Highly sensitive and label-free protein immunoassay-based biosensor comprising infrared metamaterial absorber inducing strong coupling.

A mid-infrared label-free immunoassay-based biosensor is an effective device to help identify and quantify biomolecules. This biosensor employs a surface-enhanced infrared absorption spectroscopy, which is a highly potent sensing technique for detecting minute quantities of analytes. In this study, a biosensor was constructed using a metamaterial absorber, which facilitated strong coupling effects. For maximum coupling effect, it is necessary to enhance the near-field intensity and the spatial and spectral overlap between the optical cavity resonance and the vibrational mode of the analyte. Due to significant peak splitting, conventional baseline correction methods fail to adequately analyze such a coupling system. Therefore, we employed a coupled harmonic oscillation model to analyze the spectral distortion resulting from the peak splitting induced by the strong coupling effect. The proposed biosensor with a thrombin-binding aptamer-based immunoassay could achieve a limit of detection of 267.4 pM, paving the way for more efficient protein detection in clinical practice.

Nanoribbon Yarn with Versatile Inorganic Materials.

Nanomaterial-based yarns have been actively developed owing to their advantageous features, namely, high surface-area-to-volume ratios, flexibility, and unusual material characteristics such as anisotropy in electrical/thermal conductivity. The superior properties of the nanomaterials can be directly imparted and scaled-up to macro-sized structures. However, most nanomaterial-based yarns have thus far, been fabricated with only organic materials such as polymers, graphene, and carbon nanotubes. This paper presents a novel fabrication method for fully inorganic nanoribbon yarn, expanding its applicability by bundling highly aligned and suspended nanoribbons made from various inorganic materials (e.g., Au, Pd, Ni, Al, Pt, WO3, SnO2, NiO, In2O3, and CuO). The process involves depositing the target inorganic material on a nanoline mold, followed by suspension through plasma etching of the nanoline mold, and twisting using a custom-built yarning machine. Nanoribbon yarn structures of various functional inorganic materials are utilized for chemical sensors (Pd-based H2 and metal oxides (MOx)-based green gas sensors) and green energy transducers (water splitting electrodes/triboelectric nanogenerators). This method is expected to provide a comprehensive fabrication strategy for versatile inorganic nanomaterials-based yarns.

Design of High-Payload Ascorbyl Palmitate Nanosuspensions for Enhanced Skin Delivery.

A high-payload ascorbyl palmitate (AP) nanosuspension (NS) was designed to improve skin delivery following topical application. The AP-loaded NS systems were prepared using the bead-milling technique, and softly thickened into NS-loaded gel (NS-G) using hydrophilic polymers. The optimized NS-G system consisted of up to 75 mg/mL of AP, 0.5% w/v of polyoxyl-40 hydrogenated castor oil (Kolliphor® RH40) as the suspending agent, and 1.0% w/v of sodium carboxymethyl cellulose (Na.CMC 700 K) as the thickening agent, in citrate buffer (pH 4.5). The NS-G system was embodied as follows: long and flaky nanocrystals, 493.2 nm in size, -48.7 mV in zeta potential, and 2.3 cP of viscosity with a shear rate of 100 s-1. Both NS and NS-G provided rapid dissolution of the poorly water-soluble antioxidant, which was comparable to that of the microemulsion gel (ME-G) containing AP in solubilized form. In an ex vivo skin absorption study using the Franz diffusion cell mounted on porcine skin, NS-G exhibited faster absorption in skin, providing approximately 4, 3, and 1.4 times larger accumulation than that of ME-G at 3, 6, and 12 h, respectively. Therefore, the high-payload NS makes it a promising platform for skin delivery of the lipid derivative of ascorbic acid.

Robust imputation method with context-aware voting ensemble model for management of water-quality data.

