A trained phlebotomist will extract, treat and subsequently store the blood at approximately -80°C until later analysis. Analysis of blood samples through commercial ELISA kits (Thermo Fisher Scientific Australia Pty Ltd., Victoria, Australia; Randox Laboratories Ltd., West Virginia, USA; R&D Systems Inc., Minneapolis, USA) will be used for PSA, IGF-1, IGF-2, IGFBP3, IL-6, IL-8, Hepcidin, total cholesterol, and triglycerides analysis.
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Amino Acid
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IGF II
IGF II
Insulin-like growth factor II (IGF-II) is a polypeptide hormone involved in cell growth and differentiation.
It plays a crucial role in fetal development and has been implicated in various disease processes, including cancer and metabolic disorders.
PubCompare.ai is an AI-driven platform that enhances the reproducibility and accuracy of IGF-II research by providing easy access to protocols from literature, preprints, and patents.
The platform's AI-driven comparisons help researchers identify the best protocols and products for their IGF-II studies, taking the guesswork out of the process.
With PubCompare.ai, researchers can optimize their IGF-II research and make more informed decisions, leading to more reliable and impactful findings.
It plays a crucial role in fetal development and has been implicated in various disease processes, including cancer and metabolic disorders.
PubCompare.ai is an AI-driven platform that enhances the reproducibility and accuracy of IGF-II research by providing easy access to protocols from literature, preprints, and patents.
The platform's AI-driven comparisons help researchers identify the best protocols and products for their IGF-II studies, taking the guesswork out of the process.
With PubCompare.ai, researchers can optimize their IGF-II research and make more informed decisions, leading to more reliable and impactful findings.
Most cited protocols related to «IGF II»
BLOOD
Cholesterol
Enzyme-Linked Immunosorbent Assay
Hematologic Tests
Hepcidin
IGF1 protein, human
IGFBP3 protein, human
IGF II
Randox
Triglycerides
A Cas9-guided chromatin immunoprecipitation assay [68 (link)] was used to identify components that bind to a target gene DNA fragment (Wang et al, unpublished data). In this study, we constructed the Cas9-IGF2 gRNA vector by cloning two IGF2 promoter gRNAs into the Cas9-2xgRNA vector that contains a mutated Cas9 (dCas9) and the tandem U6 and H1 promoters (Supplementary Figure 1A ). Specifically, two oligonucleotides covering guiding RNA (gRNA) from the IGF2 promoters P2 and P3 (P2-Site I: 5’-GCCTTGCGTTCCCCAAAATT-3’ and P3-Site II: 5’-GTCGCCGGCTTCCAGGTAAG -3’) were synthesized and were inserted immediately downstream of the U6 and H1 promoters, respectively, followed by the Cas9-hairpin RNA-(T)5 sequence (Supplementary Figure 1B ).
The Cas9-IGF2 gRNA lentiviruses were produced in 293T cells as previously described [60 (link), 62 (link), 63 (link)]. The viral supernatants were filtered through a 0.45-μm filter, concentrated by a PEG-IT kit (SBI, CA), aliquoted and stored in a −80°C freezer. An aliquot of the Cas9-IGF2gRNA lentivirus was used to transfect pancreatic cancer ASPC cells. After transfection, cells were selected by puromycin and collected for immunoprecipitation following the method as described previously [37 (link), 64 (link)]. Briefly, cells were fixed with 1% formaldehyde and sonicated for 180 s (10 s on and 10 s off) on ice with a Branson sonicator with a 2-mm microtip at 40% output control and 90% duty cycle settings. The sonicated chromatin DNAs containing Cas9-gRNA-IGF2 promoter complex were immunoprecipitated with Cas9 antibody (#ab191468, Abcam, MA). After reversal of cross-linking and proteinase K treatment, the Cas9-bound chromatin DNA and RNA were released and subjected to miRNA/DNA/RNA sequencing and analyses.
