Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

GNPS - Common beauty products used during T4-T6

ABSTRACT: LC-MS/MS data were collected from beauty products used by 11 individuals during 3 weeks (week4 - week6/T4-T6) of a longitudinal 9 weeks study. Common beauty products include: a deodorant for armpits, a face sunscreen lotion for the face, a moisturizer for arms and a soothing powder for feet.

INSTRUMENT(S): maXis

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Pieter Dorrestein

PROVIDER: MSV000081581 | GNPS | Wed Oct 04 12:53:00 BST 2017

REPOSITORIES: GNPS

ACCESS DATA

Json Xml

Similar Datasets

GNPS - BP-Microbiome_Skin samples 12 volunteers

Project description:LC-MS/MS data were collected from skin swabs of 11 volunteers over a period of 9 weeks and for one volunteer during one week. Volunteers were asked to follow instructions required over our 9 weeks study: - We provided the same head to toe shampoo to all volunteers, that was used during shower for the first 6 weeks. - Week 1 to week 3: no other beauty products was used. - Week 4 to week 6: we provided 5 selected commercial beauty products that all volunteers applied daily on specific body part (deodorant for armpits, soothing foot powder for feet, sunscreen for face and moisturizer for arm back). - Week 7 to week 9: back to normal routine. - Samples were collected every week, before during and after application of beauty products.

2017-10-04 | MSV000081582 | GNPS

GNPS - Colgate facial cleanser longitudinal study_Skin samples

Project description:MS/MS spectra were collected from face of 6 individuals before and during 2 weeks of application of a Colgate facial cleanser. During weeks 1-4 of washout period, volunteers did not use any personal beauty product and they washed their face only with water. During the following 2 weeks, all participants applied the Colgate facial cleanser daily on their face. Samples were collected at the end of the washout period on week 4. During facial cleanser application (weeks 5 and 6), samples were collected once a week (beginning of week 5 and end of week 6) right after the first usage then 4, 8 and 24 hours after the first usage. For each timepoint, 9 samples were collected from different locations on the face.

2018-06-01 | MSV000082432 | GNPS

GNPS - Trace detection of skin molecules on objects_Volunteer 6. MS/MS Data

Project description:MS/MS spectra have been collected from skin samples (hands, arms, head) and objects (laptop, mouse, cellular device) used by volunteer 6. MS/MS spectra collected from beauty products used by the subject have been also included.

2014-08-22 | MSV000078816 | GNPS

GNPS - 3D molecular analysis of skin surface_Time_Course_Volunteer 5-man-Face. MS/MS Data

Project description:mzXML files of MS/MS data from skin swab samples of 1 man volunteer. Samples were collected from 17 spots on a man face, everyday during 10 days. MS/MS data collected from beauty products used by this subject are also included.

2014-05-27 | MSV000078683 | GNPS

Quantitative proteomics identifies Yashtimadhu as a neuroprotectant against rotenone induced cellular model of Parkinson’s disease

Project description:We aimed to explore the neuroprotective efficacy of Yashtimadhu powder, prepared from the roots of Glycyrrhiza glabra L. (https://mpns.science.kew.org; http://www.ayurveda.hu/api/API-Vol-1.pdf) commonly known as licorice, a known Medhya rasayana in the Indian Ayurvedic texts against Parkinson’s disease. To test the efficacy of Yashtimadhu powder, we used rotenone to generate an in vitro PD model using retinoic acid-differentiated IMR32 cells. Yashtimadhu powder (Lot No.64) was procured from SDP Remedies and Research Centre, Mangalore, India, a GMP-certified Ayurvedic product manufacturer ((http://sdpayurveda.com/products/choorna/yastimadhu-choorna/)The Yashtimadhu neuroprotection was ascertained using cell cytotoxicity, activation of apoptotic proteins and kinases. We used Tandem mass tag (TMT)-lables to understand the differentially regulated proteins across various treatment groups, using Orbitrap Fusion Tribrid mass spectrometer. The mass spectrometry data is acquired in biological duplicates and technical triplicates. We report 4,864 proteins corresponding to 4,783 gene symbols. The proteins were filtered out based technical and biological replicate concordance, thereby reporting 3,720 proteins common among the biological replicates.

2021-09-09 | PXD019672 | Pride

Top-down characterization of lunasin in a commercial soybean-derived product

Project description:The presence of lunasin was investigated in two soybean products, raw soy seeds and a commercial soybean beverage powder. Lunasin from the commercial soybean derivative was purified by reverse phase high pressure liquid chromatography and bystrong anion exchange solid phase extraction. Lunasin was further characterized by Top-down mass spectrometry (MS). The top-down characterization of lunasin unraveled a wide range of post-translationally modified proteoforms.

2016-05-24 | PXD003064 | Pride

Cell of origin strongly influences genetic selection in a mouse model of T-ALL.

Project description:Thymic lymphomas were generated by inducing Sleeping Beauty transposon mutagenesis at different stages of T-cell development. This dataset includes exon array results from 14 tumor samples from two different Sleeping Beauty models of T-ALL (7 Vav-SB and 7 CD4-SB samples).

2011-08-20 | E-GEOD-29849 | biostudies-arrayexpress

Project description:DEVOTES ARMS

| PRJNA557002 | ENA

A comparison of common programming languages used in bioinformatics.

Project description:BACKGROUND: The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python. RESULTS: Implementations in C and C++ were fastest and used the least memory. Programs in these languages generally contained more lines of code. Java and C# appeared to be a compromise between the flexibility of Perl and Python and the fast performance of C and C++. The relative performance of the tested languages did not change from Windows to Linux and no clear evidence of a faster operating system was found. Source code and additional information are available from http://www.bioinformatics.org/benchmark/. CONCLUSION: This benchmark provides a comparison of six commonly used programming languages under two different operating systems. The overall comparison shows that a developer should choose an appropriate language carefully, taking into account the performance expected and the library availability for each language.

| S-EPMC2267699 | biostudies-literature

Transcription profiling of Arabidopsis 8 GFP marked lines with 2-3 replicates were used to augment existing microarray expression profiles of the root

Project description:Transcriptional programs that regulate development are exquisitely controlled in space and time. Elucidating these programs that underlie development is essential to understanding the acquisition of cell and tissue identity. We present microarray expression profiles of a high resolution set of developmental time points within a single Arabidopsis root, and a comprehensive map of nearly all root cell-types. These cell-type specific transcriptional signatures often predict novel cellular functions. A computational pipeline identified dominant expression patterns that demonstrate transcriptional connections between disparate cell types. Dominant expression patterns along the rootâs longitudinal axis do not strictly correlate with previously defined developmental zones, and in many cases, expression fluctuation along this axis was observed. Both robust co-regulation of gene expression and potential phasing of gene expression were identified between individual roots. Methods that combine these two sets of profiles demonstrate transcriptionally rich and complex programs that define Arabidopsis root development in both space and time. We used microarrays to profile expression of nearly all cell types in the Arabidopsis root, and to profile at high resolution, developmental time points along the root's longitudinal axis. Experiment Overall Design: Microarray expression profiles of 8 new GFP marked lines with 2-3 replicates were used to augment existing microarray expression profiles of the root. RNA isolated from 13 cross sections along a single root's longitudinal axis were also profiled by microarray analysis. An independent root with 12 sections were used as a biological replicate.

2008-06-16 | E-GEOD-8934 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data