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  1. Article: The Interrelationship Between the Gut Microbiome and Glucose Homeostasis Following Boiled and Chilled Potato Consumption (P20-020-19)

    Patterson, Mindy / Ajami, Nadim / Fong, Joy Nolte / Kim, Jaeweon / Koboziev, Iurii / Lier, Christina van / Wang, Wanyi

    Current developments in nutrition. 2019 June 13, v. 3, no. Supplement_1

    2019  

    Abstract: Many factors influence the gut microbiome which in turn mediates physiological responses following food intake, especially when fermentable fibers such as resistant starch (RS) are consumed. Here we examined the relationship body composition and diet on ... ...

    Abstract Many factors influence the gut microbiome which in turn mediates physiological responses following food intake, especially when fermentable fibers such as resistant starch (RS) are consumed. Here we examined the relationship body composition and diet on gut microbiome diversity and composition in females. We also compared the effects of glucose and insulin following boiled (∼6 g RS) and chilled (∼12 g RS) potato intake on the gut microbiome. Using a randomized cross-over study design 250 g of both boiled and chilled Russet potatoes were consumed on two separate visits with a one-week wash-out period. Fasting and postprandial (15, 30, 60, and 120 min) blood were collected for area under the curve (AUC(0–120)) glucose and insulin calculation. Prior to visit one stool and three-day food records were collected. At visit one anthropometrics and body composition (% fat mass (%FM) and lean mass (%LM)) using air displacement plethysmograph were assessed. Microbiome profiling via 16Sv3–4 sequencing identified bacterial diversity and composition in the stool. BMI, %FM, %LM, mean energy and nutrients, and AUC(0–120) glucose and insulin following the consumption of each potato were grouped into tertiles then compared to microbiome profiles using Kruskal-Wallis nonparametric tests. Twenty-four healthy females (mean age 28.8 ± 5.9 yr and BMI of 31.8 ± 7.4 kg/m2) completed the study. Females with a lower AUC(0–120) insulin following chilled potato intake had a higher Shannon diversity index (5.8 vs 4.9; P = .033) and Lentisphaerae abundance (3.3 vs ≤ 0.1; P = .005). Higher Actinobacteria (120 vs < 33) was associated with lower AUC(0–120) insulin (P = .025) following boiled potato intake. Higher %LM (> 54%) was associated with Lentisphaerae abundance (P = .036). BMI, %FM, diet, AUC(0–120) glucose following intake of both potatoes, and AUC insulin(0–120) following boiled potato intake did not correlate with specific microbiome profiles. These data indicate that microbiome diversity is correlated with reduced insulin response following the intake of potatoes rich in RS, which may be a result of the bacterial fermentation of RS. Lentisphaerae and Actinobacteria abundance were also related to glycemic control. The Alliance for Potato Research and Education and Texas Woman's University Small Grants Program.
    Keywords Actinobacteria ; air ; blood ; body composition ; body mass index ; cross-over studies ; education ; energy ; experimental design ; fasting ; females ; fermentation ; food intake ; food records ; glucose ; glycemic control ; homeostasis ; insulin ; intestinal microorganisms ; Lentisphaerae ; lipid content ; microbiome ; nutrients ; physiological response ; potatoes ; resistant starch ; women
    Language English
    Dates of publication 2019-0613
    Publishing place Oxford University Press
    Document type Article
    ISSN 2475-2991
    DOI 10.1093/cdn/nzz040.P20-020-19
    Database NAL-Catalogue (AGRICOLA)

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  2. Article: Chilled Potatoes Decrease Postprandial Glucose, Insulin, and Glucose-dependent Insulinotropic Peptide Compared to Boiled Potatoes in Females with Elevated Fasting Glucose and Insulin

    Patterson, Mindy A / Fong, Joy Nolte / Maiya, Madhura / Kung, Stephanie / Sarkissian, Araz / Nashef, Nezar / Wang, Wanyi

    Nutrients. 2019 Sept. 03, v. 11, no. 9

    2019  

    Abstract: Resistant starch (RS) has been shown to improve postprandial glycemia and insulin sensitivity in adults with metabolic syndrome. RS is found naturally in potatoes, where the amount varies based on cooking method and serving temperature. Thirty females ... ...