To amplify the miRNAs that interacted with the IGF2 promoter, the Cas9-immunoprecipitated RNAs were treated with DNase I. The 3’ and 5’ SR adaptors were ligated to RNAs following the protocol of the NEBNext Small RNA library Prep Kit (#E7330S, NEB, MA). After PCR amplification, the predicted PCR bands were cut and cloned into a pJET vector (Thermo Fisher Scientific, CA) for sequencing.
The Cas9-IGF2 gRNA lentiviruses were produced in 293T cells as previously described [60 (link), 62 (link), 63 (link)]. The viral supernatants were filtered through a 0.45-μm filter, concentrated by a PEG-IT kit (SBI, CA), aliquoted and stored in a −80°C freezer. An aliquot of the Cas9-IGF2gRNA lentivirus was used to transfect pancreatic cancer ASPC cells. After transfection, cells were selected by puromycin and collected for immunoprecipitation following the method as described previously [37 (link), 64 (link)]. Briefly, cells were fixed with 1% formaldehyde and sonicated for 180 s (10 s on and 10 s off) on ice with a Branson sonicator with a 2-mm microtip at 40% output control and 90% duty cycle settings. The sonicated chromatin DNAs containing Cas9-gRNA-IGF2 promoter complex were immunoprecipitated with Cas9 antibody (#ab191468, Abcam, MA). After reversal of cross-linking and proteinase K treatment, the Cas9-bound chromatin DNA and RNA were released and subjected to miRNA/DNA/RNA sequencing and analyses.
To amplify the miRNAs that interacted with the IGF2 promoter, the Cas9-immunoprecipitated RNAs were treated with DNase I. The 3’ and 5’ SR adaptors were ligated to RNAs following the protocol of the NEBNext Small RNA library Prep Kit (#E7330S, NEB, MA). After PCR amplification, the predicted PCR bands were cut and cloned into a pJET vector (Thermo Fisher Scientific, CA) for sequencing.
Biological Assay
Cells
Chromatin
Cloning Vectors
Deoxyribonuclease I
DNA Library
Endopeptidase K
Formaldehyde
Genes
HEK293 Cells
IGF II
Immunoglobulins
Immunoprecipitation
Immunoprecipitation, Chromatin
Lentivirus
MicroRNAs
Oligonucleotides
Pancreatic Cancer
Puromycin
Transfection
Embryoid bodies were generated from clumps of human iPSCs in suspension culture for 6 days in IMDM with 15% FBS, and then grown in adherent culture on gelatin-coated dish with cytokine cocktails (100 ng/ml SCF, 100 ng/ml Flt3L, 50 ng/ml TPO, 100 ng/ml G-CSF, 20 ng/ml IGF-2, and 100 ng/ml VEGF) to induce lymphoid lineage cells and cardimyocytes. 29) (link) For differentiation to dopaminergic neurons, small clumps of SeV-iPSC were cocultured with PA6 (stromal cells derived from skull bone marrow; RIKEN BRC, Japan) in GMEM (Invitrogen, USA) containing 10% KSR (Invitrogen, USA), 1 × 10−4 M non-essential amino acids and 2-mercaptoethanol for 16 days.30) (link) For induction of definitive endoderm cells and pancreatic cells, small clumps of iPSCs were cultured on feeder cells with 100 ng/ml activin A (R&D Systems, USA) in RPMI1640 (Invitrogen, USA) supplemented with 2% FBS for 4 days, and followed by additional 8 days culture in DMEM/F12 supplemented with N2 and B27, non-essential amino acids, β-mercaptoethanol, 0.5 mg/ml bovine serum albumin, l -glutamine and penicillin/streptomycin.31) (link)
2-Mercaptoethanol
activin A
Amino Acids, Essential
Bone Marrow
Cells
Cranium
Cultured Cells
Cytokine
Dopaminergic Neurons
Embryoid Bodies
Endoderm
Gelatins
Glutamine
Granulocyte Colony-Stimulating Factor
Homo sapiens
Hyperostosis, Diffuse Idiopathic Skeletal
IGF II
Induced Pluripotent Stem Cells
Lymphoid Cells
Marrow
neuronectin
Pancreas
Penicillins
Serum Albumin, Bovine
Streptomycin
Stromal Cells
Vascular Endothelial Growth Factors
Under an Institutional Review Board approved study our laboratory has accessed samples from 17 sperm donors (of known fertility) that were collected in the 1990's. These donors provided an additional semen sample in 2008, enabling the evaluation of intra-individual changes to sperm DNA methylation with age. These samples are referred to as young (1990's collection) and aged (2008 collection) samples. The age difference between each collection varied between 9 and 19 years, and the age at first collection (“young” sample) was between 23 and 56 years of age.
