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Mendeley | Further Information

{"title"=>"Metabolic factors limiting performance in marathon runners", "type"=>"journal", "authors"=>[{"first_name"=>"Benjamin I.", "last_name"=>"Rapoport", "scopus_author_id"=>"7102019504"}], "year"=>2010, "source"=>"PLoS Computational Biology", "identifiers"=>{"scopus"=>"2-s2.0-78349235793", "sgr"=>"78349235793", "issn"=>"1553734X", "doi"=>"10.1371/journal.pcbi.1000960", "pmid"=>"20975938", "isbn"=>"1553-7358 (Electronic)\\r1553-734X (Linking)", "pui"=>"359972755"}, "id"=>"3fb2248a-e522-3397-9d68-84818e9839e1", "abstract"=>"Each year in the past three decades has seen hundreds of thousands of runners register to run a major marathon. Of those who attempt to race over the marathon distance of 26 miles and 385 yards (42.195 kilometers), more than two-fifths experience severe and performance-limiting depletion of physiologic carbohydrate reserves (a phenomenon known as 'hitting the wall'), and thousands drop out before reaching the finish lines (approximately 1-2% of those who start). Analyses of endurance physiology have often either used coarse approximations to suggest that human glycogen reserves are insufficient to fuel a marathon (making 'hitting the wall' seem inevitable), or implied that maximal glycogen loading is required in order to complete a marathon without 'hitting the wall.' The present computational study demonstrates that the energetic constraints on endurance runners are more subtle, and depend on several physiologic variables including the muscle mass distribution, liver and muscle glycogen densities, and running speed (exercise intensity as a fraction of aerobic capacity) of individual runners, in personalized but nevertheless quantifiable and predictable ways. The analytic approach presented here is used to estimate the distance at which runners will exhaust their glycogen stores as a function of running intensity. In so doing it also provides a basis for guidelines ensuring the safety and optimizing the performance of endurance runners, both by setting personally appropriate paces and by prescribing midrace fueling requirements for avoiding 'the wall.' The present analysis also sheds physiologically principled light on important standards in marathon running that until now have remained empirically defined: The qualifying times for the Boston Marathon.", "link"=>"http://www.mendeley.com/research/metabolic-factors-limiting-performance-marathon-runners-6", "reader_count"=>286, "reader_count_by_academic_status"=>{"Unspecified"=>5, "Professor > Associate Professor"=>16, "Librarian"=>2, "Researcher"=>47, "Student > Doctoral Student"=>13, "Student > Ph. D. 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ORCID

CrossRef

• http://doi.org/10.1249/MSS.0b013e31827e0fca
• http://doi.org/10.1371/journal.pone.0057602
• http://doi.org/10.3389/fphys.2017.00319
• http://doi.org/10.3390/metabo10030087
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• http://doi.org/10.3389/fphys.2017.00293
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• http://doi.org/10.1007/s00421-013-2670-3
• http://doi.org/10.1016/j.physbeh.2016.03.038

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Europe PMC Database Citations

PubMed Central

• 4289124
• 3439386
• 3583862
• 4048621
• 3356747
• 4415847
• 4039327
• 3781899

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• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/35596d5b-4272-4b4d-8df6-cc34d1d7ef0d", "title"=>"Interesting but flawed", "body"=>"I have posted a detailed response to this article on my blog:\nhttp://www.running-blogs.com/crowther/2010/10/marathoning_made_easy_um_not_r.html", "isRemoved"=>false, "created"=>"2010-10-24T14:43:15Z", "lastModified"=>"2010-10-24T14:43:15Z", "creator"=>{"userId"=>"172739"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pcbi.1000960", "state"=>"published", "journals"=>{"PLoSCompBiol"=>{"journalKey"=>"PLoSCompBiol", "eIssn"=>"1553-7358", "title"=>"PLOS Computational