Glucose Oxidase Activity Colorimetric Assay Using Redox-Sensitive Electrochromic Nanoparticle-Functionalized Paper Sensors.

Glucose oxidase (GOx) activity assays are vital for various applications, including glucose metabolism estimation and fungal testing. However, conventional methods involve time-consuming and complex procedures. In this study, we present a colorimetric platform for in situ GOx activity measurement utilizing redox-sensitive electrochromic nanoparticles based on polyaniline (PAni). The glucose-adsorbed colorimetric paper sensor, herein termed Glu@CPS, is created by immobilizing ferrocene and glucose onto paper substrates that have been functionalized with PAni nanoparticles. Glu@CPS not only demonstrated rapid detection (within 5 min) but also exhibited remarkable selectivity for GOx and a limit of detection as low as 1.25 µM. Moreover, Glu@CPS demonstrated consistent accuracy in the measurement of GOx activity, exhibiting no deviations even after being stored at ambient temperature for a duration of one month. To further corroborate the effectiveness of this method, we applied Glu@CPS in the detection of GOx activity in a moldy red wine. The results highlight the promising potential of Glu@CPS as a convenient and precise platform for GOx activity measurement in diverse applications including food quality control, environmental monitoring, and early detection of fungal contamination.

Hydrophobic Barriers for Directing Physarum polycephalum Propulsion and Navigation.

Physarum polycephalum (P. polycephalum) is a unicellular protist with unique properties, such as learning and remembering in its cultured environment without a brain or central nervous system. The organism has been extensively used in morphology, taxis, and positive feedback dynamics studies. However, the lack of standardization of materials and substrate designs used in P. polycephalum studies has significantly limited conducting such studies, increasing the cost and time. In this study, we introduce a method to control the direction and migration of P. polycephalum by drawing hydrophobic lines and patterns. Our study succeeded in controlling the movement of P. polycephalum by setting a variety of hydrophobic designs such as complete barrier, single-slit barrier, taper barrier, dumbbell barrier, and one-side-opened rectangular barrier, suggesting the effectiveness of the hydrophobic barrier in regulating the propulsion and navigation of the organisms. Moreover, we demonstrated that utilizing such geometric constraints can reduce the experimental time required for toxicity testing based on P. polycephalum by more than 300%. Our techniques open new possibilities for studying the biophysical properties and behaviors of P. polycephalum, while also facilitating toxicity 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.

Direct observation of surface charge and stiffness of human metaphase chromosomes.

Metaphase chromosomes in which both polynucleotides and proteins are condensed with hierarchies are closely related to life phenomena such as cell division, cancer development, and cellular senescence. Nevertheless, their nature is rarely revealed, owing to their structural complexity and technical limitations in analytical methods. In this study, we used surface potential and nanomechanics mapping technology based on atomic force microscopy to measure the surface charge and intrinsic stiffness of metaphase chromosomes. We found that extra materials covering the chromosomes after the extraction process were positively charged. With the covering materials, the chromosomes were positively charged (ca. 44.9 ± 16.48 mV) and showed uniform stiffness (ca. 6.23 ± 1.98 MPa). In contrast, after getting rid of the extra materials through treatment with RNase and protease, the chromosomes were strongly negatively charged (ca. -197.4 ± 77.87 mV) and showed relatively non-uniform and augmented stiffness (ca. 36.87 ± 17.56 MPa). The results suggested undulating but compact coordination of condensed chromosomes. Additionally, excessive treatment with RNase and protease could destroy the chromosomal structure, providing an exceptional opportunity for multiscale stiffness mapping of polynucleotides, nucleosomes, chromatin fibers, and chromosomes in a single image. Our approach offers a new horizon in terms of an analytical technique for studying chromosome-related diseases.

Mosaic RBD nanoparticles induce intergenus cross-reactive antibodies and protect against SARS-CoV-2 challenge.

Recurrent spillovers of α- and ß-coronaviruses (CoV) such as severe acute respiratory syndrome (SARS)-CoV, Middle East respiratory syndrome-CoV, SARS-CoV-2, and possibly human CoV have caused serious morbidity and mortality worldwide. In this study, six receptor-binding domains (RBDs) derived from α- and ß-CoV that are considered to have originated from animals and cross-infected humans were linked to a heterotrimeric scaffold, proliferating cell nuclear antigen (PCNA) subunits, PCNA1, PCNA2, and PCNA3. They assemble to create a stable mosaic multivalent nanoparticle, 6RBD-np, displaying a ring-shaped disk with six protruding antigens, like jewels in a crown. Prime-boost immunizations with 6RBD-np in mice induced significantly high Ab titers against RBD antigens derived from α- and ß-CoV and increased interferon (IFN-γ) production, with full protection against the SARS-CoV-2 wild type and Delta challenges. The mosaic 6RBD-np has the potential to induce intergenus cross-reactivity and to be developed as a pan-CoV vaccine against future CoV spillovers.

