Quantification Technology Research Articles

Development and assessment of a duplex droplet digital PCR method for quantification of GM rice Kemingdao.

The implementation of genetically modified organism (GMO) labeling policies requires accurate quantitative methods to measure the GMO content in test samples. A Kemingdao/phospholipase D (KMD/PLD) duplex ddPCR method was established with rice genomic DNA (gDNA) of homozygous KMD as template by optimizing the annealing temperature and cycle number. Duplex ddPCR showed a linear response over the dynamic range from 68 to 175,000 copies, covering four orders of magnitude. The limit of detection (LOD) and limit of quantification (LOQ) for duplex ddPCR were determined to be 9 copies and 34 copies of the rice haploid genome, respectively. A very high dilution factor would result in unacceptable bias and coefficients of variation for determining copy number of the gDNA solution, and more than 1000 copies of the DNA template in one reaction is preferred to obtain accurate quantitative results by duplex PCR. Five blinded DNA samples with copy number ratio of 10%, 5%, 1%, 0.1%, and 0.05%, and three blinded real-life matrix samples with mass fraction of 5%, 1%, and 0.5% were quantified by duplex ddPCR, simplex ddPCR, and qPCR. These three methods all gave comparable GMO content and copy numbers within the required precision, but the duplex ddPCR showed the narrowest uncertainty interval and provided the highest precision in comparison to simplex ddPCR and qPCR. The ddPCR is a more appealing and reliable technology for the accurate quantification of GMO content than simplex ddPCR and qPCR considering the uncertainty and precision of quantitative results, the time consumption of generating droplets, and the cost of ddPCR reagents.

Identification of potential plasma protein biomarkers for bipolar II disorder: a preliminary/exploratory study

The diagnostic peripheral biomarkers are still lacking for the bipolar II disorder (BD-II). We used isobaric tags for relative and absolute quantification technology to identify five upregulated candidate proteins [matrix metallopeptidase 9 (MMP9), phenylalanyl-tRNA synthetase subunit beta (FARSB), peroxiredoxin 2 (PRDX2), carbonic anhydrase 1 (CA-1), and proprotein convertase subtilisin/kexin type 9 (PCSK9)] for the diagnosis of BD-II. We analysed the differences in the plasma levels of these candidate proteins between BD-II patients and controls (BD-II, n = 185; Controls, n = 186) using ELISA. To establish a diagnostic model for the prediction of BD-II, the participants were divided randomly into a training group (BD-II, n = 149; Controls, n = 150) and a testing group (BD-II, n = 36; Controls, n = 36). Significant increases were found in all five protein levels between BD-II and controls in the training group. Logistic regression was analysed to form the composite probability score of the five proteins in the training group. Receiver-operating characteristic curve analysis revealed the diagnostic validity of the probability score [area under curve (AUC) = 0.89, P < 0.001]. The composite probability score of the testing group also showed good diagnostic validity (AUC = 0.86, P < 0.001). We propose that plasma levels of PRDX2, CA-1, FARSB, MMP9, and PCSK9 may be associated with BD-II as potential biomarkers.

Proteomic analysis of hemocyte reveals the immune regulatory mechanisms after the injection of corticosteroid-releasing hormone in mud crab Scylla Paramamosain