Biology"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2010-10-24T14:43:15Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/07643663-e8e8-472d-a728-83f1c637a36c", "title"=>"Endurance Calculator", "body"=>"A lot of readers have written to ask where they can find the online calculator based on the mathematical model published here. It is not on our website, but can be found here: http://endurancecalculator.com/", "isRemoved"=>false, "created"=>"2010-11-04T18:32:18Z", "lastModified"=>"2010-11-04T18:32:18Z", "creator"=>{"userId"=>"110881"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pcbi.1000960", "state"=>"published", "journals"=>{"PLoSCompBiol"=>{"journalKey"=>"PLoSCompBiol", "eIssn"=>"1553-7358", "title"=>"PLOS Computational Biology"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2010-11-04T18:32:18Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/71def6c4-de26-4b7f-96ab-51ace8b8f3f4", "title"=>"Assessment of the fuel partitioning model", "body"=>"The impact of relative exercise intensity upon use of carbohydrate and fat as fuel is well established. The author has attempted to use such knowledge to lead to practical recommendations; this is to be commended as translation to real world application is very important.\r\n\r\nUnfortunately, the author has incorrectly modeled the relative contribution of fat and carbohydrate (Figure 1). The model is correct at high-intensity exercise but is incorrect at lower-intensity exercise. Indeed it is true that carbohydrate supplies nearly 100% of fuel at 100% VO2max. However, the y-intercepts (left side of graph) are incorrect. The graph implies that the resting fuel mix is approximately 100% fat (RQ = ~0.7). This is only true during prolonged fasting; this is certainly not the fuel mix of a typical marathon runner on the morning of a race. A typical fuel mix at rest is closer to 50% carbohydrate and 50% fat. Fat contributes a bit more as time since the last meal increases, and carbohydrate use will be higher following meals. Because of the dependence upon the timing and size of recent meals, it is difficult to say exactly what a “normal” resting fuel mix is. However, the resting fuel mix used in the modeling for this paper represents that of an individual who is severely carbohydrate-depleted, not that of a glycogen-loaded runner. Therefore, the model proposed by B.I. Rapoport underestimates the importance of carbohydrate during low-intensity exercise.\r\n", "isRemoved"=>false, "created"=>"2010-11-10T19:47:01Z", "lastModified"=>"2010-11-10T19:47:01Z", "creator"=>{"userId"=>"94453"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pcbi.1000960", "state"=>"published", "journals"=>{"PLoSCompBiol"=>{"journalKey"=>"PLoSCompBiol", "eIssn"=>"1553-7358", "title"=>"PLOS Computational Biology"}}}, "replyTreeSize"=>2, "mostRecentActivity"=>"2010-11-21T03:47:10Z", "replies"=>[{"type"=>"REPLY", "parentID"=>10447, "annotationUri"=>"info:doi/10.1371/reply/a4591959-85e1-436c-937f-ec4dc8688782", "title"=>"RE: Assessment of the fuel partitioning model", "body"=>"I think this may be an issue of fuel use by the whole body vs. fuel use by the muscles. It's true that, at rest, some carbohydrate is normally used by the body, but mostly by nonmuscle tissues like the brain. At rest, muscle use of carbohydrate is extremely low. I think Figure 1 is meant to apply to the skeletal muscles rather than the whole body and is a fairly accurate representation of how muscles' fuel use varies with exercise intensity.", "isRemoved"=>false, "created"=>"2010-11-18T21:52:27Z", "lastModified"=>"2010-11-18T21:52:27Z", "creator"=>{"userId"=>"172739"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pcbi.1000960", "state"=>"published", "journals"=>{"PLoSCompBiol"=>{"journalKey"=>"PLoSCompBiol", "eIssn"=>"1553-7358", "title"=>"PLOS Computational Biology"}}}, "replyTreeSize"=>1, "mostRecentActivity"=>"2010-11-21T03:47:10Z", "replies"=>[{"type"=>"REPLY", "parentID"=>34703, "annotationUri"=>"info:doi/10.1371/reply/1a35cfce-1d94-4c04-9b64-8adce3a0be78", "title"=>"RE: RE: Assessment of the fuel partitioning model", "body"=>"What I stated above about the fuel mix utilized at rest generally applies to both the whole body and the muscle. This has been described in studies in which the gas exchange across the leg was measured in addition to the assessment of energy use at the whole body level. For example:\r\nBergman et al. Am J Physiol 276:E106-17, 1999.