Gene therapy for CNS disorders: modalities, delivery and translational challenges.

Gene therapy is emerging as a powerful tool to modulate abnormal gene expression, a hallmark of most CNS disorders. The transformative potentials of recently approved gene therapies for the treatment of spinal muscular atrophy (SMA), amyotrophic lateral sclerosis (ALS) and active cerebral adrenoleukodystrophy are encouraging further development of this approach. However, most attempts to translate gene therapy to the clinic have failed to make it to market. There is an urgent need not only to tailor the genes that are targeted to the pathology of interest but to also address delivery challenges and thereby maximize the utility of genetic tools. In this Review, we provide an overview of gene therapy modalities for CNS diseases, emphasizing the interconnectedness of different delivery strategies and routes of administration. Important gaps in understanding that could accelerate the clinical translatability of CNS genetic interventions are addressed, and we present lessons learned from failed clinical trials that may guide the future development of gene therapies for the treatment and management of CNS disorders.

Bioengineered amyloid peptide for rapid screening of inhibitors against main protease of SARS-CoV-2.

The coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) has evoked a worldwide pandemic. As the emergence of variants has hampered the neutralization capacity of currently available vaccines, developing effective antiviral therapeutics against SARS-CoV-2 and its variants becomes a significant challenge. The main protease (Mpro) of SARS-CoV-2 has received increased attention as an attractive pharmaceutical target because of its pivotal role in viral replication and proliferation. Here, we generated a de novo Mpro-inhibitor screening platform to evaluate the efficacies of Mpro inhibitors based on Mpro cleavage site-embedded amyloid peptide (MCAP)-coated gold nanoparticles (MCAP-AuNPs). We fabricated MCAPs comprising an amyloid-forming sequence and Mpro-cleavage sequence, mimicking in vivo viral replication process mediated by Mpro. By measuring the proteolytic activity of Mpro and the inhibitory efficacies of various drugs, we confirmed that the MCAP-AuNP-based platform was suitable for rapid screening potential of Mpro inhibitors. These results demonstrated that our MCAP-AuNP-based platform has great potential for discovering Mpro inhibitors and may accelerate the development of therapeutics against COVID-19.

Progress and challenges in intravesical drug delivery.

INTRODUCTION: Intravesical drug delivery (IDD) has gained recognition as a viable approach for treating bladder-related diseases over the years. However, it comes with its set of challenges, including voiding difficulties and limitations in mucosal and epithelial penetration. These challenges lead to drug dilution and clearance, resulting in poor efficacy. Various strategies for drug delivery have been devised to overcome these issues, all aimed at optimizing drug delivery. Nevertheless, there has been minimal translation to clinical settings. AREAS COVERED: This review provides a detailed description of IDD, including its history, advantages, and challenges. It also explores the physical barriers encountered in IDD, such as voiding, mucosal penetration, and epithelial penetration, and discusses current strategies for overcoming these challenges. Additionally, it offers a comprehensive roadmap for advancing IDD into clinical trials. EXPERT OPINION: Physical bladder barriers and limitations of conventional treatments result in unsatisfactory efficacy against bladder diseases. Nevertheless, substantial recent efforts in this field have led to significant progress in overcoming these challenges and have raised important attributes for an optimal IDD system. However, there is still a lack of well-defined steps in the workflow to optimize the IDD system for clinical settings, and further research is required to establish more comprehensive in vitro and in vivo models to expedite clinical translation.

Advancing diagnostic efficacy using a computer vision-assisted lateral flow assay for influenza and SARS-CoV-2 detection.

