Abuse detection in healthcare insurance with disease-treatment network embedding.

Abuse in healthcare insurance refers to a medical service or practice inconsistent with the generally accepted sound fiscal practices, such as overtreatment or overcharging. These types of abuses may lead to prescriptions that do not meet the criteria for medical stability. On the other hand, abuse may incur unnecessary costs by deliberately executing gratuitous treatments. In efforts to detect and prevent abuse, insurance companies hire medical professionals to manually examine the legitimacy of claim filings. It is, however, very costly in terms of labor and time to review all of the claims given the exploding amount of filings. In this light, there are growing interests for employing data mining techniques to automatically detect abusive claims or providers showing an abnormal billing pattern. Unfortunately, most of these models do not consider the disease-treatment information explicitly. In order for detection models to properly address the issues rising from individual drugs with similar efficacy, it is absolutely essential to account for the relationship between diseases and treatments during the learning process. In this paper, we propose a network-based approach which assesses the relationship between the diseases and treatments when detecting abuse from claim filings. Our proposed model consists of three stages. During the first stage, a disease-treatment network is constructed based on information extracted from the claim filings. Since the association between diseases and treatments is not explicitly expressed on these filings, we infer the disease-treatment relationship by computing the relative risk (RR). Second stage involves selecting the best graph embedding method from several candidates. We select the best method by comparing performances on link prediction. At the final stage, we solve a link prediction problem as a vehicle to detecting overtreatments. If our link prediction model predicts links to be nonexistent for all of the diseases and treatments listed in a given claim, then the claim is classified as an overtreatment case. We test the proposed model using the real-world claim data and showed that the proposed method classifies the treatment well which does not explicitly exist in the training network.

A scoring model to detect abusive medical institutions based on patient classification system: Diagnosis-related group and ambulatory patient group.

The detection of medical abuse is essential because medical abuse imposes extra payments on individual insurance fees and increases unnecessary social costs. To reduce the costs due to medical abuse, insurance companies hire medical experts who examine claims, suspected to arise as a result of overtreatment from institutions, and review the suitability of claimed treatments. Owing to the limited number of reviewers and mounting volume of claims, there is need for a comprehensive method to detect medical abuse that uses a scoring model that selects a few institutions to be investigated. Numerous studies for detecting medical abuse have focused on institution-level variables such as the average values of hospitalization period and medical expenses to find the abuse score and selected institutions based on it. However, these studies use simple variables to construct a model that has poor performance with regard to detecting complex abuse billing patterns. Institution-level variables could easily represent the characteristics of institutions but loss of information is inevitable. Hence, it is possible to reduce information loss by using the finest granularity of data with treatment-level variables. In this study, we develop a scoring model by using treatment-level information and it is first of its kind to use a patient classification system (PCS) to improve the detection performance of medical abuse. PCS is a system that classifies patients in terms of clinical significance and consumption of medical resources. Because PCS is based on diagnosis, the patients grouped according to PCS tend to suffer from similar diseases. Claim data segmented by PCS is composed of patients with fewer types of diseases; hence, the data distribution by PCS is more homogeneous than data classified with respect to medical departments. We define an abusive institution as an institution having numerous number of abused treatments and containing their large sum of the abuse amounts, and the main idea of our model is that the abuse score of an institution is approximated as the sum of abuse scores for all treatments claimed from the institution. The proposed method consists of two steps: training a binary classification model to predict the abusiveness of each treatment and yielding an abuse score for each institution by aggregating the predicted abusiveness. The resulting abuse score is used to prioritize institutions to investigate. We tested the performance of our model against the scoring model employed by the insurance review agency in South Korea, making use of the real world claim data submitted to the agency. We compared these models with efficiency which represents the extent to which the model may detect the abused amounts per treatment. Experimental results show that the proposed model has efficiency up to 3.57 times higher than the model employed by the agency. In addition, we put forward an efficient and realistic reviewing process when the proposed scoring model is applied to the existing process. The proposed process has efficiency up to 2.17 times higher than the existing process.

