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2. Novel scoring system and algorithm for classifying chronic rhinosinusitis: the JESREC Study

Author

Tokunaga, T., Sakashita, M., Haruna, T., Asaka, D., Takeno, S., Ikeda, H., Nakayama, T., Seki, N., Ito, S., Murata, J., Sakuma, Y., Yoshida, N., Terada, T., Morikura, I., Sakaida, H., Kondo, K., Teraguchi, K., Okano, M., Otori, N., Yoshikawa, M., Hirakawa, K., Haruna, S., Himi, T., Ikeda, K., Ishitoya, J., Iino, Y., Kawata, R., Kawauchi, H., Kobayashi, M., Yamasoba, T., Miwa, T., Urashima, M., Tamari, M., Noguchi, E., Ninomiya, T., Imoto, Y., Morikawa, T., Tomita, K., Takabayashi, T., and Fujieda, S.

Published
2015
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5. GLCCI1 variant accelerates pulmonary function decline in patients with asthma receiving inhaled corticosteroids

Author

Izuhara, Y., Matsumoto, H., Kanemitsu, Y., Izuhara, K., Tohda, Y., Horiguchi, T., Kita, H., Kuwabara, K., Tomii, K., Otsuka, K., Fujimura, M., Ohkura, N., Tomita, K., Yokoyama, A., Ohnishi, H., Nakano, Y., Oguma, T., Hozawa, S., Nagasaki, T., Ito, I., Inoue, H., Tajiri, T., Iwata, T., Ono, J., Ohta, S., Tamari, M., Hirota, T., Yokoyama, T., Niimi, A., and Mishima, M.

Published
2014
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6. 106 IL-33 signaling in sensory neurons promotes dry skin itch

Author

Trier, A.M., primary, Mack, M.R., additional, Guo, J., additional, Tamari, M., additional, Fredman, A., additional, Oetjen, L.K., additional, Feng, J., additional, Gereau, R.W., additional, Davidson, S., additional, Hu, H., additional, Liu, Q., additional, and Kim, B.S., additional

Published
2021
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11. ORMDL3/GSDMB Genotype as a Risk Factor for Early-Onset Adult Asthma Is Linked to Total Serum IgE Levels but Not to Atopy

Author

Kitazawa, H., primary, Masuko, H., additional, Shigemasa, R., additional, Hyodo, K., additional, Kanazawa, J., additional, Yamada, H., additional, Yatagai, Y., additional, Iijima, H., additional, Naito, T., additional, Saito, T., additional, Konno, S., additional, Hirota, T., additional, Tamari, M., additional, Sakamoto, T., additional, and Hizawa, N., additional

Published
2020
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17. Induction of human regulatory innate lymphoid cells from group 2 innate lymphoid cells by retinoic acid

Author

Morita, H, Kubo, Terufumi, Ruckert, B, Ravindran, Avinash, Soyka, M B, Rinaldi, A O, Sugita, Kazunari, Wawrzyniak, Marcin; https://orcid.org/0000-0002-6911-8010, Wawrzyniak, P, Motomura, Kenichiro, Tamari, M, Orimo, K, Okada, N, Arae, Ken, Saito, Kazuki, Altunbulakli, Can, Castro-Giner, Francesc; https://orcid.org/0000-0001-6111-0754, Tan, Ge; https://orcid.org/0000-0003-0026-8739, Neumann, A, Sudo, Katsuko, O'Mahony, L; https://orcid.org/0000-0003-4705-3583, Honda, K, Nakae, Susumu, Saito, H, Mjösberg, J, Nilsson, Gunnar, Matsumoto, Kenji, Akdis, Mübeccel; https://orcid.org/0000-0003-0554-9943, Akdis, Cezmi A; https://orcid.org/0000-0001-8020-019X, Morita, H, Kubo, Terufumi, Ruckert, B, Ravindran, Avinash, Soyka, M B, Rinaldi, A O, Sugita, Kazunari, Wawrzyniak, Marcin; https://orcid.org/0000-0002-6911-8010, Wawrzyniak, P, Motomura, Kenichiro, Tamari, M, Orimo, K, Okada, N, Arae, Ken, Saito, Kazuki, Altunbulakli, Can, Castro-Giner, Francesc; https://orcid.org/0000-0001-6111-0754, Tan, Ge; https://orcid.org/0000-0003-0026-8739, Neumann, A, Sudo, Katsuko, O'Mahony, L; https://orcid.org/0000-0003-4705-3583, Honda, K, Nakae, Susumu, Saito, H, Mjösberg, J, Nilsson, Gunnar, Matsumoto, Kenji, Akdis, Mübeccel; https://orcid.org/0000-0003-0554-9943, and Akdis, Cezmi A; https://orcid.org/0000-0001-8020-019X

