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Somatomedins

Somatomedins are a group of insulin-like growth factors that mediate the effects of growth hormone.
They play a key role in regulating cell growth, proliferation, and differentiation.
Somatomedins include IGF-I and IGF-II, which are essential for normal development and maintenance of tissues.
Understanding the complex biology of somatomedins is crucial for research into growth, metabolism, and related disorders.
This MeSH term provides a concise overview of this important class of signaling molecules.

Most cited protocols related to «Somatomedins»

1
Cardiometabolic Traits and BF% Associations
Cited 38 times
Cardiometabolic consortia. To explore the relationship between
BF% and an array of cardiometabolic traits and diseases, the
association results for the 12 GWS-index SNPs were requested from seven primary
cardiometabolic genetic consortia: the LEPgen consortium (circulating leptin,
Kilpeläinen et al., in preparation), VATGen consortium27 (link), GIANT (BMI, height and WHRadjBMI)19 (link)20 (link)26 (link), GLGC (HDL-C, LDL-C, TG, TC)28 (link),
MAGIC29 (link), DIAGRAM (T2D)30 (link) and CARDIoGRAMplusC4D
(CAD)31 (link). On the basis of known correlations among these
cardiometabolic traits, we considered circulating leptin levels, abdominal
adipose tissue storage, height, WHRadjBMI, plasma lipid levels,
plasma glycemic traits, T2D and CAD as eight independent trait groups. In
addition, the associations for these 12 SNPs were also looked up in four
consortia that examined phenotypes more distantly related to BF%:
ADIPOGen (BMI-adjusted adiponectin)64 (link), ReproGen (age at
menarche)24 (link), liver enzyme meta-analysis65 (link) and
CRP meta-analysis38 (link). For certain GWAS-index SNPs, we also did
specific lookups: rs6857 association in liver fat storage, rs3761445
associations in cutaneous nevi and melanoma risk meta-analysis42 (link)43 (link)44 (link), early growth genetics (birth weight32 (link)
and pubertal height33 (link)), insulin-like growth factor 1
meta-analysis (Teumer et al. under review) and CHARGE testosterone
meta-analysis66 (link), and rs9906944 associations in tooth
development meta-analysis35 (link) and Early Growth Genetics Consortium
(birth weight32 (link) and pubertal height33 (link)).
NHGRI GWAS catalogue lookups. We manually curated and searched the
National Human Genome Research Institute (NHGRI) GWAS Catalogue ( www.genome.gov/gwastudies)
for previously reported associations for SNPs within 500 kb and
r2>0.7 (1000 Genomes Pilot1 EUR
population based on SNAP: http://www.broadinstitute.org/mpg/snap/ldsearch.php) with each of
the 12 GWS-index SNPs. All previously reported associations that reached
P<5 × 10−8 were retained
(Supplementary Table 11).
Lu Y., Day F.R., Gustafsson S., Buchkovich M.L., Na J., Bataille V., Cousminer D.L., Dastani Z., Drong A.W., Esko T., Evans D.M., Falchi M., Feitosa M.F., Ferreira T., Hedman Å.K., Haring R., Hysi P.G., Iles M.M., Justice A.E., Kanoni S., Lagou V., Li R., Li X., Locke A., Lu C., Mägi R., Perry J.R., Pers T.H., Qi Q., Sanna M., Schmidt E.M., Scott W.R., Shungin D., Teumer A., Vinkhuyzen A.A., Walker R.W., Westra H.J., Zhang M., Zhang W., Zhao J.H., Zhu Z., Afzal U., Ahluwalia T.S., Bakker S.J., Bellis C., Bonnefond A., Borodulin K., Buchman A.S., Cederholm T., Choh A.C., Choi H.J., Curran J.E., de Groot L.C., De Jager P.L., Dhonukshe-Rutten R.A., Enneman A.W., Eury E., Evans D.S., Forsen T., Friedrich N., Fumeron F., Garcia M.E., Gärtner S., Han B.G., Havulinna A.S., Hayward C., Hernandez D., Hillege H., Ittermann T., Kent J.W., Kolcic I., Laatikainen T., Lahti J., Leach I.M., Lee C.G., Lee J.Y., Liu T., Liu Y., Lobbens S., Loh M., Lyytikäinen L.P., Medina-Gomez C., Michaëlsson K., Nalls M.A., Nielson C.M., Oozageer L., Pascoe L., Paternoster