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> Anatomy > Body Part > Colon

Colon

The colon is a vital part of the human digestive system, responsible for the final stages of waste elimination.
It is a long, tubular organ that connects the small intestine to the rectum.
The colon plays a crucial role in water absorption, electrolyte balance, and the formation of stool.
Diseases and conditions affecting the colon, such as colorectal cancer, inflammatory bowel disease, and diverticulitis, can have serious health consequences.
Optimizing colon health through research into effective protocols and products is essential for maintaining overall gastrointestinal wellbeing.
PubCompare.ai, an innovative AI-powered platform, can help researchers locate relevant protocols from literature, preprints, and patents, and use AI-driven comparisons to identify the best approaches for their needs, ensuring reproducibility and accruacy in their work.

Most cited protocols related to «Colon»

1
Standardized Variant Call Format for Genomic Data
A VCF file (Fig. 1a) consists of a header section and a data section. The header contains an arbitrary number of meta-information lines, each starting with characters ‘##’, and a TAB delimited field definition line, starting with a single ‘#’ character. The meta-information header lines provide a standardized description of tags and annotations used in the data section. The use of meta-information allows the information stored within a VCF file to be tailored to the dataset in question. It can be also used to provide information about the means of file creation, date of creation, version of the reference sequence, software used and any other information relevant to the history of the file. The field definition line names eight mandatory columns, corresponding to data columns representing the chromosome (CHROM), a 1-based position of the start of the variant (POS), unique identifiers of the variant (ID), the reference allele (REF), a comma separated list of alternate non-reference alleles (ALT), a phred-scaled quality score (QUAL), site filtering information (FILTER) and a semicolon separated list of additional, user extensible annotation (INFO). In addition, if samples are present in the file, the mandatory header columns are followed by a FORMAT column and an arbitrary number of sample IDs that define the samples included in the VCF file. The FORMAT column is used to define the information contained within each subsequent genotype column, which consists of a colon separated list of fields. For example, the FORMAT field GT:GQ:DP in the fourth data entry of Figure 1a indicates that the subsequent entries contain information regarding the genotype, genotype quality and read depth for each sample. All data lines are TAB delimited and the number of fields in each data line must match the number of fields in the header line. It is strongly recommended that all annotation tags used are declared in the VCF header section.

(a) Example of valid VCF. The header lines ##fileformat and #CHROM are mandatory, the rest is optional but strongly recommended. Each line of the body describes variants present in the sampled population at one genomic position or region. All alternate alleles are listed in the ALT column and referenced from the genotype fields as 1-based indexes to this list; the reference haplotype is designated as 0. For multiploid data, the separator indicates whether the data are phased (|) or unphased (/). Thus, the two alleles C and G at the positions 2 and 5 in this figure occur on the same chromosome in SAMPLE1. The first data line shows an example of a deletion (present in SAMPLE1) and a replacement of two bases by another base (SAMPLE2); the second line shows a SNP and an insertion; the third a SNP; the fourth a large structural variant described by the annotation in the INFO column, the coordinate is that of the base before the variant. (b–f) Alignments and VCF representations of different sequence variants: SNP, insertion, deletion, replacement, and a large deletion. The REF columns shows the reference bases replaced by the haplotype in the ALT column. The coordinate refers to the first reference base. (g) Users are advised to use simplest representation possible and lowest coordinate in cases where the position is ambiguous.

Danecek P., Auton A., Abecasis G., Albers C.A., Banks E., DePristo M.A., Handsaker R.E., Lunter G., Marth G.T., Sherry S.T., McVean G, & Durbin R. (2011). The variant call format and VCFtools. Bioinformatics, 27(15), 2156-2158.
Publication 2011
Alleles Character Chromosomes Colon Deletion Mutation Genetic Diversity Genome Genotype Haplotypes Human Body
2
Standardizing Bowel Preparation Evaluation

