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Article ; Online: Metabolite signature of human malignant thyroid tissue: A systematic review and meta-analysis.

Razavi, S Adeleh / Khorsand, Babak / Salehipour, Pouya / Hedayati, Mehdi

2024 Volume 13, Issue 8, Page(s) e7184

Abstract: Background: Thyroid cancer (TC) is the predominant malignancy within the endocrine system. However, the standard method for TC diagnosis lacks the capability to identify the pathological condition of all thyroid lesions. The metabolomics approach has ... ...

Abstract	Background: Thyroid cancer (TC) is the predominant malignancy within the endocrine system. However, the standard method for TC diagnosis lacks the capability to identify the pathological condition of all thyroid lesions. The metabolomics approach has the potential to manage this problem by identifying differential metabolites. Aims: This study conducted a systematic review and meta-analysis of the NMR-based metabolomics studies in order to identify significant altered metabolites associated with TC. Methods: A systematic search of published literature in any language in three databases including Embase, PubMed, and Scopus was conducted. Out of 353 primary articles, 12 studies met the criteria for inclusion in the systematic review. Among these, five reports belonging to three articles were eligible for meta-analysis. The correlation coefficient of the orthogonal partial least squares discriminant analysis, a popular model in the multivariate statistical analysis of metabolomic data, was chosen for meta-analysis. The altered metabolites were chosen based on the fact that they had been found in at least three studies. Results: In total, 49 compounds were identified, 40 of which were metabolites. The increased metabolites in thyroid lesions compared normal samples included lactate, taurine, alanine, glutamic acid, glutamine, leucine, lysine, phenylalanine, serine, tyrosine, valine, choline, glycine, and isoleucine. Lipids were the decreased compounds in thyroid lesions. Lactate and alanine were increased in malignant versus benign thyroid lesions, while, myo-inositol, scyllo-inositol, citrate, choline, and phosphocholine were found to be decreased. The meta-analysis yielded significant results for three metabolites of lactate, alanine, and citrate in malignant versus benign specimens. Discussion: In this study, we provided a concise summary of 12 included metabolomic studies, making it easier for future researchers to compare their results with the prior findings. Conclusion: It appears that the field of TC metabolomics will experience notable advancement, leading to the discovery of trustworthy diagnostic and prognostic biomarkers.
MeSH term(s)	Humans ; Thyroid Neoplasms/metabolism ; Thyroid Neoplasms/pathology ; Thyroid Neoplasms/diagnosis ; Metabolomics/methods ; Metabolome ; Biomarkers, Tumor/metabolism ; Thyroid Gland/metabolism ; Thyroid Gland/pathology ; Magnetic Resonance Spectroscopy/methods
Chemical Substances	Biomarkers, Tumor
Language	English
Publishing date	2024-04-22
Publishing country	United States
Document type	Systematic Review ; Journal Article ; Meta-Analysis ; Research Support, Non-U.S. Gov't ; Review
ZDB-ID	2659751-2
ISSN	2045-7634 ; 2045-7634
ISSN (online)	2045-7634
ISSN	2045-7634
DOI	10.1002/cam4.7184
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Article ; Online: Systematic Review and Dose-Response Meta-Analysis on the Relationship between Different Gluten Doses and Risk of Coeliac Disease Relapse.

Rostami-Nejad, Mohammad / Asri, Nastaran / Olfatifar, Meysam / Khorsand, Babak / Houri, Hamidreza / Rostami, Kamran

Nutrients

2023 Volume 15, Issue 6

Abstract: Gluten proteins are known as immunological triggers for inflammation resulting in mucosal lesions in patients with coeliac disease (CD). Adherence to a strict gluten-free diet (GFD) is currently known as the only effective treatment for CD. In this study, ...

