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> Anatomy > Body Substance > Mucus

Mucus

Mucus is a viscous, slippery secretion produced by specialized cells in various tissues, including the respiratory, gastrointestinal, and urogenital tracts.
It serves as a protective barrier, trapping pathogens, allergens, and other particles, while also facilitating lubrication and moisture retention.
Mucus is composed of water, glycoproteins, lipids, and various other compounds, and its composition and properties can vary depending on the specific physiological context.
Alterations in mucus production, viscosity, or clearance can contribute to the pathogenesis of numerous diseases, such as cystic fibrosis, chronic obstructive pulmonary disease, and inflammatory bowel disorders.
Reseach into the mechanisms and functions of mucus is crucial for developing effective therapies and improving patient outcomes.

Most cited protocols related to «Mucus»

1
Validating PICRUSt's Metagenome Prediction Accuracy
Several microbiome studies that included both 16S sequencing and WGS metagenome sequencing for the same samples were used to test the accuracy of PICRUSt. These included 530 paired human microbiome samples22 (link), 39 paired mammal gut samples24 (link), 14 paired soil samples34 (link), 10 paired hypersaline microbial mats23 (link), 24 (link) and two even/staggered synthetic mock communities from the HMP33 (link). We additionally used PICRUSt to make predictions on three 16S-only microbiome studies, specifically 6,431 HMP samples (http://hmpdacc.org/HMQCP), 993 vaginal time course samples43 and 335 coral mucus samples(http://www.microbio.me/qiime/; Study ID 1854).
For 16S data, PICRUSt-compatible OTU tables were constructed using the closed-reference OTU picking protocol in QIIME 1.5.0-dev (pick_reference_otus_through_otu_table.py) against Greengenes+IMG using ‘uclust’48 (link). For paired metagenomes, WGS reads were annotated to KOs using v0.98 of HUMAnN30 (link). Expected KO counts for the HMP mock communities were obtained by multiplying the mixing proportions of community members by the annotated KO counts of their respective reference genomes in IMG. PICRUSt was used to predict the metagenomes using the 16S-based OTU tables, and predictions were compared to the annotated WGS metagenome across all KOs using Spearman rank correlation. In addition, KOs were mapped to KEGG Module abundances, following the conjugative normal form as implemented in HUMAnN script “pathab.py” for the HMP and vaginal datasets to compare modules and pathways. Bray-Curtis distances (for Beta-diversity comparison between OTU or PICRUSt KO abundances across samples) were calculated using as implemented in the QIIME “beta_diversity.py” script. The PCA plot and identification of KEGG modules with significant mean proportion differences for both the HMP and vaginal datasets was created using STAMP v2.036 (link).
The Nearest Sequenced Taxon Index (NSTI) was developed as an evaluation measure describing the novelty of organisms within an OTU table with respect to previously sequenced genomes. For every OTU in a sample, the sum of branch lengths between that OTU in the Greengenes tree to the nearest tip in the tree with a sequenced genome is weighted by the relative abundance of that OTU. All OTU scores are then summed to give a single NSTI value per microbial community sample. PICRUSt calculates NSTI values for every sample in the given OTU table, and we compared NSTI scores and PICRUSt accuracies for all of the metagenome validation datasets.
In the metagenome rarefaction analysis (Fig. 4), a given number of counts were randomly selected from either the collection of microbial OTUs for each sample (i.e. the 16S rRNA OTU table) or the collection of sequenced genes in that sample using the multiple_rarefactions.py script in QIIME 1.5.0-dev29 (link). To estimate the number of raw reads at which PICRUSt outperforms metagenomic sequencing the annotated shotgun reads were transformed to total sequenced reads by dividing by the mean annotation rates from the original manuscript (17.3%), while 16S rRNA reads were transformed using the success rate for closed-reference OTU picking at a 97% 16S rRNA identity threshold (68.9%). Both the subsampled metagenome and the PICRUSt predictions from the subsampled OTU table were compared for accuracy using Spearman rank correlation versus the non-subsampled metagenome.