At every collection donors were required to strictly follow the University of Utah Andrology Laboratory collection instructions, which includes abstinence time of between 2 and 5 days. The whole ejaculate (no sperm selection method was employed) collected at each visit was frozen in a 1∶1 ratio with Test Yolk Buffer (TYB; Irvine Scientific, Irvine, CA) and stored in liquid nitrogen prior to DNA isolation. Samples were thawed and the DNA was extracted simultaneously to decrease batch effects. Sperm DNA was extracted with the use of a sperm-specific extraction protocol used routinely in our laboratory [36] (link). Briefly, sperm DNA was isolated by enzymatic and detergent-based lysis followed by treatment with RNase and finally DNA precipitation using isopropanol and salt, with subsequent DNA cleanup using ethanol. To ensure the absence of potential contamination from somatic cells the samples were visually inspected prior to DNA extraction. Additionally, we analyzed our sequencing results in an attempt to identify reads that did not match the methylation profile of sperm but instead reflected that of leukocytes. We also analyzed imprinted regions from our array data in an attempt to identify fraction methylation values that were inconsistent with previous reports of sperm DNA methylation patterns. Specifically, at a region of the IGF-2 locus that is tiled on the 450K array, it has been previously shown that sperm DNA is strongly hypermethlyated with a fraction methylation of approximately 0.8–0.85 and in leukocytes this same region is strongly demethylated with a fraction methylation of <0.1 [37] (link). Our array data indicate average methylation in every sample screened at these sites is approximately 0.844. In summary, with neither approach did we identify any signal that indicated leukocyte or other somatic cell contamination.
At every collection donors were required to strictly follow the University of Utah Andrology Laboratory collection instructions, which includes abstinence time of between 2 and 5 days. The whole ejaculate (no sperm selection method was employed) collected at each visit was frozen in a 1∶1 ratio with Test Yolk Buffer (TYB; Irvine Scientific, Irvine, CA) and stored in liquid nitrogen prior to DNA isolation. Samples were thawed and the DNA was extracted simultaneously to decrease batch effects. Sperm DNA was extracted with the use of a sperm-specific extraction protocol used routinely in our laboratory [36] (link). Briefly, sperm DNA was isolated by enzymatic and detergent-based lysis followed by treatment with RNase and finally DNA precipitation using isopropanol and salt, with subsequent DNA cleanup using ethanol. To ensure the absence of potential contamination from somatic cells the samples were visually inspected prior to DNA extraction. Additionally, we analyzed our sequencing results in an attempt to identify reads that did not match the methylation profile of sperm but instead reflected that of leukocytes. We also analyzed imprinted regions from our array data in an attempt to identify fraction methylation values that were inconsistent with previous reports of sperm DNA methylation patterns. Specifically, at a region of the IGF-2 locus that is tiled on the 450K array, it has been previously shown that sperm DNA is strongly hypermethlyated with a fraction methylation of approximately 0.8–0.85 and in leukocytes this same region is strongly demethylated with a fraction methylation of <0.1 [37] (link). Our array data indicate average methylation in every sample screened at these sites is approximately 0.844. In summary, with neither approach did we identify any signal that indicated leukocyte or other somatic cell contamination.