Water-quality monitoring and management are crucial for ensuring the safety and sustainability of water resources. However, missing data is a frequent problem in water-quality datasets, which can result in biased results in hydrological modeling and data analysis. While classic statistical methods and emerging machine/deep learning methods have been applied for imputing missing values, most existing studies perform well in specific missing scenarios, but not in universal scenarios. Therefore, existing imputation methods often fail to robustly impute missing values across various scenarios. To address the problem, we propose an imputation method that uses a context-aware voting-ensemble model to dynamically select optimal weights to integrate various imputation models across different missingness scenarios. For first identify the attributes of missingness scenarios that influence imputation accuracy. Then after introducing missing values in collected data according to the missingness scenarios, we measure the accuracy of various imputation models across the missingness scenarios. Weights of imputation models are optimized by estimating non-linear functions with regression model that can capture relationships between missingness scenarios and imputation accuracies of models. The final imputed value of the ensemble model for a missing scenario can be determined by multiplying each imputation model's weight by its imputed value, then summing the products. The method inherits the advantages of state-of-art imputation models, including the ability to learn long-term dependencies in time series, as well as the flexibility of using a dynamic weighting strategy to process various missingness scenarios. To validate the superiority of our method, we evaluate on real-world water-quality data from a river in South Korea. The proposed method achieves higher accuracy and lower variation of imputed values than baseline models across various missingness scenarios. Furthermore, we showed the applicability of our method to various hydrological environment by validating our method on industrial water quality dataset. This study highlights the potential value of the ensemble model with dynamic weighting in robust imputation of water-quality data.

How Can Insulin Resistance Cause Alzheimer's Disease?

Alzheimer's disease (AD) is a neurodegenerative disorder associated with cognitive decline. Despite worldwide efforts to find a cure, no proper treatment has been developed yet, and the only effective countermeasure is to prevent the disease progression by early diagnosis. The reason why new drug candidates fail to show therapeutic effects in clinical studies may be due to misunderstanding the cause of AD. Regarding the cause of AD, the most widely known is the amyloid cascade hypothesis, in which the deposition of amyloid beta and hyperphosphorylated tau is the cause. However, many new hypotheses were suggested. Among them, based on preclinical and clinical evidence supporting a connection between AD and diabetes, insulin resistance has been pointed out as an important factor in the development of AD. Therefore, by reviewing the pathophysiological background of brain metabolic insufficiency and insulin insufficiency leading to AD pathology, we will discuss how can insulin resistance cause AD.

R-loop-derived cytoplasmic RNA-DNA hybrids activate an immune response.

R-loops are RNA-DNA-hybrid-containing nucleic acids with important cellular roles. Deregulation of R-loop dynamics can lead to DNA damage and genome instability1, which has been linked to the action of endonucleases such as XPG2-4. However, the mechanisms and cellular consequences of such processing have remained unclear. Here we identify a new population of RNA-DNA hybrids in the cytoplasm that are R-loop-processing products. When nuclear R-loops were perturbed by depleting the RNA-DNA helicase senataxin (SETX) or the breast cancer gene BRCA1 (refs. 5-7), we observed XPG- and XPF-dependent cytoplasmic hybrid formation. We identify their source as a subset of stable, overlapping nuclear hybrids with a specific nucleotide signature. Cytoplasmic hybrids bind to the pattern recognition receptors cGAS and TLR3 (ref. 8), activating IRF3 and inducing apoptosis. Excised hybrids and an R-loop-induced innate immune response were also observed in SETX-mutated cells from patients with ataxia oculomotor apraxia type 2 (ref. 9) and in BRCA1-mutated cancer cells10. These findings establish RNA-DNA hybrids as immunogenic species that aberrantly accumulate in the cytoplasm after R-loop processing, linking R-loop accumulation to cell death through the innate immune response. Aberrant R-loop processing and subsequent innate immune activation may contribute to many diseases, such as neurodegeneration and cancer.

Weighted Domain Adaptation Using the Graph-Structured Dataset Representation for Machinery Fault Diagnosis under Varying Operating Conditions.

Data-driven fault diagnosis has received significant attention in the era of big data. Most data-driven methods have been developed under the assumption that both training and test data come from identical data distributions. However, in real-world industrial scenarios, data distribution often changes due to varying operating conditions, leading to a degradation of diagnostic performance. Although several domain adaptation methods have shown their feasibility, existing methods have overlooked metadata from the manufacturing process and treated all domains uniformly. To address these limitations, this article proposes a weighted domain adaptation method using a graph-structured dataset representation. Our framework involves encoding a collection of datasets into the proposed graph structure, which captures relations between datasets based on metadata and raw data simultaneously. Then, transferability scores of candidate source datasets for a target are estimated using the constructed graph and a graph embedding model. Finally, the fault diagnosis model is established with a voting ensemble of the base classifiers trained on candidate source datasets and their estimated transferability scores. For validation, two case studies on rotor machinery, specifically tool wear and bearing fault detection, were conducted. The experimental results demonstrate the effectiveness and superiority of the proposed method over other existing domain adaptation methods.