Langille M.G., Zaneveld J., Caporaso J.G., McDonald D., Knights D., Reyes J.A., Clemente J.C., Burkepile D.E., Vega Thurber R.L., Knight R., Beiko R.G, & Huttenhower C. (2013). Predictive functional profiling of microbial communities using 16S rRNA marker gene sequences. Nature biotechnology, 31(9), 814-821.
Publication 2013
Coral Genes Genome Human Microbiome Mammals Metagenome Microbial Community Microbiome Mucus RNA, Ribosomal, 16S Trees Vagina
2
Transwell Culture of Human Intestinal Spheroids
Transwell culture methods were adapted from our recently published method for mouse colonic spheroids[19 ]. Human spheroids (~1 well of a 24-well plate per Transwell) were dissociated, strained through a 40-μm filter, seeded onto Transwell membranes (Fisher Scientific, CoStar 3470) coated with 0.1% gelatin (earlier experiments) or Matrigel diluted 1:40 in PBS (later experiments) and provided 5% L-WRN CM (10 μM Y-27632 was included O/N and then removed during daily media changes). TER measurements[19 ] and mucus layer analyses[21 (link)] were performed as previously described. Z-stack images (1.1-μm, with an optimal interval of 0.55-μm) were generated with a Zeiss LSM510 Meta laser scanning confocal microscope (Carl Zeiss Inc., Thornwood, NY) equipped with Argon (Ex. 488 Em. BP 505–530) and HeNe1 (Ex. 543 Em. BP 560–615) lasers, a 63X, 1.4 numerical aperture Zeiss Plan Apochromat oil objective and LSM software. Rectal and ileal spheroid lines were infected with recombinant lentiviruses expressing an enhanced green fluorescent protein (EGFP) under the hPGK promoter [7 (link), 8 (link)] using a described protocol[8 (link)].
VanDussen K.L., Marinshaw J.M., Shaikh N., Miyoshi H., Moon C., Tarr P.I., Ciorba M.A, & Stappenbeck T.S. (2014). Development of an enhanced human gastrointestinal epithelial culture system to facilitate patient-based assays. Gut, 64(6), 911-920.
Publication 2014
Argon Colon Culture Techniques enhanced green fluorescent protein Gelatins Homo sapiens Ileum Lentivirus matrigel Microscopy, Confocal Mucus Mus Rectum Tissue, Membrane Y 27632
3
Quantification of Tumor Stroma Ratio
H&E stained tissue sections from the primary tumor of 4 μm thickness are analyzed by conventional microscopy. Areas appearing to have the highest amount of stroma are selected using the × 2.5 or the × 5 lens. Hereafter, an area where both tumor and stromal tissue are present within this vision-site is selected using a × 10 objective. Tumor cells are to be present at all borders of the selected image field (Fig. 1). The amount of stroma tissue is estimated per 10% increment (10, 20, 30%, etc.) per image field. For statistical analysis, stromal ratio groups are divided in stroma-high and stroma-low groups. Stroma-high is defined as > 50% stromal area, and stroma-low as ≤ 50% stromal area in the histological section, as determined a priori to have maximum discriminative power [4 (link)]. Even if there is only one image field with a stroma-high score, this image field is decisive.

Examples of a stroma-low (a) and stroma-high (b) colon carcinoma, which meet the criteria for the presence of vital tumor cells on all four sides of the field of vision (arrows) and are thus correct for scoring. When tumor cells are only present at two (c) or three (d) sides of the field of vision (mucus is not included in estimating TSR), these areas are not suitable for scoring (Images displaying the microscopic view, all images × 100 magnification)

When scoring the TSR, misinterpretations while estimating the percentage of stroma can occur due to general issues, as well as based on specific histological issues. Both are discussed below.
van Pelt G.W., Kjær-Frifeldt S., van Krieken J.H., Al Dieri R., Morreau H., Tollenaar R.A., Sørensen F.B, & Mesker W.E. (2018). Scoring the tumor-stroma ratio in colon cancer: procedure and recommendations. Virchows Archiv, 473(4), 405-412.
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Publication 2018
Cancer of Colon Cells Discrimination, Psychology Lens, Crystalline Microscopy Mucus Neoplasms Tissues Vision
4
Planarian Regeneration Protocol
Note: Unless noted at particular steps, intact planarians may be nutated/rocked while early regenerating fragments (up to day 2) should be slowly rocked.
