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Abstract The amyloid cascade hypothesis suggests that amyloid beta (Aβ) contributes to initiating subsequent tau pathology in Alzheimer’s disease (AD). However, the underlying mechanisms through which Aβ contributes to tau uptake and propagation remain poorly understood. Here, we show that preexisting amyloid pathology accelerates the uptake of extracellular tau into neurons. Using quantitative proteomic analysis of endocytic vesicles, we reveal that Aβ induces the internalization of fibroblast growth factor receptor 3 (FGFR3). Extracellular tau binds to the extracellular domain of FGFR3 and is internalized by the FGFR3 ligand, fibroblast growth factor 2 (FGF2). Aβ accelerates FGF2 secretion from neurons, thereby inducing the internalization of tau-attached FGFR3. Knockdown of FGFR3 in the hippocampus reduces tau aggregation by decreasing tau uptake and improving memory function in AD model mice. These data suggest FGFR3 in neurons as a novel tau receptor and a key mediator of Aβ-induced tau uptake in AD.

Abstract Amyloid-β (Aβ) oligomers are implicated in the onset of Alzheimer’s disease (AD). Herein, quinoline-derived half-curcumin-dioxaborine (Q-OB) fluorescent probe was designed for detecting Aβ oligomers by finely tailoring the hydrophobicity of the biannulate donor motifs in donor-π-acceptor structure. Q-OB shows a great sensing potency in dynamically monitoring oligomerization of Aβ during amyloid fibrillogenesis in vitro. In addition, we applied this strategy to fluorometrically analyze Aβ self-assembly kinetics in the cerebrospinal fluids (CSF) of AD patients. The fluorescence intensity of Q-OB in AD patients’ CSF revealed a marked change of log (I/I 0 ) value of 0.34 ± 0.13 (cognitive normal), 0.15 ± 0.12 (mild cognitive impairment), and 0.14 ± 0.10 (AD dementia), guiding to distinguish a state of AD continuum for early diagnosis of AD. These studies demonstrate the potential of our approach can expand the currently available preclinical diagnostic platform for the early stages of AD, aiding in the disruption of pathological progression and the development of appropriate treatment strategies.

This study addresses the academic gap in the adoption of generative AI systems by investigating the factors influencing technology acceptance and usage behavior in Korean firms. Although recent advancements in AI are accelerating digital transformation and innovation, empirical research on the adoption of these systems remains scarce. To fill this gap, this study applies the Unified Theory of Acceptance and Use of Technology (UTAUT) model, surveying 300 employees from both large and small enterprises in South Korea. The findings reveal that effort expectancy and social influence significantly influence employees’ behavioral intention to use generative AI systems. Specifically, effort expectancy plays a critical role in the early stages of adoption, while social influence, including support from supervisors and peers, strongly drives the adoption process. In contrast, performance expectancy and facilitating conditions show no significant impact. The study also highlights the differential effects of age and work experience on behavioral intention and usage behavior. For older employees, social support is a key factor in technology acceptance, whereas employees with more experience exhibit a more positive attitude toward adopting new technologies. Conversely, facilitating conditions are more critical for younger employees. This study contributes to the understanding of the interaction between various factors in AI technology adoption and offers strategic insights for the successful implementation of AI systems in Korean companies.

This study focuses on the health and sanitation projects carried out on Koje Island by the United Nations Civil Assistance Command in Korea (UNCACK). Koje Island was unique as it served as a destination for dispersed refugees and as an area for housing prisoners of war. Unlike in other regions, UNCACK was actively involved in the implementation of health and sanitation projects on Koje Island. Their infectious disease control projects on Koje Island serve as a valuable example for studying infectious disease prevention initiatives and local medical projects in modern and contemporary Korea. In this study, I examine the documents produced by UNCACK to assess the status of infectious disease control and vaccination plans. Additionally, I analyze the disease prevention initiatives implemented among the residents of Koje Island, including isolation, treatment, and improvement of living conditions. Finally, I explore the characteristics of the Koje Island preventive measures and assess the efforts and limitations of both UNCACK and the Korean government in addressing health issues during the Korean War. Despite the presence of refugees and POWs, Koje Island managed to implement systematic public health initiatives in a controlled environment, widely regarded as highly successful. The public health initiatives on Koje Island, led by UNCACK, provided an opportunity to utilize limited resources, manpower, and Korean health professionals, cultivating the skills necessary to manage infectious diseases effectively. Moreover, these initiatives on Koje Island, although modest, continued into the postwar period, influencing medical missionary activities, the demand for health services among residents, the establishment of independent medical institutions, and the implementation of local health projects.

Abstract Some individuals with mild traumatic brain injury (mTBI), also known as concussion, have neuropsychiatric and physical problems that last longer than a few months. Symptoms following mTBI are not only impacted by the kind and severity of the injury but also by the post-injury experience and the individual's responses to it, making the persistence of mTBI particularly difficult to predict. We aimed to identify prognostic blood-based protein biomarkers predicting 6-month outcomes, in light of the clinical course after the injury, in a longitudinal mTBI cohort (N = 42). Among 420 target proteins quantified by multiple-reaction monitoring-mass spectrometry assays of blood samples, 31, 43, and 15 proteins were significantly associated with the poor recovery of neuropsychological symptoms at

With the advancement in information and communication technology, modern society has relied on various computing systems in areas closely related to human life. However, cyberattacks are also becoming more diverse and intelligent, with personal information and human lives being threatened. The moving target defense (MTD) strategy was designed to protect mission-critical systems from cyberattacks. The MTD strategy shifted the paradigm from passive to active system defense. However, there is a lack of indicators that can be used as a reference when deriving general system components, making it difficult to configure a systematic MTD strategy. Additionally, even when selecting system components, a method to confirm whether the systematic components are selected to respond to actual cyberattacks is needed. Therefore, in this study, we surveyed and analyzed existing cyberattack information and MTD strategy research results to configure a component dataset. Next, we found the correlation between the cyberattack information and MTD strategy component datasets and used this to design and implement the MTD-Diorama data visualization engine to configure a systematic MTD strategy. Through this, researchers can conveniently identify the attack surface contained in cyberattack information and the MTD strategies that can respond to each attack surface. Furthermore, it will allow researchers to configure more systematic MTD strategies that can be used universally without being limited to specific computing systems.

