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Tablet

Tablets are a solid dosage form of medication that are designed for oral administration.
They typically consist of an active pharmaceutical ingredient(s) compressed or molded into a solid form, along with various excipients such as binders, disintegrants, and lubricants.
Tablets offer several advantages, including accurate dosing, ease of administration, and improved drug stability.
They are a commonly used and versatile dosage form across many therapeutic areas.
Reasearch into tablet formulation, manufacturing, and quality control is essential for developing safe and effective oral medications.

Most cited protocols related to «Tablet»

1
Developing GEPIA: A Comprehensive Cancer Gene Expression Profiling Tool
Cited 2360 times
The GEPIA website is freely available to all users. It is built by the HTML5 and JavaScript libraries, including jQuery (http://jquery.com), Bootstrap (http://getbootstrap.com/) for the client-side user interface. The server-side and interactive data processing are carried out by PHP scripts (version 7.0.13). The web site automatically adjusts the look and feel according to different browsers and devices, ranging from desktop computers to tablets and smart phones. There is no login requirement for accessing any features in GEPIA.
To solve the imbalance between the tumor and normal data which can cause inefficiency in various differential analyses, we download the TCGA and GTEx gene expression data that are re-computed from raw RNA-Seq data by the UCSC Xena project based on a uniform pipeline (Figure 1). We consult with medical experts to determine the most appropriate sample grouping for tumor-normal comparisons. The datasets are stored in a MySQL relational database (version 5.7.17).
The GEPIA web server features are divided into seven major tabs: General, Differential Genes, Expression DIY, Survival, Similar Genes, Correlation and PCA, which provides key interactive functions corresponding to differential expression analysis, customizable profiling plotting, patient survival analysis, similar gene detection, correlation analysis and dimensionality reduction analysis (Figure 2).
All plotting features in GEPIA are developed using R (version 3.3.2) and Perl (version 5.22.1) programs. The GEPIA outputs consist of plots and tables. Static visualizations are rendered as Portable Document Format (PDF), Scalable Vector Graphics (SVG) and Portable Network Graphics (PNG) images. The rotatable 3D plots are built by the plotly.js library (https://plot.ly/). Tables are generated by the DataTables (https://www.datatables.net/) JavaScript library, allowing for data querying and selection.
Tang Z., Li C., Kang B., Gao G., Li C, & Zhang Z. (2017). GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses. Nucleic Acids Research, 45(Web Server issue), W98-W102.
Publication 2017
cDNA Library Cloning Vectors Feelings Gene Expression Genes Medical Devices Neoplasms Patients RNA-Seq
2
Mitochondrial Genome Assembly and Analysis
Cited 113 times
To evaluate the MITObim results, we performed direct mapping assemblies to the correct reference genomes using MIRA v3.4.1.1 (35 ). All mapping results were visualized and quality checked using the program Tablet (37 (link)). De novo assemblies on the mitochondrial readpools identified by MITObim were performed by MIRA v3.4.1.1 (35 ), Velvet v1.2.07 (25 (link)) and ABySS v1.3.3 (26 (link)) to further verify the results obtained by MITObim. All obtained consensus sequences were aligned to the respective reference using Clustal W (38 (link)). Any 5′ and/or 3′ overhangs in respect to the reference were removed and/or displaced in MEGA 5 (39 (link)) after verification of correct circularity. Resulting sequences were subjected to Blast searches (40 (link)) against GenBank to confirm identity and subsequently compared with each other using Blast (41 (link)). The MITOS web server (42 ) was used for automated annotation of the obtained mitochondrial genomes.