Day 1 (kill, remove mucus, fix, reduce/permeabilize, dehydrate, bleach)
Notes:
Notes:
Notes:
When ready (bleach)
Note: This step removes pigment from the animal to help with visualization of the signal
Note: After this, specimens were then returned to -20°C or used immediately
Day 2 (rehydrate, proteinase K, post-fix, hybridization)
Pearson B.J., Eisenhoffer G.T., Gurley K.A., Rink J.C., Miller D.E, & Alvarado A.S. (2009). A Formaldehyde-based Whole-Mount In Situ Hybridization Method for Planarians. Developmental dynamics : an official publication of the American Association of Anatomists, 238(2), 443-450.
Publication 2009
Animals Crossbreeding Endopeptidase K Mucus Pigmentation Planarians
5
Twin-SHIME: Simulating Gut Microbiome
The SHIME is a dynamic in vitro model of the human intestinal tract, composed of five double‐jacketed vessels, respectively simulating the stomach, small intestine and the three colon regions. In this experiment, only the first colon compartment was used (Fig. 5). Two SHIME units were used in parallel ('Twin‐SHIME') in order to obtain identical environmental conditions and identical microbial composition and activities for both units (Van den Abbeele et al., 2010 (link)). Whereas the first unit consisted of the conventional set‐up that only harbours luminal microbes (= luminal SHIME or L‐SHIME), the second unit was modified by incorporating a mucosal environment (= mucosal SHIME or M‐SHIME). In order to achieve a representative mucosal surface in the M‐SHIME, 100 mucin‐covered microcosms were added per 500 ml luminal suspension. The microcosms (length = 7 mm, diameter = 9 mm, total surface area = 800 m2/m3, AnoxKaldnes K1 carrier, AnoxKaldnes AB, Lund, Sweden) were coated by submerging them in mucin agar. To simulate the renewal of the mucus layer, half of the mucin‐covered microcosms were replaced daily by sterile ones.
The ascending compartment (500 ml) from both SHIME units was inoculated with 40 ml of a 1:5 dilution of fresh stools provided by a healthy human volunteer (25 years) who had no history of antibiotic treatment 6 months before the study. Inoculum preparation was done as previously described by Possemiers and colleagues (2004 (link)). Three times per day, 140 ml SHIME feed and 60 ml pancreatic juice were added to the stomach and small intestine respectively.
Van den Abbeele P., Roos S., Eeckhaut V., MacKenzie D.A., Derde M., Verstraete W., Marzorati M., Possemiers S., Vanhoecke B., Van Immerseel F, & Van de Wiele T. (2011). Incorporating a mucosal environment in a dynamic gut model results in a more representative colonization by lactobacilli. Microbial biotechnology, 5(1), 106-115.
Publication 2011
Agar Antibiotics Blood Vessel Colon Feces Healthy Volunteers Homo sapiens Intestines Intestines, Small Mucins Mucous Membrane Mucus Pancreatic Juice Sterility, Reproductive Stomach Technique, Dilution Twins

Most recents protocols related to «Mucus»

1
Microbiome Composition Analysis with ANCOM-BC
The program Analysis of Compositions of Microbiomes with Bias Correction (ANCOM_BC) was used to identify differentially abundant microbial taxa [75 ]. ANCOM_BC was used with the global test option and the results were considered significant if the false discovery rate adjusted p-value (Padj) was <0.001 and if the W statistic was >90. Field-sourced AH samples were tested for differential abundance among zones (vulnerable, endemic, and epidemic), and SCTLD-susceptible coral samples (without Acropora spp.) were evaluated for differences in disease state (AH, DU, and DL). For SCTLD-susceptible corals, the data were parsed by the three coral compartments (mucus, tissue slurry, and tissue slurry skeleton). ANCOM_BC analyses were run for each compartment due to the relatively low sample size of tissue slurry skeleton samples compared to the two other compartment types. The taxa were further evaluated if they had a log-fold change between −1.5< and >1.5. The ASVs that were significantly enriched were used to identify the relative abundance of the ASVs across sample types and zones. In addition, those enriched only in either DU or DL were used to identify the presence or absence of each ASV in coral species and study per biome. The same ANCOM_BC analysis was repeated without MCAV and OFAV to evaluate if the two dominant coral species in our meta-analysis were driving the enriched bacteria.