Lateral flow assays (LFAs) have emerged as indispensable tools for point-of-care testing during the pandemic era. However, the interpretation of results through unassisted visual inspection by untrained individuals poses inherent limitations. In our study, we propose a novel approach that combines computer vision (CV) and lightweight machine learning (ML) to overcome these limitations and significantly enhance the performance of LFAs. By incorporating CV-assisted analysis into the LFA assay, we achieved a remarkable three-fold improvement in analytical sensitivity for detecting Influenza A and for SARS-CoV-2 detection. The obtained R2 values reached approximately 0.95, respectively, demonstrating the effectiveness of our approach. Moreover, the integration of CV techniques with LFAs resulted in a substantial amplification of the colorimetric signal specifically for COVID-19 positive patient samples. Our proposed approach, which incorporates a simple machine learning algorithm, provides substantial enhancements in assay sensitivity, improving diagnostic efficacy and accessibility of point-of-care testing without requiring significant additional resources. Moreover, the simplicity of the machine learning algorithm enables its standalone use on a mobile phone, further enhancing its practicality for point-of-care testing.

PCR-like performance of rapid test with permselective tunable nanotrap.

Highly sensitive rapid testing for COVID-19 is essential for minimizing virus transmission, especially before the onset of symptoms and in asymptomatic cases. Here, we report bioengineered enrichment tools for lateral flow assays (LFAs) with enhanced sensitivity and specificity (BEETLES2), achieving enrichment of SARS-CoV-2 viruses, nucleocapsid (N) proteins and immunoglobulin G (IgG) with 3-minute operation. The limit of detection is improved up to 20-fold. We apply this method to clinical samples, including 83% with either intermediate (35%) or low viral loads (48%), collected from 62 individuals (n = 42 for positive and n = 20 for healthy controls). We observe diagnostic sensitivity, specificity, and accuracy of 88.1%, 100%, and 91.9%, respectively, compared with commercial LFAs alone achieving 14.29%, 100%, and 41.94%, respectively. BEETLES2, with permselectivity and tunability, can enrich the SARS-CoV-2 virus, N proteins, and IgG in the nasopharyngeal/oropharyngeal swab, saliva, and blood serum, enabling reliable and sensitive point-of-care testing, facilitating fast early diagnosis.

Caco-2 cell-derived biomimetic electrochemical biosensor for cholera toxin detection.

Cholera is a highly contagious and lethal waterborne disease induced by an infection with Vibrio cholerae (V. cholerae) secreting cholera toxin (CTx). Cholera toxin subunit B (CTxB) from the CTx specifically binds with monosialo-tetra-hexosyl-ganglioside (GM1) found on the exterior cell membrane of an enterocyte. Bioinspired by the pathological process of CTx, we developed an electrochemical biosensor with GM1-expressing Caco-2 cell membrane (CCM) on the electrode surface. Briefly, the electrode surface was functionalized with CCM using the vesicle fusion method. We determined the CTxB detection performances of Caco-2 cell membrane-coated biosensor (CCB) using electrochemical impedance spectroscopy (EIS). the CCB had an excellent limit of detection of ∼11.46 nM and a detection range spanning 100 ng/mL - 1 mg/mL. In addition, the CCB showed high selectivity against various interfering molecules, including abundant constituents of intestinal fluid and various bacterial toxins. The long-term stability of the CCBs was also verified for 3 weeks using EIS. Overall, the CCB has excellent potential for practical use such as point-of-care and cost-effective testing for CTxB detection in developing countries.

Proteolysis-driven proliferation and rigidification of pepsin-resistant amyloid fibrils.

Proteolysis of amyloids is related to prevention and treatment of amyloidosis. What if the conditions for proteolysis were the same to those for amyloid formation? For example, pepsin, a gastric protease is activated in an acidic environment, which, interestingly, is also a condition that induces the amyloid formation. Here, we investigate the competition reactions between proteolysis and synthesis of amyloid under pepsin-activated conditions. The changes in the quantities and nanomechanical properties of amyloids after pepsin treatment were examined by fluorescence assay, circular dichroism and atomic force microscopy. We found that, in the case of pepsin-resistant amyloid, a secondary reaction can be accelerated, thereby proliferating amyloids. Moreover, after this reaction, the amyloid became 32.4 % thicker and 24.2 % stiffer than the original one. Our results suggest a new insight into the proteolysis-driven proliferation and rigidification of pepsin-resistant amyloids.

