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Mesenchyma
Mesenchyma
Mesenchyma refers to the loose connective tissue that gives rise to many of the body's structures, including bone, cartilage, muscle, and blood vessels.
This versatile tissue plays a crucial role in development, homeostasis, and repair processes.
Mesenchymal stem cells found within mesenchyma have the potential to differentiate into a variety of cell types, making them a focus of regenerative medicine research.
Understanding the biology and optimization of mesenchyma-related protocols is essential for advancing tissue engineering and personalized therapies.
PubCompare.ai's AI-driven comparisons can help locate the best practices and products from the scientific literature to improve reproducibility and accuracy in mesenchyma research.
This versatile tissue plays a crucial role in development, homeostasis, and repair processes.
Mesenchymal stem cells found within mesenchyma have the potential to differentiate into a variety of cell types, making them a focus of regenerative medicine research.
Understanding the biology and optimization of mesenchyma-related protocols is essential for advancing tissue engineering and personalized therapies.
PubCompare.ai's AI-driven comparisons can help locate the best practices and products from the scientific literature to improve reproducibility and accuracy in mesenchyma research.
Most cited protocols related to «Mesenchyma»
4-carboxyphenylglyoxal
ASNS protein, human
beta-Catenin
Brain Neoplasm, Malignant
Breast
Cadherins
Caspase-7
CCNE1 protein, human
CDKN2A Gene
Chronic Obstructive Airway Disease
Claudins
Cyclin B1
DPP4 protein, human
Estrogen Receptor alpha
FASN protein, human
GAPDH protein, human
Gastric Cancer
IGFBP-2 protein, human
Kidney
Liver
Malignant Neoplasms
Mesenchyma
Mitogen Activated Protein Kinase 1
Neoplasms
Phenobarbital
Phosphoproteins
PRKCA protein, human
Protein Arrays
Proteins
SERPINE1 protein, human
TFRC protein, human
Tubulin
Congenital Abnormality
EGFR protein, human
Germ Cells
Glioblastoma
Mesenchyma
Mus
Patients
Radiotherapy
Temozolomide
Method stability was examined using 500 TCGA breast cancer samples with both RNA-seq and microarray data (Sample IDs in Additional file 2 : Table S1), sub-sampled to vary the number of samples and genes present for each evaluation. To examine sample size effects upon a given sample, si, two data sets were created by sampling from both the RNA-seq and microarray data to select a sample si and n − 1 other random samples. The score for sample si was then computed using all listed methods, and this process was repeated across all 500 samples at a given sample size, such that there are 500 matched scores in total from both the microarray data and RNA-seq data. The Spearman’s rank correlation coefficient and concordance index were then calculated between sample scores from the microarray and the RNA-seq data. We note that for some methods sampling data in this manner can modify the background samples for a sample of interest, reflecting the influence of overall sample composition on the final scores. A similar analysis was performed by varying the number of genes, sub-sampling genes from the gene set of interest.
We performed this analysis with both epithelial and mesenchymal gene sets (expected up-regulated gene sets) [17 (link)], and the bidirectional TGFβ-EMT signature [8 (link)], varying the number of samples, NS = (2, 5, 25, 50, 500), and genes, NG = (1000, 3000, 5000, 10000, ALLGENES). All permutations were repeated 20 times to estimate error margins.
We performed this analysis with both epithelial and mesenchymal gene sets (expected up-regulated gene sets) [17 (link)], and the bidirectional TGFβ-EMT signature [8 (link)], varying the number of samples, NS = (2, 5, 25, 50, 500), and genes, NG = (1000, 3000, 5000, 10000, ALLGENES). All permutations were repeated 20 times to estimate error margins.
Genes
Malignant Neoplasm of Breast
Mesenchyma
Microarray Analysis
RNA-Seq
Transforming Growth Factor beta
CDH1 protein, human
Malignant Neoplasms
Mesenchyma
Neoplasms
Plant Embryos
RNA, Messenger
The Nkx3.1CreERT2/+ allele was generated by gene targeting using standard techniques; the Nkx3.1 null mutant mice have been previously described21 (link). R26R-lacZ and Pten conditional mutant mice were obtained from the Jackson Laboratory Induced Mutant Resource; the R26R-YFP mice were provided by Dr. Frank Costantini. All lines were maintained on a hybrid C57BL/6-129/Sv strain background.