Rosales S.M., Huebner L.K., Evans J.S., Apprill A., Baker A.C., Becker C.C., Bellantuono A.J., Brandt M.E., Clark A.S., del Campo J., Dennison C.E., Eaton K.R., Huntley N.E., Kellogg C.A., Medina M., Meyer J.L., Muller E.M., Rodriguez-Lanetty M., Salerno J.L., Schill W.B., Shilling E.N., Stewart J.M, & Voss J.D. (2023). A meta-analysis of the stony coral tissue loss disease microbiome finds key bacteria in unaffected and lesion tissue in diseased colonies. ISME Communications, 3, 19.
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Publication 2023
Bacteria Biome Coral Epidemics Microbiome Mucus Skeleton Tissues
2
Microbial Community Dynamics in Coral Ecology
The data were imported into R v4.0.5 and converted into a phyloseq object [70 ]. ASVs were removed if they were present less than four times in 20% of the samples. The filtered count table was transformed using centered log-ratio (CLR) with the package microbiome [71 ]. Beta-diversity was analyzed with the package VEGAN 2.5.4 [72 (link)] and the filtered CLR-transformed table. The function vegdist was used to generate dissimilarity indices with a Euclidean distance. To identify significant differences among groups, a Permutational Multivariate Analysis of Variance (PERMANOVA) was used with the function adonis2 with 999 permutations, using a Euclidean distance. The function betadisper was used to calculate group dispersion, which was then tested for significance with the function Permutest.
Differences in beta-diversity for field samples were evaluated in apparently healthy (AH) corals across three zones (vulnerable, endemic, and epidemic). In addition, pairwise group comparison was assessed from betadisper output using the Tukey’s HSD function. The PERMANOVA output was also tested for pairwise comparisons with the function pairwise.adonis and adjusted with a Bonferroni correction [73 ]. Furthermore, all samples (including Acropora spp., sediment, and seawater) were also evaluated for beta-diversity differences in primers, year of collection, biome (field and aquaria), studies, coral species, and sample type (seawater, mucus, tissue slurry, tissue slurry and skeleton, and sediment). These factors were also correlated to principal components (PCs) using the R package PCAtools 2.5.15, and the functions pca and eigencorplot were used to remove the lowest 10% of the variance and to correlate the data and test for significance, respectively.
SCTLD-susceptible coral samples (i.e., without Acropora spp., sediment, and seawater) were also evaluated for beta-diversity. Both biomes (aquaria or field) were examined together and also separately. The matrices were generated with QIIME2-2021.11 with the plugin DEICODE, which runs a robust Aitchison Distance—a method that is not influenced by zeros in the data [74 ]. Pairwise comparisons of dispersion and differences in microbial composition between groups were evaluated using the QIIME2-2021.11 diversity beta-group-significance function using either the permdisp or PERMANOVA method, respectively. DEICODE was also applied to the data without the two most prevalent corals species, Orbicella faveolata (OFAV) and Montastraea cavernosa (MCAV), to see if the same pattern was evident in disease states with and without these coral species.
Rosales S.M., Huebner L.K., Evans J.S., Apprill A., Baker A.C., Becker C.C., Bellantuono A.J., Brandt M.E., Clark A.S., del Campo J., Dennison C.E., Eaton K.R., Huntley N.E., Kellogg C.A., Medina M., Meyer J.L., Muller E.M., Rodriguez-Lanetty M., Salerno J.L., Schill W.B., Shilling E.N., Stewart J.M, & Voss J.D. (2023). A meta-analysis of the stony coral tissue loss disease microbiome finds key bacteria in unaffected and lesion tissue in diseased colonies. ISME Communications, 3, 19.