    Abstract Resistant starch (RS) has been shown to improve postprandial glycemia and insulin sensitivity in adults with metabolic syndrome. RS is found naturally in potatoes, where the amount varies based on cooking method and serving temperature. Thirty females with a mean BMI of 32.8 ± 3.7 kg/m2, fasting glucose of 110.5 mg/dL, and insulin of 10.3 μIU/L, completed this randomized, crossover study. A quantity of 250 g of boiled (low RS) and baked then chilled (high RS) russet potatoes were consumed on two separate occasions. Glycemic (glucose and insulin) and incretin response, subjective satiety, and dietary intake were measured. Results showed that the chilled potato elicited significant reductions at 15 and 30 min in glucose (4.8% and 9.2%), insulin (25.8% and 22.6%), and glucose-dependent insulinotropic peptide (GIP) (41.1% and 37.6%), respectively. The area under the curve for insulin and GIP were significantly lower after the chilled potato, but no differences were seen in glucose, glucagon-like peptide-1, and peptide YY, or overall subjective satiety. A higher carbohydrate and glycemic index but lower fat diet was consumed 48-hours following the chilled potato than the boiled potato. This study demonstrates that consuming chilled potatoes higher in RS can positively impact the glycemic response in females with elevated fasting glucose and insulin.
    Keywords adults ; blood glucose ; body mass index ; cooking ; cross-over studies ; fasting ; females ; food intake ; glucagon-like peptide 1 ; glucose ; glycemic effect ; glycemic index ; insulin ; insulin resistance ; metabolic syndrome ; peptide YY ; potatoes ; resistant starch ; satiety ; secretin ; temperature
    Language English
    Dates of publication 2019-0903
    Publishing place Multidisciplinary Digital Publishing Institute
    Document type Article
    ZDB-ID 2518386-2
    ISSN 2072-6643
    ISSN 2072-6643
    DOI 10.3390/nu11092066
    Database NAL-Catalogue (AGRICOLA)

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  3. Article ; Online: Chilled Potatoes Decrease Postprandial Glucose, Insulin, and Glucose-dependent Insulinotropic Peptide Compared to Boiled Potatoes in Females with Elevated Fasting Glucose and Insulin.

    Patterson, Mindy A / Fong, Joy Nolte / Maiya, Madhura / Kung, Stephanie / Sarkissian, Araz / Nashef, Nezar / Wang, Wanyi

    Nutrients

    2019  Volume 11, Issue 9

    Abstract: Resistant starch (RS) has been shown to improve postprandial glycemia and insulin sensitivity in adults with metabolic syndrome. RS is found naturally in potatoes, where the amount varies based on cooking method and serving temperature. Thirty females ... ...

    Abstract Resistant starch (RS) has been shown to improve postprandial glycemia and insulin sensitivity in adults with metabolic syndrome. RS is found naturally in potatoes, where the amount varies based on cooking method and serving temperature. Thirty females with a mean BMI of 32.8 ± 3.7 kg/m
    MeSH term(s) Adult ; Biomarkers ; Blood Glucose ; Cold Temperature ; Cooking ; Cross-Over Studies ; Female ; Gastric Inhibitory Polypeptide/blood ; Gastric Inhibitory Polypeptide/metabolism ; Humans ; Insulin/blood ; Overweight ; Postprandial Period ; Solanum tuberosum ; Young Adult
    Chemical Substances Biomarkers ; Blood Glucose ; Insulin ; Gastric Inhibitory Polypeptide (59392-49-3)
    Language English
    Publishing date 2019-09-03
    Publishing country Switzerland
    Document type Journal Article ; Randomized Controlled Trial
    ZDB-ID 2518386-2
    ISSN 2072-6643 ; 2072-6643
    ISSN (online) 2072-6643
    ISSN 2072-6643
    DOI 10.3390/nu11092066
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  4. Article ; Online: An imageomics and multi-network based deep learning model for risk assessment of liver transplantation for hepatocellular cancer.

