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  1. #1
    Registered User mc4_a's Avatar
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    Study: Fructose can adversely affect both insulin and Abdominal fat

    Very interesting stuff:
    http://www.jci.org/articles/view/37385

    "In general, insulin sensitivity and glucose tolerance were not affected by the consumption of glucose but were decreased during the consumption of fructose (Table 5). Fasting glucose concentrations decreased in subjects consuming glucose but increased in subjects consuming fructose. Fasting insulin concentrations were unchanged during glucose consumption but were increased during consumption of fructose beverages."

    "...both total abdominal fat and VAT volume were significantly increased in subjects consuming fructose"

    Worth the read.
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  2. #2
    un scronnying willldabeast's Avatar
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    "fasting participants" is all i need to read
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  3. #3
    nevigsawkufelgnisaton in10city's Avatar
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    Originally Posted by mc4_a View Post
    Very interesting stuff:
    http://www.jci.org/articles/view/37385

    "In general, insulin sensitivity and glucose tolerance were not affected by the consumption of glucose but were decreased during the consumption of fructose (Table 5). Fasting glucose concentrations decreased in subjects consuming glucose but increased in subjects consuming fructose. Fasting insulin concentrations were unchanged during glucose consumption but were increased during consumption of fructose beverages."

    "...both total abdominal fat and VAT volume were significantly increased in subjects consuming fructose"

    Worth the read.
    So is not taking the results out of context from the study.

    There is nothing shocking about what would happen when you take obese subjects eating god knows how much and pump them full of an impractical amount of fructose - 25% of their caloric intake was fructose - about 150 grams worth.
    Last edited by in10city; 05-02-2009 at 01:30 PM.
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  4. #4
    Registered User mc4_a's Avatar
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    Originally Posted by in10city View Post
    So is not taking the results out of context from the study.

    There is nothing shocking about what would happen when you take obese subjects eating god knows how much and pump them full of an impractical amount of fructose - 25% of their caloric intake was fructose - about 150 grams worth.
    Right, the interesting point here is that the reaction between fructose and glucose was different.
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    Originally Posted by willldabeast View Post
    "fasting participants" is all i need to read
    What, where did you see that? I haven't read the whole thing, but from what I've gathered, only the blood tests were taken in a fasted state, which I think is a pretty common practice.
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    The Merciful alan aragon's Avatar
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    Originally Posted by mc4_a View Post
    Very interesting stuff:
    http://www.jci.org/articles/view/37385

    "In general, insulin sensitivity and glucose tolerance were not affected by the consumption of glucose but were decreased during the consumption of fructose (Table 5). Fasting glucose concentrations decreased in subjects consuming glucose but increased in subjects consuming fructose. Fasting insulin concentrations were unchanged during glucose consumption but were increased during consumption of fructose beverages."

    "...both total abdominal fat and VAT volume were significantly increased in subjects consuming fructose"

    Worth the read.
    Let's say some guy likes to play 3 games of basketball per week. Let's say some other guy likes to do a 60-minute nonstop succession of jumps off off his rooftop 3x per week... Which guy stands a greater chance of hurting himself?
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  7. #7
    Registered User mc4_a's Avatar
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    Originally Posted by alan aragon View Post
    Let's say some guy likes to play 3 games of basketball per week. Let's say some other guy likes to do a 60-minute nonstop succession of jumps off off his rooftop 3x per week... Which guy stands a greater chance of hurting himself?
    I'm not sure I understand your point, Yoda.
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  8. #8
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    Here's a far better and far more realistic study:



    Dietary Fructose and Glucose Differentially Affect Lipid and Glucose Homeostasis.

    Schaefer EJ, Gleason JA, Dansinger ML.

    Lipid Metabolism Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging at Tufts University, Cardiovascular Research Laboratory, Friedman School of Nutrition Science and Policy at Tufts University, Tufts University School of Medicine, Boston, MA 02111.

