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281 results on '"Dong, Xiaoxi"'

2. Mediation Impact of Physical Literacy and Activity between Psychological Distress and Life Satisfaction among College Students during COVID-19 Pandemic

Author

Dong, Xiaoxi, Huang, Fan, Shi, Xiangyun, Xu, Menglin, Yan, Zengyin, and Türegün, Mehmet

Abstract

The study aims to examine the mediation effects of physical literacy and physical activity behavior in a relationship between psychological distress and life satisfaction among Chinese college students during the real-life Coronavirus disease pandemic (COVID-19) circumstance. This study implemented a cross-sectional design, and 1,516 participants from 12 universities participated in this study. Structural equation modeling was used to examine a hypothesized model. The findings indicated an acceptable model fit (X[superscript 2][61] = 508.2, Comparative Fit Index [CFI] = 0.958, Tucker Lewis Index [TLI] = 0.946, Root Mean Square Error of Approximation [RMSEA] = 0.076, 90% CI [0.070, 0.082], Standardized Root Mean Square Residual [SRMR] = 0.047). The results indicated that college students with low participation in physical activity could experience less than healthy living conditions. The findings offered empirical support to the theory that physical literacy could advance individuals' healthy living by promoting physical activity participation. The study suggested that educational institutions and physical activity programs should cultivate individuals' physical literacy in order to promote lifelong healthy living.

Published
2023
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5. Supplementary Table 1 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2024
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6. Supplementary Table 2 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2024
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7. Supplementary Figures S1-S15 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2024
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8. Supplementary Table 3 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2024
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9. Supplementary Data S1 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2024
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10. Supplementary Methods S1 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2024
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12. CVID enteropathy is characterized by exceeding low mucosal IgA levels and interferon-driven inflammation possibly related to the presence of a pathobiont

Author

Shulzhenko, Natalia, Dong, Xiaoxi, Vyshenska, Dariia, Greer, Renee L, Gurung, Manoj, Vasquez-Perez, Stephany, Peremyslova, Ekaterina, Sosnovtsev, Stanislav, Quezado, Martha, Yao, Michael, Montgomery-Recht, Kim, Strober, Warren, Fuss, Ivan J, and Morgun, Andrey

Subjects
Medical Microbiology, Biomedical and Clinical Sciences, Genetics, Digestive Diseases, Nutrition, Clinical Research, Aetiology, 2.1 Biological and endogenous factors, Inflammatory and immune system, Acinetobacter baumannii, Common Variable Immunodeficiency, Down-Regulation, Duodenitis, Female, Gastrointestinal Microbiome, Gene Expression, Humans, Immunity, Mucosal, Immunoglobulin A, Inflammation, Interferons, Lipid Metabolism, Malabsorption Syndromes, Male, RNA, Bacterial, RNA, Ribosomal, 16S, Immunology
Abstract

Common variable immunodeficiency (CVID), the most common symptomatic primary antibody deficiency, is accompanied in some patients by a duodenal inflammation and malabsorption syndrome known as CVID enteropathy (E-CVID).The goal of this study was to investigate the immunological abnormalities in CVID patients that lead to enteropathy as well as the contribution of intestinal microbiota to this process.We found that, in contrast to noE-CVID patients (without enteropathy), E-CVID patients have exceedingly low levels of IgA in duodenal tissues. In addition, using transkingdom network analysis of the duodenal microbiome, we identified Acinetobacter baumannii as a candidate pathobiont in E-CVID. Finally, we found that E-CVID patients exhibit a pronounced activation of immune genes and down-regulation of epithelial lipid metabolism genes. We conclude that in the virtual absence of mucosal IgA, pathobionts such as A. baumannii, may induce inflammation that re-directs intestinal molecular pathways from lipid metabolism to immune processes responsible for enteropathy.

Published
2018

16. An Exploratory Analysis of a Subjective Well-Being Model for Chinese University Students

Author

Dong, Xiaoxi, Dibello, Lilia C., Türegün, Mehmet, and Ban, Ruth A.

Abstract

College students experience great stress due to many factors, such as an uncertain future, academic responsibilities, and pressures imposed by social communication. Many institutions of higher education are focusing on how to mediate stressful situations and increase the subjective well-being (SWB) of students to sustain a lifestyle focused on wellness. The online survey used for this study focused on testing an exploratory SWB model by implementing partial least squares structural equation modeling (PLS-SEM) techniques. The participants were 470 college-aged students enrolled in seven different institutions in six cities across China. Findings yielded a good model fit (the Standardized Root Mean Squared Residual [SRMR] = 0.054) with the validity of manifest variables, reliability of the latent variables (LVs), and overall SWB model indicating moderate predictiveness (GoF R[superscript 2] = 0.476) by the LVs. Additionally, all of the direct path coefficients and indirect path coefficients that consisted of four partial mediators and one full mediator yielded statistically significant results via bootstrapping. Furthermore, path coefficients for utilization of emotion to life satisfaction for the cognitive exercise group were significantly higher than for the non-cognitive exercise group. The findings illustrated a good model fit for an exploratory SWB model that can predict an individual's SWB, and cognitive and non-cognitive exercises had different effects on the individuals' SWB.