Biomimetically Engineered Amyloid-Shelled Gold Nanocomplexes for Discovering α-Synuclein Oligomer-Degrading Drugs.

The assembly of α-synuclein (αS) oligomers is recognized as the main pathological driver of synucleinopathies. While the elimination of toxic αS oligomers shows promise for the treatment of Parkinson's disease (PD), the discovery of αS oligomer degradation drugs has been hindered by the lack of proper drug screening tools. Here, we report a drug screening platform for monitoring the efficacy of αS-oligomer-degrading drugs using amyloid-shelled gold nanocomplexes (ASGNs). We fabricate ASGNs in the presence of dopamine, mimicking the in vivo generation process of pathological αS oligomers. To test our platform, the first of its kind for PD drugs, we use αS-degrading proteases and various small molecular substances that have shown efficacy in PD treatment. We demonstrate that the ASGN-based in vitro platform has strong potential to discover effective αS-oligomer-targeting drugs, and thus it may reduce the attrition problem in drug discovery for PD treatment.

Scalable Functionalization of Polyaniline-Grafted rGO Field-Effect Transistors for a Highly Sensitive Enzymatic Acetylcholine Biosensor.

For decades, acetylcholine (Ach) has been considered a critical biomarker for several degenerative brain diseases, including Alzheimer's, Parkinson's disease, Huntington's disease, and schizophrenia. Here, we propose a wafer-scale fabrication of polyaniline (PAni)-grafted graphene-based field-effect transistors (PGFET) and their biosensing applications for highly sensitive and reliable real-time monitoring of Ach in flow configuration. The grafted PAni provides suitable electrostatic binding sites for enzyme immobilization and enhances the pH sensitivity (2.68%/pH), compared to that of bare graphene-FET (1.81%/pH) for a pH range of 3-9 without any pH-hysteresis. We further evaluated the PGFET's sensing performance for Ach detection with a limit of detection at the nanomolar level and significantly improved sensitivity (~103%) in the concentration range of 108 nM to 2 mM. Moreover, the PGFET exhibits excellent selectivity against various interferences, including glucose, ascorbic acid, and neurotransmitters dopamine and serotonin. Finally, we investigated the effects of an inhibitor (rivastigmine) on the AchE activity of the PGFET. From the results, we demonstrated that the PGFET has great potential as a real-time drug-screening platform by monitoring the inhibitory effects on enzymatic activity.

Nanoelectrokinetic-assisted lateral flow assay for COVID-19 antibody test.

A lateral flow assay (LFA) platform is a powerful tool for point-of-care testing (POCT), especially for self-testing. Although the LFA platform provides a simple and disposable tool for Coronavirus disease of 2019 (COVID-19) antigen (Ag) and antibody (Ab) screening tests, the lower sensitivity for low virus titers has been a bottleneck for practical applications. Herein, we report the combination of a microfluidic paper-based nanoelectrokinetic (NEK) preconcentrator and an LFA platform for enhancing the sensitivity and limit of detection (LOD). Biomarkers were electrokinetically preconcentrated onto a specific layer using the NEK preconcentrator, which was then coupled with LFA diagnostic devices for enhanced performance. Using this nanoelectrokinetic-assisted LFA (NEK-LFA) platform for self-testing, the severe acute respiratory syndrome coronavirus 2 Immunoglobulin G (SARS-CoV-2 IgG) sample was preconcentrated from serum samples. After preconcentration, the LOD of the LFA was enhanced by 32-fold, with an increase in analytical sensitivity (16.4%), which may offer a new opportunity for POCT and self-testing, especially in the COVID-19 pandemic and endemic global context.

Surface Functionalization of Enzyme-Coronated Gold Nanoparticles with an Erythrocyte Membrane for Highly Selective Glucose Assays.

