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Journal articles on the topic 'Heterogeneity'

To see the other types of publications on this topic, follow the link: Heterogeneity.

Author: Grafiati

Published: 4 June 2021

Last updated: 7 July 2024

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1

MIMURA, Keiji, Susumu YUKAWA, Akira HIBINO, and Hiroshi NOMOTO. "Heterogeneity of MDA-rich LDL." Journal of Japan Atherosclerosis Society 18, no. 9-10 (1990): 793–802. http://dx.doi.org/10.5551/jat1973.18.9-10_793.

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2

EDWARDS, J. H. "Heterogeneity." Annals of the New York Academy of Sciences 615, no. 1 Tuberous Scle (April 1991): 344–53. http://dx.doi.org/10.1111/j.1749-6632.1991.tb37777.x.

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3

Tran, Hien Thu, and Enrico Santarelli. "Spatial heterogeneity, industry heterogeneity, and entrepreneurship." Annals of Regional Science 59, no. 1 (February 28, 2017): 69–100. http://dx.doi.org/10.1007/s00168-017-0819-4.

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4

Zlatohurska, M. A., and F. I. Tovkach. "Morphological heterogeneity of temperate erwiniophage 59." Mikrobiolohichnyi Zhurnal 78, no. 1 (January 30, 2016): 71–83. http://dx.doi.org/10.15407/microbiolj78.01.071.

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5

Ni, Xu Dong, Ji Hong Yu, and Xian An Li. "Effects of Speciality Heterogeneity, Education Heterogeneity and Work Experience Heterogeneity on Team Performance." Applied Mechanics and Materials 411-414 (September 2013): 2451–57. http://dx.doi.org/10.4028/www.scientific.net/amm.411-414.2451.

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This paper started with theories of team heterogeneity and team performance, according to questionnaire survey method, reviewed three dimensions of knowledge heterogeneity (speciality heterogeneity, education heterogeneity and work experience heterogeneity) and their effects on team performance. The result showed that speciality heterogeneity was positively related to task performance and contextual performance, while work experience heterogeneity was positively related to contextual performance significantly, but had no significant relationship with task performance. In addition, education heterogeneity had no significant relationship with task performance and contextual performance.

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6

Prat, A. "HER2 heterogeneity." Breast 56 (April 2021): S4. http://dx.doi.org/10.1016/s0960-9776(21)00050-3.

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7

Pe’er, Dana, Seishi Ogawa, Ofer Elhanani, Leeat Keren, Trudy G. Oliver, and David Wedge. "Tumor heterogeneity." Cancer Cell 39, no. 8 (August 2021): 1015–17. http://dx.doi.org/10.1016/j.ccell.2021.07.009.

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8

Lichtenberk, Frantisek. "Reconstructing Heterogeneity." Oceanic Linguistics 33, no. 1 (June 1994): 1. http://dx.doi.org/10.2307/3622999.

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9

DELLINGER, JAMES J. "Heterogeneity missing." Journal of Clinical Nursing 11, no. 5 (September 2002): 697. http://dx.doi.org/10.1046/j.1365-2702.2002.00664.x.

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10

Rowse, Tim. "Indigenous Heterogeneity." Australian Historical Studies 45, no. 3 (September 2, 2014): 297–310. http://dx.doi.org/10.1080/1031461x.2014.946523.

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11

Leone, Giuseppe, Augusto Agostini, Alberto DeCrescenzo, and Bruno Bizzi. "Platelet Heterogeneity." Scandinavian Journal of Haematology 23, no. 3 (April 24, 2009): 204–10. http://dx.doi.org/10.1111/j.1600-0609.1979.tb02692.x.

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12

Harrison, Charlotte. "Intratumour heterogeneity." Nature Reviews Drug Discovery 11, no. 5 (April 30, 2012): 354. http://dx.doi.org/10.1038/nrd3741.

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13

Eagger, Sarah A., and Richard J. Harvey. "Clinical Heterogeneity." Alzheimer Disease & Associated Disorders 9 (1995): 37. http://dx.doi.org/10.1097/00002093-199501002-00007.

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14

Olejnik, Stephen F. "Variance Heterogeneity." Journal of Experimental Education 56, no. 4 (July 1988): 193–97. http://dx.doi.org/10.1080/00220973.1988.10806487.

