Shortest-Path Percolation on Random Networks.

We propose a bond-percolation model intended to describe the consumption, and eventual exhaustion, of resources in transport networks. Edges forming minimum-length paths connecting demanded origin-destination nodes are removed if below a certain budget. As pairs of nodes are demanded and edges are removed, the macroscopic connected component of the graph disappears, i.e., the graph undergoes a percolation transition. Here, we study such a shortest-path-percolation transition in homogeneous random graphs where pairs of demanded origin-destination nodes are randomly generated, and fully characterize it by means of finite-size scaling analysis. If budget is finite, the transition is identical to the one of ordinary percolation, where a single giant cluster shrinks as edges are removed from the graph; for infinite budget, the transition becomes more abrupt than the one of ordinary percolation, being characterized by the sudden fragmentation of the giant connected component into a multitude of clusters of similar size.

Melatonin alleviates myocardial dysfunction through inhibition of endothelial-to-mesenchymal transition via the NF-κB pathway.

Endothelial-to-mesenchymal transition (EndMT) is a complex biological process of cellular transdifferentiation by which endothelial cells (ECs) lose their characteristics and acquire mesenchymal properties, leading to cardiovascular remodeling and complications in the adult cardiovascular diseases environment. Melatonin is involved in numerous physiological and pathological processes, including aging, and has anti-inflammatory and antioxidant activities. This molecule is an effective therapeutic candidate for preventing oxidative stress, regulating endothelial function, and maintaining the EndMT balance to provide cardiovascular protection. Although recent studies have documented improved cardiac function by melatonin, the mechanism of action of melatonin on EndMT remains unclear. The present study investigated the effects of melatonin on induced EndMT by transforming growth factor-ß2/interleukin-1ß in both in vivo and in vitro models. The results revealed that melatonin reduced the migratory ability and reactive oxygen species levels of the cells and ameliorated mitochondrial dysfunction in vitro. Our findings indicate that melatonin prevents endothelial dysfunction and inhibits EndMT by activating related pathways, including nuclear factor kappa B and Smad. We also demonstrated that this molecule plays a crucial role in restoring cardiac function by regulating the EndMT process in the ischemic myocardial condition, both in vessel organoids and myocardial infarction (MI) animal models. In conclusion, melatonin is a promising agent that attenuates EC dysfunction and ameliorates cardiac damage compromising the EndMT process after MI.

Administration of Gas6 attenuates lung fibrosis via inhibition of the epithelial-mesenchymal transition and fibroblast activation.

The epithelial-mesenchymal transition (EMT) and fibroblast activation are major events in idiopathic pulmonary fibrosis pathogenesis. Here, we investigated whether growth arrest-specific protein 6 (Gas6) plays a protective role in lung fibrosis via suppression of the EMT and fibroblast activation. rGas6 administration inhibited the EMT in isolated mouse ATII cells 14 days post-BLM treatment based on morphologic cellular alterations, changes in mRNA and protein expression profiles of EMT markers, and induction of EMT-activating transcription factors. BLM-induced increases in gene expression of fibroblast activation-related markers and the invasive capacity of primary lung fibroblasts in primary lung fibroblasts were reversed by rGas6 administration. Furthermore, the hydroxyproline content and collagen accumulation in interstitial areas with damaged alveolar structures in lung tissue were reduced by rGas6 administration. Targeting Gas6/Axl signaling events with specific inhibitors of Axl (BGB324), COX-2 (NS-398), EP1/EP2 receptor (AH-6809), or PGD2 DP2 receptor (BAY-u3405) reversed the inhibitory effects of rGas6 on EMT and fibroblast activation. Finally, we confirmed the antifibrotic effects of Gas6 using Gas6-/- mice. Therefore, Gas6/Axl signaling events play a potential role in inhibition of EMT process and fibroblast activation via COX-2-derived PGE2 and PGD2 production, ultimately preventing the development of pulmonary fibrosis.

Leak Event Diagnosis for Power Plants: Generative Anomaly Detection Using Prototypical Networks.