Published
2020
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22. Reverse enGENEering of regulatory networks from Big Data: a guide for a biologist

Author

Dong, Xiaoxi, Yambartsev, Anatoly, Ramsey, Stephen, Thomas, Lina, Shulzhenko, Natalia, and Morgun, Andrey

Subjects
Quantitative Biology - Molecular Networks
Abstract

Omics technologies enable unbiased investigation of biological systems through massively parallel sequence acquisition or molecular measurements, bringing the life sciences into the era of Big Data. A central challenge posed by such omics datasets is how to transform this data into biological knowledge. For example, how to use this data to answer questions such as: which functional pathways are involved in cell differentiation? Which genes should we target to stop cancer? Network analysis is a powerful and general approach to solve this problem consisting of two fundamental stages, network reconstruction and network interrogation. Herein, we provide an overview of network analysis including a step by step guide on how to perform and use this approach to investigate a biological question. In this guide, we also include the software packages that we and others employ for each of the steps of a network analysis workflow.

Published
2014

30. Unexpected links reflect the noise in networks

Author

Yambartsev, Anatoly, Perlin, Michael, Kovchegov, Yevgeniy, Shulzhenko, Natalia, Mine, Karina L., Dong, Xiaoxi, and Morgun, Andrey

Subjects
Quantitative Biology - Molecular Networks, Quantitative Biology - Genomics, Statistics - Applications, 62P10, 62H15, 92B99
Abstract

Gene covariation networks are commonly used to study biological processes. The inference of gene covariation networks from observational data can be challenging, especially considering the large number of players involved and the small number of biological replicates available for analysis. We propose a new statistical method for estimating the number of erroneous edges in reconstructed networks that strongly enhances commonly used inference approaches. This method is based on a special relationship between sign of correlation (positive/negative) and directionality (up/down) of gene regulation, and allows for the identification and removal of approximately half of all erroneous edges. Using the mathematical model of Bayesian networks and positive correlation inequalities we establish a mathematical foundation for our method. Analyzing existing biological datasets, we find a strong correlation between the results of our method and false discovery rate (FDR). Furthermore, simulation analysis demonstrates that our method provides a more accurate estimate of network error than FDR.

Published
2013
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37. Supplementary Table 3 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2023
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38. Supplementary Figures S1-S15 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2023
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39. Supplementary Data S1 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2023
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40. Supplementary Methods S1 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2023
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41. Supplementary Table 2 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2023
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42. Data from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2023
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43. Supplementary Table 1 from Genomic Complexity Predicts Resistance to Endocrine Therapy and CDK4/6 Inhibition in Hormone Receptor–Positive (HR+)/HER2-Negative Metastatic Breast Cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, primary, Zheng, Tiantian, primary, Dai, Chao, primary, Dong, Xiaoxi, primary, Tan, Lu, primary, Suresh, Rama, primary, Ademuyiwa, Foluso O., primary, Rigden, Caron, primary, Rearden, Timothy P., primary, Clifton, Katherine, primary, Weilbaecher, Katherine, primary, Frith, Ashley, primary, Tandra, Pavan K., primary, Summa, Tracy, primary, Haas, Brittney, primary, Thomas, Shana, primary, Hernandez-Aya, Leonel F., primary, Peterson, Lindsay L., primary, Wang, Xiaohong, primary, Luo, Shujun J., primary, Zhou, Kemin, primary, Du, Pan, primary, Jia, Shidong, primary, King, Bonnie L., primary, Krishnamurthy, Jairam, primary, and Ma, Cynthia X., primary

Published
2023
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45. Response to Letter to the Editor from Modarressi and Derakhshan: “Effects of Coenzyme Q10 Supplementation on Lipid Profiles in Adults: A Meta-analysis of Randomized Controlled Trials”

Author

Liu, Zhihao, primary, Tian, Zezhong, additional, Zhao, Dan, additional, Liang, Ying, additional, Dai, Suming, additional, Liu, Meitong, additional, Hou, Shanshan, additional, Dong, Xiaoxi, additional, Zhaxinima, Zhaxinima, additional, and Yang, Yan, additional

Published
2023
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47. Genomic complexity predicts resistance to endocrine therapy and CDK4/6 inhibition in hormone receptor-positive (HR+)/HER2-negative metastatic breast cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, additional, Zheng, Tiantian, additional, Dai, Chao, additional, Dong, Xiaoxi, additional, Tan, Lu, additional, Suresh, Rama, additional, Ademuyiwa, Foluso O., additional, Rigden, Caron, additional, Rearden, Timothy P., additional, Clifton, Katherine, additional, Weilbaecher, Katherine, additional, Frith, Ashley, additional, Tandra, Pavankumar K., additional, Summa, Tracy, additional, Haas, Brittney, additional, Thomas, Shana, additional, Hernandez-Aya, Leonel F., additional, Peterson, Lindsay L., additional, Wang, Xiaohong, additional, Luo, Shujun J., additional, Zhou, Kemin, additional, Du, Pan, additional, Jia, Shidong, additional, King, Bonnie L., additional, Krishnamurthy, Jairam, additional, and Ma, Cynthia X., additional

Published
2023
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50. 70. Assessment of circulating tumor DNA tumor mutational burden to define resistance in HR+ HER2- metastatic breast cancer

Author

Davis, Andrew A., primary, Luo, Jingqin, additional, Zheng, Tiantian, additional, Dong, Xiaoxi, additional, Tan, Lu, additional, Wang, Amy, additional, Suresh, Rama, additional, Ademuyiwa, Foluso, additional, Rigden, Caron, additional, Rearden, Timothy, additional, Clifton, Katherine, additional, Weilbaecher, Katherine, additional, Frith, Ashley, additional, Tandra, Pavan K., additional, Summa, Tracy, additional, Haas, Britney, additional, Thomas, Shana, additional, Hernandez-Aya, Leonel, additional, Peterson, Lindsay, additional, Dai, Chao, additional, King, Bonnie L., additional, Du, Pan, additional, Jia, Shidong, additional, Krishnamurthy, Jairam, additional, and Ma, Cynthia X., additional

Published
2022
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