L., Polašek O., Ripatti S., Sarzynski M.A., Shin C.S., Narančić N.S., Spira D., Srikanth P., Steinhagen-Thiessen E., Sung Y.J., Swart K.M., Taittonen L., Tanaka T., Tikkanen E., van der Velde N., van Schoor N.M., Verweij N., Wright A.F., Yu L., Zmuda J.M., Eklund N., Forrester T., Grarup N., Jackson A.U., Kristiansson K., Kuulasmaa T., Kuusisto J., Lichtner P., Luan J., Mahajan A., Männistö S., Palmer C.D., Ried J.S., Scott R.A., Stancáková A., Wagner P.J., Demirkan A., Döring A., Gudnason V., Kiel D.P., Kühnel B., Mangino M., Mcknight B., Menni C., O'Connell J.R., Oostra B.A., Shuldiner A.R., Song K., Vandenput L., van Duijn C.M., Vollenweider P., White C.C., Boehnke M., Boettcher Y., Cooper R.S., Forouhi N.G., Gieger C., Grallert H., Hingorani A., Jørgensen T., Jousilahti P., Kivimaki M., Kumari M., Laakso M., Langenberg C., Linneberg A., Luke A., Mckenzie C.A., Palotie A., Pedersen O., Peters A., Strauch K., Tayo B.O., Wareham N.J., Bennett D.A., Bertram L., Blangero J., Blüher M., Bouchard C., Campbell H., Cho N.H., Cummings S.R., Czerwinski S.A., Demuth I., Eckardt R., Eriksson J.G., Ferrucci L., Franco O.H., Froguel P., Gansevoort R.T., Hansen T., Harris T.B., Hastie N., Heliövaara M., Hofman A., Jordan J.M., Jula A., Kähönen M., Kajantie E., Knekt P.B., Koskinen S., Kovacs P., Lehtimäki T., Lind L., Liu Y., Orwoll E.S., Osmond C., Perola M., Pérusse L., Raitakari O.T., Rankinen T., Rao D.C., Rice T.K., Rivadeneira F., Rudan I., Salomaa V., Sørensen T.I., Stumvoll M., Tönjes A., Towne B., Tranah G.J., Tremblay A., Uitterlinden A.G., van der Harst P., Vartiainen E., Viikari J.S., Vitart V., Vohl M.C., Völzke H., Walker M., Wallaschofski H., Wild S., Wilson J.F., Yengo L., Bishop D.T., Borecki I.B., Chambers J.C., Cupples L.A., Dehghan A., Deloukas P., Fatemifar G., Fox C., Furey T.S., Franke L., Han J., Hunter D.J., Karjalainen J., Karpe F., Kaplan R.C., Kooner J.S., McCarthy M.I., Murabito J.M., Morris A.P., Bishop J.A., North K.E., Ohlsson C., Ong K.K., Prokopenko I., Richards J.B., Schadt E.E., Spector T.D., Widén E., Willer C.J., Yang J., Ingelsson E., Mohlke K.L., Hirschhorn J.N., Pospisilik J.A., Zillikens M.C., Lindgren C., Kilpeläinen T.O, & Loos R.J. (2016). New loci for body fat percentage reveal link between adiposity and cardiometabolic disease risk. Nature Communications, 7, 10495.
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Publication 2016
Adiponectin Childbirth Enzymes Fatty Liver Genome Genome, Human Genome-Wide Association Study Gigantism Leptin Lipids Liver Melanoma Nevus, Intradermal Phenotype Plasma Puberty Single Nucleotide Polymorphism Somatomedins Tissues
2
Isolation and Culture of Human ECFCs and HMVECs
Cited 6 times
Human umbilical cord blood ECFCs were isolated using a protocol approved by the Institutional Review Board of the Indiana University School of Medicine as previously described [18 (link)]. The adherent ECFCs were cultured in T-75 culture flasks (Nunc) coated with a layer of 5 μg/cm2 rat tail collagen I (BD Biosciences) in EGM®-2 media supplemented with Lonza’s SingleQuot supplement (hydrocortisone, gentamycin, human VEGF, human fibroblast growth factor (FGF), human epidermal growth factor (EGF), human insulin-like growth factor (IGF), and heparin) and supplemented with 10% fetal bovine serum (FBS, JR Scientific), 1% penicillin/streptomycin, and 0.1% amphotericin β (Mediatech). Adult dermal HMVECs were received in cryogenic ampoules (Clonetics® HMVEC-dAd-Adult Human Dermal Microvascular Endothelial Cells, Lonza) and cultured in EGM®-2MV Microvascular Endothelial Cell Growth Medium-2 supplemented with the Bulletkit supplement (5% FBS, hydrocortisone, gentamycin, human VEGF, human FGF, human EGF, human IGF, and ascorbic acid). Both hECFCs and HMVECs were maintained in standard CO2 incubators at 37°C prior to experimentation.