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Publication 2009
Bohring syndrome Cecum Colon Colon, Ascending Colon, Descending Colonoscopy Endoscopy Feces Intestines Left Colic Flexure Mucous Membrane Rectum Sigmoid Colon Transverse Colon Vision
3
Proteomic Profiling of TCGA Tumor Samples
All tumor samples for the current study were obtained through the TCGA Biospecimen Core Resource (BCR) as described previously6 (link). No other selection criteria other than availability were applied for this study. Patient-derived xenograft tumors from established Basal and Luminal-B breast cancer intrinsic subtypes 37 (link), 38 (link) were raised subcutaneously in 8 week old NOD.Cg-Prkdcscid Il2rgtm1Wjl/SzJ mice (Jackson Labs, Bar Harbor, Maine) as previously described39 (link), 40 (link). Normal colon biopsies were obtained from screening colonoscopies performed between July 2006 and October 2010 under Vanderbilt University IRB approval #061096.
Tissue proteins were extracted and tryptic peptide digests were analyzed by multidimensional liquid chromatography-tandem mass spectrometry. Xenograft QC samples were run after every 5 colorectal tumor samples. Raw data were processed for peptide identification by database and spectral library searching and identified peptides were assembled as proteins and mapped to gene identifiers for proteogenomic comparisons. Quantitative proteomic comparisons were based on spectral count data. Detailed descriptions of the samples, LC-MS/MS analysis, and data analysis methods can be found in Supplementary Methods. All of the primary mass spectrometry data on TCGA tumor samples are deposited at the CPTAC Data Coordinating Center as raw and mzML files and complete protein assembly datasets for public access (https://cptac-data-portal.georgetown.edu).
Zhang B., Wang J., Wang X., Zhu J., Liu Q., Shi Z., Chambers M.C., Zimmerman L.J., Shaddox K.F., Kim S., Davies S.R., Wang S., Wang P., Kinsinger C.R., Rivers R.C., Rodriguez H., Townsend R.R., Ellis M.J., Carr S.A., Tabb D.L., Coffey R.J., Slebos R.J, & Liebler D.C. (2014). Proteogenomic characterization of human colon and rectal cancer. Nature, 513(7518), 382-387.
Publication 2014
Biopsy Breast Carcinoma cDNA Library Colon Colonoscopy Colorectal Neoplasms Heterografts Liquid Chromatography Mass Spectrometry Mice, Inbred NOD Neoplasms Patients Peptides Phenobarbital Proteins Tandem Mass Spectrometry Tissues Trypsin
4
Comprehensive Colorectal Cancer Genomics
After quality control (QC), this study included whole-genome sequencing (WGS) data for 1,439 colorectal cancer (CRC) cases and 720 controls from 5 studies, and GWAS array data for 58,131 CRC or advanced adenoma cases (3,674; 6.3% of cases) and 67,347 controls from 45 studies from GECCO, CORECT, and CCFR. The Stage 1 meta-analysis comprised existing genotyping data from 30 studies that were included in previously published CRC GWAS13 (link),18 (link),22 (link). After QC, the Stage 1 meta-analysis included 34,869 cases and 29,051 controls. Study participants were predominantly of European ancestry (31,843 cases and 26,783 controls; 91.7% of participants). Because it was shown previously that the vast majority of known CRC risk variants are shared between Europeans and East Asians17 (link), we included 3,026 cases and 2,268 controls of East Asian ancestry to increase power for discovery. The Stage 2 meta-analysis comprised newly generated genotype data involving 4 genotyping projects and 22 studies. After QC, the Stage 2 meta-analysis included 23,262 cases and 38,296 controls, all of European ancestry. Studies, sample selection, and matching are described in the Supplementary Text. Supplementary Table 1 provides details on sample numbers, and demographic characteristics of study participants. All participants provided written informed consent, and each study was approved by the relevant research ethics committee or institutional review board. Four normal colon mucosa biopsies for ATAC-seq were obtained from patients with a normal colon at colonoscopy at the Institut d’Investigació Biomèdica de Bellvitge (IDIBELL), Spain. Patients signed informed consent, and the protocol was approved by the Bellvitge Hospital Ethics Committee (Colscreen protocol PR084/16).
