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Kongres Novosti u dijabetesu i neuroendokrine neoplazme

 
 
U palači Hrvatske akademije znanosti i umjetnosti u petak 10. travnja otvoren je 4. e-kongres Novosti u dijabetesu i neuroendokrine neoplazme koji su organizali HAZU, Zavod za endokrinologiju, dijabetes i bolesti metabolizma „Mladen Sekso“ i Hrvatsko društvo za endokrinološku onkologiju. Osim stručnjaka iz Hrvatske, u e-kongres su bili uključeni i stručnjaci iz Srbije, Slovenije, Bosne i Hercegovine i Crne Gore pa se e-kongres mogao pratiti i u tim zemljama. Kongres je otvorio predsjednik HAZU-a akademik Zvonko Kusić koji je istaknuo važnost djelovanja Zavoda za endokrinologiju, dijabetes i bolesti metabolizma u Kliničkoj bolnici Sestre milosrdnice koji je 1959. osnovao Mladen Sekso i koji je stekao europsku i svjetsku reputaciju. Podsjetio je i da je u okrilju te bolnice nastao i Medicinski fakultet Sveučilišta u Zagrebu i većina hrvatskih klinika. Do sada su održana već tri e-kongresa iz endokrinologije i dijabetologije i prema riječima akademika Kusića, to je bio značajan iskorak koji je promijenio paradigmu cjeloživotnog obrazovanja liječnika koja se do tada temeljila na klasičnim kongresima. „Time je prestao monopol na znanje pa i liječnici u manjim mjestima imaju mogućnost edukacije“, kazao je akademik Kusić.
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Na otvorenju e-kongresa govorio je i rektor Sveučilišta u Zagrebu prof. dr. sc. Damir Boras koji je podsjetio na početke e-obrazovanja u sklopu Sveučilišta, u čemu je i osobno sudjelovao, i poručio da su e-kongresi iznimno važni u transferu znanja.
 
Prethodna tri e-kongresa naišla su na vrlo dobar odaziv kod liječnika obiteljske medicine, specijalista internista, subspecijalista endokrinologa-dijabetologa i ostalih liječnika. Oko 700 sudionika je do sada odslušalo barem jedan e-kongres, što ovaj projekt svrstava na sam vrh trajne medicinske edukacije u Hrvatskoj. Ovogodišnji kongres podijeljen je u dvije sekcije: Novosti u dijabetesu, s obzirom na epidemiju šećerne bolesti u Hrvatskoj i svijetu te brojne novosti u liječenju, te Neuroendokrine neoplazme koja je posvećena neuroendokrinim tumorima. Incidencija neuroendokrinih tumora je značajno niža u Hrvatskoj u odnosu na gospodarski razvijenije zemlje Europske unije, a jedan od razloga je i manjkavo znanje i svijest o ovom području. Stoga je cilj ovogodišnjeg e-kongresa podići svijest o neuroendokrinim tumorima te educirati liječnike brojnih specijalnosti o dijagnostici i liječenju ovih tumora.
 

Marijan Lipovac

Značajno negativna promjena u sadržaju kolostruma ima i te kako važnu ulogu u rastu mladunčadi

 
 
Dr. Eva Sirinathsinghji, Institute for Science in Society, objavila je vrlo zanimljiv tekst u kojem je predstavila rezultat značajnog znanstvenog istraživanja. Nova znanstvena studija, piše dr. Eva Sirinathsinghji, otkrila je da koze hranjene genetski modificiranom sojom tolerantnom na herbicid glifozat MON 4-3-2 (proizvod kompanije 'Monsanto') imaju znatnu promjenu u sastavu kolostruma, odn. prvog mlijeka izrazito bogatog hranjivim tvarima koje se stvara za vrijeme bređosti. Kolostrum je izrazito bogat sadržajem proteina/bjelančevina, vitamina i antitijela/protutijela koja imaju ulogu u zaštiti novorođenih od različitih bolesti.
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Znanstveni rad objavljen je „online“ 31. siječnja 2015. u časopisu „Small Ruminant Research“ („Istraživanje malih preživača“ - časopis Međunarodnog udruženja uzgajivača koza), a istraživanje je provedeno na Sveučilištu u Napulju, Italija, pod vodstvom prof. Lombardia. Ovo znanstveno istraživanje moramo gledati u svjetlu novijih istraživanja u kojima je otkriveno prisustvo herbicida glifozata (ili glifosata) u humanom majčinom mlijeku diljem SAD-a i to u visokim koncentracijama – 1.600 puta veća koncentracija nego što je zakonom dozvoljena gornja granica sadržaja jednog pesticida u pitkoj vodi u Europskoj uniji.
 
