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Quince

Quince is a member of the Rosaceae family, a group of flowering plants that includes apples, pears, and other edible fruits.
Quince is a small, golden-yellow fruit with a distinctive aroma and tart flavor.
It is commonly used in jams, jellies, and other preserves, as well as in baking and cooking.
Quince is a rich source of vitamin C and dietary fiber, and has been used in traditional medicine for its potential health benefits.
Researchers are exploring the use of quince in various applications, including food processing, nutraceuticals, and pharmaceuticals.
PubCompare.ai can help researchers optimize their quince experinces by providing intelligent comparisons of the latest protocols from literature, preprints, and patents, enhancing reproducibility and accuracy.

Most cited protocols related to «Quince»

Three test datasets were used in this work. (i) SIM2 is a selected subset of the simulated bimeras and control sequences used to train and evaluate ChimeraSlayer. (ii) MOCK is the Uneven datasets used to evaluate Perseus (Quince et al., 2011 (link)). They are derived from pyrosequencing reads of ‘mock’ communities, i.e. experimentally mixed DNAs of known composition. These reads were processed by AmpliconNoise (Quince et al., 2011 (link)), which attempts to remove sequencing error and generates a set of predicted sequences for the amplicons. Sequences in this set were classified as biological or chimeric by comparing them to reference sequences for the species in each community, and chimera detection algorithms were assessed by their success in reproducing this classification. (iii) SIMM is a new set of simulated m-meras created for this work. SIM2 and SIMM were used to compare the performance of the reference database mode of UCHIME with ChimeraSlayer, MOCK was used to compare the de novo mode of UCHIME with Perseus. The parameters of UCHIME were trained on SIM2; the score threshold h was set to a value giving an average error rate over the whole SIM2 dataset lower than the error rate of ChimeraSlayer on the same data. UCHIME was trained by an exhaustive search over manually selected pairs (β,n). The optimal pair (β+,n+) was identified by maximizing the area under a receiver operating characteristic curve (Mason and Graham, 2002 ). Given β+ and n+, an optimal score threshold h+ is determined by (i) specifying a maximum desired error rate or minimum desired sensitivity and (ii) maximizing sensitivity or minimizing error rate, respectively. After training, the sensitivity of UCHIME averaged over all SIM2 sets was 70.6% with an error rate of 0.49%, compared with 54.6% sensitivity and 0.62% errors for ChimeraSlayer.
Publication 2011
Biopharmaceuticals Chimera DNA Hypersensitivity Quince
The SILVA database v.106 and ARB software v. 5.2 were used to identify and test specificity of the different primers in silico[30] (link), [31] (link), [51] (link). An internally developed AmpliconGenerator v.0.1 (http://sf.net/projects/amplicongenerator) was used to characterize nucleotide variability along the reference sequence. The software was also used to generate in silico amplicons and to assess the conservation of biodiversity as a function of sequence similarity. IDT SciTools OligoAnalyzer 3.0 (Integrated DNA Technologies, Coralville, IA) was used to estimate melting temperatures of the primers as well as the presence of hairpins, self- and hetero-dimers in the candidate primers. Sequences from the environmental samples were processed through the bioinformatic pipeline AmpliconNoise according to Quince and co-workers [6] . As a first step in the pipeline, low quality reads were removed, defined as shorter than 200 nt or having inadequate signal intensity. Subsequently, noise from the flowgram and PCR-generated errors were removed using established probabilistic iterative algorithms [6] , [52] (link) and chimeras removed using the program Perseus [6] . The reads were then clustered together using the complete linkage-clustering algorithm implemented in FCluster, based on pairwise distances as calculated by NDist [6] , and aligned to the SILVA and NCBI databases using BLAST for the purpose of taxonomic annotation. The same software package was also applied to build operational taxonomic units (OTUs). Since the choice of the pipeline can influence the results of metagenetic studies and because there is no consensus on which pipeline to use, the results produced with AmpliconNoise were compared to results produced by an alternative commonly used pipeline, QIIME. In QIIME, original reads were filtered based on the quality score, but no further denoising procedure was applied. Further, in order to remove potential chimeras, OTUs representing singletons were discarded.
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Publication 2014
Base Sequence Chimera Oligonucleotide Primers Quince Workers