    Absorbed glucose and fructose differ in that glucose largely escapes first-pass removal by the liver, whereas fructose does not, resulting in different metabolic effects of these 2 monosaccharides. In short-term controlled feeding studies, dietary fructose significantly increases postprandial triglyceride (TG) levels and has little effect on serum glucose concentrations, whereas dietary glucose has the opposite effects. When dietary glucose and fructose have been directly compared at approximately 20-25% of energy over a 4- to 6-wk period, dietary fructose caused significant increases in fasting TG and LDL cholesterol concentrations, whereas dietary glucose did not, but dietary glucose did increase serum glucose and insulin concentrations in the postprandial state whereas dietary fructose did not. When fructose at 30-60 g ( approximately 4-12% of energy) was added to the diet in the free-living state, there were no significant effects on lipid or glucose biomarkers. Sucrose and high-fructose corn syrup (HFCS) contain approximately equal amounts of fructose and glucose and no metabolic differences between them have been noted. Controlled feeding studies at more physiologic dietary intakes of fructose and glucose need to be conducted. In our view, to decrease the current high prevalence of obesity, dyslipidemia, insulin resistance, and diabetes, the focus should be on restricting the intake of excess energy, sucrose, HFCS, and animal and trans fats and increasing exercise and the intake of vegetables, vegetable oils, fish, fruit, whole grains, and fiber.
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  9. #9
    The Merciful alan aragon's Avatar
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    Originally Posted by mc4_a View Post
    I'm not sure I understand your point, Yoda.
    Let's imagine a girl named Glucy beats her forehead against her bedroom wall for 3 hrs a day. Her friend Frucy beats her forehead against her concrete driveway for 3 hrs a day. Both aren't wearing protective gear.

    Now the question: does the fact that Frucy is worse off than Glucy have any real-world application, or is it a laughably far-fetched scenario with no relevance to us?

    Please answer this question to the best of your ability, thanks.
    Last edited by alan aragon; 05-05-2009 at 10:03 AM.
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    Originally Posted by alan aragon View Post
    Let's imagine a girl named Glucy beats her head against her forehead against her bedroom wall for 3 hrs a day. Her friend Frucy beats her forehead against her concrete driveway for 3 hrs a day. Both aren't wearing protective gear.

    Now the question: does the fact that Frucy is worse off than Glucy have any real-world application, or is it a laughably far-fetched scenario with no relevance to us?

    Please answer this question to the best of your ability, thanks.

    My guess is Frucy is going to be much worse off because concrete is harder then a wall, that is unless she gets lucky and hits a stud. But ya I get the points in this here post

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  11. #11
    Registered User mc4_a's Avatar
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    Originally Posted by alan aragon View Post
    Let's imagine a girl named Glucy beats her forehead against her bedroom wall for 3 hrs a day. Her friend Frucy beats her forehead against her concrete driveway for 3 hrs a day. Both aren't wearing protective gear.

    Now the question: does the fact that Frucy is worse off than Glucy have any real-world application, or is it a laughably far-fetched scenario with no relevance to us?

    Please answer this question to the best of your ability, thanks.
    Condescending...is that necessary? Perhaps if you made yourself clear instead of trying to come up with colorful idioms you wouldn't have to repeat yourself.

    I think it's is important for people that struggle with problem areas like belly fat. If fructose is a factor there, every little bit counts. Unless you're on a total low carb / no carb diet, it is a factor and may effect how you pick your carb sources. Considering how obsessive people get out G load and the GI index, I hardly see how interest in this study so distasteful to you. The regular caveats about sample size and the rest apply...
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  12. #12
    Eye-Stetik Pajama Own3r's Avatar
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    Oh damn it... so fruits are bad again?
    *Runs to throw out his 10lb costco apple bag*

    Feels gooood.
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  13. #13
    ‏‏‏‏‏‏‏‏‏‏‏‏‏‏‏‏‏‏‏‏ ‏‏‏‏ factotum's Avatar
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    Originally Posted by Own3r View Post
    Oh damn it... so fruits are bad again?
    *Runs to throw out his 10lb costco apple bag*

    Feels gooood.
    Fruits are fine. While they do contain fructose it is in negligible amounts. Eating a piece of fruit preworkout is fine. Eating 40 per day may be a different story.
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    Eye-Stetik Pajama Own3r's Avatar
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    Originally Posted by factotum View Post
    Fruits are fine. While they do contain fructose it is in negligible amounts. Eating a piece of fruit preworkout is fine. Eating 40 per day may be a different story.
    Fruits cause teh fat gainz and the distruction of my ripped fibraz.
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    Originally Posted by mc4_a View Post
    Condescending...is that necessary? Perhaps if you made yourself clear instead of trying to come up with colorful idioms you wouldn't have to repeat yourself.

