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måndag 11 juli 2022

Järkyttävät suomalaisdieetit

Löytyi tämän päivän IS-lehdestä.Siiehn aikaan kun olin aloittanut lääketieteenopiskelut ja sitten valmistuttua , 1964-1972 aikoihin , suomalaisia vaivasi korkeat kolesteroliarvot  -sellaisia t- 9  välillä olevia arvoja   pidettiin  tavallisina. vastaavasti sydänverisuonitaudit olivat niin yleisiä, että  niiden ongleman laajuutta  vain harva  käsitti, mutta  lääkärikunnassa oli   niitäkin joilla oli  insikti asiaan ja niin alkoi suomalaisen kolesterolin  alnetamisohjelmat  ja dietin sekä lääkityksen  haku tähän ongelmaan.  Anamneeseja otettaessa kysyttiin mm. kanamunien käytöstä ja muusta  ruoan sisällöstä, kun verenpaineet olivat sellaista 200/120 luokkaa useilla korkeiden kolesteroliarvojen ja huoon munuaistoiminnan ohella. Vernsokerit olivat myös  huilkeita ja  diabeteksen käypää hoitoa ei ollut  siinä  moniuolisessa kaaviossaan kuin nykyisin. Lääkkeetkin olivat  hyvin  niukkaa kirjoa. Kun havaittiin, että kolesteroli oli molekyyli, jolla oli erikoinen aineenvaihduntansa, johon ravinnon kolesteroliakin tarvittiin  noin 300 mg jotta  tasapaino tuon  jätemolekyylin  aineenvaihdunnassa olisi maksimaalisen hyvå- koska se säätyy reseptorivälitteisesti- eli voi säätyä  eri suuntiin  ulkoisista tekijöistä kuten dieetistä. kolestgerolia  tarvitsee joka solu hieman sillä solukalvon rakenne vaatii kolestgerolikerroksen jotta  solut ja iho saavat tietyn oikeanlaisen lipiditaspainon ja  keho on "vedenpitävä"-  ennen vanhaan suomalaisilla oli paljon sitä  vanhankansan  nimittämää "tihkunaa"- koska ei ollut tavallista käyttää  kasvisöljyjäkään, joissa on linoli ja linoleenihappoa, niistä tulee ihoa ja solua korjaavat tekijät.kovien rasvoje osuus oli tietysti  suuri verrattuna   nykyiseen rasvaäaineiden suositetltuun jakaumaan.  Kolesterolin nykyinen  suositus  vastaa  yhden keltuaisen määrää  vuorokaudessa.  Sen keho  pystyy käsittelemään  niin ettei  metabolia  säädy  normaalitasosta ääriasemiin endogeenin  kolesterolisynteesin suhteen käsittääkseni. 

Munuaisillekin löydettiin  sopiva proteiinirasituksen taso. Diabeteksessa  tosin täytyy ottaa huomioon, että munuaistoiminnalle on eduksi  keveänlainen proteiinirasitus. Elimistöhän pystyy  syntetisoimaan osan  proteiinien rakenneaminohapoista aivan  jätetypestä , jota liitetään hiilihydraattiaineenvaihdunnan  orgaanisiin happoihin ( sitruunahapposyklin  tiettyihin  hiiliketjurakenteisiin ja niin niistä tulee perustavia aminohappoja) Osa aminohapoista noin 8 kappaletta  20:stä rakenneaminohaposta  nimitetään essentielleiksi, koska  niitä  saa vain ravinnosta ja niitä pystyy syntetisoitumaan vain kasvikunnassa  tai sitten niitä voi saada   valmiissa liharuoassa   animaalisista rakenteista purkamalla aineenvaihdunnan entsyymien avulla: tietyt eläimet syövät  paljon  ruohoa   ja saavat  kasvien valmistamia  aminohappoja  kuodksiinsa. Yleensä sanotaan nyrkkisääntönä että ihminen tarvitsee  proteiinia ravinnossa noin gramman painokiloaan kohti. Jos munuaistoiminta kehnonee, tuota  grammaa  pienennetään sopivasti munuaisia helpottavaan  määrään,   esim 0.6 g/ painokilo.  Toinen keino helpotaa munuaisia on  pitäää hedelmä tai kasvisvälipäiviä, sillä proteiinin tarve aikayksikköä kohden on  eri  tavalla mitattua kuin esim hiilihydraattienergian  tarve. Proteiinin saannin voi  laskea esim viikkoa kohden riittäväksi, jos tarkoituksena on pitää painoa ennallaan. proteiinielaatujen vaihtelu on myös  edullista  keholle:  kala joskus, kanaa joskus, hernetta ja papua joskus, pähkinää, siemenravintoa,  punaista lihaa  harvemmin,  itseasiasas kaikissa  ruoissa on proteiinia , kasvisruoissakin, sillä proteiini pitää energia-aineet rakenteina: hiilihydraatit ja rasva ovat  energiaa ja ne sijaitsevat proteiinirakenteissa kuin astiassa, joten  kaikessa ravinnossa  on proteiinia siinä mielessä. 