A medical treatment based scoring model to detect abusive institutions.

Medical abuse refers to a type of abnormal medical practice which is not in compliance with qualitative or ethical standards, such as excessive prescription or overbilling of medical services. Detection of such medical abuses is crucial, especially for the patients and insurance providers, because they become subject to the extra payments incurred. As a result, insurance providers hire medical experts in order to review claims manually, yet through examination is almost impossible due to the volume of the claims filed. A typical approach is to select institutions on suspicion of abusive practices and to manually review all claims involving suspect institutions. In this light, several studies have developed models designed to extract institution-level variables. However, since these variables are at an institution-level, the model cannot account for different types of abuse practiced by individual institutions, hence degrading the accuracy of the prediction model. At the same time, these variables contain information too simple to construct an effective scoring model. In this study, we propose a model that scores the degree of abuse practiced by institutions at the treatment-level, which is the lowest level of data that can be obtained from a medical claim. Our model is the first to use such fine-grained information to construct a model for scoring the abuse by medical institutions. The proposed model consists of two stages: Training a deep neural network with embedding layers for categorical variables, and scoring the abuse degree for each treatment with the model. Then, we aggregate the resulting abuse score of each treatment and the claim amount associated with each treatment by an institution which we define as the abuse score of the institution. We test our model using real-world claim data submitted to the Health Insurance Review and Assessment (HIRA) in 2016. We also compare the performance of the proposed model against the scoring model HIRA has been using, which computes the abuse score of an institution by using institution-level variables as proposed in past literature. Experiment results show that the proposed model represents the degree of medical abuse better. In addition, the results suggest that the reviewers may examine through the claims by at most 6.1 times more efficiently than when using the scoring model with institution-level variables.

Correlation between Solid Content and Antioxidant Activities in Umbelliferae Salad Plants.

The aim of this study is to evaluate the antioxidant properties of 70% methanolic extracts and the correlation between several antioxidant activities in selected Umbelliferae plants, based on total phenolic content (TPC) and total flavonoid content (TFC). For Umbelliferae plants extracts, the IC50 of DPPH radical (100 µM) quenching activities for extract, TPC, and TFC were 39∼179 µg dry weight (DW)/mL, 14.08∼38.11 µg TPC/mL, and 0.36∼1.51 µg TFC/mL, respectively. The oxygen radical absorbance capacity (ORAC) of extracts ranged from 11.44 to 42.88 mg Trolox equivalent (TE)/g DW extract, whereas ORAC for TPC and TFC was 47.40∼240.19 mg TE/g and 0.72∼11.22 g TE/g, respectively. The TPC had a superior linear correlation (r2=0.817) with 2,2'-azinobis (3-ethylbenzothiazoline-6-sulfonic acid) values. Of the 14 Umbelliferae plant extracts, Sanicula rubiflora, Sanicula chinensis, Torilis japonica, Torilis scabra, and Angelica fallax showed the strongest antioxidant activity.

Antiobesity Effects of Salvia plebeia R. Br. Extract in High-Fat Diet-Induced Obese Mice.