Castration of adult male mice was performed using standard techniques. For tamoxifen induction of Cre activity in mice containing Nkx3.1CreERT2/+, mice were administered 9 mg/40 g tamoxifen for 4 consecutive days. For prostate regeneration, physiological levels of testosterone (1.875 µg/hr) were administered for four weeks by subcutaneous implantation of mini-osmotic pumps (Alzet)45 (link). When included, BrdU (100 mg/kg) was administered once daily during the first three days of regeneration. For single-cell transplantation, single YFP+ cells were isolated by mouth-pipetting under epifluorescence illumination from a dissociated prostate cell suspension obtained from castrated and tamoxifen-induced Nkx3.1CreERT2/+; R26R-YFP/+ mice. A single YFP+ cell (or YFP− cell as a control) was recombined with 2.5 × 105 rat urogenital sinus mesenchyme cells in a 10 µl collagen pad, followed by transplantation under the kidney capsule of nude mice and harvesting after 10–12 weeks.
Cryosections were stained with primary antibodies as listed inSupp. Table 5 , and counterstained with TOPRO3 or DAPI (Invitrogen/Molecular Probes). Secondary antibodies were labeled with Alexa Fluor 488 , 555, or 594 (Invitrogen/Molecular Probes). Immunofluorescence staining was imaged using a Leica TCS5 spectral confocal microscope. Cell counting was performed manually using confocal photomicrographs with at least three animals for each experiment or genotype analyzed.
Castration of adult male mice was performed using standard techniques. For tamoxifen induction of Cre activity in mice containing Nkx3.1CreERT2/+, mice were administered 9 mg/40 g tamoxifen for 4 consecutive days. For prostate regeneration, physiological levels of testosterone (1.875 µg/hr) were administered for four weeks by subcutaneous implantation of mini-osmotic pumps (Alzet)45 (link). When included, BrdU (100 mg/kg) was administered once daily during the first three days of regeneration. For single-cell transplantation, single YFP+ cells were isolated by mouth-pipetting under epifluorescence illumination from a dissociated prostate cell suspension obtained from castrated and tamoxifen-induced Nkx3.1CreERT2/+; R26R-YFP/+ mice. A single YFP+ cell (or YFP− cell as a control) was recombined with 2.5 × 105 rat urogenital sinus mesenchyme cells in a 10 µl collagen pad, followed by transplantation under the kidney capsule of nude mice and harvesting after 10–12 weeks.
Cryosections were stained with primary antibodies as listed in
Adult
alexa fluor 488
Alleles
Animals
Antibodies
Bromodeoxyuridine
Capsule
Cells
Cell Transplantation
Collagen
Cryoultramicrotomy
DAPI
Fluorescent Antibody Technique
Genotype
Hybrids
Kidney
LacZ Genes
Light
Male Castration
Mesenchyma
Mice, Knockout
Mice, Nude
Microscopy, Confocal
Molecular Probes
Mus
Oral Cavity
Orchiectomy
Osmosis
Ovum Implantation
Photomicrography
physiology
Prostate
PTEN protein, human
Regeneration
Sinuses, Nasal
Strains
System, Genitourinary
Tamoxifen
Testosterone
Transplantation
Most recents protocols related to «Mesenchyma»
Example 4
Given the effect of the overexpression of the SEQ ID NO:1, further experiments were performed to study its effect in cell invasion, another key oncogenic trait. Boyden chamber assay was used to determine invasiveness of A549 and H10 cancer cells after 4 days of doxycycline induction of SEQ ID NO:1, showing that the expression of the micropeptide induces a significant decrease in invasion (
Biological Assay
Carcinogenesis
Cell Lines
Cells
Down-Regulation
Doxycycline
Mesenchyma
N-Cadherins
Neoplastic Cell Transformation
Slugs
Snails
Tumor Suppressor Genes
TWIST1 protein, human
Vimentin
Example 7
Tumor-Derived MSC-Like Lymphoma Stromal Cells are Immunosuppressive
Since the tumor cells in lymphoma are not adherent, it is possible to isolate tumor stromal cells from lymphomas developed in p53+/− mice. It was observed that these cells can be passaged in vitro and can be differentiated into adipocytes and osteoblast-like cells. Interestingly, like bone marrow derived MSCs, these tumor stromal cells are also immunosuppressive and can effectively inhibit the proliferation of ant-CD3-activated splenocytes. This immunosuppressive effect was also dependent on IFNγ+TNF α and NO, since anti-IFNγ IFNγ and iNOS inhibitors could reverse the immunosuppressive effect.