Abstract Nephritis is common in systemic lupus erythematosus patients and is associated with hyper-activation of immune and renal cells. Although mesenchymal stem cells (MSCs) ameliorate nephritis by inhibiting T and B cells, whether MSCs directly affect renal cells is unclear. To address this issue, we examined the direct effect of MSCs on renal cells with a focus on chemokines. We found that expression of CCL2, CCL3, CCL4, CCL5, CCL8, CCL19, and CXCL10 increased 1.6–5.6-fold in the kidney of lupus-prone MRL.Fas lpr mice with advancing age from 9 to 16 weeks. Although MSCs inhibited the increase in the expression of most chemokines by 52–95%, they further increased CCL8 expression by 290%. Using renal cells, we next investigated how MSCs enhanced CCL8 expression. CCL8 was expressed by podocytes, but not by tubular cells. MSCs enhanced CCL8 expression by podocytes in a contact-dependent manner, which was proved by transwell assay and blocking with anti-VCAM-1 antibody. Finally, we showed that CCL8 itself activated MSCs to produce more immunosuppressive factors (IL-10, IDO, TGF-β1, and iNOS) and to inhibit more strongly IFN-γ production by T cells. Taken together, our data demonstrate that MSCs activate podocytes to produce CCL8 in a contact-dependent manner and conversely, podocyte-derived CCL8 might potentiate immunosuppressive activity of MSCs in a paracrine fashion. Our study documents a previously unrecognized therapeutic mechanism of MSCs in nephritis.

Abstract Alzheimer’s disease (AD) is characterized by misfolding, oligomerization, and accumulation of amyloid-β (Aβ) peptides in the brain. Aβ monomers transform into Aβ oligomers, which are toxic species, inducing tau hyperphosphorylation and the downstream effects on microglia and astrocytes, triggering synaptic and cognitive dysfunctions. The oligomers then deposit into Aβ plaques, primarily composed of β-stranded fibrils, required for definitive AD diagnosis. As amyloid burden plays the pivotal role in AD pathogenesis, many efforts are devoted in preventing amyloidosis as a therapeutic approach to impede the disease progression. Here, we discovered carprofen, a non-steroidal anti-inflammatory drug, accelerates Aβ aggregating into fibrils and increases Aβ plaques when intraperitoneally injected to 5XFAD transgenic mouse model. However, the drug seems to alleviate the key Alzheimer-like phenotypes induced by Aβ aggregation as we found attenuated neuroinflammation, improved post-synaptic density expression, associated with synaptic plasticity, and decreased phosphorylated tau levels. Carprofen also rescued impaired working memory as we discovered improved spontaneous alternation performance through Y-maze test assessed with Aβ(1–42)-infused mouse model. Collectively, while carprofen accelerates the conversion of Aβ monomers into fibrils in vitro, the drug ameliorates the major pathological hallmarks of AD in vivo.

Abstract The conventional differentiation of affective disorders into major depressive disorder (MDD) and bipolar disorder (BD) has insufficient biological evidence. Utilizing multiple proteins quantified in plasma may provide critical insight into these limitations. In this study, the plasma proteomes of 299 patients with MDD or BD (aged 19–65 years old) were quantified using multiple reaction monitoring. Based on 420 protein expression levels, a weighted correlation network analysis was performed. Significant clinical traits with protein modules were determined using correlation analysis. Top hub proteins were determined using intermodular connectivity, and significant functional pathways were identified. Weighted correlation network analysis revealed six protein modules. The eigenprotein of a protein module with 68 proteins, including complement components as hub proteins, was associated with the total Childhood Trauma Questionnaire score (r = −0.15, p = 0.009). Another eigenprotein of a protein module of 100 proteins, including apolipoproteins as hub proteins, was associated with the overeating item of the Symptom Checklist-90-Revised (r = 0.16, p = 0.006). Functional analysis revealed immune responses and lipid metabolism as significant pathways for each module, respectively. No significant protein module was associated with the differentiation between MDD and BD. In conclusion, childhood trauma and overeating symptoms were significantly associated with plasma protein networks and should be considered important endophenotypes in affective disorders.

Abstract The adsorption behavior of furan on the Ge(100) surface was studied using a combination of high-resolution photoemission spectroscopy (HRPES) and density functional theory (DFT) calculations. We identified the two adsorption species produced by the [4 + 2] cycloaddition and deoxygenation reactions of furan with the Ge(100) surface in a ratio of approximately 76:24 at the surveyed coverages, via an analysis of the binding energies and relative area proportions of all the peaks in the C 1s and O 1s core-level spectra. The DFT simulation results revealed that the [4 + 2] cycloaddition and deoxygenation adducts are thermodynamically preferred by the reaction of furan with the Ge(100) surface compared with others, which is consistent with the HRPES results. The findings will further our understanding of the surface reactions of five-membered heterocyclic molecules.

Abstract Data-driven approaches to subtype transdiagnostic samples are important for understanding heterogeneity within disorders and overlap between disorders. Thus, this study was conducted to determine whether plasma proteomics-based clustering could subtype patients with transdiagnostic psychotic-affective disorder diagnoses. The study population included 504 patients with schizophrenia, bipolar disorder, and major depressive disorder and 160 healthy controls, aged 19 to 65 years. Multiple reaction monitoring was performed using plasma samples from each individual. Pathologic peptides were determined by linear regression between patients and healthy controls. Latent class analysis was conducted in patients after peptide values were stratified by sex and divided into tertile values. Significant demographic and clinical characteristics were determined for the latent clusters. The latent class analysis was repeated when healthy controls were included. Twelve peptides were significantly different between the patients and healthy controls after controlling for significant covariates. Latent class analysis based on these peptides after stratification by sex revealed two distinct classes of patients. The negative symptom factor of the Brief Psychiatric Rating Scale was significantly different between the classes (t = −2.070, p = 0.039). When healthy controls were included, two latent classes were identified, and the negative symptom factor of the Brief Psychiatric Rating Scale was still significant (t = −2.372, p = 0.018). In conclusion, negative symptoms should be considered a significant biological aspect for understanding the heterogeneity and overlap of psychotic-affective disorders.

Indoor service robots have been widely introduced in the fields of cleaning, delivery, education, guidance, and healthcare, etc. in indoor environments. The mobility of an indoor service robot is essential to expanding its applications. However, the mobility of existing indoor service robots is highly limited by surrounding indoor environments. For example, a stair is one of the major obstacles that restrict the reachable areas of indoor service robots. Even though many studies have been performed to develop reliable and fast stair-climbing robots based on legged, tracked, wheel-legged and wheel-linkage mechanisms, a market-dominant stair-climbing robot remains unsolved. This review investigates the efforts of engineers devoted to stair-climbing robots. To this end, the locomotion mechanisms of stair climbing robots are classified and their sensing method are summarized. In this review, we also propose useful criteria for evaluating the stair-climbing ability of an indoor service robot. By virtue of these criteria, the stair-climbing performance of existing robots are qualitatively compared. We hope this review helps develop the reliable and fast stair-climbing robots and the reasonable criteria for their performances.