Match activity profile of professional female soccer players during a season.

It is necessary to understand movement characteristics of elite female soccer players during a match to develop effective training program. The purpose of this study is to analyze the physical demands of Korean female professional soccer players during a competitive season. Twenty-four female professional players (age: 27.8±3.9 years; height: 165.7± 5.1 cm) from a team, belonging to the women's professional soccer league in South Korea participated in the study. The players participated in 11 home matches and 10 away matches from April 26 to November 9 of the 2011 season. Body weight and body mass index decreased during the first half-season compared to the preseason (P<0.05), and the decreased values were maintained until the second half-season. Total distance covered by the players was more than 9.5 km per match. No difference was found in the total distance, movement distance by exercise intensities, number of sprints and accelerations, and maximum speed between the first half- and second half-seasons. Midfielders covered the most distance during a match compared to other positions (P<0.05). Wing forward covered the most distance of high-intensity exercise. Maximum speed during the match was higher among wing forward and forward than in other positions (P<0.05). There were no significant differences between home and away matches in all variables (P>0.05). In conclusion, in order to improve the performance of female soccer players and prevent injuries, a training program should be constructed that considers the characteristics of each player and playing position rather than uniform training in a team.

High-Frequency Vibrating Stimuli Using the Low-Cost Coin-Type Motors for SSSEP-Based BCI.

Steady-state somatosensory-evoked potential- (SSSEP-) based brain-computer interfaces (BCIs) have been applied for assisting people with physical disabilities since it does not require gaze fixation or long-time training. Despite the advancement of various noninvasive electroencephalogram- (EEG-) based BCI paradigms, researches on SSSEP with the various frequency range and related classification algorithms are relatively unsettled. In this study, we investigated the feasibility of classifying the SSSEP within high-frequency vibration stimuli induced by a versatile coin-type eccentric rotating mass (ERM) motor. Seven healthy subjects performed selective attention (SA) tasks with vibration stimuli attached to the left and right index fingers. Three EEG feature extraction methods, followed by a support vector machine (SVM) classifier, have been tested: common spatial pattern (CSP), filter-bank CSP (FBCSP), and mutual information-based best individual feature (MIBIF) selection after the FBCSP. Consequently, the FBCSP showed the highest performance at 71.5 ± 2.5% for classifying the left and right-hand SA tasks than the other two methods (i.e., CSP and FBCSP-MIBIF). Based on our findings and approach, the high-frequency vibration stimuli using low-cost coin motors with the FBCSP-based feature selection can be potentially applied to developing practical SSSEP-based BCI systems.

Rapid-Onset Antidepressant-Like Effect of Nelumbinis semen in Social Hierarchy Stress Model of Depression.

Depression is a disease with increasing prevalence worldwide, and it is necessary to develop a therapeutic agent with better efficacy than existing antidepressant drugs. Antidepressants that act on the glutamatergic nervous system, such as ketamine, have a rapid-onset antidepressant effect and are effective against treatment-resistant depression. However, because of the addictive potential of ketamine, alternative substances without psychological side effects are recommended. In particular, many natural compounds have been tested for their antidepressant effects. The antidepressant effects of Nelumbinis semen (NS) have been tested in many studies, along with the various actions of NS on the glutamatergic system. Thus, it was expected that NS might have a rapid-onset antidepressant effect. To test the antidepressant potential, despair and anhedonic behaviors were measured after administering NS to mice exposed to social hierarchy stress (SHS), and biochemical changes in the prefrontal cortex and hippocampus were analyzed. NS reduced despair-like responses in the forced swim test and tail suspension test. Mice exposed to SHS showed depression-like responses such as increased despair, reduced hedonia, and an anxiety-like response in the novelty suppressed feeding test. NS, but not fluoxetine, improved those depression-like behaviors after acute treatment, and NBQX, an AMPA receptor blocker, inhibited the antidepressant-like effects of NS. The antidepressant-like effect of NS was related to enhanced phosphorylation of mTOR in the prefrontal cortex and dephosphorylation of GluR1 S845 in the hippocampus. Since NS has shown antidepressant-like potential in a preclinical model, it may be considered as a candidate for the development of antidepressants in the future.

