPI.

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