Lisäsisällöt – Työ

Tervetuloa työ-osion lisätietosivustolle. Täältä saat kirjan sisältöön liittyen lisätietoja, tuotesuosituksia, välinelinkkejä ja lähdeluettelon. Toimituksen suositukset on merkitty kolmella sydämellä (❤❤❤).

Sisällysluettelo (pikalinkit)

  1. Fysiologiset järjestelmät
  2. Muisti
  3. Matkustaminen
  4. Teknologiset apuvälineet
  5. Videot
  6. Podcastit
  7. Kirjat
  8. Geenitestit
  9. Lähteet
  10. Palaute ja kommentit

Fysiologiset järjestelmät

Verensokerin säätely

Pätkäpaasto

Ketoosi

Verenpaineen säätely

Muisti

Matkustaminen

Teknologiset apuvälineet

Tavarat ja laitteet

Ajanhallinta & organisointi

Opiskelu & tietojenkäsittely

Delegointi

Tietoturva

Viihde

Videot

Podcastit

Kirjat

  • David Allen: Getting Things Done: The Art of Stress-Free Productivity (❤❤❤)
  • Charles Duhigg – The Power of Habit (❤❤❤)
  • Stephen R. Covey – 7 Habits of Highly Effective People
  • Timothy Ferriss – Four Hour Workweek (❤❤❤)
  • Moretimer J. Adler & Charles Van Doren – How to Read a Book
  • By Oddbjorn – Memo
  • Joshua Foer – Moonwalking with Einstein (❤❤❤)
  • Josh Waitzkin – The Art of Learning (❤❤❤)
  • Timothy Ferriss – The Four Hour Chef
  • Richard Koch – The 80/20 principle

Geenitestit (painetusta kirjasta poistettu kappale)

Tässä kappaleessa käsitellään lyhyesti niitä geneettisiä tekijöitä, jotka vaikuttavat Työ-osiossa esiteltyihin systeemeihin (verensokeri, verenpaine ja muisti). Verensokerin säätelyyn vaikuttavia geenejä on esitelty myös Biohakkerin käsikirjan Ravinto- ja Liikunta-osioissa. Näitä ovat esimerkiksi ACE, PPARGC1A, TCF7L2 ja PPRG2.

Geenitutkimuksen kehittyessä löydetään jatkuvasti uusia geenejä, jotka vaikuttavat esimerkiksi verenpaineen säätelyyn. Vuonna 2014 julkaistussa meta-analyysissä tutkittiin yli 87 000 eurooppalaisen ihmisen perimää, minkä perusteella tunnistettiin 11 uutta geeniä, jotka vaikuttavat verenpaineen säätelyyn. Tutkijat arvelevat, että tällä voi jatkossa olla vaikutusta uusien lääkkeiden ja terapiamuotojen kehittämiseksi verenpainetaudin hoitoon.(346)

 

Verensokerin säätelyyn vaikuttavia geenejä

MC4R

MC4R-geeni säätelee tyypin 4 melanokortiinireseptorin toimintaa. Reseptoriin sitoutuu alfa-melanosyyttiä stimuloiva hormoni (α-MSH), joka vaikuttaa elimistössä muun muassa nautitun ravinnon määrään. Geenin polymorfismin rs17782312 genotyyppi CC on yhteydessä lisääntyneeseen metabolisen oireyhtymän riskiin.(347)

IRS1

IRS1-geeni säätelee insuliinireseptorisubstraatti 1:tä (IRS1), joka on yksi keskeisimmistä insuliinin aineenvaihdunnallista signaalia välittävistä proteiineista. IRS1:n pistemutaatiota ja polymorfismeja käsittelevät tutkimukset ovat osittain ristiriitaisia, mutta ilmeisen selviä yhteyksiä ruokavalion vaikutuksesta insuliinin säätelyyn eri genotyypeillä on olemassa. Geenin polymorfismin G972R (rs1801278) GA-genotyyppi on yhteydessä insuliiniresistenssiin erityisesti runsassuolaisen ruokavalion yhteydessä. Samalla riski sairastua sokeritautiin on kohonnut, jos verenpainetauti on jo todettu.(348)

IRS1-geenin polymorfismin rs7578326 genotyyppi GG ja polymorfismin rs2943641 genotyyppi TT ovat yhteydessä pienempään insuliiniresistenssiriskiin sekä pienentyneeseen riskiin sairastua tyypin 2 diabetekseen ja metaboliseen oireyhtymään. Alentunut riski oli huomattava, kun ruokavaliossa tyydyttyneen rasvan suhde hiilihydraatteihin oli matala (< 0.25). Lisäksi ainakin Puerto Ricon väestöllä suoritetussa tutkimuksessa IRS1-geenin polymorfismin rs7578326 G-alleelin kantajilla oli pienentynyt riski metaboliseen syndroomaan, kun ravinnon kertatyydyttymättömien rasvahappojen saanti oli keskiarvoa alhaisempi. (349)

CRP

CRP-geeni säätelee C-reaktiivisen proteiinin toimintaa, joka on akuutin tulehduksen keskeisin markkeri. Sitä käytetään muun muassa ennustamaan sydän- ja verisuonitautien kehittymistä. Geenin polymorfismin -732A/G genotyyppi GG paransi merkittävästi fyysisen harjoittelun tuomaa insuliiniherkkyyttä.(350)

LIPC

LIPC-geeni säätelee maksan lipaasin (engl. hepatic lipase) toimintaa, joka hydrolysoi lipoproteiinien triglyseridejä ja fosfolipidejä. Se muun muassa muuntaa IDL-molekyylejä (intermediate density lipoprotein) LDL-molekyyleiksi. Geenin polymorfismin -514C/T genotyyppi TT on yhteydessä merkittävästi kohonneeseen verensokeritasoon kaksi tuntia oraalisen glukoosinsietokokeen jälkeen sekä kohonneeseen paastoinsuliinipitoisuuteen ja kolesteroliarvoihin (kokonaiskolesteroli, HDL ja triglyseridit). Negatiivista vaikutusta insuliiniresistenssiiin ei kuitenkaan havaittu.(351) Geenin polymorfismin G-250A genotyyppi GG on yhteydessä suurentuneeseen riskiin sairastua tyypin 2 diabetekseen.(352)

VDR

VDR-geeni säätelee D-vitamiinireseptorin toimintaa. Reseptoreita on elimistön jokaisessa solussa, mikä kuvastaa D-vitamiinin merkitystä solutasolla. Geenin polymorfismin Fok1 genotyyppi FF on yhteydessä insuliiniherkkyyden alentumiseen ja alttiuteen sairastua tyypin 2 diabetekseen.(353) Tämä genotyyppi myös reagoi hyvin D-vitamiinin nauttimiseen ravintolisänä, mikä laski riskiä insuliiniresistenssin kehittymiselle.(354) Nuorilla miehillä tehdyn tutkimuksen perusteella VDR-geenin polymorfismin Bsm1 genotyyppi BB on yhteydessä korkeampiin paastoverensokeritasoihin (< 5.55 mmol/l). Tätä ei kuitenkaan havaittu kyseistä genotyyppiä kantavilla miehillä, jotka olivat fyysisesti erittäin aktiivisia.(355)

ADIPOQ/APM1

ADIPOQ- tai APM1-geeni säätelee adiponektiini-hormonin toimintaa. Se osallistuu muun muassa rasvahappojen hapettamiseen, glukoosiaineenvaihduntaan, insuliiniherkkyyteen ja energia-aineenvaihdunnan säätelyyn. Lihavuus on tutkimuksissa yhdistetty matalaan adiponektiini-tasoon verenkierrossa. Geenin polymorfismin +45T>G (rs2241766) genotyyppi TT ja polymorfismin +276G>T (rs266729) genotyyppi GG ovat yhteydessä selvästi alentuneisiin adiponektiinitasoihin ja lisääntyneeseen insuliiniresistenssiin. Näiden kahden polymorfismin haplotyyppi TG on vahvimmin yhteydessä heikentyneeseen insuliiniresistenssiin.(356)

Myös geenin polymorfismin G-11391A genotyyppi GA (ja edellä kuvattu polymorfismin +45T>G genotyyppi GG) on erityisesti naisilla yhteydessä kohonneisiin adiponektiinitasoihin ja hyperglykemian kehittymiseen kolmen vuoden seurannan aikana.(357) Ruokavaliomuutoksella (kasvisten lisääminen ja korkean GI:n hiilihydraattien korvaaminen matalilla) sekä säännöllisellä kävelemisellä on tehokas adiponektiinitasoja laskeva vaikutus ylipainoisilla geenin polymorfismien (ks. yllä) kantajilla. Normaalipainoisilla ihmisillä tätä muutosta ei kuitenkaan ole havaittu.(358)

 

Verenpaineen säätelyyn vaikuttavia geenejä

AGT

AGT-geeni säätelee angiotensinogeenin toimintaa. Angiotensinogeeni on maksan tuottama proteiini, joka muuntaa munuaisten tuottamaa reniiniä angiotensiini I:ksi. Tämä on osa RAA-järjestelmää, joka säätelee verenpainetta. Geenin polymorfismin M235T genotyyppi TT:n on todettu olevan yhteydessä kohonneeseen diastoliseen verenpaineeseen miehillä(359) mutta pienempään riskiin sairastua verenpainetautiin naisilla.(360) Genotyypin vaikutus verenpaineeseen on riippuvainen väestön alkuperästä ja sukupuolesta.

ATP6AP2

ATP6A2- eli (pro)reniinin reseptori-geeni säätelee reniini-reseptorin toimintaa. Se edistää angiotensinogeenin muuntumista angiotensiini I:ksi. Eläinkokeiden perusteella pistemutaatiot (SNP) geenissä voivat altistaa verenpainetaudin kehittymiselle.(361) Geenin polymorfismin IVS5+169C>T C-alleelin kantajilla oli alhaisempi verenpaine kuin T-alleeleja kantavilla. Tämä oli myös yhteydessä matalampaan aldosteronipitoisuuteen verenkierrossa.(362)

CYP11B2

CYP11B2-geeni säätelee muun muassa aldosteronisyntaasi-entsyymin toimintaa, joka osallistuu aldosteroni-hormonin biosynteesiin. Aldosteroni eli nk. suolahormoni säätelee elimistössä suolatasapainoa ja verenpainetta. Geenin polymorfismin C-344T genotyyppi CC on yhteydessä hieman alentuneeseen riskiin sairastua verenpainetautiin genotyyppi TT:hen verrattuna.(363) Japanilaisilla miehillä tehdyn tutkimuksen perusteella saman polymorfismin genotyypeillä CT ja TT oli riski verenpainetaudin kehittymiseen, mikäli henkilö nauttii runsaasti suolaa.(364)

VEGF

VEGF-geeni säätelee verisuonten endoteelin kasvutekijöiden (VEGF) toimintaa verisuonissa. Nämä kasvutekijät aktivoituvat muun muassa loukkaantumisen tai kovan fyysisen harjoittelun jälkeen. Verenpainetautia sairastavilla on todettu plasmassa merkittävästi koholla oleva VEGF-taso. Geenin polymorfismien 634G>C (C-alleeli) ja 936C>T (T-alleeli) ovat merkittävästi yleisempiä verenpainetautia sairastavilla ihmisillä.(365)

NOS (1,2,3)

NOS-geenit säätelevät typpioksidisyntaaseja (1,2 ja 3). Ne ovat entsyymejä, jotka katalysoivat typpioksidin muodostumista arginiinista. Typpioksidi vaikuttaa moniin fysiologisiin ilmiöihin elimistössä kuten verisuonten laajenemiseen. Puutteellinen typpioksidin saatavuus verisuonten sisäkalvolla eli endoteelissa altistaa verenpainetaudille.(366)