Colorimetric glucose sensors using enzyme-coronated gold nanoparticles have been developed for high-throughput assays to monitor the blood glucose levels of diabetic patients. Although those sensors have shown sensitivity and wide linear detection ranges, they suffer from poor selectivity and stability in detecting blood glucose, which has limited their practical use. To address this limitation, herein, we functionalized glucose-oxidase-coronated gold nanoparticles with an erythrocyte membrane (EM-GOx-GNPs). Because the erythrocyte membrane (EM) selectively facilitates the permeation of glucose via glucose transporter-1 (GLUT1), the functionalization of GOx-GNPs with EM improved the stability, selectivity (3.3- to 15.8-fold higher), and limit of detection (LOD). Both membrane proteins, GLUT1 and aquaporin-1 (AQP1), on EM were shown to be key components for selective glucose detection by treatment with their inhibitors. Moreover, we demonstrated the stability of EM-GOx-GNPs in high-antioxidant-concentration conditions, under long-term storage (∼4 weeks) and a freeze-thaw cycle. Selectivity of the EM-GOx-GNPs against other saccharides was increased, which improved the LOD in phosphate-buffered saline and human serum. Our results indicated that the functionalization of colorimetric glucose sensors with EM is beneficial for improving selectivity and stability, which may make them candidates for use in a practical glucose sensor.

Effects of mechanical properties of gelatin methacryloyl hydrogels on encapsulated stem cell spheroids for 3D tissue engineering.

Cell spheroids are three-dimensional cell aggregates that have been widely employed in tissue engineering. Spheroid encapsulation has been explored as a method to enhance cell-cell interactions. However, the effect of hydrogel mechanical properties on spheroids, specifically soft hydrogels (<1 kPa), has not yet been studied. In this study, we determined the effect of encapsulation of stem cell spheroids by hydrogels crosslinked with different concentrations of gelatin methacryloyl (GelMA) on the functions of the stem cells. To this end, human adipose-derived stem cell (ADSC) spheroids with a defined size were prepared, and spheroid-laden hydrogels with various concentrations (5, 10, 15%) were fabricated. The apoptotic index of cells from spheroids encapsulated in the 15% hydrogel was high. The migration distance was five-fold higher in cells encapsulated in the 5% hydrogel than the 10% hydrogel. After 14 days of culture, cells from spheroids in the 5% hydrogel were observed to have spread and proliferated. Osteogenic factor and pro-angiogenic factor production in the 15% hydrogel was high. Collectively, our results indicate that the functionality of spheroids can be regulated by the mechanical properties of hydrogel, even under 1 kPa. These results indicate that spheroid-laden hydrogels are suitable for use in 3D tissue construction.

Erythrocyte-camouflaged biosensor for α-hemolysin detection.

Without appropriate treatment, Staphylococcus aureus (S. aureus) infection can cause life-threatening diseases (e.g., meningitis, pneumonia, bacteremia, and sepsis). However, a rapid and accurate point-of-care test for the infection remains challenging. The bacterium secretes α-hemolysin (Hla), which spontaneously binds to the cell membrane of erythrocyte, and eventually lyses the cell via pore formation. Taking advantage of this phenomenon, we apply the erythrocyte membrane (EM) extracted from human whole blood as a novel bioreceptor for detecting Hla, fabricating erythrocyte-camouflaged biosensors (ECB) by coating EM onto electrochemical impedance electrodes. We verify the existence of EM on the ECB by using confocal microscopy and atomic force microscopy. We demonstrate that ECBs sensitively detect Hla spiked in phosphate buffer saline and human serum. Also, the sensor shows higher sensitivity to Hla than major blood proteins, such as human serum albumin, fibrinogen, and gamma globulin. Specifically, the signal intensities for Hla are 8.8-12.7 times higher than those in the same concentration of those blood proteins. The detection limit of the ECB for Hla is 1.9 ng/ml while the dynamic range is 0.0001-1 mg/ml. Finally, we validate the constant sensing performance of ECB with 99.0 ± 5.6% accuracy for 35 days of storage.

Nanoindentation for Monitoring the Time-Variant Mechanical Strength of Drug-Loaded Collagen Hydrogel Regulated by Hydroxyapatite Nanoparticles.