This study was designed to investigate the antiobesity effects of Salvia plebeia R. Br. ethanolic extracts (SPE) in mice fed high-fat diets (HFD). Male C57BL/6J mice were randomly assigned to four groups: normal diet (Chow), high-fat diet (HFD, 45% fat), HFD+SPE 200 (200 mg/kg b.w.), and HFD+SPE 400 (400 mg/kg b.w.). Extracts were administered orally every day for 8 weeks. Increases in body/fat weight and feed efficiency ratio were monitored in all mice. In addition, obesity resulting from feeding HFD to the mice was confirmed by the increase of glucose level, aspartate transaminase, alanine transaminase, triglyceride (TG), high-density lipoprotein cholesterol, very low-density lipoprotein-c, leptin, and adiponectin in blood. The SPE-treated mice gained less body and mesenteric/subcutaneous adipose tissues weights and had lower TG, very low-density lipoprotein cholesterol, leptin, and glucose level in serum, compared to the HFD group. Moreover, histopathological examinations revealed that the size of adipocytes in liver and adipose tissue was significantly decreased by SPE, compared to the HFD group. The expression of adipogenesis transcription factors (e.g., peroxisome proliferator activated receptor γ and CCAAT/enhancer binding protein α) and lipogenesis-related target genes (adipocyte fatty acid-binding protein 2, lipoprotein lipase, fatty acid synthase, and sterol regulatory element-binding transcription factor 1c) in HFD-induced obese mice was decreased by SPE treatment. These results suggest that SPE attenuates the fat accumulation in HFD-induced obese mice by suppressing the expressions of genes related to adipogenesis and lipogenesis activity. Therefore, SPE could be developed as a potential therapy for reduction of body weight and antiobesity intervention.

Aglycone Isoflavones and Exopolysaccharides Produced by Lactobacillus acidophilus in Fermented Soybean Paste.

Bioconversion of aglycone-formed isoflavones from glycoside-formed isoflavones by commercial lactic acid bacteria in fermented soybean paste was evaluated. Enterococcus faecium KCTC 13410 showed the most resistant capacity and Lactobacillus acidophilus KCTC 3925 had a sensitive susceptibility at a high NaCl concentration (13.2%) in fermented soybean paste. Among the 5 strains tested, Lac. acidophilus KCTC 3925 showed the highest relative ratio of aglycone-formed isoflavones to total isoflavones in fermented soybean paste. Production of exopolysaccarides (EPS) by lactic acid bacteria was compared using de Man, Rogosa, and Sharpe medium containing 1% sucrose at 37°C for 48 h. Among the 5 lactic acid bacteria, Lac. acidophilus KCTC 3925 and Lactobacillus rhamnosus KCTC 3929 were investigated to produce EPS. Based on the results concerning growing susceptibility and conversion of aglycone-formed isoflavones/EPS production, it is anticipated that Lac. acidophilus KCTC 3925 may be used for preparation of Cheonggukjang, which contains relative low NaCl content.

Eating Habits and Food Preferences of Elementary School Students in Urban and Suburban Areas of Daejeon.

This study investigated the dietary habits and food preferences of elementary school students. The survey was conducted by means of a questionnaire distributed to 4th and 5th grade elementary school students (400 boys and 400 girls) in urban and suburban areas of Daejeon. The results of this study were as follows: male students in urban areas ate breakfast, unbalanced diets, and dairy products more frequently than male students in suburban areas (p < 0.05). Female students in urban areas ate dairy products (p < 0.01) and fruits (p < 0.001) more frequently than female students in suburban areas. Students had the high preferences for boiled rice and noodles with black bean sauce, beef rib soup, steamed beef rib, steamed egg, beef boiled in soy sauce, egg roll, bulgogi, pork cutlet, deep-fried pork covered with sweet and sour starchy sauce, and honeyed juice mixed with fruit as a punch. All students preferred kimchi, although students in the suburban areas preferred kimchi-fried rice (p < 0.05), and those in the urban areas preferred bean-paste soup (p < 0.01). Students in suburban areas showed a greater preference for seasoned bean sprouts and Altari kimchi. All of the students preferred fruits, rice cake made with glutinous rice, and pizza among other foods. Overall, there were distinct differences in the eating habits and food preferences of elementary school students according to the place of residence.

Analysis of six elements (Ca, Mg, Fe, Zn, Cu, and Mn) in several wild vegetables and evaluation of their intakes based on Korea National Health and Nutrition Examination Survey 2010-2011.