    I think it's is important for people that struggle with problem areas like belly fat. If fructose is a factor there, every little bit counts. Unless you're on a total low carb / no carb diet, it is a factor and may effect how you pick your carb sources. Considering how obsessive people get out G load and the GI index, I hardly see how interest in this study so distasteful to you. The regular caveats about sample size and the rest apply...
    1) You failed to answer my question. I'm not being condescending, I'm teaching Socratically. Now, if you want to learn, you can follow my line of questioning, which was prompted by you calling me Yoda & claiming that you didn't understand my response.

    2) If you feel that "every little bit counts" tell me how you would apply the findings of this study to your carb choices. Then, tie in your response to the original question I asked you.
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    Originally Posted by mc4_a View Post
    If fructose is a factor there, every little bit counts. Unless you're on a total low carb / no carb diet, it is a factor and may effect how you pick your carb sources
    I think you missed the study i posted, so ill pick out the key bit for you:

    "When fructose at 30-60 g ( approximately 4-12% of energy) was added to the diet in the free-living state, there were no significant effects on lipid or glucose biomarkers."

    so when you eat sane amounts, it doesnt adversely effect anything
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    Random Reading....

    As above....^^
    Simply a thread to post any links to articles of interest you feel like sharing....
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    http://www.ncbi.nlm.nih.gov/pubmed/17356526

    Int J Obes (Lond). 2007 Sep;31(9):1378-83. Epub 2007 Mar 13. Links
    How adaptations of substrate utilization regulate body composition.

    Hall KD, Bain HL, Chow CC.
    Laboratory of Biological Modeling, National Institute of Diabetes & Digestive & Kidney Diseases, National Institutes of Health, Bethesda, MD, USA. kevinh@niddk.nih.gov
    OBJECTIVE: To elucidate the mathematical relationship between longitudinal changes of body composition and the adaptations of substrate utilization required to produce those changes. DESIGN: We developed a simple mathematical model of macronutrient balance. By using an empirical relationship describing lean body mass as a function of fat mass, we derived a mathematical expression for how substrate utilization adapts to changes of diet, energy expenditure and body fat such that energy imbalances produced the required changes of body composition. RESULTS: The general properties of our model implied that short-term changes of dietary fat alone had little impact on either fat or non-fat oxidation rates, in agreement with indirect calorimetry data. In contrast, changes of non-fat intake caused robust adaptations of both fat and non-fat oxidation rates. Without fitting any model parameters, the predicted body composition changes and oxidation rates agreed with experimental studies of overfeeding and underfeeding when the measured food intake, energy expenditure and initial body composition were used as model inputs. CONCLUSION: This is the first report to define the quantitative connection between longitudinal changes of body composition and the required relationship between substrate utilization, diet, energy expenditure and body fat mass. The mathematical model predictions are in good agreement with experimental data and provide the basis for future study of how changes of substrate utilization impact body composition regulation.
    PMID: 17356526 [PubMed - indexed for MEDLINE]
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    http://www.ncbi.nlm.nih.gov/pubmed/19501861
    Metabolism. 2009 Sep;58(9):1320-8. Epub 2009 Jun 18. Links
    Individual responsiveness to exercise-induced fat loss is associated with change in resting substrate utilization.

