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marylin monroe
Showing posts with label carbohydrates. Show all posts
Showing posts with label carbohydrates. Show all posts

Complete Meals & GI (Non-)Sense, Glutamine & GLP-1, Low Thyroid & High Trigs, N-3 vs. N-6 Interactions, Optimal DHA Dosage in Kids W/ NAFLD, Selenium vs. Aluminum Toxicity

While this is not the exact combination of chicken breast, mashed potatoes and salad in the first one of today's news items, it's more than likely that the predicted GI (and thus probably what you would find if you looked it up in a table) overestimates the postprandial glucose response to this meal by ~50% and says absolutely nothing about the insulin response. It looks like complex meals and over-simplified theories, don't mix well, at all ;-)
78% that's the SuppVersity Figure of the Week and actually part of the additional information I provided on one of today's On Short Notice items. It's the increase in coronary heart disease risk women with subclinical hypothyroidism have compared to their peers with spot on TSH levels of 0.5-1.5mU/L (Asvold. 2012). In conjunction with other more or less recent studies, such as Mitchel's, Hsu's and Sahai's paper confirming the previously often talked about but not well-established 2-fold increase in congenital hypothyroidism from the early 1990s to the first years of the new millennium (Mitchel 2011), the predictive value of high TSH levels in the first trimester (early pregnancy hypothyroidism) for adverse pregnancy outcomes (Schneuer. 2012), the 30% risk increase in all-cause mortality in both women and men with subclinical hypothyroidism Tseng et al. reported in their paper earlier this year or the impairment of spatial working memory (Yin. 2012), Asvold's results only add to the evidence that the potential pitfalls of an increasingly prevalent metabolic dysfunction may have been ignored way too long.

  • More GI lovin' - On the menu today: Mashed potaoes with chicken, rapeseed oil or both (Hätönen. 2011) - I thought a mini-follow-up on Friday's post on the GI would be nice, 'cause some of you have not without reason been complaining that not everyone would eat pure white bread, like my students do.

    Figure 1: The real (=measured) GI of a meal does differ significantly from the theoretical prediction. So, even if the concept was worth bothering, the GIs of complete meals simply wrong, if they are not measured (Hötönen. 2011).
    Moreover, the mere fact that the scientists from the Department of Lifestyles and Participation at the National Institute for Health and Welfare in Helsinki, Finland, found that the addition of chicken breast, rapeseed oil and a salad, individually and in combination, had the GI of a meal containing six mashed potatoes (this was the parameter that was held constant) induced more than twofold changes in GI, with the addition of chicken breast having the greatest deviation from the predicted value in this group of 11 (initially 12) healthy subjects, three men and nine women, aged 36.2 (SD 14.1) years with a BMI of 21.3 (SD 1.7) kg/m² and normal glucose tolerance (see figure 1).

    Now given the fact that most data on the GI of complete meals has never been measured, but is actually based on the same predictions the scientists used, it stands to reason that...
    [...] this highlights the problems encountered when predicting the GI values of mixed meals. The protein com-ponent of the mixed meal evoked the largest insulinaemic responses and markedly increased the II of the mixed meal containing protein. However, introducing fat into the meal decreased the effect of protein on the insulinaemic responses (Hätönen. 2011)
    So, this does not simply bust the idea that you could calculate the GI, it does likewise show you that people who are still overtly scared of insulin (which is hillarious as long as you are insulin sensitive) are doing he exact wrong thing, when they make food-choices based on GI: Whey protein would in that case be in as much a no-go as simply eating a chicken breast with your mashed potatoes would be, because other than what most people believe, it does increase the insulin spike and thus reduce the glycemic index by allowing your body to clear the glucose more efficiently from the circulation.

    Suggested reads: The red box in the "Whey is More Insulinogenic than White Bread" post on the partitioning effects of BCAAs and yesterday's Facebook post on the anti-Alzheimer's effects of insulin.

  • Suggested read: Amino Acids for Super Humans the purported ergogenic effects of l-glutamine
    30g of oral glutamine have similar effects on GLP-1 as 75g of glucose (Greenfield. 2008) - Still a follow up on the GI discussion, I think you may be interested in. If you are someone who follows the questionable practice of ingesting large boluses of glutamine in the futile believe that this would increase your gains or speed up recovery, you may be pleased to hear that only 30g of oral l-glutamine produced an increase in the "Fat Burning Satiety Hormone GLP-1" (read more on GLP-1) that's on a gram to gram basis more pronounced than in response to insulin (0.41pmol/L per gram glucose vs. 0.75pmol/L per gram of glutamine; in 8 healthy subjects).

    Before you go and buy tons of glutamine, you should however consider that GIP, the pro-insulinogenic peptide and glucagon (ramps up gluconeogenesis in the liver) were likewise increased by the ingestion of this bolus of glutamine. It is therefore no wonder that glutamine has never been shown to be a "fat burner". Nonetheless, a 1999 study by Bowtell et al. would suggest that it may come handy to replenish liver and muscle glycogen after a workout (8g alone did increase glucose storage after a workout to a similar degree as a 18.5% glucose polymer solution and additional 25% glucose storage mostly in the liver, when both were coingested; cf. Bowtell. 1999). And if you don't care about that - your gut integrity could also be a reason to consider supplementation in the vicinity of particular strenuous or length workouts (see "Shedding Some Light on the Leaky Gut <> Exercise Connection") 

  • Practical relevance? Based on data from a 12-year longitudinal study, even women with subclinical hypothyroidism have 76% risk for coronary heart disease (p = 0.005), than women with spot on TSH levels of 0.5-1.5mU/L (Asvold. 2012). And even women well within in the "normal range" (TSH of 1.5-2.4mU/l) have a 41% higher risk of heart disease, although this is only borderline significant (p = 0.08). For men the TSH level alone had not predictive value. Spec. w/ regards to T3, there are also reports of increased incidence of ventricular disfuntion (Cassetti. 2009), increased cardiac death in CVD patients (Iervasi. 2003) and impaired recovery after a stroke (Alevizaki. 2007). We do yet have to be cautious, here as "low T3" syndrome could as well be the consequence of overall inflammation and the association does not tell us anything about what's the chicken and the egg.
    Low thyroid, high triglyceride (Hashimoto. 2012) -- If you are wondering why on earth your trigs won't come down, it may well be that it's the absence of sufficient amounts of thyroid hormone. I a soon-to-be-published paper in Endocrinology scientists from the Gunma University in Maebashi, Gunma, Japan, report that thyroid hormone regulates the expression of a Stearoyl-CoA desaturase-1 (SCD-1) which controls the production of trigs from carbohydrates.