Wild vegetables, those edible among naturally grown vegetables, have been reported to contain many bioactive substances, dietary fibers, vitamins, and minerals. The purpose of this study is to examine the six elements of the wild vegetables frequently consumed by Koreans and assess the element intakes through them. Contents of six kinds of elements (Ca, Mg, Fe, Zn, Cu, and Mn) in 11 wild vegetables were analyzed by inductively coupled plasma optical emission spectroscopy. Using these analysis data, the 6-element intakes from the wild vegetables were evaluated in healthy Korean adults aged 19-64 years from the Korea National Health and Nutrition Examination Survey (2010-2011). Sedum and shepherd's purse contained over 100 mg of Ca in 100 g of their edible portion. The Mg content per 100 g of the 11 wild vegetables ranged from 12.1 mg to 43.4 mg. The wild vegetable with the highest mineral content per 100 g was sedum for Ca, spinach for Mg, shepherd's purse for Fe, spinach for Zn, bracken for Cu, and fragrant edible wild aster for Mn. The element intakes from the 11 wild vegetables compared with dietary reference intakes in the healthy Koreans were 1.0 % for Ca, 2.1 % for Mg, 5.3 % for Fe, 1.4 % for Zn, 0.3 % for Cu, and 1.8 % for Mn. Considering the low intake ratio (1.2 %) of the wild vegetable to total food intake, wild vegetables may contribute to some element intakes. Our results show the nutritional value of the wild vegetables in the aspect of mineral nutrition; however, further research is needed to evaluate the bioavailability of various elements in wild vegetables.

High-resolution antibody dynamics of vaccine-induced immune responses.

The adaptive immune system confers protection by generating a diverse repertoire of antibody receptors that are rapidly expanded and contracted in response to specific targets. Next-generation DNA sequencing now provides the opportunity to survey this complex and vast repertoire. In the present work, we describe a set of tools for the analysis of antibody repertoires and their application to elucidating the dynamics of the response to viral vaccination in human volunteers. By analyzing data from 38 separate blood samples across 2 y, we found that the use of the germ-line library of V and J segments is conserved between individuals over time. Surprisingly, there appeared to be no correlation between the use level of a particular VJ combination and degree of expansion. We found the antibody RNA repertoire in each volunteer to be highly dynamic, with each individual displaying qualitatively different response dynamics. By using combinatorial phage display, we screened selected VH genes paired with their corresponding VL library for affinity against the vaccine antigens. Altogether, this work presents an additional set of tools for profiling the human antibody repertoire and demonstrates characterization of the fast repertoire dynamics through time in multiple individuals responding to an immune challenge.

On the design of clone-based haplotyping.

BACKGROUND: Haplotypes are important for assessing genealogy and disease susceptibility of individual genomes,but are difficult to obtain with routine sequencing approaches. Experimental haplotype reconstruction based on assembling fragments of individual chromosomes is promising, but with variable yields due to incompletely understood parameter choices. RESULTS: We parameterize the clone-based haplotyping problem in order to provide theoretical and empirical assessments of the impact of different parameters on haplotype assembly. We confirm the intuition that long clones help link together heterozygous variants and thus improve haplotype length. Furthermore, given the length of the clones, we address how to choose the other parameters, including number of pools, clone coverage and sequencing coverage, so as to maximize haplotype length. We model the problem theoretically and show empirically the benefits of using larger clones with moderate number of pools and sequencing coverage. In particular, using 140 kb BAC clones, we construct haplotypes for a personal genome and assemble haplotypes with N50 values greater than 2.6 Mb. These assembled haplotypes are longer and at least as accurate as haplotypes of existing clone-based strategies, whether in vivo or in vitro. CONCLUSIONS: Our results provide practical guidelines for the development and design of clone-based methods to achieve long range, high-resolution and accurate haplotypes.

Anticancer, antiobesity, and anti-inflammatory activity of Artemisia species in vitro.