Huyghe J.R., Bien S.A., Harrison T.A., Kang H.M., Chen S., Schmit S.L., Conti D.V., Qu C., Jeon J., Edlund C.K., Greenside P., Wainberg M., Schumacher F.R., Smith J.D., Levine D.M., Nelson S.C., Sinnott-Armstrong N.A., Albanes D., Alonso M.H., Anderson K., Arnau-Collell C., Arndt V., Bamia C., Banbury B.L., Baron J.A., Berndt S.I., Bézieau S., Bishop D.T., Boehm J., Boeing H., Brenner H., Brezina S., Buch S., Buchanan D.D., Burnett-Hartman A., Butterbach K., Caan B.J., Campbell P.T., Carlson C.S., Castellví-Bel S., Chan A.T., Chang-Claude J., Chanock S.J., Chirlaque M.D., Cho S.H., Connolly C.M., Cross A.J., Cuk K., Curtis K.R., de la Chapelle A., Doheny K.F., Duggan D., Easton D.F., Elias S.G., Elliott F., English D.R., Feskens E.J., Figueiredo J.C., Fischer R., FitzGerald L.M., Forman D., Gala M., Gallinger S., Gauderman W.J., Giles G.G., Gillanders E., Gong J., Goodman P.J., Grady W.M., Grove J.S., Gsur A., Gunter M.J., Haile R.W., Hampe J., Hampel H., Harlid S., Hayes R.B., Hofer P., Hoffmeister M., Hopper J.L., Hsu W.L., Huang W.Y., Hudson T.J., Hunter D.J., Ibañez-Sanz G., Idos G.E., Ingersoll R., Jackson R.D., Jacobs E.J., Jenkins M.A., Joshi A.D., Joshu C.E., Keku T.O., Key T.J., Kim H.R., Kobayashi E., Kolonel L.N., Kooperberg C., Kühn T., Küry S., Kweon S.S., Larsson S.C., Laurie C.A., Le Marchand L., Leal S.M., Lee S.C., Lejbkowicz F., Lemire M., Li C.I., Li L., Lieb W., Lin Y., Lindblom A., Lindor N.M., Ling H., Louie T.L., Männistö S., Markowitz S.D., Martín V., Masala G., McNeil C.E., Melas M., Milne R.L., Moreno L., Murphy N., Myte R., Naccarati A., Newcomb P.A., Offit K., Ogino S., Onland-Moret N.C., Pardini B., Parfrey P.S., Pearlman R., Perduca V., Pharoah P.D., Pinchev M., Platz E.A., Prentice R.L., Pugh E., Raskin L., Rennert G., Rennert H.S., Riboli E., Rodríguez-Barranco M., Romm J., Sakoda L.C., Schafmayer C., Schoen R.E., Seminara D., Shah M., Shelford T., Shin M.H., Shulman K., Sieri S., Slattery M.L., Southey M.C., Stadler Z.K., Stegmaier C., Su Y.R., Tangen C.M., Thibodeau S.N., Thomas D.C., Thomas S.S., Toland A.E., Trichopoulou A., Ulrich C.M., Van Den Berg D.J., van Duijnhoven F.J., Van Guelpen B., van Kranen H., Vijai J., Visvanathan K., Vodicka P., Vodickova L., Vymetalkova V., Weigl K., Weinstein S.J., White E., Win A.K., Wolf C.R., Wolk A., Woods M.O., Wu A.H., Zaidi S.H., Zanke B.W., Zhang Q., Zheng W., Scacheri P.C., Potter J.D., Bassik M.C., Kundaje A., Casey G., Moreno V., Abecasis G.R., Nickerson D.A., Gruber S.B., Hsu L, & Peters U. (2018). Discovery of common and rare genetic risk variants for colorectal cancer. Nature genetics, 51(1), 76-87.
Publication 2018
Adenoma Asian Persons ATAC-Seq Biopsy Colon Colonoscopy Colorectal Carcinoma East Asian People Ethics Committees, Clinical Ethics Committees, Research Europeans Genome-Wide Association Study Malignant Neoplasms Mucous Membrane Patients
5
Comprehensive CRC Transcriptome Normalization
The publicly available data sets with CRC tumor samples from the Gene Expression Omnibus (Supplementary Table 3) were normalized using the robust multi-array average (RMA) method as implemented in the affy package39 . Overlapping samples in GSE14333 and GSE17536 were excluded from GSE14333. For consensus network analysis and training a consensus subtype classifier, all private and public Affymetrix data sets were renormalized using the single-sample frozen RMA method33 as implemented in the frma package for R/Bioconductor.
Several of the CRC tumor sets were analysed on full genome Agilent microarrays (Agilent, Santa Clara). Samples were hybridized against a common CRC reference pool, and full genome data was normalized using loess and local background subtraction (limma package). Details about sample processing and microarray analysis can be found in Roepman et al.3 (link).
Level 3 TCGA RNA-seq data for colon and rectal was downloaded from the TCGA data portal (January 2014). RSEM normalized data40 was further log transformed, and non-tumor samples were removed. Principal component analysis (PCA) revealed no clear differences between rectal and colon samples (data not shown) and samples were combined without adjustment. PCA showed a strong separation between GA and HiSeq samples, and corrected using the ComBat method32 .
We additionally performed outlier sample detection within each data set using 2 methods: a method based on PCA, and the arrayQualityMetrics R package41 . For the PCA approach, we took into account the first two principal components and marked all samples with a distance greater than 2.5 as potential outliers. We next employed arrayQualityMetrics to flag outliers based on pairwise sample distances, gene expression value distributions and MA plots (MA plots were not investigated for Agilent-based expression data sets). Overall, a sample was classified as outlier if it was flagged based on the distribution of gene expression values and either pairwise distances to other samples or the PCA criterion. Outliers were removed from further analysis.
Guinney J., Dienstmann R., Wang X., de Reyniès A., Schlicker A., Soneson C., Marisa L., Roepman P., Nyamundanda G., Angelino P., Bot B.M., Morris J.S., Simon I.M., Gerster S., Fessler E., de Sousa e Melo F., Missiaglia E., Ramay H., Barras D., Homicsko K., Maru D., Manyam G.C., Broom B., Boige V., Perez-Villamil B., Laderas T., Salazar R., Gray J.W., Hanahan D., Tabernero J., Bernards R., Friend S.H., Laurent-Puig P., Medema J.P., Sadanandam A., Wessels L., Delorenzi M., Kopetz S., Vermeulen L, & Tejpar S. (2015). The Consensus Molecular Subtypes of Colorectal Cancer. Nature medicine, 21(11), 1350-1356.
Publication 2015
Colon Freezing Gene Expression Genome Microarray Analysis Neoplasms Rectum RNA-Seq