Decaris M.L., Lee C.I., Yoder M.C., Tarantal A.F, & Leach J.K. (2009). Influence of the oxygen microenvironment on the proangiogenic potential of human endothelial colony forming cells. Angiogenesis, 12(4), 303-311.
Publication 2009
Adult Amphotericin Ascorbic Acid Collagen Type I Cultured Cells Culture Media Dietary Supplements Endothelial Cells Endothelium Epidermal growth factor Ethics Committees, Research Gentamicin Heparin Homo sapiens Hydrocortisone Penicillins Pharmaceutical Preparations Skin Somatomedins Streptomycin Tail Umbilical Cord Blood Vascular Endothelial Growth Factors
3
Insect Insulin-Like Peptide Discovery
Cited 5 times
The sratoolkit (https://trace.ncbi.nlm.nih.gov/Traces/sra/sra.cgi?view=software) in combination with Trinity (Grabherr et al., 2011 (link)) was used in the search for transcripts encoding peptides that might be somewhat similar to insulin in insect gonad transcriptome short read archives (SRAs). The method consisted of using the tblastn_vdb command from the sratoolkit to recover individual reads from transcriptome SRAs that show possible sequence homology with insulin-like molecules. Since insulin-like peptides have highly variable sequences the command is run with the -seg no and -evalue 100 options. Reads that are identified are then collected using the vdb-dump command from the sratoolkit. The total number of reads recovered is much smaller than those typically present in an SRA and this allows one to use Trinity on a normal desktop computer to make a mini-transcriptome of those reads. This transcriptome is than searched using the BLAST+ program (https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE_TYPE=BlastDocsDOC_TYPE=Download) for possible insulin transcripts. This first round usually yields numerous false positives and perhaps a few partial transcripts that look interesting. These promising but partial transcripts are then used as query using the blastn_vdb command from the sratoolkit on the same SRAs and reads are collected anew and Trinity is used to make another transcriptome that is again queried for the presence of insulin-like transcripts. In order to obtain complete transcript the blastn_vdb search may need to be repeated several times. Alternatively genes coding such transcripts were identified in genome assemblies using the BLAST+ program and Artemis (Rutherford et al., 2000 (link)). Once such transcripts had been found, it was often possible to find orthologs from related species. For example, once the honeybee gonadulin was found, it was much easier to find it in other Hymenoptera. The same methods were used to identify relaxin and C-terminally extended ilps, which have much better conserved primary amino acid sequences and consequently are more easily identified, as well as their putative receptors. Whenever possible all sequences were confirmed in both genome assemblies and in transcriptome SRAs. In many cases transcripts for the various ilps and receptors were already present in genbank, although they were not always correctly identified. All these sequences are listed in Spreadsheet S1.
Expression was estimated by counting how many RNAseq reads in each SRA contained coding sequence for each of the genes. In order to avoid untranslated sequences of the complete transcripts, that sometimes share homologous stretches with transcripts from other genes and can cause false positives, only the coding sequences were used as query in the blastn_vdb command from the sratoolkit. This yielded the blue numbers in Spreadsheet S2. In order to more easily compare the different SRAs these numbers were then expressed as per million spots in each particular SRA. These are the bold black numbers in Spreadsheet S2.
For the expression of alternative aIGF (arthropod insulin-like growth factor) splice forms reads for each splice variant were first separately identified. Unique identifiers in these two sets were determined to obtain the total number of reads for aIGF. Those identifiers that were present in the initial counts for both splice forms were counted separately and subtracted from the initial counts of the two splice variants to obtain the number of reads specific for each isoform.