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15

Gordon, Siamon. "Macrophage Heterogeneity." Arteriosclerosis, Thrombosis, and Vascular Biology 32, no. 6 (June 2012): 1339–42. http://dx.doi.org/10.1161/atvbaha.111.238139.

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16

Katenkamp, Detlef. "Cellular Heterogeneity." Pathology - Research and Practice 183, no. 6 (November 1988): 698–705. http://dx.doi.org/10.1016/s0344-0338(88)80055-4.

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17

Mott, K. "Stomatal heterogeneity." Journal of Experimental Botany 49, no. 90001 (March 1, 1998): 407–17. http://dx.doi.org/10.1093/jexbot/49.suppl_1.407.

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18

Rogina, Blanka. "Biological Heterogeneity." Innovation in Aging 4, Supplement_1 (December 1, 2020): 854–55. http://dx.doi.org/10.1093/geroni/igaa057.3145.

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Abstract Studies of aging in invertebrates, mammalian animal models and humans have demonstrated increasing heterogeneity with aging in terms of varied facets of biological aging. In addition to growing heterogeneity, aging is also associated with qualitative and quantitative changes involving DNA methylation captured in epigenetic clocks of aging which seek to predict chronological and biological aging. Increased heterogeneity with aging is also evident in terms of posttranslational histone modification, gene expression, somatic clonal expansion, and increased degree of tissue mosaicism. Senescent cells accumulating with aging demonstrate significant heterogeneity. For example, while most studies targeting senescent cells have focused on cells expressing p16 (CDKN2A), not all p16-positive cells are senescent and not all senescent cells express p16. Further studies are needed to better define heterogeneity involving other hallmarks of aging and to also explore associations between heterogeneity involving these biological measures with clinical manifestations or outcomes.

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19

Haynes, Laura. "Immunological Heterogeneity." Innovation in Aging 4, Supplement_1 (December 1, 2020): 855. http://dx.doi.org/10.1093/geroni/igaa057.3146.

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Abstract Ease of access to circulating peripheral blood cells (PBMCs) can offer unique insights into human immune function, as well as responses to vaccination and infection. Nevertheless, PBMC heterogeneity has been under-appreciated since results obtained from mixed populations may reflect changes in subset abundance as opposed to true age-related changes involving a specific subset. Technological advances have allowed for the examination of age-related heterogeneity with regards to systemic cytokine levels, immune cell frequencies and chemokine receptor expression by peripheral lymphocytes. Furthermore, introduction of sex as a variable in the examination of human PBMCs adds additional dimorphism to the study of aging and immunity including differences in epigenetic modifications, levels of pro-inflammatory activity and adaptive immunity.

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20

Koumas, Laura, Anne E. King, Hilary O. D. Critchley, Rodney W. Kelly, and Richard P. Phipps. "Fibroblast Heterogeneity." American Journal of Pathology 159, no. 3 (September 2001): 925–35. http://dx.doi.org/10.1016/s0002-9440(10)61768-3.

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21

Wilkin, G. P., D. R. Marriott, and A. J. Cholewinski. "Astrocyte heterogeneity." Trends in Neurosciences 13, no. 2 (February 1990): 43–46. http://dx.doi.org/10.1016/0166-2236(90)90065-i.

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22

Heida, Annejet, Willemijn F. B. van der Does, Lianne N. van Staveren, Yannick J. H. J. Taverne, Maarten C. Roos-Serote, Ad J. J. C. Bogers, and Natasja M. S. de Groot. "Conduction Heterogeneity." JACC: Clinical Electrophysiology 6, no. 14 (December 2020): 1844–54. http://dx.doi.org/10.1016/j.jacep.2020.09.030.

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23

van der Ploeg, Jan Douwe, and Flaminia Ventura. "Heterogeneity reconsidered." Current Opinion in Environmental Sustainability 8 (October 2014): 23–28. http://dx.doi.org/10.1016/j.cosust.2014.07.001.

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24

Mott, K. A., and T. N. Buckley. "Stomatal heterogeneity." Journal of Experimental Botany 49, Special (March 1, 1998): 407–17. http://dx.doi.org/10.1093/jxb/49.special_issue.407.

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25

Marte, Barbara. "Tumour heterogeneity." Nature 501, no. 7467 (September 2013): 327. http://dx.doi.org/10.1038/501327a.