Corticosteroid-releasing hormone (CRH) is a crucial neuroendocrine-immune factor regulating the immune response of Scylla paramamosain. To understand the regulatory mechanisms of CRH in S. paramamosain, the hemolymph of S. paramamosain with injection of CRH (1.5 ng/crab) at 24 h were chosen to perform proteomic analysis in this study. Furthermore, quantitative real-time PCR (RT-PCR) method was used to validate the accuracy of proteomic data at 24 h after CRH injection. The proteomic data showed that 255 DEPs were identified, in which 231 and 24 were up- or down-regulated, respectively. Besides, the results of enriched pathways showed that the DEPs were involved in signaling pathways, cellular immunity, humoral immunity and the response of immune related processes. These results revealed that CRH promoted the activation of signal transduction, regulated immune systems and antioxidation, and enhanced the immune related processes (such as protein synthesis, protein transport, carbohydrate mobilization and energy redistribution). These findings will benefit to foster the understanding on the effects of glucocorticoids on neuroendocrine-immune (NEI) networks of crustacean, and supply a substantial material and foundation for further researching of the NEI response. SignificanceCorticotrophin-releasing hormone (CRH) is a 41-amino acid neuropeptide and has been preliminarily studied in aquatic animals. CRH can regulate many important physiological activities comprising protein synthesis, energy metabolism, growth, breeding and behavior in fish, which play an important roles in neuroendocrine-immune (NEI) regulatory network of fish. The neuroendocrine system of crustacean has a primary research, that inspired by fish NEI network. Despite the research on the neuroendocrine system in crustacean has rapidly increased in recent years, our understanding of the regulation between neuroendocrine system and immune system in crustacean is still limited. The research on the strategy of NEI network in crustaceans becomes a significant issue.In the present study, the isobaric tags for relative and absolute quantification (iTRAQ) technology approach were applied to examine the NEI network of Scylla Paramamosain. control group and treatment group (CRH: 1.5 ng/crab) were settled for the iTRAQ experiment, and sampled at 24 h after CRH injection. The study aimed to gain knowledge on the immune response in Scylla Paramamosain after CRH injection and identify related differentially expressed proteins (DEPs) of the crab. The results of this study provide a preliminary resource for analysis the immune mechanism for crustaceans.In general, our work represents the first report of the utilization of the iTRAQ proteomics method for the study of NEI regulatory network in Scylla Paramamosain after CRH injection. We identified a number of DEPs involved in diverse pathways including immune signaling pathways, cellular immunity, humoral immunity, immune related process. These results demonstrated a very complex network involving immune and multiple related metabolic pathways in hemocytes of Scylla Paramamosain and will be of great value in understanding the crab neuroendocrine-immune immune mechanism.

Application of LIBS technology for quantification of Er3+ ions in tellurite glasses

Application of LIBS technology for quantification of Er3+ ions in tellurite glasses

Low Field Gradient and Highly Enhanced Plasmonic Nanocavity Array for Supersensitive Determination of Multiple Hazardous Chemical Residues

Surface-enhanced Raman scattering (SERS) has become the key technology for identification and quantification of various chemical molecules, biomolecules, viruses, and other pathogens in biology, el...

Profiling of circRNAs using an enzyme-free digital counting method.

Circular RNAs (circRNAs) have recently gained substantial attention as potential biomarkers in several human diseases, most prominently in cancer. However, the detection and quantification of circRNA biomarkers pose specific challenges owing to their circular nature. In particular, the use of enzymes, such as reverse transcriptases, may lead to impaired quantification, poor interlaboratory reproducibility and even false-positive results. Therefore, the development of methods for accurate quantification of circRNA biomarkers is a high priority. An enzyme-free and digital quantification method, named NanoString nCounter, was recently adapted for circRNA detection. In this review, I describe the advantages of using this technology for circRNA quantification as well as methodological considerations, potential pitfalls and disadvantages.

Assessment and visualization of performance indicators of reinforced concrete beams by distributed optical fibre sensing

The implementation of structural health monitoring systems in civil engineering structures already in the construction phase could contribute to safer and more resilient infrastructure. Due to their lightweight, small size and high resistance to the environment, distributed optical fibre sensors stand out as a very promising technology for damage detection and quantification in reinforced concrete structures. In this article, the suitability of embedding robust distributed optical fibre sensors featuring a protective sheath to accurately assess the performance indicators, in terms of vertical deflection and crack width, of three reinforced concrete beams subjected to four-point bending is investigated. The results revealed that a certain strain attenuation occurs in embedded robust distributed optical fibre sensors compared to commonly used thin polyimide-coated distributed optical fibre sensors bonded to steel reinforcement bars. However, the presence of the protective sheath prevented the appearance of strain reading anomalies which has been a frequently reported issue. Performance wise, the robust distributed optical fibre sensors were able to provide a good estimate of the beam deflections with errors of between 12.3% and 6.5%. Similarly, crack widths computed based on distributed optical fibre sensor strain measurements differed by as little as ±20 µm with results from digital image correlation, provided individual cracks could be successfully detected in the strain profiles. Finally, a post-processing procedure is presented to generate intuitive contour plots that can help delivering critical information about the element’s structural condition in a clear and straightforward manner.