Anomaly detection systems based on artificial intelligence (AI) have demonstrated high performance and efficiency in a wide range of applications such as power plants and smart factories. However, due to the inherent reliance of AI systems on the quality of training data, they still demonstrate poor performance in certain environments. Especially in hazardous facilities with constrained data collection, deploying these systems remains a challenge. In this paper, we propose Generative Anomaly Detection using Prototypical Networks (GAD-PN) designed to detect anomalies using only a limited number of normal samples. GAD-PN is a structure that integrates CycleGAN with Prototypical Networks (PNs), learning from metadata similar to the target environment. This approach enables the collection of data that are difficult to gather in real-world environments by using simulation or demonstration models, thus providing opportunities to learn a variety of environmental parameters under ideal and normal conditions. During the inference phase, PNs can classify normal and leak samples using only a small number of normal data from the target environment by prototypes that represent normal and abnormal features. We also complement the challenge of collecting anomaly data by generating anomaly data from normal data using CycleGAN trained on anomaly features. It can also be adapted to various environments that have similar anomalous scenarios, regardless of differences in environmental parameters. To validate the proposed structure, data were collected specifically targeting pipe leakage scenarios, which are significant problems in environments such as power plants. In addition, acoustic ultrasound signals were collected from the pipe nozzles in three different environments. As a result, the proposed model achieved a leak detection accuracy of over 90% in all environments, even with only a small number of normal data. This performance shows an average improvement of approximately 30% compared with traditional unsupervised learning models trained with a limited dataset.

Applicability of Brassica juncea as a bioindicator for As contamination in soil near the abandoned mine area.

Soil monitoring in abandoned mine areas is important from the perspective of ecological and human health risk. Arsenic (As) is a predominant metalloid contaminant in abandoned mine area and its behavior has been influenced by various soil characteristics. Bioindicator can be a useful tool in terms of testing the extent to which they are uptaken by plants bioavailability. Eighteen soils near the mine tailings dam were collected to investigate the effect of As contamination on As absorption by Brassica juncea. The pH range of the experimental soils was between 4.90 and 8.55, and the total As concentrations were between 34 mg kg-1 and 3017 mg kg-1. The bioavailability of As was evaluated by Olsen method, and B. juncea was cultivated in eighteen soils for 3 weeks. Principal component analysis, correlation, and multiple regression analysis were performed to estimate a significant factor affecting As uptake by B. juncea. All statistical results indicated that As bioavailability in soil is the main factor affecting As uptake in root and shoot of B. juncea. Although translocation process, the amount of As in shoot was exponentially explained by As bioavailability in soil. This result suggests that the contamination and bioavailability of As can be confirmed only by analyzing the shoot of B. juncea, which is be easily found in environmental ecosystem, and implies the applicability of B. juncea as a bioindicator for the monitoring of As contamination and its behavior in soil ecosystem.

Intelligent Complementary Multi-Modal Fusion for Anomaly Surveillance and Security System.

Recently, security monitoring facilities have mainly adopted artificial intelligence (AI) technology to provide both increased security and improved performance. However, there are technical challenges in the pursuit of elevating system performance, automation, and security efficiency. In this paper, we proposed intelligent anomaly detection and classification based on deep learning (DL) using multi-modal fusion. To verify the method, we combined two DL-based schemes, such as (i) the 3D Convolutional AutoEncoder (3D-AE) for anomaly detection and (ii) the SlowFast neural network for anomaly classification. The 3D-AE can detect occurrence points of abnormal events and generate regions of interest (ROI) by the points. The SlowFast model can classify abnormal events using the ROI. These multi-modal approaches can complement weaknesses and leverage strengths in the existing security system. To enhance anomaly learning effectiveness, we also attempted to create a new dataset using the virtual environment in Grand Theft Auto 5 (GTA5). The dataset consists of 400 abnormal-state data and 78 normal-state data with clip sizes in the 8-20 s range. Virtual data collection can also supplement the original dataset, as replicating abnormal states in the real world is challenging. Consequently, the proposed method can achieve a classification accuracy of 85%, which is higher compared to the 77.5% accuracy achieved when only employing the single classification model. Furthermore, we validated the trained model with the GTA dataset by using a real-world assault class dataset, consisting of 1300 instances that we reproduced. As a result, 1100 data as the assault were classified and achieved 83.5% accuracy. This also shows that the proposed method can provide high performance in real-world environments.