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.

A regression-based machine learning approach for pH and glucose detection with redox-sensitive colorimetric paper sensors.

Colorimetric paper sensors are used in various fields due to their convenience and intuitive manner. However, these sensors present low accuracy in practical use because it is difficult to distinguish color changes for a minute amount of analyte with the naked eye. Herein, we demonstrate that a machine learning (ML)-based paper sensor platform accurately determines the color changes. We fabricated a colorimetric paper sensor by adsorbing polyaniline nanoparticles (PAni-NPs), whose color changes from blue to green when the ambient pH decreases. Adding glucose oxidase (GOx) to the paper sensor enables colorimetric glucose detection. Target analytes (10 µL) were aliquoted onto the paper sensors, and their images were taken with a smartphone under the same conditions in a darkroom. The red-green-blue (RGB) data from the images were extracted and used to train and test three regression models: support vector regression (SVR), decision tree regression (DTR), and random forest regression (RFR). Of the three regression models, RFR performed the best at estimating pH levels (R2 = 0.957) ranging from pH 2 to 10 and glucose concentrations (R2 = 0.922) ranging from 0 to 10 mg mL-1.

Nanoscale biophysical properties of small extracellular vesicles from senescent cells using atomic force microscopy, surface potential microscopy, and Raman spectroscopy.

Cells secrete extracellular vesicles (EVs) carrying cell-of-origin markers to communicate with surrounding cells. EVs regulate physiological processes ranging from intercellular signaling to waste management. However, when senescent cells (SnCs) secrete EVs, the EVs, which are newly regarded as senescence-associated secretory phenotype (SASP) factors, can evoke inflammation, senescence induction, and metabolic disorders in neighboring cells. Unlike other soluble SASP factors, the biophysical properties of EVs, including small EVs (sEVs), derived from SnCs have not yet been investigated. In this study, sEVs were extracted from a human IMR90 lung fibroblast in vitro senescence model. Their biomechanical properties were mapped using atomic force microscopy-based quantitative nanomechanical techniques, surface potential microscopy, and Raman spectroscopy. The surfaces of sEVs derived from SnCs are slightly stiffer but their cores are softer than those of sEVs secreted from non-senescent cells (non-SnCs). This inversely proportional relationship between deformation and stiffness, attributed to a decrease in the concentration of genetic and protein materials inside the vesicles and the adsorption of positively charged SASP factors onto the vesicle surfaces, respectively, was found to be a peculiar characteristic of SnC-derived sEVs. Our results demonstrate that the biomechanical properties of SnC-derived sEVs differ from those of non-SnC-derived sEVs and provide insight into the mechanisms underlying their formation and composition.

Isothermal amplification-mediated lateral flow biosensors for in vitro diagnosis of gastric cancer-related microRNAs.

MicroRNAs (miRNAs) are important diagnostic and prognostic biomarkers for various tumors. Currently, many diagnostic systems have been developed to detect miRNAs, but simple techniques for detecting miRNAs are still required. Recently, we reported that the expression of miRNA-135b is upregulated in gastric epithelial cells during gastric inflammation and carcinogenesis. Our aim was to develop an in vitro diagnostic platform to analyze the expression of gastric cancer-related biomarkers in the blood. The diagnostic platform comprised an isothermal amplification-based lateral flow biosensor (IA-LFB) that enables easy diagnosis of gastric cancer through visual observation. In this platform, trace amounts of biomarkers are isothermally amplified through rolling circle amplification (RCA), and the amplified product is grafted to the LFB. The performance of the IA-LFB was confirmed using RNAs extracted from in vitro and in vivo models. The platform could detect target miRNAs within 3 h with excellent sensitivity and selectivity. In particular, the IA-LFB could detect the overexpression of gastric cancer-related markers (miRNA-135b and miRNA-21) in RNAs extracted from the blood of patients with various stages (stages 1-4) of gastric cancer compared to that in healthy volunteers. Therefore, IA-LFB is a simple and sensitive in vitro diagnostic system for detecting gastric cancer-related biomarkers and can contribute to the early diagnosis and prognosis monitoring of gastric cancer. Furthermore, this technology can be applied to systems that can detect multiple biomarkers related to various diseases (such as infectious and genetic diseases).