Yleensä ravintotaulukot  annetaan 100 gramman painomäärää kohden. Esim  100 grammaa  kalaa  antaa noin 18 g proteiinia.  Kalkkuna on  aika tiivistä lihaa ja siitä saa proteiinia yli 20 g / 100g.  Leivässä on taas noin 7-10 g proteiinia sadassa grammassa.  

Jos  on verenpainetta ja  munuaistoiminta normaalin alakantissa, kannattaa  käyttää proteiinnia alle 1 g painokiloa kohden päivässä. Jos painaa 70 kg tuo määrä olisi 70 grammaa. Jos todellakin kokoaa ravinnossaan  yhtenä päivänä koko 70 grammaa proteiinia, saa tosiaan katsoa ettei siten ole  verenpaineessa heijastumaa, muta paljon voi johtua siitä, miten suolaa. Vähäsuolaisena voi tuollainen 70 gramman  proteiinimäärä  mennä " verenpaineen huomaamatta" .   Toiset  tuntevat proteiinilaadut nivelissä. Jos nivelet tuntuvat kipeiltä jonkin proteiinilaaduun jälkeen, kannattaa siirtyä kohti  vähäpuriinisia proteiinilaatuja ( maitoproteiinit, kananmunanvalkuainen, tuorejuustot, kasvisproteiinit). Punainen liha on varsinkin  nivelissä tuntuva niillä joilla on jotain ongelmaa pyrimidiinipitoisten lihojen sulattamisen kanssa. ( kihti ja artriittijoukko) .


Jaa jaa.  Atleeteista kyllä sanotaan, että he voivat käyttää  niissä lihaksia  kehittävissä  (varsinkin rikkovissa) amateissaan   suurempiakin proteiinimääriä kuin 1-1,5 grammaa painokiloa kohti,  vaan minun on vaikea käsittää, miten ihmeessä  munuaiset   selviävät sellaisista massiivisista rasitteista. tuo kolesterolikin on  varsinainen jätetuote, se ei käyty energiaksi, se on kuin  kutistuva rysä, jonka pitäisi mennä läpi kehon suoliston kautta ulos lopulta. Se on tärkeä verkkomainen rakenne, jonka tehtävä on muodostavaa vedenpitävyys iholle. , mutta sitä keho  produsoi endogeenisesti kuin baanalta  enemmänkin päivittäin kuin yhden kananmunan keltuainen  (300 mg) .  Tuollainen pieni määrä tarvitaan hillitsemään endogeeniä synteesiä. 

Pohdituttaa seuraavavnlainen dieetti: Se on lisäksi  matalahiilihydraattinen, millä on  vaaransakin. Rasvan määrästä ei mainita.   Vvaikea sanoa mitään  kun dieettiä ei ole ajettu AIVO-ohjelman läpio  se on dieteistien dataohjelma. täällä Ruotsissa.  Jos  nnoin vähille hiilareille menee, on  vaarassa sydämen johtoradan energian saanti. Hisin kimppu.

 




Robert Helenius syö kilon lihaa päivässä – lataa nyt kaunistelemattoman näkemyksen vegeruokavaliosta

Yksi lautasmalli ei sovi kaikille huippu-urheilijoille, kuten Robert Heleniuksen esimerkki osoittaa.

Nyrkkeilijä Robert Helenius saa osan ravinnostaan kotipihaltaan.