Abstract

BACKGROUND: Group 2 innate lymphoid cells (ILC2s) play critical roles in induction and exacerbation of allergic airway inflammation. Thus, clarification of the mechanisms that underlie the regulation of ILC2 activation has received significant attention. Although ILCs are divided into three major subsets that mirror helper effector T-cell subsets, counterpart subsets of regulatory T (Treg) cells have not been well characterized. OBJECTIVE: We sought to determine the factors that induce regulatory ILCs (ILCregs). METHODS: IL-10+ ILCregs induced from ILC2s by retinoic acid (RA) were analyzed using RNA-sequencing and flow cytometry. ILCregs were evaluated in human nasal tissues from healthy individuals and patients with chronic rhinosinusitis with nasal polyp (CRSwNP), and in lung tissues from house dust mite (HDM)- or saline-treated mice. RESULTS: RA induced IL-10 secretion by human ILC2s, but not type-2 cytokines. IL-10+ ILCregs, converted from ILC2s by RA stimulation, expressed a Treg-like signature with the expression of IL-10, CTLA-4 and CD25, with down regulated effector type 2-related markers such as CRTH-2 and ST2, and suppressed activation of CD4+ T cells and ILC2s. ILCregs were rarely detected in human nasal tissue from healthy individuals or lung tissues from saline-treated mice, but were increased in nasal tissues from patients with CRSwNP and in lung tissues from HDM-treated mice. Enzymes for RA synthesis were up-regulated in airway epithelial cells during type-2 inflammation in vivo and by IL-13 in vitro. CONCLUSION: We have identified a unique immune regulatory and anti-inflammatory pathway by which RA converts ILC2s to ILCregs. Interactions between airway epithelial cells and ILC2s play an important roles in the generation of ILCregs.

Published
2019

20. A cis-eQTL Allele Lowering Gene Expression of CHL3L1 Is Associated with Late-Onset Adult Asthma in Japanese

Author

Shigemasa, R., primary, Kanazawa, J., additional, Kitazawa, H., additional, Masuko, H., additional, Hyodo, K., additional, Yatagai, Y., additional, Sakamoto, T., additional, Kaneko, Y., additional, Iijima, H., additional, Naito, T., additional, Saito, T., additional, Noguchi, E., additional, Konno, S., additional, Nishimura, M., additional, Hirota, T., additional, Tamari, M., additional, and Hizawa, N., additional

Published
2019
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25. Trans-ethnic meta-analysis of white blood cell phenotypes

