Conductive polymers: towards a smart biomaterial for tissue engineering.

Recent progress in electronic skin or e-skin research is broadly reviewed, focusing on technologies needed in three main applications: skin-attachable electronics, robotics, and prosthetics. First, since e-skin will be exposed to prolonged stresses of various kinds and needs to be conformally adhered to irregularly shaped surfaces, materials with intrinsic stretchability and self-healing properties are of great importance. Second, tactile sensing capability such as the detection of pressure, strain, slip, force vector, and temperature are important for health monitoring in skin attachable devices, and to enable object manipulation and detection of surrounding environment for robotics and prosthetics. For skin attachable devices, chemical and electrophysiological sensing and wireless signal communication are of high significance to fully gauge the state of health of users and to ensure user comfort. For robotics and prosthetics, large-area integration on 3D surfaces in a facile and scalable manner is critical. Furthermore, new signal processing strategies using neuromorphic devices are needed to efficiently process tactile information in a parallel and low power manner. For prosthetics, neural interfacing electrodes are of high importance. These topics are discussed, focusing on progress, current challenges, and future prospects.

https://onlinelibrary.wiley.com/doi/pdf/10.1002/adma.201904765

Electronic Skin: Recent Progress and Future Prospects for Skin‐Attachable Devices for Health Monitoring, Robotics, and Prosthetics

Hydrogels are hydrophilic polymer-based materials with high water content and physical characteristics that resemble the native extracellular matrix. Because of their remarkable properties, hydrogel systems are used for a wide range of biomedical applications, such as three-dimensional (3D) matrices for tissue engineering, drug-delivery vehicles, composite biomaterials, and as injectable fillers in minimally invasive surgeries. In addition, the rational design of hydrogels with controlled physical and biological properties can be used to modulate cellular functionality and tissue morphogenesis. Here, the development of advanced hydrogels with tunable physiochemical properties is highlighted, with particular emphasis on elastomeric, light-sensitive, composite, and shape-memory hydrogels. Emerging technologies developed over the past decade to control hydrogel architecture are also discussed and a number of potential applications and challenges in the utilization of hydrogels in regenerative medicine are reviewed. It is anticipated that the continued development of sophisticated hydrogels will result in clinical applications that will improve patient care and quality of life.

/pdf/25th-anniversary-article-rational-design-and-applications-of-4vstyfvewj.pdf

25th Anniversary Article: Rational Design and Applications of Hydrogels in Regenerative Medicine

Electrically conductive polymeric materials have recently attracted considerable interest from academic and industrial researchers to explore their potential in biomedical applications such as in biosensors, drug delivery systems, biomedical implants and tissue engineering. Conventional conductive homopolymers such as polypyrrole and PEDOT show promising conductivity for these applications, however their mechanical properties, biocompatibility and processability are often poor. This has led to more recent attention being directed towards conductive polymeric composites comprised of biostable/biocompatible polymers with dispersed conductive fillers such as graphene, carbon nanotubes and metallic nanoparticles. The major objective of this paper is to provide an up to date review of the recent investigations conducted in the development of conductive polymer composites focussing on the methods of their preparation, underlying concepts of their conductivity and the ways to tailor their properties. Furthermore, recent progress made in conventional conducting polymers and their composites/blends for biomedical applications is also discussed.

/pdf/electrically-conductive-polymers-and-composites-for-14kz3hoqk7.pdf

Electrically conductive polymers and composites for biomedical applications

Advances in hydrogel technology have unlocked unique and valuable capabilities that are being applied to a diverse set of translational applications. Hydrogels perform functions relevant to a range of biomedical purposes-they can deliver drugs or cells, regenerate hard and soft tissues, adhere to wet tissues, prevent bleeding, provide contrast during imaging, protect tissues or organs during radiotherapy, and improve the biocompatibility of medical implants. These capabilities make hydrogels useful for many distinct and pressing diseases and medical conditions and even for less conventional areas such as environmental engineering. In this review, we cover the major capabilities of hydrogels, with a focus on the novel benefits of injectable hydrogels, and how they relate to translational applications in medicine and the environment. We pay close attention to how the development of contemporary hydrogels requires extensive interdisciplinary collaboration to accomplish highly specific and complex biological tasks that range from cancer immunotherapy to tissue engineering to vaccination. We complement our discussion of preclinical and clinical development of hydrogels with mechanical design considerations needed for scaling injectable hydrogel technologies for clinical application. We anticipate that readers will gain a more complete picture of the expansive possibilities for hydrogels to make practical and impactful differences across numerous fields and biomedical applications.

Translational Applications of Hydrogels.