6:15

Kilo lihaa kuulostaa varsin suurelta määrältä, kun syöjänä on yksi ihminen ja aikaa ruokailuun on vain vuorokauden verran.

Paperilla näin varmasti onkin, mutta Robert Helenius ei ole kuka tahansa. Kaksimetrinen rautanyrkki on kokemuksen kautta saanut hiottua ruokavalionsa sellaiseksi, että homma toimii ja ruoka maistuu.

– Edelleen se kuuluu ruokavaliooni. Sillä kroppani toimii parhaiten. Päivittäin tarvitsen vähintään 250 grammaa proteiinia. Nauta sopii minulle kaikissa muodoissa, sikaakin syön, ja kanasta en oikein pidä, mutta sitäkin tulee syötyä, luettelee Helenius.

Lumparlandin kauniissa maisemissa, Ahvenanmaalla asuva Helenius elää jonkinlaisessa omavaraistaloudessa, sillä osa ravinnoista kerätään suoraan kotipihasta.

– Meillä on 20 kananmunaa pihassa päivittäin. Talvisin niitä joudutaan ostamaan. Kaikki on luonnollisesti lähiruokaa lihasta lähtien.

Tiu munia ei kuitenkaan riitä edes päiväksi, sillä Heleniuksen proteiinintarvetta täydennetään kananmunilla. Vain hiilihydraattien määrää kontrolloidaan tiukasti.

– On päiviä, jolloin syön 30 kananmunaa kahdessa erässä. Olen jo vuosia mennyt sellaisella puolipaastolla. Hiilareiden määrän täytyy jäädä alle 40 gramman päivässä. Silloin verensokeri ei hypi.

Tuskin kukaan uskoikaan, että kasvisruokavalio siivittäisi isokokoista miestä treenaamaan kovaa päivittäin, tai että saatava ravinto riittäisi palautumiseen.

– Kummeksun hieman sitä, että nykyään promotaan vegeruokavaliota niin paljon. Ei siitä saa tarpeellisia mineraaleja ja vitamiineja. Ihmisten aivopesu on aika kauheaa. Rehut jätän eläimille.

Ruokaviraston julkaisemissa aikuisia koskevissa ravinto- ja ruokasuosituksissa todetaan, että ”lihavalmisteita ja punaista lihaa ei tulisi käyttää enempää kuin 500 g viikossa”. Samoissa ohjeissa lukijoita kannustetaan lisäämään ruokavalioonsa kasviksia. Juureksia, vihanneksia, palkokasveja, sieniä, hedelmiä ja marjoja tulisi ohjeiden mukaan nauttia ”vähintään 500 g päivässä eli noin 5–6 annosta”.

Helenius on asunut Ahvenanmaalla jo vuosia. Hän nauttii luonnon läheisyydestä, eläimistä ja siitä, että on tilaa temmeltää.

– Ahvenanmaalla varmasti pysytään. Ei minulla ole kiire minnekään. Lapset käyvät täällä koulua, ja minulla on oma sali täällä. Kun on pinna kireällä, voi mennä koiran kanssa metsään, ja heti tuntuu paremmalta.

– Lappi voisi olla sitten eläkkeellä sopiva paikka. Siellä voisi mennä metsään yksin moneksi päiväksi ilman puhelinta, Helenius maalailee.

lördag 12 februari 2022

B.1 Sars-2 viruslinjan avulla tutkittu VOC-virusten patogeenisuutta

 https://www.sciencedirect.com/science/article/pii/S1876034121004263#bib0085

Heikennetty viruskanta sars-2 NIV-2020 on perustana Covaxin rokotteessa

 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7366528/

2020 Feb-Mar; 151(2-3): 244–250.
PMCID: PMC7366528
PMID: 32362649
First isolation of SARS-CoV-2 from clinical samples in India
 