Author

Keller, Margaux F, Reiner, Alexander P, Okada, Yukinori, van Rooij, Frank J. A, Johnson, Andrew D, Chen, Ming Huei, Smith, Albert V, Morris, Andrew P, Tanaka, Toshiko, Ferrucci, Luigi, Zonderman, Alan B, Lettre, Guillaume, Harris, Tamara, Garcia, Melissa, Bandinelli, Stefania, Qayyum, Rehan, Yanek, Lisa R, Becker, Diane M, Becker, Lewis C, Kooperberg, Charles, Keating, Brendan, Reis, Jared, Tang, Hua, Boerwinkle, Eric, Kamatani, Yoichiro, Matsuda, Koichi, Kamatani, Naoyuki, Nakamura, Yusuke, Kubo, Michiaki, Liu, Simin, Dehghan, Abbas, Felix, Janine F, Hofman, Albert, Uitterlinden, André G, van Duijn, Cornelia M, Franco, Oscar H, Longo, Dan L, Singleton, Andrew B, Psaty, Bruce M, Evans, Michelle K, Cupples, L. Adrienne, Rotter, Jerome I, O'Donnell, Christopher J, Takahashi, Atsushi, Wilson, James G, Ganesh, Santhi K, Nalls, Mike A, Arepalli, S, Bandinelli, S, Biffi, A, Bis, Jc, Boerwinkle, E, Chakravarti, A, Chen, Mh, Chong, S, Coresh, J, Couper, Dj, Cupples, L, Dehghan, A, Do'Ring, A, Eiriksdottir, G, Felix, Jf, Ferrucci, L, Folsom, Ar, Fox, Cs, Frayling, Tm, Ganesh, Sk, Garcia, M, Garner, Sf, Gasparini, Paolo, Gieger, C, Glazer, Nl, Gouskova, Na, Greinacher, A, Gudnason, V, Harris, Tb, Hernandez, Dg, Hofman, A, Illig, T, Kamatani, Y, Kamatani, N, Kubo, M, Kuhnel, B, Lagou, V, Lettre, G, Levi, D, Lin, J, Liu, Y, Longo, Dl, Lumley, T, Mangino, M, Matsuda, K, Meisinger, C, Melzer, D, Menzel, S, Moore, M, Nakamura, Y, Nalls, Ma, Nauck, M, O'Donnell, Cj, Okada, Y, Oostra, Ba, Ouwehand, Wh, Patel, Kv, Pirastu, Nicola, Pistis, Giorgio, Prokisch, H, Prokopenko, I, Psaty, Bm, Reiner, Ap, Rendon, A, Sambrook, J, Singleton, Ab, Smith, Av, Soranzo, N, Spector, Td, Stephens, J, Stumvoll, M, Takahashi, A, Tanaka, T, Taylor, K, Teumer, A, Thein, Sl, To'Njes, A, Toniolo, D, Tsunoda, T, Uitterlinden, Ag, van Duijn CM, van Rooij FJ, Vo'Lker, U, Vo'Lzke, H, Wichmann, H., Wiggins, Kl, Wilson, Jg, Witteman, Jc, Wood, Ar, Yamamoto, K, Yang, Q, Zakai, Na, Austin, Ma, Becker, Dm, Britton, A, Chen, Z, Couper, D, Curb, J, Dean, E, Eaton, Cb, Evans, Mk, Fornage, M, Grant, Sf, Hernandez, D, Kamatini, N, Keating, Bj, Lacroix, A, Lange, La, Liu, S, Lohman, K, Mathias, R, Meng, Y, Mohler ER 3rd, Musani, S, Palmer, Cd, Papanicolaou, Gj, Snively, Bm, Tang, H, Taylor HA Jr, Thomson, C, Yanek, Lr, Yang, L, Ziv, E, Zonderman, Ab, Higasa, K, Hirota, T, Hosono, N, Kumasaka, N, Ohmiya, H, Tamari, M, Yamaguchi Kabata, Y, Yamamoto, K., Epidemiology, Medical Informatics, Urology, Erasmus MC other, Internal Medicine, Keller, Margaux F, Reiner, Alexander P, Okada, Yukinori, van Rooij, Frank J. A, Johnson, Andrew D, Chen, Ming Huei, Smith, Albert V, Morris, Andrew P, Tanaka, Toshiko, Ferrucci, Luigi, Zonderman, Alan B, Lettre, Guillaume, Harris, Tamara, Garcia, Melissa, Bandinelli, Stefania, Qayyum, Rehan, Yanek, Lisa R, Becker, Diane M, Becker, Lewis C, Kooperberg, Charle, Keating, Brendan, Reis, Jared, Tang, Hua, Boerwinkle, Eric, Kamatani, Yoichiro, Matsuda, Koichi, Kamatani, Naoyuki, Nakamura, Yusuke, Kubo, Michiaki, Liu, Simin, Dehghan, Abba, Felix, Janine F, Hofman, Albert, Uitterlinden, André G, van Duijn, Cornelia M, Franco, Oscar H, Longo, Dan L, Singleton, Andrew B, Psaty, Bruce M, Evans, Michelle K, Cupples, L. Adrienne, Rotter, Jerome I, O'Donnell, Christopher J, Takahashi, Atsushi, Wilson, James G, Ganesh, Santhi K, Nalls, Mike A, Arepalli, S, Bandinelli, S, Biffi, A, Bis, Jc, Boerwinkle, E, Chakravarti, A, Chen, Mh, Chong, S, Coresh, J, Couper, Dj, Cupples, L, Dehghan, A, Do'Ring, A, Eiriksdottir, G, Felix, Jf, Ferrucci, L, Folsom, Ar, Fox, C, Frayling, Tm, Ganesh, Sk, Garcia, M, Garner, Sf, Gasparini, Paolo, Gieger, C, Glazer, Nl, Gouskova, Na, Greinacher, A, Gudnason, V, Harris, Tb, Hernandez, Dg, Hofman, A, Illig, T, Kamatani, Y, Kamatani, N, Kubo, M, Kuhnel, B, Lagou, V, Lettre, G, Levi, D, Lin, J, Liu, Y, Longo, Dl, Lumley, T, Mangino, M, Matsuda, K, Meisinger, C, Melzer, D, Menzel, S, Moore, M, Nakamura, Y, Nalls, Ma, Nauck, M, O'Donnell, Cj, Okada, Y, Oostra, Ba, Ouwehand, Wh, Patel, Kv, Pirastu, Nicola, Pistis, Giorgio, Prokisch, H, Prokopenko, I, Psaty, Bm, Reiner, Ap, Rendon, A, Sambrook, J, Singleton, Ab, Smith, Av, Soranzo, N, Spector, Td, Stephens, J, Stumvoll, M, Takahashi, A, Tanaka, T, Taylor, K, Teumer, A, Thein, Sl, To'Njes, A, Toniolo, D, Tsunoda, T, Uitterlinden, Ag, van Duijn, Cm, van Rooij, Fj, Vo'Lker, U, Vo'Lzke, H, Wichmann, H., Wiggins, Kl, Wilson, Jg, Witteman, Jc, Wood, Ar, Yamamoto, K, Yang, Q, Zakai, Na, Austin, Ma, Becker, Dm, Britton, A, Chen, Z, Couper, D, Curb, J, Dean, E, Eaton, Cb, Evans, Mk, Fornage, M, Grant, Sf, Hernandez, D, Kamatini, N, Keating, Bj, Lacroix, A, Lange, La, Liu, S, Lohman, K, Mathias, R, Meng, Y, Mohler ER, 3rd, Musani, S, Palmer, Cd, Papanicolaou, Gj, Snively, Bm, Tang, H, Taylor HA, Jr, Thomson, C, Yanek, Lr, Yang, L, Ziv, E, Zonderman, Ab, Higasa, K, Hirota, T, Hosono, N, Kumasaka, N, Ohmiya, H, Tamari, M, Yamaguchi Kabata, Y, and Yamamoto, K.