\r\nFriedlander et al. Am J Physiol 292: E107-16, 2007. ", "isRemoved"=>false, "created"=>"2010-11-21T03:47:10Z", "lastModified"=>"2010-11-21T03:47:10Z", "creator"=>{"userId"=>"94453"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pcbi.1000960", "state"=>"published", "journals"=>{"PLoSCompBiol"=>{"journalKey"=>"PLoSCompBiol", "eIssn"=>"1553-7358", "title"=>"PLOS Computational Biology"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2010-11-21T03:47:10Z", "replies"=>[]}]}]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/89736847-c62a-4052-b9a1-0b8d6a2d9762", "title"=>"Excellent article", "body"=>"Thank you for addressing this important facet of human psychology+physiology. Well done!", "isRemoved"=>false, "created"=>"2011-10-11T00:30:30Z", "lastModified"=>"2011-10-11T00:30:30Z", "creator"=>{"userId"=>"156925"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pcbi.1000960", "state"=>"published", "journals"=>{"PLoSCompBiol"=>{"journalKey"=>"PLoSCompBiol", "eIssn"=>"1553-7358", "title"=>"PLOS Computational Biology"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2011-10-11T00:30:30Z", "replies"=>[]}
• {"type"=>"COMMENT", "annotationUri"=>"info:doi/10.1371/annotation/d4a71a68-fa6f-4fe9-82cd-0892e5bd1e0e", "title"=>"Media Coverage for this Article", "body"=>"The following article represents some of the media coverage that has occurred for this paper:\n\nPublication: The Future of Things\nTitle: Mathematical Model for Carb Loading\nURL: http://thefutureofthings.com/news/11032/mathematical-model-for-carb-loading.html\n\nIf you see any additional coverage of this paper in the press or blogosphere, please reply to this thread and add the link to the article.\n\n", "isRemoved"=>false, "created"=>"2011-10-25T14:27:35Z", "lastModified"=>"2011-10-25T14:27:35Z", "creator"=>{"userId"=>"40493"}, "highlightedText"=>"", "competingInterestStatement"=>{"creatorWasPrompted"=>true, "hasCompetingInterests"=>false}, "parentArticle"=>{"doi"=>"info:doi/10.1371/journal.pcbi.1000960", "state"=>"published", "journals"=>{"PLoSCompBiol"=>{"journalKey"=>"PLoSCompBiol", "eIssn"=>"1553-7358", "title"=>"PLOS Computational Biology"}}}, "replyTreeSize"=>0, "mostRecentActivity"=>"2011-10-25T14:27:35Z", "replies"=>[]}

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• {"id"=>"232084605786791936", "text"=>"Metabolic Factors Limiting Performance in Marathon Runners. http://t.co/ViwAuGe1 #Olympics", "created_at"=>"2012-08-05T12:04:16Z", "user"=>"whereisdaz", "user_name"=>"Dr Darren Saunders", "user_profile_image"=>"http://a0.twimg.com/profile_images/2357663656/0042zokq0jx92kgamwwm_normal.jpeg"}
• {"id"=>"278285624308555777", "text"=>"\"Metabolic Factors Limiting Performance in Marathon Runners\" at http://t.co/XgtIV3VS would be a great bedtime read #rungeek", "created_at"=>"2012-12-10T23:50:37Z", "user"=>"arungupta", "user_name"=>"Arun Gupta", "user_profile_image"=>"http://a0.twimg.com/profile_images/2627568475/6hj1myjhqvva6gaurxml_normal.png"}
• {"id"=>"303148683229274113", "text"=>"@GreenLizard07 AMEN, SISTAH! Now let's get sciencey: http://t.co/AYNYovy1", "created_at"=>"2013-02-17T14:27:32Z", "user"=>"michelleyoc", "user_name"=>"Michelle O'Connor", "user_profile_image"=>"http://a0.twimg.com/profile_images/3052971320/a824ab387e7f9b7eacaf5b7ccba984e3_normal.jpeg"}
• {"id"=>"305244359304048640", "text"=>"Factores metabólicos limitantes del rendimiento en maratonianos.Cálculo d ritmos,cargas,etc según tus características http://t.co/1Xb5FTnkeT", "created_at"=>"2013-02-23T09:15:01Z", "user"=>"nutricionumh", "user_name"=>"Nutrición y Deporte", "user_profile_image"=>"http://a0.twimg.com/profile_images/2402601290/gr6my5eux8awcpz62w5j_normal.jpeg"}
• {"id"=>"309993984288256002", "text"=>"@gaceladeretiro eso está muy bien pero de verdad alguien cree que me voy a leer este tocho? http://t.co/2loo8qjWu4 :D", "created_at"=>"2013-03-08T11:48:19Z", "user"=>"irimadrid", "user_name"=>"Irene R.", "user_profile_image"=>"http://a0.twimg.com/profile_images/3338522472/8da2cc95864faa64bc8f45047d3de015_normal.jpeg"}