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Publication 2023
Adonis asunaprevir Biome Coral Epidemics Microbiome Mucus Oligonucleotide Primers Skeleton Tissues Vegan
3
Early Syphilis Screening in HIV Patients
Following informed consent, a targeted physical examination was performed by trained study clinicians (operators 2–5, see below) to identify signs of early syphilis (i.e. rash, ulcers, mucous patches or condyloma lata). An electronic case report form (eCRF) was used to collect demographic (birth date, sex assigned at birth, current gender, ethnicity, area of residency) and clinical information (history of previous syphilis, date of HIV diagnosis and current antiretroviral therapy) via face-to-face or telephonic survey according to the participant time availability. Date and results of the closest (up to 134 days before the enrolment date) viral load (copies/mm3) and CD4 cell count (cells/mm3) were collected from laboratory results in the corresponding electronic medical record. In clinic A, as part of routine care all patients with newly diagnosed HIV were tested using p24 HIV antigen and CD4 rapid tests. Additionally, patients who had been lost to follow-up and were re-engaged in the HIV care program were also tested for CD4 rapid test. Two samples were obtained from each participant: capillary blood (CB) from finger prick and serum from venous blood. CB was used for RDTs performed at point-of-care and serum for both RDTs and reference tests performed at a reference laboratory.
García Luna J.A., Romero-Rosas N., Silva Peña S.A., Oviedo Sarmiento O.J., Galindo Orrego X., Lenis Quintero W., Perea L.C., Martínez Buitrago E., Osorio L., Salazar J.C., Smith A.D, & Alexander N. (2023). Diagnostic performance of two rapid tests for syphilis screening in people living with HIV in Cali, Colombia. PLOS ONE, 18(3), e0282492.
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Publication 2023
Antigens BLOOD Capillaries CD4+ Cell Counts Cells Childbirth Condylomata Acuminata Ethnicity Exanthema Face Fingers Gender HIV Core Protein p24 latrunculin A Mucus Patients Physical Examination Point-of-Care Systems Residency Rhabdoid Tumor Serum Syphilis Therapeutics Ulcer Veins
4
Syphilis Diagnostic Protocol with RPR
Rapid Plasma Reagin (RPR) (Human Gesellschaft für Biochemica und Diagnostica mbH, Wiesbaden, Germany) was performed using 100 μL of serum. All reactive RPR results were followed by serial serum dilutions to obtain the RPR titer. Participants who were a) positive by either TPHA or ELISA, and b) non-reactive by RPR were considered as no active syphilis. Those with positive TPHA or ELISA and reactive RPR results were also considered as having no active syphilis if RPR titers had a fourfold decrease compared to a previous test, or if they had received syphilis treatment within the last 6 months. Those with positive TPHA or ELISA and reactive RPR results were considered as having active syphilis if signs of primary (chancre on genitals, oral cavity, or perianal region) or secondary syphilis (rash, condyloma lata or mucous patches) were present or if they had a fourfold increase in RPR titers compared to previous results. Serofast status was inferred for those subjects without a fourfold decrease in RPR titers six months after treatment [6 (link)].
García Luna J.A., Romero-Rosas N., Silva Peña S.A., Oviedo Sarmiento O.J., Galindo Orrego X., Lenis Quintero W., Perea L.C., Martínez Buitrago E., Osorio L., Salazar J.C., Smith A.D, & Alexander N. (2023). Diagnostic performance of two rapid tests for syphilis screening in people living with HIV in Cali, Colombia. PLOS ONE, 18(3), e0282492.