    Barwell ND, Malkova D, Leggate M, Gill JM.
    Integrative and Systems Biology, Faculty of Biomedical and Life Sciences, University of Glasgow, Glasgow, G12 8QQ, United Kingdom. j.gill@bio.gla.ac.uk
    Fat loss in response to exercise training varies between individuals, even when differences in compliance to the exercise program are accounted for. The purpose of this study was to investigate whether individual variation in change in fasting respiratory quotient (RQ) after exercise training contributes to this interindividual variability. Fifty-five premenopausal women participated in a 7-week endurance-type exercise training program; and fitness, body composition, and resting substrate utilization and metabolic rate in the fasted state were assessed at baseline and postintervention. Total net energy expenditure of the exercise intervention (exEE) was determined from heart rate obtained in all exercise sessions and individualized calibration of the heart rate vs oxygen uptake relationship. Dietary intake and physical activity (by constant heart rate monitoring) were assessed at baseline and during the final week of the intervention. Mean change in fat mass for the group was -0.97 kg (range, +2.1 to -5.3 kg). The strongest correlate of change in fat mass was exEE (r = 0.60, P < .0005). Change in fasting RQ correlated significantly (r = -0.26, P = .05) with the residual for change in fat mass after adjusting for the effects of both exEE and change in energy intake, explaining 7% of the variance. In multiple regression analysis, exEE (P < .0005) and change in fasting RQ (P = .02) were the only statistically significant independent predictors of change in fat mass, together explaining 40.2% of the variance. Thus, fat loss in response to exercise training depends not only on exercise energy expenditure but also on exercise training-induced changes in RQ at rest. This suggests that development of strategies to maximize the change in resting fat oxidation in response to an exercise training program may help individuals to maximize exercise-induced fat loss.
    PMID: 19501861 [PubMed - indexed for MEDLINE]
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    http://www.ncbi.nlm.nih.gov/pubmed/18840293
    Dyn Med. 2008 Oct 7;7:16. Links
    Modeling transitions in body composition: the approach to steady state for anthropometric measures and physiological functions in the Minnesota human starvation study.

    Hargrove JL, Heinz G, Heinz O.
    Department of Foods and Nutrition, University of Georgia, Dawson Hall, Athens, GA, USA 30602. jhargrov@fcs.uga.edu.
    ABSTRACT: BACKGROUND: This study evaluated whether the changes in several anthropometric and functional measures during caloric restriction combined with walking and treadmill exercise would fit a simple model of approach to steady state (a plateau) that can be solved using spreadsheet software (Microsoft Excel(R)). We hypothesized that transitions in waist girth and several body compartments would fit a simple exponential model that approaches a stable steady-state. METHODS: The model (an equation) was applied to outcomes reported in the Minnesota starvation experiment using Microsoft Excel's Solver(R) function to derive rate parameters (k) and projected steady state values. However, data for most end-points were available only at t = 0, 12 and 24 weeks of caloric restriction. Therefore, we derived 2 new equations that enable model solutions to be calculated from 3 equally spaced data points. RESULTS: For the group of male subjects in the Minnesota study, body mass declined with a first order rate constant of about 0.079 wk-1. The fractional rate of loss of fat free mass, which includes components that remained almost constant during starvation, was 0.064 wk-1, compared to a rate of loss of fat mass of 0.103 wk-1. The rate of loss of abdominal fat, as exemplified by the change in the waist girth, was 0.213 wk-1.On average, 0.77 kg was lost per cm of waist girth. Other girths showed rates of loss between 0.085 and 0.131 wk-1. Resting energy expenditure (REE) declined at 0.131 wk-1. Changes in heart volume, hand strength, work capacity and N excretion showed rates of loss in the same range. The group of 32 subjects was close to steady state or had already reached steady state for the variables under consideration at the end of semi-starvation. CONCLUSION: When energy intake is changed to new, relatively constant levels, while physical activity is maintained, changes in several anthropometric and physiological measures can be modeled as an exponential approach to steady state using software that is widely available. The 3 point method for parameter estimation provides a criterion for testing whether change in a variable can be usefully modelled with exponential kinetics within the time range for which data are available.
    PMID: 18840293 [PubMed - in process]
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    http://www.ncbi.nlm.nih.gov/pubmed/18369435
    PLoS Comput Biol. 2008 Mar 28;4(3):e1000045. Links
    The dynamics of human body weight change.