• {"id"=>"310506003957440513", "text"=>"http://t.co/4xetthB4WL", "created_at"=>"2013-03-09T21:42:54Z", "user"=>"hattmaldiman", "user_name"=>"Matthew Haldiman", "user_profile_image"=>"http://a0.twimg.com/profile_images/2229663083/546613_10151515647265131_647265130_23775184_1552206269_n_normal.jpg"}
• {"id"=>"310506248716042240", "text"=>"http://t.co/4xetthB4WL @bjonen", "created_at"=>"2013-03-09T21:43:53Z", "user"=>"hattmaldiman", "user_name"=>"Matthew Haldiman", "user_profile_image"=>"http://a0.twimg.com/profile_images/2229663083/546613_10151515647265131_647265130_23775184_1552206269_n_normal.jpg"}
• {"id"=>"323839276867543040", "text"=>"#PLOSCompBio: Metabolic Factors Limiting Performance in Marathon Runners http://t.co/nDooMIVHPp", "created_at"=>"2013-04-15T16:44:34Z", "user"=>"MoreRomNacho", "user_name"=>"Nacho Moreno", "user_profile_image"=>"http://a0.twimg.com/profile_images/1602349695/Monument_Valley_normal.jpg"}
• {"id"=>"372665794142167040", "text"=>"PLOS Computational Biology: Metabolic Factors Limiting Performance in Marathon Runners http://t.co/EUNfHUg5VC", "created_at"=>"2013-08-28T10:23:43Z", "user"=>"kousi552", "user_name"=>"kousi552", "user_profile_image"=>"http://a0.twimg.com/sticky/default_profile_images/default_profile_4_normal.png"}
• {"id"=>"386473421762490368", "text"=>"PLOS Computational Biology: Metabolic Factors Limiting Performance in Marathon Runners http://t.co/CRJOEq3p7z", "created_at"=>"2013-10-05T12:50:18Z", "user"=>"TokenYardClub", "user_name"=>"The Token Yard Club", "user_profile_image"=>"http://a0.twimg.com/profile_images/2135357631/AvantGardeBook_HandOfSean_normal.jpg"}
• {"id"=>"394773529121411072", "text"=>"what if scientist involved in marathon? here is the interesting research paper http://t.co/xOy8GvgFY1", "created_at"=>"2013-10-28T10:31:58Z", "user"=>"ades_daely", "user_name"=>"archimedes daely", "user_profile_image"=>"http://pbs.twimg.com/profile_images/378800000619011136/1e8bf98228d7e1f834908dddb12de486_normal.jpeg"}
• {"id"=>"441135278426976256", "text"=>"Great article on Metabolic Factors limiting running performance. Get assessed by Richard Brennan/SSC @UCSActive http://t.co/olWh6sevPV", "created_at"=>"2014-03-05T08:57:00Z", "user"=>"SportSciConsult", "user_name"=>"Richard Brennan", "user_profile_image"=>"http://pbs.twimg.com/profile_images/3476531523/1725b6598148d4c0b33d58dbef711199_normal.jpeg"}
• {"id"=>"441135376275886080", "text"=>"RT @SportSciConsult: Great article on Metabolic Factors limiting running performance. Get assessed by Richard Brennan/SSC @UCSActive http:…", "created_at"=>"2014-03-05T08:57:24Z", "user"=>"thepauldillon", "user_name"=>"Dill", "user_profile_image"=>"http://pbs.twimg.com/profile_images/421251321933881344/WITnzfpj_normal.jpeg"}
• {"id"=>"441160085579235328", "text"=>"RT @SportSciConsult: Great article on Metabolic Factors limiting running performance. Get assessed by Richard Brennan/SSC @UCSActive http:…", "created_at"=>"2014-03-05T10:35:35Z", "user"=>"UCSActive", "user_name"=>"UCS Active", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2301309349/7bfeaoywrechd7xhqjw2_normal.png"}
• {"id"=>"467211780624633856", "text"=>"anyone interested in carbo-loading here's the science #PLOSCompBio: Metabolic Factors Limiting Performance in Runners http://t.co/DyIx7UfOdU", "created_at"=>"2014-05-16T07:55:43Z", "user"=>"deeptantra", "user_name"=>"Christopher Michaels", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1329853096/Picture_81_normal.png"}
• {"id"=>"517412545662308352", "text"=>"Metabolic factors limiting performance (from a computational perspective): http://t.co/Fol0P85BEm", "created_at"=>"2014-10-01T20:35:38Z", "user"=>"QuiteLT", "user_name"=>"Luca Toldo", "user_profile_image"=>"http://pbs.twimg.com/profile_images/496642879222480896/26YuFl6F_normal.jpeg"}
• {"id"=>"524304607678169089", "text"=>"Metabolic Factors Limiting Performance in Marathon Runners http://t.co/7jJM7iwNQM", "created_at"=>"2014-10-20T21:02:14Z", "user"=>"TheAnalogLife", "user_name"=>"Analog Man™", "user_profile_image"=>"http://pbs.twimg.com/profile_images/487314789379485696/Lqodpxks_normal.png"}