The various SRAs that were used are listed in the supplementary pdf file and were downloaded from https://www.ncbi.nlm.nih.gov/sra/. The following genome assemblies were also analyzed: Aedes aegypti (Matthews et al., 2018 (link)), Blattella germanica (Harrison et al., 2018 (link)), Bombyx mori (Kawamoto et al., 2019 (link)), Galleria melonella (Lange et al., 2018 (link)), Glossina morsitans (Attardo et al., 2019 (link)), Hermetia illucens (Zhan et al., 2020 (link)), Latrodectus hesperus (https://www.ncbi.nlm.nih.gov/genome/?term=Latrodectus+hesperus), Mesobuthus martensii (Cao et al., 2013 (link)), Oncopeltus fasciatus (Panfilio et al., 2019 (link)), Parasteatoda tepidariorum (Schwager et al., 2017 (link)), Pardosa pseudoannulata (Yu et al., 2019 (link)), Periplaneta americana (Li et al., 2018 (link)), Stegodyphus dumicola (Liu et al., 2019 (link)), Tetranychus urticae (Grbic et al., 2011 (link)), Timema cristinae (Riesch et al., 2017 (link)), Tribolium castaneum (Herndon et al., 2020 (link)) and Zootermopsis nevadensis (Terrapon et al., 2014 (link)). All genomes were downloaded from https://www.ncbi.nlm.nih.gov/genome/.
, & Veenstra J.A. (2020). Arthropod IGF, relaxin and gonadulin, putative orthologs of Drosophila insulin-like peptides 6, 7 and 8, likely originated from an ancient gene triplication. PeerJ, 8, e9534.
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Publication 2020
2'-deoxyuridylic acid Aedes Amino Acid Sequence Arthropods BIRC4 protein, human Bombyx mori Exanthema Exons FGF8 protein, human Genes Genome Glossina Gonads Hymenoptera Insecta Insulin Open Reading Frames Peptides Periplaneta americana Protein Isoforms Relaxin Somatomedins Transcriptome Tribolium
4
Differentiation of Motor Neurons from iPSCs
Cited 5 times
MN differentiation from iPSCs was performed using established protocol24 (link) with minor modifications. iPSCs were dissociated into single cells using 1 × Accutase, 2 × 106 iPSCs were neuralized as a suspension culture using SB-431542 (20 µM), LDN-193189 (0.1 µM), and CHIR-99021 (3 µM) in N2/B27 media (0.5 × Neurobasal, 0.5 × Advanced DMEM/F12, 1 × Antibiotic-Antimycotic, 1 × Glutamax, 100 µM beta-mercaptoethanaol, 1 × B27, 1 × N2, and 10 µM ascorbic acid). On day 2, neural spheres were simultaneously patterned to spinal cord identity by treating with retinoic acid (RA, 0.1 µM) and smoothened agonist (SAG, 500 nM) along with SB-431542, LDN-193189, and CHIR-99021 in N2/B27 media for additional 5 days. On day 7, spheres continued to be cultured in RA and SAG and, also, brain-derived neurotrophic factor (BDNF, 10 ng/ml) in N2/B27 media to generate MN progenitors. On day 9, MN progenitors were cultured in the previous media in addition to DAPT (10 µM) for additional 5–7 days. At day 14–16, MN spheres were dissociated using 0.05% Trypsin-EDTA and plated on to a poly-ornithine, laminin (5 µg/ml), fibronectin (10 µg/ml), Matrigel (1:20)-coated dishes. Dissociated MNs were cultured in NB media (1 × Neurobasal, 1 × Glutamax, 1 × non-essential amino acids, 100 µM beta-mercaptoethanol, 1 × B27, 1 × N2, RA (1 µM), ascorbic acid (2.5 µM), BDNF (10 ng/ml), glial-derived neurotrophic factor (10 ng/ml), ciliary neurotrophic factor (10 ng/ml), insulin-like growth factor (10 ng/ml)). Cells were treated with Uridine (1 µM)/5-fluoro-2′-deoxyuridine (U/FDU) on day 1 to remove residual proliferating cells. Media was changed every 2–3 days.