    Chow CC, Hall KD.
    Laboratory of Biological Modeling, National Institute of Diabetes and Digestive and Kidney Diseases, National Institutes of Health, Bethesda, Maryland, United States of America. carsonc@mail.nih.gov
    An imbalance between energy intake and energy expenditure will lead to a change in body weight (mass) and body composition (fat and lean masses). A quantitative understanding of the processes involved, which currently remains lacking, will be useful in determining the etiology and treatment of obesity and other conditions resulting from prolonged energy imbalance. Here, we show that a mathematical model of the macronutrient flux balances can capture the long-term dynamics of human weight change; all previous models are special cases of this model. We show that the generic dynamic behavior of body composition for a clamped diet can be divided into two classes. In the first class, the body composition and mass are determined uniquely. In the second class, the body composition can exist at an infinite number of possible states. Surprisingly, perturbations of dietary energy intake or energy expenditure can give identical responses in both model classes, and existing data are insufficient to distinguish between these two possibilities. Nevertheless, this distinction has important implications for the efficacy of clinical interventions that alter body composition and mass.
    PMID: 18369435 [PubMed - indexed for MEDLINE]
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    http://www.ncbi.nlm.nih.gov/pubmed/19386028

    Nutr Rev. 2009 May;67(5):249-54. Links
    The energy balance equation: looking back and looking forward are two very different views.

    Schoeller DA.
    Department of Nutritional Sciences, University of Wisconsin-Madison, Madison, Wisconsin 53706, USA. dschoell@nutrisci.wisc.edu
    The energy balance equation has served as an important tool for the study of bioenergetics. It is based on one of the most fundamental properties of thermodynamics and has been invaluable in understanding the interactions of energy intake, energy expenditure, and body composition. Recently, however, the obesity epidemic has extended the use of the equation to the creation of public health messages for preventing or even reversing secular trends in body mass index. This usage often fails to consider how changes in any one term of the equation can lead to accommodations in one or both of the other two terms. It is concluded that research and public health messages should not simply consider how interventions affect just energy expenditure or energy intake, but rather how they affect the balance or gap between energy intake and expenditure.
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    http://www.ncbi.nlm.nih.gov/pubmed/18842775

    Am J Clin Nutr. 2008 Oct;88(4):906-12. Links
    Long-term persistence of adaptive thermogenesis in subjects who have maintained a reduced body weight.

    Rosenbaum M, Hirsch J, Gallagher DA, Leibel RL.
    Columbia University College of Physicians & Surgeons, New York Presbyterian Medical Center, New York, NY 10032, USA. mr475@columbia.edu
    BACKGROUND: After weight loss, total energy expenditure -- in particular, energy expenditure at low levels of physical activity -- is lower than predicted by actual changes in body weight and composition. An important clinical issue is whether this reduction, which predisposes to weight regain, persists over time. OBJECTIVE: We aimed to determine whether this disproportionate reduction in energy expenditure persists in persons who have maintained a body-weight reduction of > or =10% for >1 y. DESIGN: Seven trios of sex- and weight-matched subjects were studied in an in-patient setting while receiving a weight-maintaining liquid formula diet of identical composition. Each trio consisted of a subject at usual weight (Wt(initial)), a subject maintaining a weight reduction of > or =10% after recent (5-8 wk) completion of weight loss (Wt(loss-recent)), and a subject who had maintained a documented reduction in body weight of >10% for >1 y (Wt(loss-sustained)). Twenty-four-hour total energy expenditure (TEE) was assessed by precise titration of fed calories of a liquid formula diet necessary to maintain body weight. Resting energy expenditure (REE) and the thermic effect of feeding (TEF) were measured by indirect calorimetry. Nonresting energy expenditure (NREE) was calculated as NREE = TEE - (REE +TEF). RESULTS: TEE, NREE, and (to a lesser extent) REE were significantly lower in the Wt(loss-sustained) and Wt(loss-recent) groups than in the Wt(initial) group. Differences from the Wt(initial) group in energy expenditure were qualitatively and quantitatively similar after recent and sustained weight loss. CONCLUSION: Declines in energy expenditure favoring the regain of lost weight persist well beyond the period of dynamic weight loss.
    PMID: 18842775 [PubMed - indexed for MEDLINE]
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    http://www.ncbi.nlm.nih.gov/pubmed/19253879

    Rev Prat. 2009 Jan 20;59(1):41-7.Links
    [Energy expenditure. How can they be measured?]