Hydroxyapatite nanoparticle-complexed collagen (HAP/Col) hydrogels have been widely used in biomedical applications as a scaffold for controlled drug release (DR). The time-variant mechanical properties (Young's modulus, E) of HAP/Col hydrogels are highly relevant to the precise and efficient control of DR. However, the correlation between the DR and the E of hydrogels remains unclear because of the lack of a nondestructive and continuous measuring system. To reveal the correlations, herein, we investigate the time-variant behavior of E for HAP/Col hydrogels during 28 days using the atomic force microscopy (AFM) nanoindentation technique. The initial E of hydrogels was controlled from 200 to 9000 Pa by the addition of HAPs. Subsequently, we analyzed the relationship between the DR of the hydrogels and the changes in their mechanical properties (ΔE) during hydrogel degradation. Interestingly, the higher the initial E value of HAP/Col hydrogels is, the higher is the rate of hydrogel degradation over time. However, the DR of hydrogels with higher initial E appeared to be significantly delayed by up to 40% at a maximum. The results indicate that adding an appropriate amount of HAPs into hydrogels plays a crucial role in determining the initial E and their degradation rate, which can contribute to the properties that prolong DR. Our findings may provide insights into designing hydrogels for biomedical applications such as bone regeneration and drug-delivery systems.

Plasmonic nanoparticle amyloid corona for screening Aß oligomeric aggregate-degrading drugs.

The generation of toxic amyloid ß (Aß) oligomers is a central feature of the onset and progression of Alzheimer's disease (AD). Drug discoveries for Aß oligomer degradation have been hampered by the difficulty of Aß oligomer purification and a lack of screening tools. Here, we report a plasmonic nanoparticle amyloid corona (PNAC) for quantifying the efficacy of Aß oligomeric aggregate-degrading drugs. Our strategy is to monitor the drug-induced degradation of oligomeric aggregates by analyzing the colorimetric responses of PNACs. To test our strategy, we use Aß-degrading proteases (protease XIV and MMP-9) and subsequently various small-molecule substances that have shown benefits in the treatment of AD. We demonstrate that this strategy with PNAC can identify effective drugs for eliminating oligomeric aggregates. Thus, this approach presents an appealing opportunity to reduce attrition problems in drug discovery for AD treatment.

Sequential dual-drug delivery of BMP-2 and alendronate from hydroxyapatite-collagen scaffolds for enhanced bone regeneration.

The clinical use of bioactive molecules in bone regeneration has been known to have side effects, which result from uncontrolled and supraphysiological doses. In this study, we demonstrated the synergistic effect of two bioactive molecules, bone morphogenic protein-2 (BMP-2) and alendronate (ALN), by releasing them in a sequential manner. Collagen-hydroxyapatite composite scaffolds functionalized using BMP-2 are loaded with biodegradable microspheres where ALN is encapsulated. The results indicate an initial release of BMP-2 for a few days, followed by the sequential release of ALN after two weeks. The composite scaffolds significantly increase osteogenic activity owing to the synergistic effect of BMP-2 and ALN. Enhanced bone regeneration was identified at eight weeks post-implantation in the rat 8-mm critical-sized defect. Our findings suggest that the sequential delivery of BMP-2 and ALN from the scaffolds results in a synergistic effect on bone regeneration, which is unprecedented. Therefore, such a system exhibits potential for the application of cell-free tissue engineering.

Coagulation-Inspired Direct Fibrinogen Assay Using Plasmonic Nanoparticles Functionalized with Red Blood Cell Membranes.

The fast measurement of fibrinogen is essential in evaluating life-threatening sepsis and cardiovascular diseases. Here, we aim to utilize biomimetic plasmonic Au nanoparticles using red blood cell membranes (RBCM-AuNPs) and demonstrate nanoscale coagulation-inspired fibrinogen detection via cross-linking between RBCM-AuNPs. The proposed biomimetic RBCM-AuNPs are highly suitable for fibrinogen detection because hemagglutination, occurring in the presence of fibrinogen, induces a shift in the localized surface plasmon resonance of the NPs. Specifically, when the two ends of the fibrinogen protein are bound to receptors on separate RBCM-AuNPs, cross-linking of the RBCM-AuNPs occurs, yielding a corresponding plasmon shift within 10 min. This coagulation-inspired fibrinogen detection method, with a low sample volume, high selectivity, and high speed, could facilitate the diagnosis of sepsis and cardiovascular diseases.