Abstract Pyroglutamate amyloid-β3-42 (AβpE3-42) is an N-terminally truncated and pyroglutamate-modified Aβ peptide retaining highly hydrophobic, amyloidogenic, and neurotoxic properties. In Alzheimer’s disease (AD) patients, AβpE3-42 peptides accumulate into oligomers and induce cellular toxicity and synaptic dysfunction. AβpE3-42 aggregates further seed the formation of amyloid plaques, which are the pathological hallmarks of AD. Given that AβpE3-42 peptides play critical roles in the development of neurodegeneration, a reliable and reproducible synthetic access to these peptides may support pathological and medicinal studies of AD. Here, we synthesized AβpE3-42 peptides through the microwave-assisted solid-phase peptide synthesis (SPPS). Utilizing thioflavin T fluorescence assay and dot blotting analysis with anti-amyloid oligomer antibody, the amyloidogenic activity of synthesized AβpE3-42 peptides was confirmed. We further observed the cytotoxicity of AβpE3-42 aggregates in cell viability test. To examine the cognitive deficits induced by synthetic AβpE3-42 peptides, AβpE3-42 oligomers were intracerebroventricularly injected into imprinting control region mice and Y-maze and Morris water maze tests were performed. We found that AβpE3-42 aggregates altered the expression level of postsynaptic density protein 95 in cortical lysates. Collectively, we produced AβpE3-42 peptides in the microwave-assisted SPPS and evaluated the amyloidogenic and pathological function of the synthesized peptides.

Abstract Indolethylamine N-methyltransferase (INMT) is a transmethylation enzyme that utilizes the methyl donor S-adenosyl-L-methionine to transfer methyl groups to amino groups of small molecule acceptor compounds. INMT is best known for its role in the biosynthesis of N,N-Dimethyltryptamine (DMT), a psychedelic compound found in mammalian brain and other tissues. In mammals, biosynthesis of DMT is thought to occur via the double methylation of tryptamine, where INMT first catalyzes the biosynthesis of N-methyltryptamine (NMT) and then DMT. However, it is unknown whether INMT is necessary for the biosynthesis of endogenous DMT. To test this, we generated a novel INMT-knockout rat model and studied tryptamine methylation using radiometric enzyme assays, thin-layer chromatography, and ultra-high-performance liquid chromatography tandem mass spectrometry. We also studied tryptamine methylation in recombinant rat, rabbit, and human INMT. We report that brain and lung tissues from both wild type and INMT-knockout rats show equal levels of tryptamine-dependent activity, but that the enzymatic products are neither NMT nor DMT. In addition, rat INMT was not sufficient for NMT or DMT biosynthesis. These results suggest an alternative enzymatic pathway for DMT biosynthesis in rats. This work motivates the investigation of novel pathways for endogenous DMT biosynthesis in mammals.

Alzheimer’s disease (AD) is the most prevalent type of dementia and is characterized by cognitive deficits and accumulation of pathological plaques. Owing to the complexity of AD development, paradigms for AD research and drug discovery have shifted to target factors that mediate multiple pathogenesis in AD. Increasing evidence suggests that the suppression of the Wnt/β-catenin signaling pathway plays substantial roles in AD progression. However, the underlying mechanism for the suppression of Wnt/β-catenin pathway associated with AD pathogenesis remains unexplored. In this study, we identified that CXXC5, a negative feedback regulator of the Wnt/β-catenin pathway, was overexpressed in the tissues of AD patients and 5xFAD transgenic mice paired with the suppression of Wnt/β-catenin pathway and its target genes related to AD. The level of CXXC5 was upregulated, upon aging of 5xFAD mice. AD characteristics including cognitive deficits, amyloid-β (Aβ) plaques, neuronal inflammation, and age-dependent increment of AD-related markers were rescued in Cxxc5-/-/5xFAD mice. 5-methoxyindirubin-3'-oxime (KY19334), a small molecule that restores the suppressed Wnt/β-catenin pathway via interference of the CXXC5-Dvl interaction, significantly improved the overall pathogenic phenotypes of 5xFAD mice. Collectively, our findings revealed that CXXC5 plays a key role in AD pathogenesis and suggest inhibition of CXXC5-Dvl interaction as a new therapeutic approach for AD.

Abstract Viperin is a radical S-adenosylmethionine enzyme that catalyzes the formation of the antiviral ribonucleotide, 3’-deoxy-3’,4’-didehydroCTP. The enzyme is conserved across all kingdoms of life, and in higher animals viperin is localized to the ER-membrane and lipid droplets through an N-terminal extension that forms an amphipathic helix. Evidence suggests that the N-terminal extension plays an important role in viperin’s interactions with other membrane proteins. These interactions serve to modulate the activity of various other enzymes that are important for viral replication and constitute another facet of viperin’s antiviral properties, distinct from its catalytic activity. However, the full-length form of the enzyme, which has proved refractory to expression in E. coli, has not been previously purified. Here we report the purification of the full-length form of viperin from HEK293T cells transfected with viperin. The purification method utilizes nanodiscs to maintain the protein in its membrane-bound state. Unexpectedly, the enzyme exhibits significantly lower catalytic activity once purified, suggesting that interactions with other ER-membrane components may be important to maintain viperin’s activity.

Measurement(s) electroencephalography (EEG) Technology Type(s) electroencephalography (EEG) Factor Type(s) Chronic sleep restriction Sample Characteristic - Organism Mus musculus

Abstract Suicide is a leading cause of death worldwide, presenting a serious public health problem. We aimed to investigate the biological basis of suicide completion using proteomics on postmortem brain tissue. Thirty-six postmortem brain samples (23 suicide completers and 13 controls) were collected. We evaluated the proteomic profile in the prefrontal cortex (Broadmann area 9, 10) using tandem mass tag-based quantification with liquid chromatography–tandem mass spectrometry. Bioinformatics tools were used to elucidate the biological mechanisms related to suicide. Subgroup analysis was conducted to identify common differentially expressed proteins among clinically different groups. Of 9801 proteins identified, 295 were differentially expressed between groups. Suicide completion samples were mostly enriched in the endocannabinoid and apoptotic pathways (CAPNS1, CSNK2B, PTP4A2). Among the differentially expressed proteins, GSTT1 was identified as a potential biomarker among suicide completers with psychiatric disorders. Our findings suggest that the previously under-recognized endocannabinoid system and apoptotic processes are highly involved in suicide.