Otkrića stručnjaka od goleme su važnosti jer imaju znatan učinak na zdravlje, budući kolostrum ima značajnu kratkoročnu ulogu na zdravlje i opstanak, odn. preživljavanje kod novorođenih preživača jednako kao i kod novorođenih beba. Nadalje, osim što je kolostrum iznimno bogat hranjivim tvarima, on je bogat i u sadržaju protutijela ili antitijela koja su esencijalno važna za tzv. pasivan prijenos imuniteta s majke na mladunčad u prvih 24 – 48 sati njihovog života. To isto vrijedi i za novorođenčad.
 
Već je dobro poznato da poremećena probava ili apsorbcija antitijela iz kolostruma kod preživača neminovno uzrokuje stanje tzv. sekundarne imunodeficijencije, radi čega je mladunčad znatno podložna bakterijskoj septikemiji i uobičajenim bolestima, dok je rizik od uginuća znatno povećan u prvih 10 tjedana života. Humano majčino mlijeko također ima ulogu u zaštiti novorođenčeta od proljeva, infekcija dišnih putova i nekrotičnog enterokolitisa.
 
U navedenoj studiji sudjelovalo je 40 muške jaradi i njihove majke poznate talijanske pasmine 'Cilantana' iz Napuljske regije. Sve koze su do ovog istraživanja imale isti broj jarenja, a u prethodnim laktacijama dale su slične količine mlijeka. Šezdeset dana prije jarenja sve bređe koze bile su podijeljene u grupe i to: dvije ispitne grupe – svaka grupa 10 koza, i one su hranjene genetski modificiranom/GM sojom; te dvije kontrolne grupe (u svakoj je 10 koza), koje su hranjene konvencionalnom (genetski ne-modificiranom) sojom. Sve skupine hranjene su neograničenom količinom kvalitetnog sijena uz dodatak iste koncentracije konvencionalne soje ili genetski modificirane soje. U svrhu potvrde prisutnosti GM hrane korišten je specifičan laboratorijski test, tzv. lančana reakcija polimeraze koja je također korištena i u dokazu genetski ne-modificirane soje za kontrolnu grupu koza koje su hranjene genetski ne-modificiranom sojom.
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
Eva Sirinathsinghji
 
Kod koza iz ispitnih grupa koje su hranjene genetski modificiranom sojom otkriveno je dramatično smanjenje sadržaja proteina/bjelančevina u kolostrumu: 6,1 % i 6,0 % dok je kod dvije kontrolne grupe sadržaj proteina u kolostrumu bio 18,7 % i 18,8 %. Nadalje, prosječni sadržaj masti u kolostrumu obje kontrolne grupe bio je 7,2 % i 7,1 % dok je kod koza u obje ispitne grupe iznosio 4,6 %. A na kraju ono najvažnije: prosječan sadržj protutijela u kolostrumu koza iz obje kontrolne grupe bio je 33,2 % i 31,2 % dok je kod koza iz obje ispitne grupe (koze hranjene GM sojom) prosječan sadržaj protutijela u kolostrumu bio 20,9 % i 18,0 %.
 