Anti-biofilm activity of chlorhexidine-releasing elastomerics against dental microcosm biofilms.

OBJECTIVE: To evaluate the anti-biofilm activity of chlorhexidine-releasing elastomerics (CRE) developed to prevent biofilm-related diseases in orthodontic patients, using dental microcosm biofilms. METHODS: Elastomerics coated with one of two solutions (CRE 1 and 2) were attached to bovine enamel specimens. Uncoated elastomerics were used for negative (distilled water [DW]) and positive (0.1% chlorhexidine [CHX]) control groups. After saliva inoculation on the surface of the specimen for biofilm formation, DW and CRE groups were treated with DW, and the positive control group was treated with CHX twice a day for 5 min. After 7 days of biofilm formation, colony-forming units (CFUs, total and aciduric bacteria), red/green (R/G) ratio, biofilm thickness, live/dead cell ratio, and bacterial morphology in the biofilms were evaluated. Enamel demineralization was evaluated by fluorescence loss (ΔF). RESULTS: The CFUs of total and aciduric bacteria and R/G ratios in the CRE groups were significantly lower than those in the DW group with a reduction by 13%, 13%, and 19%, respectively (p < 0.05). The CFUs of total bacteria was significantly lower in the CRE groups than in the 0.1% CHX group (p < 0.05). Among the CRE groups, only CRE 1 exhibited a significantly reduced biofilm thickness of 54% compared to the DW group (p < 0.05) and apparent changes in bacterial morphology. ΔF in the CRE groups was significantly higher by 36% compared to that in the DW group (p < 0.05). CONCLUSIONS: CREs exhibited anti-biofilm and demineralization-inhibiting effect. Particularly, CRE 1 using dichloromethane as the solvent was most effective against biofilms. CLINICAL SIGNIFICANCE: Chlorhexidine-releasing elastomerics exhibited increased anti-biofilm and demineralization-inhibiting effect compared to 0.1% chlorhexidine mouthwash. Therefore, it is possible to prevent biofilm-related diseases simply and effectively by applying chlorhexidine-releasing elastomerics to orthodontic patients.

Active DNA damage eviction by HLTF stimulates nucleotide excision repair.

Nucleotide excision repair (NER) counteracts the onset of cancer and aging by removing helix-distorting DNA lesions via a "cut-and-patch"-type reaction. The regulatory mechanisms that drive NER through its successive damage recognition, verification, incision, and gap restoration reaction steps remain elusive. Here, we show that the RAD5-related translocase HLTF facilitates repair through active eviction of incised damaged DNA together with associated repair proteins. Our data show a dual-incision-dependent recruitment of HLTF to the NER incision complex, which is mediated by HLTF's HIRAN domain that binds 3'-OH single-stranded DNA ends. HLTF's translocase motor subsequently promotes the dissociation of the stably damage-bound incision complex together with the incised oligonucleotide, allowing for an efficient PCNA loading and initiation of repair synthesis. Our findings uncover HLTF as an important NER factor that actively evicts DNA damage, thereby providing additional quality control by coordinating the transition between the excision and DNA synthesis steps to safeguard genome integrity.

TREX1 degrades the 3' end of the small DNA oligonucleotide products of nucleotide excision repair in human cells.

The nucleotide excision repair (NER) machinery removes UV photoproducts from DNA in the form of small, excised damage-containing DNA oligonucleotides (sedDNAs) ∼30 nt in length. How cells process and degrade these byproducts of DNA repair is not known. Using a small scale RNA interference screen in UV-irradiated human cells, we identified TREX1 as a major regulator of sedDNA abundance. Knockdown of TREX1 increased the level of sedDNAs containing the two major UV photoproducts and their association with the NER proteins TFIIH and RPA. Overexpression of wild-type but not nuclease-inactive TREX1 significantly diminished sedDNA levels, and studies with purified recombinant TREX1 showed that the enzyme efficiently degrades DNA located 3' of the UV photoproduct in the sedDNA. Knockdown or overexpression of TREX1 did not impact the overall rate of UV photoproduct removal from genomic DNA or cell survival, which indicates that TREX1 function in sedDNA degradation does not impact NER efficiency. Taken together, these results indicate a previously unknown role for TREX1 in promoting the degradation of the sedDNA products of the repair reaction. Because TREX1 mutations and inefficient DNA degradation impact inflammatory and immune signaling pathways, the regulation of sedDNA degradation by TREX1 may contribute to photosensitive skin disorders.