Enrichment of Activated Fibroblasts as a Potential Biomarker for a Non-Durable Response to Anti-Tumor Necrosis Factor Therapy in Patients with Crohn's Disease.

We investigated whether the response to anti-tumor necrosis factor (anti-TNF) treatment varied according to inflammatory tissue characteristics in Crohn's disease (CD). Bulk RNA sequencing (RNA-seq) data were obtained from inflamed and non-inflamed tissues from 170 patients with CD. The samples were clustered based on gene expression profiles using principal coordinate analysis (PCA). Cellular heterogeneity was inferred using CiberSortx, with bulk RNA-seq data. The PCA results displayed two clusters of CD-inflamed samples: one close to (Inflamed_1) and the other far away (Inflamed_2) from the non-inflamed samples. Inflamed_1 was rich in anti-TNF durable responders (DRs), and Inflamed_2 was enriched in non-durable responders (NDRs). The CiberSortx results showed that the cell fraction of activated fibroblasts was six times higher in Inflamed_2 than in Inflamed_1. Validation with public gene expression datasets (GSE16879) revealed that the activated fibroblasts were enriched in NDRs over Next, we used DRs by 1.9 times pre-treatment and 7.5 times after treatment. Fibroblast activation protein (FAP) was overexpressed in the Inflamed_2 and was also overexpressed in the NDRs in both the RISK and GSE16879 datasets. The activation of fibroblasts may play a role in resistance to anti-TNF therapy. Characterizing fibroblasts in inflamed tissues at diagnosis may help to identify patients who are likely to respond to anti-TNF therapy.

Shrimp miR-965 transfers tumoricidal mitochondria.

BACKGROUND: Micro RNA of Marsupenaeus japonicas has been known to promote apoptosis of tumor cells. However, the detailed mechanisms are not well understood. RESULTS: Using tomographic microscope, which can detect the internal structure of cells, we observed breast tumor cells following treatment of the miRNA. Intriguingly, we found that mitochondria migrate to an adjacent tumor cells through a tunneling nanotube. To recapitulate this process, we engineered a microfluidic device through which mitochondria were transferred. We show that this mitochondrial transfer process released endonuclease G (Endo G) into tumor cells, which we referred to herein as unsealed mitochondria. Importantly, Endo G depleted mitochondria alone did not have tumoricidal effects. Moreover, unsealed mitochondria had synergistic apoptotic effects with subtoxic dose of doxorubicin thereby mitigating cardiotoxicity. CONCLUSIONS: Together, we show that the mitochondrial transfer through microfluidics can provide potential novel strategies towards tumor cell death.

Resource-allocation constraint governs structure and function of microbial communities in metabolic modeling.

Predictive modeling tools for assessing microbial communities are important for realizing transformative capabilities of microbiomes in agriculture, ecology, and medicine. Constraint-based community-scale metabolic modeling is unique in its potential for making mechanistic predictions regarding both the structure and function of microbial communities. However, accessing this potential requires an understanding of key physicochemical constraints, which are typically considered on a per-species basis. What is needed is a means of incorporating global constraints relevant to microbial ecology into community models. Resource-allocation constraint, which describes how limited resources should be distributed to different cellular processes, sets limits on the efficiency of metabolic and ecological processes. In this study, we investigate the implications of resource-allocation constraints in community-scale metabolic modeling through a simple mechanism-agnostic implementation of resource-allocation constraints directly at the flux level. By systematically performing single-, two-, and multi-species growth simulations, we show that resource-allocation constraints are indispensable for predicting the structure and function of microbial communities. Our findings call for a scalable workflow for implementing a mechanistic version of resource-allocation constraints to ultimately harness the full potential of community-scale metabolic modeling tools.

Suppressive effect of α-mangostin for cancer stem cells in colorectal cancer via the Notch pathway.