NOS1-geenin polymorfismin rs3782218 genotyyppi CC on yhteydessä verenpainetaudin ja sepelvaltimotaudin lisääntyneeseen riskiin. NOS2-geenin polymorfismin rs2255929 genotyyppi AT on yhteydessä hieman suurentuneeseen verenpainetaudin riskiin ja NOS3-geenin polymorfismin rs3918227 genotyyppi CC merkittävästi lisääntyneeseen verenpainetaudin riskiin.(367)

 

Muistin toimintaan vaikuttavia geenejä

COMT & ANKK1

COMT-geeni säätelee katekoliamiini-O-metyylitransferaasi-entsyymin toimintaa, joka hajottaa katekoliamiineja kuten esimerkiksi dopamiinia prefrontaalisella aivoalueella. Vastaavasti DRD2/ANKK1-geenikompleksi vaikuttaa dopamiinireseptoreiden tiheyteen aivojen tyvitumakkeessa (engl. striatum). COMT-geenin polymorfismi rs4680 (Met/Met) yhdessä DRD2/ANKK1-geenin polymorfismin Taq-Ia (A1+) kanssa on havaittu olevan yhteydessä parantuneeseen visuaaliseen työmuistiin. Tämä liittyy oleellisesti dopamiinin hidastuneeseen poistumiseen prefrontaaliselta aivoalueelta.(368)

CACNA1C

CACNA1C-geeni säätelee L-tyypin kalsium-kanavan (Cav1.2) alayksikköä alfa-1C. Kalsium-kanavat ovat merkittävässä roolissa sähköisen aktiivisuuden muuntamisessa biokemiallisiksi tapahtumiksi esimerkiksi hermosoluissa. Kyseisen geenin polymorfismi rs1006737 on yhteydessä heikentyneeseen työmuistiin terveillä ihmisillä, mutta ei kaksisuuntaista mielialahäiriötä sairastavilla.(369) Saman polymorfismin on todettu olevan yhteydessä myös heikentyneeseen oppimiseen terveillä ihmisillä.(370)

BDNF

BDNF-geeni säätelee aivoperäisen neurotrofisen tekijän (BDNF) toimintaa. BDNF on kasvutekijä, joka auttaa uusien hermosolujen erilaistumisessa sekä jo olemassa olevien hermosolujen eloonjäämisessä. Sen rooli on keskeinen muistin toiminnassa erityisesti hippokampuksessa ja aivokuorella.(371) Geenin polymorfismin rs6265 (Val66Met) genotyypin Val/Val on todettu olevan yhteydessä parempaan elämänkertamuistiin vanhemmilla ihmisillä vain, mikäli he olivat fyysisesti aktiivisia.(372)

OXTR

OXTR-geeni säätelee oksitosiini-reseptorin toimintaa. Oksitosiinilla on tärkeä merkitys muun muassa kiintymisen, kasvomuistin ja kasvojen ilmeiden erottelukyvyn kannalta. Geenin polymorfismi rs237887, genotyyppi A/A on yhteydessä heikentyneeseen kasvomuistiin ja sosiaalisuuteen.(373) Vastaavasti genotyyppi G/G on yhteydessä lisääntyneeseen sosiaalisuuteen ja kiintymiseen.(374)

GRIN2B

GRIN2B (tai NR2B) geeni säätelee NMDA-reseptorin alayksikön 2 toimintaa. NMDA-reseptori on yksi tärkeimmistä välittäjäaineiden reseptoreista aivoissa. Sen toiminta on yhteydessä erityisesti pitkäaikaispotentiaatioon (muisti ja oppiminen). Geenin polymorfismin rs7301328 (C366G) genotyyppi CC on yhteydessä heikentyneeseen verbaaliseen muistiin (esimerkiksi lueteltujen sanojen muistamisessa).(375)

ADRA2B

ADRA2B-geeni säätelee alfa 2b-adrenergisen reseptorin toimintaa. Geenin niin sanottuun poistumaan liittyvä variantti (engl. deletion variant), jossa reseptoria koodaavasta geenistä poistetaan kolme glutamiinihappoa (SNP:t rs28365031, rs29000568 ja rs4066772), on yhteydessä parempaan tunnemuistiin(376) ja tilanteiden negatiivisten aspektien havaitsemiseen.(377)

GCR

GCR-geeni säätelee glukokortikortikoidi-reseptorin (GR) toimintaa soluissa. Stressihormoni kortisoli ja muut glukokortikoidit kiinnittyvät glukokortikoidireseptoriin. Näitä on todettu olevan erityisen runsaasti prefrontaalisella aivoalueella. Geenin polymorfismin rs6198 (genotyyppi 9-beta A3669G) G-alleeli on yhteydessä parantuneeseen reaktioaikaan naisilla mutta ei miehillä.(378)

