Ineffective implementation of emergency reduction measures against high concentrations of particulate matter in Seoul, Republic of Korea.

Since December 30, 2017, the Seoul Metropolitan Government, Republic of Korea, has been implementing emergency reduction measures (ERMs) restricting the operation of industrial sites, thermal power plants, and vehicles when air quality is expected to deteriorate. ERMs are implemented when the present observed concentration of particulate matter (PM) of aerodynamic diameter less than 2.5 µm (PM2.5) and/or the predicted values for the following day exceed a threshold value. In this study, the effectiveness of ERMs was evaluated for 33 days with and 6 days without ERM implementation but where the PM2.5 concentration exceeded the threshold value, until March 15, 2021. Of the 33 days of ERM implementation, on 7 days it was executed despite the thresholds not being met. The ERM on these days might have been properly executed because the pre-notice and implementation of ERM might have reduced the local emissions of air pollutants. Our major findings are that even on days of ERM implementation, there were marginal reductions in vehicle traffic, thermal power generation, and industrial emissions. Second, the concentrations of PM2.5 and related air pollutants in Seoul were almost unchanged for most ERM implementation episodes. Third, most of the 39 (= 33 + 6) days when the air quality worsened were caused by the transboundary transport of air pollutants from China. In conclusion, it was revealed that the currently executed ERM law is insufficient for effectively reducing PM2.5. To achieve the required reductions, it is necessary to undertake stricter policies in Seoul and its neighboring regions.

Economic analysis of the circular economy based on waste plastic pyrolysis oil: a case of the university campus.

Recently, the concept of a circular economy for carbon neutrality is emerging. In particular, waste plastics are one of the key wastes, and efforts are being made to recycle them as energy rather than dispose of them. Accordingly, the technology of producing and utilizing pyrolysis oil from waste plastics attracts attention. As it is an early stage of technology development, however, there are not many demonstrations and papers that analyze the technology broadly. The goal of this study is to propose building a circular economy on a university campus through waste plastic pyrolysis oil technology. To show its feasibility, waste plastic pyrolysis oil technology is analyzed comprehensively from economic, environmental, and policy perspectives using the scenario analysis technique on the university campus level. A methodology of the scenario analysis technique enables predicting the uncertainties. Since plastic pyrolysis oil technologies and carbon neutrality are accompanied by many uncertainties, this technique is expected to be an appropriate methodology for this study. First, the amount of pyrolysis oil production from waste plastics from the campus is estimated. Then, the cost and carbon emissions from waste plastics are estimated if the pyrolysis oil technology is used instead of the traditional waste disposal process. As a result, the total economic profits of up to 425,484,022 won/year (354,570.01 $/year) are expected when a circular economy is built using waste plastic pyrolysis oil. In addition, it is also confirmed that greenhouse gas (GHG) emissions can be reduced by up to 840,891 kgCO2eq/year. The waste plastic pyrolysis oil satisfies Korea's gas pollutant standards and is consistent with the GHG reduction policy. It can be concluded that building a circular economy at the university campus level using waste plastic pyrolysis oil technology is suitable from economic, environmental, and policy perspectives.

Identification of Chemical Vapor Mixture Assisted by Artificially Extended Database for Environmental Monitoring.

A fully integrated sensor array assisted by pattern recognition algorithm has been a primary candidate for the assessment of complex vapor mixtures based on their chemical fingerprints. Diverse prototypes of electronic nose systems consisting of a multisensory device and a post processing engine have been developed. However, their precision and validity in recognizing chemical vapors are often limited by the collected database and applied classifiers. Here, we present a novel way of preparing the database and distinguishing chemical vapor mixtures with small data acquisition for chemical vapors and their mixtures of interest. The database for individual vapor analytes is expanded and the one for their mixtures is prepared in the first-order approximation. Recognition of individual target vapors of NO2, HCHO, and NH3 and their mixtures was evaluated by applying the support vector machine (SVM) classifier in different conditions of temperature and humidity. The suggested method demonstrated the recognition accuracy of 95.24%. The suggested method can pave a way to analyze gas mixtures in a variety of industrial and safety applications.