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26

Kempton, Christine L., Maureane Hoffman, Harold R. Roberts, and Dougald M. Monroe. "Platelet Heterogeneity." Arteriosclerosis, Thrombosis, and Vascular Biology 25, no. 4 (April 2005): 861–66. http://dx.doi.org/10.1161/01.atv.0000155987.26583.9b.

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27

Phelps, Charles E. "Tackling Heterogeneity." Medical Decision Making 34, no. 8 (October 17, 2014): 944–47. http://dx.doi.org/10.1177/0272989x14552495.

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28

Everts, Vincent, Teun J. de Vries, and Miep H. Helfrich. "Osteoclast heterogeneity:." Biochimica et Biophysica Acta (BBA) - Molecular Basis of Disease 1792, no. 8 (August 2009): 757–65. http://dx.doi.org/10.1016/j.bbadis.2009.05.004.

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29

Maron, Steven, and Adam Bass. "Tumor Heterogeneity." JAMA Network Open 3, no. 4 (April 27, 2020): e203677. http://dx.doi.org/10.1001/jamanetworkopen.2020.3677.

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30

Lawrie, Stephen M. "Parsing Heterogeneity." JAMA Psychiatry 74, no. 11 (November 1, 2017): 1089. http://dx.doi.org/10.1001/jamapsychiatry.2017.2953.

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31

Masterton, Robert G. "Antibiotic heterogeneity." International Journal of Antimicrobial Agents 36 (November 2010): S15—S18. http://dx.doi.org/10.1016/s0924-8579(10)70005-4.

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32

Mendell, Nancy Role, Marie-Claude Babron, Inke Böddeker, Yeng-Feng Chiu, Jorg Grigull, Paul Van Eerdewegh, and Kai Wang. "Introduction: Heterogeneity." Genetic Epidemiology 21, S1 (2001): S42—S43. http://dx.doi.org/10.1002/gepi.2001.21.s1.s42.

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33

Barzgar Barough, Neda, Fakhrosadat Sajjadian, Nazila Jalilzadeh, Hajar Shafaei, and Kobra Velaei. "Understanding breast cancer heterogeneity through non-genetic heterogeneity." Breast Cancer 28, no. 4 (March 15, 2021): 777–91. http://dx.doi.org/10.1007/s12282-021-01237-w.

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34

Albin, R. L., and W. T. Dauer. "Parkinson syndrome: Heterogeneity of etiology; heterogeneity of pathogenesis?" Neurology 79, no. 3 (June 20, 2012): 202–3. http://dx.doi.org/10.1212/wnl.0b013e31825dd3d0.

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35

Swaminathan, Mahesh, Kiyomi Morita, Yan Yuanqing, Feng Wang, Jared K. Burks, Curtis Gumbs, Latasha Little, et al. "Clinical Heterogeneity of AML Is Associated with Mutational Heterogeneity." Blood 132, Supplement 1 (November 29, 2018): 5240. http://dx.doi.org/10.1182/blood-2018-99-117287.