Selvaraj B.T., Livesey M.R., Zhao C., Gregory J.M., James O.T., Cleary E.M., Chouhan A.K., Gane A.B., Perkins E.M., Dando O., Lillico S.G., Lee Y.B., Nishimura A.L., Poreci U., Thankamony S., Pray M., Vasistha N.A., Magnani D., Borooah S., Burr K., Story D., McCampbell A., Shaw C.E., Kind P.C., Aitman T.J., Whitelaw C.B., Wilmut I., Smith C., Miles G.B., Hardingham G.E., Wyllie D.J, & Chandran S. (2018). C9ORF72 repeat expansion causes vulnerability of motor neurons to Ca2+-permeable AMPA receptor-mediated excitotoxicity. Nature Communications, 9, 347.
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Publication 2018
1,2-dilinolenoyl-3-(4-aminobutyryl)propane-1,2,3-triol 2-Mercaptoethanol 4-(5-benzo(1,3)dioxol-5-yl-4-pyridin-2-yl-1H-imidazol-2-yl)benzamide 5-fluoro-2'-deoxyuridine accutase Amino Acids, Essential Antibiotics Ascorbic Acid Cells Chir 99021 Ciliary Neurotrophic Factor Culture Media Edetic Acid Fibronectins Glial Cell Line-Derived Neurotrophic Factor Hyperostosis, Diffuse Idiopathic Skeletal Induced Pluripotent Stem Cells Laminin LDN 193189 matrigel Nervousness Neurotrophic Factor, Brain-Derived Ornithine Poly A Somatomedins Spinal Cord Tretinoin Trypsin Uridine
5
Genetic Associations in Gestational Diabetes
Cited 5 times
As two different diagnostic GDM criteria were applied (IADPSG or the modified 99' WHO) in the two participating countries the following protocol was employed for the analysis of genotype associations: we first had to reclassify the entire dataset of the whole study population according to both criteria based on the OGTT results (FPG and 2 hour PG values) as a ‘diagnosis stratification procedure’. This was possible since there was no medical intervention prior to the 75g OGTT and the test itself was performed in the standardized time-frame of gestation (24th-28th gestational week). Those individuals in whom the GDM diagnosis was established exclusively on the basis of the 60 min OGTT result remained in the GDM group in the ‘diagnosis stratification procedure’. Such cases are rare (less than 5.7% according to the Hyperglycemia and Adverse Pregnancy Outcomes (HAPO) Study [24 (link)] and 13% in the participating Austrian study population). We have performed all binary analysis twice, first using the 99’ modified WHO criteria and second using the IADPSG criteria.
A set of 77 SNPs were selected based on the results of prior genome wide association studies (GWAS) on T2D, BMI, Insulin resistance (IR), Insulin secretion/ beta cell function, plasma glucose or serum insulin level traits. Functionally, the reported genes were suggested to be implicated in the incretin effect, beta-cell function or genesis, potassium channel function, amyloid formation, zinc transport, insulin resistance, obesity development, insulin-like growth factor (IGF) system, vessel formation, glucose homeostasis, circadian rhythm, neuronal regulation of appetite, energy balance or immunoregulation (S1 Table).
Subsequently we provided two numerically different odds ratios and p-values for each gene variants that were significantly associated with GDM according to the corresponding diagnostic system applied in the analysis.
Rosta K., Al-Aissa Z., Hadarits O., Harreiter J., Nádasdi Á., Kelemen F., Bancher-Todesca D., Komlósi Z., Németh L., Rigó J J.r., Sziller I., Somogyi A., Kautzky-Willer A, & Firneisz G. (2017). Association Study with 77 SNPs Confirms the Robust Role for the rs10830963/G of MTNR1B Variant and Identifies Two Novel Associations in Gestational Diabetes Mellitus Development. PLoS ONE, 12(1), e0169781.