OBJECTIVE: To investigate the anticancer, anti-inflammatory, and antiobesity activity of methanol extracts of eight distinct species: Artemisia Stolonifera (AST), Artemisia Selengensis (ASE), Artemisia Japonica, Artemisia Montana, Artemisia Capillaris (ACA), Artemisia Sylvatica (ASY), Artemisia Keiskeana (AKE), and Artemisia Scoparia (ASC) in vitro. METHODS: Antiproliferative activity was investigated in human breast cancer estrogen receptor-a positive T47D and negative HS578T cell lines exposed to the extracts at various concentrations (5-200 mg/ mL) for 24, 48, and 72 h. For evaluating the anti-inflammatory activity of the extracts, inhibition of nitrite synthesis was investigated in lipopolysaccharide (LPS)-stimulated cultures of macrophages cells exposed to 10, 50, 100, and 200 mg/mL for 24 h. The antiobesity activity of the extracts was determined as triglyceride content and by a lipolysis assay in differentiated 3T3-L1 cells exposed to the extracts for 72 h at the same concentrations described above. RESULTS: All extracts showed similar antiproliferative activity in a dose- and time-dependent manner in HS578T cells. Although extracts at lower concentrations and shorter times stimulated growth of T47D cells, the antiproliferative effects of the extracts on T47D cells at higher concentrations (> 100 mg/ mL) for 72 h were significantly greater than those of HS578T cells. In case of anti-inflammatory activity, some extracts (AST, ASE, ACA, and AKE) significantly reduced nitric oxide production at higher concentrations in the presence of LPS compared with that in control cells. Antiobesity activity was showed with reducing lipid accumulation significantly (> 50%) at concentrations above 100 mg/mL in most extracts (except AST and ACA). Additionally, AKE and ASC increased lipolysis by 11%-24% compared with that in the control. CONCLUSION: Artemisia spp. demonstrates potential as bioactive food supplements.

Barcoding cells using cell-surface programmable DNA-binding domains.

We report an approach to barcode cells through cell-surface expression of programmable zinc-finger DNA-binding domains (surface zinc fingers, sZFs). We show that sZFs enable sequence-specific labeling of living cells by dsDNA, and we develop a sequential labeling approach to image more than three cell types in mixed populations using three fluorophores. We demonstrate the versatility of sZFs through applications in which they serve as surrogate reporters, function as selective cell capture reagents and facilitate targeted cellular delivery of viruses.

Quality characteristics and ginsenosides composition of ginseng-yakju according to the particle size of ginseng powder.

The aim of this study was to develop rice wine (Yakju) containing various amounts and particle sizes of ginseng powder and to analyze the physicochemical characteristics and content of ginsenosides in ginseng-Yakju. Soluble solid content, pH, ethanol concentration, acidity, amino acid content, and evaluation of preference showed no difference between four kinds of Yakju groups, regardless of ginseng supplementation and particle size of the ginseng powder. During fermentation of Yakju containing ginseng, the contents of ginsenosides Rb1, Rb2, Rb3, and Rc were decreased. Otherwise, the content of ginsenoside Rh1 was increased highly by brewing microorganisms in Yakju. Recovery ratios of ginsenosides in ginseng-Yakju were approximately 25.4% (coarse ginseng power) and 23.8% (fine ginseng powder), which were superior to the recovery ratio of ginsenosides in Yakju containing ginseng slices (5%).

Accurate whole-genome sequencing and haplotyping from 10 to 20 human cells.

Recent advances in whole-genome sequencing have brought the vision of personal genomics and genomic medicine closer to reality. However, current methods lack clinical accuracy and the ability to describe the context (haplotypes) in which genome variants co-occur in a cost-effective manner. Here we describe a low-cost DNA sequencing and haplotyping process, long fragment read (LFR) technology, which is similar to sequencing long single DNA molecules without cloning or separation of metaphase chromosomes. In this study, ten LFR libraries were made using only ∼100 picograms of human DNA per sample. Up to 97% of the heterozygous single nucleotide variants were assembled into long haplotype contigs. Removal of false positive single nucleotide variants not phased by multiple LFR haplotypes resulted in a final genome error rate of 1 in 10 megabases. Cost-effective and accurate genome sequencing and haplotyping from 10-20 human cells, as demonstrated here, will enable comprehensive genetic studies and diverse clinical applications.