    Surprisingly the 75% increase due to hypothyroidism and the 75% decrease in SCD-1 mRNA expression (both compared to a euthyroid state) the scientists observed in rodents in response to the administration of T3 were not mediated by receptor binding, but simply as a down-stream effect of direct modifications of the SCD-1 gene promoter between -124 and -92 bp by T3.

    On a related side note: It is actually the last mentioned mechanism which is the major new finding in the study at hand and not the fact that T3 can reduce the conversion of carbohydrates to triglicerides that is the actual news here. After all, the latter is something scientist should know, but obviously like to forget about ever since the late 1999s (Waters. 1997)

  • Omega-6 intake and not low omega-3 intake is the problem (Liou. 2007) -- Another older study, but one I am posting in response to a discussion some of you are having about omega-3 (ALA) intake in the post about safflower oil and DHT, because I simply feel that it's necessary to shed some light  on the erroneous assumption that by simply upping your intake of omega-3s or fish oil intake you could get away without decreasing your omega-6 intake, which in and out of itself will already increase the amount of anti-inflammatory omega-3 fatty acids (supplementation of DHA can still be advisable, specifically if you are a vegetarian).

    Figure 2: Effect of 4 weeks of high (red) vs. 4 weeks of low (green) linoleic acid (n-6) intake on short and long-chain omega-3 plasma phospholipid content in healthy men (Liou. 2007)
    In 2007, already Liu et al. conducted a very interesting experiment in the course of which they fed healthy men diets with identical amounts of omega-3 fatty acids (1% of the total energy intake), but two different amounts of linoleic acid (omega-6) and found that the high omega-6 intake (10.1% vs. 3.8% of the total energy intake) alone decreased the total amount of EPA among the plasma phospholipids (the major long-chain omega-3 fatty acid in fish oil), not just the ratio of omega-3 to omega-6, in the blood of their 29-45 year-old subjects by more than 25% (see figure 2). The paradoxical effect on DHA, on the other hand, would warrant further investigation, and underlines how reliant we are - if anything on the intake of pure DHA, which dropped in consequence to the test diet, which was devoid of fatty fish, while the original diet of the non-vegetarian subjects had fish in it.

    In this context, I would also like to point out that DHA is exactly where real fish is far superior to fish oil caps, because it has a way more favorable EPA:DHA ratio than fish oil caps. Salmon fillets for example have - depending on the fatty acid source in the diet 8.5g : 13.8g, 4.4g : 7.8g and 1.5g : 2.9g (all values per 100g) when the feed contains fish oil, fish and rapeseed and fish + rapeseed and rapeseed, only.

    And while the ratios are similar regardless of the chow, the data from the Seierstad et al. clearly shows that the fatty acid content of the diets can induce almost 5-fold differences in terms of the total DHA content and the omega-3 to omega 6 ratio (fish oil diet: 6.5, fish oil + rapeseed: 1.7, rapeseed: 0.6) of salmon fillets (Seierstad. 2003). 

  • It does not take much: 500mg DHA not more effective than 250mg  (Nobili. 2012) -- At least if it comes to its beneficial effects against liver steatosis in children  (mean age 11 years; BMI 26.6kg/m² and 24.4kg/m², in the low and high dose groups respectively with with NAFLD, the amount of DHA does not appear to be so important. According to the results of their 2-year registered controlled trial, both 250mg and 500mg of Docosahexaenoic acid lead to identical and profound reductions in the odds ratio of developing more severe steatosis during the study period.

    Figure 3: Odds ratio (comparing DHA supplement vs. placebo) of more severe vs. less severe liver steatosis determined every 6 months during the 24-month study period (Nobili. 2012)
    If you take a closer look at the data in figure 3, you will even have to concede that the lower dosage did a better job - while the mean odds ratios were only marginally lower in the 250mg DHA group, the extremely high standard deviations in the 500mg DHA would suggest that the 250mg dose appears to be more reliable. In this regard it may be interesting that the increase in serum DHA did mirror the dosages. With a 0.65% and 1.15% increase in DHA those were about 2x higher in the 20 boys and girls in the high dose group compared to the 20 kids in the control group who received a 290 mg linoleic acid germ oil supplement "placebo" (by the way, a monosaturated fatty acid placebo would have been more of a placebo than 290mg of omega-6)

    In view of the fact that the changes in triglycerides, ALT, HOMA-IR and BMI (which was not even different from the placebo group) were likewise identical, it does not appear as if anything that goes beyond the amount you will find in 2x cheap fish oil caps, or 10g even of the cheapest salmon fillet (see last paragraph of previous item) would be necessary to ellicit the anti-steatosis effect of fish oil - since those kids weight on average 55kg, an adult may want to add in another fish oil cap to get up to 360mg DHA per day or simply eat his fatty fish once or twice a week.

    • Selenium ameliorates aluminum toxicity (Viezeliene. 2012) -- With the whole upheaval about the potential negative side effects of the aluminum in vaccines, the formerly overlooked yet well-known neurotoxic (Exley. 1992; Gupta. 2005), hepatotoxic (Abubakar. 2003; Perez. 2005) and nephrotoxic metal (Geyikoglu. 2012) has all of a sudden returned to the center of public interest.

      Therefore I thought that you will be interested in the results of a study that's going to be published in the next issue of the Journal of Trace Elements in Medicine and Biology - irrespective of whether you believe, like Tomljenovic and Shaw that
      "the possibility that vaccine benefits may have been overrated and the risk of potential adverse effects underestimated, has not been rigorously evaluated in the medical and scientific community"(Tomljenovic. 2011)
      After all, vaccines are not the only potential source of aluminum in our environment, so that the ameliorative effects (all values remained normal in the aluminum exposed group, while there were 30%, 55% and 42% increases in GSH in the animals who received only the selenium injection) the co-administration of supplemental selenium had on the GSH reductions in liver, kidney and brain of Balb/c mice weighing 20–25g who were exposed (by i.p. injection)to AlCl3 (25 mg Al(3+)/kg body mass) for 16h could be important, regardless of whether you do or don't intend to get vaccinated.