MEGA software version 7.0.11 was used for the multiple alignments of the sequences retrieved in this study and the sequences from the Global Initiative on Sharing All Influenza Data (GISAID) database (https://www.gisaid.org/) (Supplementary Table (available from http://www.ijmr.org.in/articles/2020/151/2/images/IndianJMedRes_2020_151_2_244_282559_sm7.pdf)). A neighbour-joining tree was generated using the best substitution model (Kimura 2-parameter model) with a bootstrap of 1000 replicates. As per Tang et al, the circulating SARS-CoV-2 can be grouped into two types (S and L type) based on the two different single-nucleotide polymorphisms (SNPs) at positions 8782 and 28144 in the genome. The S type possesses TC SNPs while the L type possesses CT SNPs at positions 8782 and 28144, respectively. In the present study, it was observed that two sequences from clinical samples (nCoV-763 and nCoV-770) had TT SNPs, while the other sequences had CT as the SNP (L type) (Table II). The TT SNPs have been observed in few of the GISAID sequences, including one of the Kerala genome sequences (nCoV-19/India/31 January 2020) submitted by us earlier. All the isolates of the clinical samples were of L type. Specific amino acid mutations in the nsp3 region, spike protein and ORF8, in general, lead to the formation of V, G and S genetic variants/clades, respectively, as per the recent classification followed by GISAID. It was observed that the clinical samples, as well as the isolates, had the mutation D614G in the spike protein, classifying the study samples and isolates into the G clade (Table II and Fig. 4). No specific substitutions were observed in any of the isolate sequences with respect to the corresponding clinical sample sequences, as these were sequences from a low passage. The sequences of the clinical samples and the isolate from the contact of the infected Delhi-based individual, who returned from Italy, further showed two mutations, R203K and G204R in the nucleocapsid protein (N). Although all strains demonstrated 99.6 per cent identity with the original Wuhan Hu-1 sequence, the role of unique SNPs and mutations in identifying the source of infection needs to be explored.

 

COVAXIN rokote on inaktivoitua Sars-2 virusta, jossa on immunostimulatorinen ingredienssi

https://assets.researchsquare.com/files/rs-1332649/v1/fefdc6fb-b855-41d2-b2f1-07812c0f1115.pdf?c=1644355488

 

Covaxin Vaccine Efficacy, Price, Side Effects, Dose Gap

Here you will discover all information on the Covaxin Vaccine, including its effects, the vaccine’s effective period in the body, vaccination protocols, and much more. Our company has offered all nuances to supply knowledge to those who need it.

Covaxin Vaccine

Bharat Biotech, an Indian biotechnology business, and the Indian Council of Medical Research produced Covaxin, a COVID-19 vaccine. According to interim phase 3 clinical data, it’s a two-dose vaccination with a 78 percent effectiveness rate.

On January 3, 2021, India’s drug regulatory authorities, the Central Drugs Standard Control Organization, approved the vaccine for emergency use. People aged 18 and above may now receive vaccinations with it. Bahrain, Botswana, Iran, Mexico, Nepal, the Philippines, Vietnam, Paraguay, Zimbabwe, Guyana, Trinidad & Tobago, and Mauritius are among the 12 approved vaccines for emergency use.

Covaxin, also known as BBV152, is an inactivated vaccine, a form of whole-virus vaccination. A modified or dead form of the virus, SARS-CoV-2, is included in an inactivated vaccine, which cannot reproduce and cause sickness.

The virus is an inactivated vaccine that activates the immune system and causes the body to manufacture antibodies, preparing it to fight infection in the future.

Covaxin Efficacy

In India, 25,800 people ranging in age from 18 to 98 took part in the Phase 3 experiment. Two thousand four hundred thirty-three of them were above 60, and 4,500 had pre-existing medical disorders (comorbidities) such as cardiovascular disease, diabetes, or obesity.

Covaxin demonstrated a 93.4 percent effectiveness against severe COVID-19 illness and an overall vaccination efficacy of 77.8 percent against symptomatic infections validated by PCR testing, according to the research. The point against asymptomatic COVID-19 was 63.6 percent. At least two weeks following the second dose, the vaccination provided 65.2 percent protection against symptomatic infection with the Delta variant.

COVAXIN proved to be 77.8% effective against symptomatic COVID-19 illness in a study of 130 confirmed cases, including 24 cases in the vaccination group and 106 in the placebo group. The effectiveness studies show that it protects against asymptomatic COVID-19 by 63.6 percent. 93.4 percent effectiveness against severe symptomatic COVID-19 illness has been shown.

Covaxin is licensed for emergency use in 15 countries outside India, including Iran, Zimbabwe, Mexico, the Philippines, Guatemala, and Botswana. Bharat Biotech has also struck agreements with Ocugen, a biopharmaceutical firm in the United States, to develop the vaccine for the North American market and Precisa Medicamentos, a business based in Brazil, subject to further studies and regulatory clearance.