Značajne razlike uočene su i 15 dana nakon jarenja, a sve se vratilo u normalu nakon 30 dana. Smanjena koncentracija protutijela u kolostrumu objašnjava se smanjenim sadržajem proteina, iako nije posve jasno zašto je koncentracija proteina u mlijeku bila smanjena i 15 dana nakon jarenja. Autori ove znanstvene studije smatraju da je to možda zbog manjka B limfocita, stanica koje proizvode protutijela (antitijela). Analiza težine jaradi pokazala je znatno smanjenje težine jaradi u dobi od 30 dana i to onih koza koje su bile hranjene GM sojom: prosječna težina jaradi od koza iz obje ispitne grupe bila je 8,3 kg i 8,2 kg dok je jarad koza iz obje kontrolne grupe imala prosječnu težinu 9,5 kg i 9,4kg. Nadalje, težina jaradi u dobi od 60 dana (netom prije klanja) iz obje ispitne grupe bila je 10,3 kg i 10,1 kg, a težina jaradi iz obje kontrolne grupe bila je 12,5 kg i 12,3 kg. Nije uočena značajna razlika u težini pojedinih unutarnjih organa. No, razina serumskih protutijela (IgG) bila je značajno niža kod jaradi iz obje ispitne grupe.
 
Ova znanstvena studija dokazala je da značajno negativna promjena u sadržaju kolostruma ima i te kako važnu ulogu u rastu mladunčadi, a posljedica je kasnija smanjena težina životinja. Znanstvenici su otkrili i transgenu DNK u kolostrumu koza hranjenih genetski modificiranom sojom. Ovo je otkriveno zahvaljujući nedavnom otkriću transgene DNK iste sekvence  - promotor mozaičnog virusa cvjetače (CaMV 35S) u genomu DNK organa štakora hranjenih genetski modificiranom hranom (naslov originalnog teksta: CaMV 35S Promoter in GM Feed that Sickened Rats Transferred into Rat Blood, Liver and Brain Cells; Science in Society 65, 32-33, 2015.). 
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
Horizontalni prijenos transgene DNK u genom onih koji se hrane genetski modificiranom hranom, ili mikroba koji žive u organizmu onih hranjenih GM hranom, predstavlja još jedan i do sada nepoznat i neotkriven rizik kao i opasnost koju donose genetski modificirane poljoprivredne kulture. Promotor CaMV 35S nosi i svoj vlastiti, specifičan rizik uključujući njegovu sklonost rekombinaciji s DNK, što potencijalno modificira (mijenja) sekvence genoma onih koji se hrane genetski modificiranom hranom. On je također aktivan u stanicama sisavaca, što znači da može utjecati i na ekspresiju ostalih gena, uljučujući i tzv. neaktivne ('spavajuće') viruse. Ovo je sada potpuno novo otkriće koje je u suprotnosti s dosadašnjim tvrdnjama o navodnom cijepanju nukleotida u probavnom traktu, čime se sprječava svaka toksičnost transgene DNK za svakog onog koji konzumira genetski modificiranu hranu.
 
Danas su SAD suočene s najvećom razinom neonatalnog mortaliteta (smrtnosti) od svih industrijaliziranih država. Mnogi različiti faktori sigurno utječu na to, no posve je jasno da cjelovitost prvih obroka novorođenih ima dalekosežne i dugotrajne učinke i mora biti zaštićeno od svakog onečišćenja s pesticidima i genetski modificiranom hranom. [Izvor: dr. Eva Sirinathsinghji, Institute for Science in Society (ISIS izvješće: 16. 3. 2015.)]
 

Prevela: Rodjena Marija Kuhar, dr. med. vet.

Osvrt na intervju Nevena Budaka u Večernjem listu od 10. siječnja 2015.