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Publication 2023
Chancre Condylomata Acuminata Enzyme-Linked Immunosorbent Assay Exanthema Genitalia Homo sapiens latrunculin A Mucus Oral Cavity Plasma Reagins Serum Syphilis Syphilis, secondary Technique, Dilution
5
Ureteral Stent Evaluation in Porcine Model
This study was conducted between October 2021 and July 2022. Six Yorkshire female pigs (aged 20 weeks, weighing 30–40 kg) were sequentially housed according to the experimental schedule. A preliminary experiment was conducted on one of the six animals to optimize the experiment. In the preliminary experiment, encrustation occurred 2 weeks after ureteral stenting, which was subsequently considered the optimal experimental period. After one week of stabilization, ureteral stenting was performed using a ureteroscope under general anesthesia. A bare stent was inserted on one side and the stent with the inner surface modification was inserted on the other side. Each animal was kept in an individual cage and provided free purified drinking water. The experimental pigs (Biopia) were fed once daily at 2% of their body weight. The pigs were administered 0.8% ethylene glycol, with a maximum daily intake of 40 mL [11 (link)]. The room temperature was maintained at 22℃±2℃, and the humidity was maintained at 40%–60%. The light source was switched on from 7 am to 7 pm in both the control and experimental groups, and the light source was blocked from 7 pm to 7 am. Two weeks after inserting the ureteral stents, laparotomies were performed to harvest the ureteral stents; thereafter, the pigs were euthanized.
Changes in the inner surface were evaluated as the primary endpoint. The harvested ureteral stents were dried at room temperature for two days, following which they were cut, and the inner surface was grossly evaluated. Scanning electron microscopy (SEM) and energy-dispersive X-ray spectrometry (EDS) (Field-Emission Scanning Electronic Microscopy, AURIGATm, Carl Zeiss Co.) were used for imaging. In addition, if encrustation was observed, the components were analyzed using Fourier-transform infrared spectroscopy (FT-IR) (System 2000 FT-IR, Perkin Elmer). Stone materials and materials judged to contain mucus were collected and conservatively analyzed.
Urine samples were cultured before and after stenting for safety assessment. The porcine models were numbered 1 to 5 and classified into bare stent (B) and inner surface-modified stent (M) groups. In the bare stent, we used polyurethane (PU) ureteral stents (M. I. Tech Co., Ltd.), which is approved for use by the Korean Ministry of Food and Drug Safety. Any safety issues that occurred, were considered to be related to the stent modifications.
Chung J.H., Baek N., Lim H., Seo C., Cho Y.K., Jung D, & Han D.H. (2023). Inner surface modification of polyurethane ureteral stents using plasma-enhanced chemical vapor deposition to improve the resistance to encrustation in a pig model. Investigative and Clinical Urology, 64(2), 175-181.
Publication 2023
Animals Body Weight Calculi Energy Dispersive X-Ray Spectrometry Food General Anesthesia Glycol, Ethylene Humidity Koreans Laparotomy Light Mucus Pharmaceutical Preparations Pigs Polyurethanes Safety Scanning Electron Microscopy Spectroscopy, Fourier Transform Infrared Stents Ureter Ureteroscopes Urine Woman

Top products related to «Mucus»

1
Dithiothreitol (dtt) by Merck Group
Sourced in United States, Germany, United Kingdom, Italy, Sao Tome and Principe, France, China, Switzerland, Macao, Spain, Australia, Canada, Belgium, Sweden, Brazil, Austria, Israel, Japan, New Zealand, Poland, Bulgaria
Dithiothreitol (DTT) is a reducing agent commonly used in biochemical and molecular biology applications. It is a small, water-soluble compound that helps maintain reducing conditions and prevent oxidation of sulfhydryl groups in proteins and other biomolecules.
2
Fetal bovine serum (fbs) by Thermo Fisher Scientific
Sourced in United States, China, United Kingdom, Germany, Australia, Japan, Canada, Italy, France, Switzerland, New Zealand, Brazil, Belgium, India, Spain, Israel, Austria, Poland, Ireland, Sweden, Macao, Netherlands, Denmark, Cameroon, Singapore, Portugal, Argentina, Holy See (Vatican City State), Morocco, Uruguay, Mexico, Thailand, Sao Tome and Principe, Hungary, Panama, Hong Kong, Norway, United Arab Emirates, Czechia, Russian Federation, Chile, Moldova, Republic of, Gabon, Palestine, State of, Saudi Arabia, Senegal
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.
3
Dnase 1 by Merck Group
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DNase I is a laboratory enzyme that functions to degrade DNA molecules. It catalyzes the hydrolytic cleavage of phosphodiester linkages in the DNA backbone, effectively breaking down DNA strands.