Scripts from the software package khmer (43 (link)) were used to calculate k-mer frequencies (20 mer) for (i) the entire data sets ‘thy’ and ‘der’ and (ii) for the parasite mitochondrial readpools identified by MITObim, to estimate the mitochondrial copy number relative to the number of nuclear copies based on the relative k-mer frequency distributions. The parasites’ nuclear genome size was estimated based on the k-mer frequency distributions of the entire data sets, respectively, as demonstrated in previous studies (44 ,45 (link)).
Hahn C., Bachmann L, & Chevreux B. (2013). Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach. Nucleic Acids Research, 41(13), e129.
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Publication 2013
1-(propoxymethyl)maleimide Consensus Sequence Genome, Mitochondrial Mitochondrial Inheritance Parasites Tablet
3
Fractionation of Breast Epithelial Cell Proteome
Cited 65 times
Human breast epithelial cells (MCF10A) were transfected with a pQCXIH vector and were cultured in DMEM/F12 (Invitrogen, Carlsbad, CA) supplemented with 5% horse serum (Invitrogen), 20 ng/mL EGF, 0.5 μg/mL hydro-cortisone, 100 ng/mL cholera toxin, 10 μg/mL insulin, and 50 μg/mL penicillin/streptomycin until 70–80% confluence was reached. The cells were then lysed in a buffer containing 8 M urea, 2.5 mM sodium pyrophosphate, 1 mM β-glycerophosphate, 50 mM ammonium bicarbonate, one-third tablet of protease inhibitor, and 2 mM sodium ortho-vanadate. Proteins were denatured, reduced, and alkylated after which tryptic digestions were performed at an enzyme/substrate ratio of 1:50. For method comparison between SCX and RP, digested peptides were cleaned by flowing through a 1 mL solid-phase extraction C18 column (Discovery DSC-18, SUPELCO, Bellefonte, PA). Samples were concentrated using a Speed-Vac SC 250 Express (Thermo Savant, Holbrook, NY) and stored at −80°C until time for analysis. A 300.0 μg desalted peptide sample was used for each SCX, low-pH RPLC, and high-pH RPLC fractionation. A 300.0 μg nondesalted protein digest was used to evaluate the potential of high-pH approach for desalting.
Wang Y., Yang F., Gritsenko M.A., Wang Y., Clauss T., Liu T., Shen Y., Monroe M.E., Lopez-Ferrer D., Reno T., Moore R.J., Klemke R.L., Camp DG I.I, & Smith R.D. (2011). Reversed-phase chromatography with multiple fraction concatenation strategy for proteome profiling of human MCF10A cells. Proteomics, 11(10), 2019-2026.
Publication 2011
ammonium bicarbonate beta-glycerol phosphate Breast Buffers Cells Cholera Toxin Cloning Vectors Cortisone Digestion Enzymes Epithelial Cells Equus caballus Fractionation, Chemical Homo sapiens Insulin Penicillins Peptides Protease Inhibitors Proteins Serum sodium pyrophosphate Sodium Vanadate Solid Phase Extraction Streptomycin Tablet Trypsin Urea
4
Assessing Comorbidities and Outcomes in COVID-19
Cited 46 times
Demographic, clinical, and outcome data were collected by using a prespecified case report form. Comorbidities were defined according to a modified Charlson comorbidity index.10 (link) Comorbidities collected were chronic cardiac disease, chronic respiratory disease (excluding asthma), chronic renal disease (estimated glomerular filtration rate ≤30), mild to severe liver disease, dementia, chronic neurological conditions, connective tissue disease, diabetes mellitus (diet, tablet, or insulin controlled), HIV or AIDS, and malignancy. These conditions were selected a priori by a global consortium to provide rapid, coordinated clinical investigation of patients presenting with any severe or potentially severe acute infection of public interest and enabled standardisation.
Clinician defined obesity was also included as a comorbidity owing to its probable association with adverse outcomes in patients with covid-19.11 (link)