 

torsdag 10 februari 2022

COVID-19 ja metabolomin tuotteiden esiintymiä taudin pahetessa

 https://www.nature.com/articles/s41598-022-05667-0

 

Introduction

SARS-COV-2 (severe acute respiratory syndrome coronavirus 2) is extremely infectious and has triggered a global pandemic. Infection of the lungs and human respiratory tract by this coronavirus leads to fever, myalgia and cough, and in some patients to acute respiratory distress syndrome (ARDS). While most patients experience very mild-to-moderate symptoms, around one in five patients develop pneumonia coupled with severe respiratory distress. These patients require treatment in hospital intensive care units (ICU), where infection can lead to multi-organ dysfunction, failure, and sometimes death. The COVID-19 (coronavirus disease 2019) pandemic has led to urgent and intense investigations of this disease, its causative agent, and its interaction with the human host. However, there are still many difficulties for an accurate SARS-CoV-2 patient’s risk categorization, which are consequences of COVID-19 complexity since coronavirus infection reflects a broad spectrum of patient symptoms, and as a result, diverse pathophysiological pathways are perturbed during the disease course. This complexity has taken to many groups to investigate this exciting topic using metabolomics, given that the circulating metabolome provides a snapshot of the physiological state of the organism1,2.

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 Many topics have been addressed regarding COVID-19 disease using metabolomics, for instance, metabolomics has displayed sex-specific metabolic shifts in non-severe COVID-19 patients during recovery process, showing that the major plasma metabolic changes were fatty acids in men and glycerophosphocholines and carbohydrates in women5. Metabolomics has also shown that it is possible to differentiate plasma metabolite profiles of COVID-19 survivors with abnormal pulmonary function from those of healthy donors or subjects with normal pulmonary function. These alterations mainly involved amino acid and glycerophospholipid metabolic pathways, increased levels of triacylglycerols (TG), phosphatidylcholines (PC), prostaglandin E2, arginine, and decreased levels of betain and adenosine6. Since many issues regarding the immune, both innate and adaptive, response remains unclear, they are subject to ongoing multi-omic investigations1, as well as comprehensive meta-analysis of global metabolomics datasets of COVID-192. Metabolomics also showed that more than 100 lipids including glycerophospholipid, sphingolipids, and fatty acids (FA) were downregulated in COVID-19 patient sera, probably because of damage to the liver, which is also reflected in aberrancy in bilirubin and bile acids7. Significant differences were also determined between COVID-19 patients and healthy controls in terms of purine, glutamine, leukotriene D4 (LTD4), and glutathione metabolisms. Decrease levels were determined in R‐S lactoglutathione and glutamine (Q, gln)  , and increase levels were detected for hypoxanthine, inosine, and LTD48).

As mentioned above, there are still many difficulties for an adequate categorization of SARS-COV-2 patients through the use of potential metabolic markers of clinical severity identified at the beginning of the COVID-19 disease, reason why many different works have addressed this challenging topic. Thus, using high-throughput omics, the dynamic changes in the metabolome (and proteome) profile of non/severe to severe disease cohorts were studied, and they could be used to predict the disease development: for example, the simultaneous decline in the levels of malic acid and glycerol 3-phosphate in healthy to mild to fatal groups9. On the other hand, the level of guanosine monophosphate was found to be modulated along with carbamoyl phosphate in mild to severe patients, suggesting the role of immune dysfunction and nucleotide metabolism in the progression of non/severe COVID-19 to severe condition9.

Danlos et al. also reported alterations in the plasma metabolome reflecting the clinical presentation of COVID-19 patients with mild (ambulatory) diseases, moderate disease (radiologically confirmed pneumonitis, hospitalization and oxygen therapy), and critical disease (in intensive care)10; and altered tryptophan (w, trp) metabolism into the kynurenine pathway has been related to inflammation and immunity in critical COVID-19 patients in comparison to mild disease patients10. Increased levels of kynurenine and decreased levels of arginine (R, arg) , sarcosine and LPC were also observed as the top-performing metabolites for identifying COVID-19 positive patients from healthy control subjects11. The role of the tryptophan-nicotinamide pathway, linked to inflammatory signals and microbiota, and the involvement of cytosine were also described as possible markers to discriminate and predict the disease evolution12.