Adipocytes
Bone Marrow
Cardiac Arrest
Cells
Immunosuppressive Agents
inhibitors
Interferon Type II
Lymphoma
Mesenchyma
Mus
Neoplasms
NOS2A protein, human
Osteoblasts
Response, Immune
Stem, Plant
Stromal Cells
Tumor-Derived Activated Cells
Tumor Necrosis Factor-alpha
Example 1
The pluripotent stem cell line H9 was obtained from NIH line WA 09, supplied by WiCell (Madison, Wis.) and was maintained in an undifferentiated state by passaging on irradiated human foreskin fibroblasts (line HS27, ATCC, Manassas, Va.) and gelatin coated plates. To differentiate the pluripotent stem cells towards a mesodermal and then mesenchymal lineage, the colonies of the pluripotent stem cells were mechanically dissected into small pieces under microscopic guidance and then transferred to tissue culture-treated 6-well plates (Corning). The cells at this stage were considered passage 0 (P0). The cells were cultured in DMEM/F12 supplemented with non-essential amino acids and 10% fetal bovine serum (FBS, Invitrogen-Gibco, Grand Island, N.Y.). When the culture approached confluency, cells were trypsinized and transferred to a new tissue culture flask.
Amino Acids, Essential
Cells
Fibroblasts
Foreskin
Gelatins
Homo sapiens
Mesenchyma
Mesoderm
Microscopy
Pluripotent Stem Cells
Tissues
Staining was compared among UC, inflammatory non-neoplastic (cystitis), and normal urinary bladder samples. A histologically confirmed canine metastatic hemangiosarcoma served as a positive control for VEGFR2; a canine liposarcoma served as a positive control for KIT; a canine squamous cell carcinoma served as a positive control for PDGFR-β; and a canine mesenchymal neoplasm was used as a positive control for CDK4 (Suppl. Figs. 1–4 ). A negative control that omitted incubation with the primary antibody (antibody diluent with no antibody) was included for each sample.
Samples were evaluated for urothelial expression of VEGFR2, KIT, PDGFR-β, and CDK4 in an anonymized study by 3 veterinary pathologists, each from a different institution. A qualitative immunohistochemical assessment was performed to evaluate staining intensity. As described previously,32
staining intensity was assessed over the whole sample at 200 × magnification (0 = none, 1 = mild, 2 = moderate, 3 = intense). Staining distribution (% urothelial cells affected) was evaluated semi-quantitatively over 10 hpfs at 400 × magnification (0 = no staining, 1 = >0% to <10% positive, 2 = ≥10% to <25% positive, 3 = ≥25% to 50% positive, 4 = ≥50% to <75% positive, 5 = ≥75% positive). To calculate a score for every sample, the average scores were taken and called the standardized score. After averaging the 10 selected fields, a final immunohistochemical score for each sample was calculated by multiplying the intensity (qualitative) standardized score by the staining distribution (semi-quantitative) standardized score, as described previously.3 (link),22 (link)
Samples were evaluated for urothelial expression of VEGFR2, KIT, PDGFR-β, and CDK4 in an anonymized study by 3 veterinary pathologists, each from a different institution. A qualitative immunohistochemical assessment was performed to evaluate staining intensity. As described previously,32
staining intensity was assessed over the whole sample at 200 × magnification (0 = none, 1 = mild, 2 = moderate, 3 = intense). Staining distribution (% urothelial cells affected) was evaluated semi-quantitatively over 10 hpfs at 400 × magnification (0 = no staining, 1 = >0% to <10% positive, 2 = ≥10% to <25% positive, 3 = ≥25% to 50% positive, 4 = ≥50% to <75% positive, 5 = ≥75% positive). To calculate a score for every sample, the average scores were taken and called the standardized score. After averaging the 10 selected fields, a final immunohistochemical score for each sample was calculated by multiplying the intensity (qualitative) standardized score by the staining distribution (semi-quantitative) standardized score, as described previously.3 (link),22 (link)
Canis familiaris
Cells
Cystitis
Figs
Hemangiosarcoma
Immunoglobulins
Inflammation
Liposarcoma
Mesenchyma
Neoplasms
Pathologists
Platelet-Derived Growth Factor beta Receptor
Squamous Cell Carcinoma
Urinary Bladder
Urothelium
Vascular Endothelial Growth Factor Receptor-2
