Journal articles: 'Proteomics and metabolomics'

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Lambert, David G. "Proteomics and metabolomics." Anaesthesia & Intensive Care Medicine 11, no. 9 (September 2010): 372–73. http://dx.doi.org/10.1016/j.mpaic.2010.06.005.

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Lambert, David G. "Proteomics and metabolomics." Anaesthesia & Intensive Care Medicine 14, no. 4 (April 2013): 169–70. http://dx.doi.org/10.1016/j.mpaic.2013.02.007.

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Stubbs, Keith A., and David J. Vocadlo. "Affinity-Based Proteomics Probes; Tools for Studying Carbohydrate-Processing Enzymes." Australian Journal of Chemistry 62, no. 6 (2009): 521. http://dx.doi.org/10.1071/ch09140.

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As more information becomes available through the efforts of high-throughput screens, there is increasing pressure on the three main ‘omic’ fields, genomics, proteomics, and metabolomics, to organize this material into useful libraries that enable further understanding of biological systems. Proteomics especially is faced with two highly challenging tasks. The first is assigning the activity of thousands of putative proteins, the existence of which has been suggested by genomics studies. The second is to serve as a link between genomics and metabolomics by demonstrating which enzymes play roles in specific metabolic pathways. Underscoring these challenges in one area are the thousands of putative carbohydrate-processing enzymes that have been bioinformatically identified, mostly in prokaryotes, but that have unknown or unverified activities. Using two brief examples, we illustrate how biochemical pathways within bacteria that involve carbohydrate-processing enzymes present interesting potential antimicrobial targets, offering a clear motivation for gaining a functional understanding of biological proteomes. One method for studying proteomes that has been developed recently is to use synthetic compounds termed activity-based proteomics probes. Activity-based proteomic profiling using such probes facilitates rapid identification of enzyme activities within proteomes and assignment of function to putative enzymes. Here we discuss the general design principles for these probes with particular reference to carbohydrate-processing enzymes and give an example of using such a probe for the profiling of a bacterial proteome.

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Wu, Xinghong, and Chongge You. "The biomarkers discovery of hyperuricemia and gout: proteomics and metabolomics." PeerJ 11 (January 6, 2022): e14554. http://dx.doi.org/10.7717/peerj.14554.

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Background Hyperuricemia and gout are a group of disorders of purine metabolism. In recent years, the incidence of hyperuricemia and gout has been increasing, which is a severe threat to people’s health. Several studies on hyperuricemia and gout in proteomics and metabolomics have been conducted recently. Some literature has identified biomarkers that distinguish asymptomatic hyperuricemia from acute gout or remission of gout. We summarize the physiological processes in which these biomarkers may be involved and their role in disease progression. Methodology We used professional databases including PubMed, Web of Science to conduct the literature review. This review addresses the current landscape of hyperuricemia and gout biomarkers with a focus on proteomics and metabolomics. Results Proteomic methods are used to identify differentially expressed proteins to find specific biomarkers. These findings may be suggestive for the diagnosis and treatment of hyperuricemia and gout to explore the disease pathogenesis. The identified biomarkers may be mediators of the link between hyperuricemia, gout and kidney disease, metabolic syndrome, diabetes and hypertriglyceridemia. Metabolomics reveals the main influential pathways through small molecule metabolites, such as amino acid metabolism, lipid metabolism, or other characteristic metabolic pathways. These studies have contributed to the discovery of Chinese medicine. Some traditional Chinese medicine compounds can improve the metabolic disorders of the disease. Conclusions We suggest some possible relationships of potential biomarkers with inflammatory episodes, complement activation, and metabolic pathways. These biomarkers are able to distinguish between different stages of disease development. However, there are relatively few proteomic as well as metabolomic studies on hyperuricemia and gout, and some experiments are only primary screening tests, which need further in-depth study.

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Lin, Chuwei, Aneirin Alan Lott, Wei Zhu, Craig P. Dufresne, and Sixue Chen. "Mitogen-Activated Protein Kinase 4-Regulated Metabolic Networks." International Journal of Molecular Sciences 23, no. 2 (January 14, 2022): 880. http://dx.doi.org/10.3390/ijms23020880.

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Mitogen-activated protein kinase 4 (MPK4) was first identified as a negative regulator of systemic acquired resistance. It is also an important kinase involved in many other biological processes in plants, including cytokinesis, reproduction, and photosynthesis. Arabidopsis thaliana mpk4 mutant is dwarf and sterile. Previous omics studies including genomics, transcriptomics, and proteomics have revealed new functions of MPK4 in different biological processes. However, due to challenges in metabolomics, no study has touched upon the metabolomic profiles of the mpk4 mutant. What metabolites and metabolic pathways are potentially regulated by MPK4 are not known. Metabolites are crucial components of plants, and they play important roles in plant growth and development, signaling, and defense. Here we used targeted and untargeted metabolomics to profile metabolites in the wild type and the mpk4 mutant. We found that in addition to the jasmonic acid and salicylic acid pathways, MPK4 is involved in polyamine synthesis and photosynthesis. In addition, we also conducted label-free proteomics of the two genotypes. The integration of metabolomics and proteomics data allows for an insight into the metabolomic networks that are potentially regulated by MPK4.