Chemical sensing platforms for detecting trace-level Alzheimer's core biomarkers.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and affects more than 10% of the population aged over 65 worldwide. Despite considerable global efforts, AD patients can only be diagnosed after the onset of symptoms based on neuropsychological tests and neuroimaging. Because the changes in the levels of biomarkers associated with Aß deposits and tau tangles precede the appearance of the first cognitive symptoms, accurate measurements of AD core biomarkers is critical for identifying asymptomatic AD patients and predicting disease progression. In this regard, significant efforts have been made to develop novel AD biomarker-targeting sensor platforms that have superb sensitivity and high accessibility. This review provides an overview of recent advances in optical and electrical sensing of core AD biomarkers in clinically relevant fluids such as the cerebrospinal fluid and human blood. We have summarized current challenges and future strategies for translating the sensing techniques discovered in the academic laboratories into clinical analytic platforms for early diagnosis of AD.

"Tree to Bone": Lignin/Polycaprolactone Nanofibers for Hydroxyapatite Biomineralization.

Bone contains an organic matrix composed of aligned collagen fibers embedded with nanosized inorganic hydroxyapatite (HAp). Many efforts are being made to mimic the natural mineralization process and create artificial bone scaffolds that show elaborate morphologies, excellent mechanical properties, and vital biological functions. This study reports a newly discovered function of lignin mediating the formation of human bone-like HAp. Lignin is the second most abundant organic material in nature, and it exhibits many attractive properties for medical applications, such as high durability, stability, antioxidant and antibacterial activities, and biocompatibility. Numerous phenolic and aliphatic hydroxyl moieties exist in the side chains of lignin, which donate adequate reactive sites for chelation with Ca2+ and the subsequent nucleation of HAp through coprecipitation of Ca2+ and PO43-. The growth of HAp crystals was facilitated by simple incubation of the electrospun lignin/polycaprolactone (PCL) matrix in a simulated body fluid. Multiple analyses revealed that HAp crystals were structurally and mechanically similar to the native bone. Furthermore, the mineralized lignin/PCL nanofibrous films facilitated efficient adhesion and proliferation of osteoblasts by directing filopodial extension. Our results underpin the expectations for this lignin-based biomaterial in future biointerfaces and hard-tissue engineering.

Gait Variability Can Predict the Risk of Cognitive Decline in Cognitively Normal Older People.

BACKGROUND: The aim of this study was to investigate the association of gait speed and gait variability, an index of how much gait parameters, such as step time, fluctuate step-to-step, with risk of cognitive decline in cognitively normal elderly individuals. While high gait variability is emerging as an early indicator of dementing illnesses, there is little research on whether high gait variability predicts cognitive decline in cognitively normal elderly who have no evidence of cognitive impairment. METHODS: In this 4-year prospective cohort study on 91 community-dwelling cognitively normal elderly individuals without cerebral ischemic burden or Parkinsonism, we evaluated gait speed and step time variability using a tri-axial accelerometer placed on the center of body mass, and diagnosed mild cognitive impairment (MCI) according to the International Working Group on MCI. We performed Kaplan-Meier analysis with consecutive log-rank testing for MCI-free survival by cohort-specific tertiles of gait speed; hazard ratios (HR) of incident MCI were estimated using Cox proportional hazards regression analysis adjusted for age, sex, education level, Cumulative Illness Rating Scale score, GDS score, and presence of the apolipoprotein E ε4 allele. RESULTS: Out of the 91 participants in the baseline assessment, 87 completed one or more 2-year follow-up assessments, and the median duration of follow-up was 47.1 months. Kaplan-Meier curves of incident MCI show evident differences in risk by gait variability group (χ2 = 9.64, p = 0.002, log-rank test). Mean MCI-free survival in the high variability group was 12% shorter than in the mid-to-low tertile group (47.4 ± 1.74 [SD] vs. 54.04 ± 0.52 months), while it was comparable between gait speed groups (51.59 ± 0.70 vs. 50.64 ± 1.77 months; χ2 = 1.16, p = 0.281). In multivariate analysis, subjects with high gait variability showed about 12-fold higher risk of MCI (HR = 11.97, 95% CI = 1.29-111.37) than those with mid-to-low variability. However, those with slow gait speed showed comparable MCI risk to those with mid-to-high speed (HR = 5.04, 95% CI = 0.53-48.18). CONCLUSIONS: Gait variability may be a better predictor of cognitive decline than gait speed in cognitively normal elderly individuals without cerebral ischemic burden or Parkinsonism.