We extracted the single-cell RNA sequencing data used in this paper from Gene Expression Omnibus (GEO; GSE138826) (https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE138826 ; GSE138826_expression_matrix.txt) (Oprescu et al., 2020 (link)). The preliminary analyses of processed scRNA-seq data were analysed using the Seurat suite (version 4.0.3) standard workflow in RStudio Version 1.2.5042 and R version 4.0.3. First, we applied initial quality control to Oprescu et al., 2020 (link) dataset. We kept all the features (genes) expressed at least in five cells and cells with more than 200 genes detected. Otherwise, we filtered out the cells. Second, we verified nUMIs_RNA (>200 and < 4,000) and percent.mt. (less than 5%) Third, UMIs were normalized to counts-per-ten-thousand log-transformed (normalization.method = LogNormalize). The log-normalized data were then used to find variable genes (FindVariableFeatures) and scaled (ScaleData). Finally, Principal Component Analysis (PCA) was run (RunPCA) on the scaled data using highly variable features or genes. Elbowplot were used to decide the number of principal components (PCs) to use for unsupervised graph-based clustering and dimensional reduction plot (UMAP) embedding of all cells or further subclustering analyses (i.e., FAPs) using the standard FindNeighbors, FindClusters, and RunUMAP workflow. We used 30 PCs and a resolution of 0.6 to visualize a Uniform manifold approximation and projection (UMAP) dimensionality reduction plot generated on the same set of PCs used for clustering. We decided the resolution value for FindClusters on a supervised basis after considering clustering output from a range of resolutions (0.4, 0.6, 0.8, and 1.2). We used a resolution of 0.6. Our initial clustering analysis returned 29 clusters (clusters 0–28). We identified cell populations and lineage-specific marker genes for the analyzed dataset using the FindAllMarkers function with logfc.threshold = 0.25, test.use = “wilcox,” and max.cells.per.ident = 1,000. We then plotted the top 10 expressed genes, grouped by orig.ident and seurat_clusters using the DoHeatmap function. We determine cell lineages and cell types based on the expression of canonical genes. We also inspected the clusters (in Figures 2 , 3 ) for hybrid or not well-defined gene expression signatures. Clusters that had similar canonical marker gene expression patterns were merged.
For Mesenchymal Clusters (group of FAPs + DiffFibroblasts + Tenocytes obtained inFigure 2 ) we used PCs 20 and a resolution of 20 to visualize on the UMAP plot. Our mesenchymal subclustering analysis returned 10 clusters (clusters 0–9). Cell populations and lineage-specific marker genes were identified for the analyzed dataset using the FindAllMarkers function with logfc.threshold = 0.25 and max.cells.per.ident = 1,000. We then plotted the top eight expressed genes, grouped by orig.ident and seurat_clusters using the DoHeatmap function. The identity of the returned cell clusters was then annotated based on known marker genes (see details about cell type and cell lineage definitions in the main text, Results section). Individual cell clusters were grouped to represent cell lineages and types better. Finally, figures were generated using Seurat and ggplot2 R packages. We also used dot plots because they reveal gross differences in expression patterns across different cell types and highlight moderately or highly expressed genes.
To validate our initial skeletal muscle single-cell analysis, we explored three publicly available scRNAseq datasets (McKellar et al., 2021 (link); Yang et al., 2022 (link); Zhang et al., 2022 (link)). Zhang et al. dataset was explored using R/ShinyApp (https://mayoxz.shinyapps.io/Muscle ), McKellar et al. (2021) (link) using their web tool developed http://scmuscle.bme.cornell.edu/ , and Yang et al. using their Single Cell Metab Browser http://scmetab.mit.edu/ . All the figures used were downloaded from the websites (Supplementary Figure S6 ).
The scRNAseq pipeline used for MuSC subclustering was developed following previous studies (Oprescu et al., 2020 (link); Contreras et al., 2021a (link)). To perform unsupervised MuSC subclustering, we used Seurat’s subset function FindClusters, followed by dimensionality reduction and UMAP visualization (DimPlot) in Seurat.
For Mesenchymal Clusters (group of FAPs + DiffFibroblasts + Tenocytes obtained in
To validate our initial skeletal muscle single-cell analysis, we explored three publicly available scRNAseq datasets (McKellar et al., 2021 (link); Yang et al., 2022 (link); Zhang et al., 2022 (link)). Zhang et al. dataset was explored using R/ShinyApp (
The scRNAseq pipeline used for MuSC subclustering was developed following previous studies (Oprescu et al., 2020 (link); Contreras et al., 2021a (link)). To perform unsupervised MuSC subclustering, we used Seurat’s subset function FindClusters, followed by dimensionality reduction and UMAP visualization (DimPlot) in Seurat.