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Song, Tao, Ying Zhu, Peng Zhang, Minzhu Zhao, Dezhang Zhao, Shijia Ding, Shisheng Zhu, and Jianbo Li. "Integrated Proteomics and Metabolomic Analyses of Plasma Injury Biomarkers in a Serious Brain Trauma Model in Rats." International Journal of Molecular Sciences 20, no. 4 (February 20, 2019): 922. http://dx.doi.org/10.3390/ijms20040922.

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Diffuse axonal injury (DAI) is a prevalent and serious brain injury with significant morbidity and disability. However, the underlying pathogenesis of DAI remains largely unclear, and there are still no objective laboratory-based tests available for clinicians to make an early diagnosis of DAI. An integrated analysis of metabolomic data and proteomic data may be useful to identify all of the molecular mechanisms of DAI and novel potential biomarkers. Therefore, we established a rat model of DAI, and applied an integrated UPLC-Q-TOF/MS-based metabolomics and isobaric tag for relative and absolute quantitation (iTRAQ)-based proteomic analysis to obtain unbiased profiling data. Differential analysis identified 34 metabolites and 43 proteins in rat plasma of the injury group. Two metabolites (acetone and 4-Hydroxybenzaldehyde) and two proteins (Alpha-1-antiproteinase and Alpha-1-acid glycoprotein) were identified as potential biomarkers for DAI, and all may play important roles in the pathogenesis of DAI. Our study demonstrated the feasibility of integrated metabolomics and proteomics method to uncover the underlying molecular mechanisms of DAI, and may help provide clinicians with some novel diagnostic biomarkers and therapeutic targets.

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Perkel, Jeffrey M. "Metabolomics, transcriptomics, proteomics, oh my!" Journal of Proteome Research 7, no. 3 (March 2008): 839. http://dx.doi.org/10.1021/pr083707+.

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Hoffman, Jessica M., Yang Lyu, Scott D. Pletcher, and Daniel E. L. Promislow. "Proteomics and metabolomics in ageing research: from biomarkers to systems biology." Essays in Biochemistry 61, no. 3 (July 11, 2017): 379–88. http://dx.doi.org/10.1042/ebc20160083.

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Age is the single greatest risk factor for a wide range of diseases, and as the mean age of human populations grows steadily older, the impact of this risk factor grows as well. Laboratory studies on the basic biology of ageing have shed light on numerous genetic pathways that have strong effects on lifespan. However, we still do not know the degree to which the pathways that affect ageing in the lab also influence variation in rates of ageing and age-related disease in human populations. Similarly, despite considerable effort, we have yet to identify reliable and reproducible ‘biomarkers’, which are predictors of one’s biological as opposed to chronological age. One challenge lies in the enormous mechanistic distance between genotype and downstream ageing phenotypes. Here, we consider the power of studying ‘endophenotypes’ in the context of ageing. Endophenotypes are the various molecular domains that exist at intermediate levels of organization between the genotype and phenotype. We focus our attention specifically on proteins and metabolites. Proteomic and metabolomic profiling has the potential to help identify the underlying causal mechanisms that link genotype to phenotype. We present a brief review of proteomics and metabolomics in ageing research with a focus on the potential of a systems biology and network-centric perspective in geroscience. While network analyses to study ageing utilizing proteomics and metabolomics are in their infancy, they may be the powerful model needed to discover underlying biological processes that influence natural variation in ageing, age-related disease, and longevity.

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Govorov, Igor, Stanislav Sitkin, Tatyana Pervunina, Alexey Moskvin, Denis Baranenko, and Eduard Komlichenko. "Metabolomic Biomarkers in Gynecology: A Treasure Path or a False Path?" Current Medicinal Chemistry 27, no. 22 (June 30, 2020): 3611–22. http://dx.doi.org/10.2174/0929867326666190104124245.

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Omic-technologies (genomics, transcriptomics, proteomics and metabolomics) have become more important in current medical science. Among them, it is metabolomics that most accurately reflects the minor changes in body functioning, as it focuses on metabolome – the group of the metabolism products, both intermediate and end. Therefore, metabolomics is actively engaged in fundamental and clinical studies and search for potential biomarkers. The biomarker could be used in diagnostics, management and stratification of the patients, as well as in prognosing the outcomes. The good example is gynecology, since many gynecological diseases lack effective biomarkers. In the current review, we aimed to summarize the results of the studies, devoted to the search of potential metabolomic biomarkers for the most common gynecological diseases.

