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The eukaryotic RNA polymerase II (Pol II) multi-protein complex transcribes mRNA and coordinates several steps of co-transcriptional mRNA processing and chromatin modification. The largest Pol II subunit, Rpb1, has a C-terminal domain (CTD) comprising dozens of repeated heptad sequences (Tyr1-Ser2-Pro3-Thr4-Ser5-Pro6-Ser7), each containing five phospho-accepting amino acids. The CTD heptads are dynamically phosphorylated, creating specific patterns correlated with steps of transcription initiation, elongation, and termination. This CTD phosphorylation 'code' choreographs dynamic recruitment of important co-regulatory proteins during gene transcription. Genetic tools were used to engineer protease cleavage sites across the CTD (msCTD), creating tryptic peptides with unique sequences amenable to mass spectrometry analysis. However, phosphorylation isoforms within each msCTD sequence are difficult to resolve by standard reversed phase chromatography typically used for LC-MS/MS applications. Here, we use a panel of synthetic CTD phosphopeptides to explore the potential of hydrophilic interaction and electrostatic repulsion hydrophilic interaction (HILIC and ERLIC) chromatography as alternatives to reversed phase separation for CTD phosphopeptide analysis. Our results demonstrate that ERLIC provides improved performance for separation of singly- and doubly-phosphorylated CTD peptides for sequence analysis by LC-MS/MS. Analysis of native yeast msCTD confirms that phosphorylation on Ser5 and Ser2 represents the major endogenous phosphoisoforms. We expect this methodology will be especially useful in the investigation of pathways where multiple protein phosphorylation events converge in close proximity.

This study measured parameters automatically by marking the point for measuring each parameter on whole-spine radiographs. Between January 2020 and December 2021, 1017 sequential lateral whole-spine radiographs were retrospectively obtained. Of these, 819 and 198 were used for training and testing the performance of the landmark detection model, respectively. To objectively evaluate the program's performance, 690 whole-spine radiographs from four other institutions were used for external validation. The combined dataset comprised radiographs from 857 female and 850 male patients (average age 42.2 ± 27.3 years; range 20-85 years). The landmark localizer showed the highest accuracy in identifying cervical landmarks (median error 1.5-2.4 mm), followed by lumbosacral landmarks (median error 2.1-3.0 mm). However, thoracic landmarks displayed larger localization errors (median 2.4-4.3 mm), indicating slightly reduced precision compared with the cervical and lumbosacral regions. The agreement between the deep learning model and two experts was good to excellent, with intraclass correlation coefficient values >0.88. The deep learning model also performed well on the external validation set. There were no statistical differences between datasets in all parameters, suggesting that the performance of the artificial intelligence model created was excellent. The proposed automatic alignment analysis system identified anatomical landmarks and positions of the spine with high precision and generated various radiograph imaging parameters that had a good correlation with manual measurements.

This study aimed to evaluate the cholesterol-lowering and antioxidant activities of soymilk fermented with probiotic Lactobacillaceae strains and to investigate the production of related bioactive compounds. Lactiplantibacillus plantarum KML06 (KML06) was selected for the fermentation of soymilk because it has the highest antioxidant, cholesterol-lowering, and β-glucosidase activities among the 10 Lactobacillaceae strains isolated from kimchi. The genomic information of strain KML06 was analyzed. Moreover, soymilk fermented with KML06 was evaluated for growth kinetics, metabolism, and functional characteristics during the fermentation period. The number of viable cells, which was similar to the results of radical scavenging activities and cholesterol assimilation, as well as the amount of soy isoflavone aglycones, daidzein, and genistein, was the highest at 12 h of fermentation. These results indicate that soymilk fermented with KML06 can prevent oxidative stress and cholesterol-related problems through the production of soy isoflavone aglycones.

The generative adversarial network (GAN) is a promising deep learning method for generating images. We evaluated the generation of highly realistic and high-resolution chest radiographs (CXRs) using progressive growing GAN (PGGAN). We trained two PGGAN models using normal and abnormal CXRs, solely relying on normal CXRs to demonstrate the quality of synthetic CXRs that were 1000 × 1000 pixels in size. Image Turing tests were evaluated by six radiologists in a binary fashion using two independent validation sets to judge the authenticity of each CXR, with a mean accuracy of 67.42% and 69.92% for the first and second trials, respectively. Inter-reader agreements were poor for the first (κ = 0.10) and second (κ = 0.14) Turing tests. Additionally, a convolutional neural network (CNN) was used to classify normal or abnormal CXR using only real images and/or synthetic images mixed datasets. The accuracy of the CNN model trained using a mixed dataset of synthetic and real data was 93.3%, compared to 91.0% for the model built using only the real data. PGGAN was able to generate CXRs that were identical to real CXRs, and this showed promise to overcome imbalances between classes in CNN training., (© 2023. The Author(s).)

Background: The long-term outcomes of patients with T1 colorectal cancer (CRC) who undergo endoscopic and/or surgical treatment are not well understood. Invasive CRC confined to the colonic submucosa (T1 CRC) is challenging in terms of clinical decision-making. We compared the long-term outcomes of T1 CRC by treatment method., Methods: We examined 370 patients with pathological T1 CRC treated between 2000 and 2015 at Seoul St. Mary's Hospital. In total, 93 patients underwent endoscopic resection (ER) only, 82 underwent additional surgery after ER, and 175 underwent surgical resection only. Patients who did not meet the curative criteria were defined as "high-risk." High-risk patients were classified into three groups according to the treatment modalities: ER only (Group A: 35 patients), additional surgery after ER (Group B: 72 patients), and surgical resection only (Group C: 133 patients). The recurrence-free and overall survival (OS) rates, and factors associated with recurrence and mortality, were analyzed. Factors associated with lymph node metastasis (LNM) were subjected to multivariate analysis., Results: Of the 370 patients, 7 experienced recurrence and 7 died. All recurrences occurred in the high-risk group and two deaths were in the low-risk group. In high-risk groups, there was no significant group difference in recurrence-free survival (P = 0.511) or OS (P =0.657). Poor histology (P =0.042) was associated with recurrence, and vascular invasion (P =0.044) with mortality. LNMs were observed in 30 of 277 patients who underwent surgery either initially or secondarily. Lymphatic invasion was significantly associated with the incidence of LNM (P < 0.001)., Conclusions: ER prior to surgery did not affect the prognosis of high-risk T1 CRC patients, and did not worsen the clinical outcomes of patients who required additional surgery. Lymphatic invasion was the most important predictor of LNM., (© 2022. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Realistic image generation is valuable in dental medicine, but still challenging for generative adversarial networks (GANs), which require large amounts of data to overcome the training instability. Thus, we generated lateral cephalogram X-ray images using a deep-learning-based progressive growing GAN (PGGAN). The quality of generated images was evaluated by three methods. First, signal-to-noise ratios of real/synthesized images, evaluated at the posterior arch region of the first cervical vertebra, showed no statistically significant difference (t-test, p = 0.211). Second, the results of an image Turing test, conducted by non-orthodontists and orthodontists for 100 randomly chosen images, indicated that they had difficulty in distinguishing whether the image was real or synthesized. Third, cephalometric tracing with 42 landmark points detection, performed on real and synthesized images by two expert orthodontists, showed consistency with mean difference of 2.08 ± 1.02 mm. Furthermore, convolutional neural network-based classification tasks were used to classify skeletal patterns using a real dataset with class imbalance and a dataset balanced with synthesized images. The classification accuracy for the latter case was increased by 1.5%/3.3% at internal/external test sets, respectively. Thus, the cephalometric images generated by PGGAN are sufficiently realistic and have potential to application in various fields of dental medicine.