Most recents protocols related to «Colon»

1
Tryptamine's Effect on Gut Motility
Not available on PMC !

Example 6

The organ bath system represents an ex vivo system lacking central nervous system (CNS) connections. Gastrointestinal motility is investigated using mice as an animal model. Experiments are performed to measure colonic contractility in conscious germ free (GF) and colonized mice with infusion of tryptamine by enema as well as following colonization of GF with tryptamine producing E. coli. The effect of tryptamine on epithelial biology also is determined.

US11878002B2. Methods and materials for using Ruminococcus gnavus or Clostridium sporogenes to treat gastrointestinal disorders (2024-01-23). Mayo Foundation for Medical Education and Research [US], The Regents of the University of California [US]. Inventors: Purna C. Kashyap [US], Michael Fischbach [US], Brianna B. Williams [US].
Full text: Click here
Patent 2024
Animal Model Bath Central Nervous System Colon Consciousness Enema Escherichia coli Gastrointestinal Motility Mus Muscle Contraction Tryptamines
2
Adalimumab PK/PD in Swine Colitis
Not available on PMC !

Example 11

The purpose of this non-Good Laboratory Practice (GLP) study is to explore the PK/PD and bioavailability of adalimumab when applied to DSS-induced colitis in Yorkshire-cross farm swine. All animals are randomized into groups of three. Animals are dosed once with adalimumab via subcutaneous (SC), perirectal (PR), or intracecal (IC) administration.

The concentration of adalimumab and TNFα is measured in plasma at 1, 2, 3, 4, 6, and 12 hours post-dose. The concentration of adalimumab is measured in rectal contents at 1, 3, 6, and 12 hours post-dose and in luminal content at 12 hours post-dose. Concentration of adalimumab and TNFα, HER2, and total protein is measured in gastrointestinal tissue, e.g., cecum sample (CAC), proximal colon sample (PCN), transverse colon sample (TCN), distal colon sample (DCNi) inflamed, distal colon non-inflamed sample (DCNn), and rectum sample (RTM), at 12 hours post-dose.

US11857669B2. Treatment of a disease of the gastrointestinal tract with a JAK inhibitor and devices (2024-01-02). BIORA THERAPEUTICS, INC. [US]. Inventors: Mitchell Lawrence Jones [US], Sharat Singh [US], Christopher Loren Wahl [US], Harry Stylli [US].
Full text: Click here
Patent 2024
Adalimumab Animals Cecum Colitis Colon Drug Kinetics ERBB2 protein, human Gastrointestinal Contents Medical Devices Obstetric Delivery Phenobarbital Pigs Plasma Proteins Rectum Tissues Transverse Colon Tumor Necrosis Factor-alpha
3
Evaluating Tucaresol and Checkpoint Inhibitors in Xenograft Models
Not available on PMC !