Colorimetric Nanoparticle-Embedded Hydrogels for a Biosensing Platform.

Hydrogels containing colorimetric nanoparticles have been used for ion sensing, glucose detection, and microbial metabolite analyses. In particular, the rapid chemical reaction owing to both the hydrogel form of water retention and the sensitive color change of nanoparticles enables the rapid detection of target substances. Despite this advantage, the poor dispersibility of nanoparticles and the mechanical strength of nanoparticle-hydrogel complexes have limited their application. In this study, we demonstrate a milliliter agarose gel containing homogeneously synthesized polyaniline nanoparticles (PAni-NPs), referred to as PAni-NP-hydrogel complexes (PNHCs). To fabricate the optimal PNHC, we tested various pH solvents based on distilled water and phosphate-buffered saline and studied the colorimetric response of the PNHC with thickness. The colorimetric response of the prepared PNHC to the changes in the pH of the solution demonstrated excellent linearity, suggesting the possibility of using PNHC as a pH sensor. In addition, it was verified that the PNHC could detect minute pH changes caused by the cancer cell metabolites without cytotoxicity. Furthermore, the PNHC can be stably maintained outside water for approximately 12 h without deformation, indicating that it can be used as a disposable patch-type wearable biosensing platform.

Dynamically Generated Hierarchical Neural Networks Designed With the Aid of Multiple Support Vector Regressors and PNN Architecture With Probabilistic Selection.

The two issues on dynamically generated hierarchical neural networks such as the sort of basic neurons and how to compose a layer are considered in this article. On the first issue, a variant version of the least-square support vector regression (SVR) is chosen as a basic neuron. Support vector machine (SVM) is a representative classifier which usually shows good classification performance. Along with the SVMs, SVR was introduced to deal with the regression problem. Especially, least-square SVR has the advantages of high learning speed due to the substitution of the inequality constraints by the equality constraint in the formulation of the optimization problem. Based on the least-square SVR, the multiple least-square (MLS) SVR, which is a type of a linear combination of least-square SVRs with fuzzy clustering, is proposed to improve the modeling performance. In addition, a hierarchical neural network, where the MLS SVR is utilized as the generic node instead of the conventional polynomial, is developed. The key issues of hierarchical neural networks, which are generated dynamically layer by layer, are discussed on how to retain the diversity of the nodes located at the same layer according to the increase of the layer. In order to maintain the diversity of the nodes, various selection methods such as truncation selection and roulette wheel selection (RWS) to choose the nodes among candidate nodes are proposed. In addition, in order to reduce the computational overhead to determine all candidates which exhibit all compositions of the input variables, a new implementation method is proposed. From the viewpoint of the diversity of the selected nodes and the computational aspects, it is shown that the proposed method is preferred over the conventional design methodology.

Selective colorimetric urine glucose detection by paper sensor functionalized with polyaniline nanoparticles and cell membrane.

For the diabetes diagnosis, noninvasive methods are preferred to invasive methods; urine glucose measurement is an example of a noninvasive method. However, conventional noninvasive methods for urine glucose measurement are not intuitive. Furthermore, such methods exhibit low selectivity because they can detect interfering molecules in addition to glucose. Herein, we fabricate a noninvasive, intuitive, and highly selective paper sensor consisting of polyaniline nanoparticles (PAni-NPs) and red blood cell membranes (RBCMs). The PAni-NPs (adsorbed on the paper) are highly sensitive to hydrogen ions and change color from emeraldine blue to emeraldine green within a few seconds. The RBCM (coated on the PAni-NP-adsorbed paper) having the glucose transporter-1 protein plays the role of a smart filter that transports glucose but rejects other interfering molecules. In particular, the selectivity of the RBCM-coated PAni-NP-based paper sensor was approximately improved ∼85%, compared to the uncoated paper sensors. The paper sensor could detect urine glucose over the range of 0-10 mg/mL (0-56 mM), with a limit of detection of 0.54 mM. The proposed paper sensor will facilitate the development of a highly selective and colorimetric urine glucose monitoring system.