12 (link) The clinical information used to calculate prognostic scores was taken from the day of admission to hospital.13 (link) A practical approach was taken to sample size requirements.14 We used all available data to maximise the power and generalisability of our results. Model reliability was assessed by using a temporally distinct validation cohort with geographical subsetting, together with sensitivity analyses.
Knight S.R., Ho A., Pius R., Buchan I., Carson G., Drake T.M., Dunning J., Fairfield C.J., Gamble C., Green C.A., Gupta R., Halpin S., Hardwick H.E., Holden K.A., Horby P.W., Jackson C., Mclean K.A., Merson L., Nguyen-Van-Tam J.S., Norman L., Noursadeghi M., Olliaro P.L., Pritchard M.G., Russell C.D., Shaw C.A., Sheikh A., Solomon T., Sudlow C., Swann O.V., Turtle L.C., Openshaw P.J., Baillie J.K., Semple M.G., Docherty A.B., Harrison E.M., Baillie J.K., Semple M.G., Openshaw P.J., Carson G., Alex B., Bach B., Barclay W.S., Bogaert D., Chand M., Cooke G.S., Docherty A.B., Dunning J., da Silva Filipe A., Fletcher T., Green C.A., Harrison E.M., Hiscox J.A., Ho A.Y., Horby P.W., Ijaz S., Khoo S., Klenerman P., Law A., Lim W.S., Mentzer A.J., Merson L., Meynert A.M., Noursadeghi M., Moore S.C., Palmarini M., Paxton W.A., Pollakis G., Price N., Rambaut A., Robertson D.L., Russell C.D., Sancho-Shimizu V., Scott J.T., Sigfrid L., Solomon T., Sriskandan S., Stuart D., Summers C., Tedder R.S., Thomson E.C., Thwaites R.S., Turtle L.C., Zambon M., Hardwick H., Donohue C., Ewins J., Oosthuyzen W., Griffiths F., Norman L., Pius R., Drake T.M., Fairfield C.J., Knight S., Mclean K.A., Murphy D., Shaw C.A., Dalton J., Girvan M., Saviciute E., Roberts S., Harrison J., Marsh L., Connor M., Halpin S., Jackson C., Gamble C., Leeming G., Law A., Hendry R., Scott-Brown J., Greenhalf W., Shaw V., McDonald S., Ahmed K.A., Armstrong J.A., Ashworth M., Asiimwe I.G., Bakshi S., Barlow S.L., Booth L., Brennan B., Bullock K., Catterall B.W., Clark J.J., Clarke E.A., Cole S., Cooper L., Cox H., Davis C., Dincarslan O., Dunn C., Dyer P., Elliott A., Evans A., Fisher L.W., Foster T., Garcia-Dorival I., Greenhalf W., Gunning P., Hartley C., Ho A., Jensen R.L., Jones C.B., Jones T.R., Khandaker S., King K., Kiy R.T., Koukorava C., Lake A., Lant S., Latawiec D., Lavelle-Langham L., Lefteri D., Lett L., Livoti L.A., Mancini M., McDonald S., McEvoy L., McLauchlan J., Metelmann S., Miah N.S., Middleton J., Mitchell J., Moore S.C., Murphy E.G., Penrice-Randal R., Pilgrim J., Prince T., Reynolds W., Ridley P.M., Sales D., Shaw V.E., Shears R.K., Small B., Subramaniam K.S., Szemiel A., Taggart A., Tanianis-Hughes J., Thomas J., Trochu E., van Tonder L., Wilcock E., Zhang J.E., Adeniji K., Agranoff D., Agwuh K., Ail D., Alegria A., Angus B., Ashish A., Atkinson D., Bari S., Barlow G., Barnass S., Barrett N., Bassford C., Baxter D., Beadsworth M., Bernatoniene J., Berridge J., Best N., Bothma P., Brealey D., Brittain-Long R., Bulteel N., Burden T., Burtenshaw A., Caruth V., Chadwick D., Chambler D., Chee N., Child J., Chukkambotla S., Clark T., Collini P., Cosgrove C., Cupitt J., Cutino-Moguel M.T., Dark P., Dawson C., Dervisevic S., Donnison P., Douthwaite S., DuRand I., Dushianthan A., Dyer T., Evans C., Eziefula C., Fegan C., Finn A., Fullerton D., Garg S., Garg S., Garg A., Godden J., Goldsmith A., Graham C., Hardy E., Hartshorn S., Harvey D., Havalda P., Hawcutt D.B., Hobrok M., Hodgson L., Holme A., Hormis A., Jacobs M., Jain S., Jennings P., Kaliappan A., Kasipandian V., Kegg S., Kelsey M., Kendall J., Kerrison C., Kerslake I., Koch O., Koduri G., Koshy G., Laha S., Larkin S., Leiner T., Lillie P., Limb J., Linnett V., Little J., MacMahon M., MacNaughton E., Mankregod R., Masson H., Matovu E., McCullough K., McEwen R., Meda M., Mills G., Minton J., Mirfenderesky M., Mohandas K., Mok Q., Moon J., Moore