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Abstract BACKGROUND: AML is a group of clinically heterogeneous diseases. We hypothesized that heterogeneous presentation of AML is a reflection of equally heterogeneous genetic process during the leukemogenesis. METHODS: 536 AML patients (pts) bone marrow samples were analyzed by targeted capture exome sequencing of 295 genes. Extensive clinical-genotype correlation was performed using well annotated clinical data. RESULTS: The median age of the cohort was 62 years (IQR: 51-72) including 297 (55%) elderly (age ≥60), and 239 (45%) young (age <60) pts. Of the 536 pts, 308 (57%) pts had de novo AML (dnAML), and 103 (19%) had secondary or therapy-related AML (stAML). DNA sequencing revealed 1,586 high-confidence somatic mutations (922 SNVs and 664 indels) in 79 genes in 493 (92%) pts [median 3 (IQR 2-4) mutations/patient]. Cytogenetics were favorable in 10 (2%), intermediate in 326 (61%), and adverse in 177 (33%) (All defined by ELN 2017criteria); 23 (4%) pts had no cytogenetics data. Elderly pts and young pts had distinct mutational landscape. (1.3-9.6), p = 0.0079] were significantly more enriched in elderly AML, whereas young AML pts were enriched with mutations in FLT3 [OR 0.6 (0.4-0.9), p = 0.0089], NPM1 [OR 0.5 (0.3-0.9), p = 0.0113], PTPN11 [OR 0.2 (0.2-0.7), p = 0.0033], and WT1 [OR 0.4 (0.2-0.7), p = 0.0033]. Some of the mutations enriched in elderly pts are frequently observed in pts with clonal hematopoiesis with indeterminate potential. Based on the ontogeny of AML, PTPN11 [OR 7.6 (1-57.2), p=0.0210], NPM1 [OR 3.0 (1.5-6.1), p = 0.0007], WT1 [OR 2.9 (1.1-7.4), p=0.0279] mutations were significantly enriched in dnAML, while SF3B1 [OR 0.4 (0.18-0.89), p=0.0376], SRSF2 [OR 0.5 (0.3-0.85), p = 0.0109], TP53 [OR 0.5 (0.3-0.8), p = 0.0131], ASXL1 [OR 0.6 (0.36-0.95), p=0.0451] mutations were more enriched in stAML (Figure A). We then correlated mutation data with clinical and immunological parameters that are routinely tested in AML. Mutations in NPM1, FLT3, PTPN11 and NRAS were associated with significantly higher white blood cell (WBC) counts, bone marrow blast and LDH, which is consistent with their hyperproliferative activity as class 1 genes. In contrast, pts with mutations in TP53, STAG2 and ASXL1 presented with significantly low bone marrow blast, circulating blast, and WBC. Mutations in BCOR and ASXL1 was associated with significantly low LDH. Interestingly, pts with IDH2 mutations presented with significantly higher platelet, which is consistent with anecdotal report (DiNardo et al. Am J Hematology). Not surprisingly, TP53 mutations were associated with complex cytogenetics, whereas SRSF2, NPM1, IDH2, FLT3, and CEBPA mutations were associated with good and intermediate cytogenetics by ELN classification (Figure B). Pts with NPM1, IDH2, and IDH1 mutations were associated with less HLA-DR and CD34 expression in blast by flow cytometry. This is consistent with the frequent presentation of these AML sub-types with cuplike nuclei (Rakheja et al. BJH). DNA sequencing of a large cohort also allowed us to detect mutations that have not been as commonly reported in AML. We detected hot-spot mutations in exon 2 of MYC and MYCN genes in 9 (2%) AML pts. Additionally, internal tandem duplication (ITD) in MYC was also detected in one patient. Immunohistochemical staining showed that MYC expression was significantly elevated in patients with MYC mutations than in patients without the mutations (median H score 22 vs. 15 in MYC mutated vs. normal karyotype control, p < 0.001, 22 vs. 13.5 in MYC mutated vs. trisomy 8 control). These data suggest that a subset of AML is driven by the strong MYC signaling, consistent with a prior study (Ohanian et al. Leuk Lymphoma). CONCLUSION: Heterogeneous clinical presentation of AML has significant association with genetic heterogeneity, which suggest that distinct genetic basis of leukemogenic process has strong role in defining clinical presentation of AML. These data also help stratifying the patients for the likely target of precision medicine. Disclosures DiNardo: Medimmune: Honoraria; Celgene: Honoraria; Agios: Consultancy; Abbvie: Honoraria; Karyopharm: Honoraria; Bayer: Honoraria. Kadia:Celgene: Research Funding; Pfizer: Consultancy, Research Funding; BMS: Research Funding; Jazz: Consultancy, Research Funding; Abbvie: Consultancy; Abbvie: Consultancy; Amgen: Consultancy, Research Funding; BMS: Research Funding; Pfizer: Consultancy, Research Funding; Jazz: Consultancy, Research Funding; Takeda: Consultancy; Amgen: Consultancy, Research Funding; Takeda: Consultancy; Novartis: Consultancy; Celgene: Research Funding; Novartis: Consultancy. Cortes:novartis: Research Funding. Daver:Daiichi-Sankyo: Research Funding; Pfizer: Consultancy; Alexion: Consultancy; ARIAD: Research Funding; Karyopharm: Consultancy; ImmunoGen: Consultancy; Kiromic: Research Funding; Otsuka: Consultancy; Sunesis: Consultancy; Novartis: Research Funding; BMS: Research Funding; Incyte: Consultancy; Novartis: Consultancy; Sunesis: Research Funding; Karyopharm: Research Funding; Pfizer: Research Funding; Incyte: Research Funding. Pemmaraju:SagerStrong Foundation: Research Funding; celgene: Consultancy, Honoraria; cellectis: Research Funding; samus: Research Funding; daiichi sankyo: Research Funding; Affymetrix: Research Funding; stemline: Consultancy, Honoraria, Research Funding; plexxikon: Research Funding; novartis: Research Funding; abbvie: Research Funding.