Blind super-resolution (blind-SR) is an important task in the field of computer vision and has various applications in real-world. Blur kernel estimation is the main element of blind-SR along with the adaptive SR networks and a more accurately estimated kernel guarantees a better performance. Recently, generative adversarial networks (GANs), comparing recurrence patches across scales, have been the most successful unsupervised kernel estimation methods. However, they still involve several problems. ① Their sharpness discrimination ability has been noted as being too weak, causing them to focus more on pattern shapes than sharpness. ② In some cases, kernel correction processes were omitted; however, these are essential because the optimally generated kernel may be narrower than a point spread function (PSF) except when the PSF is ideal low-pass filter. ③ Previous studies also did not consider that GANs are affected by the thickness of edges as well as PSF. Thus, in this paper, 1) we propose a degradation and ranking comparison process designed to induce GAN models to became sensitive to image sharpness, and 2) propose a scale-free kernel correction technique using Gaussian kernel approximation including a thickness parameter. To improve the kernel accuracy further, we 3) propose a combination model of the proposed GAN and DIP(deep image prior) for more supervision, and designed a kernel correction network to propagate gradients through developed correction method. Several experiments demonstrate that our methods enhanced the $l_{2}$ error and the shape of the kernel significantly. In addition, by combining with ordinary blind-SR algorithms, the best reconstruction accuracy was achieved among unsupervised blur kernel estimation methods.

Abstract Alzheimer disease (AD) is a leading cause of dementia that has gained prominence in our aging society. Yet, the complexity of diagnosing AD and measuring its invasiveness poses an obstacle. To this end, blood-based biomarkers could mitigate the inconveniences that impede an accurate diagnosis. We developed models to diagnose AD and measure the severity of neurocognitive impairment using blood protein biomarkers. Multiple reaction monitoring–mass spectrometry, a highly selective and sensitive approach for quantifying targeted proteins in samples, was used to analyze blood samples from 4 AD groups: cognitive normal control, asymptomatic AD, prodromal AD), and AD dementia. Multimarker models were developed using 10 protein biomarkers and apolipoprotein E genotypes for amyloid beta and 10 biomarkers with Korean Mini-Mental Status Examination (K-MMSE) score for predicting Alzheimer disease progression. The accuracies for the AD classification model and AD progression monitoring model were 84.9% (95% CI 82.8 to 87.0) and 79.1% (95% CI 77.8 to 80.5), respectively. The models were more accurate in diagnosing AD, compared with single APOE genotypes and the K-MMSE score. Our study demonstrates the possibility of predicting AD with high accuracy by blood biomarker analysis as an alternative method of screening for AD.

Hepatocellular carcinoma (HCC) is a malignant cancer with one of the highest mortality rates. Des‐γ‐carboxyprothrombin (DCP) is an HCC serologic surveillance marker that can complement the low sensitivity of alpha‐fetoprotein (AFP). DCP exists in the blood as a mixture of proteoforms from an impaired carboxylation process at glutamic acid (Glu) residues within the N‐terminal domain. The heterogeneity of DCP may affect the accuracy of measurements because DCP levels are commonly determined using an immunoassay that relies on antibody reactivity to an epitope in the DCP molecule. In this study, we aimed to improve the DCP measurement assay by applying a mass spectrometry (MS)‐based approach for a more inclusive quantification of various DCP proteoforms. We developed a multiple‐reaction monitoring–MS (MRM‐MS) assay to quantify multiple noncarboxylated peptides included in the various des‐carboxylation states of DCP. We performed the MRM‐MS assay in 300 patients and constructed a robust diagnostic model that simultaneously monitored three noncarboxylated peptides. The MS‐based quantitative assay for DCP had reliable surveillance power, which was evident from the area under the receiver operating characteristic curve (AUROC) values of 0.874 and 0.844 for the training and test sets, respectively. It was equivalent to conventional antibody‐based quantification, which had AUROC values at the optimal cutoff (40 mAU/mL) of 0.743 and 0.704 for the training and test sets, respectively. The surveillance performance of the MS‐based DCP assay was validated using an independent validation set consisting of 318 patients from an external cohort, resulting in an AUROC value of 0.793. Conclusion: Due to cost effectiveness and high reproducibility, the quantitative DCP assay using the MRM‐MS method is superior to antibody‐based quantification and has equivalent performance.

Abstract Neural network-based generative models have been actively investigated as an inverse design method for finding novel materials in a vast design space. However, the applicability of conventional generative models is limited because they cannot access data outside the range of training sets. Advanced generative models that were devised to overcome the limitation also suffer from the weak predictive power on the unseen domain. In this study, we propose a deep neural network-based forward design approach that enables an efficient search for superior materials far beyond the domain of the initial training set. This approach compensates for the weak predictive power of neural networks on an unseen domain through gradual updates of the neural network with active transfer learning and data augmentation methods. We demonstrate the potential of our framework with a grid composite optimization problem that has an astronomical number of possible design configurations. Results show that our proposed framework can provide excellent designs close to the global optima, even with the addition of a very small dataset corresponding to less than 0.5% of the initial training dataset size.

Abstract Alzheimer’s disease (AD) is the most common type of dementia characterized by the abnormal accumulation of amyloid-β (Aβ) in the brain. Aβ misfolding is associated with neuroinflammation and synaptic dysfunction, leading to learning and memory deficits. Therefore, Aβ production and aggregation have been one of the most popular drug targets for AD. Failures of drug candidates regulating the aforementioned Aβ cascade stimulated development of immunotherapy agents for clearance of accumulated Aβ in the brain. Here, we report that quinacrine, a blood–brain barrier penetrating antimalarial chemical drug, dissociates Aβ plaques in the brain of AD transgenic mice. When co-incubated with pre-formed Aβ fibrils, quinacrine decreased thioflavin T-positive β-sheets in vitro, on top of its inhibitory function on the fibril formation. We confirmed that quinacrine induced dissociation of high-molecular-weight Aβ aggregates into low-molecular-weight species by dot blots in association with size cut-off filtrations. Quinacrine was then administered to adult 5XFAD transgenic mice via weekly intravenous injections for 6 weeks, and we found a significant reduction of Aβ plaques and astrocytosis in their cortex and hippocampus. In western blots of quinacrine-administered mouse brains, amelioration of AD-related biomarkers, glial fibrillary acidic protein, postsynaptic protein 95, phosphorylated cAMP response element-binding protein, phosphorylated c-Jun N-terminal kinase were observed. Lastly, quinacrine-stimulated dissociation of misfolded aggregates induced recovery of synaptic function associated with Aβ in excitatory post-synaptic current recordings of primary rat cortical neurons treated with Aβ aggregates and quinacrine. Collectively, quinacrine can directly dissociate Aβ fibrils and alleviate decreased synaptic functions.