E., Morgan P., Morris C., Mortimore K., Moses S., Mpenge M., Mulla R., Murphy M., Nagel M., Nagarajan T., Nelson M., Otahal I., Pais M., Panchatsharam S., Paraiso H., Patel B., Pepperell J., Peters M., Phull M., Pintus S., Pooni J.S., Post F., Price D., Prout R., Rae N., Reschreiter H., Reynolds T., Richardson N., Roberts M., Roberts D., Rose A., Rousseau G., Ryan B., Saluja T., Shah A., Shanmuga P., Sharma A., Shawcross A., Sizer J., Smith R., Snelson C., Spittle N., Staines N., Stambach T., Stewart R., Subudhi P., Szakmany T., Tatham K., Thomas J., Thompson C., Thompson R., Tridente A., Tupper-Carey D., Twagira M., Ustianowski A., Vallotton N., Vincent-Smith L., Visuvanathan S., Vuylsteke A., Waddy S., Wake R., Walden A., Welters I., Whitehouse T., Whittaker P., Whittington A., Wijesinghe M., Williams M., Wilson L., Wilson S., Winchester S., Wiselka M., Wolverson A., Wooton D.G., Workman A., Yates B, & Young P. (2020). Risk stratification of patients admitted to hospital with covid-19 using the ISARIC WHO Clinical Characterisation Protocol: development and validation of the 4C Mortality Score. The BMJ, 370, m3339.
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Publication 2020
Acquired Immunodeficiency Syndrome Asthma Chronic Condition Chronic Kidney Diseases Connective Tissue Diseases COVID 19 Dementia Diabetes Mellitus Diet Disease, Chronic Glomerular Filtration Rate Heart Heart Diseases Hypersensitivity Infection Insulin Liver Diseases Malignant Neoplasms Obesity Patients Respiration Disorders Respiratory Rate Tablet
5
Illumina Reads Mapping and Visualization
Cited 43 times
We created a new software program for mapping Illumina sequencer reads (MPSmap) and visualizing the mapping results (PSmap). Detailed description and evaluation of the software will appear elsewhere; here, we describe our method briefly. Initially, a simple index of k-mers was prepared for the reference sequence. Then all bases of the read were compared with that of the reference for each index match of the read. This comparison was performed for all the index matches, and the best-matched position for each read was identified. A limitation of the index approach is that some of the close-match positions may not be identified if any mismatches are present within the index. To minimize this problem, we repeated the index search while shifting the index position on read sequences. For instance, we repeated the index search three times to correctly locate the read positions while allowing two mismatches. Similarly, we repeated the index search (n + 1) times, where n is the number of mismatches per read allowed in the search. Each index hit is aligned on the reference in order to look for the best location, allowing up to the specified number of mismatches without a gap. The index approach is fast but does not guarantee sensitivity for reads shorter than k (n + 1), where, k is the index length. For the mapping of B. subtilis allowing 35 mismatches, we compared searches with index lengths of k = 2 and k = 10 in order to confirm that the difference in results is small (Supplementary Table S1). We also performed mapping with BWA and BFAST using Tablet (29 (link)) for visualization, in order to confirm that multiple mapping algorithms detect the SSE (Supplementary Data S1). The visualization program (PSmap) converts the mapping results to a PostScript file. The programs, executable on Linux (CentOS5.3) and MacOSX (ver. 10.6.6) systems, are available for download on our website (http://metalmine.naist.jp/maps/).
Nakamura K., Oshima T., Morimoto T., Ikeda S., Yoshikawa H., Shiwa Y., Ishikawa S., Linak M.C., Hirai A., Takahashi H., Altaf-Ul-Amin M., Ogasawara N, & Kanaya S. (2011). Sequence-specific error profile of Illumina sequencers. Nucleic Acids Research, 39(13), e90.
Publication 2011
GPER protein, human Hypersensitivity Microtubule-Associated Proteins Tablet

