scholarly journals Classification of Raw Stingless Bee Honeys by Bee Species Origins using NMR-LCMS-based Metabolomics Approach

2018 ◽  
Author(s):  
Muhammad Taufiq Atsifa Razali ◽  
Zaim Akmal Zainal ◽  
Maulidiani Maulidiani ◽  
Khozirah Shaari ◽  
Zulkifli Zambri ◽  
...  
Keyword(s):  
1H Nmr ◽  
High Performance ◽  
Stingless Bee ◽  
Proton Nuclear Magnetic Resonance ◽  
Flight Mass Spectrometry ◽  
Nmr Data ◽  
Classification Technique ◽  
Diagnostic Ions

Background: The official standard for quality control of honey is currently based on physicochemical properties. However, this method is time-consuming, cost intensive, and do not lead to information on the originality of honey. This study aims to classify raw stingless bee honeys by bee species origins as a potential classifier using NMR-LCMS-based metabolomics approach. Methods: Raw stingless bee honeys were analysed and classified by bee species origins using proton nuclear magnetic resonance (1H NMR) spectroscopy and an ultra-high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-QTOF MS) in combination with chemometrics tools. Results: The honey samples were able to be classified into three different groups based on the bee species origins of Heterotrigona itama, Geniotrigona thoracica, and Tetrigona apicalis. D-Fructofuranose (H. itama honey), β-D-Glucose, D-Xylose, α-D-Glucose (G. thoracica honey), and L-Lactic acid, Acetic acid, L-Alanine (T. apicalis honey) identified via 1H NMR data and the diagnostic ions of UHPLC-QTOF MS were characterized as the discriminant metabolites or putative chemical markers. Conclusion: It could be suggested that the quality of honey in terms of originality and purity can be rapidly determined using classification technique by bee species origins via 1H NMR- and UHPLC-QTOF MS-based metabolomics approach.

scholarly journals Classification of Raw Stingless Bee Honeys by Bee Species Origins Using the NMR- and LC-MS-Based Metabolomics Approach

Molecules ◽  
2018 ◽  
Vol 23 (9) ◽  
pp. 2160 ◽  
Author(s):  
Muhammad Razali ◽  
Zaim Zainal ◽  
M. Maulidiani ◽  
Khozirah Shaari ◽  
Zulkifli Zamri ◽  
...  
Keyword(s):  
1H Nmr ◽  
High Performance ◽  
Stingless Bee ◽  
Proton Nuclear Magnetic Resonance ◽  
Flight Mass Spectrometry ◽  
Nmr Data ◽  
Classification Technique ◽  
Diagnostic Ions

The official standard for quality control of honey is currently based on physicochemical properties. However, this method is time-consuming, cost intensive, and does not lead to information on the originality of honey. This study aims to classify raw stingless bee honeys by bee species origins as a potential classifier using the NMR-LCMS-based metabolomics approach. Raw stingless bee honeys were analysed and classified by bee species origins using proton nuclear magnetic resonance (1H-NMR) spectroscopy and an ultra-high performance liquid chromatography-quadrupole time of flight mass spectrometry (UHPLC-QTOF MS) in combination with chemometrics tools. The honey samples were able to be classified into three different groups based on the bee species origins of Heterotrigona itama, Geniotrigona thoracica, and Tetrigona apicalis. d-Fructofuranose (H. itama honey), β-d-Glucose, d-Xylose, α-d-Glucose (G. thoracica honey), and l-Lactic acid, Acetic acid, l-Alanine (T. apicalis honey) ident d-Fructofuranose identified via 1H-NMR data and the diagnostic ions of UHPLC-QTOF MS were characterized as the discriminant metabolites or putative chemical markers. It could be suggested that the quality of honey in terms of originality and purity can be rapidly determined using the classification technique by bee species origins via the 1H-NMR- and UHPLC-QTOF MS-based metabolomics approach.

scholarly journals LC-QTOF-MS and 1H NMR Metabolomics Verifies Potential Use of Greater Omentum for Klebsiella pneumoniae Biofilm Eradication in Rats