A public resource facilitating clinical use of genomes.

Rapid advances in DNA sequencing promise to enable new diagnostics and individualized therapies. Achieving personalized medicine, however, will require extensive research on highly reidentifiable, integrated datasets of genomic and health information. To assist with this, participants in the Personal Genome Project choose to forgo privacy via our institutional review board- approved "open consent" process. The contribution of public data and samples facilitates both scientific discovery and standardization of methods. We present our findings after enrollment of more than 1,800 participants, including whole-genome sequencing of 10 pilot participant genomes (the PGP-10). We introduce the Genome-Environment-Trait Evidence (GET-Evidence) system. This tool automatically processes genomes and prioritizes both published and novel variants for interpretation. In the process of reviewing the presumed healthy PGP-10 genomes, we find numerous literature references implying serious disease. Although it is sometimes impossible to rule out a late-onset effect, stringent evidence requirements can address the high rate of incidental findings. To that end we develop a peer production system for recording and organizing variant evaluations according to standard evidence guidelines, creating a public forum for reaching consensus on interpretation of clinically relevant variants. Genome analysis becomes a two-step process: using a prioritized list to record variant evaluations, then automatically sorting reviewed variants using these annotations. Genome data, health and trait information, participant samples, and variant interpretations are all shared in the public domain-we invite others to review our results using our participant samples and contribute to our interpretations. We offer our public resource and methods to further personalized medical research.

Anti-gastric actions of eugenol and cinnamic acid isolated from Cinnamomi Ramulus.

We investigated the evidence of gastric protection for ulcer and gastritis by Cinnamomi Ramulus (Cinnamomum cassia Blume, Geiji, CR) extract and its several constituents. CR ethanolic extract showed the potent antioxidant activity and cytotoxicity of Helicobacter pylori (H. pylori) and acid-neutralizing capacity. Especially, eugenol exerted a significant antioxidant activity and inhibited the colonization of H. pylori. In vivo test, eugenol and cinnamic acid significantly inhibited HCl/ethanol-induced gastric lesions and increased the mucus content though they didn't inhibit gastric secretion effectively. Taken together, eugenol and cinnamic acid, which were isolated from CR, exhibited the antioxidant activity in vitro and protective effect against gastric damage in vivo through stimulation of mucus secretion and so on. It suggested that they are useful as the neutraceuticals for gastritis.

Somatic coding mutations in human induced pluripotent stem cells.

Defined transcription factors can induce epigenetic reprogramming of adult mammalian cells into induced pluripotent stem cells. Although DNA factors are integrated during some reprogramming methods, it is unknown whether the genome remains unchanged at the single nucleotide level. Here we show that 22 human induced pluripotent stem (hiPS) cell lines reprogrammed using five different methods each contained an average of five protein-coding point mutations in the regions sampled (an estimated six protein-coding point mutations per exome). The majority of these mutations were non-synonymous, nonsense or splice variants, and were enriched in genes mutated or having causative effects in cancers. At least half of these reprogramming-associated mutations pre-existed in fibroblast progenitors at low frequencies, whereas the rest occurred during or after reprogramming. Thus, hiPS cells acquire genetic modifications in addition to epigenetic modifications. Extensive genetic screening should become a standard procedure to ensure hiPS cell safety before clinical use.

Generation of functional human hepatic endoderm from human induced pluripotent stem cells.

