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Abstract β‐secretase (BACE1) is instrumental in amyloid‐β (Aβ) production, with overexpression noted in Alzheimer's disease (AD) neuropathology. The interaction of Aβ with the receptor for advanced glycation endproducts (RAGE) facilitates cerebral uptake of Aβ and exacerbates its neurotoxicity and neuroinflammation, further augmenting BACE1 expression. Given the limitations of previous BACE1 inhibition efforts, the study explores reducing BACE1 expression to mitigate AD pathology. The research reveals that the anticancer agent 6‐thioguanosine (6‐TG) markedly diminishes BACE1 expression without eliciting cytotoxicity while enhancing microglial phagocytic activity, and ameliorate cognitive impairments with reducing Aβ accumulation in AD mice. Leveraging advanced deep learning‐based tool for target identification, and corroborating with surface plasmon resonance assays, it is elucidated that 6‐TG directly interacts with RAGE, modulating BACE1 expression through the JAK2‐STAT1 pathway and elevating soluble RAGE (sRAGE) levels in the brain. The findings illuminate the therapeutic potential of 6‐TG in ameliorating AD manifestations and advocate for small molecule strategies to increase brain sRAGE levels, offering a strategic alternative to the challenges posed by the complexity of AD.

Abstract The application of extracellular vesicles (EVs) as vehicles for anti‐Parkinson's agents represents a significant advance, yet their clinical translation is hampered by challenges in efficient brain delivery and complex blood‐brain barrier (BBB) targeting strategies. In this study, we engineered dopamine onto the surface of adipose‐derived stem cell EVs (Dopa‐EVs) utilizing a facile, two‐step cross‐linking approach. This engineering enhanced neuronal uptake of the EVs in primary neurons and neuroblastoma cells, a process shown to be competitively inhibited by dopamine pretreatment and dopamine receptor antibodies. Notably, Dopa‐EVs demonstrated increased brain accumulation in mouse Parkinson's disease (PD) models. Therapeutically, Dopa‐EVs administration led to the rescue of dopaminergic neuronal loss and amelioration of behavioural deficits in both 6‐hydroxydopamine (6‐OHDA) and α‐Syn PFF‐induced PD models. Furthermore, we observed that Dopa‐EVs stimulated autophagy evidenced by the upregulation of Beclin‐1 and LC3‐II. These findings collectively indicate that surface modification of EVs with dopamine presents a potent strategy for targeting dopaminergic neurons in the brain. The remarkable therapeutic potential of Dopa‐EVs, demonstrated in PD models, positions them as a highly promising candidate for PD treatment, offering a significant advance over current therapeutic modalities.

Safety and efficacy are essential in the process of disease treatment. However, off-label medication use is inevitable because various medications do not contain regulatory labels for pediatric use. We aimed to examine off-label medication use and analyze the risk factors correlated with adverse drug reactions (ADRs). This study was performed retrospectively using electronic medical data from a pediatric intensive care unit (PICU) of a tertiary hospital in Korea from July 2019 to June 2020. A total 6,183 prescribed medications from 502 PICU patients were examined in the present study. A total of 80% were infants or children, and 96.0% of them were treated with off-label medications. It was discovered that 4,778 off-label cases (77.2%) of the top 100 drugs had prescriptions with dosage (67.8%). Drugs prescribed to patients admitted to the cardiothoracic department (odds ratio [OR], 3.248; p = 0.019), total number of medications (OR, 1.116; p = 0.001), and length of PICU stay of ≥ 7 days (OR, 4.981; p = 0.008) were significantly associated with ADRs. ADRs were noted to be more severe in off-label use (p = 0.0426). For appropriate medication use, evidence regarding the safety of off-label medications is required and ultimately reflected in the official regulation.