Background: Generative adversarial network (GAN)-based synthetic images can be viable solutions to current supervised deep learning challenges. However, generating highly realistic images is a prerequisite for these approaches., Objective: The aim of this study was to investigate and validate the unsupervised synthesis of highly realistic body computed tomography (CT) images by using a progressive growing GAN (PGGAN) trained to learn the probability distribution of normal data., Methods: We trained the PGGAN by using 11,755 body CT scans. Ten radiologists (4 radiologists with <5 years of experience [Group I], 4 radiologists with 5-10 years of experience [Group II], and 2 radiologists with >10 years of experience [Group III]) evaluated the results in a binary approach by using an independent validation set of 300 images (150 real and 150 synthetic) to judge the authenticity of each image., Results: The mean accuracy of the 10 readers in the entire image set was higher than random guessing (1781/3000, 59.4% vs 1500/3000, 50.0%, respectively; P<.001). However, in terms of identifying synthetic images as fake, there was no significant difference in the specificity between the visual Turing test and random guessing (779/1500, 51.9% vs 750/1500, 50.0%, respectively; P=.29). The accuracy between the 3 reader groups with different experience levels was not significantly different (Group I, 696/1200, 58.0%; Group II, 726/1200, 60.5%; and Group III, 359/600, 59.8%; P=.36). Interreader agreements were poor (κ=0.11) for the entire image set. In subgroup analysis, the discrepancies between real and synthetic CT images occurred mainly in the thoracoabdominal junction and in the anatomical details., Conclusions: The GAN can synthesize highly realistic high-resolution body CT images that are indistinguishable from real images; however, it has limitations in generating body images of the thoracoabdominal junction and lacks accuracy in the anatomical details., (©Ho Young Park, Hyun-Jin Bae, Gil-Sun Hong, Minjee Kim, JiHye Yun, Sungwon Park, Won Jung Chung, NamKug Kim. Originally published in JMIR Medical Informatics (http://medinform.jmir.org), 17.03.2021.)

Current multimodal approaches for the prognostication of out-of-hospital cardiac arrest (OHCA) are based mainly on the prediction of poor neurological outcomes; however, it is challenging to identify patients expected to have a favorable outcome, especially before the return of spontaneous circulation (ROSC). We developed and validated a machine learning-based system to predict good outcome in OHCA patients before ROSC. This prospective, multicenter, registry-based study analyzed non-traumatic OHCA data collected between October 2015 and June 2017. We used information available before ROSC as predictor variables, and the primary outcome was neurologically intact survival at discharge, defined as cerebral performance category 1 or 2. The developed models' robustness were evaluated and compared with various score metrics to confirm their performance. The model using a voting classifier had the best performance in predicting good neurological outcome (area under the curve = 0.926). We confirmed that the six top-weighted variables predicting neurological outcomes, such as several duration variables after the instant of OHCA and several electrocardiogram variables in the voting classifier model, showed significant differences between the two neurological outcome groups. These findings demonstrate the potential utility of a machine learning model to predict good neurological outcome of OHCA patients before ROSC.

Objective: To assess the performance of content-based image retrieval (CBIR) of chest CT for diffuse interstitial lung disease (DILD)., Materials and Methods: The database was comprised by 246 pairs of chest CTs (initial and follow-up CTs within two years) from 246 patients with usual interstitial pneumonia (UIP, n = 100), nonspecific interstitial pneumonia (NSIP, n = 101), and cryptogenic organic pneumonia (COP, n = 45). Sixty cases (30-UIP, 20-NSIP, and 10-COP) were selected as the queries. The CBIR retrieved five similar CTs as a query from the database by comparing six image patterns (honeycombing, reticular opacity, emphysema, ground-glass opacity, consolidation and normal lung) of DILD, which were automatically quantified and classified by a convolutional neural network. We assessed the rates of retrieving the same pairs of query CTs, and the number of CTs with the same disease class as query CTs in top 1-5 retrievals. Chest radiologists evaluated the similarity between retrieved CTs and queries using a 5-scale grading system (5-almost identical; 4-same disease; 3-likelihood of same disease is half; 2-likely different; and 1-different disease)., Results: The rate of retrieving the same pairs of query CTs in top 1 retrieval was 61.7% (37/60) and in top 1-5 retrievals was 81.7% (49/60). The CBIR retrieved the same pairs of query CTs more in UIP compared to NSIP and COP ( p = 0.008 and 0.002). On average, it retrieved 4.17 of five similar CTs from the same disease class. Radiologists rated 71.3% to 73.0% of the retrieved CTs with a similarity score of 4 or 5., Conclusion: The proposed CBIR system showed good performance for retrieving chest CTs showing similar patterns for DILD., Competing Interests: The authors have no potential conflicts of interest to disclose., (Copyright © 2021 The Korean Society of Radiology.)

Medical image analyses have been widely used to differentiate normal and abnormal cases, detect lesions, segment organs, etc. Recently, owing to many breakthroughs in artificial intelligence techniques, medical image analyses based on deep learning have been actively studied. However, sufficient medical data are difficult to obtain, and data imbalance between classes hinder the improvement of deep learning performance. To resolve these issues, various studies have been performed, and data augmentation has been found to be a solution. In this review, we introduce data augmentation techniques, including image processing, such as rotation, shift, and intensity variation methods, generative adversarial network-based method, and image property mixing methods. Subsequently, we examine various deep learning studies based on data augmentation techniques. Finally, we discuss the necessity and future directions of data augmentation., Competing Interests: Conflicts of Interest: The authors have no potential conflicts of interest to disclose., (Copyrights © 2020 The Korean Society of Radiology.)

Background: The association between long-term exposure to air pollutants, including nitrogen dioxide (NO 2 ), carbon monoxide (CO), sulfur dioxide (SO 2 ), ozone (O 3 ), and particulate matter 10 μm or less in diameter (PM 10 ), and mortality by ischemic heart disease (IHD), cerebrovascular disease (CVD), pneumonia (PN), and chronic lower respiratory disease (CLRD) is unclear. We investigated whether living in an administrative district with heavy air pollution is associated with an increased risk of mortality by the diseases through an ecological study using South Korean administrative data over 19 years., Methods: A total of 249 Si-Gun-Gus, unit of administrative districts in South Korea were studied. In each district, the daily concentrations of CO, SO 2 , NO 2 , O 3 , and PM 10 were averaged over 19 years (2001-2018). Age-adjusted mortality rates by IHD, CVD, PN and CLRD for each district were averaged for the same study period. Multivariate beta-regression analysis was performed to estimate the associations between air pollutant concentrations and mortality rates, after adjusting for confounding factors including altitude, population density, higher education rate, smoking rate, obesity rate, and gross regional domestic product per capita. Associations were also estimated for two subgrouping schema: Capital and non-Capital areas (77:172 districts) and urban and rural areas (168:81 districts)., Results: For IHD, higher SO 2 concentrations were significantly associated with a higher mortality rate, whereas other air pollutants had null associations. For CVD, SO 2 and PM 10 concentrations were significantly associated with a higher mortality rate. For PN, O 3 concentrations had significant positive associations with a higher mortality rate, while SO 2 , NO 2 , and PM 10 concentrations had significant negative associations. For CLRD, O 3 concentrations were associated with an increased mortality rate, while CO, NO 2 , and PM 10 concentrations had negative associations. In the subgroup analysis, positive associations between SO 2 concentrations and IHD mortality were consistently observed in all subgroups, while other pollutant-disease pairs showed null, or mixed associations., Conclusion: Long-term exposure to high SO 2 concentration was significantly and consistently associated with a high mortality rate nationwide and in Capital and non-Capital areas, and in urban and rural areas. Associations between other air pollutants and disease-related mortalities need to be investigated in further studies.