XPA is susceptible to proteolytic cleavage by cathepsin L during lysis of quiescent cells.

The xeroderma pigmentosum group A (XPA) protein plays an essential role in the removal of UV photoproducts and other bulky lesions from DNA as a component of the nucleotide excision repair (NER) machinery. Using cell lysates prepared from confluent cultures of human cells and from human skin epidermis, we observed an additional XPA antibody-reactive band on immunoblots that was approximately 3-4 kDa smaller than the native, full-length XPA protein. Biochemical studies revealed this smaller molecular weight XPA species to be due to proteolysis at the C-terminus of the protein, which negatively impacted the ability of XPA to interact with the NER protein TFIIH. Further work identified the endopeptidase cathepsin L, which is expressed at higher levels in quiescent cells, as the protease responsible for cleaving XPA during cell lysis. These results suggest that supplementation of lysis buffers with inhibitors of cathepsin L is important to prevent cleavage of XPA during lysis of confluent cells.

Ultrasensitive Molecule Detection Based on Infrared Metamaterial Absorber with Vertical Nanogap.

Surface-enhanced infrared absorption (SEIRA) spectroscopy is a powerful methodology for sensing and identifying small quantities of analyte molecules via coupling between molecular vibrations and an enhanced near-field induced in engineered structures. A metamaterial absorber (MA) is proposed as an efficient SEIRA platform; however, its efficiency is limited because it requires the appropriate insulator thickness and has a limited accessible area for sensing. SEIRA spectroscopy is proposed using an MA with a 10 nm thick vertical nanogap, and a record-high reflection difference SEIRA signal of 36% is experimentally achieved using a 1-octadecanethiol monolayer target molecule. Theoretical and experimental comparative studies are conducted using MAs with three different vertical nanogaps. The MAs with a vertical nanogap are processed using nanoimprint lithography and isotropic dry etching, which allow cost-effective large-area patterning and mass production. The proposed structure may provide promising routes for ultrasensitive sensing and detection applications.

Multi-Domain Convolutional Neural Networks for Lower-Limb Motor Imagery Using Dry vs. Wet Electrodes.

Motor imagery (MI) brain-computer interfaces (BCIs) have been used for a wide variety of applications due to their intuitive matching between the user's intentions and the performance of tasks. Applying dry electroencephalography (EEG) electrodes to MI BCI applications can resolve many constraints and achieve practicality. In this study, we propose a multi-domain convolutional neural networks (MD-CNN) model that learns subject-specific and electrode-dependent EEG features using a multi-domain structure to improve the classification accuracy of dry electrode MI BCIs. The proposed MD-CNN model is composed of learning layers for three domain representations (time, spatial, and phase). We first evaluated the proposed MD-CNN model using a public dataset to confirm 78.96% classification accuracy for multi-class classification (chance level accuracy: 30%). After that, 10 healthy subjects participated and performed three classes of MI tasks related to lower-limb movement (gait, sitting down, and resting) over two sessions (dry and wet electrodes). Consequently, the proposed MD-CNN model achieved the highest classification accuracy (dry: 58.44%; wet: 58.66%; chance level accuracy: 43.33%) with a three-class classifier and the lowest difference in accuracy between the two electrode types (0.22%, d = 0.0292) compared with the conventional classifiers (FBCSP, EEGNet, ShallowConvNet, and DeepConvNet) that used only a single domain. We expect that the proposed MD-CNN model could be applied for developing robust MI BCI systems with dry electrodes.

Inducible Prmt1 ablation in adult vascular smooth muscle leads to contractile dysfunction and aortic dissection.