Intermittent fasting (IF) has been shown to reduce cardiovascular risk factors in both animals and humans, and can protect the heart against ischemic injury in models of myocardial infarction. However, the underlying molecular mechanisms behind these effects remain unclear. To shed light on the molecular and cellular adaptations of the heart to IF, we conducted comprehensive system-wide analyses of the proteome, phosphoproteome, and transcriptome, followed by functional analysis. Using advanced mass spectrometry, we profiled the proteome and phosphoproteome of heart tissues obtained from mice that were maintained on daily 12- or 16 hr fasting, every-other-day fasting, or ad libitum control feeding regimens for 6 months. We also performed RNA sequencing to evaluate whether the observed molecular responses to IF occur at the transcriptional or post-transcriptional levels. Our analyses revealed that IF significantly affected pathways that regulate cyclic GMP signaling, lipid and amino acid metabolism, cell adhesion, cell death, and inflammation. Furthermore, we found that the impact of IF on different metabolic processes varied depending on the length of the fasting regimen. Short IF regimens showed a higher correlation of pathway alteration, while longer IF regimens had an inverse correlation of metabolic processes such as fatty acid oxidation and immune processes. Additionally, functional echocardiographic analyses demonstrated that IF enhances stress-induced cardiac performance. Our systematic multi-omics study provides a molecular framework for understanding how IF impacts the heart’s function and its vulnerability to injury and disease.

Adult hippocampal neurogenesis supports the structural and functional plasticity of the brain, while its decline is associated with neurodegeneration common in Alzheimer’s disease (AD). Although the dysregulation of certain microRNAs (miRNAs) in AD have been observed, the effects of miRNAs on hippocampal neurogenesis are largely unknown.In this study, we demonstrated miR-351-5p as a causative factor in hippocampal neural progenitor cell death through modulation of the mitochondrial guanosine triphosphatase (GTPase), Miro2. Downregulation of Miro2 by siMiro2 induced cell death, similar to miR-351-5p, whereas ectopic Miro2 expression using an adenovirus abolished these effects. Excessively fragmented mitochondria and dysfunctional mitochondria were indexed by decreased mitochondrial potential, and increased reactive oxygen species were identified in miR-351-5p-induced cell death. Moreover, subsequent induction of mitophagy via Pink1 and Parkin was observed in the presence of miR-351-5p and siMiro2. The suppression of mitochondrial fission by Mdivi-1 completely inhibited cell death by miR-351-5p. miR-351-5p expression increased whereas the level of Miro2 decreased in the hippocampus of AD model mice, emulating expression in AD patients. Collectively, the data indicate the mitochondrial fission and accompanying mitophagy by miR-351-5p/Miro2 axis as critical in hippocampal neural progenitor cell death, and a potential therapeutic target in AD.

Abstract Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) entry is mediated by the interaction of the viral spike (S) protein with angiotensin‐converting enzyme 2 (ACE2) on the host cell surface. Although a clinical trial testing soluble ACE2 (sACE2) for COVID‐19 is currently ongoing, our understanding of the delivery of sACE2 via small extracellular vesicles (sEVs) is still rudimentary. With excellent biocompatibility allowing for the effective delivery of molecular cargos, sEVs are broadly studied as nanoscale protein carriers. In order to exploit the potential of sEVs, we design truncated CD9 scaffolds to display sACE2 on the sEV surface as a decoy receptor for the S protein of SARS‐CoV‐2. Moreover, to enhance the sACE2‐S binding interaction, we employ sACE2 variants. sACE2‐loaded sEVs exhibit typical sEVs characteristics and bind to the S protein. Furthermore, engineered sEVs inhibit the entry of wild‐type (WT), the globally dominant D614G variant, Beta (K417N‐E484K‐N501Y) variant, and Delta (L452R‐T478K‐D614G) variant SARS‐CoV‐2 pseudovirus, and protect against authentic SARS‐CoV‐2 and Delta variant infection. Of note, sACE2 variants harbouring sEVs show superior antiviral efficacy than WT sACE2 loaded sEVs. Therapeutic efficacy of the engineered sEVs against SARS‐CoV‐2 challenge was confirmed using K18‐hACE2 mice. The current findings provide opportunities for the development of new sEVs‐based antiviral therapeutics.

Reactive oxygen species (ROS) are chemically reactive oxygen containing molecules. ROS consist of radical oxygen species including superoxide anion (O2•−) and hydroxyl radical (•OH) and non-radical oxygen species such as hydrogen peroxide (H2O2), singlet oxygen (O2). ROS are generated by mitochondrial oxidative phosphorylation, environmental stresses including UV or heat exposure, and cellular responses to xenobiotics (Ray et al., 2012). Excessive ROS production over cellular antioxidant capacity induces oxidative stress which results in harmful effects such as cell and tissue damage. Sufficient evidence suggests that oxidative stresses are involved in cancers, cardiovascular disease, and neurodegenerative diseases including Alzheimer’s disease and Parkinson disease (Waris and Ahsan, 2006). Though excessive level of ROS triggers detrimental effects, ROS also have been implicated to regulate cellular processes. Since ROS function is context dependent, measurement of ROS level is important to understand cellular processes (Finkel, 2011). This protocol describes how to detect intracellular and mitochondrial ROS in live cells using popular chemical fluorescent dyes.