An amendment to this paper has been published and can be accessed via the original article.

Background: Emergency department overcrowding negatively impacts critically ill patients and could lead to the occurrence of cardiac arrest. However, the association between emergency department crowding and the occurrence of in-hospital cardiac arrest has not been thoroughly investigated. This study aimed to evaluate the correlation between emergency department occupancy rates and the incidence of in-hospital cardiac arrest., Methods: A single-center, observational, registry-based cohort study was performed including all consecutive adult, non-traumatic in-hospital cardiac arrest patients between January 2014 and June 2017. We used emergency department occupancy rates as a crowding index at the time of presentation of cardiac arrest and at the time of maximum crowding, and the average crowding rate for the duration of emergency department stay for each patient. To calculate incidence rate, we divided the number of arrest cases for each emergency department occupancy period by accumulated time. The primary outcome is the association between the incidence of in-hospital cardiac arrest and emergency department occupancy rates., Results: During the study period, 629 adult, non-traumatic cardiac arrest patients were enrolled in our registry. Among these, 187 patients experienced in-hospital cardiac arrest. Overall survival discharge rate was 24.6%, and 20.3% of patients showed favorable neurologic outcomes at discharge. Emergency department occupancy rates were positively correlated with in-hospital cardiac arrest occurrence. Moreover, maximum emergency department occupancy in the critical zone had the strongest positive correlation with in-hospital cardiac arrest occurrence (Spearman rank correlation ρ = 1.0, P < .01). Meanwhile, occupancy rates were not associated with the ED mortality., Conclusion: Maximum emergency department occupancy was strongly associated with in-hospital cardiac arrest occurrence. Adequate monitoring and managing the maximum occupancy rate would be important to reduce unexpected cardiac arrest.

Methylation of histone H3 lysine 4 (H3K4) by Set1/COMPASS occurs co-transcriptionally, and is important for gene regulation. Set1/COMPASS associates with the RNA polymerase II C-terminal domain (CTD) to establish proper levels and distribution of H3K4 methylations. However, details of CTD association remain unclear. Here we report that the Set1 N-terminal region and the COMPASS subunit Swd2, which interact with each other, are both needed for efficient CTD binding in Saccharomyces cerevisiae. Moreover, a single point mutation in Swd2 that affects its interaction with Set1 also impairs COMPASS recruitment to chromatin and H3K4 methylation. A CTD interaction domain (CID) from the protein Nrd1 can partially substitute for the Set1 N-terminal region to restore CTD interactions and histone methylation. However, even when Set1/COMPASS is recruited via the Nrd1 CID, histone H2B ubiquitylation is still required for efficient H3K4 methylation, indicating that H2Bub acts after the initial recruitment of COMPASS to chromatin.

Recently, significant improvements have been made in artificial intelligence. The artificial neural network was introduced in the 1950s. However, because of the low computing power and insufficient datasets available at that time, artificial neural networks suffered from overfitting and vanishing gradient problems for training deep networks. This concept has become more promising owing to the enhanced big data processing capability, improvement in computing power with parallel processing units, and new algorithms for deep neural networks, which are becoming increasingly successful and attracting interest in many domains, including computer vision, speech recognition, and natural language processing. Recent studies in this technology augur well for medical and healthcare applications, especially in endoscopic imaging. This paper provides perspectives on the history, development, applications, and challenges of deep-learning technology.

Background and Objective: We investigated a novel method using a 2D convolutional neural network (CNN) to identify superior and inferior vertebrae in a single slice of CT images, and a post-processing for 3D segmentation and separation of cervical vertebrae., Methods: The cervical spines of patients (N == 17, 1684 slices) from Severance and Gangnam Severance Hospitals (S/GSH) and healthy controls (N == 24, 3490 slices) from Seoul National University Bundang Hospital (SNUBH) were scanned by using various volumetric CT protocols. To prepare gold standard masks of cervical spine in CT images, each spine was segmented by using conventional image-processing methods and manually corrected by an expert. The gold standard masks were preprocessed and labeled into superior and inferior cervical vertebrae separately in the axial slices. The 2D U-Net model was trained by using the disease dataset (S/GSH) and additional validation was performed by using the healthy control dataset (SNUBH), and then the training and validation were repeated by switching the two datasets., Results: In case of the model was trained with the disease dataset (S/GSH) and validated with the healthy control (SNUBH), the mean and standard deviation (SD) of the Dice similarity coefficient (DSC), Jaccard similarity coefficient (JSC), mean surface distance (MSD), and Hausdorff surface distance (HSD) were 94.37%% ± 1.45%, 89.47%% ± 2.55%, 0.33 ± 0.12 mm and 20.89 ± 3.98 mm, and 88.67%% ± 5.82%, 80.83%% ± 8.09%, 1.05 ± 0.63 mm and 29.17 ± 19.74 mm, respectively. In case of the model was trained with the healthy control (SNUBH) and validated with the disease dataset (S/GSH), the mean and SD of DSC, JSC, MSD, and HSD were 96.23%% ± 1.55%, 92.95%% ± 2.58%, 0.39 ± 0.20 mm and 16.23 ± 6.72 mm, and 93.15%% ± 3.09%, 87.54%% ± 5.11%, 0.38 ± 0.17 mm and 20.85 ± 7.11 mm, respectively., Conclusions: The results demonstrated that our fully automated method achieved comparable accuracies with inter- and intra-observer variabilities of manual segmentation by human experts, which is time consuming., Competing Interests: Declaration of Competing Interest The authors have no relevant conflicts of interest to disclose., (Copyright © 2019. Published by Elsevier B.V.)

The artificial neural network (ANN), one of the machine learning (ML) algorithms, inspired by the human brain system, was developed by connecting layers with artificial neurons. However, due to the low computing power and insufficient learnable data, ANN has suffered from overfitting and vanishing gradient problems for training deep networks. The advancement of computing power with graphics processing units and the availability of large data acquisition, deep neural network outperforms human or other ML capabilities in computer vision and speech recognition tasks. These potentials are recently applied to healthcare problems, including computer-aided detection/diagnosis, disease prediction, image segmentation, image generation, etc. In this review article, we will explain the history, development, and applications in medical imaging.

Media reports of a celebrity's suicide may be followed by copycat suicides, and the impact may vary in different age and sex subgroups. We proposed a quantitative framework to assess the vulnerability of age and sex subgroups to copycat suicide and used this method to investigate copycat suicides in relation to the suicides of 10 celebrities in South Korea from 1993 to 2013. By applying a detrending model to control for annual and seasonal fluctuations, we estimated the expected number of suicides within a copycat suicide period. The copycat effect was assessed in two ways: the magnitude of copycat suicide by dividing the observed by the expected number of suicides, and the mortality rate by subtracting the expected from the observed number of suicides. Females aged 20-29 years were the most vulnerable subgroup according to both the magnitude of the copycat effect (2.31-fold increase over baseline) and the mortality rate from copycat suicide (22.7-increase). Males aged 50-59 years were the second most vulnerable subgroup according to the copycat suicide mortality rate (20.5- increase). We hope that the proposed quantitative framework will be used to identify vulnerable subgroups to copycat effect, thereby helping devise strategies for prevention.