Vascular smooth muscle cells (VSMCs) have remarkable plasticity in response to diverse environmental cues. Although these cells are versatile, chronic stress can trigger VSMC dysfunction, which ultimately leads to vascular diseases such as aortic aneurysm and atherosclerosis. Protein arginine methyltransferase 1 (Prmt1) is a major enzyme catalyzing asymmetric arginine dimethylation of proteins that are sources of asymmetric dimethylarginine (ADMA), an endogenous inhibitor of nitric oxide synthase. Although a potential role of Prmt1 in vascular pathogenesis has been proposed, its role in vascular function has yet to be clarified. Here, we investigated the role and underlying mechanism of Prmt1 in vascular smooth muscle contractility and function. The expression of PRMT1 and contractile-related genes was significantly decreased in the aortas of elderly humans and patients with aortic aneurysms. Mice with VSMC-specific Prmt1 ablation (smKO) exhibited partial lethality, low blood pressure and aortic dilation. The Prmt1-ablated aortas showed aortic dissection with elastic fiber degeneration and cell death. Ex vivo and in vitro analyses indicated that Prmt1 ablation significantly decreased the contractility of the aorta and traction forces of VSMCs. Prmt1 ablation downregulated the expression of contractile genes such as myocardin while upregulating the expression of synthetic genes, thus causing the contractile to synthetic phenotypic switch of VSMCs. In addition, mechanistic studies demonstrated that Prmt1 directly regulates myocardin gene activation by modulating epigenetic histone modifications in the myocardin promoter region. Thus, our study demonstrates that VSMC Prmt1 is essential for vascular homeostasis and that its ablation causes aortic dilation/dissection through impaired myocardin expression.

Effects of Radix Polygalae on Cognitive Decline and Depression in Estradiol Depletion Mouse Model of Menopause.

Postmenopausal syndrome refers to symptoms caused by the gradual decrease in female hormones after mid-40 years. As a target organ of estrogen, decrease in estrogen causes various changes in brain function such as a decrease in choline acetyltransferase and brain-derived neurotrophic factor; thus, postmenopausal women experience cognitive decline and more depressive symptoms than age-matched men. Radix Polygalae has been used for memory boosting and as a mood stabilizer and its components have shown neuroprotective, antidepressant, and stress relief properties. In a mouse model of estrogen depletion induced by 4-vinylcyclohexene diepoxide, Radix Polygalae was orally administered for 3 weeks. In these animals, cognitive and depression-related behaviors and molecular changes related to these behaviors were measured in the prefrontal cortex and hippocampus. Radix Polygalae improved working memory and contextual memory and despair-related behaviors in 4-vinylcyclohexene diepoxide-treated mice without increasing serum estradiol levels in this model. In relation to these behaviors, choline acetyltransferase and brain-derived neurotrophic factor in the prefrontal cortex and hippocampus and bcl-2-associated athanogene expression increased in the hippocampus. These results implicate the possible benefit of Radix Polygalae in use as a supplement of estrogen to prevent conditions such as postmenopausal depression and cognitive decline.

Probing TGF-ß1-induced cytoskeletal rearrangement by fluorescent-labeled silica nanoparticle uptake assay.

Cytoskeletal proteins are essential in maintaining cell morphology, proliferation, and viability as well as internalizing molecules in phagocytic and non-phagocytic cells. Orderly aligned cytoskeletons are disturbed by a range of biological processes, such as the epithelial-mesenchymal transition, which is observed in cancer metastasis. Although many biological methods have been developed to detect cytoskeletal rearrangement, simple and quantitative in vitro approaches are still in great demand. Herein, we applied a flow cytometry-based nanoparticle uptake assay to measure the degree of cytoskeletal rearrangement induced by transforming growth factor ß1 (TGF-ß1). For the assay, silica nanoparticles, selected for their high biocompatibility, were fluorescent-labeled to facilitate quantification with flow cytometry. Human keratinocyte HaCaT cells were treated with different concentrations of TGF-ß1 and then exposed to FITC-labeled silica nanoparticles. Increasing concentrations of TGF-ß1 induced gradual changes in cytoskeletal rearrangement, as confirmed by conventional assays. The level of nanoparticle uptake increased by TGF-ß1 treatment in a dose-dependent manner, indicating that our nanoparticle uptake assay can be used as a quick and non-destructive approach to measure cytoskeletal rearrangement.