ITRAQ-based proteomic analysis of the hippocampus of pentylenetetrazole-kindled epileptic rats.

Epilepsy can severely affect the quality of life of patients, who are often at higher risk of mortality. However, the molecular mechanisms and pathogenesis underlying epileptogenesis are poorly understood. In this study, we performed a proteomic analysis of the hippocampus in pentylenetetrazole (PTZ)-kindled epileptic rats to explore the molecular mechanisms of epileptogenesis. We established an epileptic model in Sprague Dawley rats by injecting PTZ intraperitoneally and applied isobaric tags for relative and absolute quantification (iTRAQ) technology integrated with liquid chromatography-tandem mass spectrometry (LC-MS/MS) to identify differentially expressed proteins (DEPs) in the hippocampus. A total of 99 proteins, comprising 93 upregulated and 6 downregulated proteins, were identified based on a fold change >1.2 (or <0.83) and a p-value<.05. A further bioinformatics analysis suggested that the candidate proteins were mainly involved in the ubiquitin ligase complex or metabolite homeostasis or acted as intrinsic components of the membrane. A Kyoto Encyclopedia of Gene and Genomes (KEGG) pathway enrichment analysis identified a series of representative pathological pathways, including the calcium signaling pathway, neuroactive ligand-receptor interaction pathway, and the NF-kappa B pathway. The mass spectrometry results were further confirmed by assessing five representative proteins (Akt1, Syvn1, Amfr, Lamb1, and Cox17) using western blotting and immunohistochemistry. These results may help to reveal the molecular mechanisms underlying epileptogenesis and provide new directions or targets for epilepsy research.

BIM plug-in technology for construction waste quantification

Current building management standards demand that construction waste management occurs in the planning phase. This paper presents the development of a plug-in as a BIM tool to predict waste generation. As a research strategy, the plug-in was applied to a single-family housing project, the respective construction wastes were predicted in the BIM technology and compared to the literature. Through waste generation indexes, some planning indicators were calculated. The identified wastes were automatically classified, and a management structure was designed. The study showed that the best results are obtained when the construction waste is estimated from Actual Built Volume instead of Apparent Constructed Volume like the traditional models uses. In conclusion, adopting a plug-in do predict construction waste has proved to be advantageous. A specific advantage of the proposed method is that the plug-in user may adopt their waste generation indexes according to the regional and the production team aspects. The adoption of a plug-in made the acquisition and processing of data fast and versatile.

Using Head-Mounted Ethanol Sensors to Monitor Olfactory Information and Determine Behavioral Changes Associated with Ethanol-Plume Contact during Mouse Odor-Guided Navigation.

Olfaction guides navigation and decision-making in organisms from multiple animal phyla. Understanding how animals use olfactory cues to guide navigation is a complicated problem for two main reasons. First, the sensory cues used to guide animals to the source of an odor consist of volatile molecules, which form plumes. These plumes are governed by turbulent air currents, resulting in an intermittent and spatiotemporally varying olfactory signal. A second problem is that the technologies for chemical quantification are cumbersome and cannot be used to detect what the freely moving animal senses in real time. Understanding how the olfactory system guides this behavior requires knowing the sensory cues and the accompanying brain signals during navigation. Here, we present a method for real-time monitoring of olfactory information using low-cost, lightweight sensors that robustly detect common solvent molecules, like alcohols, and can be easily mounted on the heads of freely behaving mice engaged in odor-guided navigation. To establish the accuracy and temporal response properties of these sensors we compared their responses with those of a photoionization detector (PID) to precisely controlled ethanol stimuli. Ethanol-sensor recordings, deconvolved using a difference-of-exponentials kernel, showed robust correlations with the PID signal at behaviorally relevant time, frequency, and spatial scales. Additionally, calcium imaging of odor responses from the olfactory bulbs (OBs) of awake, head-fixed mice showed strong correlations with ethanol plume contacts detected by these sensors. Finally, freely behaving mice engaged in odor-guided navigation showed robust behavioral changes such as speed reduction that corresponded to ethanol plume contacts.