Detergents
Diploid Cell
DNA Methylation
Donors
Endoribonucleases
Enzymes
Ethanol
Ethics Committees, Research
Fertility
Freezing
IGF II
isolation
Isopropyl Alcohol
Leukocytes
Methylation
Nitrogen
Plant Embryos
Salts
Sperm
TES-Tris yolk buffer
Antibodies
Antibody Diversity
Antigens
Bacteriophages
Binding Sites
Cells
DNA Library
Escherichia coli Infections
Homo sapiens
IGF1 protein, human
IGF1R protein, human
IGF II
Ligands
Most recents protocols related to «IGF II»
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Acceleration
Acetone
Alexa594
Anti-Antibodies
Buffers
cadherin 5
Cells
DAPI
Dehydration
F-Actin
fluorescein isothiocyanate-phalloidin
Glutaral
Gold
IGF II
Immunoglobulins
Microscopy
Palladium
Phalloidine
Phosphates
Polaron
Proteins
Protoplasm
Reconstructive Surgical Procedures
Sapphire
Technique, Dilution
tetramethylrhodamine isothiocyanate
Triton X-100
Vacuum
All measurements and descriptive data were tested for normality. IGF variables (STC2, PAPP-A, IGF1, IGF-2, intact and total IGFBP4) were log2-transformed prior to statistical analysis. Other non-normally distributed variables were transformed by the natural logarithm. All events of all-cause mortality and the composite CVD outcome were combined for comparison of baseline characteristics. Categorical variables were compared using Pearson’s chi-squared test, and continuous variables were compared using a two-sample t-test for normally distributed variables and the Wilcoxon rank-sum test for non-normally distributed variables. Basic characteristics are presented as mean ± s.d. (parametric data), median (25th and 75th percentiles) (non-parametric data) or sums and percentages (categorical variables), as appropriate. Displayed data are based on non-missing data. Correlations were examined with a Bonferroni-adjusted significance level using the Spearman correlation coefficient (r).
Survival analyses were performed using Cox proportional hazards model. For the composite CVD event, non-CVD death was considered a competing event. Multiple imputation methods were applied to handle missing covariable data. No systematic differences between the non-missing and missing data were observed. Consequently, data were assumed to be missing at random. The CVD comorbidity variable had the highest proportion of missing at 11.7%. Survival analyses were performed with and without the CVD comorbidity variable and this did not significantly affect the final results. Imputations were not performed on IGF variables or outcome variables. We performed univariable and multivariable analyses and included potential confounders in two models. Model 1 included traditional CVD risk factors (age, sex, smoking and waist circumference) and the trial randomisation. Model 2 consisted of model 1 variables and furthermore included the CVD comorbidity variable, cholesterol, creatinine and HbA1c levels as well as the average diastolic blood pressure at baseline. STC2, PAPP-A, IGF1 and -2, intact and total IGFBP4 were added in the log2-transformed version, and results are reported as hazard ratios (HR) and 95% CI. One-unit increase on the log2-scale corresponds to a doubling in the non-transformed version. Assumptions of proportionality were evaluated by log-minus-log plots and assessment of Schoenfeld residuals. A two-tailed P-value of P < 0.05 was considered statistically significant. All statistics were performed by using Stata version 15 (StataCorp, College Station, TX, USA).
Survival analyses were performed using Cox proportional hazards model. For the composite CVD event, non-CVD death was considered a competing event. Multiple imputation methods were applied to handle missing covariable data. No systematic differences between the non-missing and missing data were observed. Consequently, data were assumed to be missing at random. The CVD comorbidity variable had the highest proportion of missing at 11.7%. Survival analyses were performed with and without the CVD comorbidity variable and this did not significantly affect the final results. Imputations were not performed on IGF variables or outcome variables. We performed univariable and multivariable analyses and included potential confounders in two models. Model 1 included traditional CVD risk factors (age, sex, smoking and waist circumference) and the trial randomisation. Model 2 consisted of model 1 variables and furthermore included the CVD comorbidity variable, cholesterol, creatinine and HbA1c levels as well as the average diastolic blood pressure at baseline. STC2, PAPP-A, IGF1 and -2, intact and total IGFBP4 were added in the log2-transformed version, and results are reported as hazard ratios (HR) and 95% CI. One-unit increase on the log2-scale corresponds to a doubling in the non-transformed version. Assumptions of proportionality were evaluated by log-minus-log plots and assessment of Schoenfeld residuals. A two-tailed P-value of P < 0.05 was considered statistically significant. All statistics were performed by using Stata version 15 (StataCorp, College Station, TX, USA).