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Yates, John R. "Rising Stars in Proteomics and Metabolomics." Journal of Proteome Research 20, no. 2 (January 14, 2021): 1105–6. http://dx.doi.org/10.1021/acs.jproteome.0c01026.

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Christians, Uwe, Jelena Klawitter, and Jost Klawitter. "Biomarkers in Transplantation—Proteomics and Metabolomics." Therapeutic Drug Monitoring 38 (April 2016): S70—S74. http://dx.doi.org/10.1097/ftd.0000000000000243.

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Marx, David, Jochen Metzger, Martin Pejchinovski, Ryan Bruce Gil, Maria Frantzi, Agnieszka Latosinska, Iwona Belczacka, et al. "Proteomics and Metabolomics for AKI Diagnosis." Seminars in Nephrology 38, no. 1 (January 2018): 63–87. http://dx.doi.org/10.1016/j.semnephrol.2017.09.007.

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Gahlaut, Anjum, Vikas, Monika Dahiya, Ashish Gothwal, Mahesh Kulharia, Anil K. Chhillar, Vikas Hooda, and Rajesh Dabur. "Proteomics & metabolomics: Mapping biochemical regulations." Drug Invention Today 5, no. 4 (December 2013): 321–26. http://dx.doi.org/10.1016/j.dit.2013.08.007.

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Karjalainen, Erkki J. "Linking medicine to metabolomics and proteomics." European Journal of Pharmaceutical Sciences 34, no. 1 (June 2008): S23. http://dx.doi.org/10.1016/j.ejps.2008.02.056.

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Resurreccion, Eleazer P., and Ka-wing Fong. "The Integration of Metabolomics with Other Omics: Insights into Understanding Prostate Cancer." Metabolites 12, no. 6 (May 27, 2022): 488. http://dx.doi.org/10.3390/metabo12060488.

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Our understanding of prostate cancer (PCa) has shifted from solely caused by a few genetic aberrations to a combination of complex biochemical dysregulations with the prostate metabolome at its core. The role of metabolomics in analyzing the pathophysiology of PCa is indispensable. However, to fully elucidate real-time complex dysregulation in prostate cells, an integrated approach based on metabolomics and other omics is warranted. Individually, genomics, transcriptomics, and proteomics are robust, but they are not enough to achieve a holistic view of PCa tumorigenesis. This review is the first of its kind to focus solely on the integration of metabolomics with multi-omic platforms in PCa research, including a detailed emphasis on the metabolomic profile of PCa. The authors intend to provide researchers in the field with a comprehensive knowledge base in PCa metabolomics and offer perspectives on overcoming limitations of the tool to guide future point-of-care applications.

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Guo, Qi, Xiang Hui Qi, and Ya Ping Zhou. "Metabonomics and the Research of Traditional Chinese Medicine." Advanced Materials Research 396-398 (November 2011): 1676–79. http://dx.doi.org/10.4028/www.scientific.net/amr.396-398.1676.

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Metabolomics is another important branch of systems biology after genomics, transcriptomics and proteomics and a new kind of holistic analysis technology. As part of Metabolomics is another important branch of systems biology after genomics, transcriptomics and proteomics and a new kind of holistic analysis technology. As part of system biology, the core of metabolomics is qualitative and quantitative analysis of all small molecule metabolites in a cell or biological system at specific time and conditions. The field of metabolomics study covers the diagnosis, nutrition, microbiology, environmental science, mechanism of drug action, toxicology and other aspects of botany. The metabolomics study of the traditional Chinese medicine (TCM) mainly focus on the safety evaluation of drugs, efficacy mechanism of traditional Chinese medicine, the variety and the quality control of Chinese medicine resources and so on. This paper provides an overview of metabolomics study of TCM.

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Jin, Qiao, and Ronald Ching Wan Ma. "Metabolomics in Diabetes and Diabetic Complications: Insights from Epidemiological Studies." Cells 10, no. 11 (October 21, 2021): 2832. http://dx.doi.org/10.3390/cells10112832.