Most recents protocols related to «Tablet»

1
Formulation and Manufacture of Mifepristone Tablets
Not available on PMC !

Example 4

TABLE 15
Composition of mifepristone tablet 240 mg
Composition H
Ingredientsmg/unit
Mifepristone nano-suspension
Mifepristone240.00
HPMC20.00
Sodium lauryl sulphate6.40
Docusate sodium0.80
Purified waterQ.S.
Intra-granular material
Silicified microcrystalline cellulose280.40
Sodium starch glycolate27.20
Extra-granular material
Microcrystalline cellulose119.6
Sodium starch glycolate20.40
Colloidal silicon dioxide1.8
Magnesium Stearate3.40
Core tablet weight (mg)720.00
Film-coating blend
OPADRY ® II Complete Film Coating21.60
System 85F18422 white
Purified WaterQ.S.
Coated Tablet Weight (mg)741.60
Manufacturing Procedure of Composition H:

Composition H was manufactured according to the following procedure:

  • a) Specified amount of purified water was taken in a suitable container and specified quantity of docusate sodium was added and stirred continuously to obtain a solution.
  • b) Sodium lauryl sulphate was added to the step (a) solution and stirred continuously to obtain a solution.
  • c) Hydroxypropyl methyl cellulose was added to the step (b) solution and stirred continuously to obtain a solution.
  • d) Mifepristone was added to the step (c) solution and stirred for 5 minutes to obtain Mifepristone dispersion.
  • e) Mifepristone dispersion was homogenized using IKA's Ultra TURRAX® homogenizer at 1000 RPM for 15 minutes.
  • f) The above homogenized mifepristone slurry was nano-sized in ball-mill chamber to obtain nano-suspension containing desired particle size of mifepristone. The particle size distribution was measured by using Mastersizer 3000 particle analyser.
  • g) Specified quantities of the silicified microcrystalline cellulose and sodium starch glycolate were dispensed in a bowl and warmed to reach 28° C. to 30° C. temperature.
  • h) The nano-sized mifepristone suspension according to step (f) was sprayed onto the warmed intra-granular material according to step (g). The sprayed granules were dried at a temperature of 50° C. to 65° C. and sieved through 30 number mesh sieve.
  • i) Specified quantities of milled granules of step (h), sodium starch glycolate, microcrystalline cellulose, colloidal silicon dioxide and magnesium stearate were blended and compressed using tablet compression machine. The tablets according to step (i) were coated with suitable coating materials.

US11878025B2. Pharmaceutical compositions of mifepristone (2024-01-23). SLAYBACK PHARMA LLC [US]. Inventors: Paras P. Jain [IN], Somnath Devidas Navgire [IN], Sumitra Ashokkumar Pillai [IN].
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Patent 2024
Cytoplasmic Granules Docusate Sodium Hypromellose magnesium stearate microcrystalline cellulose Mifepristone Pharmaceutical Preparations Silicon Silicon Dioxide sodium starch glycolate Sulfate, Sodium Dodecyl
2
Drug Dissolution and pH Change
Not available on PMC !

Example 2

General Procedure for Drug Dissolution and pH Change: The tablet is placed in acid medium (pH 2) and kept therein for two (2) hours. Thereafter phosphate buffer is added, which changes the pH to 6.0. The tablet coating is dissolved at this pH; the tablet breaks down and the drug is released. Prior to the pH change, i.e., in acid media, less than about 10% of the drug is released. Dissolution profiles are obtained using HPLC.

US11872229B2. Modified release formulations of 2-[3-[4-amino-3-(2-fluoro-4-phenoxy-phenyl)pyrazolo[3,4-d]pyrimidin-1-yl]piperidine-1-carbonyl]-4-methyl-4-[4-(oxetan-3-yl)piperazin-1-yl]pent-2-enenitrile (2024-01-16). Principia Biopharma Inc. [US]. Inventors: Abu J. Ferdous [US], Mohammad R. Masjedizadeh [US], Wu Lin [GB].
Full text: Click here
Patent 2024
Acids Buffers Drug Liberation High-Performance Liquid Chromatographies Pharmaceutical Preparations Phosphates Piperazine piperidine Tablet Tetranitrate, Pentaerythritol
3
Multimodal Approach for Periodontal Health
Not available on PMC !

Example 10

    • 6 months oral administration of 10 mg of bioavailable silicic acid per day in the form of choline-stabilized orthosilicic acid (ch-OSA®), wherein silicic acid is stabilized with choline chloride; preferably in the form of two dosage units, such as tablets
    • Local application of an ethylene/vinyl acetate copolymer fiber that contains tetracycline (12.7 mg per 9 inches) in the affected periodontal pocket for 10 days.
    • mouth rinsing with chlorhexidine 1% solution twice daily during 4 weeks.