The 454-pyrosequencing errors, PCR single base errors and chimeric sequences were removed from the 454-pyrosequencing amplicon library employing AmpliconNoise (v1.26; Quince et al., 2011 (link)) followed by Perseus (Quince et al., 2011 (link)). Pyrosequencing reads not matching multiplex identifier and/or primer sequences were removed just as were reads shorter than 200 bp. Reads were further truncated at 450 bp, eliminating additional noise (Mardis, 2008 (link)), and finally trimmed off multiplex identifier and primer sequences.
Denoised 454-pyrosequences were clustered into operational taxonomic units (OTUs) at a level of 97% sequence identity (AmpliconNoise, v1.29; Quince et al., 2011 (link)) and classified based on the RDP naive Bayesian rRNA Classifier (RDP Classifier, v2.6; Wang et al., 2007 (link)). Representative sequences were aligned based on the SILVA alignment (release 102; Quast et al., 2013 (link)) using mothur (v1.33.2; Schloss et al., 2009 (link)). Finally, pyrosequences that could neither be aligned nor assigned, or were assigned as Archaea or Eukaryota (for example, chloroplasts) were further removed. The 454-pyrosequencing reads of both experimental (Ba, GW, HL, and VA) and environmental (EnvBa, EnvGW, EnvHL, and EnvVA) samples have been deposited at the NCBI Sequence Read Archive under accession number SRP021096.
Publication 2015
Archaea Chimera Chloroplasts DNA Library Eukaryota Oligonucleotide Primers Quince Ribosomal RNA
We tested AbundantOTU on two mock datasets, for which the microbial composition and reference sequences are known, and three metagenomic datasets derived from real communities (see Table I for the summary of the datasets). The first mock dataset (designated as Priest09) is the ‘divergent sequence’ dataset from [4 (link)] that contains amplified and pyrosequenced sequences from 23 divergent 16S rRNA fragments spanning V5 (the pyrosequences dataset and reference sequences were downloaded from http://people.civil.gla.ac.uk/~quince/Data/PyroNoise.html). The second mock dataset (designated as Mock07) contains short sequences generated by pyrosequencing PCR amplicon libraries of 43 known 16S rRNA gene fragments spanning V6 using the Roche GS20 system, generated in a study of sequencing errors [17 (link)]. This dataset was downloaded from http://genomebiology.com/2007/8/7/R143. The three real metagneomic datasets contain reads from oral [18 (link)] and skin [2 ] samples, respectively, downloaded from the NCBI Short Read Archive (SRA) with accession numbers SRR002260 (oral/plaque), SRR002259 (oral/saliva), and SRR00606 (skin).
Publication 2011
Dental Plaque Gene Library Metagenome Quince RNA, Ribosomal, 16S Saliva Skin
For our primary analysis, we used a previously published dataset [19 (link)] derived from the microbiomes of fourteen individual nematodes. Two regions of the bacterial 16S ribosomal RNA gene (V3-V5 and V6-V8) were PCR amplified and sequenced using the Roche-454 GS FLX platform with the Titanium protocol (800 flows), resulting in just over 40,000 reads.
To calculate error rates, we retrieved the Titanium mock community dataset of Quince et al. [6 (link)], which was used to validate AmpliconNoise, as well as other denoising algorithms [23 (link)]. The 62,873 reads were derived from PCR amplification of the V4-V5 region of the 16S gene, using 91 plasmid clones as the source DNA (mock community). The set of original reads (“Stage 0”) was determined by filtering only for mid tag and primer sequences and allowing one and two mismatches to them, respectively. The initial error rate was calculated by finding the best match of each read to the 90 reference sequences (see Additional files 2 and 3) using ClustalW [24 (link)] with a reduced gap-opening penalty (-gapopen=1). In this and other error-rate calculations, we counted only insertions and deletions, which are the dominant form of errors in Roche-454 pyrosequencing [9 (link)]. We filtered the reads with FlowClus (version 1.1) using criteria similar to those recommended with the QIIME denoising pipeline and denoised with a constant value of 0.90. The dataset was also processed through the equivalent steps of AmpliconNoise V1.27 [6 (link)] and the denoising pipeline in QIIME 1.8.0 [8 (link)].
To evaluate scalability, we analyzed the large datasets from Krych et al. [25 (link)]. In this study of the human gut microbiome, the V3-V4 region of the 16S gene was amplified by PCR and sequenced on the Roche-454 GS FLX Titanium platform. The total number of reads for all three groups (baseline, synbiotic, and placebo) was 2.2 million.
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Publication 2015
Clone Cells Gastrointestinal Microbiome Gene Amplification Gene Deletion Genes Genes, Bacterial Homo sapiens Human Microbiome Insertion Mutation Microbiome Nematoda Oligonucleotide Primers Placebos Plasmids Quince RNA, Ribosomal, 16S Synbiotics Titanium