BACKGROUND: Since colon cancer stem cells (CSCs) play an important role in chemoresistance and in tumor recurrence and metastasis, targeting of CSCs has emerged as a sophisticated strategy for cancer therapy. α-mangostin (αM) has been confirmed to have antiproliferative and apoptotic effects on cancer cells. This study aimed to evaluate the selective inhibition of αM on CSCs in colorectal cancer (CRC) and the suppressive effect on 5-fluorouracil (5-FU)-induced CSCs. METHODS: The cell viability assay was performed to determine the optimal concentration of αM. A sphere forming assay and flow cytometry with CSC markers were carried out to evaluate the αM-mediated inhibition of CSCs. Western blot analysis and quantitative real-time PCR were performed to investigate the effects of αM on the Notch signaling pathway and colon CSCs. The in vivo anticancer efficacy of αM in combination with 5-FU was investigated using a xenograft mouse model. RESULTS: αM inhibited the cell viability and reduced the number of spheres in HT29 and SW620 cells. αM treatment decreased CSCs and suppressed the 5-FU-induced an increase in CSCs on flow cytometry. αM markedly suppressed Notch1, NICD1, and Hes1 in the Notch signaling pathway in a time- and dose-dependent manner. Moreover, αM attenuated CSC markers CD44 and CD133, in a manner similar to that upon DAPT treatment, in HT29 cells. In xenograft mice, the tumor and CSC makers were suppressed in the αM group and in the αM group with 5-FU treatment. CONCLUSION: This study shows that low-dose αM inhibits CSCs in CRC and suppresses 5-FU-induced augmentation of CSCs via the Notch signaling pathway.

Effect of bioavailable arsenic fractions on the collembolan community in an old abandoned mine waste.

Mine waste from abandoned mines poses a risk to soil ecosystems due to the dispersion of arsenic (As) in the mine waste to the nearby soil environment. Because the bioavailability of As varies depending on the As chemical fraction and exposure conditions, chemical assessment of As fractions in soil around mine waste is essential to understand their impact on soil ecosystem. Here, six sites around the mine waste were selected for investigating toxic effects of As-contaminant soil on Collembola community. To measure the As chemical fraction in soil and bioavailability, Wenzel sequential extraction employed. Meanwhile, the collembolans that live in each sampling site were identified at the species level, and the characteristics and composition of the collembola community were investigated. The mobility fraction (F1 + F2 + F3; MF) was related to the risk to the collembolan community, and the adverse impact of high MF appeared to lead to a decrease in abundance, richness, and Shannon index. According to non-metric multidimensional scaling analysis, F1, F2, F3, and pH were shown as the significant factor explaining the NMDS space. Especially, the sampling site with the highest concentration of F3 showed statistically different species composition from the other sites. In the case of As-contaminated soil around the old mine waste, the toxic effects of the remaining F3 in soil, as well as that of F1 and F2, should be fully considered. This study suggested that collembolan community could be used for understanding the impact of bioavailable As fraction in the old abandoned mine area.

BeReTa: a systematic method for identifying target transcriptional regulators to enhance microbial production of chemicals.

MOTIVATION: Modulation of regulatory circuits governing the metabolic processes is a crucial step for developing microbial cell factories. Despite the prevalence of in silico strain design algorithms, most of them are not capable of predicting required modifications in regulatory networks. Although a few algorithms may predict relevant targets for transcriptional regulator (TR) manipulations, they have limited reliability and applicability due to their high dependency on the availability of integrated metabolic/regulatory models. RESULTS: We present BeReTa (Beneficial Regulator Targeting), a new algorithm for prioritization of TR manipulation targets, which makes use of unintegrated network models. BeReTa identifies TR manipulation targets by evaluating regulatory strengths of interactions and beneficial effects of reactions, and subsequently assigning beneficial scores for the TRs. We demonstrate that BeReTa can predict both known and novel TR manipulation targets for enhanced production of various chemicals in Escherichia coli Furthermore, through a case study of antibiotics production in Streptomyces coelicolor, we successfully demonstrate its wide applicability to even less-studied organisms. To the best of our knowledge, BeReTa is the first strain design algorithm exclusively designed for predicting TR manipulation targets. AVAILABILITY AND IMPLEMENTATION: MATLAB code is available at https://github.com/kms1041/BeReTa (github). CONTACT: byungkim@snu.ac.krSupplementary information: Supplementary data are available at Bioinformatics online.