Kirjan lähteet

  1. Charbonneau, D. & Dornhaus, A. (2015). Workers ´specialized´on inactivity: Behavioral consistency of inactive workers and their role in task allocation. Behavioral Ecology and Sociobiology 69 (9): 1–14.
  2. Faragher, E, & Cass, M. & Cooper, C. (2005). The relationship between job satisfaction and health: a meta-analysis. Occupational and Environmental Medicine 62 (2): 105–112.
  3. Ahola, K. & Tuisku, K. & Rossi, H. (2015). Työuupumus (burnout). Lääkärikirja Duodecim. [luettu: 9.5.2016]
  4. Maslach, C. & Schaufeli, W. & Leiter, M. (2001). Job burnout. Annual Reviews of Psychology 52: 397–422.
  5. Prem, R. & Kubicek, B. & Diestel, S. & Korunka, C. (2016). Regulatory job stressors and their within-person relationships with ego depletion: The roles of state anxiety, self-control effort, and job autonomy. Journal of Vocational Behavior 92: 22–32.
  6. Gold, A. & MacLeod, K. & Frier, B. & Deary, J. (1995). Changes in mood during acute hypoglycemia in healthy participants. Journal of Personality and Social Psychology 68 (3): 498–504.
  7. Evans, M. & Pernet, A. & Lomas, J. & Jones, J. & Amiel, S. (2000). Delay in onset of awareness of acute hypoglycemia and of restoration of cognitive performance during recovery. Diabetes Care 23 (7): 893–897.
  8. Sommerfield, A. & Deary, I. & Frier, B. (2004). Acute hyperglycemia alters mood state and impairs cognitive performance in people with type 2 diabetes. Diabetes Care 27 (10): 2335–2340.
  9. Felig, P. & Cherif, A. & Minagawa, A. & Wahren, J. (1982). Hypoglycemia during prolonged exercise in normal men. The New England Journal of Medicine 306 (15): 895–900.
  10. Merimee, T. & Tyson, J. (1974). Stabilization of plasma glucose during fasting; Normal variations in two separate studies. The New England Journal of Medicine 291 (24): 1275–1278.
  11. Campfield, L. & Smith, F. (2003). Blood glucose dynamics and control of meal initiation: a pattern detection and recognition theory. Physiological Reviews 83 (1): 25–58. Review.
  12. Aronoff, S. & Berkowitz, K. & Shreiner, B. & Want, L. (2004). Glucose metabolism and regulation: beyond insulin and glucagon. Diabetes Spectrum 17 (3): 183–190.
  13. Hers, H. (1990). Mechanisms of blood glucose homeostasis. Journal of Inherited Metabolic Disease 13 (4): 395-410. Review.
  14. Dhumpa, R. & Truong, T. & Wang, X. & Bertram, R. & Roper, M. (2014). Negative Feedback Synchronizes Islets of Langerhans. Biophysical Journal 106 (10): 2275–2282.
  15. Schuit, F. & Huypens, P. & Heimberg, H. & Pipeleers, D. (2001). Glucose sensing in pancreatic beta-cells: a model for the study of other glucose-regulated cells in gut, pancreas, and hypothalamus. Diabetes 50 (1): 1–11. Review.
  16. Karnani, M. & Burdakov, D. (2011). Multiple hypothalamic circuits sense and regulate glucose levels. American Journal of Physiology – Regulatory Integrative and Comparative Physiology 300 (1): R47–R55.
  17. Guo, X. et al. (2012). Glycolysis in the control of blood glucose homeostasis. Acta Pharmaceutica Sinica B 2 (4): 358–367.
  18. Stumvoll, M. et al. (1998). Human kidney and liver gluconeogenesis: evidence for organ substrate selectivity. American Journal of Physiology 274 (5 Pt 1): E817–826.
  19. Mithieux, G. & Rajas, F. & Gautier-Stein, A. (2004). A novel role for glucose 6-phosphatase in the small intestine in the control of glucose homeostasis. The Journal of Biological Chemistry 279 (43): 44231–44234.
  20. Mithieux, G. & Andreelli, F. & Magnan, C. (2009). Intestinal gluconeogenesis: key signal of central control of energy and glucose homeostasis. Current Opinion in Clinical Nutrition and Metabolic Care 12 (4): 419–423.
  21. Berg, J. & Tymoczko, J. & Stryer, L. (2002). Biochemistry, 5th edition. Section 16.4, Gluconeogenesis and Glycolysis Are Reciprocally Regulated. New York: W H Freeman. [luettu: 16.4.2016]
  22. Venn, B. & Green, T. (2007). Glycemic index and glycemic load: measurement issues and their effect on diet-disease relationships. European Journal of Clinical Nutrition 61 (Suppl 1): S122-131. Review.
  23. Holt, S. & Miller, J. & Petocz, P. (1997). An insulin index of foods: the insulin demand generated by 1000-kJ portions of common foods. The American Journal of Clinical Nutrition 66 (5): 1264–1276.
  24. Bell, K. et al. (2014). Estimating insulin demand for protein-containing foods using the food insulin index. European Journal of Clinical Nutrition 68 (9): 1055–1059.
  25. Holt, S. & Miller, J. & Petocz, P. & Farmakalidis, E. (1995). A satiety index of common foods. European Journal of Clinical Nutrition 49 (9): 675–690.
  26. Esfahani, A. & Wong, J. & Mirrahimi, A. & Villa, C. & Kendall, C. (2011). The application of the glycemic index and glycemic load in weight loss: A review of the clinical evidence. IUBMB Life 63 (1): 7–13.
  27. Liu, S. et al. (2002). Relation between a diet with a high glycemic load and plasma concentrations of high-sensitivity C-reactive protein in middle-aged women. The American Journal of Clinical Nutrition 75 (3): 492–498.
  28. Bulló, M. et al. (2013). Dietary glycemic index/load and peripheral adipokines and inflammatory markers in elderly subjects at high cardiovascular risk. Nutrition Metabolism and Cardiovascular Diseases 23 (5): 443–450.
  29. Jones, J. & Park, Y. & Lee, J. & Lerman, R. & Fernandez, M. (2011). A Mediterranean-style, low-glycemic-load diet reduces the expression of 3-hydroxy-3-methylglutaryl-coenzyme A reductase in mononuclear cells and plasma insulin in women with metabolic syndrome. Nutrition Research 31 (9): 659–664.
  30. Kanetkar, P. & Singhal, R. & Kamat, M. (2007). Gymnema sylvestre: A Memoir. Journal of Clinical Biochemistry and Nutrition 41 (2): 77–81.
  31. Inoue, K. & Yamazaki, H. & Shimada, T. (2000). CYP2A6 genetic polymorphisms and liver microsomal coumarin and nicotine oxidation activities in Japanese and Caucasians. Archives of Toxicology 73 (10-11): 532–539.
  32. Anderson, R. (2008). Chromium and polyphenols from cinnamon improve insulin sensitivity. Proceedings of the Nutrition Society 67 (1): 48–53.
  33. Davis, P & Yokoyama, W. (2011). Cinnamon intake lowers fasting blood glucose: meta-analysis. Journal of Medicinal Food 14 (9): 884–889. Review.
  34. Akilen, R. & Tsiami, A. & Devendra, D. & Robinson, N. (2012). Cinnamon in glycaemic control: Systematic review and meta analysis. Clinical Nutrition 31 (5): 609–615. Review.
  35. Shishtar, E. & Sievenpiper, J. L. et.al. (2014). The effect of ginseng (the genus panax) on glycemic control: a systematic review and meta-analysis of randomized controlled clinical trials. PLoS One 9 (9): e107391. Review.
  36. van Dam, R. & Pasman, W. & Verhoef, P. (2004). Effects of coffee consumption on fasting blood glucose and insulin concentrations: randomized controlled trials in healthy volunteers. Diabetes Care 27 (12): 2990–2992.
  37. Pizziol A. at al. (1998). Effects of caffeine on glucose tolerance: a placebo-controlled study. European Journal of Clinical Nutrition 52 (11) :846–869.
  38. Battram, D. & Arthur, R. & Weekes, A. & Graham, T. (2006). The glucose intolerance induced by caffeinated coffee ingestion is less pronounced than that due to alkaloid caffeine in men. The Journal of Nutrition 136 (5): 1276–1280.
  39. Palatini, P. (2015). Association of coffee consumption and CYP1A2 polymorphism with risk of impaired fasting glucose in hypertensive patients. European Journal of Epidemiology 30 (3): 209–217.
  40. Simon, C. & Gronfier, C. & Schlienger, J. & Brandenberger, G. (1998). Circadian and ultradian variations of leptin in normal man under continuous enteral nutrition: relationship to sleep and body temperature. The Journal of Clinical Endocrinology and Metabolism 83 (6): 1893–1899.
  41. Simon, C. (1998). Ultradian pulsatility of plasma glucose and insulin secretion rate: circadian and sleep modulation. Hormone Research 49 (3-4): 185-190. Review.
  42. Nofzinger, E. et al. (2002). Human regional cerebral glucose metabolism during non-rapid eye movement sleep in relation to waking. Brain 125 (Pt 5): 1105–1115.
  43. Scheen, A. & Byrne, M. & Plat, L. & Leproult, R. & Van Cauter, E. (1996). Relationships between sleep quality and glucose regulation in normal humans. American Journal of Physiology 271 (2 Pt 1): E261–270.
  44. Spiegel, K. & Leproult, R. & Van Cauter, E. (1999). Impact of sleep debt on metabolic and endocrine function. Lancet 354 (9188): 1435–1439.
  45. Spiegel, K. & Knutson, K. & Leproult, R. & Tasali, E. & Van Cauter, E. (2005). Sleep loss: a novel risk factor for insulin resistance and Type 2 diabetes. Journal of Applied Physiology 99: 2008–2019.
  46. Shan, Z. et al. (2015). Sleep duration and risk of type 2 diabetes: a meta-analysis of prospective studies. Diabetes Care 38 (3): 529–537. Review.
  47. Spiegel, K. & Tasali, E. & Penev, P. & Van Cauter, E. (2004). Brief communication: Sleep curtailment in healthy young men is associated with decreased leptin levels, elevated ghrelin levels, and increased hunger and appetite. Annals of Internal Medicine 141 (11): 846–850.
  48. Littman, A. et al. (2007). Sleep, ghrelin, leptin and changes in body weight during a 1-year moderate-intensity physical activity intervention. International Journal of Obesity 31 (3): 466–475.
  49. Taheri, S. & Lin, L. & Austin, D. & Young, T. & Mignot, E. (2004). Short Sleep Duration Is Associated with Reduced Leptin, Elevated Ghrelin, and Increased Body Mass Index. Froguel P, ed. PLoS Medicine 1 (3): e62.
  50. Tuomi, T, et al. (2016). Increased Melatonin Signaling Is a Risk Factor for Type 2 Diabetes. Cell Metabolism 23 (6): 1067–77.
  51. Martin, A. et al. (2000). Is advice for breakfast consumption justified? Results from a short-term dietary and metabolic experiment in young healthy men. British Journal of Nutrition 84 (3): 337–344.
  52. Bellisle, F. & McDevitt, R. & Prentice, A. (1997). Meal frequency and energy balance. British Journal of Nutrition 77 (Suppl 1): S57–70. Review.
  53. Raynor, H. & Goff, M. & Poole, S. & Chen, G. (2015). Eating Frequency, Food Intake, and Weight: A Systematic Review of Human and Animal Experimental Studies. Frontiers in Nutrition 2: 38. Review.
  54. Webber, J. & Macdonald, I. (1994). The cardiovascular, metabolic and hormonal changes accompanying acute starvation in men and women. British Journal of Nutrition 71 (3): 437–447.
