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1.
Healthcare (Basel) ; 7(2)2019 May 19.
Article in English | MEDLINE | ID: mdl-31109144

ABSTRACT

Conventional sauna bathing may have some health benefits as it facilitates relaxing, detoxing and promoting metabolism. However, conventional sauna bathing at a high temperature may be harmful for the body by increasing the risk of heart failure. The nano-mist sauna has been developed to provide nano-size water particles at a lower temperature. Hence, nano-mist sauna bathing is expected to be useful for health without the risks that arise at high temperatures. In this study, we performed a comprehensive proteomics analysis of urine samples obtained from healthy volunteers before and after they had taken a sauna bath with nano-mist (n = 10) or with conventional mist (n = 10) daily for two weeks (4 groups). The average numbers of urine proteins identified by liquid chromatography-linked mass chromatography in each group varied from 678 to 753. Interestingly, the protein number was increased after sauna bathing both with nano-mist or with conventional mist. Quantitative analysis indicated that considerable numbers of proteins were obviously up-regulated, with more than two-folds in urine samples after the nano-mist sauna bathing. The KEGG pathway analysis showed significant stimulation of the lysosome pathway (p = 5.89E-6) after the nano-mist bathing, which may indicate the nano-mist sauna bathing promotes metabolism related to the lysosome pathway more efficiently than conventional mist sauna bathing and may provide more health benefits.

2.
Pathogens ; 7(3)2018 Jul 29.
Article in English | MEDLINE | ID: mdl-30060633

ABSTRACT

Staphylococcus aureus (S. aureus) is a commensal bacteria on the human skin, which causes serious skin inflammation. Several immune cells, especially effector T cells (Teff), have been identified as key players in S. aureus-derived skin inflammation. However, the bacterial component that induces dramatic host immune responses on the skin has not been well characterized. Here, we report that S. aureus lipoprotein (SA-LP) was recognized by the host immune system as a strong antigen, so this response induced severe skin inflammation. SA-LP activated dendritic cells (DCs), and this activation led to Teff accumulation on the inflamed skin in the murine intradermal (ID) injection model. The skin-accumulated Teff pool was established by IFN-ɤ-producing CD4⁺ and CD8⁺T (Th1 and Tc1). SA-LP activated dermal DC (DDC) in a dominant manner, so that these DCs were presumed to possess the strong responsibility of SA-LP-specific Teff generation in the skin-draining lymph nodes (dLN). SA-LP activated DC transfer into the mice ear, which showed similar inflammation, accompanied with Th1 and Tc1 accumulation on the skin. Thus, we revealed that SA-LP has a strong potential ability to establish skin inflammation through the DC-Teff axis. This finding provides novel insights not only for therapy, but also for the prevention of S. aureus-derived skin inflammation.

3.
Proteomes ; 6(1)2018 Feb 06.
Article in English | MEDLINE | ID: mdl-29415455

ABSTRACT

Diabetic mellitus (DM) is a disease that affects glucose homeostasis and causes complications, such as diabetic nephropathy (DN). For early diagnosis of DN, microalbuminuria is currently one of the most frequently used biomarkers. However, more early diagnostic biomarkers are desired in addition to microalbuminuria. In this study, we performed comprehensive proteomics analysis of urine proteomes of diabetic mellitus patients without microalbuminuria and healthy volunteers to compare the protein profiles by mass spectrometry. With high confidence criteria, 942 proteins in healthy volunteer urine and 645 proteins in the DM patient urine were identified with label-free semi-quantitation, respectively. Gene ontology and pathway analysis were performed with the proteins, which were up- or down-regulated in the DM patient urine to elucidate significant changes in pathways. The discovery of a useful biomarker for early DN discovery is expected.

4.
J Proteome Res ; 16(12): 4403-4414, 2017 12 01.
Article in English | MEDLINE | ID: mdl-28980472

ABSTRACT

In an attempt to complete human proteome project (HPP), Chromosome-Centric Human Proteome Project (C-HPP) launched the journey of missing protein (MP) investigation in 2012. However, 2579 and 572 protein entries in the neXtProt (2017-1) are still considered as missing and uncertain proteins, respectively. Thus, in this study, we proposed a pipeline to analyze, identify, and validate human missing and uncertain proteins in open-access transcriptomics and proteomics databases. Analysis of RNA expression pattern for missing proteins in Human protein Atlas showed that 28% of them, such as Olfactory receptor 1I1 ( O60431 ), had no RNA expression, suggesting the necessity to consider uncommon tissues for transcriptomic and proteomic studies. Interestingly, 21% had elevated expression level in a particular tissue (tissue-enriched proteins), indicating the importance of targeting such proteins in their elevated tissues. Additionally, the analysis of RNA expression level for missing proteins showed that 95% had no or low expression level (0-10 transcripts per million), indicating that low abundance is one of the major obstacles facing the detection of missing proteins. Moreover, missing proteins are predicted to generate fewer predicted unique tryptic peptides than the identified proteins. Searching for these predicted unique tryptic peptides that correspond to missing and uncertain proteins in the experimental peptide list of open-access MS-based databases (PA, GPM) resulted in the detection of 402 missing and 19 uncertain proteins with at least two unique peptides (≥9 aa) at <(5 × 10-4)% FDR. Finally, matching the native spectra for the experimentally detected peptides with their SRMAtlas synthetic counterparts at three transition sources (QQQ, QTOF, QTRAP) gave us an opportunity to validate 41 missing proteins by ≥2 proteotypic peptides.


Subject(s)
Data Mining/methods , Databases, Protein , Proteome/analysis , Computational Biology , Humans , Proteomics/methods , Tissue Distribution , Transcriptome
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