Bio-Inspired Electronic Textile Yarn-Based NO2 Sensor Using Amyloid-Graphene Composite.

Graphene-based e-textile gas sensors have received significant attention as wearable electronic devices for human healthcare and environmental monitoring. Theoretically, more the attached graphene on the devices, better is the gas-sensing performance. However, it has been hampered by poor adhesion between graphene and textile platforms. Meanwhile, amyloid nanofibrils are reputed for their ability to improve adhesion between materials, including between graphene and microorganisms. Despite that fact, there has been no attempt to apply amyloid nanofibrils to fabricate graphene-based e-textiles. By biomimicking the adhesion ability of amyloid nanofibrils, herein, we developed a graphene-amyloid nanofibril hybrid e-textile yarn (RGO/amyloid nanofibril/CY) for the detection of NO2. Compared to traditional e-textile yarn, the RGO/amyloid nanofibril/CY showed better performance in response time, sensing efficiency, sensitivity, and selectivity for NO2. Last, we suggested a practical use of RGO/amyloid nanofibril/CY combined with a light-emitting diode as a wearable e-textile gas sensor.

Highly Conductive and Flexible Dopamine-Graphene Hybrid Electronic Textile Yarn for Sensitive and Selective NO2 Detection.

Graphene-based electronic textile (e-textile) gas sensors have been developed for detecting hazardous NO2 gas. For the e-textile gas sensor, electrical conductivity is a critical factor because it directly affects its sensitivity. To obtain a highly conductive e-textile, biomolecules have been used for gluing the graphene to the textile surface, though there remain areas to improve, such as poor conductivity and flexibility. Herein, we have developed a dopamine-graphene hybrid electronic textile yarn (DGY) where the dopamine is used as a bio-inspired adhesive to attach graphene to the surface of yarns. The DGY shows improved electrical conductivity (∼40 times) compared to conventional graphene-based e-textile yarns with no glue. Moreover, it exhibited improved sensing performance in terms of short response time (∼2 min), high sensitivity (0.02 µA/ppm), and selectivity toward NO2. The mechanical flexibility and durability of the DGY were examined through a 1000-cycle bending test. For a practical application, the DGY was attempted to detect the NOx emitted from vehicles, including gasoline, diesel, and fuel cell electric vehicles. Our results demonstrated that the DGYs-as a graphene-based e-textile gas sensor for detecting NO2-are simple to fabricate, cheap, disposable, and mechanically stable.

Multiplexed femtomolar detection of Alzheimer's disease biomarkers in biofluids using a reduced graphene oxide field-effect transistor.

Alzheimer's disease (AD) is a neurodegenerative disease that accounts for 70% of all dementia. Early stage diagnosis of AD is essential as there is no certain treatment after the lesion has progressed in the late stage. Nevertheless, there are still limitations of early diagnosis of AD using neuroimaging and psychological memory assessments. Here, we demonstrate ultrasensitive and multiplexed detection of pivotal AD biomarkers (Aß1-42 and t-Tau) in biofluids using a reduced graphene oxide field-effect transistor (gFET). The proposed approach provides a wide logarithmically linear range of detection from 10-1-105 pg mL-1 and a femtomolar-level limit of detection in biofluids (human plasma and artificial cerebrospinal fluid) as well as phosphate-buffered saline (PBS). Furthermore, as these core biomarkers have different surface charges in physiological conditions based on the isoelectric point (pI), we achieved a distinctive output signal for each biomarker. The gFET biosensor platform presented in this paper has great potential and can be used for early diagnosis of AD in clinical practice as well as accurate analysis based on the surface charge of the analytes.