Backgrounds/aims: The etiology of colon diverticulosis is related to a range of genetic, biological, and environmental factors, but the risk factors for asymptomatic diverticulosis of the colon are unclear. This study examined the risk factors for asymptomatic colon diverticulosis., Methods: This retrospective study included examinees who underwent a colonoscopy for screening at the health check-up center of SAM Hospital between January 2016 and December 2016. The examinees with colon diverticulosis found by colonoscopy were compared with those without diverticulosis. The comparison factors were age, gender, alcohol consumption, smoking status, medical history, lipid profile, body mass index, visceral fat area, waist-hip ratio, and severity of a fatty liver., Results: This study included 937 examinees and the overall prevalence of diverticulosis was 8.1% (76/937). Fatty liver was found in 69.7% (53/76) in cases of colon diverticulosis and 50.3% (433/861) in the control group (p=0.001). The average waist-hip ratio was 0.92±0.051 in colon diverticulosis and 0.90±0.052 in the control group (p=0.052). Multivariate analysis revealed the waist-hip ratio (OR=1.035, 95% CI 1.000-1.070, p=0.043), moderate fatty liver (OR=2.238, 95% CI 1.026-4.882, p=0.043), and severe fatty liver (OR=5.519, 95% CI 1.236-21.803, p=0.025) to be associated with an increased risk of asymptomatic colon diverticulosis., Conclusions: The waist-hip ratio, moderate fatty liver, and severe fatty liver are risk factors for asymptomatic colon diverticulosis. Central obesity, which can be estimated by the waist-hip ratio, and fatty liver might affect the pathogenesis of asymptomatic colon diverticulosis.

Deep learning is now widely used as an efficient tool for medical image classification and segmentation. However, conventional machine learning techniques are still more accurate than deep learning when only a small dataset is available. In this study, we present a general data augmentation strategy using Perlin noise, applying it to pixel-by-pixel image classification and quantification of various kinds of image patterns of diffuse interstitial lung disease (DILD). Using retrospectively obtained high-resolution computed tomography (HRCT) images from 106 patients, 100 regions-of-interest (ROIs) for each of six classes of image patterns (normal, ground-glass opacity, reticular opacity, honeycombing, emphysema, and consolidation) were selected for deep learning classification by experienced thoracic radiologists. For extra-validation, the deep learning quantification of the six classification patterns was evaluated for 92 HRCT whole lung images for which hand-labeled segmentation masks created by two experienced radiologists were available. FusionNet, a convolutional neural network (CNN), was used for training, test, and extra-validation on classifications of DILD image patterns. The accuracy of FusionNet with data augmentation using Perlin noise (89.5%, 49.8%, and 55.0% for ROI-based classification and whole lung quantifications by two radiologists, respectively) was significantly higher than that with conventional data augmentation (82.1%, 45.7%, and 49.9%, respectively). This data augmentation strategy using Perlin noise could be widely applied to deep learning studies for image classification and segmentation, especially in cases with relatively small datasets.

Background: Accurate, rapid, and cost-effective screening tests for hepatitis B virus (HBV) and hepatitis C virus (HCV) infection may be useful in laboratories that cannot afford automated chemiluminescent immunoassays (CLIAs). We evaluated the diagnostic performance of a novel rapid automated fluorescent lateral flow immunoassay (LFIA)., Methods: A fluorescent LFIA using a small bench-top fluorescence reader, Automated Fluorescent Immunoassay System (AFIAS; Boditech Med Inc., Chuncheon, Korea), was developed for qualitative detection of hepatitis B surface antigen (HBsAg), antibody to HBsAg (anti-HBs), and antibody to HCV (anti-HCV) within 20 minutes. We compared the diagnostic performance of AFIAS with that of automated CLIAs-Elecsys (Roche Diagnostics GmbH, Penzberg, Germany) and ARCHITECT (Abbott Laboratories, Abbott Park, IL, USA)-using 20 seroconversion panels and 3,500 clinical serum samples., Results: Evaluation with the seroconversion panels demonstrated that AFIAS had adequate sensitivity for HBsAg and anti-HCV detection. From the clinical samples, AFIAS sensitivity and specificity were 99.8% and 99.3% for the HBsAg test, 100.0% and 100.0% for the anti-HBs test, and 98.8% and 99.1% for the anti-HCV test, respectively. Its agreement rates with the Elecsys HBsAg, anti-HBs, and anti-HCV detection assays were 99.4%, 100.0%, and 99.0%, respectively. AFIAS detected all samples with HBsAg genotypes A-F and H and anti-HCV genotypes 1, 1a, 1b, 2a, 2b, 4, and 6. Cross-reactivity with other infections was not observed., Conclusions: The AFIAS HBsAg, anti-HBs, and anti-HCV tests demonstrated diagnostic performance equivalent to current automated CLIAs. AFIAS could be used for a large-scale HBV or HCV screening in low-resource laboratories or low-to middle-income areas., Competing Interests: No potential conflicts of interest relevant to this article were reported., (© The Korean Society for Laboratory Medicine.)

Background/aims: In Korea, increasing clarithromycin resistance has led to the need for an alternative first-line therapy for the eradication of Helicobacter pylori ( H. pylori ) infection. Concomitant therapy (CT) and sequential therapy (ST) have been proposed as alternative regimens. The aim of this study was to compare the eradication rate from using CT and ST in Korea., Methods: A literature review was performed on studies comparing the efficacy of CT and ST in Korea. Data were pooled to obtain the odds ratio (OR) of the eradication rate with 95% confidence intervals (CIs). The eradication rates were considered both on an intention-to-treat (ITT) and a per-protocol (PP) bases., Results: Six studies provided data on 1,897 Korean adult patients. The pooled OR was 1.382 (95% CI: 1.031-1.853, p=0.031) for ITT analysis and 2.114 (95% CI: 1.502-2.974, p<0.001) for PP analysis. There was no difference in the rate of adverse events and compliances between the two regimens., Conclusions: The efficacy of CT was superior to ST in both ITT and PP analyses. Therefore, CT could be an excellent alternative regimen for the eradication of H. pylori as a first-line therapy in Korea.

Background/aim: Decreased Natural killer cell activity (NKA) for interferon-gamma production (NKA-IFNγ) has been reported in cancer patients. The aim of this study was to determine the diagnostic performance of NKA-IFNγ for gastric cancer (GC)., Results: NKA-IFNγ levels were decreased in 261 GC patients with all stages of tumor compared to those in 48 healthy donors ( P < 0.001), and lower levels of NKA-IFNγ were associated with higher GC stages. NKA-IFNγ levels were also associated with clinicopathological parameters including tumor size, depth of invasion, and lymph node metastasis. NKA-INFγ assay had better diagnostic value (AUC = 0.822) compared to serum CEA (0.624) or CA19-9 assay (0.566) ( P < 0.001). Using different cut-off levels, serum CEA and CA19-9 showed sensitivities of 6.1-14.2% and 4.2-28.0%, respectively, which were much lower than that of NKA-IFNγ (55.6-66.7%)., Methods: This study included 261 patients with newly diagnosed GC and 48 healthy donors. NKA for IFNγ was determined by enzyme immunoassay after incubation of whole blood, and diagnostic performance was evaluated., Conclusions: NK cell activities for IFNγ production could be used as a supportive non-invasive tumor marker for GC diagnosis., Competing Interests: CONFLICTS OF INTEREST The authors have no conflicts of interest to declare.