The prevalence of smart devices and cloud computing has led to an explosion in the amount of data generated by IoT devices [...]

This study presents a novel shape-morphing wheel that enables to not only traverse flat ground quickly in a circular configuration but also overcome obstacles like steps effectively in a transformed configuration. The proposed wheel mechanism has two degrees-of-freedoms (DOFs) to change its wheel radius and the tilting angle of its lobe simultaneously in response to obstacles of various sizes. The kinematic requirements for the 2-DOF shape-morphing wheel mechanism are first defined. Then, the proper mechanisms for the proposed wheel mechanism are exhaustively searched. As a result, five mechanisms are selected in combination with four-bar mechanism to synchronize the motions of wheel lobes. From the kinematic viewpoints including the singularity, transformation range and interference, the characteristics of selected mechanisms are analyzed extensively, and a novel 2-DOF shape-morphing wheel mechanism has been successfully constructed.

Abstract Transgenic mouse models recapitulating Alzheimer’s disease (AD) pathology are pivotal in molecular studies and drug evaluation. In transgenic models selectively expressing amyloid-β (Aβ), thioflavin S (ThS), a fluorescent dye with β-sheet binding properties, is widely employed to observe amyloid plaque accumulation. In this study, we investigated the possibility that a commonly used Aβ-expressing AD model mouse, 5XFAD, generates ThS-positive aggregates of β-sheet structures in addition to Aβ fibrils. To test this hypothesis, brain sections of male and female 5XFAD mice were double-stained with ThS and monoclonal antibodies against Aβ, tau, or α-synuclein, all of which aggregates are detected by ThS. Our results revealed that, in addition to amyloid plaques, 5XFAD mice express ThS-positive phospho-tau (p-tau) aggregates. Upon administration of a small molecule that exclusively disaggregates Aβ to 5XFAD mice for six weeks, we found that the reduction level of plaques was smaller in brain sections stained by ThS compared to an anti-Aβ antibody. Our findings implicate that the use of ThS complicates the quantification of amyloid plaques and the assessment of Aβ-targeting drugs in 5XFAD mice.

As communication technology advances with 5G, the amount of data accumulated online is explosively increasing. From these data, valuable results are being created through data analysis technologies. Among them, artificial intelligence (AI) has shown remarkable performances in various fields and is emerging as an innovative technology. In particular, machine learning and deep learning models are evolving rapidly and are being widely deployed in practical applications. Meanwhile, behind the widespread use of these models, privacy concerns have been continuously raised. In addition, as substantial privacy invasion attacks against machine learning and deep learning models have been proposed, the importance of research on privacy-preserving AI is being emphasized. Accordingly, in the field of differential privacy, which has become a de facto standard for preserving privacy, various mechanisms have been proposed to preserve the privacy of AI models. However, it is unclear how to calibrate appropriate privacy parameters, taking into account the trade-off between a model’s utility and data privacy. Moreover, there is a lack of research that analyzes the relationship between the degree of differential privacy guarantee and privacy invasion attacks. In this paper, we investigate the resistance of differentially private AI models to substantial privacy invasion attacks according to the degree of privacy guarantee, and analyze how privacy parameters should be set to prevent the attacks while preserving the utility of the models. Specifically, we focus on generative adversarial networks (GAN), which is one of the most sophisticated AI models, and on the membership inference attack, which is the most fundamental privacy invasion attack. In the experimental evaluation, by quantifying the effectiveness of the attack based on the degree of privacy guarantee, we show that differential privacy can simultaneously preserve data privacy and the utility of models with moderate privacy budgets.

Abstract Amyloid‐β (Aβ) deposition in the brain is a primary biomarker of Alzheimer's disease (AD) and Aβ measurement for AD diagnosis mostly depends on brain imaging and cerebrospinal fluid analyses. Blood Aβ can become a reliable surrogate biomarker if issues of low concentration for conventional laboratory instruments and uncertain correlation with brain Aβ are solved. Here, brain‐to‐blood efflux of Aβ is stimulated in AD transgenic mice by orally administrating a chemical that dissociates amyloid plaques and observing the subsequent increase of blood Aβ concentration. 5XFAD transgenic and wild‐type mice of varying ages and genders are prepared, and blood samples of each mouse are collected six times for 12 weeks; three weeks of no treatment and additional nine weeks of daily oral administration, ad libitum, of Aβ plaque‐dissociating chemical agent. By the dissociation of Aβ aggregates, the altered levels of plasma Aβ distinguish between transgenic and wild‐type mice, displaying potential as an amyloid burden marker of AD brains.

Apart from the enzymatic role of ketohexokinase isoform A (KHK-A) in fructose metabolism the alternative physiological functions of the enzyme are unclear. Here, the authors show that KHK-A mediates fructose-induced metastasis in breast cancer through a nuclear role in repressing the transcriptional activity of the cell-adhesion molecule CDH1.

This paper examines the trends and prospects of medical history in Japan. The study of medical history in Japan has developed in various periods and themes. In particular, many studies period have actively made full use of old documents and materials that have been well-preserved. This paper introduces the research trends of medical history in Japan, while discussing the issues surrounding the concept and designation of medical history in present day Japan. This can be seen as an inevitable phenomenon that emerged as methods of medical history research have become diversified, and there are many suggestions related to the future direction of this study. Based on this, this paper points out the characteristics of medical history research conducted in each period since the first half of the twentieth century. In particular, this investigation confirmed that the subjects and research methods of medical history became diversified under the influence of the nation state theory. Furthermore, this study also found that the major topics of medical history research are analysis of medical books, doctors and medical personnel, the starting point of modern medicine, the establishment and change of the medical system, the social impact of infectious diseases, and the discipline and management of the national body. In addition, studies are being conducted to compare how the regulations and operations of medicine and medical and hygiene systems are being developed in the context of “East Asia.”