      There is more about selenium at the SuppVersity, for example on its pro-fertility effects, and its anti-corrosive effects in the brain.
      That said, the dosage requirements necessary to maintain healthy GSH levels are probably much lower than the hillarious (for a healthy individual) in the study at hand 1,250µg/kg body weight of sodium selenite (Na2SeO3). Considering the elemental selenium content in Na2SeO3, the latter would equal to ~3,650µg - unquestionably WAY too much (remember this was a one-time dosage that was specifically co-administered w/ the aluminum). Even the 'no observed adverse effect' level for a 70kg man of intake which is ~1000µg/d (Whanger. 1999) appears unnecessarily high, so that the consumption of a handful of brazil nuts once or twice a week and/or other high selenium foods such as tuna, cod, oysters, shrimp, but also eggs, meats, poultry, mushroom and onions on a regular should suffice to get what you need, to fortify yourself against the constant assault of heavy metals.

      What would be interesting, though, is a study into the effects of adding selenium to the "safe" aluminum in vaccines. I mean, you cannot seriously tell me that we could not afford doing that and if it reduced any toxicity issues, why not?

    That's about it for today, I did not post all too many new facebook news as of yet (I mean, come on, it's Saturday ;-), but if you are into medicinal horror-stories, you will certainly like the story about the flesh eating killer fungus. If you prefer microbes over fungi, you are probably better off with the latest insights into the associations of certain gutbacteria with the incidence of stroke. And if you are more into other aspects of the digestive tract you may be interested in the effects of gastric emptying time on postprandial gylcemia and insulin release.

    If none of those news is to your liking, I suggest you either wait for me to post something else (could be happening within the next hours at www.facebook.com/SuppVersity), or simply enjoy the weekend and come back tomorrow when you are rested for another (hopefully) enlightening SuppVersity post.

      References:
      • Abubakar  MG,  Taylor  A,  Ferns  GA.  Aluminium  administration  is  associated  with enhanced  hepatic  oxidant  stress  that  may  be  offset  by  dietary  vitamin  E  in  the rat. Int J Exp Pathol 2003;84:49–54.
      • Asvold BO, Bjøro T, Platou C, Vatten LJ. Thyroid function and the risk of coronary heart disease: 12-year follow-up of the HUNT Study in Norway. Clin Endocrinol (Oxf). 2012 Dec;77(6):911-7.
      • Bowtell JL, Gelly K, Jackman ML, Patel A, Simeoni M, Rennie MJ. Effect of oral glutamine on whole body carbohydrate storage during recovery from exhaustive exercise. J Appl Physiol. 1999 Jun;86(6):1770-7.
      • Cassetti G, Pinelli M, Bindi M, Bianchi M, Castiglioni M. [Low T3 syndrome and left ventricular diastolic function]. G Ital Cardiol (Rome). 2009 Aug;10(8):553-7. 
      • Exley  C,  Birchall  JD.  The  cellular  toxicity  of  aluminium.  J  Theor  Biol 1992;159:83–98.
      • Geyikoglu  F,  Turkez  H,  Ozhan  Bakir  T,  Cicek  M.  The  genotoxic,  hepa- totoxic,  nephrotoxic,  haematotoxic  and  histopathological  effects  in  rats after aluminium chronic intoxication. Toxicol Ind Health 2012;15.
      • Greenfield JR, Farooqi IS, Keogh JM, Henning E, Habib AM, Blackwood A, Reimann F, Holst JJ, Gribble FM. Oral glutamine increases circulating glucagon-like peptide 1, glucagon, and insulin concentrations in lean, obese, and type 2 diabetic subjects. Am J Clin Nutr. 2009 Jan;89(1):106-13.
      • Gupta  VB,  Anitha  S,  Hegde  ML,  Zecca  L,  Garruto  RM,  Ravid  R,  et  al.  Alu- minium  in  Alzheimer’s  disease:  are  we  still  at  a  crossroad?  Cell  Mol  Life  Sci 2005;62:143–58.
      • Hashimoto K, Ishida E, Miura A, Ozawa A, Shibusawa N, Satoh T, Okada S, Yamada M, Mori M. Human Stearoyl-CoA Desaturase 1 (SCD-1) Gene Expression Is Negatively Regulated by Thyroid Hormone without Direct Binding of Thyroid Hormone Receptor to the Gene Promoter. Endocrinology. 2012 Dec 7.
      • Hätönen KA, Virtamo J, Eriksson JG, Sinkko HK, Sundvall JE, Valsta LM. Protein and fat modify the glycaemic and insulinaemic responses to a mashed potato-based meal. Br J Nutr. 2011 Jul;106(2):248-53. 
      • Iervasi G, Pingitore A, Landi P, Raciti M, Ripoli A, Scarlattini M, L'Abbate A, Donato L. Low-T3 syndrome: a strong prognostic predictor of death in patients with heart disease. Circulation. 2003 Feb 11;107(5):708-13.
      • Liou YA, King DJ, Zibrik D, Innis SM. Decreasing linoleic acid with constant alpha-linolenic acid in dietary fats increases (n-3) eicosapentaenoic acid in plasma phospholipids in healthy men. J Nutr. 2007 Apr;137(4):945-52. 
      • Mitchell ML, Hsu HW, Sahai I; Massachusetts Pediatric Endocrine Work Group. The increased incidence of congenital hypothyroidism: fact or fancy? Clin Endocrinol (Oxf). 2011 Dec;75(6):806-10.
      • Perez  G,  Pregi  N,  Vittori  D,  Di  Risio  C,  Garbossa  G,  Nesse  A.  Aluminium  expo- sure  affects  transferrin-dependent  and  -independent  iron  uptake  by  K562  cells. Biochim  Biophys  Acta  2005;1745:124–30. 
      • Schneuer FJ, Nassar N, Tasevski V, Morris JM, Roberts CL. Association and predictive accuracy of high TSH serum levels in first trimester and adverse pregnancy outcomes. J Clin Endocrinol Metab. 2012 Sep;97(9):3115-22.
      • Seierstad SL, Seljeflot I, Johansen O, Hansen R, Haugen M, Rosenlund G, Frøyland L, Arnesen H. Dietary intake of differently fed salmon; the influence on markers of human atherosclerosis. Eur J Clin Invest. 2005 Jan;35(1):52-9.
      • Waters KM, Miller CW, Ntambi JM. Localization of a negative thyroid hormone-response region in hepatic stearoyl-CoA desaturase gene 1. Biochem Biophys Res Commun. 1997 Apr 28;233(3):838-43. 
      • Whanger P, Vendeland S, Park Y-C & Xia Y. Metabolism of sub-toxic levels of selenium in animals and humans. Annals of Clinical Laboratory Science. 1996;26, 99-113.