Background & Aims: Most common reason behind changes in histone deacetylase (HDAC) function is its overexpression in cancer. However, among HDACs in liver cancer, HDAC6 is uniquely endowed with a tumor suppressor, but the mechanism underlying HDAC6 inactivation has yet to be uncovered., Methods: Microarray profiling and target prediction programs were used to identify miRNAs targeting HDAC6. A series of inhibitors, activators and siRNAs was introduced to validate regulatory mechanisms for microRNA-221-3p (miR-221) governing HDAC6 in hepatocarcinogenesis., Results: Comprehensive miRNA profiling analysis identified seven putative endogenous miRNAs that are significantly upregulated in hepatocellular carcinoma (HCC). While miR-221 was identified as a suppressor of HDAC6 by ectopic expression of miRNA mimics in Dicer knockdown cells, targeted-disruption of miR-221 repressed cancer cell growth through derepressing HDAC6 expression. Suppression of HDAC6 via miR-221 was induced by JNK/c-Jun signaling in liver cancer cells but not in normal hepatic cells. Additionally, cytokine-induced NF-κBp65 independently regulated miR-221, thereby suppressing HDAC6 expression in HCC cells. HCC tissues derived from chemical-induced rat and H-ras12V transgenic mice liver cancer models validated that JNK/c-Jun activation and NF-κBp65 nuclear translocation are essential for the transcription of miR-221 leading to repression of HDAC6 in HCC., Conclusions: Our findings suggest that the functional loss or suppression of the tumor suppressor HDAC6 is caused by induction of miR-221 through coordinated JNK/c-Jun- and NF-κB-signaling pathways during liver tumorigenesis, providing a novel target for the molecular treatment of liver malignancies., (Copyright © 2015 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.)

MicroRNA-31 (miR-31) is among the most frequently altered microRNAs in human cancers and altered expression of miR-31 has been detected in a large variety of tumor types, but the functional role of miR-31 still hold both tumor suppressive and oncogenic roles in different tumor types. MiR-31 expression was down-regulated in a large cohort of hepatocellular carcinoma (HCC) patients, and low expression of miR-31 was significantly associated with poor prognosis of HCC patients. Ectopic expression of miR-31 mimics suppressed HCC cell growth by transcriptional deregulation of cell cycle proteins. Additional study evidenced miR-31 directly to suppress HDAC2 and CDK2 expression by inhibiting mRNA translation in HCC cells. We also found that ectopic expression of miR-31 mimics reduced metastatic potential of HCC cells by selectively regulating epithelial-mesenchymal transition (EMT) regulatory proteins such as N-cadherin, E-cadherin, vimentin and fibronectin. HCC tissues derived from chemical-induced rat liver cancer models validated that miR-31 expression is significantly down-regulated, and that those cell cycle- and EMT-regulatory proteins are deregulated in rat liver cancer. Overall, we suggest that miR-31 functions as a tumor suppressor by selectively regulating cell cycle and EMT regulatory proteins in human hepatocarcinogenesis providing a novel target for the molecular treatment of liver malignancies.

Drug-induced liver injury (DILI) is a major safety concern during drug development and remains one of the main reasons for withdrawal of drugs from the market. Although it is crucial to develop methods that will detect potential hepatotoxicity of drug candidates as early and as quickly as possible, there is still a lack of sensitive and specific biomarkers for DILI that consequently leads to a scarcity of reliable hepatotoxic data. Hence, in this study, we assessed characteristic molecular signatures in rat liver treated with drugs (pyrazinamide, ranitidine, enalapril, carbamazepine and chlorpromazine) that are known to cause DILI in humans. Unsupervised hierarchical clustering analysis of transcriptome changes induced by DILI-causing drugs resulted in three different subclusters on dendrogram, i.e., hepatocellular, cholestatic and mixed type of DILI at early time points (2 days), and multiclassification analysis suggested 31 genes as discernible markers for each DILI pattern. Further analysis for characteristic molecular signature of each DILI pattern provided a molecular basis for different modes of DILI action. A proteomics study of the same rat livers was used to confirm the results, and the two sets of data showed 60 matching classifiers. In conclusion, the data of different DILI-causing drug treatments from genomic analysis in a rat model suggest that DILI-specific molecular signatures can discriminate different patterns of DILI at an early exposure time point, and that they provide useful information for mechanistic studies that may lead to a better understanding of the molecular basis of DILI., (Copyright © 2014 John Wiley & Sons, Ltd.)

The aberrant regulation of histone deacetylase 6 (HDAC6) contributes to malignant progression in various types of cancer, but the mechanism underlying gastric carcinogenesis remains unknown. Aberrant HDAC6 overexpression was observed in a subset of human gastric cancer cells. HDAC6 knockdown caused the significant inhibition of gastric cancer cell growth without affecting the transition of cell cycles or the processing of cell death. We demonstrate that an increase in epidermal growth factor receptor (EGFR) signaling through decreased EGFR degradation was mediated by HDAC6 in gastric carcinogenesis. These results establish a molecular mechanism responsible for oncogenic HDAC6, explaining how EGFR signaling induced by the growth factor is sustained during the malignant progression of gastric cancer., (Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.)

Nemo-like kinase (NLK), an evolutionarily conserved MAP kinase-related kinase, has been reported to be involved in the development of hepatocellular carcinoma (HCC), but the underlying mechanisms leading to oncogenic NLK are poorly understood. A comprehensive microRNA (miRNA) profiling analysis on human HCC tissues identified four downregulated miRNAs that may target NLK. Ectopic expression of miRNA mimics suggested that miR-101 could suppress NLK in HCC cells. Notably, ectopic miR-101 expression repressed cancer cell growth and proliferation and imitated NLK knockdown effect on HCC cells. In conclusion, we suggest that miR-101 functions as a tumor suppressor by regulating abnormal NLK activity in liver., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Aberrant regulation of histone deacetylase 2 (HDAC2) contributes to malignant progression in various cancers, but the underlying mechanism leading to the activation of oncogenic HDAC2 remains unknown. In this study, we show that HDAC2 expression is upregulated in a large cohort of patients with human hepatocellular carcinoma, and that high expression of HDAC2 was significantly associated with poor prognosis of patients with hepatocellular carcinoma. We found that mTORC1/NF-κBp50 signaling is necessary for the growth factor-induced HDAC2 and is sustained in hepatocellular carcinoma, but not in normal hepatic cells. Growth factor-induced mTORC1 activates the nuclear translocation of NF-κBp50, where it binds to the intragenic sequences of the HDAC2 gene and promotes its transcription. Hepatocellular carcinoma tissues derived from chemical-induced mouse and rat liver cancer models validated that mTORC1 activation and NF-κBp50 nuclear translocation are essential for the transcriptional activation of oncogenic HDAC2 in hepatocellular carcinoma. In addition, we demonstrate that HDAC2 is required to maintain mTORC1 activity by stabilizing the mTOR/RAPTOR complex. Elevated expression of HDAC2 triggers a positive feedback loop that activates AKT phosphorylation via the transcriptional modulation of phosphoinositide signaling molecules. Bioinformatics analysis of HDAC2 signature and immunoblot analysis of mesenchymal genes also evidenced that HDAC2 plays a role in the malignant behavior of tumor cells by Snail induction and simultaneously E-cadherin suppression in hepatocellular carcinoma cells. These findings establish a molecular mechanism responsible for the activation of oncogenic HDAC2, which explains how growth factor-induced HDAC2 maintains mitogenic signaling and function during hepatocellular malignant progression and provide a novel strategy for therapeutic intervention in liver cancer. Cancer Res; 74(6); 1728-38. ©2014 AACR.