• {"id"=>"532316258641780736", "text"=>"Desde la mañana empece a leer esto http://t.co/IBvhVQxTmP y pues la neta solo le entiendo 2 a 3 cosas :(", "created_at"=>"2014-11-11T23:37:40Z", "user"=>"WebMAAC", "user_name"=>"Sy Parrish ", "user_profile_image"=>"http://pbs.twimg.com/profile_images/512740907053903876/3MgtCtSC_normal.jpeg"}
• {"id"=>"600198561360257024", "text"=>"Metabolic Factors Limiting Performance in Marathon Runners http://t.co/Z0RvsMMblr #marathon #fueling", "created_at"=>"2015-05-18T07:17:42Z", "user"=>"jrr0", "user_name"=>"Ja'far Railton", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1373612205/jrr0-logo-clean_normal.png"}
• {"id"=>"647187534972354561", "text"=>"http://t.co/zAXYMjWRMW @raphaels7 for info", "created_at"=>"2015-09-24T23:15:07Z", "user"=>"chimbo23", "user_name"=>"chimbo23", "user_profile_image"=>"http://pbs.twimg.com/profile_images/472149754219343872/6HX9iiEZ_normal.jpeg"}
• {"id"=>"652937296262635520", "text"=>"Has anybody used this model to plan pacing strategy? http://t.co/6TrbjTj88d", "created_at"=>"2015-10-10T20:02:37Z", "user"=>"SamueleMarcora", "user_name"=>"Samuele Marcora", "user_profile_image"=>"http://pbs.twimg.com/profile_images/527546841684905984/HAu0MImt_normal.jpeg"}
• {"id"=>"652937537347035136", "text"=>"@SamueleMarcora: Has anybody used this model to plan pacing strategy? http://t.co/6TrbjTj88d Even strategy is considered the optimal one", "created_at"=>"2015-10-10T20:03:34Z", "user"=>"SamueleMarcora", "user_name"=>"Samuele Marcora", "user_profile_image"=>"http://pbs.twimg.com/profile_images/527546841684905984/HAu0MImt_normal.jpeg"}
• {"id"=>"652941671387254784", "text"=>"RT @SamueleMarcora: @SamueleMarcora: Has anybody used this model to plan pacing strategy? http://t.co/6TrbjTj88d Even strategy is considere…", "created_at"=>"2015-10-10T20:20:00Z", "user"=>"dannytails", "user_name"=>"Danny Taylor", "user_profile_image"=>"http://pbs.twimg.com/profile_images/3240055520/4f0c9076785d8b877ea0cefd90c7bcf1_normal.jpeg"}
• {"id"=>"702999516673347584", "text"=>"@ReadEatWriteRun No easy ones—This paper derives general formula but I'd need to do some hefty math to get specifics https://t.co/mnzptB34Ti", "created_at"=>"2016-02-25T23:32:00Z", "user"=>"JDruns", "user_name"=>"John Davis", "user_profile_image"=>"http://pbs.twimg.com/profile_images/598361431805833216/khrGmJ4s_normal.jpg"}
• {"id"=>"712426857661075456", "text"=>"@CaloriesProper between this https://t.co/RcL5yWcRf1 and FASTER study, seems lots to do, there was one for HIIT and fat contribution bt lost", "created_at"=>"2016-03-22T23:52:53Z", "user"=>"chimbo23", "user_name"=>"chimbo23", "user_profile_image"=>"http://pbs.twimg.com/profile_images/472149754219343872/6HX9iiEZ_normal.jpeg"}
• {"id"=>"715843798396506113", "text"=>"#PLOSCompBio: Metabolic Factors Limiting Performance in Marathon Runners https://t.co/zxSTHhrpH0 - some great graphics to accompany this", "created_at"=>"2016-04-01T10:10:35Z", "user"=>"SimplyRussBest", "user_name"=>"Russ Best", "user_profile_image"=>"http://pbs.twimg.com/profile_images/689131593110278144/ZgTnmhNg_normal.jpg"}
• {"id"=>"715844568143511552", "text"=>"RT @SimplyRussBest: #PLOSCompBio: Metabolic Factors Limiting Performance in Marathon Runners https://t.co/zxSTHhrpH0 - some great graphics…", "created_at"=>"2016-04-01T10:13:39Z", "user"=>"iamolivergibson", "user_name"=>"Oliver Gibson", "user_profile_image"=>"http://pbs.twimg.com/profile_images/436847607537618944/PaOQ50q4_normal.jpeg"}
• {"id"=>"733319014978588672", "text"=>"Just a little #lunchtimereading - 10 days to go! #melandkaterunvt #vermontcitymarathon https://t.co/veBIWxc0Sh @PLOSCompBiol", "created_at"=>"2016-05-19T15:30:52Z", "user"=>"BooksMel", "user_name"=>"Melissa Fulkerson", "user_profile_image"=>"http://pbs.twimg.com/profile_images/583994186971623424/vAYX8hjP_normal.jpg"}