Example 7

Five groups including tucaresol, tucaresol plus PD-1 or PD-L1 antibody, tucaresol plus CTLA-4 antibody, CTLA-4 antibody plus PD-1 or PD-L1 antibody, and tucaresol plus plinabulin are tested to determine their effect in an animal xenograft model.

The combined treatment with tucaresol and the checkpoint inhibitor(s) is tested in comparison with the treatment with tucaresol alone, the treatment with checkpoint inhibitor alone, or combination of checkpoint inhibitors. The tests are performed using seven to ten-week old athymic (nu/nu) mice that were injected subcutaneously with human tumor cell lines (of either solid or liquid tumor origin, for example of breast, lung, colon, brain, liver, leukemia, myeloma, lymphoma, sarcoma, pancreatic or renal origin). Six to ten testing groups are prepared, and each group includes 10 mice.

Each treatment starts at tumor size between 40-150 mm3 and continues until Day 24-56, when the animals are necropsied. To determine the efficacy of each treatment, the following data are collected: mortality; the body weight of the mice assessed twice weekly both prior to treatments; the rate of tumor growth as determined by the tumor size measurement (twice every week); the tumor growth index; overall survival rate; the tumor weight at necropsy; and the time required to increase tumor size 10 fold.

US11857522B2. Compositions containing tucaresol or its analogs (2024-01-02). BeyondSpring Pharmaceuticals, Inc. [US]. Inventors: Ramon Mohanlal [US], Lan Huang [US], George Kenneth Lloyd [US].
Full text: Click here
Patent 2024
Animal Model Animals Autopsy Body Weight Brain Breast CD274 protein, human Cell Cycle Checkpoints Cell Line, Tumor Colon Combined Modality Therapy CTLA4 protein, human Genes, Neoplasm GZMB protein, human Heterografts Homo sapiens Immunoglobulins inhibitors Kidney Leukemia Liver Lung Lymphoma Mice, Nude Multiple Myeloma Mus Neoplasms Pancreas plinabulin Sarcoma Thymic aplasia tucaresol
4
Contractile Response of Colonic Segments to Tryptamine
Not available on PMC !

Example 3

Preparations of full-thickness colonic segments (˜1.5 cm) were allowed to equilibrate in 37° C. Kreb's-jacketed organ baths with their distal ends opening to a pressure transducer and maintained under basal pressure of 5-cm column of vehicle (RL). The proximal end was closed during pressure recordings but opened to allow luminal infusion of vehicle or tryptamine in solution (100 μM, 1 mM and 3 mM; 10 minutes per treatment; n=5-7 mice).

Contractile frequency was not significantly different comparing tryptamine treatments with vehicle controls; however, there was a trend toward increased frequency in segments treated with luminal 1 mM tryptamine compared to controls (5.9±0.8 vs 4.1±0.6; P=0.15). Mean contractile amplitude and contractile magnitude, as measured by area under the curve, were also not significantly different between control (vehicle alone) and any of the tryptamine concentrations examined. Contractile duration, measured at half amplitude, was not significantly different between vehicle controls and any of the luminal tryptamine treatments.

US11878002B2. Methods and materials for using Ruminococcus gnavus or Clostridium sporogenes to treat gastrointestinal disorders (2024-01-23). Mayo Foundation for Medical Education and Research [US], The Regents of the University of California [US]. Inventors: Purna C. Kashyap [US], Michael Fischbach [US], Brianna B. Williams [US].
Full text: Click here
Patent 2024
Bath Colon Mus Muscle Contraction Phenobarbital Pressure Transducers, Pressure Tryptamines
5
5HTR4 Receptor Role in Tryptamine Signaling
Not available on PMC !

Example 5

The response to 5-hydroxytryptophan (5HT; 0.003-300 μM) on the mucosal or serosal side and tryptamine (0.003-3000 μM) on the mucosal or serosal side was determined in segments of proximal colon, stripped of external muscle layers, from both 5HTR4 KO and WT mice.