US11878031B2. Silicic acids for use in the treatment of periodontitis (2024-01-23). Bio Minerals N.V. [BE]. Inventors: Mario Remi Yvonne Calomme [BE], Kathleen Jozef Ingrid Suzanne Van Hoof [BE].
Full text: Click here
Patent 2024
Acids Administration, Oral Aggressive Periodontitis Chlorhexidine Choline Choline Chloride Dosage Forms ethylenevinylacetate copolymer Fibrosis Oral Cavity Periodontal Pocket Silicic acid Tetracycline
4
Ticagrelor Immediate-Release Tablet Formulation
Not available on PMC !

EXAMPLE 4

IngredientsWeight (mg)
Ticagrelor10
Avicel ® PH 10250
Sprayed dried lactose100
Sodium starch glycolate4
Crospovidone4
Croscarmellose sodium4
Magnesium glycerate10
Lecithin10
Talcum10
Aspartame10

Mix the ingredients in the formulation and compress into tablets each with 5 mm in diameter and 2-3 mm in thickness by a single stroke tableting machine with the hardness between 3 to 5 kg. The thoroughly blended composition is compressed into plain tablets.

US11878016B2. Methods and products for treating subjects with autism spectrum disorders (2024-01-23). NEURIM PHARMACEUTICALS (1991) LTD. [IL]. Inventors: Nava Zisapel [IL], Moshe Laudon [IL].
Full text: Click here
Patent 2024
Aspartame Autism Spectrum Disorders Avicel Cerebrovascular Accident Crospovidone Lactose Lecithin Magnesium Sodium, Croscarmellose sodium starch glycolate Talc Ticagrelor
5
Silicic Acid and Micronutrients for Health
Not available on PMC !

Example 5

    • Daily oral administration of 5 mg of bioavailable silicic acid in the form of choline-stabilized orthosilicic acid (ch-OSA®), wherein silicic acid is stabilized with choline chloride, for instance in the form of a capsule.
    • Daily administration of a tablet containing 200 mg vitamin C, 150 microgram selenium, 10 mg zinc, 1 mg copper.

US11878031B2. Silicic acids for use in the treatment of periodontitis (2024-01-23). Bio Minerals N.V. [BE]. Inventors: Mario Remi Yvonne Calomme [BE], Kathleen Jozef Ingrid Suzanne Van Hoof [BE].
Full text: Click here
Patent 2024
Acids Administration, Oral Ascorbic Acid Capsule Choline Choline Chloride Copper Periodontitis Selenium Silicic acid Tablet Zinc

Top products related to «Tablet»