• {"id"=>"846551311436926976", "text"=>"ONLY FOR PRO!\nhttps://t.co/FOGjCUSTPL", "created_at"=>"2017-03-28T02:35:35Z", "user"=>"componentesh", "user_name"=>"mikiaandy", "user_profile_image"=>"http://pbs.twimg.com/profile_images/842177514399240195/koAdup3I_normal.jpg"}
• {"id"=>"849918616493576192", "text"=>"What should your #marathon target time be? https://t.co/TtKejra5kG https://t.co/fI9T2l0dc7 #ThrowbackThursday #WorldPhysicalActivityDay", "created_at"=>"2017-04-06T09:36:03Z", "user"=>"PLOSCompBiol", "user_name"=>"PLOS Comp Biol", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2435436417/hg8nh61i55aibgx0hcvp_normal.jpeg"}
• {"id"=>"849936907329036291", "text"=>"RT @PLOSCompBiol: What should your #marathon target time be? https://t.co/TtKejra5kG https://t.co/fI9T2l0dc7 #ThrowbackThursday #WorldPhysi…", "created_at"=>"2017-04-06T10:48:44Z", "user"=>"sam6ernard", "user_name"=>"Samuel Bernard", "user_profile_image"=>"http://pbs.twimg.com/profile_images/641875703542190080/7O9P0Kvm_normal.jpg"}
• {"id"=>"850063057061466112", "text"=>"#WorldPhysicalActivityDay How metabolic factors affect marathon runner performance https://t.co/gsvH7FD9NC Rapoport… https://t.co/ezkmk8AfTW", "created_at"=>"2017-04-06T19:10:00Z", "user"=>"PLOSCompBiol", "user_name"=>"PLOS Comp Biol", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2435436417/hg8nh61i55aibgx0hcvp_normal.jpeg"}
• {"id"=>"850064128647495680", "text"=>"RT @PLOSCompBiol: #WorldPhysicalActivityDay How metabolic factors affect marathon runner performance https://t.co/gsvH7FD9NC Rapoport et al…", "created_at"=>"2017-04-06T19:14:16Z", "user"=>"widdowquinn", "user_name"=>"Leighton Pritchard", "user_profile_image"=>"http://pbs.twimg.com/profile_images/2361874280/z7co0zrwaump7iptht1s_normal.jpeg"}
• {"id"=>"850219351487651840", "text"=>"RT @PLOSCompBiol: #WorldPhysicalActivityDay How metabolic factors affect marathon runner performance https://t.co/gsvH7FD9NC Rapoport et al…", "created_at"=>"2017-04-07T05:31:04Z", "user"=>"AngelGarcia74", "user_name"=>"Angel Garcia", "user_profile_image"=>"http://pbs.twimg.com/profile_images/1444864533/ngc602_hst_c720_normal.jpg"}
• {"id"=>"862137116024852480", "text"=>"Metabolic Factors Limiting Performance in Marathon Runners https://t.co/F6rEvVuYe5", "created_at"=>"2017-05-10T02:48:00Z", "user"=>"jerodkillick", "user_name"=>"Jerod Killick ?", "user_profile_image"=>"http://pbs.twimg.com/profile_images/711726489897607168/hlEVXLu2_normal.jpg"}
• {"id"=>"862393305136586758", "text"=>"Metabolic Factors Limiting Performance in Marathon Runners https://t.co/k8hyMLIxzb", "created_at"=>"2017-05-10T19:46:01Z", "user"=>"YetiPodcast", "user_name"=>"Svelte Yeti Podcast", "user_profile_image"=>"http://pbs.twimg.com/profile_images/775124151870697472/u4Odzk0I_normal.jpg"}
• {"id"=>"893133608491167744", "text"=>"Metabolic Factors Limiting Performance in Marathon Runners https://t.co/VOZUvcJYAL", "created_at"=>"2017-08-03T15:37:00Z", "user"=>"YetiPodcast", "user_name"=>"Svelte Yeti Podcast", "user_profile_image"=>"http://pbs.twimg.com/profile_images/867927730762821632/Y23-Yina_normal.jpg"}
• {"id"=>"927527312744214528", "text"=>"Interesting research \"Metabolic Factors Limiting Performance in Marathon Runners\" 2010\nhttps://t.co/2V5rkzNpOU", "created_at"=>"2017-11-06T13:25:18Z", "user"=>"jeremygouillon", "user_name"=>"J?r?my gouillon", "user_profile_image"=>"http://pbs.twimg.com/profile_images/626134167051476992/Bo5_vwpo_normal.jpg"}
• {"id"=>"927833763152789504", "text"=>"RT @jeremygouillon: Interesting research \"Metabolic Factors Limiting Performance in Marathon Runners\" 2010\nhttps://t.co/2V5rkzNpOU", "created_at"=>"2017-11-07T09:43:02Z", "user"=>"ManoliyoJimenez", "user_name"=>"Manu Jim?nez", "user_profile_image"=>"http://pbs.twimg.com/profile_images/917284468297265153/L6LDPlLz_normal.jpg"}
• {"id"=>"950819408489873411", "text"=>"@tigriscraig @ProfTimNoakes https://t.co/fuGy9dnbt6\nThis is an interesting paper with some cool models on in-race f… https://t.co/83zb4mdofo", "created_at"=>"2018-01-09T19:59:47Z", "user"=>"cwiggs5", "user_name"=>"Chad Wiggins", "user_profile_image"=>"http://pbs.twimg.com/profile_images/557020782732529664/qhJU_p4e_normal.jpeg"}