Research on application method of uncertainty quantification technology in equipment test identification

This paper introduces the concepts of equipment test qualification and uncertainty quantification, and the analysis framework and process of equipment test uncertainty quantification. It analyzes the data uncertainty, model uncertainty and environmental uncertainty, and studies the corresponding uncertainty quantification theory to provide technical reference for the application of uncertainty quantification technology in the field of test identification.

8 Assessment of consistency in quantification of ribonucleic acid across multiple methods

Abstract Quantification and assessment of quality of ribonucleic acid (RNA) is essential for assays determining gene expression including qRT-PCR, northern blotting, and RNA sequencing. Methods assessing RNA abundance and quality vary in detection range and specificity, in part due to their differences in how quantification is achieved. Agilent chip technology utilizes fluorescent labeling of nucleic acids coupled to electrophoresis to separate RNA based on size. Nanodrop utilizes spectrophotometry assesses quantity nucleic acids based on absorption of light and allows for an estimation of purity using the A260/280 (nucleic acid to protein) ratio. RiboGreen assays utilize a fluorescent intercalating dye that specifically targets single-stranded RNA. The objective of this study was to determine the most accurate method of RNA quantification between these three assays. Male pituitary samples (n = 220) were collected at a local abattoir, anterior lobe isolated, flash frozen in methanol dry-ice bath, and stored at -80°C until further processing. Total RNA was isolated from all samples and samples were subjected to spectrophotometry, Agilent nano chip assay, and Ribogreen assay. Data were analyzed for differences in standard deviation of total yield (mg/g) across all methods and each pair of methods using an O’Brien test for unequal variances. Standard deviation differed due to quantification method (P = 0.0002). Over 5 times greater variability in quantification was observed between Agilent chip technology compared to nanodrop (P = 0.0036), 2 times greater between nanodrop and Ribogreen (P &amp;lt; 0.0001), and 10 times greater variation between Agilent and Ribogreen methods (P = 0.0029). The Ribogreen assay provides the smallest variation in quantification from sample to sample and is the most reliable method out of the three technologies for quantification of RNA; however, it does not address issues of RNA quality.

Imaging Tremor Quantification for Neurological Disease Diagnosis.

In this paper, we introduce a simple method based on image analysis and deep learning that can be used in the objective assessment and measurement of tremors. A tremor is a neurological disorder that causes involuntary and rhythmic movements in a human body part or parts. There are many types of tremors, depending on their amplitude and frequency type. Appropriate treatment is only possible when there is an accurate diagnosis. Thus, a need exists for a technique to analyze tremors. In this paper, we propose a hybrid approach using imaging technology and machine learning techniques for quantification and extraction of the parameters associated with tremors. These extracted parameters are used to classify the tremor for subsequent identification of the disease. In particular, we focus on essential tremor and cerebellar disorders by monitoring the finger–nose–finger test. First of all, test results obtained from both patients and healthy individuals are analyzed using image processing techniques. Next, data were grouped in order to determine classes of typical responses. A machine learning method using a support vector machine is used to perform an unsupervised clustering. Experimental results showed the highest internal evaluation for distribution into three clusters, which could be used to differentiate the responses of healthy subjects, patients with essential tremor and patients with cerebellar disorders.