Subjects
Linkage disequilibrium, Genotype, Quantitative Trait Loci, White blood cell count, Single-nucleotide polymorphism, Genome-wide association study, Quantitative trait locus, Biology, Polymorphism, Single Nucleotide, Linkage Disequilibrium, White People, white blood cell phenotypes, Leukocyte Count, SDG 3 - Good Health and Well-being, Asian People, Polymorphism (computer science), Genetics, Leukocytes, Humans, Allele, Molecular Biology, Genetics (clinical), White blood cell count, Trans-ethnic meta-analysis, white blood cell phenotypes, Genome, Human, Association Studies Articles, Bayes Theorem, General Medicine, Heritability, Black or African American, Phenotype, Trans-ethnic meta-analysis, Genome-Wide Association Study
Abstract

White blood cell (WBC) count is a common clinical measure used as a predictor of certain aspects of human health, including immunity and infection status. WBC count is also a complex trait that varies among individuals and ancestry groups. Differences in linkage disequilibrium structure and heterogeneity in allelic effects are expected to play a role in the associations observed between populations. Prior genome-wide association study (GWAS) meta-analyses have identified genomic loci associated with WBC and its subtypes, but much of the heritability of these phenotypes remains unexplained. Using GWAS summary statistics for over 50 000 individuals from three diverse populations (Japanese, African-American and European ancestry), a Bayesian model methodology was employed to account for heterogeneity between ancestry groups. This approach was used to perform a trans-ethnic meta-analysis of total WBC, neutrophil and monocyte counts. Ten previously known associations were replicated and six new loci were identified, including several regions harboring genes related to inflammation and immune cell function. Ninety-five percent credible interval regions were calculated to narrow the association signals and fine-map the putatively causal variants within loci. Finally, a conditional analysis was performed on the most significant SNPs identified by the trans-ethnic meta-analysis (MA), and nine secondary signals within loci previously associated with WBC or its subtypes were identified. This work illustrates the potential of trans-ethnic analysis and ascribes a critical role to multi-ethnic cohorts and consortia in exploring complex phenotypes with respect to variants that lie outside the European-biased GWAS pool.

Published
2014

31. Cover Image

Author

Sunadome, H., primary, Matsumoto, H., additional, Petrova, G., additional, Kanemitsu, Y., additional, Tohda, Y., additional, Horiguchi, T., additional, Kita, H., additional, Kuwabara, K., additional, Tomii, K., additional, Otsuka, K., additional, Fujimura, M., additional, Ohkura, N., additional, Tomita, K., additional, Yokoyama, A., additional, Ohnishi, H., additional, Nakano, Y., additional, Oguma, T., additional, Hozawa, S., additional, Nagasaki, T., additional, Ito, I., additional, Inoue, H., additional, Tajiri, T., additional, Iwata, T., additional, Izuhara, Y., additional, Ono, J., additional, Ohta, S., additional, Hirota, T., additional, Tamari, M., additional, Yokoyama, T., additional, Niimi, A., additional, Izuhara, K., additional, and Mishima, M., additional

Published
2017
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32. IL4Rα and ADAM33 as genetic markers in asthma exacerbations and type-2 inflammatory endotype

Author

Sunadome, H., primary, Matsumoto, H., additional, Petrova, G., additional, Kanemitsu, Y., additional, Tohda, Y., additional, Horiguchi, T., additional, Kita, H., additional, Kuwabara, K., additional, Tomii, K., additional, Otsuka, K., additional, Fujimura, M., additional, Ohkura, N., additional, Tomita, K., additional, Yokoyama, A., additional, Ohnishi, H., additional, Nakano, Y., additional, Oguma, T., additional, Hozawa, S., additional, Nagasaki, T., additional, Ito, I., additional, Inoue, H., additional, Tajiri, T., additional, Iwata, T., additional, Izuhara, Y., additional, Ono, J., additional, Ohta, S., additional, Hirota, T., additional, Tamari, M., additional, Yokoyama, T., additional, Niimi, A., additional, Izuhara, K., additional, and Mishima, M., additional

Published
2017
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33. Multi-ancestry genome-wide association study of 21,000 cases and 95,000 controls identifies new risk loci for atopic dermatitis