1
Protease inhibitor cocktail tablet by Roche
Sourced in Germany, United States, Switzerland, China, United Kingdom, Japan, Canada, Italy, France
Protease inhibitor cocktail tablets are a laboratory product offered by Roche. They function as a mixture of compounds designed to inhibit the activity of proteases, which are enzymes that break down proteins. The tablets provide a convenient way to incorporate protease inhibitors into experimental procedures that involve proteins or peptides.
2
Complete protease inhibitor cocktail tablet by Roche
Sourced in United States, Germany, Switzerland, United Kingdom, Canada, Japan, China, Italy
Complete protease inhibitor cocktail tablets are a laboratory product designed to inhibit the activity of various proteases. These tablets provide a broad-spectrum solution for the inhibition of proteolytic enzyme activity in biological samples.
3
Protease inhibitor tablet by Roche
Sourced in United States, Germany, Switzerland, United Kingdom, Canada, China
Protease inhibitor tablet is a laboratory equipment used in the analysis and study of proteins. It functions to inhibit the activity of proteases, which are enzymes that break down proteins. This product helps maintain the integrity of protein samples during experimental procedures.
4
Complete protease inhibitor tablet by Roche
Sourced in United States, Germany, Switzerland, United Kingdom, Canada
The Complete Protease Inhibitor Tablet is a laboratory product designed to inhibit a broad range of proteases. It functions by preventing the enzymatic activity of proteases, which are essential for various biological processes. The tablet provides a convenient and effective way to maintain protease inhibition in research and experimental settings.
5
Pierce bca protein assay kit by Thermo Fisher Scientific
Sourced in United States, United Kingdom, Germany, China, Australia, Switzerland, France, Italy, Canada, Spain, Japan, Belgium, Sweden, Lithuania, Austria, Denmark, Poland, Ireland, Portugal, Finland, Czechia, Norway, Macao, India, Singapore
The Pierce BCA Protein Assay Kit is a colorimetric-based method for the quantification of total protein in a sample. It utilizes the bicinchoninic acid (BCA) reaction, where proteins reduce Cu2+ to Cu+ in an alkaline environment, and the resulting purple-colored reaction is measured spectrophotometrically.
6
Phosstop by Roche
Sourced in Switzerland, Germany, United States, China, United Kingdom, Canada, Japan, Italy, France, Australia, Spain, Sweden
PhosSTOP is a phosphatase inhibitor cocktail designed for the inhibition of serine/threonine and tyrosine phosphatases during protein extraction and sample preparation for downstream analysis.
7
Protease inhibitor cocktail by Roche
Sourced in United States, Switzerland, Germany, China, United Kingdom, France, Canada, Japan, Italy, Australia, Austria, Sweden, Spain, Cameroon, India, Macao, Belgium, Israel
Protease inhibitor cocktail is a laboratory reagent used to inhibit the activity of proteases, which are enzymes that break down proteins. It is commonly used in protein extraction and purification procedures to prevent protein degradation.
8
Bca protein assay kit by Thermo Fisher Scientific
Sourced in United States, China, Germany, United Kingdom, Japan, Belgium, France, Switzerland, Italy, Canada, Australia, Sweden, Spain, Israel, Lithuania, Netherlands, Denmark, Finland, India, Singapore
The BCA Protein Assay Kit is a colorimetric detection and quantification method for total protein concentration. It utilizes bicinchoninic acid (BCA) for the colorimetric detection and quantification of total protein. The assay is based on the reduction of Cu2+ to Cu1+ by protein in an alkaline medium, with the chelation of BCA with the Cu1+ ion resulting in a purple-colored reaction product that exhibits a strong absorbance at 562 nm, which is proportional to the amount of protein present in the sample.
9
Pvdf membrane by Merck Group
Sourced in United States, Germany, China, United Kingdom, Morocco, Ireland, France, Italy, Japan, Canada, Spain, Switzerland, New Zealand, India, Hong Kong, Sao Tome and Principe, Sweden, Netherlands, Australia, Belgium, Austria
PVDF membranes are a type of laboratory equipment used for a variety of applications. They are made from polyvinylidene fluoride (PVDF), a durable and chemically resistant material. PVDF membranes are known for their high mechanical strength, thermal stability, and resistance to a wide range of chemicals. They are commonly used in various filtration, separation, and analysis processes in scientific and research settings.
10
Complete mini protease inhibitor cocktail tablet by Roche
Sourced in United States, Germany, Switzerland, France
The Complete Mini Protease Inhibitor Cocktail Tablets are a laboratory product designed to inhibit proteases, which are enzymes that break down proteins. The tablets provide a broad-spectrum solution for the inhibition of a wide range of proteases. This product is intended for use in various research and analytical applications where the preservation of protein integrity is crucial.

More about "Tablet"

Tablets are a versatile and commonly used solid dosage form for oral medication administration.
They typically consist of an active pharmaceutical ingredient(s) compressed or molded into a solid form, along with various excepients like binders, disintegrants, and lubricants.
Tablets offer several advantages, including accurate dosing, ease of administration, and improved drug stability.
Research into tablet formulation, manufacturing, and quality control is essential for developing safe and effective oral medications.
This includes studies on protease inhibitor cocktail tablets, complete protease inhibitor cocktail tablets, protease inhibitor tablets, and complete protease inhibitor tablets.
Techniques like the Pierce BCA Protein Assay Kit, PhosSTOP, and BCA protein assay kits are often used to evaluate tablet properties.
Beyond tablets, other common solid dosage forms include capsules, pills, and lozenges.
PVDF membranes are also frequently used in pharmaceutical research and development.
The Complete Mini Protease Inhibitor Cocktail Tablets are a specialized product that can help preserve protein samples during analysis.
Overall, tablets remain a core dosage form across many therapeutic areas, with continual advancements in formulation, manufacturing, and quality control driving the development of safer and more effective oral medications.
Reasearch is the key to unlocking these improvements.