Abstract Background Adult T-cell leukemia lymphoma (ATLL) is a chemotherapy-resistant malignancy with a median survival of less than one year that will afflict between one hundred thousand and one million individuals worldwide who are currently infected with human T-cell leukemia virus type 1. Recurrent somatic mutations in host genes have exposed the T-cell receptor pathway through nuclear factor κB to interferon regulatory factor 4 (IRF4) as an essential driver for this malignancy. We sought to determine if IRF4 represents a therapeutic target for ATLL and to identify downstream effectors and biomarkers of IRF4 signaling in vivo. Results ATLL cell lines, particularly Tax viral oncoprotein-negative cell lines, that most closely resemble ATLL in humans, were sensitive to dose- and time-dependent inhibition by a next-generation class of IRF4 antisense oligonucleotides (ASOs) that employ constrained ethyl residues that mediate RNase H-dependent RNA degradation. ATLL cell lines were also sensitive to lenalidomide, which repressed IRF4 expression. Both ASOs and lenalidomide inhibited ATLL proliferation in vitro and in vivo. To identify biomarkers of IRF4-mediated CD4 + T-cell expansion in vivo, transcriptomic analysis identified several genes that encode key regulators of ATLL, including interleukin 2 receptor subunits α and β, KIT ligand, cytotoxic T-lymphocyte-associated protein 4, and thymocyte selection-associated high mobility group protein TOX 2. Conclusions These data support the pursuit of IRF4 as a therapeutic target in ATLL with the use of either ASOs or lenalidomide.

There is an urgent need for new biomarkers that address the shortcomings of current screening methods which fail to detect a large proportion of cases with hepatocellular carcinoma (HCC) at early stage. To develop a robust, multiple‐biomarker panel based on multiple reaction monitoring–mass spectrometry with high performance in detecting early‐stage HCC within at‐risk populations. In the discovery set, 150 samples were analyzed to identify candidate biomarkers. The resulting list of candidates was tested in the training set (713 samples) to establish a multimarker panel, which was evaluated in the validation set (305 samples). We identified 385 serum HCC biomarker candidates in the discovery set and developed a multimarker panel consisting of 28 peptides that best differentiated HCC from controls. The area under the receiver operating characteristic curve of multimarker panel was significantly higher than alpha‐fetoprotein (AFP) in the training (0.976 vs. 0.804; P

Objective: Post–bariatric surgery hypoglycemia (PBH) is defined as the presence of neuroglycopenic symptoms accompanied by postprandial hypoglycemia in bariatric surgery patients. Recent clinical studies using continuous glucose monitoring (CGM) technology revealed that PBH is more frequently observed in vertical sleeve gastrectomy (VSG) patients than previously recognized. PBH cannot be alleviated by current medication. Therefore, a model system to investigate the mechanism and treatment is required. Methods: We used CGM in a rat model of VSG and monitored the occurrence of glycemic variability and hypoglycemia in various meal conditions for 4 weeks after surgery. Another cohort of VSG rats with CGM was used to investigate whether the blockade of glucagon-like peptide-1 receptor (GLP-1R) signaling alleviates these symptoms. A mouse VSG model was used to investigate whether the impaired glucose counterregulatory system causes postprandial hypoglycemia. Results: Like in humans, rats have increased glycemic variability and hypoglycemia after VSG. Postprandial hypoglycemia was specifically detected after liquid versus solid meals. Further, the blockade of GLP-1R signaling raises the glucose nadir but does not affect glycemic variability. Conclusions: Rat bariatric surgery duplicates many features of human post–bariatric surgery hypoglycemia including postprandial hypoglycemia and glycemic variability, while blockade of GLP-1R signaling prevents hypoglycemia but not the variability. Keywords: Continuous glucose monitoring, Vertical sleeve gastrectomy, Post–bariatric surgery hypoglycemia, Glycemic variability, Exendin 9-39, Glucagon-like peptide-1 receptor

The development of convolutional neural networks (CNN) has remarkably improved the current research on single image super-resolution (SISR). Several high-quality studies have been performed on reconstruction accuracy and perceptual quality, which are the two main issues in SISR. Nevertheless, numerous problems in SISR remain unsolved. SISR is inherently an ill-posed problem owing to insufficient information, and as the scale factor increases, the lack of information becomes even more pronounced. We have studied ways to solve the local characteristics of CNN to deal with additional useful information. A CNN uses a convolution layer designed based on local features, and repeatedly accumulates these features to expand a receptive field. We have explored network structures that can directly handle global information even at lower layers, which are not covered by the receptive field of a CNN. In this paper, we propose a non-local attention SISR network (NASR) that generates and utilizes the globally scattered similarity information of features. In addition, we propose a very deep architecture based on dense blocks that does not suffer from gradient vanishing without any normalization. Experimental results on standard benchmark datasets indicate the effectiveness of the proposed network, which exhibits state-of-the-art performance in terms of reconstruction accuracy and perceptual quality.

Steps are frequently encountered while mobile robots move in indoor environments; thus, the ability to overcome a step is essential to indoor mobile robots. In this study, a new adaptive transformable wheel is conceptually proposed to effectively overcome steps of different sizes. The center trajectory of the proposed wheel is optimally designed to minimize its fluctuations while the robot overcomes a step. For this purpose, a kinematic analysis of the proposed wheel is performed to identify the points that its center must pass while the robot overcomes a step. The center trajectory is optimized with an objective function to evaluate the mobile stability of the proposed wheel under kinematic constraints to avoid undesired interferences between the wheel and the step. Extensive simulations with different steps verify that the optimal trajectory ensures stable and effective overcoming of steps. The experiment using the prototype of mobile robot equipped with the proposed wheel verifies the smoothness of resulting trajectory of wheel center.

Background and Purpose Endovascular recanalization therapy (ERT) is becoming increasingly important in the management of acute ischemic stroke (AIS). However, the hospital volume threshold for optimal ERT remains unknown. We investigated the relationship between hospital volume of ERT and risk-adjusted patient outcomes. Methods From the National Health Insurance claims data in Korea, 11,745 patients with AIS who underwent ERT from July 2011 to June 2016 in 111 hospitals were selected. We measured the hospital’s ERT volume and patient outcomes, including the 30-day mortality, readmission, and postprocedural intracranial hemorrhage (ICH) rates. For each outcome measure, we constructed risk-adjusted prediction models incorporating demographic variables, the modified Charlson comorbidity index, and the stroke severity index (SSI), and validated them. Risk-adjusted outcomes of AIS cases were compared across hospital quartiles to confirm the volume-outcome relationship (VOR) in ERT. Spline regression was performed to determine the volume threshold. Results The mean AIS volume was 14.8 cases per hospital/year and the unadjusted means of mortality, readmission, and ICH rates were 11.6%, 4.6%, and 8.6%, respectively. The VOR was observed in the risk-adjusted 30-day mortality rate across all quartile groups, and in the ICH rate between the first and fourth quartiles (P

Beam steering technology is crucial for radio frequency and infrared telecommunication signal processing. Microelectromechanical systems (MEMS) are typically used for beam steering in infrared optics-based fields but have slow operational speeds. An alternative solution is to use tunable metasurfaces. Since graphene has gate-tunable optical properties, it is widely used in electrically tunable optical devices due to ultrathin physical thickness. We propose a tunable metasurface structure using graphene in a metal gap structure that can exhibit a fast-operating speed through bias control. The proposed structure can change beam steering and can focus immediately by controlling the Fermi energy distribution on the metasurface, thus overcoming the limitations of MEMS. The operation is numerically demonstrated through finite element method simulations.