    [Article in French]

    Rigaud D.
    CHU Dijon, h?pital du Bocage, service endocrinologie-nutrition, 21079 Dijon Cedex, France. daniel.rigaud@chu-dijon.fr
    Body weight is dependent on the mass of the body and on the fat-free mass. In order to accomplish its mechanical and biochemical functions, the Krebs cycle is activated and generates ATP formation. From ATP, ADP is generated, releasing energy. Total energy expenditure (EE) includes: resting EE, diet-induced thermogenesis, activity-based EE and EE from thermoregulation. They represent 65%, 15%, 20% and 2% of total EE in sedentary human being. The subjects who will being overweight have, as a mean, decreased REE, DIT, PAEE and EETR. At the opposite, the thin subjects have elevated REE, DIT, PAEE and may be EETR. When an obese people is slimming, REE, DIT, PAEE and EETR decrease. When a thin people is gaining weight, REE, DIT, PAEE and EETR increase. This adaptative phenomenon explains why change in body weight and body masses are not linear.
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    http://www.ncbi.nlm.nih.gov/pubmed/12199298

    Nutr Rev. 2002 Aug;60(8):223-33. Links

    The thermic effect of food and obesity: discrepant results and methodological variations.
    Granata GP, Brandon LJ.
    Department of Human Performance and Health Promotion, University of New Orleans, LA 70148, USA.
    Studies have yielded discrepant results concerning whether the thermic effect of food (TEF) is reduced in obesity. Methodological variations among published studies make understanding the discrepant results very difficult. Although methodological differences are often noted as contributing to the discrepant results, little work has been done to address these differences and standardize experimental protocols. This paper reviews 50 studies that have investigated TEF in obesity and focuses on factors related to experimental protocol and subject control that reportedly affect measurements of resting energy expenditure, postprandial energy expenditure, and the calculation of TEF.
    PMID: 12199298 [PubMed - indexed for MEDLINE]
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    http://www.ncbi.nlm.nih.gov/pubmed/16166564

    Arterioscler Thromb Vasc Biol. 2005 Dec;25(12):2451-62. Epub 2005 Sep 15. Links
    Fast food, central nervous system insulin resistance, and obesity.

    Isganaitis E, Lustig RH.
    Department of Pediatrics, University of California, San Francisco, CA 94143-0434, USA.
    Rates of obesity and insulin resistance have climbed sharply over the past 30 years. These epidemics are temporally related to a dramatic rise in consumption of fast food; until recently, it was not known whether the fast food was driving the obesity, or vice versa. We review the unique properties of fast food that make it the ideal obesigenic foodstuff, and elucidate the mechanisms by which fast food intake contributes to obesity, emphasizing its effects on energy metabolism and on the central regulation of appetite. After examining the epidemiology of fast food consumption, obesity, and insulin resistance, we review insulin's role in the central nervous system's (CNS) regulation of energy balance, and demonstrate the role of CNS insulin resistance as a cause of leptin resistance and in the promotion of the pleasurable or "hedonic" responses to food. Finally, we analyze the characteristics of fast food, including high-energy density, high fat, high fructose, low fiber, and low dairy intake, which favor the development of CNS insulin resistance and obesity.
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    http://www.ncbi.nlm.nih.gov/pubmed/17451048

    Ideggyogy Sz. 2007 Mar 30;60(3-4):97-108.Links
    Brain insulin signalling in the regulation of energy balance and peripheral metabolism.