Xiao et al. characterized the globally dysregulated metabolic pathways and cytokine/chemokine levels in COVID-19 patients compared to healthy controls. They identified the escalated correlations between circulating metabolites and cytokines/chemokines from mild to severe patients, and revealed the disturbed metabolic pathways linked to hyper-inflammation in severe COVID-19, demonstrating that arginine (R), tryptophan (W), or purine metabolism modulates the inflammatory cytokine release13.

As can be deduced from above and other works14,16,16, the biological mechanisms involved in SARS-CoV-2 infection are only partially understood. Thus in the current work we have explored the plasma metabolome of non-COVID controls as well as 145 COVID patients at diagnose through reverse phase liquid chromatography coupled to quadrupole-time of flight mass spectrometry (RP/HPLC-qTOF MS/MS) analysis. Moreover, patients were stratified based on their clinical evolution in asymptomatic (not requiring hospitalization), patients with mild disease (defined by a total time in hospital lower than 10 days), patients with severe disease (defined by a total time in hospital over 20 days and/or admission at the ICU) and patients with fatal outcome or deceased. In addition, follow up samples between 2 and 3 months after hospital discharge were also obtained from the hospitalized patients with mild prognosis to investigate the disease sequels in the metabolome and how the recovery is reflected in the altered biological pathways. The final goal of the currents work is to find biomarkers that will increase our understanding about how the COVID-19 illness evolves and will improve our prediction about how a patient could progress based on the metabolites profile of plasma obtained at an early stage of the infection.

Results
....
The full list of identified metabolites for each ionization mode together with the statistical values for the different analyses (ANOVA, U test and PLS-DA) is shown in Supplementary Tables S1 and S2.

 The correlation analysis showed different sets of metabolites with similar abundancy among the analyzed groups. In ESI (+), several acylcarnitines (3-hydroxybutyrylcarnitine, hexanoyl-l-carnitine, decanoyl-l-carnitine, octanoyl-l-carnitine, arachidonoyl-l-carnitine, linoleoylcarnitine, acetyl-l-carnitine, lauroylcarnitine, oleoyl-l-carnitine and palmitoyl-l-carnitine), PC/LPC compounds (2-lysophosphatidylcholine, PC (p-16:0/0:0), LPC (o-16:0), LPC (20:2), PC (18:1/16:0), LPC (16:0), LPC (p-18:0), LPC (17:0), PC (18:2e) PC (18:1e) and PC (20:4e)), and amino acids (tryptophan, L-valine, L-isoleucine, L-methionine and L-tyrosine), were grouped together; whereas in ESI (−), the most relevant sets were composed by LPC, FA derivatives or bile acids (glycodeoxycholic acid, taurodeoxycholic acid, glycocholic acid, glycoursodeoxycholic acid and taurocholic acid). The Pearson correlation (r) values and the respective p-values are presented in Supplementary Tables S3 and S4 for ESI (+), and Supplementary Tables S5 and S6 for ESI (−).

 The Mann–Whitney U test between the different COVID-19 positive groups and the non-COVID control group showed 8 metabolites altered in the asymptomatic group (5 of them with increased values and 3 with decreased values). The number of significantly altered metabolites increased to 26 in the mild disease group, 14 and 12 with increased and decreased values, respectively. Some of them were already observed as altered in the asymptomatic group, such as S-methyl-3-thioacetaminophen and nicotinamide riboside cation, which values increased more in the mild disease group; and N-methyl-2-pyrrolidone, trimethoprim and L-methionine, which values continued to decrease in the mild disease group. In the severe disease group, the number of significantly altered metabolites rose to 45 (32 with increased and 13 with decreased values); and for the deceased group, the total number of altered metabolites was 35 (23 with increased values and 12 with decreased values). Many of these metabolites were already observed as significant in the previous PLS-DA and ANOVA analyses.

 The further analysis of the fold change ratio patterns obtained in the previous comparisons suggested 8 main clusters to be formed (Fig. 2, the MFuzz membership value and cluster composition are shown in Supplementary Tables S7 and S8).