Deep learning based low-cost high-accuracy diagnostic framework for dementia using comprehensive neuropsychological assessment profiles.

BACKGROUND: The conventional scores of the neuropsychological batteries are not fully optimized for diagnosing dementia despite their variety and abundance of information. To achieve low-cost high-accuracy diagnose performance for dementia using a neuropsychological battery, a novel framework is proposed using the response profiles of 2666 cognitively normal elderly individuals and 435 dementia patients who have participated in the Korean Longitudinal Study on Cognitive Aging and Dementia (KLOSCAD). METHODS: The key idea of the proposed framework is to propose a cost-effective and precise two-stage classification procedure that employed Mini Mental Status Examination (MMSE) as a screening test and the KLOSCAD Neuropsychological Assessment Battery as a diagnostic test using deep learning. In addition, an evaluation procedure of redundant variables is introduced to prevent performance degradation. A missing data imputation method is also presented to increase the robustness by recovering information loss. The proposed deep neural networks (DNNs) architecture for the classification is validated through rigorous evaluation in comparison with various classifiers. RESULTS: The k-nearest-neighbor imputation has been induced according to the proposed framework, and the proposed DNNs for two stage classification show the best accuracy compared to the other classifiers. Also, 49 redundant variables were removed, which improved diagnostic performance and suggested the potential of simplifying the assessment. Using this two-stage framework, we could get 8.06% higher diagnostic accuracy of dementia than MMSE alone and 64.13% less cost than KLOSCAD-N alone. CONCLUSION: The proposed framework could be applied to general dementia early detection programs to improve robustness, preciseness, and cost-effectiveness.

Carbon Nanodot-Sensitized Modulation of Alzheimer's ß-Amyloid Self-Assembly, Disassembly, and Toxicity.

The self-assembly of amyloidogenic peptides into ß-sheet-rich aggregates is a general feature of many neurodegenerative diseases, including Alzheimer's disease, which signifies the need for the effective attenuation of amyloid aggregation toward alleviating amyloid-associated neurotoxicity. This study reports that photoluminescent carbon nanodots (CDs) can effectively suppress Alzheimer's ß-amyloid (Aß) self-assembly and function as a ß-sheet breaker disintegrating preformed Aß aggregates. This study synthesizes CDs using ammonium citrate through one-pot hydrothermal treatment and passivates their surface with branched polyethylenimine (bPEI). The bPEI-coated CDs (bPEI@CDs) exhibit hydrophilic and cationic surface characteristics, which interact with the negatively charged residues of Aß peptides, suppressing the aggregation of Aß peptides. Under light illumination, bPEI@CDs display a more pronounced effect on Aß aggregation and on the dissociation of ß-sheet-rich assemblies through the generation of reactive oxygen species from photoactivated bPEI@CDs. The light-triggered attenuation effect of Aß aggregation using a series of experiments, including photochemical and microscopic analysis, is verified. Furthermore, the cell viability test confirms the ability of photoactivated bPEI@CDs for the suppression of Aß-mediated cytotoxicity, indicating bPEI@CDs' potency as an effective anti-Aß neurotoxin agent.

Tailoring the Composition of Eu3+-Doped Y3NbO7 Niobate: Structural Features and Luminescent Properties Induced by Spark Plasma Sintering.

The defective fluorite-related Y3NbO7 host lattice was doped with Eu3+ ions to understand the influence of spark plasma sintering (SPS) process on this host lattice. The intrinsic disorder due to the occurrence of oxygen vacancies results in amorphous-type responses of the luminescent cations, and the spectral distribution varies as a function of the niobium content. Two spectral fingerprints of europium emissions were clearly enhanced. The correlation between luminescence, X-ray diffraction, and electron diffraction characterizations shows the existence of local inhomogeneity. Indeed, the particular nonequilibrium sintering conditions allowed pointing out a lack of miscibility within the Y3NbO7 solid solution domain. Thus, the SPS pellet is a composite of two extreme compositions. This phase demixing is mainly induced by the pressure coupled with a current effect that makes possible ionic migration in this Y3NbO7 ionic conductive matrix.