The kinase activity of inhibitory κB kinase β (IKKβ) acts as a signal transducer in the activating pathway of nuclear factor-κB (NF-κB), a master regulator of inflammation and cell death in the development of numerous hepatocellular injuries. However, the importance of IKKβ activity on acetaminophen (APAP)-induced hepatotoxicity remains to be defined. Here, a derivative of caffeic acid benzylamide (CABA) inhibited the kinase activity of IKKβ, as did IMD-0354 and sulfasalazine which show therapeutic efficacy against inflammatory diseases through a common mechanism: inhibiting IKKβ activity. To understand the importance of IKKβ activity in sterile inflammation during hepatotoxicity, C57BL/6 mice were treated with CABA, IMD-0354, or sulfasalazine after APAP overdose. These small-molecule inhibitors of IKKβ activity protected the APAP-challenged mice from necrotic injury around the centrilobular zone in the liver, and rescued the mice from hepatic damage-associated lethality. From a molecular perspective, IKKβ inhibitors directly interrupted sterile inflammation in the Kupffer cells of APAP-challenged mice, such as damage-associated molecular pattern (DAMP)-induced activation of NF-κB activity via IKKβ, and NF-κB-regulated expression of cytokines and chemokines. However, CABA did not affect the upstream pathogenic events, including oxidative stress with glutathione depletion in hepatocytes after APAP overdose. N-acetyl cysteine (NAC), the only FDA-approved antidote against APAP overdose, replenishes cellular levels of glutathione, but its limited efficacy is concerning in late-presenting patients who have already undergone oxidative stress in the liver. Taken together, we propose a novel hypothesis that chemical inhibition of IKKβ activity in sterile inflammation could mitigate APAP-induced hepatotoxicity in mice, and have the potential to complement NAC treatment in APAP overdoses.

Two new glycosylated and succinylated macrocyclic lactones, succinyl glyco-oxydifficidin (1) and succinyl macrolactin O (2), were isolated from a Bacillus strain collected from an intertidal mudflat on Anmyeon Island in Korea. The planar structures of 1 and 2 were proposed using mass spectrometric analysis and NMR spectroscopic data. The absolute configurations of 1 and 2 were determined by optical rotation, J-based configuration analysis, chemical derivatizations, including the modified Mosher’s method, and quantum-mechanics-based calculation. Biological evaluation of 1 and 2 revealed that succinyl glyco-oxydifficidin (1) inhibited/dissociated amyloid β (Aβ) aggregation, whereas succinyl macrolactin O (2) inhibited Aβ aggregation, indicating their therapeutic potential for disassembling and removing Aβ aggregation.

Abstract Background PVT1 has emerged as an oncogene in many tumor types. However, its role in Barrett’s esophagus (BE) and esophageal adenocarcinoma (EAC) is unknown. The aim of this study was to assess the role of PVT1 in BE/EAC progression and uncover its therapeutic value against EAC. Methods PVT1 expression was assessed by qPCR in normal, BE, and EAC tissues and statistical analysis was performed to determine the association of PVT1 expression and EAC (stage, metastases, and survival). PVT1 antisense oligonucleotides (ASOs) were tested for their antitumor activity in vitro and in vivo. Results PVT1 expression was up-regulated in EACs compared with paired BEs, and normal esophageal tissues. High expression of PVT1 was associated with poor differentiation, lymph node metastases, and shorter survival. Effective knockdown of PVT1 in EAC cells using PVT1 ASOs resulted in decreased cell proliferation, invasion, colony formation, tumor sphere formation, and reduced proportion of ALDH1A1+ cells. Mechanistically, we discovered mutual regulation of PVT1 and YAP1 in EAC cells. Inhibition of PVT1 by PVT1 ASOs suppressed YAP1 expression through increased phosphor-LATS1and phosphor-YAP1 while knockout of YAP1 in EAC cells significantly suppressed PVT1 levels indicating a positive regulation of PVT1 by YAP1. Most importantly, we found that targeting both PVT1 and YAP1 using their specific ASOs led to better antitumor activity in vitro and in vivo. Conclusions Our results provide strong evidence that PVT1 confers an aggressive phenotype to EAC and is a poor prognosticator. Combined targeting of PVT1 and YAP1 provided the highest therapeutic index and represents a novel therapeutic strategy.

Abstract Background Alcohol abuse and alcoholism lead to alcohol liver disease such as alcoholic fatty liver. Parkin is a component of the multiprotein E3 ubiquitin ligase complex and is associated with hepatic lipid accumulation. However, the role of parkin in ethanol-induced liver disease has not been reported. Here, we tested the effect of parkin on ethanol-induced fatty liver in parkin knockout (KO) mice with chronic ethanol feeding. Methods Male wild type (WT) and parkin KO mice (10–12 weeks old, n = 10) were fed on a Lieber-DeCarli diet containing 6.6% ethanol for 10 days. Liver histological, biochemical, and gene-expression studies were performed. Results Parkin KO mice exhibited lower hepatosteatosis after ethanol consumption. Because several studies reported that β-catenin is a critical factor in ethanol metabolism and protects against alcohol-induced hepatosteatosis, we investigated whether parkin changes β-catenin accumulation in the liver of ethanol-fed mice. Our results show that β-catenin was greatly accumulated in the livers of ethanol-fed parkin KO mice compared to ethanol-fed WT mice, and that parkin binds to β-catenin and promotes its degradation it by ubiquitination. Moreover, the β-catenin inhibitor IWR-1 abrogated the attenuation of ethanol-induced hepatic lipid accumulation by parkin deficiency in the livers of parkin KO mice and parkin siRNA-transfected human hepatic cell line. Conclusions Parkin deficiency prevents ethanol-induced hepatic lipid accumulation through promotion of β-catenin signaling by failure of β-catenin degradation.