      Natural Resistant Starch Reduces Body Fat & Weight Gain in Obesity Prone & Lean Rodents. 8% RS2 Necessary for Weight Loss Effect, Only 4% for Increases in GLP-1 and PYY

      Potatoes! I don't suggest you eat them raw, but if you did they would make a good source of resistant starch. You don't eat potatoes at all? Read the Potato Manifesto and learn why regular potatoes are not as black as they are portrait!
      I guess, you will remember my post on WM-HDP from back in the day. As usual you, as a SuppVersity reader were in the know, way before the ThermiCarbs and its identical clones hit the supplement market. It has however gotten relatively quiet around these purported super starches, which bypass enzymatic breakdown in the small intestine and get converted to short-chain fatty acids (SFCA) in the colon. Why? Well, my best bet is that people expected some sweet junk of which they could eat as much as they wanted with the only side effect being increased muscularity and decreased body fat levels. I am well aware that you knew better than that, but you know how people are: Always on the look-out for the magc pill... or in this case, the magic starch ;-)

      Cutting fat by eating more: The old adage of the "fat burning foods"

      Be that as it may, a soon to be published study by researchers from the Commonwealth Scientific & Industrial Research Organization in Australia confirms: If you exchange a high enough amount of regular carbohydrates with resistant starches (even regular ones, lower resistance to enzymatic breakdown that WM-HPD), this can be a viable tool to shed some body fat.

      Unfortunately, though, the results of the very this study do also suggest that the effectiveness of this regimen will largely depend on (a) your phenotype and (b) your willingness to follow your hopefully not totally messed up satiety response and decrease your caloric intake voluntarily, just as the male Sprague-Dawley, the 'subjects in this study by Belobrajdic, King, Christophersen and Bird.
      Figure 1: Energy intake and final body weight (left) and relative changes in fat mass and total liver weight after 6 weeks on diets with different resistant starch content (based on data from Belobrajdic. 2012)
      Both (a) and (b) could however be major caveats when it comes to the practical realization of similar results in human beings, to whom I would not suggest that they follow a standardized diet with ~15% fat, 19% protein and ~66% carbohydrate, either - regardless of whether they exchange 0%, 4%, 8%, 12% and 16% of the mostly high GI carbs in their diets by resistant starch or not (the values are relative to the weight of the chow).
      Just as raw potatoes, green bananas contain RS-2, the natural form of fermentable resistant starch. When you cook them, the RS2 content is continuously reduced.
      Note: The "2" in "RS2", indicates that RS2 is, contrary to WM-HDP, which belongs to the "RS4" variety of resistant starches, a naturally occurring molecule. And though this is the case for WM-HDP vs. high amylase maize starch, the latter does not necessarily mean that one is more resistant to enzymatic breakdown than the other. You could for example think of special applications, where you want to have a starch that of which roughly 75% will be broken down into glucose in the small intestine, while the other 25% are fermented further down in the large intestine. This would be a synthetic molecule and therefore categorized as RS4, but still relatively easily "digested".
      What I consider especially problematic, though is the fact that people who like to eat, let alone those, who use food as a, if not the only way to experience pleasure in their lives (eating for reward), are going to have a very hard time to satisfy their cravings with this blatant "food". I mean, we all know that "satiety" is not really an issue for most people with weight problems, so it remains questionable to which degree those who actually need a crouch like this will eventually benefit from a resistant starch which exerts its fat loss effect in rodent experiments at least partly via dose-dependent decreases in food intake -- 3%, 6%, 9% and 11% in the 4%, 8%, 12% and 16% resistant starch groups, respectively.

      Ok, I have to admit there is more to it than just eating less

      Figure 2: For the lean rodents, body weight gain and feed efficacy (weight gain per gram of chow) favor different "optimal" RS2 levels.
      Allegedly, the reduction in food intake alone cannot explain the decrease in weight gain in either the obese or lean rodents, but if you take a closer look at the data I plotted in figure 2, it does still become obvious that  the ameliorative effects weight gain in the obesity resistant (i.e. naturally lean) rodents don't obey the "more is more" rule, as the scientists would have it in their abstract:
      "Obesity prone rats (OB) gained less weight with 4, 12 and 16% RS compared to 0% RS, but the effect in obesity resistant [lean] animals was significant only at 16% RS. Irrespective of phenotype, diets  containing ≥8% RS reduced adiposity compared to 0% RS. Energy intake decreased by 9.8 kJ/d for every 4% increase in RS. [...] Insulin sensitivity was not affected by RS." (Belobrajdic. 2012)
      In the naturally lean animals, the "optimal", i.e. the lowest feed efficacy would be achieved with 8% of RS2 in the chow and not as the "≥8% RS" implies with 16% of resistant starch in the diet.

      Ok, I have to admit there is more to it than "minimal feed efficiency"

      In the scientists defense, it must however be mentioned that the plasma lipid and gut / satiety regulating hormone levels they measured did in fact show an almost linear increase with the amount of fermentable resistant starch in the diets (see figure 3). Since Belobrajdic et al. do not provide individual data from the two groups, but settle for a table that will tell you that there were no treatment x group interactions  (this means that the outcome was not different for obesity resistant and prone animals) and a phenotype interaction with the overall outcome was only present for leptin, there is no way to tell for sure.
      Figure 3: Inter-group comparison (not differentiated for lean vs. obese, because there were no significant interactions, except for leptin) of plasma lipid and gut derived hormone levels (data adapted from Belobrajdic. 2012)
      So, with all these "admission" (as in "I have to admit..."), I have to admit *lol* that using high-amyolse starch as a part of your contest prep, maybe to bake pancakes or use it in another food, where the "taste" does not matter that much is could in fact be a viable dietary tool. It won't get you stage ready on its own, though and has one major caveat I have not even mentioned yet: You better make sure you always know where the next clean toilette is. Assuming that those 16% RS2 have the same effect on the volume of your feces as they had on that of the rodents in the study at hand, you may be spending 5-times more time on the loo thhan usually ;-)

      If you can't remember what WM-HDP was, click on the image to go back to the article. Regardless of whether you pick up a natural or an artificial starch, this stuff is not "zero calories"! The high amylose maize starch in the study at hand has 10.45kJ (WM-HDP should be similar), i.e. 2.5kcal/g you will have to make up for by cutting out real foods.
      Bottom line: Assuming that the results from the study at hand translate to human beings the incorporation of resistant starches in your diet seems - at least to a degree at which your bowel can handle it - to entail a lot of health benefits. The problem I see, is that you will have to force down these empty calories instead of eating healthy foods if you want to benefit.