Objective: Investigation on whether the characteristic molecular signatures can discriminate individual volatile organic compounds (VOCs) and provide predictive markers for the detection of VOC exposure., Methods: Transcriptomic analysis of liver tissues was performed 48 h after the single oral administration of three VOCs doses at LD25 or LD5 values, to Sprague-Dawley., Results: Combination analysis of different multi-classifications suggested that 145 genes predicted VOC exposure. Additionally, Gene Set Enrichment Analysis of genes deregulated by VOCs revealed that T cell prolymphatic leukemia signaling was inactivated in all VOCs., Conclusions: These molecular markers could be widely implemented to assess and predict environmental exposure to VOCs.

Aberrant regulation of histone deacetylase 2 (HDAC2) plays a pivotal role in the development of hepatocellular carcinoma (HCC), but, the underlying mechanism leading to HDAC2 overexpression is not well understood. We performed microRNA (miRNA) profiling analysis in a subset of HCCs, and identified four down-regulated miRNAs that may target HDAC2 in HCC. Ectopic expression of miRNA mimics evidenced that miR-145 suppresses HDAC2 expression in HCC cells. This treatment repressed cancer cell growth and recapitulated HDAC2 knockdown effects on HCC cells. In conclusion, we suggest that loss or suppression of miR-145 may cause aberrant overexpression of HDAC2 and promote HCC tumorigenesis., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Unlabelled: Sirtuins are nicotinamide adenine dinucleotide oxidized form (NAD(+) )-dependent deacetylases and function in cellular metabolism, stress resistance, and aging. For sirtuin7 (SIRT7), a role in ribosomal gene transcription is proposed, but its function in cancer has been unclear. In this study we show that SIRT7 expression was up-regulated in a large cohort of human hepatocellular carcinoma (HCC) patients. SIRT7 knockdown influenced the cell cycle and caused a significant increase of liver cancer cells to remain in the G1 /S phase and to suppress growth. This treatment restored p21(WAF1/Cip1) , induced Beclin-1, and repressed cyclin D1. In addition, sustained suppression of SIRT7 reduced the in vivo tumor growth rate in a mouse xenograft model. To explore mechanisms in SIRT7 regulation, microRNA (miRNA) profiling was carried out. This identified five significantly down-regulated miRNAs in HCC. Bioinformatics analysis of target sites and ectopic expression in HCC cells showed that miR-125a-5p and miR-125b suppressed SIRT7 and cyclin D1 expression and induced p21(WAF1/Cip1) -dependent G1 cell cycle arrest. Furthermore, treatment of HCC cells with 5-aza-2'-deoxycytidine or ectopic expression of wildtype but not mutated p53 restored miR-125a-5p and miR-125b expression and inhibited tumor cell growth, suggesting their regulation by promoter methylation and p53 activity. To show the clinical significance of these findings, mutations in the DNA binding domain of p53 and promoter methylation of miR-125b were investigated. Four out of nine patients with induced SIRT7 carried mutations in the p53 gene and one patient showed hypermethylation of the miR-125b promoter region., Conclusion: Our findings suggest the oncogenic potential of SIRT7 in hepatocarcinogenesis. A regulatory loop is proposed whereby SIRT7 inhibits transcriptional activation of p21(WAF1/Cip1) by way of repression of miR-125a-5p and miR-125b. This makes SIRT7 a promising target in cancer therapy. (HEPATOLOGY 2013)., (Copyright © 2012 American Association for the Study of Liver Diseases.)

Predictions of toxicity are central for the assessment of chemical toxicity, and the effects of environmental toxic compounds are still a major issue for predicting potential human health risks. Among the various environmental toxicants, polycyclic aromatic hydrocarbons (PAHs) are an important class of environmental pollutant, and many PAHs are known or suspected carcinogens. In the present study, to investigate whether characteristic expression profiles of PAHs exist in rat liver and whether a characteristic molecular signature can discriminate and predict among different PAHs at an early exposure time, we analyzed the genome-wide expression profiles of rat livers exposed to PAHs [benzo[a]anthracene (BA), benzo[a]pyrene (BP), phenanthrene (PA) and naphthalene (NT)]. At early time-point PAH exposure, large-scale gene expression analysis resulted in characteristic molecular signatures for each PAH, and supervised analysis identified 1183 outlier genes as a distinct molecular signature discerning PAHs from the normal control group. We identified 158 outlier genes as early predictive and surrogate markers for predicting each tested PAH by combination of two different multi-classification algorithms with 100% accuracy through a leave-one out cross-validation method. In conclusion, the characteristic gene expression signatures from a rat model system could be used as predictable and discernible gene-based biomarkers for the detection and prediction of PAHs, and these molecular markers may provide insights into the underlying mechanisms for genotoxicity of exposure to PAHs from environmental aspect., (Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.)

Aberrant regulation of histone deacetylase 2 (HDAC2) was reported for gastric cancers. However, responsive cancer genes in disease onset and progression are less understood. HDAC2 expression was studied by quantitative RT-PCR and Western blotting. The functional consequences of HDAC2 knockdown on cell-cycle regulation, programmed cell death, and gene target identification was investigated by flow cytometry, Western blotting, electron microscopy, anchorage-independent colony formation, and cell migration assay and by whole-genome microarray. Therapeutic efficacy of HDAC2 knockdown was determined in nude mice with small hairpin expressing human gastric cancer cells. Epigenetic regulation of p16(INK4a) was studied by methylation-specific PCR and chromatin-IP to evidence HDAC2 or acetylated-histone-H4 binding at gene specific promoter sequences. HDAC2 gene and protein expression was significantly upregulated in different histopathologic grades of human gastric cancers and cancer cell lines. HDAC2 inactivation significantly reduced cell motility, cell invasion, clonal expansion, and tumor growth. HDAC2 knockdown-induced G(1)-S cell cycle arrest and restored activity of p16(INK4a) and the proapoptotic factors. This treatment caused PARP cleavage and hypophosphorylation of the Rb-protein, repressed cyclinD1, CDK4, and Bcl-2 expression and induced autophagic phenotype, that is, LC3B-II conversion. Some gastric tumors and cancer cells displayed p16(INK4a) promoter hypermethylation but treatment with 5-aza-deoxycitidine restored activity. With others the methylation status was unchanged. Here, chromatin-IP evidenced HDAC2 binding. Nonetheless, expression of p16(INK4a) was restored by HDAC2 knockdown with notable histone-H4-acetylation, as determined by chromatin-IP. Thus, p16(INK4a) is regulated by HDAC2. HDAC2 is a bona fide target for novel molecular therapies in gastric cancers., (©2012 AACR.)