Rewiring FadR regulon for the selective production of ω-hydroxy palmitic acid from glucose in Escherichia coli.

ω-Hydroxy palmitic acid (ω-HPA) is a valuable compound for an ingredient of artificially synthesized ceramides and an additive for lubricants and adhesives. Production of such a fatty acid derivative is limited by chemical catalysis, but plausible by biocatalysis. However, its low productivity issue, including formations of unsaturated fatty acid (UFA) byproducts in host cells, remains as a hurdle toward industrial biological processes. In this study, to achieve selective and high-level production of ω-HPA from glucose in Escherichia coli, FadR, a native transcriptional regulator of fatty acid metabolism, and its regulon were engineered. First, FadR was co-expressed with a thioesterase with a specificity toward palmitic acid production to enhance palmitic acid production yield, but a considerable quantity of UFAs was also produced. In order to avoid the UFA production caused by fadR overexpression, FadR regulon was rewired by i) mutating FadR consensus binding sites of fabA or fabB, ii) integrating fabZ into fabI operon, and iii) enhancing the strength of fabI promoter. This approach led to dramatic increases in both proportion (48.3-83.0%) and titer (377.8 mg/L to 675.8 mg/L) of palmitic acid, mainly due to the decrease in UFA synthesis. Introducing a fatty acid ω-hydroxylase, CYP153A35, into the engineered strain resulted in a highly selective production of ω-HPA (83.5 mg/L) accounting for 87.5% of total ω-hydroxy fatty acids. Furthermore, strategies, such as i) enhancement in CYP153A35 activity, ii) expression of a fatty acid transporter, iii) supplementation of triton X-100, and iv) separation of the ω-HPA synthetic pathway into two strains for a co-culture system, were applied and resulted in 401.0 mg/L of ω-HPA production. For such selective productions of palmitic acid and ω-HPA, the rewiring of FadR regulation in E. coli is a promising strategy to develop an industrial process with economical downstream processing.

Production of pikromycin using branched chain amino acid catabolism in Streptomyces venezuelae ATCC 15439.

Branched chain amino acids (BCAA) are catabolized into various acyl-CoA compounds, which are key precursors used in polyketide productions. Because of that, BCAA catabolism needs fine tuning of flux balances for enhancing the production of polyketide antibiotics. To enhance BCAA catabolism for pikromycin production in Streptomyces venezuelae ATCC 15439, three key enzymes of BCAA catabolism, 3-ketoacyl acyl carrier protein synthase III, acyl-CoA dehydrogenase, and branched chain α-keto acid dehydrogenase (BCDH) were manipulated. BCDH overexpression in the wild type strain resulted in 1.3 fold increase in pikromycin production compared to that of WT, resulting in total 25 mg/L of pikromycin. To further increase pikromycin production, methylmalonyl-CoA mutase linked to succinyl-CoA production was overexpressed along with BCDH. Overexpression of the two enzymes resulted in the highest titer of total macrolide production of 43 mg/L, which was about 2.2 fold increase compared to that of the WT. However, it accumulated and produced dehydroxylated forms of pikromycin and methymycin, including their derivatives as well. It indicated that activities of pikC, P450 monooxygenase, newly became a bottleneck in pikromycin synthesis.

Impact of the Health Insurance Coverage Policy on Oral Anticoagulant Prescription among Patients with Atrial Fibrillation in Korea from 2014 to 2016.