‘From fat and frazzled to fit and happy’: governing the unhealthy employee through quantification and wearable technologies

ABSTRACT Fitbits are one of an increasing number of wearable devices that are being used in workplace wellness programmes to track steps taken, stairs climbed, distance walked, calories burned, hours slept, and more. In this paper I examine Fitbit Health Solutions (FHS), a subset of the larger Fitbit, Inc., that is devoted to uses of Fitbit devices in workplace wellness programs. Using digital methods to collect documents pertaining to workplace wellness and FHS, as well as interviews with experts who have worked in a professional capacity to bring Fitbits into the workplace, the goal of this paper is to reflect on the increasing ubiquity of quantification and surveillance in employee health initiatives. Drawing on the Foucauldian tool of governmentality analysis, I excavate how these forms of ‘government at a distance’ construct employees as unfit and how quantification is mobilised to characterise and address that problem. First, I discuss the creation of identity categories of fit and unfit employees. Second, I describe how quantification provides a path to fitness for those needing improvement. Third, I explore how quantification and other means of measurement are used in the evaluation of programs and in selling the ‘story’ that Fitbits are a solid return on investment. Finally, I consider the ethical implications of these quantification initiatives, and consider the future of these technologies in workplaces.

Chip-based digital PCR for direct quantification dynamic bacterial load in target organs of tilapia infected with Streptococcus agalactiae, a pathogen causing meningoencephalitis in teleosts

To detection of pathogens DNA is considered a promising strategy in sick fish. The current standard for enumeration of pathogens to obtain colony forming units by plate counts has several drawbacks: long time to results, high variability. While qPCR can target genetic identity, its limitations require enumeration to be calculated from a relative standard curve. There is a growing interest in techniques that allows an absolute quantification of pathogens DNA which could be useful for early diagnosis. Recently, digital PCR mainly based on droplets generation, emerged as an affordable technology for precise and absolute quantification of nucleic acids. In this work, we described a new interesting approach for profiling Streptococcus agalactiae DNA in tilapia different tissues samples using a chip-based platform, the Quant Studio 3D digital PCR. A total of 120 tissue samples were analyzed by plant count, qPCR and chip-based dPCR. The cdPCR method had a 5% relative standard deviation (RSD), marking it more precise than plate counts and qPCR with an RSD of 15 % and 10 %. Given its reproducibility and reliability, our approach could be potentially applied for the identification and quantification of pathogens DNA in infected fish. As chip-digital PCR becomes more established, it would be a robust tool for quantitative assessment of S. agalactiae DNA copy number for diagnosis of Streptococcosis.

The optimization of process analytical technology for the inline quantification of multiple drugs in fixed dose combinations during continuous processing

Complications associated with uncontrolled hypertension are considered the major cause of premature death worldwide. Fixed-dose combinations (FDCs) offer an alternative approach to polypharmacy with the aim to improve patient compliance. Process Analytical Technology (PAT) is gaining momentum as a non-invasive, predictive tool to control the quality of drugs during continuous processing. PAT offers real-time quality control that can be built into the production line. However, the vast majority of studies reported in the literature have focused on quantifying a single drug during continuous processing. The aim of this study was to develop non-destructive, predictive inline PAT tools allowing for the simultaneous quantification of two antihypertensive drugs, Hydrochlorothiazide (HCTZ) and Ramipril (RMP), during the continuous manufacture of FDCs. A calibration set composed of HCTZ and RMP at concentration ranges of 6.5 to 40 and 2.5-15 (% w/w), respectively, were manufactured using hot melt extrusion. The extrudates were analysed during the process using inline Raman spectroscopy. Optimum wavenumber regions were observed at 200-400 and 630-730cm-1 for HCTZ, and 980-1100cm-1 for RMP using principal component analysis. Partial least squares (PLS) regression was performed to establish the predictive calibration models. The PLS developed models showed excellent linearity (R2=0.986 and 0.974), selectivity (PC1=98.6% and 91.9%) and accuracy (RMSEcv=1.586 and 0.645%) for HCTZ and RMP, respectively. Additionally, RMSEP values were reported as 1.237 and 1.007% for HCTZ and RMP, respectively, depicting good predictability for drug content in the validation set. The output of this study demonstrated that utilisation of the full potential of chemometrics, Raman spectroscopy can be used for the simultaneous inline quantification of multiple drugs in complex formulations. This facilitates the in-process quality control of FDCs and other multicomponent systems during continuous pharmaceutical production.