Cholesterol
Creatinine
IGF1 protein, human
IGFBP4 protein, human
IGF II
Pregnancy-Associated Plasma Protein-A
Pressure, Diastolic
Waist Circumference
The BW and uterine weight of the rats were observed before and after the interventions. Biochemical indicators, including serum calcium (Ca), phosphorus (P), and alkaline phosphatase (ALP) levels, were measured before and after the interventions. Biochemical markers of bone turnover, including serum osteocalcin (BGP) and IGF-2 levels, were determined using BGP and IGF-2 detection kits (Science and Technology Development Center of the PLA General Hospital) after the interventions. The intra-assay variation in serum BGP was 2.61%, and the sensitivity was 0.22 μg/L. The intra-assay variation in serum IGF-2 was <10%, and the sensitivity was <0.1 ng/mL.
The dry and ash weights of the femurs were collected. To determine the dry weight, the femur was placed in a crucible and dried at 80°C for 2 h. The dried femur was then placed in a crucible and ashed at 600°C for 6 h.
The BMD of the entire segment of the isolated femur, distal metaphysis, and lumbar L1–4 was evaluated using dual-energy X-ray absorptiometry (DEXA) (LUNAR DPXIQ, GE Healthcare, USA). The intra-assay variation was 0.72% and the inter-assay variation was 0.84%.
The dry and ash weights of the femurs were collected. To determine the dry weight, the femur was placed in a crucible and dried at 80°C for 2 h. The dried femur was then placed in a crucible and ashed at 600°C for 6 h.
The BMD of the entire segment of the isolated femur, distal metaphysis, and lumbar L1–4 was evaluated using dual-energy X-ray absorptiometry (DEXA) (LUNAR DPXIQ, GE Healthcare, USA). The intra-assay variation was 0.72% and the inter-assay variation was 0.84%.
Alkaline Phosphatase
Biological Assay
Calcium, Dietary
Dual-Energy X-Ray Absorptiometry
Femur
Hypersensitivity
IGF II
Lumbar Region
Osteocalcin
Phosphorus
Rattus norvegicus
Remodeling, Bone
Serum
Silver
Uterus
In our research lab (Dr Lye), cord plasma myostatin (pg/mL) was measured by an enzyme-linked immunosorbent assay (ELISA) kit (Cat# DGDF80, R & D Systems, Minneapolis, USA). Cord plasma IGF-2 (ng/mL) was measured by an ELISA kit (Cat# 22-IG2HU-E01, ALPCO Diagnostics, Salem, USA). Plasma proinsulin (pmol/L) was measured by an ELISA kit (Cat# 80-PINHUT-CH01, ALPCO Diagnostics, Salem, USA). In the clinical biochemistry laboratory of Mount Sinai Hospital, cord serum glucose (in mmol/L, 1 mmol/L=18 mg/dL) was determined by an enzymatic (hexokinase) method (Roche Diagnostics, Switzerland), serum insulin (in μU/mL, 1 μU/mL=6 pmol/L) and C-peptide (in ng/mL, 1 ng/mL= 333 pmol/L) were determined by chemiluminescence immunoassays (Roche Diagnostics, Switzerland), serum IGF-1 (ng/mL) was determined by a chemiluminescent immunoassay (Liaison XL, DiaSorin, Italy). Cord serum testosterone (nmol/L) was measured by a chemiluminescent immunoassay, and cross reactivity was 18% with 11-β-hydroxy-testosterone, less than 0.16% with estradiol and progesterone, and less than 6% for other testosterone-like hormones according to the manufacturer’s instructions (Roche Diagnostics, Switzerland). The limits of detection were 0.922 pg/mL for myostatin, 0.11 mmol/L for glucose, 0.2 mU/L for insulin, 0.01 ng/mL for C-peptide, 0.455 pg/mL for proinsulin, 10 ng/mL for IGF-1, 0.02 ng/mL for IGF-2, and 0.087 nmol/L for testosterone, respectively. Intra- and inter-assay coefficients of variation were in the ranges of 1.8-6.0% for myostatin, 0.5-1.3% for glucose, 0.8-4.9% for insulin, 0.5-2.3% for C-peptide, 4.0-9.7% for proinsulin, 2.37-8.5% for IGF-1, 3.1-7.2% for IGF-2, and 2.1-18.1% for testosterone, respectively. All biomarkers were assayed in duplicates, and the average values were taken. The assay technicians were blinded to the clinical characteristics of study subjects.