 This analysis provides 

 a general overview of groups of metabolites with similar alteration patterns between the different groups of samples (after normalization by the non-COVID control group) and allows the combination of ESI (+) and ESI (−) data together since the normalization using the non-COVID control group eliminates the bias derived from the use of different ESI ionization modes. It has to be noted that this analysis does not take into account the statistical differences after a non-parametric Mann–Whitney U test between the COVID-19 positive samples and the control group, as it only clusters the metabolites according to their fold change ratio similarity.

 Among the identified clusters, cluster 1 represented those metabolites which abundance continuously increased from the asymptomatic to the deceased group, and included 3-hydroxybutyrylcarnitine, glycocholic acid, LPE (22:6), nervonic acid and palmitic acid, among others.

 On the other hand, cluster 7 represented those metabolites which abundance continuously decreased from the asymptomatic to the deceased group, and was composed by three PC (PC (16:0/20:4), PC (20:4e) and PC (20:5e)) and tryptophan (W).

 Based on the previous PLS-DA and ANOVA results, metabolites of cluster 6 were of special interest because their abundance was highest in the severe disease and the deceased groups. This cluster included 2-lysophosphatidylcholine, alpha-linolenic acid, linoleic acid or L-isoleucine  (I, ile) , methyl ester. 

Finally, cluster 8 was the most crowded (24 metabolites) and was composed by metabolites which abundance mainly increased in the deceased group. Some of these metabolites were adipoyl-l-carnitine, glycodeoxycholic acid and taurodeoxycholic acid.

In order to provide the chemical classes significantly altered in the different group comparisons, a chemical enrichment analysis using ChemRICH was performed. No chemical classes were significantly altered in the comparison between the asymptomatic and the non-COVID control group;

 but the chemical class “carnitines” was increased, and the “unsaturated lysophosphatidylcholines” was altered (some species increased, others decreased) in the mild disease group

In the case of the severe disease group, “androstenols” were significantly decreased (considering 3 metabolites); xanthines were significantly altered with some species increased, others decreased; and 2-pyridinylmethylsulfinylbenzimidazoles, pyridines and unsaturated fatty acids were significantly increased.

 This last chemical class was also increased in the deceased group, based on the abundance of nervonic acid, linoleic acid, alpha-linolenic acid, trans-vaccenic acid and palmitoleic acid.

 The whole list of chemical classes and the respective p-values obtained for each comparison is presented in Supplementary Tables S9S11, and the representations of all the annotated metabolites onto biochemical networks, constructed using chemical and biochemical similarities from MetaMapp, is shown in Supplementary Figs. S4S7.

Finally, metabolite set enrichment analysis using the significantly altered metabolites in each comparison was performed using MBROLE 2.0 (Table 1). It has to be noted that only 5, 17, 28 and 16 altered metabolites in the asymptomatic, mild disease, severe disease and deceased groups, respectively, could be mapped with valid KEGG IDs (many carnitines and omeprazole derivatives could not be mapped).

Table 1 Significantly enriched KEGG human metabolic pathways (in dark shade) from the analysis of significantly altered metabolites (after Mann–Whitney U test with p-value < 0.05) in asymptomatic, mild disease, severe disease and deceased COVID-19 positive groups as compared to non-COVID control patients.

From: Metabolomics study of COVID-19 patients in four different clinical stages

( Kommenttini: Dietisteille  tämä on  ajattelemisen aihetta). 

Lipoproteiinit, apolipoproteiinit ja nutrientit

 https://academic.oup.com/edrv/article/27/1/2/2355160

The Effect of Select Nutrients on Serum High-Density Lipoprotein Cholesterol and Apolipoprotein A-I Levels
Endocrine Reviews, Volume 27, Issue 1, 1 February 2006, Pages 2–16, https://doi.org/10.1210/er.2005-0013
Published:
01 February 2006

K1 vitamiinin fyllokinonin ja E-vitamiinin kuljttajalipoproteiinit

 https://pubmed.ncbi.nlm.nih.gov/10509895/

 

. 1999 Sep;287(1-2):45-57.
doi: 10.1016/s0009-8981(99)00117-5.

Interdependence of serum concentrations of vitamin K1, vitamin E, lipids, apolipoprotein A1, and apolipoprotein B: importance in assessing vitamin status

Affiliations