CTAB modified Fe-WO3 as an electrochemical detector of amitrole by catalytic oxidation

The increasing health risk associated with the exposure to mutagenic, teratogenic and carcinogenic herbicide in the environment has encouraged a significant interest towards the development of rapid and cheaper detection technologies for the accurate quantification. The present work involves the exploitation of catalytic oxidation of herbicide, amitrole (AMT) at iron doped tungsten oxide (Fe-WO3) nanoparticles and cationic surfactant cetyltrimethylammonium bromide (CTAB) based carbon paste electrode for the sensitive quantification. The working electrode assembly of Fe-WO3/CTAB causes the catalytic oxidation via faster electron transfer compared to bare electrode. Furthermore, the physiochemical properties and thermodynamic properties of AMT were explored. Under the optimized conditions, the modified sensor exhibits good linear detection range (5.0 × 10−8 M to 8.0 × 10−5 M), lower limit of detection (0.82 nM) and limit of quantification (2.82 nM) by square wave voltammetric (SWV) technique. Hence, developed senor showed an intensification of peak current of AMT with significant sensitivity, selectivity and reproducibility for AMT analysis and received acceptable results indicates the application of sensors for the analysis of AMT in water as well as soil samples.

Proteomic Analysis of UV-B-Induced Virulence-Mutant Strains of Puccinia striiformis f. sp. tritici Based on iTRAQ Technology.

The emergence of new physiological races of Puccinia striiformis f. sp. tritici (Pst) causing wheat stripe rust can lead to the loss of resistance of wheat cultivars to stripe rust, thus resulting in severe losses in wheat yield. In this study, after the germination of urediospores of three Pst strains including the original strain (CYR32, a dominant physiological race of Pst in China) and two virulence-mutant strains (CYR32-5 and CYR32-61) acquired from CYR32 via UV-B radiation, proteomic analysis based on isobaric tags for relative and absolute quantification (iTRAQ) technology was performed on the strains. A total of 2,271 proteins were identified, and 59, 74, and 64 differentially expressed proteins (DEPs) were acquired in CYR32-5 vs. CYR32, CYR32-61 vs. CYR32, and CYR32-61 vs. CYR32-5, respectively. The acquired DEPs were mainly involved in energy metabolism, carbon metabolism, and cellular substance synthesis. Furthermore, quantitative reverse transcription PCR assays were used to determine the relative expression of the 6, 7, and 1 DEPs of CYR32-5 vs. CYR32, CYR32-61 vs. CYR32, and CYR32-61 vs. CYR32-5, respectively, at the transcriptional level. The relative expression levels of one, five, and one gene, respectively, encoding the DEPs, were consistent with the corresponding protein abundance determined by iTRAQ technology. Compared with CYR32, the DEPs associated with energy metabolism and stress—including E3JWK6, F4S0Z3, and A8N2Q4—were up-regulated in the mutant strains. The results indicated that the virulence-mutant strains CYR32-5 and CYR32-61 had more tolerance to stress than the original strain CYR32. The results obtained in this study are of great significance for exploring the virulence variation mechanisms of Pst, monitoring the changes in Pst populations, breeding new disease-resistant wheat cultivars, and managing wheat stripe rust sustainably.

Proteomic Analysis of Proteins Associated with Inhibition of Pseudomonas aeruginosa Resistance to Imipenem Mediated by the Chinese Herbal Medicine Qi Gui Yin.