In image processing, deep learning networks have been continuously developed and are used in many fields. However, most networks do not reflect image continuity. In this paper, we propose a novel bunch-of-keys module connected to the backend of a deep learning network to improve the detector performance on sequential images. This module optimizes existing deep learning networks to detect sequential images without retraining. This procedure reduces time and computing costs, and the average precision improves with a minimal drop in the frames per second. By adopting a sliding window method that uses three consecutive images, the keys are generated by comparing the positions of the detected boxes for each of the images using generalized intersection over union. The two key types perform correcting operations. The rectifying key has the effect of adding or merging undetected bounding boxes in mid-frame. The tracking key has the effect of compensating for bounding boxes lost for no reason in the third frame. The candidate box extracted using each key determines whether to add or merge to the target image in the correction task. This task calculates the complete intersection over union (CIoU) score between candidate boxes and all boxes of the target image and is divided into add or merge cases according to a set of CIoU criterion. As a result of adding or merging the bounding box to the missing object, detection performance was improved up to 3% in terms of the average precision.

During recent years, researchers throughout academia and industry have been advancing the theory, designing, and applications of mobile service computing through the Internet of Things (IoT). Research interest in mobile service computing stems from its performance, security, reliability, and power consumption. Hence, ultra-low power integrated circuits are essential for mobile service computing that can offer the advantages of low power for computational tasks in the IoT that is driven by the restricting constraints of power consumption and autonomy in both computation and idle phases. To attain the benefits of ultra-low power circuits, the energy-consuming and computational intense demands are imposed by the underlying processing and memory devices on which the conventional ultra-low power integrated circuit can benefit substantially from innovative hardware designs. Logic-in-Memory (LIM) architectures are considered as the potential approaches to attain goals within area and energy constraints starting with the lowest layers of the hardware stack. In this paper, we propose and implement the LIM asynchronous computing paradigm for energy-efficient mobile service computing. The results indicate that the proposed design achieves 38% leakage reduction and 30% accuracy improvement compared to the state-of-the-art non-volatile asynchronous circuits. At the system level, we compare our designs with various commercial microprocessors. The experimental results show that the asynchronous processors attain a four-fold throughput increase relative to their synchronous counterparts under these operating constraints. Therefore, the proposed design offers an approach toward tangible benefits of the battery-constrained embedded mobile service computing.

This paper proposes a novel model predictive control (MPC) algorithm that increases the path tracking performance according to the control input. The proposed algorithm reduces the path tracking errors of MPC by updating the sampling time of the next step according to the control inputs (i.e., the lateral velocity and front steering angle) calculated in each step of the MPC algorithm. The scenarios of a mixture of straight and curved driving paths were constructed, and the optimal control input was calculated in each step. In the experiment, a scenario was created with the Automated Driving Toolbox of MATLAB, and the path-following performance characteristics and computation times of the existing and proposed MPC algorithms were verified and compared with simulations. The results prove that the proposed MPC algorithm has improved path-following performance compared to those of the existing MPC algorithm.

Despite the wide application of organic light-emitting diodes (OLEDs), the performance of OLED devices is sometimes limited by their reliabilities. In this paper, we report the transient degradation behaviors of fluorescent blue OLEDs, where both the current and luminance initially increase under electrical stress within a short stress time. We analyze the degradation mechanism in terms of the carrier recombination and transport. From the comprehensive analyses of electrical and optical characteristics, it is suggested that the electron transport is responsible for the initial transient behavior of the device.

This paper describes the manufacturing method and properties of a superalloy as a gas turbine blade material and a thermal barrier coating to protect it. The development process of superalloy and characteristics of each casting method were introduced. In particular, the single crystal superalloys were analyzed for creep and tensile properties with temperature according to chemical composition. In addition, the theories of creep life prediction models were summarized and comparative analysis was performed. Finally, the manufacturing processes of thermal barrier coatings were introduced, and the characteristics and effects of mechanical, thermal, and durability characteristics of each manufacturing process are described. We believe that this comprehensive review will help not only the gas turbine industry/community, but also material scientists, measurement physicists/engineers, and theorists interested in superalloys and high-temperature ceramics.