Biological Assay
Biological Markers
C-Peptide
Chemiluminescent Assays
Clinical Laboratory Services
Cone-Rod Dystrophy 2
Cross Reactions
Diagnosis
Enzyme-Linked Immunosorbent Assay
Enzymes
Estradiol
GDF8 protein, human
Glucose
Hexokinase
Hormones
IGF1 protein, human
IGF II
Immunoassay
Insulin
Plasma
Progesterone
Proinsulin
Serum
Testosterone
The primary outcome was cord blood myostatin concentration. Birth weight z score was calculated according to the Canadian sex- and gestational age-specific birth weight standards (25 (link)). Mean±standard deviation (SD) or median (interquartile range) were presented for continuous variables. Frequency (percentage) was presented for categorical variables. Student’s t tests were conducted to compare continuous variables, and Chi-square tests or Fisher’s exact tests (where appropriate) were conducted to compare categorical variables between two groups. Pearson correlation coefficients were calculated to examine the correlations of cord blood myostatin with testosterone, fetal growth (birth weight z score) and fetal growth factors (insulin, C-peptide, proinsulin, IGF-1 and IGF-2). Log-transformed data were used for all cord blood biomarkers in t tests, correlation and regression analyses. Generalized linear regression was used to examine the determinants of cord blood myostatin. GDM status and fetal sex were the primary exposures of interest. Other covariates included maternal age, pre-pregnancy BMI (calculated from self-reported height and weight, kg/m2), ethnicity (Caucasian/Asian), education (university, yes/no), family history of type 2 diabetes (yes/no), smoking before pregnancy (yes/no), primiparity (yes/no), cesarean section (yes/no) and gestational age at delivery. Only a few mothers reported smoking (n=1) or alcohol drinking (n=2) during pregnancy, and thus not considered in data analyses. Covariates with P>0.2 that did not affect the comparisons were excluded in the parsimonious final regression models to obtain more stable effect estimates. In the presence of sex difference in cord blood myostatin concentrations, we examined the mediation effect of testosterone using the product (“Baron and Kenney”) method (26 (link)). P<0.025 was considered statistically significant in testing the primary hypothesis on the difference in cord blood myostatin concentrations by GDM status and fetal sex (Bonferroni correction for 2 tests). With Bonferroni correction for multiple tests, P<0.025 was considered statistically significant in examining the primary correlation of interest between cord blood myostatin and testosterone in sex-specific analyses. P<0.05 was considered statistically significant in other exploratory analyses. All data analyses were conducted in R Studio (Version 1.4.1717).
Asian Persons
Biological Markers
Birth Weight
BLOOD
C-Peptide
Caucasoid Races
Cesarean Section
Cone-Rod Dystrophy 2
Diabetes Mellitus, Non-Insulin-Dependent
Ethnicity
Fetal Growth
Fetus
GDF8 protein, human
Gestational Age
Growth Factor
IGF1 protein, human
IGF II
Insulin
Mothers
Obstetric Delivery
Pregnancy
Proinsulin
Sex Characteristics
Student
Testosterone
Umbilical Cord Blood
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Fetal Bovine Serum (FBS) is a cell culture supplement derived from the blood of bovine fetuses. FBS provides a source of proteins, growth factors, and other components that support the growth and maintenance of various cell types in in vitro cell culture applications.
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EGF is a lab equipment product from Thermo Fisher Scientific. It is a recombinant human Epidermal Growth Factor (EGF) protein. EGF is a growth factor that plays a role in cell proliferation and differentiation.