    Diamant M.
    Department of Endocrinology, VU University Medical Center, PO BOX 7057, 1007 MB Amsterdam, The Netherlands. m.diamant@vumc.nl
    The unparalleled global rates of obesity and type 2 diabetes, together with the associated cardiovascular morbidity and mortality, are referred to as the "diabesity pandemic". Changes in lifestyle occurring worldwide, including the increased consumption of high-caloric foods and reduced exercise, are regarded as the main causal factors. Central obesity and insulin resistance have emerged as important linking components. Understanding the aetiology of the cluster of pathologies that leads to the increased risk is instrumental in the development of preventive and therapeutic strategies. Historically, skeletal muscle, adipose tissue and liver were regarded as key insulin target organs involved in insulin-mediated regulation of peripheral carbohydrate, lipid and protein metabolism. The consequences of impaired insulin action in these organs were deemed to explain the functional and structural abnormalities associated with insulin resistance. The discovery of insulin receptors in the central nervous system, the detection of insulin in the cerebrospinal fluid after peripheral insulin administration and the well-documented effects of intracerebroventricularly injected insulin on energy homeostasis, have identified the brain as an important target for insulin action. In addition to its critical role as a peripheral signal integrating the complex network of hypothalamic neuropeptides and neurotransmitters that influence parameters of energy balance, central nervous insulin signalling is also implicated in the regulation of peripheral glucose metabolism. This review summarizes the evidence of insulin action in the brain as part of the multifaceted circuit involved in the central regulation of energy and glucose homeostasis, and discuss the role of impaired central nervous insulin signalling as a pathogenic factor in the obesity and type 2 diabetes epidemic.
    PMID: 17451048 [PubMed - indexed for MEDLINE]
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    Effects of severe protein restriction with ketoanalogues in advanced renal failure.Malvy D, Maingourd C, Pengloan J, Bagros P, Nivet H.
    Centre Ren? Labusqui?re and INSERM U.330, Universit? Victor Segalen Bordeaux 2, France.

    OBJECTIVE: To compare a severe protein restriction diet supplemented with ketoanalogues to a moderate protein restriction diet in order to limit glomerular filtration rate (GFR) decrease in an advanced renal insufficiency stage. DESIGN: Prospective randomised study conducted to compare a severe protein restriction diet (0.30 g/kg/day) supplemented with a preparation of ketoanalogues, hydroxyanalogues of aminoacids and aminoacids (Group A) to a moderate protein restriction diet (0.65 g/kg/day) (Group B). PATIENTS: 50 uremic patients included (25 in each group) with GFR is <20 mL/min/1.73m2. RESULTS: There were no statistically significant differences between the two dietary regimens for the renal survival. But uremia decreased significantly in Group A (22.7+/-5.2 to 18.5+/-6.7 mmol/L) and increased in Group B (26.8+/-9.0 to 34.9+/-9.9 mmol/L). Calcemia increased in Group A from 2.28+/-0.18 to 2.42+/-0.17 mmol/L, p<0.01 with a stable phosphoremia while calcemia decreased in Group B (2.33+/-0.18 to 2.25+/-0.17 mmol/L, p<0.05). At the end of the study, Group A was different from Group B for calcemia (2.42+/-0.17 vs. 2.25+/-0.17 mmol/L, p<0.01), phosphoremia (1.39+/-0.30 vs. 1.80+/-0.65 mmol/L, p<0.02), alkaline phosphatase (61.42+/-22.93 vs. 78.8+/-27.0, p<0.05) and parathormone plasma levels (2.71+/-1.55 vs. 5.91+/-1.41 ng/mL, p<0.001). COMMENTS: Compared to a moderate protein restriction (0.65 g/kg/day), a severe protein restriction (0.3 g/kg/day) supplemented by ketoanologues does not limit GFR decrease when GFR is below 20 mL/min/1.73m2, but improves phosphocalcic plasma parameters.

    http://www.ncbi.nlm.nih.gov/pubmed/1...ubmed_RVDocSum



    Plasma urea appearance rate is lower when children with kwashiorkor and infection are fed egg white-tryptophan rather than milk protein.Manary MJ, Yarasheski KE, Hart CA, Broadhead RL.
    Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA.

    In kwashiorkor, there is less endogenous proteolysis in response to acute infection than in a well-nourished state. Thus the amino acid composition of dietary protein may be more important in facilitating the acute phase response in kwashiorkor. This study tested the hypothesis that during the treatment of kwashiorkor with infection, there is a lower rate of urea appearance when the dietary intake of amino acids more closely resembles the amino acid composition of acute phase proteins. Thirty children in Malawi with kwashiorkor and acute infection were fed isoenergetic, isonitrogenous meals containing either egg white-tryptophan or milk as a protein source. After 24 h, the rates of urea appearance and whole-body protein breakdown and synthesis were measured with the use of 1-13C-leucine and 15N2-urea tracers. Plasma concentrations of seven acute phase proteins, interleukin 6 and tumor necrosis factor-alpha were measured on admission, and at 24 and 48 h. The 16 children who received egg white-tryptophan had lower rates of urea appearance than those who received milk [57+/-30 vs. 87+/-36 micromol/(kg x h), mean +/- SD, P<0.02]. No significant differences were found in the rates of whole-body protein turnover or in the concentration of any of the acute phase proteins or cytokines. The concentration of interleukin 6 was consistent with an appropriate proinflammatory response and correlated directly with the concentrations of C-reactive protein (r = 0.67, P<0.01) and alpha1-antitrypsin (r = 0.40, P<0.05). The findings suggest that egg white-tryptophan is associated with less amino acid oxidation in kwashiorkor and acute infection than is milk.