UNLABELLED: With the advent of induced pluripotent stem cell (iPSC) technology, it is now feasible to generate iPSCs with a defined genotype or disease state. When coupled with direct differentiation to a defined lineage, such as hepatic endoderm (HE), iPSCs would revolutionize the way we study human liver biology and generate efficient "off the shelf" models of human liver disease. Here, we show the "proof of concept" that iPSC lines representing both male and female sexes and two ethnic origins can be differentiated to HE at efficiencies of between 70%-90%, using a method mimicking physiological relevant condition. The iPSC-derived HE exhibited hepatic morphology and expressed the hepatic markers albumin and E-cadherin, as assessed by immunohistochemistry. They also expressed alpha-fetoprotein, hepatocyte nuclear factor-4a, and a metabolic marker, cytochrome P450 7A1 (Cyp7A1), demonstrating a definitive endodermal lineage differentiation. Furthermore, iPSC-derived hepatocytes produced and secreted the plasma proteins, fibrinogen, fibronectin, transthyretin, and alpha-fetoprotein, an essential feature for functional HE. Additionally iPSC-derived HE supported both CYP1A2 and CYP3A4 metabolism, which is essential for drug and toxicology testing. CONCLUSION: This work is first to demonstrate the efficient generation of hepatic endodermal lineage from human iPSCs that exhibits key attributes of hepatocytes, and the potential application of iPSC-derived HE in studying human liver biology. In particular, iPSCs from individuals representing highly polymorphic variants in metabolic genes and different ethnic groups will provide pharmaceutical development and toxicology studies a unique opportunity to revolutionize predictive drug toxicology assays and allow the creation of in vitro hepatic disease models.

Evaluation of antioxidant and inhibitory activities for different subclasses flavonoids on enzymes for rheumatoid arthritis.

Antioxidant activities of flavonoids were decreased in the order of flavonols > flavanones > flavones. Inhibitory intensities for hyaluronidase and collagenase reaction differed clearly according to flavonoid subclasses. Kaempferol, quercetin, myricetin, and rutin in flavonols inhibited hyaluronidase reaction specifically, while apigenin, luteolin, baicalin, and baicalein in flavones showed specific inhibition to collagenase reaction. In addition, the flavonoids, except baicalin and catechin, inhibited potently LPS-induced nitrite production in a dose-dependent manner, which might be mainly due to the suppression of inducible nitric oxide (NO) synthase. Quercetin and luteolin showed the strongest inhibitory activities on 15-lipoxygenase (LOX), and quercetin showed relatively potent inhibition on cyclooxygenase-1 (COX-1) reaction. Otherwise, all tested flavonoids possessed the inhibitory activity to COX-2 reaction, and especially luteolin, kaempferol, hesperetin, and naringin showed relatively the potent inhibition on COX-2 reaction. This report elucidated the anti-inflammatory activities, such as the antioxidant property, inhibition of NO production, and inhibition of inflammatory enzymes (hyaluronidase, collagenase, LOX, and COXs) of several subclass flavonoids.

A robust approach to identifying tissue-specific gene expression regulatory variants using personalized human induced pluripotent stem cells.

Normal variation in gene expression due to regulatory polymorphisms is often masked by biological and experimental noise. In addition, some regulatory polymorphisms may become apparent only in specific tissues. We derived human induced pluripotent stem (iPS) cells from adult skin primary fibroblasts and attempted to detect tissue-specific cis-regulatory variants using in vitro cell differentiation. We used padlock probes and high-throughput sequencing for digital RNA allelotyping and measured allele-specific gene expression in primary fibroblasts, lymphoblastoid cells, iPS cells, and their differentiated derivatives. We show that allele-specific expression is both cell type and genotype-dependent, but the majority of detectable allele-specific expression loci remains consistent despite large changes in the cell type or the experimental condition following iPS reprogramming, except on the X-chromosome. We show that our approach to mapping cis-regulatory variants reduces in vitro experimental noise and reveals additional tissue-specific variants using skin-derived human iPS cells.