Oxygen-enriching triphase platform for reliable sensing of femtomolar Alzheimer's neurofilament lights.

Accurate quantification of neurofilament lights (NfLs), a prognostic blood biomarker, is highly required to predict neurodegeneration in the presymptomatic stages of Alzheimer's disease. Here, we report self-oxygen-enriching coral structures with triphase interfaces for the label-free photocathodic detection of NfLs in blood plasma with femtomolar sensitivities and high reliability. In conventional photocathodic immunoassays, the poor solubility and sluggish diffusion rate of the dissolved oxygen serving as electron acceptors have necessitated the incorporation of additional electron acceptors or aeration procedures. To address the challenge, we designed the coral-like copper bismuth oxides (CBO) with robust solid-liquid-air contact boundaries that enrich the interfacial oxygen levels without an external aeration source. By optimally assembling the perfluorododecyltrichlorosilane (FTCS) and platinum (Pt) co-catalysts into the silver-doped CBO (Ag:CBO), the stable solid-liquid-air contact boundaries were formed within the sensor interfaces, which allowed for the abundant supply of air phase oxygen through an air pocket connected to the atmosphere. The Pt/FTCS-Ag:CBO exhibited the stable background signals independent of the dissolved oxygen fluctuations and amplified photocurrent signals by 1.76-fold, which were attributed to the elevated interfacial oxygen levels and 11.15 times-lowered mass transport resistance. Under the illumination of white light-emitting diode, the oxygen-enriching photocathodic sensor composed of Pt/FTCS-Ag:CBO conjugated with NfLs-specific antibodies precisely quantified the NfLs in plasma with a low coefficient of variation (≤2.97%), a high degree of recovery (>97.0%), and a limit of detection of 40.38 fg/mL, which was 140 times lower than the typical photocathodic sensor with diphase interfaces.

The Effect of Augmented Reality and Privacy Priming in a Fashion-Related App: An Application of Technology Acceptance Model.

In this research, we tested (a) the effects of augmented reality (AR) and (b) how the effects of AR could be moderated by privacy perceptions. We used a 2 eyewear app type (AR vs. non-AR) by 2 privacy priming (prime vs. no prime) between-subject experimental design, and 114 Korean adults participated in the experiment. Results showed that AR had a main effect on perceived ease of use but not on perceived usefulness. Instead, the effect of AR on perceived usefulness was moderated by privacy priming such that the positive effect of AR on perceived usefulness was weaker when privacy concern was salient. Moreover, the results provided support for a moderated mediation model in which the indirect effect of AR on intent to use the app via perceived usefulness was moderated by privacy priming. Theoretical and practical implications are discussed.

Critical contribution of moisture to the air quality deterioration in a warm and humid weather.

The deterioration of air quality that threatens human health is recognized as focal compound hazard. Here, decisive thermodynamic conditions for activation of secondary aerosol formation have been investigated focused on Korea. In a dry environment with relative humidity < 60%, gas phase reaction to form fine particles depended largely on surface temperature. In a wet environment (relative humidity ≥ 60%), however, aqueous phase reaction of secondary inorganic aerosols, which are sulfate, nitrate, and ammonium, accounting for 67% of the total aerosol mass, was more activated. Thus, humidity is as important as temperature in the secondary production of aerosol; air quality often worsened when a low-pressure system was predominant over the Korean Peninsula. It is rather different from the general synoptic conditions of high concentrations of particulate matters characterized by high pressure and atmospheric stagnation. This study suggests additional favorable condition and responsible mechanism of air quality hazards that may be frequent in future.

On-Site Remote Monitoring System with NIR Signal-Based Detection of Infectious Disease Virus in Opaque Salivary Samples.