Abstract	Gluten proteins are known as immunological triggers for inflammation resulting in mucosal lesions in patients with coeliac disease (CD). Adherence to a strict gluten-free diet (GFD) is currently known as the only effective treatment for CD. In this study, we performed a systematic review and dose-response meta-analysis on data from previous studies to investigate the association between different gluten doses administered and the risk of CD relapse. Electronic databases were systematically searched to retrieve studies that investigated the response of CD patients to different amounts of gluten intake and evaluated the clinical, serologic, and/or histologic evidence to recognize disease relapse. Study-specific relative risks (RRs) were combined using a random effects model. A total of 440 identified published papers were screened, of which 7 records were selected following full-text reviewing and eligibility assessment for dose-response meta-analysis. According to our analysis, the risk of CD relapse is estimated to be 0.2% (RR: 1.002; 95% CI: 1.001 to 1.004) following the consumption of 6 mg gluten/day, which was increased to 7% (RR: 1.07; 95% CI: 1.03 to 1.10), 50% (RR: 1.50; 95% CI: 1.23 to 1.82), 80% (RR: 1.80; 95% CI: 1.36 to 2.38), and 100% (RR: 2.00; 95% CI: 1.43 to 2.78) by the daily intake of 150, 881, 1276, and 1505 mg gluten, respectively. Although good adherence to a GFD can adequately control CD-related symptoms, disease relapse might happen even with a very low dose of gluten, and the duration of exposure to gluten is also an important matter. The current literature has substantial limitations, such as relying on the data from just a few countries that were different in terms of the amount of gluten administered, the duration of the challenge, etc. Therefore, more randomized clinical trials using a standardized gluten challenge protocol are needed to confirm the findings of the present study.
MeSH term(s)	Humans ; Celiac Disease ; Diet, Gluten-Free ; Glutens/adverse effects ; Treatment Outcome
Chemical Substances	Glutens (8002-80-0)
Language	English
Publishing date	2023-03-14
Publishing country	Switzerland
Document type	Journal Article ; Meta-Analysis ; Systematic Review
ZDB-ID	2518386-2
ISSN	2072-6643 ; 2072-6643
ISSN (online)	2072-6643
ISSN	2072-6643
DOI	10.3390/nu15061390
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Article ; Online: High prevalence of Mucosa-Associated extended-spectrum β-Lactamase-producing Escherichia coli and Klebsiella pneumoniae among Iranain patients with inflammatory bowel disease (IBD).

Kharaghani, Ayda Afshari / Harzandi, Naser / Khorsand, Babak / Rajabnia, Mohsen / Kharaghani, Azin Afshari / Houri, Hamidreza

Annals of clinical microbiology and antimicrobials

2023 Volume 22, Issue 1, Page(s) 86

Abstract: Background: Several pieces of evidence suggest that certain pathobionts belonging to Enterobacterales are associated with the development and progression of inflammatory bowel diseases (IBD). Extended-spectrum β-lactamases (ESBLs) ESBLs are frequently ... ...

Abstract	Background: Several pieces of evidence suggest that certain pathobionts belonging to Enterobacterales are associated with the development and progression of inflammatory bowel diseases (IBD). Extended-spectrum β-lactamases (ESBLs) ESBLs are frequently found in the Enterobacterales members, particularly in Escherichia coli and Klebsiella spp., and might trigger antibiotic-induced perturbations of the intestinal microbiota and led to more severe disease activity in IBD. Therefore, the severity of IBD could be influenced by ESBL-producing Enterobacterales, and hence, this study aimed to investigate the presence of ESBLs and carbapenemases among mucosa-associated E. coli and Klebsiella pneumoniae isolated from colonic biopsies of Iranian patients with IBD. Methods: In this cross-sectional study, E. coli and K. pneumoniae were isolated from inflamed ileum and/or colon tissue of patients with IBD, including Ulcerative colitis (UC) and Crohn's disease (CD), during colonoscopy. Demographic data and clinical characteristics were recorded, and UC and CD disease activity and extent were evaluated according to the full Mayo score and Crohn's disease activity index (CDAI), respectively. Phenotypic and molecular detection of ESBL- and carbapenemase-producing E. coli and Klebsiella pneumoniae were carried out. Disease activity and other clinical and microbial features were compared in patients with and without gut colonization with ESBL producers. Results: A total of 83 IBD patients, including 67 UC and 16 CD, were enrolled in the initial analysis. Intestinal colonization with ESBL-producing E. coli and/or Klebsiella pneumoniae was found in 37 (55.2%) of UC and 9 (56.2%) of DC patients - mostly harbored E. coli containing the bla Conclusion: Intestinal colonization with ESBL producers could arise disease activity in IBD patients. Further large-scale case-control studies should be performed to investigate the possible confounding factors that could contribute to this outcome.
MeSH term(s)	Humans ; Klebsiella pneumoniae/genetics ; Crohn Disease ; Prevalence ; Cross-Sectional Studies ; Escherichia coli/genetics ; Iran/epidemiology ; Inflammatory Bowel Diseases ; beta-Lactamases/genetics
Chemical Substances	beta-Lactamases (EC 3.5.2.6)
Language	English
Publishing date	2023-09-14
Publishing country	England
Document type	Journal Article
ZDB-ID	2097873-X
ISSN	1476-0711 ; 1476-0711
ISSN (online)	1476-0711
ISSN	1476-0711
DOI	10.1186/s12941-023-00630-x
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Article ; Online: Various concentrations of hesperetin induce different types of programmed cell death in human breast cancerous and normal cell lines in a ROS-dependent manner.