      If you simply add resistant starches (natural or artificial) to your diet, without cutting back on calories, elsewhere, you will become fatter, not leaner.

      You will also have to take into account that adding resistant starch to the high sucrose diet of the rodents in this study will necessarily entail greater benefits than exchanging some tubers, rice, fruit and other non-sugary carbohydrate sources from a healthy diet with resistant starch powder - not to speak of all the beneficial micro-nutrients you will be missing!

      References:
      • Belobrajdic DP, King RA, Christophersen CT, Bird AR. Dietary resistant starch dose-dependently reduces adiposity in obesity-prone and obesity-resistant male rats. Nutr Metab (Lond). 2012 Oct 25;9(1):93.

      Meal Timing, Glycemic Index & Load: Human Study Probes Whether "Hitting Your Macros" Really is All That Counts

      High or low GI, carbs in the morning or in the evning, cookies and dingdongs or all bran. So many questions and way too many answers from rodent studies or studies in obese diabetics... but what are Mr. and Mrs. Healthy Average Joe supposed to do?
      In a recently published paper, Linda M. Morgan, JiangWen Shi, Shelagh M. Hampton and Gary Frost take yet another look on a concept that has lost much of the momentum it had only a decade ago: The GI and / or GL paradigm (GI: glycemic index (abstract unit); GL: glycemic load, i.e. GI / actual amount of food) and combines another paradigm, which is still gathering momentum within the medical science community - the issue of nutrient timing, in order to answer the following questions:
      • Will a large evening energy and carbohydrate load cause an increase in postprandial glucose that is comparable to the same amount of energy and carbohydrates in the morning?
      • Will a high glycaemic excursions in the evening be ameliorated by decreasing the glycaemic index (GI) of the meal?
      Or put simply: Does carbohydrate and energy timing make a difference and can this difference be mitigated by chosing the "right", i.e. low glycemic carbs (e.g. sweet potato vs. white bread)?

      White bread king or all-bran pauper - is that  the question?

      To answer this world-shattering question and actually prove their hypothesis that both, i.e. having carbs in the evening and having those in the form of high glycemic index foods, will have negative consequences on postprandial glycemia, the scientists picked six healthy volunteers (four females, two males; mean age 30 +/- 4.3 years, BMI 21·6 +/- 1.3 kg/m²) and randomly assigned them to a follow one of the four following dietary protocols:
      • Low GI (average GI = 34), with the majority of energy load consumed in the morning (LGI-am)
      • Low GI, with the majority of energy load consumed in the evening (LGI-pm)
      • High GI (average GI = 84), with the majority of energy load consumed in the morning (HGI-am)
      • High GI, with the majority of energy load consumed in the evening (HGI-pm)
      with identical energy content of approx. 8368 kJ (2000 kcal) for the whole day on four individual intervention days with a minimum of 7 days between each of the tests. Breakfast was given at 09.30 hours, lunch at 13.30 hours and the evening meal at 20.30 hours - subjects were at the laboratory for the whole day. Blood samples were taken 2h postprandial and blood glucose levels were monitored continuously via a "MiniMed continuous glucose monitoring system" that senses interstitial glucose by electrochemical detection in subcutaneous interstitial fluid in 5 min intervals.
      Figure 1: Composition of the two test diets (low GI, blue; high GI read) and individual macronutrient breakdown of the test meals the subjects consumed on two seperate occasions (based on Morgan. 2012)
      It does not take a nutrition expert to see that despite the obvious differences with respect to the glycemic index and load, even the allegedly healthy low GI diet with all-bran for dinner* and a macronutrient composition 72% carbohydrates 14% protein and 14% fat is not exactly what the latest research would suggest to be a healthy, let alone a "physique enhancing" diet.

      *note: The scientists probably chose similar foods for breakfast and dinner, because the study design required those to be exchangeable.
      Against that background it is still astonishing how much of a difference...
      • 99% higher fiber content,
      • -60% lower glycemic index (GI), and
      • -63% lower glycemic load (GL)
      ... actually make when it comes to the effect of isocaloric meals with identical macronutrient compositions (see figure 1, right):
      Figure 2: Total area under the curve for interstitial glucose (0–20 h), postprandial plasma insulin, TAG (**mind the text for info a potential typo, here) and NEFA (0–2 h after each meal) in six healthy volunteers following either a high-glycaemic index (HGI) or a low-glycaemic index (LGI) diet, with most of the energy consumed either early (LGI-am, HGI-am) or late (LGI-pm, HGI-pm); all values expressed relative to respective statistical mean (data calculated based on Morgan. 2012)
      I guess I don't have to tell you that the image that emerges here stands in line with the as of late largely ignored glycemic index paradigm the underlying message of which is: It is not simply the amount of sugar you eat,  but rather how fast / hard it hits your blood stream that determines it's impact of on your glucose metabolism. And with respect to the latter, the researchers remark:
      "Glucose and insulin responses showed broadly similar patterns. Both meal timing and quality of carbohydrate affected postprandial glucose and insulin responses (P < 0.01). The area under the glucose and insulin response curves was greatest for the HGI-pm meal regimen. The HGI-pm meal regimen produced a significantly greater postprandial area under the glucose curve than for any of the other three meal regimens (P < 0.05). The postprandial area under the insulin curve was significantly greater than both the LGI regimens (P < 0•05). Postprandial insulin resistance measured by homeostatic model assessment was also significantly greater for the HGI-pm meal than for the two LGI meals (P < 0•05)."
      However, since Morgan, Shi, Hampton and Frost also state that "[p]ostprandial TAG and NEFA levels were not affected by meal timing or carbohydrate quality", I do suspect that there is a typo in table 3 of the original study, where it says that the TAG would be 5.04 mmol/l x h (probably is 6.04) and thus more than 15% lower than the average (TAG levels and insulin resistance usually go hand in hand, so it is really very unlikely that the 5.04 mmol/l x h is correct).