Infectious disease viruses, such as foot-and-mouth disease virus (FMDV), are highly contagious viruses that cause significant socioeconomic damage upon spreading. Developing an on-site diagnostic tool for early clinical detection and real-time surveillance of FMDV outbreaks is essential to prevent the further spread of the disease. However, early diagnosis of FMDV is still challenging due to the limited sensitivity and time-consuming manual result entry of commercial on-site tests for salivary samples. Here, we report a near-infrared (NIR) signal nanoprobe-based highly accurate detection and remote monitoring system toward FMDVs, which automates the analysis and reporting of diagnosis data. The NIR signal lateral flow immunoassay (LFA) was assembled with a nanoprobe with a stable emission intensity at 800 nm, minimizing the interference signal of opaque salivary samples. We investigated the clinical applicability of the NIR signal LFA at biosafety level 3 (BSL-3) laboratories using 147 opaque salivary samples. The NIR signal LFA achieved a 32-fold lower limit of detection (LOD) than a commercial LFA in detecting live FMDVs, including all isolates occurring in the Republic of Korea during 2010-2017. Our results showed that the NIR signal LFA successfully discriminated the FMDV-positive clinical salivary samples from healthy controls with a sensitivity of 96.9%, specificity of 100.0%, and AUC (area under the receiver operator characteristic curve) value of 0.999. Finally, we substantiated the real-time collection of diagnostic results using a customized portable NIR reader at nine different laboratories of government-certified quarantine institutions for foot-and-mouth disease (FMD).

Isolation of Bovine Milk Exosome Using Electrophoretic Oscillation Assisted Tangential Flow Filtration with Antifouling of Micro-ultrafiltration Membrane Filters.

Tangent flow-driven ultrafiltration (TF-UF) is an efficient isolation process of milk exosomes without morphological deformation. However, the TF-UF approach with micro-ultrafiltration SiNx membrane filters suffers from the clogging and fouling of micro-ultrafiltration membrane filter pores with large bioparticles. Thus, it is limited in the long term, continuous isolation of large quantities of exosomes. In this work, we introduced electrophoretic oscillation (EPO) in the TF-UF approach to remove pore clogging and fouling of with micro-ultrafiltration SiNx membrane filters by large bioparticles. As a result, the combined EPO-assisted TF (EPOTF) filtration can isolate large quantities of bovine milk exosomes without deformation. Furthermore, several morphological and biological analyses confirmed that the EPOTF filtration approach could isolate the milk exosomes in high concentrations with high purity and intact morphology. In addition, the uptake test of fluorescent-labeled exosomes by the keratinocyte cells visualized the biological function of purified exosomes. Hence, compared to the TF-UF process, the EPOTF filtration produced a higher yield of bovine milk exosomes without stopping the filtering process for over 200 h. Therefore, this isolation process enables scalable and continuous production of morphologically intact exosomes from bovine milk, suggesting that high-quality exosome purification is possible for future applications such as drug nanocarriers, diagnosis, and treatments.

In-situ food spoilage monitoring using a wireless chemical receptor-conjugated graphene electronic nose.

Monitoring food spoilage is one of the most effective methods for preventing food poisoning caused by biogenic amines or microbes. Therefore, various analytical techniques have been introduced to detect low concentrations of cadaverine (CV) and putrescine (PT), which are representative biogenic polyamines involved in food spoilage (5-8 ppm at the stage of initial decomposition after storage for 5 days at 5 °C and 17-186 ppm at the stage of advanced decomposition after storage for 7 days at 5 °C). Although previous methods showed selective CV and PT detection even at low concentrations, the use of these methods remains challenging in research areas that require in-situ, real-time, on-site monitoring. In this study, we demonstrated for the first time an in-situ high-performance chemical receptor-conjugated graphene electronic nose (CRGE-nose) whose limits of detection (LODs), 27.04 and 7.29 ppb, for CV and PT are up to 102 times more sensitive than those of conventional biogenic amine sensors. Specifically, the novel chemical receptors 2,7-bis(3-morpholinopropyl)benzo[lmn][3,8] phenanthroline-1,3,6,8(2H,7H)-tetraone (NaPhdiMor (NPM)) and 2,7-bis(2-((3-morpholinopropyl)amino)ethyl)benzo[lmn][3,8]phenanthroline-1,3,6,8(2H,7H)-tetraone (NaPhdiEtAmMor (NPEAM)) were designed on the basis of density functional theory (DFT) calculations, and their interaction mechanism was characterized by a DFT 3D simulation. Interestingly, the CRGE-nose was connected on a micro sim chip substrate via wire bonding and then integrated into wireless portable devices, resulting in a cost-effective, high-performance prototype CRGE-nose device capable of on-site detection. The portable CRGE-nose can be used for in-situ monitoring of CV and PT concentration changes as low as 27.04 and 7.29 ppb in real meats such as pork, beef, lamb and chicken.