Alzheimer’s disease: early diagnostic biomarkers in body fluids Markers from body fluids could help clinicians diagnose Alzheimer’s disease before cognitive decline appears. After numerous setbacks in treating advanced Alzheimer’s, researchers are eager to identify biological indicators that facilitate earlier disease detection and interception. A review by YoungSoo Kim and colleagues at Yonsei University in South Korea, explores the promise of ‘fluid biomarkers,’ which enables diagnosis using cerebrospinal fluid (CSF), blood, oral, ocular, and olfactory fluid samples. Shifts in CSF levels of amyloid beta and tau, two proteins central to Alzheimer’s pathology, can reliably monitor at-risk individuals. Although CSF collection is unpleasant for patients, it remains more promising than blood, where current data for candidate fluid biomarkers are relatively inconclusive. In this review, investigations to discover safer, cheaper, and more reliable diagnostic tools to shift treatment from alleviation to prevention are introduced.

Stairs are common obstacles in indoor environments and are difficult to overcome for robots. The speed of robot stair-climbing should be similar to that of humans for commercial products, but their speed remains limited. Additionally, the variety of dimensions of stairs is also a significant problem for robust stair-climbing by robots. In this paper, a curved spoke-based tri-wheel mechanism is proposed for fast and robust stair-climbing. The goal speed of stair-climbing is similar to the human speed for variously sized stairs. The proposed wheel system is composed of a tri-wheel mechanism with a curved spoke, wherein the dimensions of the mechanism are determined based on a kinematic analysis. Between the tri-wheels, a stopper mechanism acts to make the initial condition of the sequential stair-climbing the same as the initial starting condition. Static analysis to analyze the minimum friction coefficient is performed to verify the performance of the robot. Experiments based on the prototype are performed to verify the stair-climbing speed for variously sized stairs; the results indicate that fast and robust stair climbing performance is achieved. These findings can be used to design an indoor service robot for various applications.

Objectives The purpose of this study was to estimate the mediating effect of subjective unmet healthcare needs on poor health. The mediating effect of unmet needs on health outcomes was estimated. Methods Cross-sectional research method was used to analyze Korea Health Panel data from 2011 to 2015, investigating the mediating effect for each annual dataset and lagged dependent variables. Results The magnitude of the effect of low income on poor health and the mediating effect of unmet needs were estimated using age, sex, education level, employment status, healthcare insurance status, disability, and chronic disease as control variables and self-rated health as the dependent variable. The mediating effect of unmet needs due to financial reasons was between 14.7% to 32.9% of the total marginal effect, and 7.2% to 18.7% in lagged model. Conclusions The fixed-effect logit model demonstrated that the existence of unmet needs raised the likelihood of poor self-rated health. However, only a small proportion of the effects of low income on health was mediated by unmet needs, and the results varied annually. Further studies are necessary to search for ways to explain the varying results in the Korea Health Panel data, as well as to consider a time series analysis of the mediating effect. The results of this study present the clear implication that even though it is crucial to address the unmet needs, but it is not enough to tackle the income related health inequalities.

Objectives The Regional Cardiocerebrovascular Center (RCCVC) Project designated local teaching hospitals as RCCVCs, in order to improve patient outcomes of acute cardiocerebrovascular emergencies by founding a regional system that can adequately transfer and manage patients within 3 hours. We investigated the effects of RCCVC establishment on treatment volume and 30-day mortality. Methods We constructed a panel dataset by extracting all acute myocardial infarction cases that occurred from 2007 to 2016 from the Health Insurance Review and Assessment Service claims data, a national and representative source. We then used a panel fixed-effect model to estimate the impacts of RCCVC establishment on patient outcomes. Results We found that the number of cases of acute myocardial infarction that were treated increased chronologically, but when the time effect and other related covariates were controlled for, RCCVCs only significantly increased the number of treatment cases of female in large catchment areas. There was no statistically significant impact on 30-day mortality. Conclusions The establishment of RCCVCs increased the number of treatment cases of female, without increasing the mortality rate. Therefore, the RCCVCs might have prevented potential untreated deaths by increasing the preparedness and capacity of hospitals to treat acute myocardial infarction patients.

High-quality factor dielectric microcavities like whispering-gallery-mode resonators can be widely applied in fields such as laser, optical sensor, switch, and filter. We propose the whispering-gallery-mode double-disk cavity comprising dielectric disks apart along the face of the disk. The electric field of each disk with opposite phases was excited; the emitted radiation field was annihilated by destructive interference. We numerically achieved a 5.67-fold enhancement in quality factor at the double-disk cavity with a radius, thickness, and gap distance of 850 nm, 220 nm, and 220 nm, respectively, compared to a single dielectric disk with the same structural conditions.

The semiconductor etch cluster facility is the most used facility platform in the semiconductor manufacturing process. Optimizing cluster facilities can depend on production schedules and can have a direct impact on productivity. According to the diversity of semiconductor processes, the complexity of optimization is also increasing. Various optimization methods have been studied in many papers for optimizing such a complex cluster facility. However, there is a lack of discussion of how these methods can apply to practical semiconductor manufacturing fabs and the actual performance results. Even now, data analysis and optimal parameter derivation for maximizing the productivity of cluster manufacturing in semiconductor manufacturing fabs are continuing. In this study, we propose an automated method for data collection and analysis of the cluster, which used to be done manually. In addition, the derivation of optimization parameters and application to facilities are addressed. This automated method could improve the manual analysis methods, such as simulation through data analysis using machine learning algorithms. It could also solve the inefficiency caused by manual analysis performed within the network inside the semiconductor manufacturing fabs.

Summary: The oncogenic function of suppressor of variegation, enhancer of zeste and MYeloid-Nervy-DEAF1-domain family methyltransferase Smyd3 has been implicated in various malignancies, including hepatocellular carcinoma (HCC). Here, we show that targeting Smyd3 by next-generation antisense oligonucleotides (Smyd3-ASO) is an efficient approach to modulate its mRNA levels in vivo and to halt the growth of already initiated liver tumors. Smyd3-ASO treatment dramatically decreased tumor burden in a mouse model of chemically induced HCC and negatively affected the growth rates, migration, oncosphere formation, and xenograft growth capacity of a panel of human hepatic cancer cell lines. Smyd3-ASOs prevented the activation of oncofetal genes and the development of cancer-specific gene expression program. The results point to a mechanism by which Smyd3-ASO treatment blocks cellular de-differentiation, a hallmark feature of HCC development, and, as a result, it inhibits the expansion of hepatic cancer stem cells, a population that has been presumed to resist chemotherapy.