• {"id"=>"951843214042062848", "text"=>"RT @cwiggs5: @tigriscraig @ProfTimNoakes https://t.co/fuGy9dnbt6\nThis is an interesting paper with some cool models on in-race fueling and…", "created_at"=>"2018-01-12T15:48:01Z", "user"=>"cwiggs5", "user_name"=>"Chad Wiggins", "user_profile_image"=>"http://pbs.twimg.com/profile_images/557020782732529664/qhJU_p4e_normal.jpeg"}

Wikipedia | Further Information

• {"title"=>"File:Endurance, runners must race long distances without 'hitting the wall,' exhausting carbohydrate reservoirs that fuel their working muscles.tif", "url"=>"http://commons.wikimedia.org/wiki/File:Endurance,_runners_must_race_long_distances_without_'hitting_the_wall,'_exhausting_carbohydrate_reservoirs_that_fuel_their_working_muscles.tif", "timestamp"=>"2016-11-24T21:59:57Z"}

Wordpress.com | Further Information

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Figshare

• {"files"=>["https://ndownloader.figshare.com/files/822531"], "description"=>"<p>Fractional usage of carbohydrate (plasma glucose plus muscle glycogen, blue filled curve, ) and fat (plasma free fatty acids plus muscle triglycerides, red filled curve, ) are shown as functions of relative exercise intensity, . (Based on the work of Romijn and colleagues: Points plotted correspond to data points from the 1993 study <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000960#pcbi.1000960-Romijn1\" target=\"_blank\">[24]</a>, and corresponding error bars are computed as described in the <a href=\"http://www.ploscompbiol.org/article/info:doi/10.1371/journal.pcbi.1000960#s4\" target=\"_blank\">Methods</a> section.)</p>", "links"=>[], "tags"=>["metabolic", "fuels", "depends"], "article_id"=>492905, "categories"=>["Physiology", "Mathematics", "Medicine"], "users"=>["Benjamin I. Rapoport"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000960.g001", "stats"=>{"downloads"=>3, "page_views"=>15, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Relative_use_of_fat_and_carbohydrate_as_metabolic_fuels_depends_on_exercise_intensity_/492905", "title"=>"Relative use of fat and carbohydrate as metabolic fuels depends on exercise intensity.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 22:43:16"}
• {"files"=>["https://ndownloader.figshare.com/files/822771"], "description"=>"<p>Computed distance athletes can run before completely depleting glycogen reserves (‘hitting the wall’), as a function of running intensity (expressed as a percent of ), relative leg muscle mass (leg muscle mass as a fraction of total body mass), and muscle glycogen density. The distance an athlete can run before ‘hitting the wall’ decreases with increasing levels of exertion, and as the shaded rectangular region labeled ‘Will “Hit the Wall”’ indicates, if this distance is less than 42.195 kilometers (26 miles and 385 yards) then the runner will not be able to complete a marathon without experiencing complete glycogen depletion (at least not without refueling midrace). Each colored curve corresponds to a particular density of muscle glycogen, as labeled (Red, 40; Orange, 60; Yellow, 80; Green, 100; Blue, 120; Purple, ). The colored curves each correspond to athletes whose leg muscles constitute 21.4% of total body mass and are loaded with glycogen at a particular density (relative liver mass has been assumed constant at 2.5% of total body mass, and liver glycogen density has been assumed maximized at ); a shaded region around each colored curve fills the region corresponding to relative leg muscle masses of 15% to 25% total body mass. Darker shading indicates overlapping regions and identical failure distances for different sets of physical parameters: The area of densest shading straddles the 21-mile line for athletes running at intensities of 80% to 95% , indicating that many different athletic builds and levels of glycogen loading are subject to failure at these intensities around mile 21, which has been empirically identified as the distance at which marathon runners most commonly ‘hit the wall.’ By contrast, few runners will ‘hit the wall’ before mile 11, or when running a marathon at less than 55% .</p>", "links"=>[], "tags"=>["endurance"], "article_id"=>493146, "categories"=>["Physiology", "Mathematics", "Medicine"], "users"=>["Benjamin I. Rapoport"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000960.g003", "stats"=>{"downloads"=>1, "page_views"=>11, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Distance_to_8216_The_Wall_8217_for_endurance_runners_/493146", "title"=>"Distance to ‘The Wall’ for endurance runners.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 22:44:35"}