Pathogens ◽  
2020 ◽  
Vol 9 (5) ◽  
pp. 399
Author(s):  
Joanna Teul ◽  
Stanisław Deja ◽  
Katarzyna Celińska-Janowicz ◽  
Adam Ząbek ◽  
Piotr Młynarz ◽  
...  
Keyword(s):  
Klebsiella Pneumoniae ◽  
1H Nmr ◽  
Surgical Procedures ◽  
High Performance ◽  
Tca Cycle ◽  
Alternative Methods ◽  
Proton Nuclear Magnetic Resonance ◽  
Greater Omentum ◽  
Surgical Interventions ◽  
Wound Recovery

Bacterial wound infections are a common problem associated with surgical interventions. In particular, biofilm-forming bacteria are hard to eradicate, and alternative methods of treatment based on covering wounds with vascularized flaps of tissue are being developed. The greater omentum is a complex organ covering the intestines in the abdomen, which support wound recovery following surgical procedures and exhibit natural antimicrobial activity that could improve biofilm eradication. We investigated changes in rats’ metabolome following Klebsiella pneumoniae infections, as well as the greater omentum’s ability for Klebsiella pneumoniae biofilm eradication. Rats received either sterile implants or implants covered with Klebsiella pneumoniae biofilm (placed in the peritoneum or greater omentum). Metabolic profiles were monitored at days 0, 2, and 5 after surgery using combined proton nuclear magnetic resonance (1H NMR) and high performance liquid chromatography quadrupole time-of-flight tandem mass spectrometry (LC–QTOF-MS) measurements of urine samples followed by chemometric analysis. Obtained results indicated that grafting of the sterile implant to the greater omentum did not cause major disturbances in rats’ metabolism, whereas the sterile implant located in the peritoneum triggered metabolic perturbations related to tricarboxylic acid (TCA) cycle, as well as choline, tryptophan, and hippurate metabolism. Presence of implants colonized with Klebsiella pneumoniae biofilm resulted in similar levels of metabolic perturbations in both locations. Our findings confirmed that surgical procedures utilizing the greater omentum may have a practical use in wound healing and tissue regeneration in the future.

scholarly journals A Pilot Study on Characteristics of Metabolomics and Lipidomics according to Sasang Constitution

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Min Jung Kim ◽  
Da-Hye Lee ◽  
Jiyun Ahn ◽  
Tae-Youl Ha ◽  
Young Jin Jang ◽  
...  
Keyword(s):  
Pilot Study ◽  
High Performance ◽  
The Other ◽  
Metabolomics Data ◽  
Flight Mass Spectrometry ◽  
Sasang Constitution ◽  
Canonical Pathways ◽  
Phenylalanine Metabolism ◽  
Lipid Metabolites

Although classification of an individual’s Sasang constitution is a key step in the prescription of traditional Korean medicine, the classifying process is complex and not objective. Identification of metabolic-based biomarkers could allow the development of a reliable and sensitive classification technique and even therapeutic management. Our pilot study investigated whether metabolites in plasma are characteristic of Sasang constitutions. Ultra-high-performance liquid chromatography-quadrupole time-of-flight mass spectrometry-based metabolic analysis was conducted against 15 Soyangin (SY), 15 Taeeumin (TE), and 18 Soeumin (SE) individuals, as classified according to the Questionnaire for Sasang Constitution Classification II (QSCC II) and specialist diagnosis. Metabolomics data showed that the TE group was significantly separated from the SY and SE groups. Nine canonical pathways related to constitution; phenylalanine metabolism, aminoacyl-tRNA, tyrosine, and tryptophan biosynthesis were activated in the TE group as compared with the other groups. Similar to the results of the metabolomics analysis, the TE group was also significantly separated from the other two groups by lipidomic analysis. On the other hand, the intensity of lipid metabolites was higher in the SY group than in the other groups. Our findings suggest that the combined analysis of metabolomics and lipidomics can provide useful information for characteristics of Sasang constitutions.

scholarly journals Identifying elephant flows using dynamic thresholds in programmable IXP networks

2020 ◽  
Vol 11 (1) ◽  
Author(s):  
Marcus Vinicius Brito da Silva ◽  
Jonatas Adilson Marques ◽  
Luciano Paschoal Gaspary ◽  
Lisandro Zambenedetti Granville
Keyword(s):  
High Performance ◽  
Autonomous Systems ◽  
Quality Of Services ◽  
Network Behavior ◽  
Dynamic Adjustment ◽  
Identification Process ◽  
Network Utilization ◽  
Data Plane