Author

Paternoster, L, Standl, M, Waage, J, Baurecht, H, Hotze, M, Strachan, DP, Curtin, JA, Bonnelykke, K, Tian, C, Takahashi, A, Esparza-Gordillo, J, Alves, AC, Thyssen, JP, den Dekker, HT, Ferreira, MA, Altmaier, E, Sleiman, PMA, Xiao, FL, Gonzalez, JR, Marenholz, I, Kalb, B, Pino-Yanes, M, Xu, C-J, Carstensen, L, Groen-Blokhuis, MM, Venturini, C, Pennell, CE, Barton, SJ, Levin, AM, Curjuric, I, Bustamante, M, Kreiner-Moller, E, Lockett, GA, Bacelis, J, Bunyavanich, S, Myers, RA, Matanovic, A, Kumar, A, Tung, JY, Hirota, T, Kubo, M, McArdle, WL, Henderson, AJ, Kemp, JP, Zheng, J, Smith, GD, Rueschendorf, F, Bauerfeind, A, Lee-Kirsch, MA, Arnold, A, Homuth, G, Schmidt, CO, Mangold, E, Cichon, S, Keil, T, Rodriguez, E, Peters, A, Franke, A, Lieb, W, Novak, N, Foelster-Holst, R, Horikoshi, M, Pekkanen, J, Sebert, S, Husemoen, LL, Grarup, N, De Jongste, JC, Rivadeneira, F, Hofman, A, Jaddoe, VWV, Pasmans, SGMA, Elbert, NJ, Uitterlinden, AG, Marks, GB, Thompson, PJ, Matheson, MC, Robertson, CF, Ried, JS, Li, J, Zuo, XB, Zheng, XD, Yin, XY, Sun, LD, McAleer, MA, O'Regan, GM, Fahy, CMR, Campbell, LE, Macek, M, Kurek, M, Hu, D, Eng, C, Postma, DS, Feenstra, B, Geller, F, Hottenga, JJ, Middeldorp, CM, Hysi, P, Bataille, V, Spector, T, Tiesler, CMT, Thiering, E, Pahukasahasram, B, Yang, JJ, Imboden, M, Huntsman, S, Vilor-Tejedor, N, Relton, CL, Myhre, R, Nystad, W, Custovic, A, Weiss, ST, Meyers, DA, Soederhaell, C, Melen, E, Ober, C, Raby, BA, Simpson, A, Jacobsson, B, Holloway, JW, Bisgaard, H, Sunyer, J, Probst-Hensch, NM, Williams, LK, Godfrey, KM, Wang, CA, Boomsma, DI, Melbye, M, Koppelman, GH, Jarvis, D, McLean, WHI, Irvine, AD, Zhang, XJ, Hakonarson, H, Gieger-, C, Burchard, EG, Martin, NG, Duijts, L, Linneberg, A, Jarvelin, M-R, Noethen, MM, Lau, S, Huebner, N, Lee, Y-A, Tamari, M, Hinds, DA, Glass, D, Brown, SJ, Heinrich, J, Evans, DM, Weidinger, S, AAGC, AAGC, and Epidemio, EGL

Abstract

Genetic association studies have identified 21 loci associated with atopic dermatitis risk predominantly in populations of European ancestry. To identify further susceptibility loci for this common, complex skin disease, we performed a meta-analysis of >15 million genetic variants in 21,399 cases and 95,464 controls from populations of European, African, Japanese and Latino ancestry, followed by replication in 32,059 cases and 228,628 controls from 18 studies. We identified ten new risk loci, bringing the total number of known atopic dermatitis risk loci to 31 (with new secondary signals at four of these loci). Notably, the new loci include candidate genes with roles in the regulation of innate host defenses and T cell function, underscoring the important contribution of (auto)immune mechanisms to atopic dermatitis pathogenesis.

Published
2015

34. Assessment of right ventricular size and function from cardiovascular magnetic resonance images using artificial intelligence

Author

Shuo Wang, Daksh Chauhan, Hena Patel, Alborz amir-Khalili, Isabel Ferreira da Silva, Alireza Sojoudi, Silke Friedrich, Amita Singh, Luis Landeras, Tamari Miller, Keith Ameyaw, Akhil Narang, Keigo Kawaji, Qiang Tang, Victor Mor-Avi, and Amit R. Patel

Subjects
Artificial intelligence, Deep learning, Right ventricular function, Right ventricular ejection fraction, Diseases of the circulatory (Cardiovascular) system, RC666-701
Abstract

Abstract Background Theoretically, artificial intelligence can provide an accurate automatic solution to measure right ventricular (RV) ejection fraction (RVEF) from cardiovascular magnetic resonance (CMR) images, despite the complex RV geometry. However, in our recent study, commercially available deep learning (DL) algorithms for RVEF quantification performed poorly in some patients. The current study was designed to test the hypothesis that quantification of RV function could be improved in these patients by using more diverse CMR datasets in addition to domain-specific quantitative performance evaluation metrics during the cross-validation phase of DL algorithm development. Methods We identified 100 patients from our prior study who had the largest differences between manually measured and automated RVEF values. Automated RVEF measurements were performed using the original version of the algorithm (DL1), an updated version (DL2) developed from a dataset that included a wider range of RV pathology and validated using multiple domain-specific quantitative performance evaluation metrics, and conventional methodology performed by a core laboratory (CORE). Each of the DL-RVEF approaches was compared against CORE-RVEF reference values using linear regression and Bland–Altman analyses. Additionally, RVEF values were classified into 3 categories: ≤ 35%, 35–50%, and ≥ 50%. Agreement between RVEF classifications made by the DL approaches and the CORE measurements was tested. Results CORE-RVEF and DL-RVEFs were obtained in all patients (feasibility of 100%). DL2-RVEF correlated with CORE-RVEF better than DL1-RVEF (r = 0.87 vs. r = 0.42), with narrower limits of agreement. As a result, DL2 algorithm also showed increasing accuracy from 0.53 to 0.80 for categorizing RV function. Conclusions The use of a new DL algorithm cross-validated on a dataset with a wide range of RV pathology using multiple domain-specific metrics resulted in a considerable improvement in the accuracy of automated RVEF measurements. This improvement was demonstrated in patients whose images were the most challenging and resulted in the largest RVEF errors. These findings underscore the critical importance of this strategy in the development of DL approaches for automated CMR measurements.

