Engineering Analysis of Non-Braided Polycaprolactone Bioresorbable Flow Diverters for Aneurysms.

This paper reports a nonbraided, bioresorbable polycaprolactone (PCL) flow diverter (FD) for the endovascular treatment of aneurysms. Bioresorbable FDs can reduce the risk associated with the permanent metallic FDs as they are resorbed by the body after curing of aneurysms. PCL FDs were designed and fabricated using an in-house hybrid electromelt spinning-fused deposition fabrication unit. Flow diverter's properties, surface qualities, and mechanical characteristics of PCL FDs of 50%, 60%, and 70% porosities were studied using scanning electron microscope (SEM), atomic force microscopy (AFM), and high precision universal testing machine (UTM). The deployability through a clinically relevant catheter was demonstrated in a PDMS aneurysm model. The angiographic visibility of the developed PCL FDs was evaluated using BaSO4 and Bi2O3 coatings of various concentration. The average strut thicknesses were 74.12 ± 6.63 µm, 63.07 ± 1.26 µm, and 56.82 ± 2.09 µm for PCL FDs with 50%, 60%, and 70% porosities, respectively. They average pore areas for the 50%, 60% and 70% porosities FDs were 0.055 ± 0.0056 mm2, 0. 0605 ± 0.0065 mm2, and 0.0712 ± 0.012 mm2, respectively. The surface quality was great with an RMS roughness value of 14.45 nm. The tensile, radial strength, and flexibility were found to be satisfactory and comparable to the nonbraided coronary stents. The developed PCL FDs were highly flexible and demonstrated to be deployable through conventional delivery system as low as 4 Fr catheters in a PDMS aneurysm model. The visibility under X-ray increases with the increasing concentration of coating materials BaSO4 and Bi2O3. The visibility intensity was slightly higher with Bi2O3 coating of PCL FDs. The overall results of the engineering analysis of the developed nonbraided PCL FDs are promising.

A physiological signal compression approach using optimized Spindle Convolutional Auto-encoder in mHealth applications.

Background and Objectives: The COVID-19 pandemic manifested the need of developing robust digital platforms for facilitating healthcare services such as consultancy, clinical therapies, real time remote monitoring, early diagnosis and future predictions. Innovations made using technologies such as Internet of Things (IoT), edge computing, cloud computing and artificial intelligence are helping address this crisis. The urge for remote monitoring, symptom analysis and early detection of diseases lead to tremendous increase in the deployment of wearable sensor devices. They facilitate seamless gathering of physiological data such as electrocardiogram (ECG) signals, respiration traces (RESP), galvanic skin response (GSR), pulse rate, body temperature, photoplethysmograms (PPG), oxygen saturation (SpO2) etc. For diagnosis and analysis purpose, the gathered data needs to be stored. Wearable devices operate on batteries and have a memory constraint. In mHealth application architectures, this gathered data is hence stored on cloud based servers. While transmitting data from wearable devices to cloud servers via edge devices, a lot of energy is consumed. This paper proposes a deep learning based compression model SCAElite that reduces the data volume, enabling energy efficient transmission. Results: Stress Recognition in Automobile Drivers dataset and MIT-BIH dataset from PhysioNet are used for validation of algorithm performance. The model achieves a compression ratio of up to 300 fold with reconstruction errors within 8% over the stress recognition dataset and 106.34-fold with reconstruction errors within 8% over the MIT-BIH dataset. The computational complexity of SCAElite is 51.65% less compared to state-of-the-art deep compressive model. Conclusion: It is experimentally validated that SCAElite guarantees a high compression ratio with good quality restoration capabilities for physiological signal compression in mHealth applications. It has a compact architecture and is computationally more efficient compared to state-of-the-art deep compressive model.

Incorporation of Mycobacteriophage Fulbright into Polycaprolactone Electrospun Nanofiber Wound Dressing.

The Genus Mycobacterium includes pathogens known to cause disease in mammals such as tuberculosis (Mycobacterium tuberculosis) and skin infections (M. abscessus). M. smegmatis is a model bacterium that can cause opportunistic infections in human tissues and, rarely, a respiratory disease. Due to the emergence of multidrug-resistant bacteria, phage therapy is potentially an alternative way of treating these bacterial infections. As bacteriophages are specific to their bacterial host, it ensures that the normal flora is unharmed. Fulbright is a mycobacteriophage that infects the host bacteria M. smegmatis. The main goal of this study is to incorporate Mycobacteriophage Fulbright into a polycaprolactone (PCL) nanofiber and test its antimicrobial effect against the host bacteria, M. smegmatis. Stability tests conducted over 7 days showed that the phage titer does not decrease when in contact with PCL, making it a promising vehicle for phage delivery. Antimicrobial assays showed that PCL_Fulbright effectively reduces bacterial concentration after 24 h of contact. In addition, when stored at -20 °C, the phage remains viable for up to eleven months in the fiber. Fulbright addition on the nanofibrous mats resulted in an increase in water uptake and decrease in the mechanical properties (strength and Young's modulus) of the membranes, indicating that the presence of phage Fulbright can greatly enhance the physical and mechanical properties of the PCL. Cytotoxicity assays showed that PCL_Fulbright is not cytotoxic to Balbc/3T3 mouse embryo fibroblast cell lines; thus, phage-incorporated PCL is a promising alternative to antibiotics in treating skin infections.

Design and Analysis of a Biodegradable Polycaprolactone Flow Diverting Stent for Brain Aneurysms.

The flow diverting stent (FDS) has become a promising endovascular device for the treatment of aneurysms. This research presents a novel biodegradable and non-braided Polycaprolactone (PCL) FDS. The PCL FDS was designed and developed using an in-house fabrication unit and coated on two ends with BaSO4 for angiographic visibility. The mechanical flexibility and quality of FDS surfaces were examined with the UniVert testing machine, scanning electron microscope (SEM), and 3D profilometer. Human umbilical vein endothelial cell (HUVEC) adhesion, proliferation, and cell morphology studies on PCL FDS were performed. The cytotoxicity and NO production by HUVECs with PCL FDS were also conducted. The longitudinal tensile, radial, and bending flexibility were found to be 1.20 ± 0.19 N/mm, 0.56 ± 0.11 N/mm, and 0.34 ± 0.03 N/mm, respectively. The FDS was returned to the original shape and diameter after repeated compression and bending without compromising mechanical integrity. Results also showed that the proliferation and adhesion of HUVECs on the FDS surface increased over time compared to control without FDS. Lactate dehydrogenase (LDH) release and NO production showed that PCL FDS were non-toxic and satisfactory. Cell morphology studies showed that HUVECs were elongated to cover the FD surface and developed an endothelial monolayer. This study is a step forward toward the development and clinical use of biodegradable flow diverting stents for endovascular treatment of the aneurysm.