AbstractInternet eXchange Points (IXPs) are Internet infrastructures composed of high-performance networks that allow multiple autonomous systems to exchange traffic. Given the challenges of managing the flows that cross an IXP, identifying elephant flows may help improve the quality of services provided to its participants. In this context, we leverage the new flexibility and resources of programmable data planes to identify elephant flows in IXP networks adaptively via the dynamic adjustment of thresholds. Our mechanism uses the information reported by the data plane to monitor network utilization in the control plane, calculating new thresholds based on previous flow sizes and durations percentiles and configuring them back into switches to support the local classification of flows. Thus, the thresholds are updated to make the identification process better aligned with the network behavior. The experimental results show that it is possible to identify and react to elephant flows quickly, less than 0.4ms, and efficiently, with only 98.4KB of data inserted into the network by the mechanism. In addition, the threshold updating mechanism achieved accuracy of up to 90% in our evaluation scenarios.

scholarly journals Heart Disease Prediction System Using K- Nearest Neighbour Classification Technique

2019 ◽  
pp. 229-236
Author(s):  
Sowbarnica V. S ◽  
Vismaya V ◽  
Vidhyapoonthalir M ◽  
S. Bhuvana
Keyword(s):  
Heart Disease ◽  
Input Data ◽  
Pso Algorithm ◽  
Support Vector ◽  
Disease Prediction ◽  
Nearest Neighbour ◽  
Prediction System ◽  
Classification Technique

The heart is an operating system of the human body .If it does not function properly it will affect other parts also. Heart disease problem describes a range of conditions that affect your heart. The existing system uses Support Vector Machine (SVM), it propose a system for heart disease prediction. The method will help doctor to explore their data and predict heart disease accurately. The Hospitals do not provide the same quality of service even though they provide the same type of service. The Proposed system includes the following phases: Pre-Processing of the input data with Min-Max scalar and Normalization ,Feature extraction by PSO algorithm, Classification of data by K-Nearest Neighbour. In comparison with the existing approach ,the proposed approach significantly improves the accuracy from 51% to 76.66%.

scholarly journals The impact of the method of extracting metabolic signal from 1H-NMR data on the classification of samples: A case study of binning and BATMAN in lung cancer

PLoS ONE ◽  
2019 ◽  
Vol 14 (2) ◽  
pp. e0211854 ◽  
Author(s):  
Trishanta Padayachee ◽  
Tatsiana Khamiakova ◽  
Evelyne Louis ◽  
Peter Adriaensens ◽  
Tomasz Burzykowski
Keyword(s):  
Lung Cancer ◽  
1H Nmr ◽  
Nmr Data ◽  
Metabolic Signal ◽  
The Impact

scholarly journals Identification of Chemical Markers for the Discrimination of Radix Angelica sinensis Grown in Geoherb and Non-Geoherb Regions Using UHPLC-QTOF-MS/MS Based Metabolomics

Molecules ◽  
2019 ◽  
Vol 24 (19) ◽  
pp. 3536 ◽  
Author(s):  
Kaixue Zhang ◽  
Menglin Yan ◽  
Shu Han ◽  
Longfei Cong ◽  
Liyao Wang ◽  
...  
Keyword(s):  
Nitric Oxide ◽  
Mass Spectrometry ◽  
High Performance Liquid Chromatography ◽  
Liquid Chromatography ◽  
High Performance ◽  
Angelica Sinensis ◽  
Chemical Markers ◽  
Flight Mass Spectrometry ◽  
Senkyunolide I

This research aimed to discover chemical markers for discriminating radix Angelica sinensis (RAS) from different regions and to explore the differences of RAS in the content of four active compounds and anti-inflammatory activities on lipopolysacchride (LPS)-induced RAW264.7 cells and calcium antagonists on the HEK 293T cells of RAS. Nine compounds were selected as characteristic chemical markers by ultra-high-performance liquid chromatography-quadrupole/time-of-flight mass spectrometry (UHPLC-QTOF-MS/MS), based on metabolomics, in order to rapidly discriminate RAS from geoherb and non-geoherb regions. The contents of senkyunolide I and butylidenephthalide in geoherb samples were higher than those in non-geoherb samples, but the contents of ferulic acid and levistolide A were lower in the geoherb samples. Furthermore, the geoherbs showed better nitric oxide (NO) inhibitory and calcium antagonistic activities than the non-geoherbs. These results demonstrate the diversity in quality of RAS between geoherbs and non-geoherbs.

Sign in / Sign up

Export Citation Format

Share Document