    http://www.ncbi.nlm.nih.gov/pubmed/1...ubmed_RVDocSum
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  29. #29
    Not Swimming. Emma-Leigh's Avatar
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    http://www.ncbi.nlm.nih.gov/pubmed/12436270

    Eur J Appl Physiol. 2002 Nov;88(1-2):50-60. Epub 2002 Aug 15. Links

    Muscular adaptations in response to three different resistance-training regimens: specificity of repetition maximum training zones.
    Campos GE, Luecke TJ, Wendeln HK, Toma K, Hagerman FC, Murray TF, Ragg KE, Ratamess NA, Kraemer WJ, Staron RS.
    Department of Biomedical Sciences, College of Osteopathic Medicine, Ohio University, Irvine Hall, rm 430, Athens, OH 45701, USA.

    Thirty-two untrained men [mean (SD) age 22.5 (5.8) years, height 178.3 (7.2) cm, body mass 77.8 (11.9) kg] participated in an 8-week progressive resistance-training program to investigate the "strength-endurance continuum". Subjects were divided into four groups: a low repetition group (Low Rep, n = 9) performing 3-5 repetitions maximum (RM) for four sets of each exercise with 3 min rest between sets and exercises, an intermediate repetition group (Int Rep, n = 11) performing 9-11 RM for three sets with 2 min rest, a high repetition group (High Rep, n = 7) performing 20-28 RM for two sets with 1 min rest, and a non-exercising control group (Con, n = 5). Three exercises (leg press, squat, and knee extension) were performed 2 days/week for the first 4 weeks and 3 days/week for the final 4 weeks. Maximal strength [one repetition maximum, 1RM), local muscular endurance (maximal number of repetitions performed with 60% of 1RM), and various cardiorespiratory parameters (e.g., maximum oxygen consumption, pulmonary ventilation, maximal aerobic power, time to exhaustion) were assessed at the beginning and end of the study. In addition, pre- and post-training muscle biopsy samples were analyzed for fiber-type composition, cross-sectional area, myosin heavy chain (MHC) content, and capillarization. Maximal strength improved significantly more for the Low Rep group compared to the other training groups, and the maximal number of repetitions at 60% 1RM improved the most for the High Rep group. In addition, maximal aerobic power and time to exhaustion significantly increased at the end of the study for only the High Rep group. All three major fiber types (types I, IIA, and IIB) hypertrophied for the Low Rep and Int Rep groups, whereas no significant increases were demonstrated for either the High Rep or Con groups. However, the percentage of type IIB fibers decreased, with a concomitant increase in IIAB fibers for all three resistance-trained groups. These fiber-type conversions were supported by a significant decrease in MHCIIb accompanied by a significant increase in MHCIIa. No significant changes in fiber-type composition were found in the control samples. Although all three training regimens resulted in similar fiber-type transformations (IIB to IIA), the low to intermediate repetition resistance-training programs induced a greater hypertrophic effect compared to the high repetition regimen. The High Rep group, however, appeared better adapted for submaximal, prolonged contractions, with significant increases after training in aerobic power and time to exhaustion. Thus, low and intermediate RM training appears to induce similar muscular adaptations, at least after short-term training in previously untrained subjects. Overall, however, these data demonstrate that both physical performance and the associated physiological adaptations are linked to the intensity and number of repetitions performed, and thus lend support to the "strength-endurance continuum".
    PMID: 12436270 [PubMed - indexed for MEDLINE]
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  30. #30
    Mod Negged.... *Sigh* fodosho's Avatar
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    http://www.jissn.com/content/5/1/17
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