124 research outputs found

    sj-pdf-4-hpq-10.1177_13591053221129705 – for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C)

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    sj-pdf-4-hpq-10.1177_13591053221129705 for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C) by Dan Wang, Mary M Boggiano, Ke Huang, Yuzheng Hu and Junfen Fu in Journal of Health Psychology</p

    sj-pdf-3-hpq-10.1177_13591053221129705 – for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C)

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    sj-pdf-3-hpq-10.1177_13591053221129705 for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C) by Dan Wang, Mary M Boggiano, Ke Huang, Yuzheng Hu and Junfen Fu in Journal of Health Psychology</p

    sj-docx-7-hpq-10.1177_13591053221129705 – Supplemental material for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C)

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    Supplemental material, sj-docx-7-hpq-10.1177_13591053221129705 for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C) by Dan Wang, Mary M Boggiano, Ke Huang, Yuzheng Hu and Junfen Fu in Journal of Health Psychology</p

    sj-pdf-5-hpq-10.1177_13591053221129705 – for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C)

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    sj-pdf-5-hpq-10.1177_13591053221129705 for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C) by Dan Wang, Mary M Boggiano, Ke Huang, Yuzheng Hu and Junfen Fu in Journal of Health Psychology</p

    sj-xlsx-2-hpq-10.1177_13591053221129705 – for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C)

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    sj-xlsx-2-hpq-10.1177_13591053221129705 for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C) by Dan Wang, Mary M Boggiano, Ke Huang, Yuzheng Hu and Junfen Fu in Journal of Health Psychology</p

    sj-pdf-1-hpq-10.1177_13591053221129705 – for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C)

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    sj-pdf-1-hpq-10.1177_13591053221129705 for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C) by Dan Wang, Mary M Boggiano, Ke Huang, Yuzheng Hu and Junfen Fu in Journal of Health Psychology</p

    sj-sav-6-hpq-10.1177_13591053221129705 – for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C)

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    sj-sav-6-hpq-10.1177_13591053221129705 for Psychometric and cross-cultural generalizability outcomes of the Chinese version of the Kids-Palatable Eating Motives Scale (K-PEMS-C) by Dan Wang, Mary M Boggiano, Ke Huang, Yuzheng Hu and Junfen Fu in Journal of Health Psychology</p

    Characterization and application of VFA for simplification of biochemical product downstream processing

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    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemical Engineering, 2003.Includes bibliographical references (p. 173-180).This electronic version was submitted by the student author. The certified thesis is available in the Institute Archives and Special Collections.One strategy to reduce costs in manufacturing a biochemical product is simplification of downstream processing. Biochemical product recovery often starts from fermentation broth or cell culture. In conventional downstream processing, the initial steps are clarification, concentration, and purification. Simplification of downstream processing may be achieved by reducing the number of unit operations. Integrative technologies seek to combine steps into a new single unit operation, thereby tightening the whole process. Vortex flow occurs in the annular gap between an inner rotating solid cylinder and an outer stationary cylindrical shell. Above a critical rotation rate, circular Couette flow bifurcates to a series of counter-rotating toroidal vortices. By suspending adsorbent resin in the vortices, a novel unit operation, vortex flow adsorption (VFA), is created. In VFA, the rotation of the inner cylinder facilitates the fluidization of the adsorbent resin. In addition, VFA has high fluid voidage so that it can be used to recover biochemical products directly from fermentation broths or cell homogenates without removing cells or cell debris first. VFA was characterized through two experimental approaches, tracer residence time distribution (RTD) study and breakthrough capacity measurements, and two modeling approaches, a one-dimensional dispersion convective model and a two-region vortex flow model. It was concluded that the axial dispersion in the vortex flow system is distinct in different vortex flow regimes.(cont.) The effect of the operating variables, including the rotation rate of the inner cylinder, the axial loading flowrate, and the adsorbent volume fraction, on the performance of VFA was explored. In this research, recombinant human (cl-antitrypsin ([alpha]l-AT) was expressed in Escherichia coli as a C-terminal fusion to a modified intein containing a chitin-binding domain. The VFA results indicated that VFA not only captures the fusion protein from crude cell extract containing cell debris but also purifies ocl-AT. Therefore, vortex flow adsorption is an integrative technology to combine the primary clarification, concentration, and purification steps to simplify conventional downstream processing.by Junfen Ma.Ph.D

    Noninvasive Urinary Biomarkers for Obesity-Related Metabolic Diseases: Diagnostic Applications and Future Directions

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    Obesity-related metabolic diseases include conditions linked to obesity, such as type 2 diabetes, hypertension, steatotic liver disease, and polycystic ovary syndrome. These disorders are primarily caused by insulin resistance, chronic inflammation, and excessive fat accumulation. They represent significant health challenges and often remain asymptomatic during their early stages. Traditional diagnostic tools, including blood glucose, lipid levels, blood pressure, and uric acid measurements, provide valuable insights but fall short of fully capturing the complexity of metabolic dysfunction. Consequently, there is a growing need for noninvasive, easily accessible biomarkers, especially those found in urine, to enable more accurate, sensitive, and patient-friendly diagnostic methods. Urine, with its diverse range of metabolites that reflect the body&rsquo;s metabolic changes, is an ideal sample for early detection. Recent advancements in urine metabolomics and proteomics have highlighted the potential of urinary biomarkers for diagnosing obesity-related metabolic diseases. Despite challenges such as the need for standardized detection techniques and clinical validation, the integration of artificial intelligence and multi-omics approaches holds significant promise for enhancing diagnostic accuracy and advancing disease management strategies
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