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36

Wang, Diane Catherine, and Xiangdong Wang. "Systems heterogeneity: An integrative way to understand cancer heterogeneity." Seminars in Cell & Developmental Biology 64 (April 2017): 1–4. http://dx.doi.org/10.1016/j.semcdb.2016.08.016.

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37

Boerma, E. C. "Heterogeneity in microcirculatory blood flow and heterogeneity in observations." Critical Care Medicine 38, no. 4 (April 2010): 1227–28. http://dx.doi.org/10.1097/ccm.0b013e3181ce47d5.

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38

Zardkoohi, Asghar, Leonard Bierman, and Subrata Chakrabarty. "The Interaction between Geographic Heterogeneity and Human Capital Heterogeneity." Academy of Management Proceedings 2012, no. 1 (July 2012): 16737. http://dx.doi.org/10.5465/ambpp.2012.16737abstract.

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39

Collins, Scott L., Meghan L. Avolio, Corinna Gries, Lauren M. Hallett, Sally E. Koerner, Kimberly J. La Pierre, Andrew L. Rypel, et al. "Temporal heterogeneity increases with spatial heterogeneity in ecological communities." Ecology 99, no. 4 (February 15, 2018): 858–65. http://dx.doi.org/10.1002/ecy.2154.

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40

Igrek, Apple Zefelius. "Violence and Heterogeneity." Janus Head 7, no. 2 (2004): 404–28. http://dx.doi.org/10.5840/jh20047216.

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This article begins with a response to Habermas’ critique of Bataille. Habermas argues that the realm of heterogeneity/transgression is only opened up in moments of shock which overwhelm the subject. The rational categories of thought which maintain a useful relationship with the outside (i.e., with anything construed as unfamiliar) are fragmented in the excess and horror of Bataille’s communication. Hence it is impossible to bring together under one theoretical umbrella the antitheses of subjectivity and its excluded other: by definition the other ought to be marginalized in its very objectification by the subject, normativity, rationality, etc. My response is that the two opposed terms/antitheses are indeed opposed, but they are not therefore abstract opposites. That is to say, the subject is always already an equivocation of terms, a kind of sacrilege which cannot be assimilated to an ideal completion. The law is itself a transgression.

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41

Jamal-Hanjani, M. "ES27.03 Genomic Heterogeneity." Journal of Thoracic Oncology 16, no. 3 (March 2021): S93—S94. http://dx.doi.org/10.1016/j.jtho.2021.01.058.

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42

Tammela, T. "ES27.04 Phenotypic Heterogeneity." Journal of Thoracic Oncology 16, no. 3 (March 2021): S94. http://dx.doi.org/10.1016/j.jtho.2021.01.059.

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43

Vaupel, James W., and Trifon I. Missov. "Unobserved population heterogeneity." Demographic Research 31 (September 17, 2014): 659–86. http://dx.doi.org/10.4054/demres.2014.31.22.

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44

Kasahara, Kohji. "Lipid Rafts Heterogeneity." Trends in Glycoscience and Glycotechnology 31, no. 181 (July 25, 2019): SE23—SE24. http://dx.doi.org/10.4052/tigg.1910.2se.

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45

Kasahara, Kohji. "Lipid Rafts Heterogeneity." Trends in Glycoscience and Glycotechnology 31, no. 181 (July 25, 2019): SJ23—SJ24. http://dx.doi.org/10.4052/tigg.1910.2sj.

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46

Nunes, Abraham, Martin Alda, Timothy Bardouille, and Thomas Trappenberg. "Representational Rényi Heterogeneity." Entropy 22, no. 4 (April 7, 2020): 417. http://dx.doi.org/10.3390/e22040417.