BACKGROUND: To evaluate oral anticoagulant (OAC) utilization in patients with atrial fibrillation after the changes in the health insurance coverage policy in July 2015. METHODS: We used the Health Insurance Review and Assessment Service-National Patient Samples (HIRA-NPS) between 2014 and 2016. The HIRA-NPS, including approximately 1.4 million individuals, is a stratified random sample of 3% of the entire Korean population using 16 age groups and 2 sex groups. The HIRA-NPS comprises personal and medical information such as surgical or medical treatment provided, diagnoses, age, sex, region of medical institution, and clinician characteristics. The studied drugs included non-vitamin K antagonist OACs (NOACs) such as apixaban, dabigatran, edoxaban, and rivaroxaban, and were compared with warfarin. We analyzed drug utilization pattern under three aspects: person, time, and place. RESULTS: The number of patients with atrial fibrillation who were prescribed OACs was 3,114, 3,954, and 4,828; and the proportions of prescribed NOACs to total OACs were 5.1%, 36.2%, and 60.8% in 2014, 2015, and 2016, respectively. The growth rate of OACs prescription increased from 61.4 patients/quarter before June 2015 to 147.7 patients/quarter thereafter. These changes were predominantly in elderly individuals aged more than 70 years. The proportion of NOACs to OACs showed significant regional difference. CONCLUSION: The change of health insurance coverage policy substantially influenced OACs prescription pattern in whole Korean region. But the impact has been significantly different among regions and age groups, which provides the evidence for developing standard clinical practice guideline on OACs use.

Clinical implication of an impaired fasting glucose and prehypertension related to new onset atrial fibrillation in a healthy Asian population without underlying disease: a nationwide cohort study in Korea.

AIMS: For healthy populations without comorbidities, whether prehypertension and impaired fasting glucose (IFG) are associated with new onset atrial fibrillation (AF) is not well known. METHODS AND RESULTS: We included 366 507 subjects (age ≥20 years) not diagnosed with non-valvular AF from the Korean National Health Insurance Service-National Sample Cohort (NHIS-NSC) from 2003 to 2008. In total, 139 306 subjects diagnosed with AF-related comorbidities were excluded, and a 227 102 healthy population was followed up until 2013. The body mass index (BMI), blood pressure (BP), and fasting blood glucose (BG) level were acquired during National health check-ups. Subjects with IFG [hazard ratio (HR) 1.16, P = 0.017] had a higher AF risk and the diastolic BP (HR 1.11, P = 0.045) was a stronger indicator for an AF incidence than the systolic BP. After dividing the subjects into two mutually exclusive groups, AF incidence was increased dramatically by the combination effect of both prehypertension and an IFG in BMI <25 kg/m2 group, but, in BMI ≧25 kg/m2 group, did not show this tendency. An IFG related to AF risk was more prominent in the BMI <25 kg/m2 population (HR 1.18, P = 0.025) than those with a BMI ≥25 kg/m2, and subjects with both an IFG and prehypertension had a greater AF risk (HR 1.27, P = 0.016) than those without. CONCLUSION: Even in a healthy Asian populations without comorbidities, prehypertension and IFG were important risk factors of AF. Specifically, when prehypertension, including systolic and diastolic BPs, was finally combined with the IFG, the risk of new onset AF was increased especially in the BMI <25 kg/m2 group.

Metabolomic Profiling of Portal Blood and Bile Reveals Metabolic Signatures of Primary Sclerosing Cholangitis.

Primary sclerosing cholangitis (PSC) is a pathogenically complex, chronic, fibroinflammatory disorder of the bile ducts without known etiology or effective pharmacotherapy. Emerging in vitro and in vivo evidence support fundamental pathophysiologic mechanisms in PSC centered on enterohepatic circulation. To date, no studies have specifically interrogated the chemical footprint of enterohepatic circulation in PSC. Herein, we evaluated the metabolome and lipidome of portal venous blood and bile obtained at the time of liver transplantation in patients with PSC (n = 7) as compared to individuals with noncholestatic, end-stage liver disease (viral, metabolic, etc. (disease control, DC, n = 19)) and to nondisease controls (NC, living donors, n = 12). Global metabolomic and lipidomic profiling was performed on serum derived from portal venous blood (portal serum) and bile using ultraperformance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) and differential mobility spectroscopy-mass spectroscopy (DMS-MS; complex lipid platform). The Mann⁻Whitney U test was used to identify metabolites that significantly differed between groups. Principal-component analysis (PCA) showed significant separation of both PSC and DC from NC for both portal serum and bile. Metabolite set enrichment analysis of portal serum and bile demonstrated that the liver-disease cohorts (PSC and DC) exhibited similar enrichment in several metabolite categories compared to NC. Interestingly, the bile in PSC was uniquely enriched for dipeptide and polyamine metabolites. Finally, analysis of patient-matched portal serum and biliary metabolome revealed that these biological fluids were more homogeneous in PSC than in DC or NC, suggesting aberrant bile formation and enterohepatic circulation. In summary, PSC and DC patients exhibited alterations in several metabolites in portal serum and bile, while PSC patients exhibited a unique bile metabolome. These specific alterations in PSC are amenable to hypothesis testing and, potentially, therapeutic pharmacologic manipulation.