          
 
Poznato je u eksperimentalnoj znanosti (fizici, kemiji,...) da postojanje sustavne pogrješke, a koja je imanentna samoj metodi mjerenja, onemogućava dobivanje rezultata točnijeg od reda veličine te sustavne pogrješke. Zato su u egzaktnim znanostima odavno shvatili da se sustavna pogrješka može izbjeći samo promjenom metode mjerenja. Primijenimo li ovu logiku na dio društvenih istraživanja, posebno na istraživanja u sustavu naobrazbe, brzo ćemo uočiti da je ta sustavna pogreška ugrađena u samu metodu istraživanja, čak štoviše, uključena je i što je posebno pogubno, u izbor ljudi koji provode ta istraživanja.
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
U osobama Nevena Budaka, profesora s Filozofskog fakulteta, i mladog Borisa Jokića, djelatnika Instituta za društvena istraživanja, uviđamo taj problem. To su osobe koje u istraživanju kvalitete sustava naobrazbe ne mogu izaći iz svog ograničenog i skučenog ''društvenjačkog okvira''. To su osobe (i mnogi njima slični) koje do kraja, i bez ostatka ne mogu same sebi priznati da su se nametnule u pokušaju kreiranja obrazovnog sustava i da su uzrok svih nevolja u sustavu naobrazbe od Šuvarevih vremena do danas. To su osobe koje unatoč vrlo preciznim pokazateljima glede kvalitete našeg obrazovnog sustava, OECD-ovog PISA istraživanja, ne mogu sami sebi priznati da su izvan realnog vremena i prostora.
 
Posljedica je vrtnja u krugu, nesagledavanje bitnih problema u školstvu kao i načina rješavanja tih problema. Da budem konkretan: Jedan od većih problema je nepostojanje realnih i prirodnih kriterija u osnovnom-obvezatnom školstvu, a što se ogleda u činjenici da imamo 75 % odlikaša koji završavaju tu razinu obrazovanja. Oni taj problem guraju pod tepih i bulazne o nekoj devetogodišnjoj obveznoj osnovnoj školi uvodeći 'nulti razred' za dob djeteta od šest godina. Zar će se time nešto bitno postići? Osim naravno zapošljavanja hiperprodukcijski proizvedenih 'teta učiteljica' s burze rada.
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
Bulazne također, kao nekad i Stipe Šuvar, da nam gospodarstvu manjka kadrova iz strukovnog obrazovanja. Da manjka to je točno, ali taj problem je nemoguće početi rješavati ako se ne uvažavaju preporuke OECD-ovog PISA projekta kao i porazni rezultati u znanju matematike i prirodoslovlja, u tom istom istraživanju, naših 15-godišnjaka u tri navrata: 2006., 2009. i 2012. godine. A PISA test je jako važan, posebno za najbogatije države Europe, jer on daje točan pokazatelj kakva će biti ekonomija za 20 godina, jer je dokazano da je PISA test u korelaciji s bruto nacionalnim dohotkom za 20 godina. PISA testovi su globalni pokazatelj sposobnosti učenika u dobi od 15 godina, a ocjenjuju se matematika, čitalačke kompetencije i prirodne znanosti. Naglasak je na primjenjenom znanju, a ne definicijama, nabrajanjima i podjelama popularnim u hrvatskim školama.
 
Zar nije znakovito da nam je profesor Kwong WaiLeung s The Chinese University of Hong Kong,jedan od voditelja PISA projekta, na upit naših školskih 'stručnjaka' što moramo činiti, rekao: ''Naučite djecu do 15 godine dva jezika-engleski i matematiku''?  Spomenuti dvojac ne razumije da problem neodabira strukovnih zanimanja od strane završenih osnovaca, kao i neodabir  'tvrdih studija' (tehnike, prirodoslovlja, matematike…) od strane brucoša nije samo refleksija stanja u društvu, već je prvenstveno posljedica oskudnog znanja mladih iz područja koja su relevantna u PISA istraživanjima. Za ilustraciju može poslužiti činjenica da je zagrebački FER uveo po prvi puta od kada postoji repetitorij iz matematike i fizike u prvom semestru za brucoše. I sve dok spomenuta (i slična ) gospoda pišu strategije obrazovanja možemo pjevati: ''Nema nam pomoći…''
 

Miroslav Dorešić

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Zašto A. Plenković i dalje brani nepostojeći "dan antifašističke borbe" 22. lipnja?

Četvrtak, 14/11/2019

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