  55. Keogh, J. & Pedersen, E. & Petersen, K. & Clifton, P. (2014). Effects of intermittent compared to continuous energy restriction on short-term weight loss and long-term weight loss maintenance. Clinical Obesity 4 (3): 150–156.
  56. Harvie, M. et al. (2011). The effects of intermittent or continuous energy restriction on weight loss and metabolic disease risk markers: a randomized trial in young overweight women. International Journal of Obesity 35 (5): 714–727.
  57. Taylor, M. & Garrow, J. (2001). Compared with nibbling, neither gorging nor a morning fast affect short-term energy balance in obese patients in a chamber calorimeter. International Journal of Obesity and  Related Metabolic Disorders 25 (4): 519–528.
  58. Lindseth, G. & Lindseth, P. & Thompson, M. (2013). Nutritional effects on sleep. Western Journal of Nursing Research 35 (4): 497–513
  59. Sofer, S. et al. (2013). Changes in daily leptin, ghrelin and adiponectin profiles following a diet with carbohydrates eaten at dinner in obese subjects. Nutrition Metabolism and Cardiovascular Diseases 23 (8): 744–750.
  60. Froy, O. (2007). The relationship between nutrition and circadian rhythms in mammals. Frontiers in Neuroendocrinology 28 (2-3): 61–71. Review.
  61. Howatson, G. et al. (2012). Exercise-induced muscle damage is reduced in resistance-trained males by branched chain amino acids: a randomized, double-blind, placebo controlled study. Journal of the International Society of Sports Nutrition 9: 20.
  62. Longo, V. & Mattson, M. (2014). Fasting: Molecular Mechanisms and Clinical Applications. Cell Metabolism 19 (2): 181–192.
  63. Veech, R. (2004). The therapeutic implications of ketone bodies: the effects of ketone bodies in pathological conditions: ketosis, ketogenic diet, redox states, insulin resistance, and mitochondrial metabolism. Prostaglandins Leukotriens and Essential Fatty Acids 70 (3): 309–319. Review.
  64. Tsai, A. & Wadden, T. (2006). The evolution of very-low-calorie diets: an update and meta-analysis. Obesity 14 (8): 1283–1293. Review.
  65. Joo, N. et al. (2010). Ketonuria after fasting may be related to the metabolic superiority. Journal of Korean Medicinal Science 25 (12): 1771–1776.
  66. Bach, A. & Schirardin, H. & Weryha, A. & Bauer, M. (1977). Ketogenic response to medium-chain triglyceride load in the rat. The Journal of Nutrition 107 (10): 1863–1870.
  67. Amiel,S. (1995). Organ fuel selection: brain. Proceedings of the Nutrition Society 54 (1): 151–155. Review.
  68. St-Onge, M-P. & Bosarge, A. & Goree, L. & Darnell, B. (2008). Medium Chain Triglyceride Oil Consumption as Part of a Weight Loss Diet Does Not Lead to an Adverse Metabolic Profile When Compared to Olive Oil. Journal of the American College of Nutrition 27 (5): 547–552.
  69. Koeslag, J. (1982). Post-exercise ketosis and the hormone response to exercise: a review. Medicine and Science in Sports and Exercise 14 (5): 327–334. Review.
  70. Alberti, K. & Johnston, D. & Gill, A. & Barnes, A. & Orskov, H. (1978). Hormonal regulation of ketone-body metabolism in man. Biochemical Society Symposium (43): 163–182.
  71. Fukao, T. & Lopaschuk, G. & Mitchell, G. (2004). Pathways and control of ketone body metabolism: on the fringe of lipid biochemistry. Prostaglandins Leukotriens and Essential Fatty Acids 70 (3): 243-251. Review.
  72. Berg, J. & Tymoczko, J. & Stryer, L. (2002). Biochemistry. 5th edition. Section 30.2, Each Organ Has a Unique Metabolic Profile. New York: W H Freeman. [luettu: 12.6.2016]
  73. Dashti, H. et al. (2006). Long term effects of ketogenic diet in obese subjects with high cholesterol level. Molecular and Cellular Biochemistry 286 (1-2): 1–9.
  74. Rho, J. & Rogawski, M. (2007). The Ketogenic Diet: Stoking the Powerhouse of the Cell. Epilepsy Currents 7 (2): 58–60.
  75. Paoli, A. & Rubini, A. & Volek, J. & Grimaldi, K. (2013). Beyond weight loss: a review of the therapeutic uses of very-low-carbohydrate (ketogenic) diets. European Journal of Clinical Nutrition 67 (8): 789–796.
  76. Mayet, J. & Hughes, A. (2003). Cardiac and vascular pathophysiology in hypertension. Heart 89 (9): 1104–1109.
  77. Celis, H. & Fagard, R. (2004). White-coat hypertension: a clinical review. European Journal of Internal Medicine 15 (6): 348–357.
  78. Hollister, A. (1992). Orthostatic hypotension. Causes, evaluation, and management. Western Journal of Medicine 157 (6): 652–657.
  79. Higginson, L. (2014). Orthostatic hypotension. Merck Manual. <www.merckmanuals.com> [luettu: 14.7.2016]
  80. Gasperin, D. & Netuveli, G. & Dias-da-Costa, J. & Pattussi, M. (2009). Effect of psychological stress on blood pressure increase: a meta-analysis of cohort studies. Cadernos de Saúde Pública 25 (4): 715–726. Review.
  81. Anderson, J. & Liu, C. & Kryscio, R. (2008). Blood pressure response to transcendental meditation: a meta-analysis. American Journal of Hypertension 21 (3): 310–316.
  82. Noordzij, M. et al. (2005). Blood pressure response to chronic intake of coffee and caffeine: a meta-analysis of randomized controlled trials. Journal of Hypertension 23 (5): 921–928.
  83. Yoto, A. & Motoki, M. & Murao, S. & Yokogoshi, H. (2012). Effects of L-theanine or caffeine intake on changes in blood pressure under physical and psychological stresses. Journal of Physiological Anthropology 31: 28.
  84. Lynch, J. & Long, J. & Thomas, S. &, Malinow, K. & Katcher, A. (1981). The effects of talking on the blood pressure of hypertensive and normotensive individuals. Psychosomatic Medicine 43 (1): 25–33.
  85. van Kempen, E. et al. (2002). The association between noise exposure and blood pressure and ischemic heart disease: a meta-analysis. Environmental Health Perspectives 110 (3): 307–317.
  86. Loomba, R. & Arora, R. & Shah, P. & Chandrasekar, S. & Molnar, J. (2012). Effects of music on systolic blood pressure, diastolic blood pressure, and heart rate: a meta-analysis. Indian Heart Journal 64 (3): 309–313.
  87. Puddey, I. & Beilin, L. (2006). Alcohol is bad for blood pressure. Clinical and Experimental Pharmacology and Physiology 33 (9): 847–852. Review.
  88. Greyling, A. et al. (2014). The  effect of black tea on blood pressure: a systematic review with meta-analysis of randomized controlled trials. PLoS One 9 (7): e103247. Review.
  89. Grossman, E. & Messerli, F. (2012). Drug-induced hypertension: an unappreciated cause of secondary hypertension. The American Journal of Medicine 125 (1): 14–22. Review.
  90. Li, P. et al. (2015). Long-Lasting Reduction of Blood Pressure by Electroacupuncture in Patients with Hypertension: Randomized Controlled Trial. Medical Acupuncture 27 (4): 253–266.
  91. Park, B. & Tsunetsugu, Y. & Kasetani, T. & Kagawa, T. & Miyazaki, Y. (2010). The physiological effects of Shinrin-yoku (taking in the forest atmosphere or forest bathing):evidence from field experiments in 24 forests across Japan. Environmental Health and Preventive Medicine 15 (1): 18–26.
  92. McCarron, D. & Reusser, M. (1996). Body weight and blood pressure regulation. The American Journal of Clinical Nutrition 63 (3 Suppl): 423S–425S. Review.
  93. Diaz, K. & Shimbo, D. (2013). Physical activity and the prevention of hypertension. Current Hypertension Reports 15 (6): 659–668. Review.
  94. Jalal, D. & Smits, G. & Johnson, R. & Chonchol, M. (2010). Increased fructose associates with elevated blood pressure. Journal of the American Society of Nephrology 21 (9): 1543–1549.
  95. Jakulj, F. et al. (2007). A high-fat meal increases cardiovascular reactivity to psychological stress in healthy young adults. The Journal of Nutrition 137 (4): 935–939.
  96. Nissensohn, M. & Román-Viñas, B. & Sánchez-Villegas, A. & Piscopo, S. & Serra-Majem, L. (2016). The Effect of the Mediterranean Diet on Hypertension: A Systematic Review and Meta-Analysis. Journal of Nutrition Education and Behavior 48 (1): 42–53.e1.
  97. Manheimer, E. & van Zuuren, E. & Fedorowicz, Z. & Pijl, H. (2015). Paleolithic nutrition for metabolic syndrome: systematic review and meta-analysis. The American Journal of Clinical Nutrition 102 (4): 922–932. Review.
  98. Frassetto, L. & Morris, R. Jr. & Sellmeyer, D. & Todd, K. & Sebastian, A. (2001). Diet, evolution and aging–the pathophysiologic effects of the post-agricultural inversion of the potassium-to-sodium and base-to-chloride ratios in the human diet. European Journal of Nutrition 40 (5): 200–213. Review.
  99. Houston, M. & Harper, K. (2008). Potassium, magnesium, and calcium: their role in both the cause and treatment of hypertension. The Journal of Clinical Hypertension 10 (7 Suppl 2): 3–11. Review. Pilz, S. & Tomaschitz, A. & Ritz, E. & Pieber, T. (2009). Vitamin D status and arterial hypertension: a systematic review. Nature Reviews Cardiology 6 (10): 621–630. Review.
  100. Pilz, S. & Tomaschitz, A. & Ritz, E. & Pieber, T. (2009) Vitamin D status and arterial hypertension: a systematic review. Nature Reviews Cardiology 6 (10): 621-630.
  101. Yasukouchi, A. & Ishibashi, K. (2005). Non-visual effects of the color temperature of fluorescent lamps on physiological aspects in humans. Journal of Physiological Anthropology and Applied Human Science 24 (1): 41–43. Review.
  102. Liu, D. et al. (2014). UVA irradiation of human skin vasodilates arterial vasculature and lowers blood pressure independently of nitric oxide synthase. Journal of Investigative Dermatology 134 (7): 1839–1846.
  103. Andres-Barquin, P. (2002). Santiago Ramón y Cajal and the Spanish school of neurology. The Lancet Neurology 1 (7): 445–452.
  104. Bartol, T. et al. (2015). Nanoconnectomic upper bound on the variability of synaptic plasticity. Elife 4: e10778.
  105. Cowan, N. (2008). What are the differences between long-term, short-term, and working memory? Progress in Brain Research 169: 323–338.
  106. LaBar, K. & Cabeza, R. (2006). Cognitive neuroscience of emotional memory. Nature Reviews Neuroscience 7 (1): 54–64. Review.
  107. Buzsáki, G. (2002). Theta oscillations in the hippocampus. Neuron 33 (3): 325–340. Review.
  108. Baijal, S. & Srinivasan, N. (2012). Theta activity and meditative states: spectral changes during concentrative meditation. Cognitive Processing 11 (1): 31–38.
  109. Cahn, B. & Polich, J. (2006). Meditation states and traits: EEG, ERP, and neuroimaging studies. Psychological Bulletin 132 (2): 180–211. Review.
  110. Zarkadakis, G. (2015). In Our Own Image: Will artificial intelligence save or destroy us? New York: Raider.