Objective: Antibiotic resistance of Pseudomonas aeruginosa (PA) that lowers the effectiveness of current treatments for pneumonia is a growing problem. Qi Gui Yin is a Chinese herbal medicine that has been used to improve the efficacy of antibiotic therapy against antibiotic-resistant bacteria. This study aimed to elucidate the mechanism by which Qi Gui Yin inhibits antibiotic resistance of PA. Methods: Active components of Qi Gui Yin were analyzed by chromatography. Isobaric Tags for Relative and Absolute Quantification (iTRAQ) technology was used to compare protein expression profiles of PA strains cultured in serum from rats that were and were not treated with Qi Gui Yin. Quantitative polymerase chain reaction (qPCR) analysis was performed to detect gene expression changes. Results: Proteomic analysis identified 76 differentially expressed proteins between PA strains cultured in serum from rats that were or were not treated with Qi Gui Yin. Bioinformatics analysis revealed that the largest number of differentially expressed proteins were associated with resistance mechanisms such as quorum sensing, bacterial biofilm formation, and active pumping. In addition, qPCR analysis confirmed that downregulation of iscU and arcA gene expression was associated with Qi Gui Yin treatment. Conclusions: Serum from Qi Gui Yin-treated rats could effectively inhibit antibiotic resistance of PA. Chlorogenic acid and astragaloside IV are the main components of Qi Gui Yin, which may mediate inhibition of antibiotic resistance. Our findings provide new insights into strategies involving Chinese herbal medicine that can be used to treat pneumonia caused by antibiotic-resistant bacteria.

N-MYC Downstream Regulated Gene 4 (NDRG4), a Frequent Downregulated Gene through DNA Hypermethylation, plays a Tumor Suppressive Role in Esophageal Adenocarcinoma.

Simple SummaryEsophageal adenocarcinoma has become a major clinical challenge in the western world due to its rapid increasing incidence and poor overall prognosis. Understanding the molecular events of its tumorigenesis is the key to better diagnosis and development of better therapeutic strategies. In the current study we aimed to identify epigenetic alteration targets in esophageal adenocarcinoma. We focused on a candidate gene, NDRG4 (N-myc downregulated gene 4). We found that NDRG4 was frequent downregulated in esophageal adenocarcinoma through DNA hypermethylation of its promoter region. Re-expression of NRDG4 in cancer cells significantly suppressed tumor growth via inhibition of cell proliferation. These results will improve our understanding on how dysfunction of NDRG4 contributes to esophageal adenocarcinoma. DNA hypermethylation of NDRG4 may be a useful biomarker in clinical monitoring of esophageal adenocarcinoma patients.The incidence of esophageal adenocarcinoma (EAC) has been rising dramatically in the past few decades in the United States and Western world. The N-myc downregulated gene 4 (NDRG4) belongs to the human NDRG family. In this study, we aimed to identify the expression levels, regulation, and functions of NDRG4 in EAC. Using an integrative epigenetic approach, we identified genes showing significant downregulation in EAC and displaying upregulation after 5-Aza-deoxycitidine. Among these genes, likely to be regulated by DNA methylation, NDRG4 was among the top 10 candidate genes. Analyses of TCGA (The Cancer Genome Atlas) and GEO (Gene Expression Omnibus) data sets and EAC tissue samples demonstrated that NDRG4 was significantly downregulated in EAC (p < 0.05). Using Pyrosequencing technology for quantification of DNA methylation, we detected that NDRG4 promoter methylation level was significantly higher in EAC tissue samples, as compared to normal esophagus samples (p < 0.01). A strong inverse correlation between NDRG4 methylation and its gene expression levels (r = −0.4, p < 0.01) was observed. Treatment with 5-Aza restored the NDRG4 expression, confirming that hypermethylation is a driving force for NDRG4 silencing in EAC. Pathway and gene set enrichment analyses of TCGA data suggested that NDRG4 is strongly associated with genes related to cell cycle regulation. Western blotting analysis showed significant downregulation of Cyclin D1, CDK4 and CDK6 in EAC cells after overexpression of NDRG4. Functionally, we found that the reconstitution of NDRG4 resulted in a significant reduction in tumor cell growth in two-dimensional (2D) and three-dimensional (3D) organotypic culture models and inhibited tumor cell proliferation as indicated by the EdU (5-ethynyl-2′-deoxyuridine) proliferation assay.