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Publication 2017
Amyloid Appetite Regulation Blood Vessel Circadian Rhythms Diagnosis Genes Genetic Diversity Genome-Wide Association Study Genotype Glucose Homeostasis Hyperglycemia Incretin Effect Insulin Insulin Resistance Insulin Secretion Neurons Obesity Oral Glucose Tolerance Test Pancreatic beta Cells Physiology, Cell Plasma Potassium Channel Pregnancy Reading Frames Serum Single Nucleotide Polymorphism Somatomedins Tests, Diagnostic Zinc

Most recents protocols related to «Somatomedins»

1
Quantification of Serum IGF-1 in Mice
To measure insulin-like growth factor-1 (IGF-1) mice blood was collected in specific MiniCollect ® CAT Serum Tubes (ref. 450533; Greiner Bio One GmbH). After blood collection, the samples were maintained in an upright position for 30 min. The clot was removed by centrifuging at 3.000 × g for 15 min at 4 °C, and the supernatant (serum) was stored at −80 °C. Quantification of insulin-like growth factor (IGF-1) levels in serum samples was done using an ELISA assay (ref. ab240685; Abcam), following the manufacturer’s instructions. In both cases, 10 μL serum samples were used in duplicate from each sample. The readout was obtained using a Multiskan Spectrum spectrophotometer (Thermo Electron Corporation). The concentration for each sample was estimated from a reference standard curve with known concentrations of IGF-1.
Jiménez-Gómez B., Ortega-Sáenz P., Gao L., González-Rodríguez P., García-Flores P., Chandel N, & López-Barneo J. (2023). Transgenic NADH dehydrogenase restores oxygen regulation of breathing in mitochondrial complex I-deficient mice. Nature Communications, 14, 1172.
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Publication 2023
Biological Assay BLOOD Clotrimazole Electrons Enzyme-Linked Immunosorbent Assay IGF1 protein, human insulin-like growth factor-1, mouse Serum Somatomedins
2
Comprehensive metabolic profiling protocol
Fifteen milliliters of blood were collected from each participant to assess fasting serum levels of biochemical and hormonal markers following a 12-h overnight fast. The detailed assessment of the biological parameters was previously described in Marcangeli et al., 2022 [5 (link)]. Briefly, the lipid profile was assessed through total, HDL- and LDL-cholesterol, as well as triglyceride levels. Adipose tissue metabolites and adipokines (free fatty acids, adiponectin and leptin levels, adiponectin/leptin ratio), members of the insulin-like growth factor (IGF) family (IGF1; IGFBP3 and IGFB3/IGF1 molar ratio) and glucose-insulin homeostasis (glucose and insulin levels but also HOMA and QUICKI indices) were assessed.
Youssef L., Bourgin M., Durand S., Aprahamian F., Lefevre D., Maiuri M.C., Marcangeli V., Dulac M., Hajj-Boutros G., Buckinx F., Peyrusqué E., Gaudreau P., Morais J.A., Gouspillou G., Kroemer G., Aubertin-Leheudre M, & Noirez P. (2023). Serum Metabolome Adaptations Following 12 Weeks of High-Intensity Interval Training or Moderate-Intensity Continuous Training in Obese Older Adults. Metabolites, 13(2), 198.
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Publication 2023
Adipokines ADIPOQ protein, human Biopharmaceuticals BLOOD Cholesterol, beta-Lipoprotein Family Member Glucose Homeostasis IGF1 protein, human IGFBP3 protein, human Insulin Leptin Lipids Molar Nonesterified Fatty Acids Serum Somatomedins Tissue, Adipose Triglycerides
3
Muscle Protein Analysis Post-Injury
Snap frozen whole TA muscles were crushed into powder using a mortar and pestle. Crushed muscles were then used for protein analysis at a sample size of n = 4 per group for the 56-day post-injury time point and n = 5 per group for the 28-day time point. Powdered muscle samples were suspended in T-PER™ (ThermoFisher; Waltham, MA, USA) lysis buffer and Halt™ Protease Inhibitor Cocktail 100× (Thermo Fisher Scientific Inc.; Waltham, MA, USA) at a concentration of 100 mg/mL. The suspended samples were homogenized and centrifuged at 10,000× g for 5 min at 4 °C. The supernatant was collected, and total protein concentration was quantified using a Pierce™ BCA Protein Assay Kit (Thermo Fisher Scientific Inc.; Waltham, MA, USA) according to the manufacturer’s instructions. Proteins were measured in muscle lysate using ELISA kits (MyBiosource Inc; San Diego, CA, USA). Proteins associated with fibrogenic processes included collagen type I alpha I (COL1a1), collagen 3 alpha I (COL3A1), and transforming growth factor beta (TGFβ). Proteins associated with myogenic processes included myogenin (MYOG), paired box 7 (PAX7), insulin-like growth factor (IGF-1), and myosin heavy chain 3 (MHC3). Protein lysates were further diluted in the T-PER™ lysis buffer as needed and added to antibody-coated plates along with standard protein concentrations. The plates were incubated and washed according to specific manufacturer instructions. A change in color appeared in the plate, and the optical density was measured at specific wavelengths using an Infinite M200 Pro spectrophotometer (Tecan; Männedorf, Switzerland). Fibrotic and myogenic protein concentrations were calculated by interpolation from the generated standard curve and normalized to the total protein concentration quantified from the BCA assay.