Steep switching characteristics of single-gated feedback field-effect transistors.

In this study, we propose newly designed feedback field-effect transistors that utilize the positive feedback of charge carriers in single-gated silicon channels to achieve steep switching behaviors. The band diagram, I-V characteristics, subthreshold swing, and on/off current ratio are analyzed using a commercial device simulator. Our proposed feedback field-effect transistors exhibit subthreshold swings of less than 0.1 mV dec-1, an on/off current ratio of approximately 1011, and an on-current of approximately 10-4 A at room temperature, demonstrating that the switching characteristics are superior to those of other silicon-based devices. In addition, the device parameters that affect the device performance, hysteresis characteristics, and temperature-dependent device characteristics are discussed in detail.

Constituents from Scutellaria barbata Inhibiting Nitric Oxide Production in LPS-Stimulated Microglial Cells.

The arial parts of Scutellaria barbata D. Don (Lamiaceae) efficiently inhibited NO production in BV2 microglial cells, and the active constituents were further isolated based on activity-guided isolation using silica-gel column chromatography, RP-C18 MPLC and prep-HPLC. As the results, 2 flavonoids including 6-methoxynaringenin (1) and 6-O-methylscutellarein (5), and 6 neo-clerodane diterpenes such as scutebarbatine W (2), scutebatas B (3), scutebarbatine B (4), scutebarbatine A (6), 6-O-nicotinolylscutebarbatine G (7), and scutebarbatine X (8) were isolated. The structures of these compounds were elucidated based on NMR and MS data, and the comparison of literature values. All the compounds except compound 7 inhibited NO production efficiently with IC50 values of lower than 50 µm. Particularly, compounds 1 and 8 were the most efficient with IC50 values of 25.8 and 27.4 µm, respectively. This is the first report suggesting the potential of S. barbata on the reduction of neuroinflammation.

Transcriptomics-based strain optimization tool for designing secondary metabolite overproducing strains of Streptomyces coelicolor.

In silico model-driven analysis using genome-scale model of metabolism (GEM) has been recognized as a promising method for microbial strain improvement. However, most of the current GEM-based strain design algorithms based on flux balance analysis (FBA) heavily rely on the steady-state and optimality assumptions without considering any regulatory information. Thus, their practical usage is quite limited, especially in its application to secondary metabolites overproduction. In this study, we developed a transcriptomics-based strain optimization tool (tSOT) in order to overcome such limitations by integrating transcriptomic data into GEM. Initially, we evaluated existing algorithms for integrating transcriptomic data into GEM using Streptomyces coelicolor dataset, and identified iMAT algorithm as the only and the best algorithm for characterizing the secondary metabolism of S. coelicolor. Subsequently, we developed tSOT platform where iMAT is adopted to predict the reaction states, and successfully demonstrated its applicability to secondary metabolites overproduction by designing actinorhodin (ACT), a polyketide antibiotic, overproducing strain of S. coelicolor. Mutants overexpressing tSOT targets such as ribulose 5-phosphate 3-epimerase and NADP-dependent malic enzyme showed 2 and 1.8-fold increase in ACT production, thereby validating the tSOT prediction. It is expected that tSOT can be used for solving other metabolic engineering problems which could not be addressed by current strain design algorithms, especially for the secondary metabolite overproductions.