Poly(3,4-ethylenedioxythiophene)/multiwall carbon nanotube composite coatings for improving the stability of microelectrodes in neural prostheses applications.

In-situ electrochemical conversion of Na5V12O32@graphene for enhanced cycle stability in aqueous zinc ion batteries.

Platinum (Pt) implants coated with poly (3, 4-ethylenedioxythiophene)/carbon nanotube (PEDOT/CNT) composite films were implanted into the brain of rats, and the brain response was evaluated 6 weeks after the implantation. The surface morphology of Pt implants with and without the PEDOT/CNT coating was studied using scanning electron microscopy (SEM). After 6 weeks post-implantation, the expression of laminin (vascular endothelial marker) and neuronal nuclei (NeuN, neuronal marker) were evaluated by immnohistochemistry. It is revealed that the obvious improvements of the surface density of blood vessels and neurons aound the Pt implants with the coating, which were evidenced by laminin and NeuN staining in the zone within the distance of 150 μm to the implant interface. These results suggest the PEDOT/CNT composite films can improve the biocompatibility of the Pt electrodes while it is implanted in brain.

Platinum wire implants coated with PEDOT/carbon nanotube conducting polymer films in the brain of rats: A histological evaluation

Polydimethylsiloxane (PDMS) is a commonly used insulation/packaging material for implantable neural electrodes. Nevertheless, the PDMS-initiated tissue response would lead to the deterioration of the electrode performances post-implantation, owing to its intrinsic hydrophobic and cell-repellent surface. The conventional physical coatings by hydrophilic hydrogels or bioactive molecules are unable to maintain during the long-term implantation due to their low stability by physical adhesion. In this work, we first anchor both hydrophilic polyethylene glycol (PEG) and bioactive molecule poly-L-lysine (PLL) on the PDMS surface by chemical coupling to change the PDMS surface from hydrophobic and cell-repellent to hydrophilic and cell-adhesive. XPS tests indicate the chemically coupled modification layers are stable on the PDMS surface after experiencing a harsh rinse process. Contact angle measurements show that the use of PEG 600 with the moderate molecular weight results in the highest hydrophilicity for the resulting PDMS-PEG-PLL. PC12 cell evaluation results exhibit that the PDMS-PEG-PLL with PEG 600 leads to significantly larger cell adhesion area, more neurite number, and longer neurite length than the PDMS. The PDMS-PEG-PLL with PEG 600 featuring stable modification layers, high hydrophilicity, and superior cell affinity has great potential in stabilizing the neural electrode-tissue interface for the long-term implantation. Graphical abstract. 

/pdf/significantly-improved-cell-affinity-of-polydimethylsiloxane-1pc3u8ct.pdf

Significantly improved cell affinity of polydimethylsiloxane enabled by a surface-modified strategy with chemical coupling

Abstract Background Atherosclerosis is the common pathological basis for many cardiovascular and cerebrovascular diseases. The purpose of this study is to identify the diagnostic biomarkers related to atherosclerosis through machine learning algorithm. Methods Clinicopathological parameters and transcriptomics data were obtained from 4 datasets (GSE21545, GSE20129, GSE43292, GSE100927). A nonnegative matrix factorization algorithm was used to classify arteriosclerosis patients in GSE21545 dataset. Then, we identified prognosis-related differentially expressed genes (DEGs) between the subtypes. Multiple machine learning methods to detect pivotal markers. Discrimination, calibration and clinical usefulness of the predicting model were assessed using area under curve, calibration plot and decision curve analysis respectively. The expression level of the feature genes was validated in GSE20129, GSE43292, GSE100927. Results 2 molecular subtypes of atherosclerosis was identified, and 223 prognosis-related DEGs between the 2 subtypes were identified. These genes are not only related to epithelial cell proliferation, mitochondrial dysfunction, but also to immune related pathways. Least absolute shrinkage and selection operator, random forest, support vector machine- recursive feature elimination show that IL17C and ACOXL were identified as diagnostic markers of atherosclerosis. The prediction model displayed good discrimination and good calibration. Decision curve analysis showed that this model was clinically useful. Moreover, IL17C and ACOXL were verified in other 3 GEO datasets, and also have good predictive performance. Conclusion IL17C and ACOXL were diagnostic genes of atherosclerosis and associated with higher incidence of ischemic events. 

https://bmcbioinformatics.biomedcentral.com/counter/pdf/10.1186/s12859-023-05244-w

Nonnegative matrix factorization analysis and multiple machine learning methods identified IL17C and ACOXL as novel diagnostic biomarkers for atherosclerosis

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