Samandari-Bahraseman, Mohammad Rasoul / Khorsand, Babak / Zareei, Sara / Amanlou, Massoud / Rostamabadi, Hanieh

Chemico-biological interactions

2023 Volume 382, Page(s) 110642

Abstract: The polyphenolic component of citrus fruits, hesperetin (Hst), is a metabolite of hesperidin. In this study, we examined the effect of varying doses and exposure times of hesperetin on MCF-7 and MDA-MB-231 cancer cells, as well as MCF-10A normal cells. ... ...

Abstract	The polyphenolic component of citrus fruits, hesperetin (Hst), is a metabolite of hesperidin. In this study, we examined the effect of varying doses and exposure times of hesperetin on MCF-7 and MDA-MB-231 cancer cells, as well as MCF-10A normal cells. By using MTT assay, real-time PCR, western blot, and flow cytometry, we determined the effects of Hst on cell viability, ROS levels, and markers of cell death. Furthermore, molecular docking was used to identify Hst targets that might be involved in ROS-dependent cell death. According to the results, different concentrations of Hst induced different modes of cell death at specific ROS levels. Paraptosis occurred in all cell lines at concentration ranges of IC
MeSH term(s)	Humans ; Female ; Hesperidin/pharmacology ; Reactive Oxygen Species/metabolism ; Molecular Docking Simulation ; Apoptosis ; Cell Line, Tumor ; Superoxide Dismutase/metabolism ; Breast Neoplasms
Chemical Substances	hesperetin (Q9Q3D557F1) ; Hesperidin (E750O06Y6O) ; Reactive Oxygen Species ; Superoxide Dismutase (EC 1.15.1.1)
Language	English
Publishing date	2023-07-23
Publishing country	Ireland
Document type	Journal Article
ZDB-ID	218799-1
ISSN	1872-7786 ; 0009-2797
ISSN (online)	1872-7786
ISSN	0009-2797
DOI	10.1016/j.cbi.2023.110642
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Article: SARS-CoV-2-human protein-protein interaction network.

Khorsand, Babak / Savadi, Abdorreza / Naghibzadeh, Mahmoud

Informatics in medicine unlocked

2020 Volume 20, Page(s) 100413

Abstract: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the novel coronavirus which caused the coronavirus disease 2019 pandemic and infected more than 12 million victims and resulted in over 560,000 deaths in 213 countries around the world. ... ...