Colon segments from 5HTR4 KO mice displayed decreased responsiveness to serosal serotonin and no response to mucosal serotonin when compared with colon segments from WT mice. Cumulative concentration response curves induced by serosal tryptamine were significantly different between 5HTR WT (Emax: 110±17 μA/cm2; n=6-7) and KO mice (no response). While Δlsc did not reach maximum response following mucosal application of 3000 μM tryptamine, responses were seen in 5HTR4 WT mice (99.5±30.7 n=5) while no response was elicited in 5HTR4 KO (FIG. 18).

These results show that tryptamine acts as a 5HTR4 mimetic with effects on gut epithelial function independent of serotonin.

US11878002B2. Methods and materials for using Ruminococcus gnavus or Clostridium sporogenes to treat gastrointestinal disorders (2024-01-23). Mayo Foundation for Medical Education and Research [US], The Regents of the University of California [US]. Inventors: Purna C. Kashyap [US], Michael Fischbach [US], Brianna B. Williams [US].
Full text: Click here
Patent 2024
5-Hydroxytryptophan Bladder Detrusor Muscle Colon Mice, Knockout Mucous Membrane Mus Serotonin Serous Membrane SERPINA3 protein, human tryptamine Vision

Top products related to «Colon»

1
Fetal bovine serum (fbs) by Thermo Fisher Scientific
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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.
2
Trizol reagent by Thermo Fisher Scientific
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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.
3
Hct116 by American Type Culture Collection
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The HCT116 cell line is a human colorectal carcinoma cell line that is widely used in research. It is a commonly used model system for studying various aspects of cancer biology and drug development.
4
Dextran sulfate sodium (dss) by MP Biomedicals
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The DSS is a laboratory instrument designed for the separation and analysis of molecules and particles in complex samples. It utilizes a specialized technique called differential sedimentation to achieve precise separation and characterization of the components within a sample. The core function of the DSS is to provide accurate and reliable data on the size, distribution, and concentration of the analytes present, without interpretation or extrapolation on its intended use.
5
Sw480 by American Type Culture Collection
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The SW480 is a laboratory equipment product from the American Type Culture Collection (ATCC). It is a colorectal adenocarcinoma cell line that can be used for various cell-based research applications.
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Dulbecco modified eagle medium (dmem) by Thermo Fisher Scientific
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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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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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Rpmi 1640 medium by Thermo Fisher Scientific
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RPMI 1640 medium is a commonly used cell culture medium developed at Roswell Park Memorial Institute. It is a balanced salt solution that provides essential nutrients, vitamins, and amino acids to support the growth and maintenance of a variety of cell types in vitro.
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Sw620 by American Type Culture Collection
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The SW620 is a type of cell line maintained by the American Type Culture Collection (ATCC). It is a human colorectal adenocarcinoma cell line derived from a metastatic site. The SW620 cell line is commonly used in cancer research and drug development studies.
10
Trizol by Thermo Fisher Scientific
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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.

More about "Colon"

The colon, also known as the large intestine, is a vital component of the human digestive system.
This long, tubular organ plays a crucial role in the final stages of waste elimination, water absorption, electrolyte balance, and stool formation.
Maintaining optimal colon health is essential for overall gastrointestinal wellbeing.
Conditions affecting the colon, such as colorectal cancer, inflammatory bowel diseases (e.g., ulcerative colitis, Crohn's disease), and diverticulitis, can have serious health consequences.
Researchers studying colon health and related disorders often utilize various tools and techniques, including cell lines like HCT116 and SW480 (colorectal cancer cell lines), DMEM and RPMI 1640 media for cell culture, and reagents like TRIzol and RNeasy Mini Kit for RNA extraction and analysis.
The SW620 cell line, derived from a metastatic colorectal tumor, is also commonly used in colon cancer research.
Animal models, such as the dextran sulfate sodium (DSS)-induced colitis model, are often employed to study the pathogenesis and potential treatments for inflammatory bowel diseases.
These research efforts aim to develop effective protocols and products to optimize colon health and address various gastrointestinal conditions.
PubCompare.ai, an innovative AI-powered platform, can assist researchers in locating relevant protocols from literature, preprints, and patents, and leverage AI-driven comparisons to identify the most suitable approaches for their research needs.
This tool helps ensure reproducibility and accruacy in colon health-related studies, ultimately contributing to the advancement of knowledge and the improvement of patient outcomes.