Most recents protocols related to «Quince»

Free-radical polymerization technique was used to fabricate a quince/mucin co-poly (methacrylate) hydrogel. Polymers, monomers and a cross-linker were incorporated at different ratios. The compositions of different formulations (QHM1–QHM12) are presented in Table 1. Specified amounts of each QH were dissolved in deionized water (5 mL) on a magnetic stirrer (VELP Scientifica) until the QH fragments were properly distributed. Similarly, mucin, APS, MAA and MBA were dissolved separately in deionized water (5 mL) on a hot plate magnetic stirrer. The solutions of the polymers (quince and mucin) were mixed together with continuous stirring (100 rpm), followed by APS incorporation. MBA was added to the solution of MAA with continuous stirring. This solution was transferred to the activated polymeric solution with continuous stirring. The whole mixture was sonicated for 5 min, transferred into glass tubes, and sealed with aluminum foil. The test tubes were kept in a thermostatically controlled water bath (Memmert, Tokyo, Japan) at 55 °C for 2 h and then at 65 °C for 8 h. After a specified period of time, the test tubes were removed from the water bath and placed at room temperature for some time. The prepared hydrogel was removed with the help of a spatula and impregnated with ethanol. The cutting of the prepared hydrogels in the form of discs (5 mm thick) was carried out with the help of a sharp blade. Washing was executed with an ethanol and water mixture (70:30) for 30 min to remove unreacted contents. The drying of the discs was accomplished in a hot air oven at 45 °C until a constant weight was achieved [20 (link),21 (link)].
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Publication 2023
Aluminum Bath Ethanol Free Radicals Hydrogels Methacrylate Mucins Poly A Polymerization Polymers Quince
Molar solutions with different concentrations of sodium chloride and calcium chloride (0.1, 0.2, 0.3, 0.4, 0.5, 1.0 and 2.0 M) were prepared to assess the equilibrium swelling of the quince/mucin co-poly (methacrylate) hydrogel discs. Pre-weighed discs were immersed in the electrolyte solutions for 24 h, after which they were removed from the respective immersion mediums and reweighed on an analytical balance to assess their equilibrium swelling capacities as g/g [22 (link),23 (link)].
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Publication 2023
Calcium chloride Culture Media Electrolytes Hydrogels Methacrylate Molar Mucins Poly A Quince Saline Solution Submersion
Quince seeds (100 g) were immersed in distilled water (500 mL) for 8 h to isolate the quince hydrogel (QH). To maximize the yield, heating at 50 °C for at least 30 min was performed. The extracted QH was separated with a cotton cloth and washed with n-hexane. After washing, the QH was transferred to Petri plates and dried in an hot air oven at 50 °C for 48 h. The dried QH was powdered using a mortar and pestle, sieved through a 60-mesh sieve, and stored in a well-closed plastic jar for further use. The yield of the QH was estimated at 11 gm/100 gm of dried seeds [14 (link)].
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Publication 2023
Gossypium Hydrogels n-hexane Plant Embryos Quince
To ascertain the pH responsiveness of the quince/mucin-co-poly (methacrylate) hydrogel, swelling of the hydrogel discs was investigated in an acidic buffer with a pH of 1.2, and a phosphate buffer with a pH of 6.8 or 7.4 at 37 °C. Pre-weighed discs were immersed in the buffer solution, and, after pre-determined time intervals (1, 2, 3, 4, 6, 8, 10, 12, 14, 16, 18, 20, 24, 28, 32 and 36 h), the discs were removed, allowed to drop off excessive immersion medium from their surface, and reweighed. The swelling capacity g/g was calculated using the following equation:
where Wt denotes the weight of the disc after time t, and Wo represents the initial weight of the dried disc.
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Publication 2023
Acids Buffers Hydrogels Methacrylate Mucins Phosphates Poly A Quince Submersion
Quince seeds were purchased from Awaami Laboratories Pvt. Ltd., Lahore, Pakistan. NaCl, KCl, HCl, ammonium persulfate and potassium dihydrogen phosphate were provided by Icon Chemicals, Germany, while n-hexane was obtained from Merck, Germany. N, N-Methylene bisacrylamide (MBA) was purchased from Thermo Fisher Scientific, Shanghai, China. Methacrylic acid (MAA) was sourced from Duksan Pure Chemicals, Ansan, Republic of Korea. Acyclovir sodium was donated by Trigon Pharmaceuticals Pvt. Ltd., Lahore, Pakistan. In all experimental work, distilled water was used.
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Publication 2023
ammonium peroxydisulfate methacrylic acid N,N'-methylenebisacrylamide n-hexane Pharmaceutical Preparations Plant Embryos potassium phosphate, monobasic Quince Sodium, Acyclovir Sodium Chloride