Cells
FAP protein, human
Gene Expression
Genes
Genetic Markers
Hybrids
Mesenchyma
Muscle Tissue
Single-Cell Analysis
Single-Cell RNA-Seq
Skeletal Muscles
Tenocytes
Top products related to «Mesenchyma»
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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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Penicillin/streptomycin is a commonly used antibiotic solution for cell culture applications. It contains a combination of penicillin and streptomycin, which are broad-spectrum antibiotics that inhibit the growth of both Gram-positive and Gram-negative bacteria.
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DMEM (Dulbecco's Modified Eagle's Medium) is a cell culture medium formulated to support the growth and maintenance of a variety of cell types, including mammalian cells. It provides essential nutrients, amino acids, vitamins, and other components necessary for cell proliferation and survival in an in vitro environment.
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Penicillin is a type of antibiotic used in laboratory settings. It is a broad-spectrum antimicrobial agent effective against a variety of bacteria. Penicillin functions by disrupting the bacterial cell wall, leading to cell death.
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Streptomycin is a broad-spectrum antibiotic used in laboratory settings. It functions as a protein synthesis inhibitor, targeting the 30S subunit of bacterial ribosomes, which plays a crucial role in the translation of genetic information into proteins. Streptomycin is commonly used in microbiological research and applications that require selective inhibition of bacterial growth.
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L-glutamine is an amino acid that is commonly used as a dietary supplement and in cell culture media. It serves as a source of nitrogen and supports cellular growth and metabolism.
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DMEM/F12 is a cell culture medium developed by Thermo Fisher Scientific. It is a balanced salt solution that provides nutrients and growth factors essential for the cultivation of a variety of cell types, including adherent and suspension cells. The medium is formulated to support the proliferation and maintenance of cells in vitro.
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α-MEM is a cell culture medium formulated for the growth and maintenance of mammalian cells. It provides a balanced salt solution, amino acids, vitamins, and other nutrients required for cell proliferation.
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Trypsin-EDTA is a solution used in cell culture applications to dissociate adherent cells from their growth surface. It contains the proteolytic enzyme trypsin and the chelating agent EDTA, which work together to break down the cellular adhesions and allow the cells to be harvested and passaged.
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Trypsin is a proteolytic enzyme that hydrolyzes peptide bonds in proteins. It is commonly used in cell biology and molecular biology applications to facilitate cell detachment and dissociation.
More about "Mesenchyma"
Mesenchyma, also known as mesenchyme, refers to the versatile connective tissue that gives rise to a variety of structures in the body, including bone, cartilage, muscle, and blood vessels.
This dynamic tissue plays a crucial role in development, homeostasis, and repair processes.
Mesenchymal stem cells (MSCs), found within the mesenchyma, have the remarkable ability to differentiate into diverse cell types, making them a focus of regenerative medicine research.
Understanding the biology and optimization of mesenchyma-related protocols is essential for advancing tissue engineering and personalized therapies.
Researchers often utilize cell culture media and reagents such as fetal bovine serum (FBS), penicillin/streptomycin, Dulbecco's Modified Eagle Medium (DMEM), penicillin, streptomycin, L-glutamine, DMEM/F12, α-MEM, and trypsin-EDTA to support the growth and maintenance of mesenchymal stem cells and mesenchymal tissue.
PubCompare.ai's AI-driven comparisons can help locate the best practices and products from the scientific literature, enabling researchers to improve reproducibility and accuracy in their mesenchyma research.
By leveraging this powerful platform, scientists can discover the optimal protocols and products to advance their work in this critical area of regenerative medicine.
This dynamic tissue plays a crucial role in development, homeostasis, and repair processes.
Mesenchymal stem cells (MSCs), found within the mesenchyma, have the remarkable ability to differentiate into diverse cell types, making them a focus of regenerative medicine research.
Understanding the biology and optimization of mesenchyma-related protocols is essential for advancing tissue engineering and personalized therapies.
Researchers often utilize cell culture media and reagents such as fetal bovine serum (FBS), penicillin/streptomycin, Dulbecco's Modified Eagle Medium (DMEM), penicillin, streptomycin, L-glutamine, DMEM/F12, α-MEM, and trypsin-EDTA to support the growth and maintenance of mesenchymal stem cells and mesenchymal tissue.
PubCompare.ai's AI-driven comparisons can help locate the best practices and products from the scientific literature, enabling researchers to improve reproducibility and accuracy in their mesenchyma research.
By leveraging this powerful platform, scientists can discover the optimal protocols and products to advance their work in this critical area of regenerative medicine.