      So what's the take home message here?

      The only question that still has to be answered would be "King or pauper? At least with regard to the former, the best thing I can to is to suggest you read both the posts on "Breaking the Fast" and the "Carbs Past 6PM Posts"  (Part 1 & Part 2). When you have done that your perspective on the importance of breakfast and the purported fallacy of having a large dinner should already have changed. The things that are still left to do is not fool yourself into the false belief that you can pound whatever junk you want (as long as it fits your macros). As the glucose curve of the high GI arms (light color) in the figure above goes to show you, your body won't be happy when you get your "carb macros" from sugary junk.
      Stick to starchy (or "save carbs", if you will) and fruit. Use veggies to fill you up. Use coconut & olive oil and the fats that are already in your meats, fish and dairy products to achieve baseline fat intake of at least 40-50g (all together). Aim for a 100-120g carbohydrate basis, diverge towards the lower side, when your body fat is high, you can't train or you're dieting and towards the higher side, when you are already very lean, have a high training volume, or are trying to build muscle. Complement that with min. 20g of quality protein with each meal. Don't deprive yourself on any nutrient completely and ramp up the total amount of food (at the given ratio) to fulfill your energy requirements.
      In that, avoid processed food sand rely on whole foods, whenever possible (>90%),. Use food supplements* only where it makes sense, e.g. a protein shake post workout (*creatine for example would not be a "food supplement", since you can NEVER get the amounts that are necessary to supersaturate your stores from meat alone) and don't forget to live about all that "dieting" and thinking about the best ways to eat, please!
      So if we assume that my assumption with respect to the triglyceride values in the originally published study are correct and we are simply dealing with a typo here, the next questions which arise here, are...
      1. What is / are the reason/s that the lipid metabolism did not suffer?
      2. How reliable is the HOMA-PP, i.e. the postprandial assessment of insulin sensitivity via the homeostasis model assessment? 
      3. What does all this mean for you? Does meal timing not make a difference and are macros all that counts? 
      As far as (1) goes, the answer is pretty simple: With a diet that was that low in fat and not overabundant in energy (2,000kcal for both diets) any potential the negative downsides on lipid metabolism will take their time to show. The acute ingestion of three high GI meals on a single day or modifications in their distribution across the day won't have much of an effect in healthy individuals, such as the four women and two men in the study at hand (in diabetics and especially patients with NAFLD things will probably look different, though).

      The absence of changes in lipid metabolism after one day on high vs. low GI diets w/ different meal timing patterns yields answer #1 to question (3): If you are healthy the occasional day with junk food won't hurt you as long as you keep the total amount of energy at bay and jump back on the "healthy diet" wagon the very next day.

      On the other hand, if only a single day of high GI food consumption can have such a pronounced impact on the postprandial HOMA levels, this raises the question how reliable this "long term measure" of glucose sensitivity actually is. Obviously, you should not go to the doctor's office and have your HOMA measured, at a morning after a day with three SuperSize Meals from McDonalds (even if you have been fasting after supper at night before, as the participants in the study at hand did) - unless you want a prescription for meformin, of course ;-)

      It would however be likewise unwise to "do everything right" for three (maybe even just one day) before you head to the doctor to get blood drawn, just to be able to rejoice over a HOMA reading that does by no means represent your "normal" insulin sensitivity. This may make your doctor happy and spare you getting ticked off, but could have you run around pre-diabetic unnoticed for months if not years - maybe so long until the first irreversible damage has already been done.

      The high susceptibility of HOMA measures to acute dietary modifications yields answer #2 to question (3): If you want know where you stand, don't make last minute changes to your diet before you get blood drawn. After all, the 90:10 rule (better 95:5 rule ;-) applies both ways - the 90/95 days of consistent eating patterns will decide whether you are lean, muscular and above all healthy or fat, undermuscled and sick.


      References:
      • Morgan LM, Shi JW, Hampton SM, Frost G. Effect of meal timing and glycaemic index on glucose control and insulin secretion in healthy volunteers. Br J Nutr. 2012 Oct;108(7):1286-91.

      A Bomb Calorimeter You Are Not! And That's Why Even the "Adjusted" Energy Values on Food Labels Are 5% Off

      How productive are you?
      A couple of you will probably remember the SuppVersity news from ~1 year ago in which I discussed the revelation that nuts (pistachios and almonds) effectively deliver much less energy (-25%) than the "label" or databases on the Internet will tell you. In other words, while these healthy snacks are still extremely calorie dense, our bodies are not exactly as well equipped as a bomb calorimeter to use that energy.... "bomb calorimeter"? That reminds me of a study I read about a week ago and remembered, today, when I was thinking about writing an article on a topic that is not the 10214124x study on how aerobic exercise is good for elderly obese diabetics, or how extract XYZ from whatever TCM medicine ameliorates the weight gain in obese rodents.

      The study, I was thinking of was conducted at the Department of Nutrition and Dietetics, VU University Medical Centre in Amsterdam (Wierdsma. 2013) and with it investigating the practically highly relevant ability of our tummy to extract and digest (=make bioavailable) the energy from the foods, we eat, it is truely one of a kind. After all, corresponding ...
      "[...] reference values for energy and macronutrient absorption are scarce, especially for adults in an outpatient ambulatory setting, which forms the usual circumstances for dietetic and nutritional interventions or therapy." (Wierdsma. 2013)
      That may seem hilarious in view of the bazillions of money we are spending year by year to figure out "why we are fat", but believe it or not, due to the lack of data we (=science) simply estimate the ‘standard’ energy absorption to be at a level of 95%.

      "We use 95% of the energy we eat" - says who?