Abstract	Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the novel coronavirus which caused the coronavirus disease 2019 pandemic and infected more than 12 million victims and resulted in over 560,000 deaths in 213 countries around the world. Having no symptoms in the first week of infection increases the rate of spreading the virus. The increasing rate of the number of infected individuals and its high mortality necessitates an immediate development of proper diagnostic methods and effective treatments. SARS-CoV-2, similar to other viruses, needs to interact with the host proteins to reach the host cells and replicate its genome. Consequently, virus-host protein-protein interaction (PPI) identification could be useful in predicting the behavior of the virus and the design of antiviral drugs. Identification of virus-host PPIs using experimental approaches are very time consuming and expensive. Computational approaches could be acceptable alternatives for many preliminary investigations. In this study, we developed a new method to predict SARS-CoV-2-human PPIs. Our model is a three-layer network in which the first layer contains the most similar Alphainfluenzavirus proteins to SARS-CoV-2 proteins. The second layer contains protein-protein interactions between Alphainfluenzavirus proteins and human proteins. The last layer reveals protein-protein interactions between SARS-CoV-2 proteins and human proteins by using the clustering coefficient network property on the first two layers. To further analyze the results of our prediction network, we investigated human proteins targeted by SARS-CoV-2 proteins and reported the most central human proteins in human PPI network. Moreover, differentially expressed genes of previous researches were investigated and PPIs of SARS-CoV-2-human network, the human proteins of which were related to upregulated genes, were reported.
Keywords	covid19
Language	English
Publishing date	2020-08-13
Publishing country	England
Document type	Journal Article
ISSN	2352-9148
ISSN	2352-9148
DOI	10.1016/j.imu.2020.100413
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Article: Parallelizing Assignment Problem with DNA Strands.

Khorsand, Babak / Savadi, Abdorreza / Naghibzadeh, Mahmoud

Iranian journal of biotechnology

2020 Volume 18, Issue 1, Page(s) e2547

Abstract: Background: Many problems of combinatorial optimization, which are solvable only in exponential time, are known to be Non-Deterministic Polynomial hard (NP-hard). With the advent of parallel machines, new opportunities have been emerged to develop the ... ...

Abstract	Background: Many problems of combinatorial optimization, which are solvable only in exponential time, are known to be Non-Deterministic Polynomial hard (NP-hard). With the advent of parallel machines, new opportunities have been emerged to develop the effective solutions for NP-hard problems. However, solving these problems in polynomial time needs massive parallel machines and is not applicable up to now. Objectives: DNA (Deoxyribonucleic acid) computing provides a fantastic method to solve NP-hard problems in polynomial time. Accordingly, one of the famous NP-hard problems is assignment problem, which is designed to find the best assignment of n jobs to n persons in a way that it could maximize the profit or minimize the cost. Material and methods: Applying bio molecular operations of Adelman Lipton model, a novel parallel DNA algorithm have been proposed for solving the assignment problem. Results: The proposed algorithm can solve the problem in time complexity, and just O(n Conclusions: In this article, using DNA computing, we proposed a parallel DNA algorithm to solve the assignment problem in linear time.
Language	English
Publishing date	2020-01-01
Publishing country	Iran
Document type	Journal Article
ZDB-ID	2223669-7
ISSN	2322-2921 ; 1728-3043
ISSN (online)	2322-2921
ISSN	1728-3043
DOI	10.30498/IJB.2020.195413.2547
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Article ; Online: Alpha influenza virus infiltration prediction using virus-human protein-protein interaction network.

Khorsand, Babak / Savadi, Abdorreza / Zahiri, Javad / Naghibzadeh, Mahmoud

Mathematical biosciences and engineering : MBE

2020 Volume 17, Issue 4, Page(s) 3109–3129

Abstract: More than ten million deaths make influenza virus one of the deadliest of history. About half a million sever illnesses are annually reported consequent of influenza. Influenza is a parasite which needs the host cellular machinery to replicate its genome. ...

Abstract	More than ten million deaths make influenza virus one of the deadliest of history. About half a million sever illnesses are annually reported consequent of influenza. Influenza is a parasite which needs the host cellular machinery to replicate its genome. To reach the host, viral proteins need to interact with the host proteins. Therefore, identification of host-virus protein interaction network (HVIN) is one of the crucial steps in treating viral diseases. Being expensive, time-consuming and laborious of HVIN experimental identification, force the researches to use computational methods instead of experimental ones to obtain a better understanding of HVIN. In this study, several features are extracted from physicochemical properties of amino acids, combined with different centralities of human protein-protein interaction network (HPPIN) to predict protein-protein interactions between human proteins and Alphainfluenzavirus proteins (HI-PPIs). Ensemble learning methods were used to predict such PPIs. Our model reached 0.93 accuracy, 0.91 sensitivity and 0.95 specificity. Moreover, a database including 694522 new PPIs was constructed by prediction results of the model. Further analysis showed that HPPIN centralities, gene ontology semantic similarity and conjoint triad of virus proteins are the most important features to predict HI-PPIs.
MeSH term(s)	Alphavirus ; Host-Pathogen Interactions ; Humans ; Influenza, Human ; Orthomyxoviridae ; Protein Interaction Mapping ; Protein Interaction Maps
Language	English
Publishing date	2020-09-25
Publishing country	United States
Document type	Journal Article
ZDB-ID	2265126-3
ISSN	1551-0018 ; 1551-0018
ISSN (online)	1551-0018
ISSN	1551-0018
DOI	10.3934/mbe.2020176
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Article ; Online: Comprehensive host-pathogen protein-protein interaction network analysis.

