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🥳 Paper accepted in #JMolEndo @socendocrinology.bsky.social - great work by Nuria Lopez Alcantara on the role of #deiodinase I in #MASH. Stay tuned for the full version in the next 24 hours! Spoiler alert: Dio1 is not the key to fixing MASH. At least not by itself...

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Figure from chapter 2 of the book "Hypothyroidism – A Paradigm Shift". Relational stability between TSH, FT4 and FT3 and preservation of FT3 homeostasis (a), FT3 concentrations do not parallel the decline of FT4 concentrations but remain homeostatically controlled and stable over a wide range of TSH values (b).

Figure from chapter 2 of the book "Hypothyroidism – A Paradigm Shift". Relational stability between TSH, FT4 and FT3 and preservation of FT3 homeostasis (a), FT3 concentrations do not parallel the decline of FT4 concentrations but remain homeostatically controlled and stable over a wide range of TSH values (b).

Figure from chapter 2 of the book "Hypothyroidism – A Paradigm Shift". Absence of relational stability and loss of FT3 homeostasis in athyreotic LT4-treated patients 2.1 above, FT3 homeostasis is broken in the absence of a functioning thyroid gland. It is no longer preserved and protected by TSH and FT4 (a). Rather, FT3 levels are now correlated with both FT4 and TSH concentrations (b).

Figure from chapter 2 of the book "Hypothyroidism – A Paradigm Shift". Absence of relational stability and loss of FT3 homeostasis in athyreotic LT4-treated patients 2.1 above, FT3 homeostasis is broken in the absence of a functioning thyroid gland. It is no longer preserved and protected by TSH and FT4 (a). Rather, FT3 levels are now correlated with both FT4 and TSH concentrations (b).

Relational stability is a major motif of the intertwined feedback loops of #thyroid #homeostasis. The integrated systemic roles and interdependent homeostatically regulated equilibrium of TSH, FT4 and #deiodinase​s maintains appropriate FT3 concentrations.

doi.org/10.1007/978-...

🧪 🩺 #MedSky

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Figure 1. Effect of the rs3811787 of UCP1 gene in human adaptation to cold: (a) The levels of FT3 as a function of rs3811787 genotypes of the UCP1 gene; (b) Association analysis of the TT rs3811787 genotype between SPINA-GD; (c) Association analysis of the TT rs3811787 genotype between BSA; (d) The geographical distribution of the frequencies of the T rs3811787 (UCP1) allele in global human populations to identify signals of natural selection for cold climate adaptation.

Figure 1. Effect of the rs3811787 of UCP1 gene in human adaptation to cold: (a) The levels of FT3 as a function of rs3811787 genotypes of the UCP1 gene; (b) Association analysis of the TT rs3811787 genotype between SPINA-GD; (c) Association analysis of the TT rs3811787 genotype between BSA; (d) The geographical distribution of the frequencies of the T rs3811787 (UCP1) allele in global human populations to identify signals of natural selection for cold climate adaptation.

Figure 2. Effect of the rs1800849 of UCP3 gene on human adaptation to cold: (a) The levels of FT3 as a function of rs1800849 genotypes of the UCP3 gene; (b) Association analysis of TT rs1800849 genotype between SPINA-GD; (c) Association analysis of TT rs1800849 genotype between BSA; (d) The geographical distribution of frequencies of the T rs1800849 (UCP3) allele in global human populations to identify signals of natural selection for cold climate adaptation.

Figure 2. Effect of the rs1800849 of UCP3 gene on human adaptation to cold: (a) The levels of FT3 as a function of rs1800849 genotypes of the UCP3 gene; (b) Association analysis of TT rs1800849 genotype between SPINA-GD; (c) Association analysis of TT rs1800849 genotype between BSA; (d) The geographical distribution of frequencies of the T rs1800849 (UCP3) allele in global human populations to identify signals of natural selection for cold climate adaptation.

Figure 3. The mechanism of BAT-mediated regulation of thyroid hormones and basal metabolic rate from the allelic variants rs3811787 of the UCP1 gene. Note. In the carriers of the T allele, with the active form of the UCP1 protein, brown adipocytes mitochondria use higher concentrations of T3 for increased heat generation during adaptive thermogenesis, which increases T3 clearance and in response increases peripheral deiodination (SPINA-GD), which raises blood levels of FT3 and basal metabolic rate. In carriers of the C allele, with a less active form of the protein, brown adipocytes will use less T3, which will not significantly increase SPINA-GD and blood levels of FT3, hence the metabolic rate will not significantly improve.

Figure 3. The mechanism of BAT-mediated regulation of thyroid hormones and basal metabolic rate from the allelic variants rs3811787 of the UCP1 gene. Note. In the carriers of the T allele, with the active form of the UCP1 protein, brown adipocytes mitochondria use higher concentrations of T3 for increased heat generation during adaptive thermogenesis, which increases T3 clearance and in response increases peripheral deiodination (SPINA-GD), which raises blood levels of FT3 and basal metabolic rate. In carriers of the C allele, with a less active form of the protein, brown adipocytes will use less T3, which will not significantly increase SPINA-GD and blood levels of FT3, hence the metabolic rate will not significantly improve.

#Thyroid hormones play a pivotal role in #thermoregulation and the attunement to hot and cold #climate​s. Recent research found global patterns of variants in the UCP1 and UCP3 genes and #SPINA-GD (step-up #deiodinase activity), suggesting integrated adaptation.