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A discrete system’s heterogeneity is measured by the Rényi heterogeneity family of indices (also known as Hill numbers or Hannah–Kay indices), whose units are the numbers equivalent. Unfortunately, numbers equivalent heterogeneity measures for non-categorical data require a priori (A) categorical partitioning and (B) pairwise distance measurement on the observable data space, thereby precluding application to problems with ill-defined categories or where semantically relevant features must be learned as abstractions from some data. We thus introduce representational Rényi heterogeneity (RRH), which transforms an observable domain onto a latent space upon which the Rényi heterogeneity is both tractable and semantically relevant. This method requires neither a priori binning nor definition of a distance function on the observable space. We show that RRH can generalize existing biodiversity and economic equality indices. Compared with existing indices on a beta-mixture distribution, we show that RRH responds more appropriately to changes in mixture component separation and weighting. Finally, we demonstrate the measurement of RRH in a set of natural images, with respect to abstract representations learned by a deep neural network. The RRH approach will further enable heterogeneity measurement in disciplines whose data do not easily conform to the assumptions of existing indices.

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47

YANG, Yi-Ling, Jia-You CHU, and Ming-Rong WANG. "Tumor genetic heterogeneity." Hereditas (Beijing) 35, no. 1 (September 26, 2013): 1–9. http://dx.doi.org/10.3724/sp.j.1005.2013.00001.

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48

Venuti, Lawrence. "Translation, Heterogeneity, Linguistics." TTR : traduction, terminologie, rédaction 9, no. 1 (March 20, 2007): 91–115. http://dx.doi.org/10.7202/037240ar.

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Abstract Translation, Heterogeneity, Linguistics — As an American translator of literary texts I devise and execute my projects with a distinctive set of theoretical assumptions about language and textuality, assumptions that highlight the power relations in any cultural situation and that therefore carry ethical and political implications for translation. Yet these assumptions, derived from recent European developments in literary and cultural theory (notably poststructuralism and postmarxist sociology), run counter to the linguistics-oriented approaches that currently dominate translation research and translator training, and that tend to construe language, textuality, and hence translation as relatively value-free means of communication. My article describes my conception of translation, considers how it has informed my recent translation projects — both the selection of foreign texts and the development of discursive strategies — and then examines its differences to linguistics-oriented approaches that are based on pragmatics and text linguistics. My aim is not to suggest that such approaches be abandoned, but rather that they be reconsidered from a different theoretical and practical orientation — one that will in turn be forced to rethink itself.

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49

Ng, Mei Fong, Jacinta L. Simmons, and Glen M. Boyle. "Heterogeneity in Melanoma." Cancers 14, no. 12 (June 20, 2022): 3030. http://dx.doi.org/10.3390/cancers14123030.

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There is growing evidence that tumour heterogeneity has an imperative role in cancer development, evolution and resistance to therapy. Continuing advancements in biomedical research enable tumour heterogeneity to be observed and studied more critically. As one of the most heterogeneous human cancers, melanoma displays a high level of biological complexity during disease progression. However, much is still unknown regarding melanoma tumour heterogeneity, as well as the role it plays in disease progression and treatment response. This review aims to provide a concise summary of the importance of tumour heterogeneity in melanoma.

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50

Vihinen, Mauno. "Individual Genetic Heterogeneity." Genes 13, no. 9 (September 10, 2022): 1626. http://dx.doi.org/10.3390/genes13091626.

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Genetic variation has been widely covered in literature, however, not from the perspective of an individual in any species. Here, a synthesis of genetic concepts and variations relevant for individual genetic constitution is provided. All the different levels of genetic information and variation are covered, ranging from whether an organism is unmixed or hybrid, has variations in genome, chromosomes, and more locally in DNA regions, to epigenetic variants or alterations in selfish genetic elements. Genetic constitution and heterogeneity of microbiota are highly relevant for health and wellbeing of an individual. Mutation rates vary widely for variation types, e.g., due to the sequence context. Genetic information guides numerous aspects in organisms. Types of inheritance, whether Mendelian or non-Mendelian, zygosity, sexual reproduction, and sex determination are covered. Functions of DNA and functional effects of variations are introduced, along with mechanism that reduce and modulate functional effects, including TARAR countermeasures and intraindividual genetic conflict. TARAR countermeasures for tolerance, avoidance, repair, attenuation, and resistance are essential for life, integrity of genetic information, and gene expression. The genetic composition, effects of variations, and their expression are considered also in diseases and personalized medicine. The text synthesizes knowledge and insight on individual genetic heterogeneity and organizes and systematizes the central concepts.

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