Khorsand, Babak / Savadi, Abdorreza / Naghibzadeh, Mahmoud

BMC bioinformatics

2020 Volume 21, Issue 1, Page(s) 400

Abstract: Background: Infectious diseases are a cruel assassin with millions of victims around the world each year. Understanding infectious mechanism of viruses is indispensable for their inhibition. One of the best ways of unveiling this mechanism is to ... ...

Abstract	Background: Infectious diseases are a cruel assassin with millions of victims around the world each year. Understanding infectious mechanism of viruses is indispensable for their inhibition. One of the best ways of unveiling this mechanism is to investigate the host-pathogen protein-protein interaction network. In this paper we try to disclose many properties of this network. We focus on human as host and integrate experimentally 32,859 interaction between human proteins and virus proteins from several databases. We investigate different properties of human proteins targeted by virus proteins and find that most of them have a considerable high centrality scores in human intra protein-protein interaction network. Investigating human proteins network properties which are targeted by different virus proteins can help us to design multipurpose drugs. Results: As host-pathogen protein-protein interaction network is a bipartite network and centrality measures for this type of networks are scarce, we proposed seven new centrality measures for analyzing bipartite networks. Applying them to different virus strains reveals unrandomness of attack strategies of virus proteins which could help us in drug design hence elevating the quality of life. They could also be used in detecting host essential proteins. Essential proteins are those whose functions are critical for survival of its host. One of the proposed centralities named diversity of predators, outperforms the other existing centralities in terms of detecting essential proteins and could be used as an optimal essential proteins' marker. Conclusions: Different centralities were applied to analyze human protein-protein interaction network and to detect characteristics of human proteins targeted by virus proteins. Moreover, seven new centralities were proposed to analyze host-pathogen protein-protein interaction network and to detect pathogens' favorite host protein victims. Comparing different centralities in detecting essential proteins reveals that diversity of predator (one of the proposed centralities) is the best essential protein marker.
MeSH term(s)	Communicable Diseases/metabolism ; Communicable Diseases/pathology ; Communicable Diseases/virology ; Databases, Protein ; Host-Pathogen Interactions ; Humans ; Protein Interaction Maps ; Proteins/metabolism ; User-Computer Interface ; Viruses/pathogenicity
Chemical Substances	Proteins
Language	English
Publishing date	2020-09-10
Publishing country	England
Document type	Journal Article
ZDB-ID	2041484-5
ISSN	1471-2105 ; 1471-2105
ISSN (online)	1471-2105
ISSN	1471-2105
DOI	10.1186/s12859-020-03706-z
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Article ; Online: Overrepresentation of Enterobacteriaceae and <i>Escherichia coli</i> is the major gut microbiome signature in Crohn's disease and ulcerative colitis; a comprehensive metagenomic analysis of IBDMDB datasets.

Khorsand, Babak / Asadzadeh Aghdaei, Hamid / Nazemalhosseini-Mojarad, Ehsan / Nadalian, Bahareh / Nadalian, Banafsheh / Houri, Hamidreza

Frontiers in cellular and infection microbiology

2022 Volume 12, Page(s) 1015890

Abstract: Objectives: A number of converging strands of research suggest that the intestinal Enterobacteriaceae plays a crucial role in the development and progression of inflammatory bowel disease (IBD), however, the changes in the abundance of ... ...