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TRIzol reagent is a monophasic solution of phenol, guanidine isothiocyanate, and other proprietary components designed for the isolation of total RNA, DNA, and proteins from a variety of biological samples. The reagent maintains the integrity of the RNA while disrupting cells and dissolving cell components.
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The RNeasy Mini Kit is a laboratory equipment designed for the purification of total RNA from a variety of sample types, including animal cells, tissues, and other biological materials. The kit utilizes a silica-based membrane technology to selectively bind and isolate RNA molecules, allowing for efficient extraction and recovery of high-quality RNA.
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TRIzol is a monophasic solution of phenol and guanidine isothiocyanate that is used for the isolation of total RNA from various biological samples. It is a reagent designed to facilitate the disruption of cells and the subsequent isolation of RNA.
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Insulin-like growth factor II is a protein that plays a role in cellular growth and development. It is commonly used in research applications to study its biological functions.
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FGF2 is a recombinant human fibroblast growth factor 2 protein. It is a heparin-binding growth factor that stimulates the proliferation of a variety of cell types, including fibroblasts, myoblasts, and vascular endothelial cells.
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The RNAqueous kit is a laboratory product designed for the isolation and purification of RNA from various sample types. The kit utilizes a proprietary guanidinium-based lysis and purification method to efficiently extract high-quality RNA suitable for downstream applications.
More about "IGF II"
Insulin-like growth factor II (IGF-II) is a crucial polypeptide hormone that plays a vital role in cell growth, differentiation, and fetal development.
It has been implicated in various disease processes, including cancer and metabolic disorders.
Researchers studying IGF-II can now optimize their research with the help of PubCompare.ai, an AI-driven platform that enhances the reproducibility and accuracy of IGF-II studies.
PubCompare.ai provides easy access to a vast repository of protocols from literature, preprints, and patents, allowing researchers to identify the best protocols and products for their IGF-II research.
The platform's AI-driven comparisons take the guesswork out of the process, helping researchers make more informed decisions and leading to more reliable and impactful findings.
In addition to IGF-II, researchers may also utilize other important biomolecules and reagents in their studies, such as Fetal Bovine Serum (FBS), Heparin, Epidermal Growth Factor (EGF), TRIzol reagent, Bovine Serum Albumin (BSA), RNeasy Mini Kit, TRIzol, Fibroblast Growth Factor 2 (FGF2), and the RNAqueous kit.
These tools and materials can be seamlessly integrated into IGF-II research workflows, enhancing the overall quality and efficiency of the work.
By leveraging the insights and capabilities of PubCompare.ai, researchers can optimzie their IGF-II studies, leading to more reproducible and accurate results.
This, in turn, can pave the way for groundbreaking discoveries and advancements in the understanding and treatment of various diseases associated with IGF-II.
It has been implicated in various disease processes, including cancer and metabolic disorders.
Researchers studying IGF-II can now optimize their research with the help of PubCompare.ai, an AI-driven platform that enhances the reproducibility and accuracy of IGF-II studies.
PubCompare.ai provides easy access to a vast repository of protocols from literature, preprints, and patents, allowing researchers to identify the best protocols and products for their IGF-II research.
The platform's AI-driven comparisons take the guesswork out of the process, helping researchers make more informed decisions and leading to more reliable and impactful findings.
In addition to IGF-II, researchers may also utilize other important biomolecules and reagents in their studies, such as Fetal Bovine Serum (FBS), Heparin, Epidermal Growth Factor (EGF), TRIzol reagent, Bovine Serum Albumin (BSA), RNeasy Mini Kit, TRIzol, Fibroblast Growth Factor 2 (FGF2), and the RNAqueous kit.
These tools and materials can be seamlessly integrated into IGF-II research workflows, enhancing the overall quality and efficiency of the work.
By leveraging the insights and capabilities of PubCompare.ai, researchers can optimzie their IGF-II studies, leading to more reproducible and accurate results.
This, in turn, can pave the way for groundbreaking discoveries and advancements in the understanding and treatment of various diseases associated with IGF-II.