      What's the significance of the data? It goes without saying that measuring the energy that is not absorbed is only one of the things that will eventually be necessary to elucidate "how much calories the average dietary carbohydrate-, fat- and protein calorie effectively delivers. This information would yet still have been something we'd have to have before the dozens of studies on the thermic and other metabolically relevant effects of foods had been conducted. Why? Well, at least in those cases (a non-negligible part of the currently available research), where this effect was estimated by simply monitoring the weight gain of the subject over longer time periods, the result critically depends on the amount of energy from carbs, fats and protein that did even make it into the participants organism. If the latter is not 95%, but only 90% and differs from macronutrient to macronutrient, all previous results would be skewed.
      This assumption is based on a single study from the 1970s, in which the amount of non-absorbed healthy adults is reported to be approximately 5% when digesting a standard diet (Southgate. 1970). A study like the one at hand, which was designed to
      "[...] assess faecal energy, subdivided in its major contributors of fat, protein and carbohydrate losses, to quantify standard intestinal absorption capacity in healthy adults on a Western European diet in an ambulatory setting in The Netherlands by using a feasible and unique methodology of intestinal absorptiometry reflecting routine practice." (Wierdsma. 2013)
      Put differently, the scientists wanted to find out (a) whether a calorie is a calorie or maybe just half a calorie and (b) whether this relation is different for the three main macronutrients, carbohydrates, fat and protein. What? Yeah, you'd think we'd know that all along, but aside from certain experts who know exactly "why we are fat", we obviously don't.

      So what did the scientists do?

      The Dutch researchers recruited 25 healthy subjects who had been deliberately picked from the staff of institutional healthcare workers at the facilities the authors are working at all had specific dietetic and healthcare knowledge and were thus skilled in adequately registering nutrient intake and meticulously collecting stools. Yep, you read me right: Over the course of 4 subsequent days, the study participants did not just have to track everything they ate and drink, they also had to collect specimen from what left their bodies "undigested" (=stool samples ;-).
      "All faeces were collected during 72 h (day 2–4), as per the protocol, in specifically designed 5-L buckets. Faeces were weighed (faecal wet weight in g/day ), homogenised and immediately stored at <4°C until analysis. To measure faecal macronutrient content and to calculate intestinal absorption capacity of the healthy subjects, the faeces were analysed for energy, fat and nitrogen content." (Wierdsma. 2013)
      Based on the nutrition data and the stool samples, which had been recorded and collected by all, but two male lazi-a**es who failed to comply to the rigorous requirements of the study protocol the scientists determined the intestinal absorption capacity and the faecal production and composition of male and female subjects separately:
      Figure 1: Relative energy and nutrient absorption in male and female subjects (Wierdsma. 2013)
      As you can see in my plot of the data in figure 1, the mean (SD) intestinal absorption capacity (as a percentage of nutritional intake) was different for fats, proteins and carbohydrates, so that the average subject digested only
      • 89.4% (3.8%) of the total energy their meals provided,
      • 92.5% (3.7%) of the "fat calories",
      • 86.9% (6.4%) of the energy from protein and
      • 87.3% (6.6%) of the calories from the carbohydrates
      in their meals (the values in the brackets denote the corresponding standard deviations). Accordingly, fats are not only the most energetically dense macronutrient, they are also the one healthy individuals digest best an with the lowest inter-personal differences. Overall, ...
      "[w]omen had a statistically significantly lower energy absorption capacity compared to men (88.0% versus 91.8%, respectively, P=0.02). A similar trend was seen for fat and carbohydrate absorption, although this was not statistically significant (P=0.19 and 0.06, respectively)" (Wierdsma. 2013)
      The latter may be surprising, after all, it's usually the women who complain they'd only have to 'look at a piece of cake to gain weightÄ and how unfair it was that men 'can eat whatever they want and still stay relatively lean' (obviously, the latter is not only a function of how much you eat, but also of how much energy you expend and the symbolic piece of cake may well satify 50% of a woman's, but only 25-30% of a man's daily energy requirements).

      What goes in must go out again ;-)

      Figure 2: Daily faecal production (g/day; x-axis) negatively correlated with intestinal energy absorption capacity (% of the energy intake; y-axis) (n = 23) (Pearson’s r = 0.46, P < 0.05 for the total group, r = 0.65, P < 0.05 for women and r = 0.71, P = 0.05 for men; Wierdsma. 2013).
      The mean daily stool production for both sexes was 141 (49) g (29% dry weight) and amounted to an energy loss of 891 (276) kJ, while the individual contribution of  fats, protein and carbohydrates was 5.2 (2.2) g, 10.0 (3.8) g and 29.7 (11.7) g, respectively. Accordingly, the average nutrient contribution to faecal energy content was
      • 23% (10%) for fat,
      • 20% (8%) for proteins and 
      • 57% (23%) for carbohydrates.
      With the stools of the female study participants containing a lower percentage of water than those of men (P<0.05), the energy content per gram of wet faeces was higher in women than in men (P<0.05), while the daily faecal nutrient losses were not statistically significantly different between men and women. Moreover, the scientists observed that ...
      "[...]"the daily faecal production was positively correlated with faecal energy loss in kcal (Pearson’s r =0.80, P<0.001) [and negatively] correlated with intestinal energy absorption capacity (%) (Pearson’s r = 0.46, P<0.05)." (Wierdsma. 2013)
      - an observation that means nothing else, but "the more you eat, the more inclined your body will be to have some energy pass through undigested"... or, in other words: Once you starve yourself, your body will try it's best use each joule of energy it can get! 



      Bottom line: With the main results of the study at hand being that the average calculated standard for energy absorption in healthy Dutch adults is 90% and thus 5% less than it was previously assumed, it should be obvious that the already skewed "energy in vs. energy out" calculations you may have been conducting (against my explicit recommendation!) based on food labels and co are even less reliable than previously assumed.

      "Accept There is No Magic Macronutrient Ratio" (read more)
      On the other hand, the 5% more or less energy won't make a difference anyway, after all a main characteristic of our bodies is that they are no overtly simplistic bomb calorimeters, and their energy demands, as well as uptake depend on the total amount and composition (macronutrients, vitamins, minerals and other co-factors) of what we eat. If you want to gain or lose weight you will therefore not be able to forebear doing a 2-week food-log. Record all the foods and energy containing drinks you consume, sit down and (a) re-evalute the food quality, (b) take stock of the macronutrient ratios and (c) add / subtract foods, not calories or "energy" to establish a 20% caloric defict or 10% caloric surplus as a starting point for your diet / bulk. It's easy, it's bullet proof, but it's less convenient than relying on unreliable formula and databases.

      References:
      • Southgate DA, Durnin JV. Calorie conversion factors. An experimental reassessment of the factors used in the calculation of the energy value of human diets. Br. J. Nutr. 1970; 24:517–535.
      • Van de Kamer JH, Ten Bokkel Huinink H,. Weyers HA. Rapid method for determination of fat in feces. J. Biol. Chem. 1949; 177: 347–355.
      • Wierdsma NJ, Peters JH, van Bokhorst-de van der Schueren MA, Mulder CJ, Metgod I, van Bodegraven AA. Bomb calorimetry, the gold standard for assessment of intestinal absorption capacity: normative values in healthy ambulant adults. J Hum Nutr Diet. 2013 May 6.