Published
2022
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41. Novel scoring system and algorithm for classifying chronic rhinosinusitis: the JESREC Study

Author

Tokunaga T., Sakashita M., Haruna T., Asaka D., Takeno S., Ikeda H., Nakayama T., Seki N., Ito S., Murata J., Sakuma Y., Yoshida N., Terada T., Morikura I., Sakaida H., Kondo K., Teraguchi K., Okano M., Otori N., Yoshikawa M., Hirakawa K., Haruna S., Himi T., Ikeda K., Ishitoya J., Iino Y., Kawata R., Kawauchi H., Kobayashi M., Yamasoba T., Miwa T., Urashima M., Tamari M., Noguchi E., Ninomiya T., Imoto Y., Morikawa T., Tomita K., Takabayashi T., Fujieda S., Tokunaga T., Sakashita M., Haruna T., Asaka D., Takeno S., Ikeda H., Nakayama T., Seki N., Ito S., Murata J., Sakuma Y., Yoshida N., Terada T., Morikura I., Sakaida H., Kondo K., Teraguchi K., Okano M., Otori N., Yoshikawa M., Hirakawa K., Haruna S., Himi T., Ikeda K., Ishitoya J., Iino Y., Kawata R., Kawauchi H., Kobayashi M., Yamasoba T., Miwa T., Urashima M., Tamari M., Noguchi E., Ninomiya T., Imoto Y., Morikawa T., Tomita K., Takabayashi T., and Fujieda S.

Published
2015

43. Chlorine-36 interlaboratory comparison - Can we harmonize 36Cl-data on a world-wide scale?

Author

Merchel, S., Bremser, W., Alfimov, V., Arnold, M., Aumaître, G., Benedetti, L., Bourlès, D. L., Caffee, M., Fifield, L. K., Finkel, R. C., Freeman, S. P. H. T., Martschini, M., Matsushi, Y., Rood, D. H., Sasa, K., Steier, P., Takahashi, T., Tamari, M., Tims, S. G., Tosaki, Y., Wilcken, K. M., and Xu, S.

Subjects
round-robin, accelerator mass spectrometry, quality assurance
Abstract

As a first step towards using world-wide a common 36Cl standard-type material for the normalization of 36Cl AMS results, we have initiated an interlaboratory comparison, but with differences in the execution of the project compared to other round-robin exercises: a) participants have given up anonymity to better optimize discussion and conclusions, b) preliminary results have been shown at various scientific meetings and workshops to discuss first trends and to increase the number of participants, c) participants had the possibility to repeat their AMS measurements and/or change measurement setups or data evaluation to improve individual data [e.g. 1]. We are aware and acknowledge that these later changes by some of the participants, which led to different overall data compared with the initial results, are not fully consistent with the idea of a normal proficiency test layout. However, these data changes were accepted to better meet the main objectives of the intercomparison: to identify and eliminate differences between AMS laboratories, thus, improving the 36Cl data quality world-wide as soon as possible. The evaluation of the final results of the eight participating AMS laboratories for three synthetic AgCl samples with 36Cl/Cl ratios at the 10-11 (SM-Cl-11), 10-12 (SM-Cl-12), and 10-13 (SM-Cl-13) level shows no difference in the sense of simple statistical significance [2]. However, more detailed statistical analyses indicate a certain interlaboratory bias and an under-estimation of uncertainties by some of the laboratories. The round-robin data demonstrate that 36Cl/Cl results from two individual AMS laboratories can differ by up to 17% (Fig. 1). Thus, the necessity for further work on harmonizing the 36Cl business on a world-wide scale and on improving the measurements is obvious. Fig. 1: Regression of normalized results for the three investigated samples in the order of ascending average. [1] V. Alfimov et al., Ion Beam Physics, ETH Zurich, Annual Report (2009) 13. [2] S. Merchel et al., Anal. Bioanal. Chem., submitted.