Abstract	Objectives: A number of converging strands of research suggest that the intestinal Enterobacteriaceae plays a crucial role in the development and progression of inflammatory bowel disease (IBD), however, the changes in the abundance of Enterobacteriaceae species and their related metabolic pathways in Crohn's disease (CD) and ulcerative colitis (UC) compared to healthy people are not fully explained by comprehensive comparative metagenomics analysis. In the current study, we investigated the alternations of the Enterobacterales population in the gut microbiome of patients with CD and UC compared to healthy subjects. Methods: Metagenomic datasets were selected from the Integrative Human Microbiome Project (HMP2) through the Inflammatory Bowel Disease Multi'omics Database (IBDMDB). We performed metagenome-wide association studies on fecal samples from 191 CD patients, 132 UC patients, and 125 healthy controls (HCs). We used the metagenomics dataset to study bacterial community structure, relative abundance, differentially abundant bacteria, functional analysis, and Enterobacteriaceae-related biosynthetic pathways. Results: Compared to the gut microbiome of HCs, six Enterobacteriaceae species were significantly elevated in both CD and UC patients, including Escherichia coli, Klebsiella variicola, Klebsiella quasipneumoniae, Klebsiella pneumoniae, Proteus mirabilis, Citrobacter freundii, and Citrobacter youngae, while Klebsiella oxytoca, Morganella morganii, and Citrobacter amalonaticus were uniquely differentially abundant and enriched in the CD cohort. Four species were uniquely differentially abundant and enriched in the UC cohort, including Citrobacter portucalensis, Citrobacter pasteurii, Citrobacter werkmanii, and Proteus hauseri. Our analysis also showed a dramatically increased abundance of E. coli in their intestinal bacterial community. Biosynthetic pathways of aerobactin siderophore, LPS, enterobacterial common antigen, nitrogen metabolism, and sulfur relay systems encoded by E. coli were significantly elevated in the CD samples compared to the HCs. Menaquinol biosynthetic pathways were associated with UC that belonged to K. pneumoniae strains. Conclusions: In conclusion, compared with healthy people, the taxonomic and functional composition of intestinal bacteria in CD and UC patients was significantly shifted to Enterobacteriaceae species, mainly E. coli and Klebsiella species.
MeSH term(s)	Humans ; Colitis, Ulcerative ; Crohn Disease/microbiology ; Gastrointestinal Microbiome/genetics ; Metagenome ; Escherichia coli ; Siderophores ; Lipopolysaccharides ; Inflammatory Bowel Diseases/microbiology ; Feces/microbiology ; Escherichia coli Infections ; Sulfur ; Nitrogen
Chemical Substances	Siderophores ; Lipopolysaccharides ; Sulfur (70FD1KFU70) ; Nitrogen (N762921K75)
Language	English
Publishing date	2022-10-04
Publishing country	Switzerland
Document type	Journal Article ; Research Support, Non-U.S. Gov't
ZDB-ID	2619676-1
ISSN	2235-2988 ; 2235-2988
ISSN (online)	2235-2988
ISSN	2235-2988
DOI	10.3389/fcimb.2022.1015890
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Article ; Online: Digging deeper into volatile organic compounds associated with cancer.

Janfaza, Sajjad / Khorsand, Babak / Nikkhah, Maryam / Zahiri, Javad

Biology methods & protocols

2019 Volume 4, Issue 1, Page(s) bpz014

Abstract: Volatile organic compounds (VOCs), produced and emitted through the metabolism of cancer cells or the body's immune system, are considered novel cancer biomarkers for diagnostic purposes. Of late, a large number of work has been done to find a ... ...

Abstract	Volatile organic compounds (VOCs), produced and emitted through the metabolism of cancer cells or the body's immune system, are considered novel cancer biomarkers for diagnostic purposes. Of late, a large number of work has been done to find a relationship between VOCs' signature of body and cancer. Cancer-related VOCs can be used to detect several types of cancers at the earlier stages which in turn provide a significantly higher chance of survival. Here we aim to provide an updated picture of cancer-related VOCs based on recent findings in this field focusing on cancer odor database.
Language	English
Publishing date	2019-11-27
Publishing country	England
Document type	Journal Article ; Review
ISSN	2396-8923
ISSN (online)	2396-8923
DOI	10.1093/biomethods/bpz014
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