    He, Tiancheng / Fong, Joy Nolte / Moore, Linda W / Ezeana, Chika F / Victor, David / Divatia, Mukul / Vasquez, Matthew / Ghobrial, R Mark / Wong, Stephen T C

    Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society

    2021  Volume 89, Page(s) 101894

    Abstract: Introduction: Liver transplantation (LT) is an effective treatment for hepatocellular carcinoma (HCC), the most common type of primary liver cancer. Patients with small HCC (<5 cm) are given priority over others for transplantation due to clinical ... ...

    Abstract Introduction: Liver transplantation (LT) is an effective treatment for hepatocellular carcinoma (HCC), the most common type of primary liver cancer. Patients with small HCC (<5 cm) are given priority over others for transplantation due to clinical allocation policies based on tumor size. Attempting to shift from the prevalent paradigm that successful transplantation and longer disease-free survival can only be achieved in patients with small HCC to expanding the transplantation option to patients with HCC of the highest tumor burden (>5 cm), we developed a convergent artificial intelligence (AI) model that combines transient clinical data with quantitative histologic and radiomic features for more objective risk assessment of liver transplantation for HCC patients.
    Methods: Patients who received a LT for HCC between 2008-2019 were eligible for inclusion in the analysis. All patients with post-LT recurrence were included, and those without recurrence were randomly selected for inclusion in the deep learning model. Pre- and post-transplant magnetic resonance imaging (MRI) scans and reports were compressed using CapsNet networks and natural language processing, respectively, as input for a multiple feature radial basis function network. We applied a histological image analysis algorithm to detect pathologic areas of interest from explant tissue of patients who recurred. The multilayer perceptron was designed as a feed-forward, supervised neural network topology, with the final assessment of recurrence risk. We used area under the curve (AUC) and F-1 score to assess the predictability of different network combinations.
    Results: A total of 109 patients were included (87 in the training group, 22 in the testing group), of which 20 were positive for cancer recurrence. Seven models (AUC; F-1 score) were generated, including clinical features only (0.55; 0.52), magnetic resonance imaging (MRI) only (0.64; 0.61), pathological images only (0.64; 0.61), MRI plus pathology (0.68; 0.65), MRI plus clinical (0.78, 0.75), pathology plus clinical (0.77; 0.73), and a combination of clinical, MRI, and pathology features (0.87; 0.84). The final combined model showed 80 % recall and 89 % precision. The total accuracy of the implemented model was 82 %.
    Conclusion: We validated that the deep learning model combining clinical features and multi-scale histopathologic and radiomic image features can be used to discover risk factors for recurrence beyond tumor size and biomarker analysis. Such a predictive, convergent AI model has the potential to alter the LT allocation system for HCC patients and expand the transplantation treatment option to patients with HCC of the highest tumor burden.
    MeSH term(s) Artificial Intelligence ; Carcinoma, Hepatocellular/diagnostic imaging ; Deep Learning ; Humans ; Liver Neoplasms/diagnostic imaging ; Liver Transplantation ; Neoplasm Recurrence, Local/diagnostic imaging ; Prognosis ; Retrospective Studies ; Risk Assessment
    Language English
    Publishing date 2021-03-11
    Publishing country United States
    Document type Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't
    ZDB-ID 639451-6
    ISSN 1879-0771 ; 0895-6111
    ISSN (online) 1879-0771
    ISSN 0895-6111
    DOI 10.1016/j.compmedimag.2021.101894
    Database MEDical Literature Analysis and Retrieval System OnLINE

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