4
Dnase 1 by Roche
Sourced in United States, Switzerland, Germany, Japan, United Kingdom, France, Canada, Italy, Macao, China, Australia, Belgium, Israel, Sweden, Spain, Austria
DNase I is a lab equipment product that serves as an enzyme used for cleaving DNA molecules. It functions by catalyzing the hydrolytic cleavage of phosphodiester bonds in the DNA backbone, effectively breaking down DNA strands.
5
Ethylene diamine tetraacetic acid (edta) by Merck Group
Sourced in United States, Germany, United Kingdom, France, Italy, Canada, Switzerland, India, Sao Tome and Principe, Macao, Poland, Australia, China, Spain, Ireland, Japan, Israel, Brazil, Belgium, Sweden, Denmark, Singapore, Netherlands, Austria
EDTA is a chemical compound commonly used as a laboratory reagent. Its primary function is as a chelating agent, capable of binding to metal ions and forming stable complexes. EDTA is widely used in various analytical and experimental procedures to control the availability of metal ions in solutions.
6
Collagenase 8 by Merck Group
Sourced in United States, Germany, Switzerland, Israel
Collagenase VIII is a laboratory enzyme used for the digestion and dissociation of collagen-rich tissues. It is effective in breaking down the extracellular matrix, facilitating the isolation and extraction of cells from various sources.
7
Alcian blue by Merck Group
Sourced in United States, Germany, United Kingdom, Sao Tome and Principe, Japan, China, Belgium, Italy, France, Australia
Alcian blue is a staining dye used in histology and microscopy to detect the presence of acidic polysaccharides, such as glycosaminoglycans, in biological samples. It has a high affinity for sulfated and carboxylated molecules, enabling the visualization of specific tissue structures and cellular components.
8
Percoll by GE Healthcare
Sourced in United States, Sweden, United Kingdom, Germany, Canada, Japan, Denmark, Switzerland, Italy, Australia, Spain, Norway, Belgium, Macao
Percoll is a colloidal silica-based medium used for cell separation and gradient centrifugation. It is designed to provide a density gradient for the isolation and purification of cells, organelles, and other biological particles.
9
Image pro plus 6 by Media Cybernetics
Sourced in United States, Japan, Germany, United Kingdom, China, Hungary, Singapore, Canada, Switzerland
Image-Pro Plus 6.0 is a comprehensive image analysis software package designed for scientific and industrial applications. It provides a wide range of tools for image capture, enhancement, measurement, analysis, and reporting.
10
Axiovision 4 by Zeiss
Sourced in Germany, United States, Japan, United Kingdom, Canada, France, Australia, Italy, Belgium
AxioVision 4.8 is a software package for microscope image acquisition, processing, and analysis developed by Carl Zeiss Microscopy. It provides a platform for controlling various Zeiss microscope models and capturing high-quality digital images. The software supports a range of imaging techniques, including fluorescence, brightfield, and phase contrast.

More about "Mucus"

Mucus, a viscous and slippery secretion, serves as a crucial protective barrier in the respiratory, gastrointestinal, and urogenital tracts.
It traps pathogens, allergens, and other particles, while facilitating lubrication and moisture retention.
The composition of mucus, which includes water, glycoproteins, lipids, and various other compounds, can vary depending on the physiological context.
Alterations in mucus production, viscosity, or clearance can contribute to the development of numerous diseases, such as cystic fibrosis, chronic obstructive pulmonary disease (COPD), and inflammatory bowel disorders.
Understanding the mechanisms and functions of mucus is crucial for developing effective therapies and improving patient outcomes.
Researchers often use techniques like Dithiothreitol (DTT), Fetal Bovine Serum (FBS), DNase I, EDTA, and Collagenase VIII to study mucus.
Staining methods, such as Alcian blue, can be employed to visualize and analyze mucus samples.
Techniques like Percoll density gradient centrifugation and image analysis software, such as Image-Pro Plus 6.0 and AxioVision 4.8, can also be utilized to enhance the study of mucus properties and functions.
Optimization of mucus research is crucial for advancing our understanding of this critical biological secretion and its role in health and disease.
By leveraging the latest tools and techniques, researchers can enhance the reproducibility and accuracy of their findings, leading to more effective therapies and improved patient outcomes.