Published
2011

45. Analysis of the Delamination Process with Nitric Acid in Multilayer Composite Food Packaging

Author

Agnė Šleiniūtė, Gintaras Denafas, and Tamari Mumladze

Subjects
multilayer packaging waste, nitric acid, ultrasound, delamination, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999
Abstract

Multilayer packaging, commonly referred to as composite materials, is widely utilized in food storage, distribution, and consumption. The employment of plastic packaging, which consists of multiple layers of polymers, ink, paper, and metal, has elicited concerns regarding its detrimental impact on the environment. This article presents an in-depth study of the delamination process of multilayer plastic waste (MLPW) recycling, which is deemed as an effective solution for MLPW recycling. This study aimed to examine the effects of temperature, concentration, width, and ultrasound on the separation of layers in multilayer packaging. The results demonstrated that ultrasound is the most influential factor with nitric acid concentration ranking as the second most significant factor. The findings also disclosed considerable disparities among the time frames, and the impacts of various factors, such as temperature and concentration, lay the groundwork for further investigation into this process. The study underscores the importance of temperature and nitric acid concentration, which can inform the design of future experiments and the development of more efficient methods for layer separation.

Published
2023
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47. GLCCI1variant accelerates pulmonary function decline in patients with asthma receiving inhaled corticosteroids

Author

Izuhara, Y., primary, Matsumoto, H., additional, Kanemitsu, Y., additional, Izuhara, K., additional, Tohda, Y., additional, Horiguchi, T., additional, Kita, H., additional, Kuwabara, K., additional, Tomii, K., additional, Otsuka, K., additional, Fujimura, M., additional, Ohkura, N., additional, Tomita, K., additional, Yokoyama, A., additional, Ohnishi, H., additional, Nakano, Y., additional, Oguma, T., additional, Hozawa, S., additional, Nagasaki, T., additional, Ito, I., additional, Inoue, H., additional, Tajiri, T., additional, Iwata, T., additional, Ono, J., additional, Ohta, S., additional, Tamari, M., additional, Hirota, T., additional, Yokoyama, T., additional, Niimi, A., additional, and Mishima, M., additional

Published
2014
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48. Integration of Mouse and Human Genome-Wide Association Data Identifies KCNIP4 as an Asthma Gene

Author

Himes, BE, Sheppard, K, Berndt, A, Leme, AS, Myers, RA, Gignoux, CR, Levin, AM, Gauderman, WJ, Yang, JJ, Mathias, RA, Romieu, I, Torgerson, DG, Roth, LA, Huntsman, S, Eng, C, Klanderman, B, Ziniti, J, Senter-Sylvia, J, Szefler, SJ, Lemanske, RF, Zeiger, RS, Strunk, RC, Martinez, FD, Boushey, H, Chinchilli, VM, Israel, E, Mauger, D, Koppelman, GH, Postma, DS, Nieuwenhuis, MAE, Vonk, JM, Lima, JJ, Irvin, CG, Peters, SP, Kubo, M, Tamari, M, Nakamura, Y, Litonjua, AA, Tantisira, KG, Raby, BA, Bleecker, ER, Meyers, DA, London, SJ, Barnes, KC, Gilliland, FD, Williams, LK, Burchard, EG, Nicolae, DL, Ober, C, DeMeo, DL, Silverman, EK, Paigen, B, Churchill, G, Shapiro, SD, Weiss, ST, Himes, BE, Sheppard, K, Berndt, A, Leme, AS, Myers, RA, Gignoux, CR, Levin, AM, Gauderman, WJ, Yang, JJ, Mathias, RA, Romieu, I, Torgerson, DG, Roth, LA, Huntsman, S, Eng, C, Klanderman, B, Ziniti, J, Senter-Sylvia, J, Szefler, SJ, Lemanske, RF, Zeiger, RS, Strunk, RC, Martinez, FD, Boushey, H, Chinchilli, VM, Israel, E, Mauger, D, Koppelman, GH, Postma, DS, Nieuwenhuis, MAE, Vonk, JM, Lima, JJ, Irvin, CG, Peters, SP, Kubo, M, Tamari, M, Nakamura, Y, Litonjua, AA, Tantisira, KG, Raby, BA, Bleecker, ER, Meyers, DA, London, SJ, Barnes, KC, Gilliland, FD, Williams, LK, Burchard, EG, Nicolae, DL, Ober, C, DeMeo, DL, Silverman, EK, Paigen, B, Churchill, G, Shapiro, SD, and Weiss, ST