  111. Bruce, D. (2001). Fifty years since Lashley’s In search of the Engram: refutations and conjectures. Journal of the History of the Neurosciences 10 (3): 308–18.
  112. Poo, M. et al. (2016). What is memory? The present state of the engram. BMC Biology  14 (1): 40.
  113. Riedel, W. & Blokland, A. (2015). Declarative memory. Handbook for Experimental Pharmacology 228: 215–236. Review.
  114. Hirono, N. et al. (1997). Procedural memory in patients with mild Alzheimer’s disease. Dementia and Geriatric Cognitive Disorders 8 (4): 210–216.
  115. Allain, H. et al. (1995). Procedural memory and Parkinson’s disease. Dementia 6 (3): 174–178.
  116. Tulving, E. (2002). Episodic memory: from mind to brain. Annual Reviews of Psychology 53: 1-25.
  117. Binder, J. & Desai, R. (2011). The neurobiology of semantic memory. Trends in Cognitive Sciences 15 (11): 527–536. Review.
  118. Greenberg, D., & Verfaellie,, M. (2010). Interdependence of episodic and semantic memory: Evidence from neuropsychology. Journal of the International Neuropsychological Society : JINS 16 (5): 748–753.
  119. Potkin, K. & Bunney, W. Jr. (2012) Sleep Improves Memory: The Effect of Sleep on Long Term Memory in Early Adolescence. PLoS ONE 7 (8): e42191.
  120. Cooke, S. & Bliss, T. (2006). Plasticity in the human central nervous system. Brain 129 (7): 1659–1673.
  121. Morishita, W. & Marie, H. & Malenka, R. (2005). Distinct triggering and expression mechanisms underlie LTD of AMPA and NMDA synaptic responses. Nature Neuroscience 8 (8): 1043–1050.
  122. Pérez-Otaño, I. & Ehlers, M. (2005). Homeostatic plasticity and NMDA receptor trafficking. Trends in Neuroscience 28 (5): 229–238. Review.
  123. Malleret, G. et al. (2010). Bidirectional regulation of hippocampal long-term synaptic plasticity and its influence on opposing forms of memory. The Journal of Neuroscience 30 (10): 3813–3825.
  124. Costenla, A. & Cunha, R. & de Mendonça, A. (2010). Caffeine, adenosine receptors, and synaptic plasticity. Journal of Alzheimer’s Disease 20 (Suppl 1): S25–34. Review.
  125. Nitsche, M. et al. (2008). Transcranial direct current stimulation: State of the art 2008. Brain Stimulation 1 (3): 206–223. Review.
  126. Chervyakov, A. & Chernyavsky, A, & Sinitsyn, D. & Piradov, M. (2015). Possible Mechanisms Underlying the Therapeutic Effects of Transcranial Magnetic Stimulation. Frontiers in Human Neuroscience 9: 303. Review.
  127. Nakauchi, S. & Brennan, R. & Boulter, J. & Sumikawa, K. (2007). Nicotine gates long-term potentiation in the hippocampal CA1 region via the activation of alpha2* nicotinic ACh receptors. European Journal of Neuroscience 25 (9): 2666–2681.
  128. Yamazaki, Y. & Jia, Y. & Hamaue, N. & Sumikawa, K. (2005). Nicotine-induced switch in the nicotinic cholinergic mechanisms of facilitation of long-term potentiation induction. European Journal of Neuroscience 22 (4): 845–860.
  129. Huang, Y. & Kandel, E. & Levine, A. (2008). Chronic nicotine exposure induces a long-lasting and pathway-specific facilitation of LTP in the amygdala. Learning & Memory 15 (8): 603–610.
  130. Lazar, S. et al. (2005). Meditation experience is associated with increased cortical thickness. Neuroreport 16 (17): 1893–1897.
  131. Lutz, A. & Greischar, L. & Rawlings, N, & Ricard, M. & Davidson, R. (2004). Long-term meditators self-induce high-amplitude gamma synchrony during mental practice. Proceedings of the National Academy of Sciences 101 (46): 16369–16373.
  132. Davidson, R. & Lutz, A. (2008). Buddha’s Brain: Neuroplasticity and Meditation. IEEE Signal Processing Magazine 25 (1): 176–174.
  133. Tang, Y. & Hölzel, B. & Posner, M. (2015). The neuroscience of mindfulness meditation. Nature Reviews Neuroscience 16 (4): 213–225.
  134. Malykh, A. & Sadaie, M. (2010). Piracetam and piracetam-like drugs: from basic science to novel clinical applications to CNS disorders. Drugs 70 (3): 287–312. Review.
  135. Abumaria, N. et al.  (2011). Effects of elevation of brain magnesium on fear conditioning, fear extinction, and synaptic plasticity in the infralimbic prefrontal cortex and lateral amygdala. The Journal of Neuroscience 31 (42): 14871–14881.
  136. Slutsky, I. et al. (2010). Enhancement of learning and memory by elevating brain magnesium. Neuron 65 (2): 165–177.
  137. Otmakhov N. et al. (2004). Forskolin-induced LTP in the CA1 hippocampal region is NMDA receptor dependent. Journal of Neurophysiology 91 (5): 1955–1962.
  138. Cho, H. et al. (2008). Forskolin Enhances Synaptic Transmission in Rat Dorsal Striatum through NMDA Receptors and PKA in Different Phases. Korean Journal of Physiology and Pharmacology 12 (6): 293–297.
  139. Modi, K. & Rangasamy, S. & Dasarathi, S. & Roy, A. & Pahan, K. Cinnamon Converts Poor Learning Mice to Good Learners: Implications for Memory Improvement. Journal of Neuroimmune Pharmacology 1–15.  [epub ahead of print].
  140. Jain, S. & Sangma, T. & Shukla, S. & Mediratta, P. (2015). Effect of Cinnamomum zeylanicum extract on scopolamine-induced cognitive impairment and oxidative stress in rats. Nutritional Neuroscience 18 (5): 210–216.
  141. Khasnavis, S. & Pahan, K. (2014). Cinnamon treatment upregulates neuroprotective proteins Parkin and DJ-1 and protects dopaminergic neurons in a mouse model of Parkinson’s disease. Journal of Neuroimmune Pharmacology 9 (4): 569–581.
  142. Persuh, M. & Genzer, B. & Melara, R. (2012). Iconic memory requires attention. Frontiers in Human Neuroscience 6: 126.
  143. Diamond, A. (2013). Executive functions. Annual Review of Psychology 64: 135–168. Review.
  144. Baddeley, A. (1975). Word length and the structure of short-term memory. Journal of Verbal Learning and Verbal Behavior 14 (6): 575–589.
  145. Unsworth, N. & Engle, R. (2007). The nature of individual differences in working memory capacity: active maintenance in primary memory and controlled search from secondary memory. Psychological Review 114 (1): 104–132.
  146. Kane, M. et al.  (2007). For whom the mind wanders, and when: an experience-sampling study of working memory and executive control in daily life. Psychological Science 18 (7): 614–621.
  147. Hölzel, B. et al. (2011). How Does Mindfulness Meditation Work? Proposing Mechanisms of Action From a Conceptual and Neural Perspective. Perspectives in Psychological Science 6 (6): 537–559.
  148. Zeidan, F. & Johnson, S. & Diamond, B. & David, Z. & Goolkasian, P. (2010). Mindfulness meditation improves cognition: evidence of brief mental training. Conscious and Cognition 19 (2): 597–605.
  149. Miller, G. (1956). The magical number seven plus or minus two: some limits on our capacity for processing information. Psychological Review 63 (2): 81–97.
  150. Cowan, N. (2010). The Magical Mystery Four: How is Working Memory Capacity Limited, and Why? Current Directions in Psychological Science 19 (1): 51–57.
  151. Bancroft, T. & Servos, P. (2011). Distractor frequency influences performance in vibrotactile working memory. Experimental Brain Research 208 (4): 529–532.
  152. Barrouillet, P. & Bernardin, S. & Camos, V. (2004). Time constraints and resource sharing in adults’ working memory spans. Journal of Experimental Psychology General 133 (1): 83–100.
  153. Luethi, M. & Meier, B. & Sandi, C. (2009). Stress effects on working memory, explicit memory, and implicit memory for neutral and emotional stimuli in healthy men. Frontiers in Behavioral Neuroscience 2: 5.
  154. Vytal, K. & Cornwell, B, & Letkiewicz, A. & Arkin, N. & Grillon, C. (2013). The complex interaction between anxiety and cognition: insight from spatial and verbal working memory. Frontiers in Human Neuroscience 7: 93.
  155. Owen, A. (1997). The functional organization of working memory processes within human lateral frontal cortex: the contribution of functional neuroimaging. European Journal of Neuroscience 9 (7): 1329–1339. Review.
  156. Smith, E. & Jonides, J. (1999). Storage and executive processes in the frontal lobes. Science 283 (5408): 1657–1661. Review.
  157. Wager, T. & Smith, E. (2003). Neuroimaging studies of working memory: a meta-analysis. Cognitive Affective and Behavioral Neuroscience 3 (4): 255–274. Review.
  158. Bledowski, C. & Rahm, B. & Rowe, J. (2009). What “works” in working memory? Separate systems for selection and updating of critical information. The Journal of Neuroscience 29 (43): 13735–13741.
  159. Hill, A. & Laird, A. & Robinson, J. (2014). Gender differences in working memory networks: a BrainMap meta-analysis. Biological Psychology 102: 18–29.
  160. McNab, F. et al. (2009). Changes in cortical dopamine D1 receptor binding associated with cognitive training. Science 323 (5915): 800–802.
  161. Dash, P. & Moore, A. & Kobori, N. & Runyan, J. (2007). Molecular activity underlying working memory. Learning and Memory 14 (8): 554–563. Review.
  162. Arnsten, A. & Paspalas, C. & Gamo, N. & Yang, Y. & Wang, M. (2010). Dynamic Network Connectivity: A new form of neuroplasticity. Trends in Cognitive Sciences 14 (8): 365–375.
  163. Jaeggi, S. & Buschkuehl, M. & Jonides, J. & Perrig, W. (2008). Improving fluid intelligence with training on working memory. Proceedings of the National Academy of Sciences 105 (19): 6829–6833.
  164. Morrison, A. & Chein, J. (2011). Does working memory training work? The promise and challenges of enhancing cognition by training working memory. Psychonomic Bulletin and Review 18 (1): 46–60. Review.
  165. Padilla, C. & Pérez, L. & Andrés, P. (2014). Chronic exercise keeps working memory and inhibitory capacities fit. Frontiers of Behavioral Neuroscience 8: 49.
  166. Alves, C. et al. (2014). Influence of acute high-intensity aerobic interval exercise bout on selective attention and short-term memory tasks. Perceptual and Motor Skills 118 (1): 63–72.
  167. Lo Bue-Estes, C. et al. (2008). Short-term exercise to exhaustion and its effects on cognitive function in young women. Perceptual and Motor Skills 107 (3): 933–945.
  168. van Dongen, E. & Kersten, I. & Wagner, I. & Morris, R. & Fernández, G. (2016). Physical Exercise Performed Four Hours after Learning Improves Memory Retention and Increases Hippocampal Pattern Similarity during Retrieval. Current Biology pii: S0960–9822(16)30465-1.
  169. Alloway, G. & Alloway, T. & Magyari, P. & Floyd, S. (2016). An exploratory study investigating the effects of barefoot running on working memory. Perceptual and Motor Skills 122 (2): 432–443.