      Scientists Probe the Interaction Between Saturated and Unsaturated High Fat Diets and Their Corresponding Carbohydrate Sources (Cornstarch vs. Fructose)

      This add is a perfect example of how saturated fat, in this case lard has always been blamed for the "lard" on ones hips.
      Any hypothesis that tries to blame for our "fat misery" on a single nutrient is short-sighted. After years of fat-bashing, carbophobia and fructose hating in the course of which the situation progressively, we are now seeing the first studies which investigate what the Polish researchers, Adam Jurgoński, Jerzy Juśkiewicz and Zenon Zduńczyk from the Institute of Animal Reproduction and Food Research at the Polish Academy of  Sciences call the "biological interactions among these dietary factors" in their latest paper in the peer-reviewed open-source journal Nutrients (Jurgoński. 2014).

      With the publication of the data of a their latest rodent study, the scientists have already taken the first step to a new, an "interactionist" perspective on the obesogenic effects of saturated vs.unsaturated and simple vs.complex carbohydrates and their interaction with another previously overlooked factor that has gotten quite some attention in the past months: The gut and its inhabitants.

      Goodbye! Nutritional scapegoatism 

      It goes without saying that this model study is nothing but a first step on a long road we still have to travel, but the differential effects the four diets (see Table 1)...
      • Table 1: Composition of the diets.
        the soybean powered high cornstarch diet (OS),
      • the lard-laden high cornstarch diet (LS), 
      • the soybean-powered high fructose diet (OF), and
      • the lard-laden high fructose diet (LF)
      ...had on the health, caecal short-chain fatty acid concentrations, cholesterol and triglyceride levels are revealing, to say the least.
      World premiere! I know it sounds hilarious, but this is actually the first study I have seen that focused on nutrient interactions, instead of individual (macro-)nutrients in diets that are not even suitable to isolate the effects of the nutrient of interest - most prominent example the "high fat diet"  which is high in fat (45% of the energy is the standard; there are yet also "high fat" diets with only 32% of the total energy from fat; Gajda. 2008) but leaves enough room for carbohydrates to complement, some would say "trigger" the obesogenic effects by providing a pro-insulinogenic stimulus that will blunt the oxidation of the dietary fat and help drive it into the cells.
      If you take a closer look at the actual study outcomes, you will see that the answer(s) the study provides are about as complex as its design.

      In contrast to the dietary fat which had no independent effect on any of the measured markers of gut function, the carbohydrate source, i.e. cornstarch vs. fructose lead to significant differences in total small intestinal mass, mean pH of the ileal digesta and the mucosal activity of sucrase, all of which were increase on the high fructose diet.
      Figure 1: Serum lipid levels of the rodents after 4 weeks on obesogenic diets containing different forms of dietary fat and carbohydrate (Jurgoński. 2014)
      Interactive effects were observed for the mass of the cecum itself (the tissue) and the digesta with opposing effects of fructose on when it was administered in conjunction with lard (reductions) vs. soybean oil (increases in cecum mass). Slightly different effects were observed for the short-chain fatty acid composition (SCFA):
      "Both the dietary fats and carbohydrates contributed to changes in the total SCFA concentration in the caecal digesta of rats (p < 0.05 and < 0 0.001, respectively). The highest total SCFA concentration was in group LS, while group OS had a significantly lower concentration (p ≤0.05). Similarly, the acetate concentration in the caecal digesta was influenced both by dietary fats and carbohydrates (p < 0.05 and p < 0.001, respectively) with a similar span of differences among particular groups (p ≤0.05). The type of dietary carbohydrate had significant influence on the propionate and isobutyrate concentrations in the caecal digesta (p < 0.001 and p < 0.05, respectively); however, both dietary factors had an interactive effect on their concentrations (p < 0.05). The highest propionate concentration was observed in the LS and OS group, whereas significantly lower concentration was found in the OF group. The lowest isobutyrate concentration was in group OF and it was significantly higher in group OS (p ≤0.05)." (Jurgoński. 2014)
      The serum lipid profiles were influenced by both, the types of fats and carbohydrates as shown in Figure 1. What's particularly striking, here, is the nasty effects of a combined lard + fructose feeding on the triglyceride levels.

      A similar fat-dependence as for the fructose induced triglyceride boost can be observed for the levels of total and HDL cholesterol, which were increased only by the combination of fructose + saturated fat. In the rodents that received soybean oil with their coke, ... ah, I mean with their fructose, the researchers observed the exact opposite trend and a 5x lower yet similarly increased artherosclerosis risk (as evidenced by the 5x higher atherogenic index).
      Suppversity Suggested Read: "EGGS - A Four-Letter Food Improves Both Cholesterol Particle & Phospholipid Profile + HDL-Driven Lipid Reverse-Transport" | read more
      The results are still difficult to place. The complementary increases in total and HDL cholesterol in the lard + fructose group for example could be interpreted as unproblematic in view of the contemporary social media trend to depict high cholesterol as absolutely irrelevant. In view of the concomitant 2.3x increase in the ratio of triglycerides to HDL-cholesterol, of which we do know for sure that it predicts extensive coronary disease (Luz. 2008), it is still warranted to conclude that the combination of fructose and saturated fats is even worse than the combination of a high fructose intake with unsaturated fats, which had almost no effect on the triglycerides to HDL ratio and left the rodents in the corresponding group with a trig:HDL ratio what was >2.5x lower than that of the lard + fructose rodents.

      Yes, I know - that's only rodent data, there is no information on body weight, or the gut microbiome and even the impact on glucose metabolism wasn't measured (you can predict from the triglyceride levels, though, that the animals lard + fructose diet had the lowest insulin sensitivity), the reason I still spent a whole article on this paper is that this is the kind of study, we'd need if we actually want to understand "why we are fat" from the inexplicably popular (macro-)nutrient perspective... I mean, let's be honest: On the level of food items, the complexity is not a problem and we all know the food items that propel the obesity epidemic, don't we?
      References:
      • Gajda, Angela M. "High fat diets for diet-induced obesity models." A Report for Open Source Diets (2008).