• {"files"=>["https://ndownloader.figshare.com/files/822641"], "description"=>"<p>Computed approximations of total energy consumed as carbohydrate over the course of a marathon, as a function of running speed, in runners with various aerobic capacities. Each colored line corresponds to a particular value of aerobic capacity, , in terms of milliliters of oxygen per kilogram body mass per minute, as labeled (Dark Orange, 35; Orange, 40; Yellow, 45; Light Yellow, 50; Light Green, 55; Green, 60; Aqua, 65; Light Blue, 70; Blue,75; Purple, 80; Violet, 85; Magenta, 90; Red, ). The vertical scale is expressed in terms of kilocalories of energy consumed per kilogram of body mass over 42.195 km (26 miles and 385 yards), the length of a marathon; the corresponding total energy consumption for runners of various masses is shown along the horizontal trend lines, beneath the values of body mass labeled along the top edge of the plot. Running speed is expressed in kilometers per hour along the lower horizontal axis, and as total time to complete a marathon at the corresponding speed along the upper horizontal axis. The dashed, horizontal red lines show the estimated maximum energy storage capacity in runners with maximally glycogen-loaded livers and glycogen-loaded muscles in a state of maximal glycogen supercompensation (144 kcal glycogen per kilogram leg muscle), for whom the leg muscles powering running constitute the indicated percentages of total body mass (right-sided vertical axis). The shaded region indicates the range of supranormal energy storage capacities available to a typical male runner, whose leg muscles constitute approximately 21.4% of his total body mass; the boundaries of the shaded region correspond to typical and maximal values of muscle glycogen density for trained endurance athletes (80 and 144 kcal glycogen per kilogram leg muscle, respectively). See the text for a detailed explanation.</p>", "links"=>[], "tags"=>["glycogen", "constrain", "maximal", "marathon"], "article_id"=>493013, "categories"=>["Physiology", "Mathematics", "Medicine"], "users"=>["Benjamin I. Rapoport"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000960.g002", "stats"=>{"downloads"=>1, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_When_does_glycogen_storage_capacity_constrain_maximal_marathon_speed_/493013", "title"=>"When does glycogen storage capacity constrain maximal marathon speed?", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 22:43:54"}
• {"files"=>["https://ndownloader.figshare.com/files/822867"], "description"=>"<p>Computed approximations of (in terms of milliliters of oxygen per minute per kilogram body mass), as a function of estimated fraction of maximum heart rate while running at a given speed, are shown as a set of colored curves. Each line corresponds to a particular running speed (Orange, 4 mph (); Light Green, 5 mph (); Green, 6 mph (); Dark Green, 7 mph (); Light Blue, 8 mph (); Blue, 9 mph (); Dark Blue, 10 mph (); Purple, 11 mph (); Magenta, 12 mph (); Red, 13 mph ()). See the text for a detailed explanation.</p>", "links"=>[], "tags"=>["aerobic"], "article_id"=>493247, "categories"=>["Physiology", "Mathematics", "Medicine"], "users"=>["Benjamin I. Rapoport"], "doi"=>"https://dx.doi.org/10.1371/journal.pcbi.1000960.g004", "stats"=>{"downloads"=>6, "page_views"=>13, "likes"=>0}, "figshare_url"=>"https://figshare.com/articles/_Estimating_the_aerobic_capacity_of_a_typical_runner_/493247", "title"=>"Estimating the aerobic capacity of a typical runner.", "pos_in_sequence"=>0, "defined_type"=>1, "published_date"=>"2013-02-20 22:45:08"}

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F1000Prime