🧪 🩺 #MedSky

doi.org/10.3390/biol...

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Spiel/Game: Institut für Experimentelle EndokrinologieD2 Ball Catching Game

📣 Check out the new thyroid hormone game on our homepage! Use the arrow keys to move the #deiodinase to activate the thyroxine for better #thyroid hormone action! Little surprise in level 10! #claudeAi
www.expendo.uni-luebeck.de/spiel/game

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(A, B) Reliability of SPINA-derived parameters is higher than that of measured hormone concentrations. Shown are results of Monte Carlo evaluation of  SPINA-GT and SPINA-GD based on simulated imprecise hormone assays. Hormone concentrations were modeled in SimThyr 4.0 with different pre-defined values for GT and GD, respectively. Subsequently, absolute hormone levels were converted to measurements by means of an S script that injected additive and multiplicative noise in order to get vendor-reported concentration-dependent coefficients of variation (CV). The lines show the mean SD of hormone concentrations predicted by structure parameters calculated from simulated noisy measurements. CVs as markers for measurement reliability of SPINA-GT and SPINA-GD are below 10% in all cases, although CVs of corresponding hormone assays exceed 20% in low concentrations. 

(C) SPINA-GT is sensitive for thyroid disorders of primary origin and specific with respect to secondary dysfunction. The plots show the distribution of hormone concentrations in certain primary and secondary thyroid conditions compared to normal percentiles of SPINA-GT. The green crossing rectangles define univariate reference ranges for TSH and FT4, respectively. The purple lines represent FT4 concentrations at the 2 and 97% percentiles of SPINA-GT. 

(D) SPINA-GD is an estimate for deiodination. Shown is the correlation between SPINA-GD and conversion rate in slow tissue pools.

(A, B) Reliability of SPINA-derived parameters is higher than that of measured hormone concentrations. Shown are results of Monte Carlo evaluation of SPINA-GT and SPINA-GD based on simulated imprecise hormone assays. Hormone concentrations were modeled in SimThyr 4.0 with different pre-defined values for GT and GD, respectively. Subsequently, absolute hormone levels were converted to measurements by means of an S script that injected additive and multiplicative noise in order to get vendor-reported concentration-dependent coefficients of variation (CV). The lines show the mean SD of hormone concentrations predicted by structure parameters calculated from simulated noisy measurements. CVs as markers for measurement reliability of SPINA-GT and SPINA-GD are below 10% in all cases, although CVs of corresponding hormone assays exceed 20% in low concentrations. (C) SPINA-GT is sensitive for thyroid disorders of primary origin and specific with respect to secondary dysfunction. The plots show the distribution of hormone concentrations in certain primary and secondary thyroid conditions compared to normal percentiles of SPINA-GT. The green crossing rectangles define univariate reference ranges for TSH and FT4, respectively. The purple lines represent FT4 concentrations at the 2 and 97% percentiles of SPINA-GT. (D) SPINA-GD is an estimate for deiodination. Shown is the correlation between SPINA-GD and conversion rate in slow tissue pools.

Calculating #SPINA-GT, #thyroid​'s secretory capacity, and #SPINA-GD, total #deiodinase activity, is evolving towards a standard method of research in #thyroidology, as shown by more than 100 citations of one of our defining papers. 🧪🩺

pubmed.ncbi.nlm.nih.gov/27375554/
doi.org/10.3389/fend...

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Thyroid parameters and body mass index in subclinically or overtly hyperthyroid patients (TSH < 0.4 mIU/l) with toxic adenoma, Graves’ disease or LT4-treated carcinoma, stratified by their FT4 concentration (euthyroid vs hyperthyroid). The hormonal patterns differed between the treatment categories. FT4 concentrations were higher in the treated patients, deiodinase activity was markedly lower, but FT3 concentrations similar. Body mass index was also different between diagnostic categories despite “normal” FT4. Statistical comparison between etiological groups overall and in FT4-subgroups is based on Kruskal-Wallis test

Thyroid parameters and body mass index in subclinically or overtly hyperthyroid patients (TSH < 0.4 mIU/l) with toxic adenoma, Graves’ disease or LT4-treated carcinoma, stratified by their FT4 concentration (euthyroid vs hyperthyroid). The hormonal patterns differed between the treatment categories. FT4 concentrations were higher in the treated patients, deiodinase activity was markedly lower, but FT3 concentrations similar. Body mass index was also different between diagnostic categories despite “normal” FT4. Statistical comparison between etiological groups overall and in FT4-subgroups is based on Kruskal-Wallis test

🧪 With a cut-off value of about 28 nmol/s, total step-up #deiodinase activity (#SPINA_GD) may be used for differential diagnosis between exogenous (factitious) #thyrotoxicosis and true #hyperthyroidism.
doi.org/10.1016/j.jc...
pubmed.ncbi.nlm.nih.gov/32099819/

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The association between TyG index and thyroid parameters shows a strong correlation to SPINA-GD.

The association between TyG index and thyroid parameters shows a strong correlation to SPINA-GD.

Correlation between triglyceride-glucose index and parameters of thyroid homeostasis.

Correlation between triglyceride-glucose index and parameters of thyroid homeostasis.

Total step-up #deiodinase activity (#SPINA_GD) is upregulated in metabolic syndrome, as demonstrated by a strong correlation to the triglyceride-glucose index. pubmed.ncbi.nlm.nih.gov/37946276/ doi.org/10.1186/s400... 🧪

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