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Neochlorogenic acid is a natural phenolic compound found in various plant species. It is a type of chlorogenic acid, a group of esters formed between quinic acid and certain trans-cinnamic acids, primarily caffeic acid. Neochlorogenic acid is commonly used as a reference standard in analytical applications for the identification and quantification of chlorogenic acid derivatives.
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Kaempferol-3-O-glucoside (K3g) is a flavonoid compound that can be used as a reference standard in analytical and research applications. It is a naturally occurring glycoside found in various plant species. K3g is commonly used in the identification and quantification of this compound in samples through analytical techniques such as HPLC and LC-MS.
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Chlorogenic acid is a compound found in various plants, including coffee beans. It is a type of polyphenol and is commonly used in laboratory settings for research purposes.
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More about "Quince"

Quince, a member of the Rosaceae family, is a small, golden-yellow fruit with a distinctive aroma and tart flavor.
This edible fruit is commonly used in jams, jellies, preserves, baking, and cooking, and is a rich source of vitamin C and dietary fiber.
Researchers are exploring the potential health benefits of quince, including its use in food processing, nutraceuticals, and pharmaceuticals.
Quince is closely related to other members of the Rosaceae family, such as apples and pears.
The fruit contains various bioactive compounds, including neochlorogenic acid, kaempferol-3-O-glucoside (K3g), and kaempferol-3-O-rutinoside (K3r), which have been studied for their potential antioxidant, anti-inflammatory, and antimicrobial properties.
Analytical techniques, such as the Qubit 2.0 Fluorometer and the HiSeq 2500 sequencing platform, have been utilized to characterize the chemical composition and genetic profiles of quince.
Additionally, compounds like chlorogenic acid, p-coumaric acid, cryptochlorogenic acid, and glycerol have been identified in quince and studied for their potential applications.
PubCompare.ai, an innovative AI-driven platform, can help researchers optimize their quince experiments by providing intelligent comparisons of the latest protocols from literature, preprints, and patents, enhancing reproducibility and accuracy.
By leveraging the power of PubCompare.ai, researchers can experience the future of quince research and unlock new possibilities in food processing, nutraceuticals, and pharmaceuticals.