Motherwell J.M., Dolan C.P., Kanovka S.S., Edwards J.B., Franco S.R., Janakiram N.B., Valerio M.S., Goldman S.M, & Dearth C.L. (2023). Effects of Adjunct Antifibrotic Treatment within a Regenerative Rehabilitation Paradigm for Volumetric Muscle Loss. International Journal of Molecular Sciences, 24(4), 3564.
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Publication 2023
Biological Assay Buffers COL1A1 protein, human Collagen Type I Enzyme-Linked Immunosorbent Assay Fibrosis Freezing IGF1 protein, human Immunoglobulins Injuries M-200 Muscle Tissue Myogenesis MYOG protein, human Myosin Heavy Chains Protease Inhibitors Proteins Somatomedins Transforming Growth Factor beta Vision
4
Endothelial and Fibroblast Cell Culture Protocol
Human umbilical vein endothelial cells (HUVECs) and human dermal fibroblasts (HDFs) were purchased from PromoCell Cells (Heidelberg, Germany) and were subsequently cultured in PromoCell’s Endothelial Cell Growth Medium 2 (EGM-2) containing 2% foetal bovine serum (FBS), human epidermal growth factor (EGF), human basic fibroblast growth factor (bFGF), insulin-like growth factor (IGF), human vascular endothelial growth factor (VEGF), ascorbic acid and heparin. Endothelial Cell Growth Medium-2 as well as their respective bullet kits were purchased from PromoCell. Trypsin 0.005%/EDTA 0.01% solution, Dulbecco A Phosphate Buffered Saline (PBS), 1-StepTM NBT/BCIP (Pierce Protein Research) were purchased from Thermo Scientific, Loughborough, United Kingdom. Foetal bovine serum (FBS), dimethyl sulfoxide (DMSO), paraformaldehyde, Triton® X-100, rabbit anti-human von Willebrand factor antibody (F-3520), and mouse anti-rabbit IgG-alkaline phosphatase (A9919) were purchased from Sigma-Aldrich, Gillingham, Dorset, United Kingdom. Human recombinant VEGF and precast gels were purchased from Invitrogen Life Technologies, Paisley, United Kingdom. PTK787 (vatalanib dihydrochloride) was purchased from MedChem Express, Monmouth Junction, United States. Pronase E were purchased from Solarbio, Shanghai, China.
Zhu Y., Yang H., Han L., Mervin L.H., Hosseini-Gerami L., Li P., Wright P., Trapotsi M.A., Liu K., Fan T.P, & Bender A. (2023). In silico prediction and biological assessment of novel angiogenesis modulators from traditional Chinese medicine. Frontiers in Pharmacology, 14, 1116081.
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Publication 2023
Alkaline Phosphatase anti-IgG Antibodies, Anti-Idiotypic Ascorbic Acid Cells Cultured Cells Culture Media Edetic Acid Endothelial Cells Endothelium Epidermal growth factor Factor VIII-Related Antigen Fetal Bovine Serum Fibroblast Growth Factor 2 Fibroblasts Gels Heparin Human Umbilical Vein Endothelial Cells Mus paraform Phosphates Pronase E Proteins PTK 787 Rabbits Saline Solution Skin Somatomedins Sulfoxide, Dimethyl Triton X-100 Trypsin vatalanib VEGF protein, human
5
Mosquito Gene Expression Analysis
Total RNA was extracted from the starved, sugar-fed, blood-fed, and P. falciparum-infected mosquito pools in TRIzol reagent (Invitrogen) according to the manufacturer’s instructions, including a DNase I (Turbo DNase kitTM, ThermoFisher) step. cDNA was synthesized from 1 µg of RNA using Superscript IV Reverse Transcriptase and Oligo(dTs) (ThermoFisher).