Wireless portable bioelectronic nose device for multiplex monitoring toward food freshness/spoilage.

Monitoring food freshness/spoilage is important to ensure food quality and safety. Current methods of food quality monitoring are mostly time-consuming and labor intensive processes that require massive analytical equipment. In this study, we developed a portable bioelectronic nose (BE-nose) integrated with trace amine-associated receptor (TAAR) nanodiscs (NDs), allowing food quality monitoring via the detection of food spoilage indicators, including the biogenic amines cadaverine (CV) and putrescine (PT). The olfactory receptors TAAR13c and TAAR13d, which have specific affinities for CV and PT, were produced and successfully reconstituted in ND structures. TAAR13 NDs BE-nose-based side-gated field-effect transistor (SG-FET) system was constructed by utilizing a graphene micropattern (GM) into which two types of olfactory NDs (TAAR13c ND and TAAR13d ND) were introduced, and this system showed ultrahigh sensitivity for a limit of detection (LOD) of 1 fM for CV and PT. Moreover, the binding affinities between the TAAR13 NDs and the indicators were confirmed by a tryptophan fluorescence quenching assay and biosimulations, in which the specific binding site was confirmed. Gas-phase indicators were detected by the TAAR13 NDs BE-nose platform, and the LODs for CV and PT were confirmed to be 26.48 and 7.29 ppb, respectively. In addition, TAAR13 NDs BE-nose was fabricated with commercial gas sensors as a portable platform for the measurement of NH3 and H2S, multiplexed monitoring was achieved with similar performance, and the change ratio of the indicators was observed in a real sample. The integration of commercial gas sensors on a BE-nose enhanced the accuracy and reliability for the quality monitoring of real food samples. These results indicate that the portable TAAR13 NDs BE-nose can be used to monitor CV and PT over a wide range of concentrations, therefore, the electronic nose platform can be utilized for monitoring the freshness/spoilage step in various foods.

Screening major depressive disorder using vocal acoustic features in the elderly by sex.

BACKGROUND: Vocal acoustic features are potential biomarkers of elderly depression. Previous automated diagnostic tests for depression have employed unstandardized speech samples, and few studies have considered differences in voice reactivity. We aimed to develop a voice-based screening test for depression measuring vocal acoustic features of elderly Koreans while they read a series of mood-inducing sentences (MIS). METHODS: In this case-control study, we recruited 61 individuals with major depressive disorder and 143 healthy controls (mean age [SD]: 72 [6]; female, 70%) from the community-dwelling elderly population. Participants were asked to read MIS and their variation pattern of acoustic features represented by the correlation distance between two MIS were analyzed as input features using the univariate feature selection technique and subsequently classified by AdaBoost. RESULTS: Acoustic features showing significant discriminatory performances were spectral and energy-related features for males (sensitivity 0.95, specificity 0.88, and accuracy 0.86) and prosody-related features for females (sensitivity 0.73, specificity 0.86, and accuracy 0.77). The correlation distance between negative and positive MIS was significantly shorter in the depressed group than in the healthy control (F = 18.574, P < 0.001). LIMITATIONS: Small sample size and relatively homogenous clinical profile of depression could limit the generalizability. CONCLUSIONS: While reading MIS, spectral and energy-related acoustic features for males and prosody-related features for females are good discriminators for major depressive disorder. These features may be used as biomarkers of depression in the elderly.

Femtomolar sensing of Alzheimer's tau proteins by water oxidation-coupled photoelectrochemical platform.

Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder. A key pathogenic event of AD is the formation of intracellular neurofibrillary tangles that are mainly composed of tau proteins. Here, we report on ultrasensitive detection of total tau (t-tau) proteins using an artificial electron donor-free, BiVO4-based photoelectrochemical (PEC) analysis. The platform was constructed by incorporating molybdenum (Mo) dopant and iron oxyhydroxide (FeOOH) ad-layer into the BiVO4 photoelectrode and employing a signal amplifier formed by horseradish peroxidase (HRP)-triggered oxidation of 3,3'-diaminobenzidine (DAB). Despite the absence of additional electron suppliers, the FeOOH/Mo:BiVO4 conjugated with the Tau5 antibody produced strong current signals at 0 V (vs. Ag/AgCl, 3 M NaCl) under the illumination of a white light-emitting diode. The Mo extrinsic dopants increased the charge carrier density of BiVO4-Tau5 by 1.57 times, and the FeOOH co-catalyst promoted the interfacial water oxidation reaction of Mo:BiVO4-Tau5 by suppressing charge recombination. The introduction of HRP-labeled Tau46 capture antibodies to the FeOOH/Mo:BiVO4-Tau5 platform produced insoluble precipitation on the transducer by accelerating the oxidation of DAB, which amplified the photocurrent signal of FeOOH/Mo:BiVO4-Tau5 by 2.07-fold. Consequently, the water oxidation-coupled, FeOOH/Mo:BiVO4-based PEC sensing platform accurately and selectively recognized t-tau proteins down to femtomolar concentrations; the limit of detection and limit of quantification were determined to be 1.59 fM and 4.11 fM, respectively.

Piezoelectric materials for ultrasound-driven dissociation of Alzheimer's ß-amyloid aggregate structure.

Piezoelectric materials can evoke electrochemical reactions by transferring charge carriers to reactants upon receiving mechanical stimuli. We report a newly discovered function of piezoelectric bismuth oxychloride (BiOCl) nanosheets for dissociating Alzheimer's ß-amyloid (Aß) aggregates through ultrasound-induced redox reactions. The accumulation of Aß aggregates (e.g., Aß fibrils, plaques) in the central nervous system is a major pathological hallmark of Alzheimer's disease (AD). Thus, clearing Aß aggregates is considered a key for treating AD, but the dissociation of Aß aggregates is challenging due to their extremely robust structure consisting of ß-sheets. BiOCl nanosheets are a biocompatible piezoelectric material with piezocatalytic activity in response to ultrasound. Our analyses using multiple spectroscopic and microscopic tools have revealed that BiOCl nanosheets effectively disassemble Aß fibrils under ultrasound stimulation. Sono-activated BiOCl nanosheets produce piezo-induced oxidative stress, which effectively destabilizes the ß-sheets in Aß fibrils. In vitro evolution has also shown that sono-activated BiOCl nanosheets can effectively alleviate the neuro-toxicity of Aß fibrils. Furthermore, ex vivo evolution demonstrated that amount of Aß plaques in AD mouse's brain slices was drastically reduced by treatment with sono-activated BiOCl nanosheets.

Near-Infrared-Active Copper Bismuth Oxide Electrodes for Targeted Dissociation of Alzheimer's ß-Amyloid Aggregates.

The abnormal accumulation of ß-amyloid (Aß) aggregates in the brain is a major pathological hallmark of Alzheimer's disease. We report a near-infrared (NIR)-active CuBi2O4-based photocathodic platform that can target intact Aß aggregates and dissociate them into nontoxic species. Because of its relatively narrow band gap, CuBi2O4 exhibits strong absorption of NIR light, which allows for deeper tissue penetration and causes less photodamage to tissues compared to visible light. Furthermore, its high stability in aqueous media, biocompatibility, and robustness against photocorrosion make CuBi2O4 an ideal material for medical applications. For the targeted clearance of Aß aggregates, we have conjugated the KLVFF peptide which specifically recognizes and captures Aß aggregates on the surface of silver-doped CuBi2O4 (Ag:CuBi2O4). Upon illumination of NIR light under a cathodic bias, the KLVFF-immobilized Ag:CuBi2O4 (KLVFF-Ag:CuBi2O4) effectively dissociated ß-sheet-rich, long, and entangled Aß fibrillary aggregates into small fragmented, soluble species through photo-oxygenation. We also verified that the KLVFF-Ag:CuBi2O4 photocathode is biocompatible and effective in reducing Aß aggregate-induced neurotoxicity. Our work demonstrates the potential of the KLVFF-Ag:CuBi2O4 platform for the targeted disassembly of cytotoxic, robust Aß aggregates with the aid of NIR energy and cathodic bias.