Persistent organic pollutants (POPs) are degradation-resistant anthropogenic chemicals that accumulate in the food chain and in adipose tissue, and are among the most hazardous compounds ever synthesized. However, their toxic mechanisms are still undefined. To investigate whether characteristic molecular signatures can discriminate individual POP and provide prediction markers for the early detection of POPs exposure in an animal model, we performed transcriptomic analysis of rat liver tissues after exposure to POPs. The six different POPs (toxaphene, hexachlorobenzene, chlordane, mirex, dieldrin, and heptachlor) were administered to 11-week-old male Sprague-Dawley rats, and after 48 h of exposure, RNAs were extracted from liver tissues and subjected to rat whole genome expression microarrays. Early during exposure, conventional toxicological analysis including changes in the body and organ weight, histopathological examination, and blood biochemical analysis did not reflect any toxicant stresses. However, unsupervised gene expression analysis of rat liver tissues revealed in a characteristic molecular signature for each toxicant, and supervised analysis identified 2708 outlier genes that discerned the POPs exposure group from the vehicle-treated control. Combination analysis of two different multiclassifications suggested 384 genes as early detection markers for predicting each POP exposure with 100% accuracy. The data from large-scale gene expression analysis of a different POP exposure in rat model suggest that characteristic expression profiles exist in liver hepatic cells and multiclassification of POP-specific molecular signatures can discriminate each toxicant at an early exposure time. The use of these molecular markers may be more widely implemented in combination with more traditional techniques for assessment and prediction of toxicity exposure to POPs from an environmental aspect.

The putative tumor suppressor, DBC1 (deleted in breast cancer-1), was recently found to negatively regulate SIRT1 in vitro and in vivo, but the mechanism whereby DBC1 regulates SIRT1 in liver cancer remains to be elucidated. In this study, it was found that although the expression of DBC1 and SIRT1 was not aberrantly regulated in a large cohort of human hepatocellular carcinoma (HCC) patients, these proteins were highly overexpressed in a subset of HCC tissues compared with surrounding non-cancer tissues. In liver cancer, DBC1 and SIRT1 were found to be positively correlated. Inactivation of DBC1 or SIRT1 reduced SNU-182 (a liver cancer cell line) proliferation as determined by MTT viability assays. Notably, although DBC1 functions as a negative regulator of SIRT1 in A549 lung cancer cells since it suppresses the deacetylase activity of the p53 protein, it did not affect the p53 deacetylase activity of SIRT1 in SNU-182 cells. Taken together, we conclude that DBC1 is associated with SIRT1 in HCC, but that it does not inhibit SIRT1.

Unlabelled: Ubiquitin-binding histone deacetylase 6 (HDAC6) is uniquely endowed with tubulin deacetylase activity and plays an important role in the clearance of misfolded protein by autophagy. In cancer, HDAC6 has become a target for drug development due to its major contribution to oncogenic cell transformation. In the present study we show that HDAC6 expression was down-regulated in a large cohort of human hepatocellular carcinoma (HCC) patients, and that low expression of HDAC6 was significantly associated with poor prognosis of HCC patients in 5-year overall, disease-free, and recurrence-free survival. Notably, we observed that ectopic overexpression of HDAC6 suppressed tumor cell growth and proliferation in various liver cancer cells, and elicited increased LC3B-II conversion and autophagic vacuole formation without causing apoptotic cell death or cell cycle inhibition. In addition, the sustained overexpression of HDAC6 reduced the in vivo tumor growth rate in a mouse xenograft model. It was also found that HDAC6 mediated autophagic cell death by way of Beclin 1 and activation of the LC3-II pathway in liver cancer cells, and that HDAC6 overexpression activated c-Jun NH2-terminal kinase (JNK) and increased the phosphorylation of c-Jun. In contrast, the induction of Beclin 1 expression was blocked by SP600125 (a specific inhibitor of JNK) or by small interfering RNA directed against HDAC6., Conclusion: Our findings suggest that loss of HDAC6 expression in human HCCs and tumor suppression by HDAC6 occur by way of activation of caspase-independent autophagic cell death through the JNK/Beclin 1 pathway in liver cancer and, thus, that a novel tumor suppressor function mechanism involving HDAC6 may be amenable to nonepigenetic regulation., (Copyright © 2012 American Association for the Study of Liver Diseases.)

Histone deacetylase 2 (HDAC2) is crucial for embryonic development, affects cytokine signaling relevant for immune responses, and is often significantly overexpressed in solid tumors, but little is known of its role in human lung cancer. In this study, we demonstrated the aberrant expression of HDAC2 in lung cancer tissues and investigated oncogenic properties of HDAC2 in human lung cancer cell lines. HDAC2 inactivation resulted in regression of tumor cell growth and activation of cellular apoptosis via p53 and Bax activation and Bcl2 suppression. In cell cycle regulation, HDAC2 inactivation caused induction of p21WAF1/CIP1 expression, and simultaneously suppressed the expressions of cyclin E2, cyclin D1, and CDK2, respectively. Consequently, this led to the hypophosphorylation of pRb protein in G1/S transition and thereby inactivated E2F/DP1 target gene transcriptions of A549 cells. In addition, we demonstrated that HDAC2 directly regulated p21WAF1/CIP1 expression in a p53-independent manner. However, HDAC1 was not related to p21WAF1/CIP1 expression and tumorigenesis of lung cancer. Lastly, we observed that sustained-suppression of HDAC2 in A549 lung cancer cells attenuated in vitro tumorigenic properties and in vivo tumor growth of the mouse xenograft model. Taken together, we suggest that the aberrant regulation of HDAC2 and its epigenetic regulation of gene transcription in apoptosis and cell cycle components play an important role in the development of lung cancer., (Copyright © 2012 Wiley Periodicals, Inc.)

Histone deacetylases (HDACs) are known to play a central role in the regulation of several cellular properties interlinked with the development and progression of cancer. Recently, HDAC1 has been reported to be overexpressed in hepatocellular carcinoma (HCC), but its biological roles in hepatocarcinogenesis remain to be elucidated. In this study, we demonstrated overexpression of HDAC1 in a subset of human HCCs and liver cancer cell lines. HDAC1 inactivation resulted in regression of tumor cell growth and activation of caspase-independent autophagic cell death, via LC3B-II activation pathway in Hep3B cells. In cell cycle regulation, HDAC1 inactivation selectively induced both p21(WAF1/Cip1) and p27(Kip1) expressions, and simultaneously suppressed the expression of cyclin D1 and CDK2. Consequently, HDAC1 inactivation led to the hypophosphorylation of pRb in G1/S transition, and thereby inactivated E2F/DP1 transcription activity. In addition, we demonstrated that HDAC1 suppresses p21(WAF1/Cip1) transcriptional activity through Sp1-binding sites in the p21(WAF1/Cip1) promoter. Furthermore, sustained suppression of HDAC1 attenuated in vitro colony formation and in vivo tumor growth in a mouse xenograft model. Taken together, we suggest the aberrant regulation of HDAC1 in HCC and its epigenetic regulation of gene transcription of autophagy and cell cycle components. Overexpression of HDAC1 may play a pivotal role through the systemic regulation of mitotic effectors in the development of HCC, providing a particularly relevant potential target in cancer therapy.