The expression of AKH pathway genes (AgAkh1, AgAkh2, AgAkhR, AgLsdp1, and AgLp) and insulin/insulin-like growth factor genes (AgILP1, AgILP2, AgILP3, AgILP4, AgILP5, AgILP6, AgILP7, and AgInR) were quantified from the synthesized cDNA via qPCR, using An. gambiae ribosomal protein transcripts AgRPL32 as internal controls. Primer pairs were designed using Integrated DNA Technology freeware (https://www.idtdna.com/scitools/Applications/RealTimePCR/) so that at least one oligonucleotide spanned an exon – exon boundary to prevent genomic DNA amplification. Amplicons were designed to be no longer than 150 base pairs, to promote amplification efficiency (Supplementary Table S1). Transcript sequence and exon boundary information were retrieved from VectorBase50 (link). Primer specificity was first verified in silico by BLAST comparisons of the oligonucleotide sequences against all sequences hosted by National Center for Biotechnology Information (https://www.ncbi.nlm.nih.gov/). Optimal amplifying and annealing conditions were then tested by gradient PCR for each set of primers. In addition, the primers were tested for amplification efficiency using qPCR. Each qPCR reaction contained 0.75 µL cDNA template, and a reaction master mix containing 6.25 µL SYBR Green Master Mix (Thermo Fisher Scientific) and 0.3 µM of each primer in a total reaction volume of 12.5 µL. The thermal profile used for qPCR was: 1 min at 95 °C; 40 cycles of 15 s at 95 °C and 1 min 60 °C. All qPCR assays were run as technical duplicates and each plate included a no template control. All assays were run on an Eco™ Real-Time PCR System (Illumina).
Nyasembe V.O., Hamerly T., López-Gutiérrez B., Leyte-Vidal A.M., Coatsworth H, & Dinglasan R.R. (2023). Adipokinetic hormone signaling in the malaria vector Anopheles gambiae facilitates Plasmodium falciparum sporogony. Communications Biology, 6, 171.
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Publication 2023
Biological Assay Blood Glucose Culicidae Deoxyribonuclease I DNA, Complementary Exons Gene Expression Genes Genome Insulin Oligonucleotide Primers Oligonucleotides Ribosomal Proteins RNA-Directed DNA Polymerase Somatomedins SYBR Green I trizol

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Fetal bovine serum (fbs) by Thermo Fisher Scientific
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Penicillin streptomycin by Thermo Fisher Scientific
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L glutamine by Thermo Fisher Scientific
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Epidermal growth factor (egf) by Thermo Fisher Scientific
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Fibroblast growth factor (fgf) by Thermo Fisher Scientific
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More about "Somatomedins"

Somatomedins, also known as insulin-like growth factors (IGFs), are a group of signaling molecules that play a crucial role in regulating cell growth, proliferation, and differentiation.
These important biomolecules mediate the effects of growth hormone (GH) and are essential for normal development and maintenance of various tissues.
IGF-I and IGF-II are the two primary somatomedins, and their complex biology has been the focus of extensive research in the fields of growth, metabolism, and related disorders.
Understanding the role of somatomedins is crucial for optimizing cell culture conditions, as they can influence the behavior of cells in vitro.
Researchers often utilize fetal bovine serum (FBS), which contains a variety of growth factors including somatomedins, to support the growth and proliferation of cells in culture.
Additionally, the supplementation of cell culture media with L-glutamine, epidermal growth factor (EGF), and fibroblast growth factor (FGF) can also modulate somatomedin signaling and cell behavior.
When studying somatomedins, it's important to consider the use of antibiotics like penicillin and streptomycin, as well as hydrocortisone and ascorbic acid, which can impact cellular processes.
Endothelial cell models, such as human umbilical vein endothelial cells (HUVECs) grown in endothelial basal medium-2 (EBM-2), can also provide insights into the effects of somatomedins on vascular biology.
By leveraging the knowledge of somatomedins and their interactions with various cell culture components, researchers can optimize their experimental designs and enhance the reproducibility and accuracy of their studies.
The AI-driven platform PubCompare.ai can be a valuable tool in this process, helping to identify the most effective protocols and experimental methods from the literature, preprints, and patents.