Abstract

Asthma is a common chronic respiratory disease characterized by airway hyperresponsiveness (AHR). The genetics of asthma have been widely studied in mouse and human, and homologous genomic regions have been associated with mouse AHR and human asthma-related phenotypes. Our goal was to identify asthma-related genes by integrating AHR associations in mouse with human genome-wide association study (GWAS) data. We used Efficient Mixed Model Association (EMMA) analysis to conduct a GWAS of baseline AHR measures from males and females of 31 mouse strains. Genes near or containing SNPs with EMMA p-values <0.001 were selected for further study in human GWAS. The results of the previously reported EVE consortium asthma GWAS meta-analysis consisting of 12,958 diverse North American subjects from 9 study centers were used to select a subset of homologous genes with evidence of association with asthma in humans. Following validation attempts in three human asthma GWAS (i.e., Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG) and two human AHR GWAS (i.e., SHARP, DAG), the Kv channel interacting protein 4 (KCNIP4) gene was identified as nominally associated with both asthma and AHR at a gene- and SNP-level. In EVE, the smallest KCNIP4 association was at rs6833065 (P-value 2.9e-04), while the strongest associations for Sepracor/LOCCS/LODO/Illumina, GABRIEL, DAG were 1.5e-03, 1.0e-03, 3.1e-03 at rs7664617, rs4697177, rs4696975, respectively. At a SNP level, the strongest association across all asthma GWAS was at rs4697177 (P-value 1.1e-04). The smallest P-values for association with AHR were 2.3e-03 at rs11947661 in SHARP and 2.1e-03 at rs402802 in DAG. Functional studies are required to validate the potential involvement of KCNIP4 in modulating asthma susceptibility and/or AHR. Our results suggest that a useful approach to identify genes associated with human asthma is to leverage mouse AHR association data. © 2013 Himes et al.

Published
2013

49. Morphological content and recyclability of separate collected packages: a case study for Kaunas, Lithuania

Author

Evelina Mickevičiūtė, Agnė Šleiniūtė, Inna Pitak, Tamari Mumladze, Anastasiia Sholokhova, and Gintaras Denafas

Subjects
packaging waste, plastics, paper, recycling, Ecology, QH540-549.5, Chemical engineering, TP155-156
Abstract

Packaging materials can arise from a wide range of sources and are commonly used for food, medicine, household appliances, and items to enclose or protect products during distribution, storage, sale, delivery, and use. The choice of material (paper, plastic, glass, wood, metal, multi-layer or other packaging) to be used depends on the type and properties of product, the purpose of packaging, and the price. The aim of the investigation is to analyse the morphological composition of packaging waste collected separately in Kaunas (Lithuanian) private households and to evaluate its recycling possibilities. The mixture of paper, plastic, and metal packaging waste was analyzed in the winter and spring (one time per month) in the waste management company JSC "Kauno švara".

Published
2021
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50. Identification of nine novel loci associated with white blood cell subtypes in a Japanese population

Author

Okada, Y. (Yukinori), Hirota, T. (Tomomitsu), Kamatani, Y. (Yoichiro), Takahashi, A. (Atsushi), Ohmiya, H. (Hiroko), Kumasaka, N. (Natsuhiko), Higasa, K. (Koichiro), Yamaguchi-Kabata, Y. (Yumi), Hosono, N. (Naoya), Nalls, M.A. (Michael), Chen, M-H. (Ming-Huei), Rooij, F.J.A. (Frank) van, Smith, A.V. (Albert Vernon), Tanaka, T. (Toshiko), Couper, D. (David), Zakai, N.A. (Neil), Ferrucci, L. (Luigi), Longo, D.L. (Dan), Hernandez, D.G. (Dena), Witteman, J.C.M. (Jacqueline), Harris, T.B. (Tamara), O'Donnell, C.J. (Christopher), Ganesh, S.K. (Santhi), Matsuda, K. (Koichi), Tsunoda, T. (Tatsuhiko), Kubo, M. (Michiaki), Nakamura, Y. (Yusuke), Tamari, M. (Mayumi), Yamamoto, K. (Kazuhiko), Okada, Y. (Yukinori), Hirota, T. (Tomomitsu), Kamatani, Y. (Yoichiro), Takahashi, A. (Atsushi), Ohmiya, H. (Hiroko), Kumasaka, N. (Natsuhiko), Higasa, K. (Koichiro), Yamaguchi-Kabata, Y. (Yumi), Hosono, N. (Naoya), Nalls, M.A. (Michael), Chen, M-H. (Ming-Huei), Rooij, F.J.A. (Frank) van, Smith, A.V. (Albert Vernon), Tanaka, T. (Toshiko), Couper, D. (David), Zakai, N.A. (Neil), Ferrucci, L. (Luigi), Longo, D.L. (Dan), Hernandez, D.G. (Dena), Witteman, J.C.M. (Jacqueline), Harris, T.B. (Tamara), O'Donnell, C.J. (Christopher), Ganesh, S.K. (Santhi), Matsuda, K. (Koichi), Tsunoda, T. (Tatsuhiko), Kubo, M. (Michiaki), Nakamura, Y. (Yusuke), Tamari, M. (Mayumi), and Yamamoto, K. (Kazuhiko)

Abstract

White blood cells (WBCs) mediate immune systems and consist of various subtypes with distinct roles. Elucidation of the mechanism that regulates the counts of the WBC subtypes would provide useful insights into both the etiology of the immune system and disease pathogenesis. In this study, we report results of genome-wide association studies (GWAS) and a replication study for the counts of the 5 main WBC subtypes (neutrophils, lymphocytes, monocytes, basophils, and eosinophils) using 14,792 Japanese subjects enrolled in the BioBank Japan Project. We identified 12 significantly associated loci that satisfied the genome-wide significance threshold of P<5.0×10-8, of which 9 loci were novel (the CDK6 locus for the neutrophil count; the ITG

Published
2011
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