  170. Gothe, N. & Kramer, A. & McAuley, E. (2014). The effects of an 8-week Hatha yoga intervention on executive function in older adults. The Journal of Gerontology A: Biological Sciences and Medical Sciences 69 (9): 1109–1116.
  171. Gothe, N. & Pontifex, M. & Hillman, C. & McAuley, E. (2013). The acute effects of yoga on executive function. Journal of Physical Activity and Health 10 (4): 488–495.
  172. Burunat, I. & Alluri, V. & Toiviainen, P & Numminen, J. & Brattico, E. (2014). Dynamics of brain activity underlying working memory for music in a naturalistic condition. Cortex 57: 254–69.
  173. Mammarella, N. & Fairfield, B. & Cornoldi, C. (2007). Does music enhance cognitive performance in healthy older adults? The Vivaldi effect. Aging Clinical and Experimental Research 19 (5): 394–399.
  174. Bottiroli, S. & Rosi, A. & Russo, R. & Vecchi, T. & Cavallini, E. (2014). The cognitive effects of listening to background music on older adults: processing speed improves with upbeat music, while memory seems to benefit from both upbeat and downbeat music. Frontiers in Aging Neuroscience 6: 284.
  175. Mulquiney, P. & Hoy, K. & Daskalakis, Z. & Fitzgerald, P. (2011). Improving working memory: exploring the effect of transcranial random noise stimulation and transcranial direct current stimulation on the dorsolateral prefrontal cortex. Clinical Neurophysiology 122 (12): 2384–2389.
  176. Lilienthal, L. & Tamez, E. & Shelton, J. & Myerson, J. & Hale, S. (2013). Dual n-back training increases the capacity of the focus of attention. Psychonomic Bulletin and Review 20 (1): 135–141.
  177. Lawlor-Savage, L. & Goghari, V. (2016). Dual N-Back Working Memory Training in Healthy Adults: A Randomized Comparison to Processing Speed Training. PLoS One 11 (4): e0151817.
  178. Rae, C. & Digney, A. & McEwan, S. & Bates, T. (2003). Oral creatine monohydrate supplementation improves brain performance: a double-blind, placebo-controlled, cross-over trial. Proceedings Biological Sciences 270 (1529): 2147–2150.
  179. Rawson, E. & Venezia, A. (2011). Use of creatine in the elderly and evidence for effects on cognitive function in young and old. Amino Acids 40 (5): 1349–1362.
  180. Owen, G. & Parnell, H. & De Bruin, E. & Rycroft, J. (2008). The combined effects of L-theanine and caffeine on cognitive performance and mood. Nutritional Neuroscience 11 (4): 193–198.
  181. Neale, C. & Camfield, D. & Reay, J. & Stough, C. & Scholey, A. (2013). Cognitive effects of two nutraceuticals Ginseng and Bacopa benchmarked against modafinil: a review and comparison of effect sizes. British Journal of Clinical Pharmacology 75 (3): 728–737.
  182. Kumari, V. et al. (2003). Cognitive effects of nicotine in humans: an fMRI study. Neuroimage 19 (3): 1002–1013.
  183. Thomas, J. & Lockwood, P. & Singh, A. & Deuster, P. (1999). Tyrosine improves working memory in a multitasking environment. Pharmacology Biochemistry and Behavior 64 (3): 495–500.
  184. Colzato, L. & Jongkees, B. & Sellaro, R. & Hommel, B. (2013). Working memory reloaded: tyrosine repletes updating in the N-back task. Frontiers in Behavioral Neuroscience 7: 200.
  185. Lee, M. et al. (2014).Turmeric improves post-prandial working memory in pre-diabetes independent of insulin. Asia Pacific Journal of Clinical Nutrition 23 (4): 581–591.
  186. Cox, K. & Pipingas, A. & Scholey, A. (2015). Investigation of the effects of solid lipid curcumin on cognition and mood in a healthy older population. Journal of Psychopharmacology 29 (5): 642–651.
  187. Parker, A. et al.  (2011). The effects of IQPLUS Focus on cognitive function, mood and endocrine response before and following acute exercise. Journal of the International Society of Sports Nutrition 8: 16.
  188. Ghuntla, T. et al. (2014). Influence of practice on visual reaction time. Journal of Mahatma Gandhi Institute of Medical Sciences 19 (2): 119–122.
  189. Shelton, J. & Kumar, G. (2010). Comparison between auditory and visual simple reaction times. Neuroscience and Medicine (1): 30–32.
  190. Kraus, N. & White-Schwoch, T. (2015). Unraveling the Biology of Auditory Learning: A Cognitive-Sensorimotor-Reward Framework. Trends in Cognitive Sciences 9 (11): 642–654. Review.
  191. Jain, A. & Bansal, R. & Kumar, A. & & Singh, K. (2015). A comparative study of visual and auditory reaction times on the basis of gender and physical activity levels of medical first year students. International Journal of Applied and Basic Medical Research 5 (2): 124–127.
  192. Koskinen, S. & Lundqvist, A. & Ristiluoma, N. (2012). Terveys, toimintakyky ja hyvinvointi Suomessa 2011. Terveyden ja hyvinvoinnin laitos. [luettu: 16.5.2016]
  193. Keyserling, W. (2000). Workplace risk factors and occupational musculoskeletal disorders, Part 1: A review of biomechanical and psychophysical research on risk factors associated with low-back pain. AIHAJ 61 (1): 39–50. Review.
  194. Hansraj, K. (2014). Assessment of stresses in the cervical spine caused by posture and position of the head. Surgical Technology International 25: 277–279.
  195. Sugar, O. (1978). Adverse mechanical tension in the central nervous system: An analysis of cause and effect; relief by functional neurosurgery. JAMA 204 (25): 2776.
  196. Ouchi, Y. & Okada, H. & Yoshikawa, E. & Futatsubashi, M. & Nobezawa, S. (2001). Absolute changes in regional cerebral blood flow in association with upright posture in humans: an orthostatic PET study. Journal of Nuclear Medicine 42 (5): 707–712.
  197. Briñol, P. & Petty, R. (2003). Overt head movements and persuasion: a self-validation analysis. Journal of Personality and Social Psychology 84 (6): 1123–1139.
  198. Carney, D. & Cuddy, A. & Yap, A. (2010). Power posing: brief nonverbal displays affect neuroendocrine levels and risk tolerance. Psychological Science 21 (10): 1363–1368.
  199. Ranehill, E. et al. (2015). Assessing the robustness of power posing: no effect on hormones and risk tolerance in a large sample of men and women. Psychological Science 26 (5): 653–656.
  200. Goman, C. (2011). The Silent Language of Leaders: How Body Language Can Help or Hurt How You Lead. San Francisco: Jossey-Bass. [luettu: 30.5.2016]
  201. Husu, P. et al. (2014). Istumisen yhteydet terveyteen ja hyvinvointiin poikkileikkaustutkimuksessa – tuloksia Alueellisesta terveys- ja hyvinvointitutkimuksesta. Terveyden ja hyvinvoinnin laitoksen työpapereita 37/2014, s. 49–56.
  202. Dunstan, D. & Howard, B. & Healy, G. & Owen, N. (2012) Too much sitting–a health hazard. Diabetes Research and Clinical Practice 97 (3): 368–376.
  203. Hamilton, M. & Hamilton, D. & Zderic, T. (2007) Role of low energy expenditure and sitting in obesity, metabolic syndrome, type 2 diabetes, and cardiovascular disease. Diabetes 56 (11): 2655–2667
  204. Schmid, D. & Leitzmann, M. (2014) Television viewing and time spent sedentary in relation to cancer risk: a meta-analysis. Journal of the National Cancer Institute 106 (7): pii: dju098.
  205. Ekelund, U. et al. (2015) Physical activity and all-cause mortality across levels of overall and abdominal adiposity in European men and women: the European Prospective Investigation into Cancer and Nutrition Study (EPIC). The American Journal of Clinical Nutrition 101 (3):  613–621.
  206. Chau, J. et al. (2013). Daily sitting time and all-cause mortality: a meta-analysis. PLoS One 8 (11): e80000.
  207. Buman, M. et al. (2015). Sitting and television viewing: novel risk factors for sleep disturbance and apnea risk? Results from the 2013 national sleep foundation sleep in america poll. Chest 147 (3): 728–734.
  208. Adams, M. & Hutton, W. (1980). The effect of posture on the role of the apophysial joints in resisting intervertebral compressive forces. The Journal of Bone and Joint Surgery 62 (3): 358–362.
  209. Hedman, T. & Fernie, G. (1997). Mechanical response of the lumbar spine to seated postural loads. Spine 22 (7): 734–743.
  210. Pinar, R. & Ataalkin, S. & Watson, R. (2010). The effect of crossing legs on blood pressure in hypertensive patients. Journal of Clinical Nursing 19 (9-10): 1284–1288.
  211. Huang, V. & Munarriz, R. & Goldstein, I. (2005). Bicycle riding and erectile dysfunction: an increase in interest (and concern). The Journal of Sexual Medicine 2 (5): 596–604. Review.
  212. Southorn, T. (2002). Great balls of fire and the vicious cycle: a study of the effects of cycling on male fertility. The Journal of Family Planning and Reproductive Health Care 28 (4): 211–213.
  213. Sommer, F. & Goldstein, I. & Korda, J. (2010). Bicycle riding and erectile dysfunction: a review. The Journal of Sex Medicine 7 (7): 2346–2358.
  214. Corlett, E. (2006). Background to sitting at work: research-based requirements for the design of work seats. Ergonomics 49 (14): 1538–1546.
  215. Bashir, W. (2006). Alterations of Lumbosacral Curvature and Intervertebral Disc Morphology in Normal Subjects in Variable Sitting Positions Using Whole-body Positional MRI. Paper in conference of Radiological Society of North America. [luettu: 15.5.2016]
  216. Koskelo, R. (2010). Seating pressure distribution for different chair types. University of Kuopio.  [luettu: 15.5.2016]
  217. MacEwen, B. & MacDonald, D. & Burr, J. (2015). A systematic review of standing and treadmill desks in the workplace. Preventive Medicine 70: 50–58. Review
  218. Levine, J. et al. (2005).  Interindividual variation in posture allocation: possible role in human obesity. Science 307 (5709): 584–586.
  219. Levine, J. & Vander Weg, M. & Hill, J & Klesges, R. (2006). Non-exercise activity thermogenesis: the crouching tiger hidden dragon of societal weight gain. Arteriosclerosis Thrombosis and Vascular Biology 26 (4): 729–736.
  220. Buckley, J. & Mellor, D. & Morris, M. & Joseph, F. (2014). Standing-based office work shows encouraging signs of attenuating post-prandial glycaemic excursion. Occupational and Environmental Medicine 71 (2): 109–111.
  221. Wilmot, E. et al. (2012). Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia 55 (11): 2895–2905.
  222. Thorp, A. & Kingwell, B. & Owen, N. & Dunstan, D. (2014). Breaking up workplace sitting time with intermittent standing bouts improves fatigue and musculoskeletal discomfort in overweight/obese office workers. Occupational and Environmental Medicine 71 (11): 765–771.