In a previous report we demonstrated that the transcriptomic response of liver tissue was specific to toxicants, and a characteristic molecular signature could be used as an early prognostic biomarker in rats. It is necessary to determine the transcriptomic response to toxicants in peripheral blood for application to the human system. Volatile organic compounds (VOCs) comprise a major group of pollutants which significantly affect the chemistry of the atmosphere and human health. In this study we identified and validated the specific molecular signatures of toxicants in rat whole blood as early predictors of environmental toxicants. VOCs (dichloromethane, ethylbenzene, and trichloroethylene) were administered to 11-week-old SD male rats after 48h of exposure, peripheral whole blood was subjected to expression profiling analysis. Unsupervised gene expression analysis resulted in a characteristic molecular signature for each toxicant, and supervised analysis identified 1,217 outlier genes as distinct molecular signatures discerning VOC exposure from healthy controls. Further analysis of multi-classification suggested 337 genes as early detective molecular markers for three VOCs with 100% accuracy. A large-scale gene expression analysis of a different VOC exposure animal model suggested that characteristic expression profiles exist in blood cells and multi-classification of this VOC-specific molecular signature can discriminate each toxicant at an early exposure time. This blood expression signature can thus be used as discernable surrogate marker for detection of biological responses to VOC exposure in an environment., (© 2010 Elsevier Inc. All rights reserved.)

Whole blood is one of the most easily accessible biofluids, and circulating leukocytes would include informative transcripts as a first line of immune defense for many disease processes. To demonstrate that transcriptomic responses of circulating blood cells reflect the exposure to environmental toxicants and the characteristic molecular signatures can discriminate and predict the type of toxicant at an early exposure time, we identified and validated characteristic gene expression profiles of rat whole blood after exposure to polycyclic aromatic hydrocarbons (PAHs). At an early exposure time point, conventional toxicological analysis including changes in the body and organ weight, histopathological examination, and blood biochemical analysis did not reflect any toxicant stresses. However, unsupervised gene expression analysis of blood cells resulted in a characteristic molecular signature for each toxicant. Further analysis of multiclassification suggested 220 genes as early detective and surrogate markers for predicting each PAH with 100% accuracy. These findings suggest that the blood expression signature could be used as a predictable and discernible surrogate marker for detection and prediction of PAHs, and the use of these molecular markers may be more widely implemented in combination with more traditional techniques for assessment and prediction of toxicity exposure to PAHs from an environmental aspect.

Histone deacetylase 2 (HDAC2) is crucial for embryonic development, affects cytokine signaling relevant for immune responses and is often significantly overexpressed in solid tumors; but little is known about its role in human hepatocellular carcinoma (HCC). In this study, we showed that targeted-disruption of HDAC2 resulted in reduction of both tumor cell growth and de novo DNA synthesis in Hep3B cells. We then demonstrated that HDAC2 regulated cell cycle and that disruption of HDAC2 caused G1/S arrest in cell cycle. In G1/S transition, targeted-disruption of HDAC2 selectively induced the expression of p16(INK4A) and p21(WAF1/Cip1), and simultaneously suppressed the expression of cyclin D1, CDK4 and CDK2. Consequently, HDAC2 inhibition led to the down-regulation of E2F/DP1 target genes through a reduction in phosphorylation status of pRb protein. In addition, sustained suppression of HDAC2 attenuated in vitro colony formation and in vivo tumor growth in a mouse xenograft model. Further, we found that HDAC2 suppresses p21(WAF1/Cip1) transcriptional activity via Sp1-binding site enriched proximal region of p21(WAF1/Cip1) promoter. In conclusion, we suggest that the aberrant regulation of HDAC2 may play a pivotal role in the development of HCC through its regulation of cell cycle components at the transcription level providing HDAC2 as a relevant target in liver cancer therapy.

Gastric carcinoma is the most common neoplasm in Southeast Asian populations and is the second leading cause of cancer death worldwide. Annexins are a family of cytosolic calcium and membrane binding proteins that have been implicated in a wide variety of cell functions. Recent studies have suggested that Annexin A10 (ANXA10), a member of the Annexin protein family, is down-regulated in specific types of cancer. However, the underlying molecular mechanisms of the dysregulation of ANXA10 remain to be elucidated. In the present study, to investigate the biological effects of ANXA10 on gastric carcinoma, aberrant expression of ANXA10 was evaluated by Western blot analysis, reverse transcriptase-polymerase chain reaction (RT-PCR) and immunohistochemistry (IHC), in gastric cancer tissues and cell lines. Decreased expression of ANXA10 was observed in five selected gastric cancer tissues compared to the normal surrounding mucosa. In the cancer cell lines, seven out of nine selected gastric cancer cell lines had no detectable ANXA10 by RT-PCR. Among these, when an ANXA10 expressing plasmid was introduced into MKN-1 cells, cell growth was suppressed and apoptosis augmented. The results of this study demonstrated that ANXA10 was aberrantly regulated in gastric carcinoma and suggests that down-regulation of ANXA10 might be involved in gastric carcinogenesis. In addition, ANXA10 may play a role, as a tumor suppressor, in the development and progression of gastric cancer.

The Wnt/beta-catenin signaling pathway regulates various aspects of development and plays important role in human carcinogenesis. Nemo-like kinase (NLK), which is mediator of Wnt/beta-catenin signaling pathway, phosphorylates T-cell factor/lymphoid enhancer factor (TCF/LEF) factor and inhibits interaction of beta-catenin/TCF complex. Although, NLK is known to be a tumor suppressor in Wnt/beta-catenin signaling pathway of colon cancer, the other events occurring downstream of NLK pathways in other types of cancer remain unclear. In the present study, we identified that expression of NLK was significantly up-regulated in the HCCs compared to corresponding normal tissues in five selected tissue samples. Immunohistochemical analysis showed significant over-expression of NLK in the HCCs. Targeted-disruption of NLK suppressed cell growth and arrested cell cycle transition. Suppression of NLK elicited anti-mitogenic properties of the Hep3B cells by simultaneous inhibition of cyclinD1 and CDK2. The results of this study suggest that NLK is aberrantly regulated in HCC, which might contribute to the mitogenic potential of tumor cells during the initiation and progression of hepatocellular carcinoma; this process appears to involve the induction of CDK2 and cyclin D1 and might provide a novel target for therapeutic intervention in patients with liver cancer., ((c) 2010 Wiley-Liss, Inc.)

The compound 3,4-methylenedioxymethamphetamine (MDMA or ecstasy) is a synthetic, psychoactive drug chemically similar to the stimulant methamphetamine and the hallucinogen mescaline. Accumulated data has revealed potential toxic effects associated with MDMA on brain serotonin and dopamine neurons in animal models. However, the relevance of these adverse effects on prenatal exposure to this drug remains unknown. In this study, we demonstrated that prenatal (F0) exposure to MDMA caused permanent large-scale transcriptional changes in the brains of the offspring (F1), especially in the cerebral cortex, by gene expression profiling analysis. The expression analysis of the brain of F1 pups, after maternal ingestion of MDMA (20 mg/kg MDMA), revealed significant transcriptional changes in both male and female pups. Supervised analysis resulted in the identification of 804 outlier genes in males and 1784 outlier genes in females as MDMA-associated genes in the F1 generation. Most of the functional categories of genes, among the outlier genes, were intracellular signaling pathways, including the MAPK signaling pathway, Wnt signaling pathway, and neuroactive ligand-receptor interaction pathway. Although these genes were affected by MDMA exposure in utero, their association with brain dysfunction requires further investigation. The results of this study suggest that prenatal MDMA exposure may affect the developing brain., (Copyright (c) 2010 Elsevier Ireland Ltd. All rights reserved.)