  223. Pronk, N. & Katz, A. & Lowry, M. & Payfer, J. (2012). Reducing occupational sitting time and improving worker health: the Take-a-Stand Project, 2011. Preventing Chronic Disease 9: E154.
  224. Wilmot, E. et al. (2012). Sedentary time in adults and the association with diabetes, cardiovascular disease and death: systematic review and meta-analysis. Diabetologia 55 (11): 2895–2905.
  225. Aghazadeh, J. et al. (2015). Anti-fatigue mats, low back pain, and electromyography: An interventional study. International Journal of Occupational Medicine and Environmental Health 28 (2): 347–356.
  226. Wiggermann, N. & Keyserling, W. (2013). Effects of anti-fatigue mats on perceive discomfort and weight-shifting during prolonged standing. Human Factors 55 (4): 764–775.
  227. Edelson, N. (1988). Active office systems. Work and Stress: An International Journal of Work Health and Organisations 2 (2): 173–176.
  228. Edelson, N. & Danoffz, J. (1989). Walking on an electric treadmill while performing VDT office work. ACM SIGCHI Bulletin 21 (1): 72–77.
  229. Levine, J. & Miller, J. (2007). The energy expenditure of using a “walk-and-work” desk for office workers with obesity. British Journal of Sports Medicine 41 (9): 558–561.
  230. Koepp G. et al. (2013). Treadmill desks: A 1-year prospective trial. Obesity 21 (4): 705–711.
  231. Miller, G. (1956). The magical number seven, plus or minus two: Some limits on our capacity for processing information. Psychological Review 63 (2): 81–97.
  232. Crenshaw, D. (2008). The Myth of Multitasking: How “Doing It All” Gets Nothing Done. San Francisco: Jossey-Bass Wiley. [luettu: 26.5.2016]
  233. Rogers, R. & Monsell, S. (1995). The costs of a predictable switch between simple cognitive tasks. Journal of Experimental Psychology: General 124 (2): 207–231.
  234. Rubinstein, J. & Meyer, D. & Evans, J. (2001). Executive Control of Cognitive Processes in Task Switching. Journal of Experimental Psychology: Human Perception and Performance 27 (4): 763–797.
  235. Beatty, J. (1982). Task-evoked pupillary responses, processing load, and the structure of processing resources. Psychological Bulletin 91 (2): 276–292.
  236. Iqbal, S. & Zheng, X. & Bailey, B. (2004). Task-evoked pupillary response to mental workload in human-computer interaction. Conference on Human Factors in Computing Systems – Proceedings 1446–1480.
  237. Lin, B. & Kain, J. & Fritz, C. (2013). Don’t interrupt me! An examination of the relationship between intrusions at work and employee strain. International Journal of Stress Management 20 (2): 77–94.
  238. EPA. (2016). Air and Radiation: Indoor Air Quality. U.S. Environmental Protection Agency. [luettu: 16.6.2016]
  239. Hänninen, O. & Asikainen, A. (2013). Ilmanvaihto ja terveys, Suuria mahdollisuuksia vai kinkkisiä kompromisseja. Ympäristö ja Terveys 5: 32–37.
  240. Pekkanen, J. (2010). Elin- ja työympäristön riskit Suomessa. Ympäristö ja Terveys 3: 4–5.
  241. National Institutes of Health. (2016). Indoor Air Pollution. MedlinePlus. [luettu: 18.6.2016]
  242. Bakó-Biró, Z. & Wargocki, P. & Weschler, C. & Fanger, P. (2004). Effects of pollution from personal computers on perceived air quality, SBS symptoms and productivity in offices. Indoor Air 14 (3): 178–187.
  243. Kagi, N. et al. (2007). Indoor air quality for chemical and ultrafine particle contaminants from printers. Building and Environment 42 (5): 1949–1954.
  244. Tang, T. & Hurraß, J. & Gminski, R. & Mersch-Sundermann, V. (2012). Fine and ultrafine particles emitted from laser printers as indoor air contaminants in German offices. Environmental Science and Pollution Research International 19 (9): 3840–3849.
  245. Ho, D. et al. (2011). Emission Rates of Volatile Organic Compounds Released from Newly Produced Household Furniture Products Using a Large-Scale Chamber Testing Method. The Scientific World Journal 11: 1597–1622.
  246. Allen, J. et al. (2016). Associations of cognitive function scores with carbon dioxide, ventilation, and volatile organic compound exposures in office workers: A controlled exposure study of green and conventional office environments. Environmental Health Perspectives 124 (6): 805–812.
  247. Wolverton, B. & Johnson, A. & Bounds, K. (1989). Interior landscape plants for indoor air pollution abatement. NASA 1–22. [luettu: 16.6.2016]
  248. Dijksterhuis, A. & Nordgren, L. (2006). A Theory of Unconscious Thought. Perspectives on Psychological Science 1 (2): 95–109.
  249. Dijksterhuis, A. (2004). Think different: the merits of unconscious thought in preference development and decision making. Journal of Personal and Social Psychology 87 (5): 586–598.
  250. Pocheptsova, A. & Amir, O. & Dhar, R. & Baumeister, R. (2009). Deciding without resources: Resource depletion and choice in context. Journal of Marketing Research 46 (3): 344–355.
  251. Acker, F. (2008). New findings on unconscious versus conscious thought in decision making: additional empirical data and meta-analysis. Judgement and Decision Making 3 (4): 292–303.
  252. Ashby, N. & Glöckner, A. & Dickert, S. (2011). Conscious and unconscious thought in risky choice: testing the capacity principle and the appropriate weighting principle of unconscious thought theory. Frontiers in Psychology 2: 261.
  253. Hall, C. & Ariss, L. & Todorov, A. (2007). The illusion of knowledge: When more information reduces accuracy and increases confidence. Organizational Behavior and Human Decision Processes 103 (2): 277–290.
  254. Vohs, K. et al. (2005). Decision fatigue exhausts self-regulatory resources – but so does accomodating to unchosen alternatives. Unpublished manuscript. [luettu: 7.6.2016]
  255. Baumeister, R. & Heatherton, T. (1996). Self-Regulation Failure: An Overview. Psychological Inquiry 7 (1): 1–15.
  256. Simon, H. (1956). Rational choice and the structure of the environment. Psychological Reviews 63 (2): 129–138.
  257. Boag, S. (2014). Ego, drives, and the dynamics of internal objects. Frontiers in Psychology 5: 666.
  258. Kahneman, D. & Tversky, A. (1996). On the reality of cognitive illusions. Psychological Review 103 (3): 582–596.
  259. Blumenthal-Barby, J. & Krieger, H. (2015). Cognitive biases and heuristics in medical decision making: a critical review using a systematic search strategy. Medical Decision Making 35 (4): 539–557.
  260. Bargh, J. A. & Chartrand, T. L. (1999). The unbearable automaticity of being. American Psychologist 54: 462–479.
  261. Gilbert, D. T. & Krull, D. S. & Malone, P. S. (1990). Unbelieving the unbelievable: Some problems in the rejection of false information. Journal of Personality and Social Psychology 59 (4): 601–613.
  262. Kahneman, D. (2011). Thinking, Fast and Slow. New York: Farrar, Straus and Giroux.
  263. Guo, K. (2008). DECIDE: a decision-making model for more effective decision making by health care managers. The Health Care Manager 27 (2): 118–127.
  264. Balasubramanian, P. & Nochur, K. & Henderson, J. & Kwan, M. (1999). Managing process knowledge for decision support. Decision Support Systems 27 (1–2): 145–162.
  265. Yim, N-H., Kim, S-H., Kim, H-W. & Kwahk, K-Y. (2004). Knowledge based decision making on higher level strategic concerns: system dynamic ap- proach. Expert Systems with Applications 27 (1): 143–158.
  266. Riding, R. & Cheema, I. (1991). Cognitive styles – an overview and integration. Educational Psychology: An International Journal of Experimental Educational Psychology 11 (3–4): 193–215.
  267. Damasio, A. (1996). The somatic marker hypothesis and the possible functions of the prefrontal cortex. Philosophical transactions of the Royal Society of London. Series B Biological sciences 351 (1346): 1413–1420. Review.
  268. Naqvi, N. Shiv, B. & Bechara, A. (2006). The Role of Emotion in Decision Making: A Cognitive Neuroscience Perspective. Current Directions in Psychological Science 15 (5): 260–264.
  269. Lowenstein, G., & Lerner, J.S. (2003). The role of affect in decision making. In: Davidson, R & Scherer, K. & Goldsmith, H. (2003). Handbook of affective science. 619–642. New York: Oxford University Press.
  270. Pfister, H. & Böhm, G. (2008). The multiplicity of emotions: A framework of emotional functions in decision making. Judgment and decision making 3 (1): 5–17.
  271. Buchanan, T. (2007). Retrieval of emotional memories. Psychological Bulletin 133 (5): 761–779.
  272. Cirillo, F. (2006). The Pomodoro Technique. San Francisco: Creative Commons. [luettu: 2.6.2016]
  273. Glezer, L. & Jiang, X. & Riesenhuber, M. (2009). Evidence for highly selective neuronal tuning to whole words in the “visual word form area”. Neuron 62 (2): 199–204.
  274. Mueller, P. A. & Oppenheimer, D. M. (2014). The Pen Is Mightier Than the Keyboard: Advantages of Longhand Over Laptop Note Taking. Psychological Science 25 (6): 1159–68.
  275. Draganski, B. et al. (2004). Neuroplasticity: changes in grey matter induced by training. Nature 427 (6972): 311–2.
  276. Jackson, S. (1996). Toward a conceptual understanding of the flow experience in elite athletes. Research Quarterly for Exercise and Sport 67 (1): 76–90.
  277. Dietrich, A. (2004). Neurocognitive mechanisms underlying the experience of flow. Conscious and Cognition 13 (4): 746–761. Review.
  278. Furlong, C. (2011). Exposure to triaryl phosphates: metabolism and biomarkers of exposure. Journal of Biological Physics and Chemistry 2011: 11.
  279. Bagshaw, M. (2014). Health Effects of Contaminants in Aircraft Cabin Air (version 2.7). 1–19. AsMA. [luettu: 21.6.2016]
  280. Hale, M. & Al-Seffar, J. (2009). Preliminary report on aerotoxic syndrome (AS) and the need for diagnostic neurophysiological tests. American Journal of Electroneurodiagnostic Technology 49 (3): 260–279. Review.
  281. Oakes, M. & Bor, R. (2010). The psychology of fear of flying (part I): a critical evaluation of current perspectives on the nature, prevalence and etiology of fear of flying. Travel Medicine and Infectious Diseases 8 (6): 327–338. Review.
  282. Oakes, M. & Bor, R. (2010). The psychology of fear of flying (part II): a critical evaluation of current perspectives on approaches to treatment. Travel Medicine and Infectious Disease 8 (6): 339–363. Review.
  283. Laker, M. (2012). Specific phobia: Flight. Activitas Nervosa Superior 54 (3–4): 108–117.
  284. Yong, L. et al. (2009). Increased frequency of chromosome translocations in airline pilots with long-term flying experience. Occupational and Environmental Medicine, 66 (1): 56–62.
  285. Nicholas, J. et al. (2003). Stable chromosome aberrations and ionizing radiation in airline pilots. Aviation Space and Environmental Medicine 74 (9): 953–956.
  286. Sanlorenzo, M. et al. (2015). The risk of melanoma in airline pilots and cabin crew: a meta-analysis. JAMA Dermatology 151 (1): 51–58.
  287. Oksanen, E. (2015). Ionisoiva säteily. STUK. [luettu: 21.6.2016]
  288. Guan, J. et al. (2004). Effects of dietary supplements on space radiation-induced oxidative stress in Sprague-Dawley rats. Radiation Research 162 (5): 572–579.
  289. Zhao, W. et al. (2011). [Protective effects of astaxanthin against oxidative damage induced by 60Co gamma-ray irradiation]. Wei Sheng Yan Jiu 40 (5): 551–554. Chinese.
  290. Guan, J. et al. (2006). Effects of dietary supplements on the space radiation-induced reduction in total antioxidant status in CBA mice. Radiation Research 165 (4): 373–378.
  291. Fang, Y. & Yang, S. & Wu, G. (2002). Free radicals, antioxidants, and nutrition. Nutrition 18 (10): 872–879. Review.
  292. Rahman, M. & Kundu, J. & Shin, J. & Na, H. & Surh Y. (2011). Docosahexaenoic acid inhibits UVB-induced activation of NF-κB and expression of COX-2 and NOX-4 in HR-1 hairless mouse skin by blocking MSK1 signaling. PLoS One 6 (11): e28065.
  293. Saada, H. & Said, U. & Mahdy, E. & Elmezayen, H. & Shedid, S. (2014). Fish oil omega-3 fatty acids reduce the severity of radiation-induced oxidative stress in the rat brain. International Journal of Radiation Biology 90 (12): 1179–1183.
  294. Zhang, H. & Lin, A. & Sun, Y. & Deng, Y. (2001). Chemo- and radio-protective effects of polysaccharide of Spirulina platensis on hemopoietic system of mice and dogs. Acta Pharmacologica Sinica 22 (12): 1121–1124.
  295. Singh, S. & Tiku, A. & Kesavan, P. (1995). Post-exposure radioprotection by Chlorella vulgaris (E-25) in mice. Indian Journal of Experimental Biology 33 (8): 612–615.
  296. Shleien, B. & Halperin, J. & Bilstad, J. & Botstein, P. & Dutra, E. Jr. (1983) Recommendations on the use of potassium iodide as a thyroid-blocking agent in radiation accidents: an FDA update. Bulletin of the New York Academy of Medicine 59 (10): 1009–1019.
  297. Yeritsyan, H. et al. (2013). Radiation-modified natural zeolites for cleaning liquid nuclear waste (irradiation against radioactivity). Scientific Reports 3: 2900.
  298. Mullan, B. & Camilleri, M. & Hung, J. (1998). Activated charcoal as a potential radioactive marker for gastrointestinal studies. Nuclear Medicine Communications 19 (3): 237–240.
  299. Czeisler, C. et al. (1999). Stability, precision, and near-24-hour period of the human circadian pacemaker. Science 284 (5423): 2177–21781.
  300. Choy, M. & Salbu, R. (2011). Jet Lag: Current and Potential Therapies. Pharmacy and Therapeutics 36 (4): 221–231.
  301. Gander P. et al. (1998). Flight  crew fatigue V: long-haul air transport operations. Aviation Space and Environmental Medicine 69 (9 Suppl): B37–B48.
  302. Karatsoreos, I. (2012). Effects of circadian disruption on mental and physical health. Current Neurology and Neuroscience Reports 12 (2): 218–225. Review.
  303. Scott, E. (2015). Circadian clocks, obesity and cardiometabolic function. Diabetes, Obesity and Metabolism 17 (Suppl 1): 84–89. Review.
  304. Savvidis, C. & Koutsilieris, M. (2012). Circadian Rhythm Disruption in Cancer Biology. Molecular Medicine 18 (1): 1249–1260.
  305. Partinen, M. (2012). Aikaerorasitus (jet lag). Lääkärikirja Duodecim. [luettu: 19.6.2016]
  306. Eastman, C. & Burgess, H. (2009). How To Travel the World Without Jet lag. Sleep Medicine Clinics 4 (2): 241–255.
  307. Reynolds, N. Jr. & Montgomery, R. (2002). Using the Argonne diet in jet lag prevention: deployment of troops across nine time zones. Military Medicine 167 (6): 451–453.
  308. Fuller, P. & Lu, J. & Saper, C. (2008). Differential rescue of light- and food-entrainable circadian rhythms. Science 320 (5879): 1074–1077.
  309. Lee, H. Kim, S. & Kim, D. (2014). Effects of exercise with or without light exposure on sleep quality and hormone reponses. Journal of Exercise Nutrition & Biochemistry 18 (3): 293–299.
  310. Forbes-Robertson, S. et al. (2012). Circadian disruption and remedial interventions: effects and interventions for jet lag for athletic peak performance. Sports Medicine 42 (3): 185–208.
  311. Chevalier, G. & Sinatra, S. & Oschman, J. & Sokal, K. & Sokal, P. (2012). Earthing: Health Implications of Reconnecting the Human Body to the Earth’s Surface Electrons. Journal of Environmental and Public Health 2012: 291541.
  312. Chevalier, G. & Melvin, G. & Barsotti, T. (2015). One-hour contact with the Earth’s surface (grounding) improves inflammation and blood flow – A randomized, double-blind, pilot study. Health 7 (8): 1022–1059.
  313. Belcaro, G. et al. (2008). Jet-lag: prevention with Pycnogenol. Preliminary report: evaluation in healthy individuals and in hypertensive patients. Minerva Cardioangiologica 56 (5 Suppl): 3–9.
  314. Herxheimer, A. & Petrie, K. (2002). Melatonin for the prevention and treatment of jet lag. The Cochrane Database of Systematic Reviews (2): CD001520. Review.
  315. Lyssenko V. et al. (2009). Common variant in MTNR1B associated with increased risk of type 2 diabetes and impaired early insulin secretion. Nature Genetics 41 (1): 82–88.
  316. Thayer, J &, Ahs, F. & Fredrikson, M. & Sollers, J. 3rd. & Wager, T. (2012). A meta-analysis of heart rate variability and neuroimaging studies: implications for heart rate variability as a marker of stress and health. Neuroscience and Biobehavioral Reviews 36 (2): 747–756.
  317. Pikkujämsä, S. et al.(1999). Cardiac interbeat interval dynamics from childhood to senescence : comparison of conventional and new measures based on fractals and chaos theory. Circulation 100 (4): 393–399.
  318. No authors listed. (1996). Heart rate variability: standards of measurement, physiological interpretation and clinical use. Task Force of the European Society of Cardiology and the North American Society of Pacing and Electrophysiology Circulation 93 (5): 1043–1065.
  319. McCraty, R. et.al. (1996). The effects of emotions  on short-term power spectrum analysis of heart rate variability. American Journal of Cardiology 76 (14): 1089–1093.
  320. Bravata, D. et al. (2007). Using pedometers to increase physical activity and improve health: a systematic review. JAMA 298 (19): 2296–304. Review.
  321. Ledger, D. & McCaffrey, D. (2014). Inside Wearables. Hot the Science of Human Behavior Change Offers the Secret to Long-Term Engagement. Endeavour Partners. [luettu: 12.7.2016]
  322. Suomen virallinen tilasto (SVT): Väestön tieto- ja viestintätekniikan käyttö [verkkojulkaisu]. (2015). Liitetaulukko 15. Reitti- ja paikannussovellusten ja kuntoilusovellusten käyttö matkapuhelimella, aktiivisuusrannekkeiden ja älykellojen käyttö viimeisen 3 kuukauden aikana iän, toiminnan, koulutusasteen, asuinpaikan kaupunkimaisuuden ja sukupuolen mukaan 2015, %-osuus väestöstä. Helsinki: Tilastokeskus. [luettu: 12.7.2016].
  323. Tudor-Locke, C. & Bassett, D. Jr. (2004). How many steps/day are enough? Preliminary pedometer indices for public health. Sports Medicine 34 (1): 1–8. Review.
  324. Boutitie, F. & Gueyffier, F. & Pocock, S. & Fagard, R. & Boissel, J. INDANA Project Steering Committee. INdividual Data ANalysis of Antihypertensive intervention. (2002). J-shaped relationship between blood pressure and mortality in hypertensive patients: new insights from a meta-analysis of individual-patient data. Annals of Internal Medicine 136 (6): 438–448.
  325. Lewington, S. et al. (2002). Age-specific relevance of usual blood pressure to vascular mortality: a meta-analysis of individual data for one million adults in 61 prospective studies. The Lancet 360 (9349): 1903–1913.
  326. Lindeberg, S. & Nilsson-Ehle, P. & Terént, A. & Vessby, B. & Scherstén, B. (1994). Cardiovascular risk factors in a Melanesian population apparently free from stroke and ischaemic heart disease: the Kitava study. Journal of Internal Medicine 236 (3): 331–340.
  327. Gurven, M. & Blackwell, A. & Rodriguez, D. & Stieglitz, J. & Kaplan, H. (2012). Does blood pressure inevitably rise with age? Longitudinal evidence among forager-horticulturalists. Hypertension 60 (1): 25–33.
  328. Mourad, A. & Gillies, A. & Carney, S. (2005). Inaccuracy of wrist-cuff oscillometric blood pressure devices: an arm position artefact? Blood Pressure Monitoring 10 (2): 67–71.
  329. Mourad, A. et al. (2003). Arm position and blood pressure: a risk factor for hypertension? Journal of Human Hypertension 17 (6): 389–395.
  330. Poolsup, N. & Suksomboon, N. & & Kyaw, A. (2013). Systematic review and meta-analysis of the effectiveness of continuous glucose monitoring (CGM) on glucose control in diabetes. Diabetology and Metabolic Syndrome 5: 39.
  331. Liakat, S. et al.  (2014). Noninvasive in vivo glucose sensing on human subjects using mid-infrared light. Biomedical Optics Express 5 (7): 2397–2404.
  332. So, C.-F. & Choi, K.-S. & Wong, T. & Chung, J. (2012). Recent advances in noninvasive glucose monitoring. Medical Devices 5: 45–52.
  333. Zhang, J. & Hodge, W. & Hutnick, C. & Wang, X. (2011). Noninvasive Diagnostic Devices for Diabetes through Measuring Tear Glucose. Journal of Diabetes Science and Technology 5 (1): 166–172.
  334. Zhang, W. & Yunqing, D. Wang, M. (2015). Noninvasive glucose monitoring using saliva nano-biosensor. Sensing and Bio-Sensing Research 4: 23–29.
  335. Veiseh, O. & Tang, B. & Whitehead, K. & Anderson, D. & Langer, R. (2015). Managing diabetes with nanomedicine: challenges and opportunities. Nature Reviews Drug Discovery 14 (1): 45–57.
  336. Dutt-Ballerstadt, R. et al. (2012). A human pilot study of the fluorescence affinity sensor for continuous glucose monitoring in diabetes. Journal of Diabetes Science and Technology 6 (2): 362–370.
  337. Mukai N. et al. (2012). Cut-off values of fasting and post-load plasma glucose and HbA1c for predicting Type 2 diabetes in community-dwelling Japanese subjects: the Hisayama Study. Diabetic Medicine 29 (1): 99–106.
  338. Bae, J. et al. (2011). Optimal range of HbA1c for the prediction of future diabetes: a 4-year longitudinalstudy. Diabetes Research and Clinical Practice 93 (2): 255–259.
  339. Zhang, P. et al. (2005). Efficient cutoff points for three screening tests for detecting undiagnosed diabetes and pre-diabetes: an economic analysis. Diabetes Care 28 (6): 1321–1325.
  340. Gleason, C. & Gonzalez, M. & Harmon, J. & Robertson, R. (2000). Determinants of glucose toxicity and its reversibility in the pancreatic islet beta-cell line, HIT-T15. American Journal of Physiology Endocrinology and Metabolism 279 (5): E997–E1002.
  341. Khaw, K. et al. (2004). Association of hemoglobin A1c with cardiovascular disease and mortality in adults: the European prospective investigation into cancer in Norfolk. Annals of Internal Medicine 141 (6): 413–420.
  342. Bardini, G. & Dicembrini, I. & Cresci, B. & Rotella, C.  (2010). Inflammation Markers and Metabolic Characteristics of Subjects With 1-h Plasma Glucose Levels. Diabetes Care 33 (2): 411–413.
  343. Nichols, G. & Hillier, T. & Brown, J. (2008). Normal fasting plasma glucose and risk of type 2 diabetes diagnosis. American Journal of Medicine 121 (6): 519–524.
  344. Batty, G. & Kivimäki, M. & Davey Smith, G. & Marmot, M. & Shipley, M. (2008). Post-challenge blood glucose concentration and stroke mortality rates in non-diabetic men in London: 38-year follow-up of the original Whitehall prospective cohort study. Diabetologia 51 (7): 1123–1126.
  345. Becker, D. (2012). Suppress deadly after-meal blood sugar surges. Life Extension Magazine. [luettu: 18.7.2016]
  346. Tragante, V et al. (2014). Gene-centric meta-analysis in 87,736 individuals of European ancestry identifies multiple blood-pressure-related loci. The American Journal of Human Genetics 94 (3): 349–360.
  347. Povel, C. et al. (2012). Single nucleotide polymorphisms (SNPs) involved in insulin resistance, weight regulation, lipid metabolism and inflammation in relation to metabolic syndrome: an epidemiological study. Cardiovascular Diabetology 11: 133.
  348. Dziwura, J. & Bińczak-Kuleta, A. & Miazgowski, T. & Ziemak, J. & Widecka, K. (2011). The associations between G972R polymorphism of the IRS-1 gene, insulin resistance, salt sensitivity and non-dipper hypertension. Hypertension Research 34 (10): 1082–1086.
  349. Zheng, J. et al.  (2013). Modulation by dietary fat and carbohydrate of IRS1 association with type 2 diabetes traits in two populations of different ancestries. Diabetes Care 36 (9): 2621–2627.
  350. Obisesan, T. et al. (2006). C-reactive protein genotype affects exercise training—induced changes in insulin sensitivity. Metabolism: Clinical and Experimental 55 (4): 453–460.
  351. Machicao, F. et al. (2004). Association of the -514C–>T polymorphism in the hepatic lipase gene (LIPC) promoter with elevated fasting insulin concentrations, but not insulin resistance, in non-diabetic Germans. Hormone and Metabolic Research 36 (5): 303–306.
  352. Todorova, B. et al. (2004). The G-250A promoter polymorphism of the hepatic lipase gene predicts the conversion from impaired glucose tolerance to type 2 diabetes mellitus: the Finnish Diabetes Prevention Study. Journal of Clinical Endocrinology and Metabolism 89 (5): 2019–2023.
  353. Hossein-nezhad, A. et al. (2009). Association of VDR gene polymorphism with insulin resistance in diabetic patients. Journal of Diabetes and Metabolic Disorders 8 (1): 143–150.
  354. Jain, R. et al. (2012). Association of vitamin D receptor gene polymorphisms with insulin resistance and response to  vitamin D. Metabolism 61 (3): 293–301.
  355. Ortlepp, J. et al. (2003). The vitamin D receptor gene variant and physical activity predicts fasting glucose levels in healthy young men. Diabetic Medicine 20 (6): 451–454.
  356. Prakash, J. & Mittal, B. & Awasthi, S. & Srivastava, N. (2015). Association of Adiponectin Gene Polymorphism with Adiponectin Levels And Risk for Insulin Resistance Syndrome. International Journal of Preventive Medicine 6: 31.
  357. Fumeron, F. et al. (2004). Adiponectin gene polymorphisms and adiponectin levels are independently associated with the development of hyperglycemia during a 3-year period: the epidemiologic data on the insulin resistance syndrome prospective study. Diabetes 53 (4): 1150–1157.
  358. Chung, H. et al. (2009). Influence of adiponectin gene polymorphisms on adiponectin level and insulin resistance index in response to dietary intervention in overweight-obese patients with impaired fasting glucose or newly diagnosed type 2 diabetes. Diabetes Care 32 (4): 552–558.
  359. Ortlepp, J. et al. (2003). Relation between the angiotensinogen (AGT) M235T gene polymorphism and blood pressure in a large, homogeneous study population. Journal of Human Hypertension 17 (8): 555–559.
  360. Mondry, A. & Loh, M. & Liu, P. & Zhu, A.-L. & Nagel, M. (2005). Polymorphisms of the insertion / deletion ACE and M235T AGT genes and hypertension: surprising new findings and meta-analysis of data. BMC Nephrology 6, 1.
  361. Ichihara, A. et al. (2010) Possible roles of human (pro)renin receptor suggested by recent clinical and experimental findings. Hypertension Research 33 (3): 177–180. Review.
  362. Ott, C. et al. (2011). Association of (pro)renin receptor gene polymorphism with blood pressure in Caucasian men. Pharmacogenetics and Genomics 21 (6): 347–349.
  363. Sookoian, S. & Gianotti, T. & González, C. & Pirola, C. (2007). Association of the C-344T aldosterone synthase gene variant with essential hypertension: a meta-analysis. Journal of Hypertension 25 (1): 5–13. Review.
  364. Song, Y. et al. (2008). Influence of CYP11B2 gene polymorphism on the prevalence of hypertension and the blood pressure in Japanese men: interaction with dietary salt intake. Journal of Nutrigenetics and Nutrigenomics 1 (5): 252–258.
  365. Young, R. & Seung-Ho, H. (2015). Gender-specific association of polymorphisms in the 5′-UTR and 3′-UTR of VEGF gene with hypertensive patients. Genes and Genomics 37 (6): 551–558.
  366. Hermann, M. & Flammer, A. & Lüscher, T. (2006). Nitric oxide in hypertension. Journal of ClinicalHypertension 8 (12 Suppl 4): 17–29. Review.
  367. Levinsson, A. & Olin, A. & Björck, L, Rosengren A, Nyberg F. (2014). Nitric oxide synthase (NOS) single nucleotide polymorphisms are associated with coronary heart disease and hypertension in the INTERGENE study. Nitric Oxide 39: 1–7.
  368. Berryhill, M. & Wiener, M. & Stephens, J. & Lohoff, F. & Coslett, H. (2013). COMT and ANKK1-Taq-Ia Genetic Polymorphisms Influence Visual Working Memory. PLoS ONE 8 (1): e55862.
  369. Zhang, Q. et al. (2012). The effects of CACNA1C gene polymorphism on spatial working memory in both healthy controls and patients with schizophrenia or bipolar disorder. Neuropsychopharmacology 37 (3): 677–684.
  370. Dietsche, B. et al. (2014). The impact of a CACNA1C gene polymorphism on learning andhippocampal formation in healthy individuals: a diffusion tensor imaging study. Neuroimage 89: 256–261.
  371. Yamada, K. & Nabeshima, T. (2003). Brain-derived neurotrophic factor/TrkB signaling in memory processes. Journal of Pharmacological Science 91 (4): 267–270. Review.
  372. Canivet, A. et al. (2015). Effects of BDNF polymorphism and physical activity on episodic memory in the elderly: a cross sectional study. European Review of Aging and Physical Activity 12: 15.
  373. Skuse, D. et al. (2014). Common polymorphism in the oxytocin receptor gene (OXTR) is associated with human social recognition skills. Proceedings of the National Academy of Sciences 111 (5): 1987–1992.
  374. Li, J. & Zhao, Y. & Li, R. & Broster, L. & Zhou, C. & Yang, S. (2015). Association of Oxytocin Receptor Gene (OXTR) rs53576 Polymorphism with Sociality: A Meta-Analysis. PLoS One 10 (6): e0131820.
  375. Alfimova, M. et al (2016). Polymorphism C366G of gene GRIN2B and verbal episodic memory: No association with schizophrenia. Russian Journal of Genetics 52 (6): 622–625.
  376. de Quervain, D. et al. (2007).  A deletion variant of the alpha2b-adrenoceptor is related to emotional memory in Europeans and Africans. Nature Neuroscience 10 (9): 1137–1139.
  377. Todd, R. et al. (2013). Genes for emotion-enhanced remembering are linked to enhanced perceiving. Psychological Science 24 (11): 2244–2253.
  378. Kumsta, R. et al. (2010). Working memory performance is associated with common glucocorticoid receptor gene polymorphisms. Neuropsychobiology 61 (1): 49–56.

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