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The increasing prevalence of diabetes and its complications, such as cardiovascular and kidney disease, remains a huge burden globally. Identification of biomarkers for the screening, diagnosis, and prognosis of diabetes and its complications and better understanding of the molecular pathways involved in the development and progression of diabetes can facilitate individualized prevention and treatment. With the advancement of analytical techniques, metabolomics can identify and quantify multiple biomarkers simultaneously in a high-throughput manner. Providing information on underlying metabolic pathways, metabolomics can further identify mechanisms of diabetes and its progression. The application of metabolomics in epidemiological studies have identified novel biomarkers for type 2 diabetes (T2D) and its complications, such as branched-chain amino acids, metabolites of phenylalanine, metabolites involved in energy metabolism, and lipid metabolism. Metabolomics have also been applied to explore the potential pathways modulated by medications. Investigating diabetes using a systems biology approach by integrating metabolomics with other omics data, such as genetics, transcriptomics, proteomics, and clinical data can present a comprehensive metabolic network and facilitate causal inference. In this regard, metabolomics can deepen the molecular understanding, help identify potential therapeutic targets, and improve the prevention and management of T2D and its complications. The current review focused on metabolomic biomarkers for kidney and cardiovascular disease in T2D identified from epidemiological studies, and will also provide a brief overview on metabolomic investigations for T2D.

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Yu, Shouzhi, Yao He, Wenheng Ji, Rong Yang, Yuxiu Zhao, Yan Li, Yingwei Liu, et al. "Metabolic and Proteomic Profiles Associated with Immune Responses Induced by Different Inactivated SARS-CoV-2 Vaccine Candidates." International Journal of Molecular Sciences 23, no. 18 (September 13, 2022): 10644. http://dx.doi.org/10.3390/ijms231810644.

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Since the emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) in late 2019, the virus has been mutating continuously, resulting in the continuous emergence of variants and creating challenges for epidemic prevention and control. Here, we immunized mice with different vaccine candidates, revealing the immune, protein, and metabolomic changes that take place in vaccines composed of different variants. We found that the prototype strain and Delta- and Omicron-variant inactivated vaccine candidates could all induce a high level of neutralizing antibodies and cellular immunity responses in mice. Next, we found that the metabolic and protein profiles were changed, showing a positive association with immune responses, and the level of the change was distinct in different inactivated vaccines, indicating that amino acid variations could affect metabolomics and proteomics. Our findings reveal differences between vaccines at the metabolomic and proteomic levels. These insights provide a novel direction for the immune evaluation of vaccines and could be used to guide novel strategies for vaccine design.

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Maity, Sudipa, Ivana Rubić, Josipa Kuleš, Anita Horvatić, Dražen Đuričić, Marko Samardžija, Blanka Beer Ljubić, et al. "Integrated Metabolomics and Proteomics Dynamics of Serum Samples Reveals Dietary Zeolite Clinoptilolite Supplementation Restores Energy Balance in High Yielding Dairy Cows." Metabolites 11, no. 12 (December 5, 2021): 842. http://dx.doi.org/10.3390/metabo11120842.

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Dairy cows can suffer from a negative energy balance (NEB) during their transition from the dry period to early lactation, which can increase the risk of postpartum diseases such as clinical ketosis, mastitis, and fatty liver. Zeolite clinoptilolite (CPL), due to its ion-exchange property, has often been used to treat NEB in animals. However, limited information is available on the dynamics of global metabolomics and proteomic profiles in serum that could provide a better understanding of the associated altered biological pathways in response to CPL. Thus, in the present study, a total 64 serum samples were collected from 8 control and 8 CPL-treated cows at different time points in the prepartum and postpartum stages. Labelled proteomics and untargeted metabolomics resulted in identification of 64 and 21 differentially expressed proteins and metabolites, respectively, which appear to play key roles in restoring energy balance (EB) after CPL supplementation. Joint pathway and interaction analysis revealed cross-talks among valproic acid, leucic acid, glycerol, fibronectin, and kinninogen-1, which could be responsible for restoring NEB. By using a global proteomics and metabolomics strategy, the present study concluded that CPL supplementation could lower NEB in just a few weeks, and explained the possible underlying pathways employed by CPL.

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Ahmed, Munazza, Ahlam M. Semreen, Waseem El-Huneidi, Yasser Bustanji, Eman Abu-Gharbieh, Mohammad A. Y. Alqudah, Ahmed Alhusban, et al. "Preclinical and Clinical Applications of Metabolomics and Proteomics in Glioblastoma Research." International Journal of Molecular Sciences 24, no. 1 (December 25, 2022): 348. http://dx.doi.org/10.3390/ijms24010348.

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Glioblastoma (GB) is a primary malignancy of the central nervous system that is classified by the WHO as a grade IV astrocytoma. Despite decades of research, several aspects about the biology of GB are still unclear. Its pathogenesis and resistance mechanisms are poorly understood, and methods to optimize patient diagnosis and prognosis remain a bottle neck owing to the heterogeneity of the malignancy. The field of omics has recently gained traction, as it can aid in understanding the dynamic spatiotemporal regulatory network of enzymes and metabolites that allows cancer cells to adjust to their surroundings to promote tumor development. In combination with other omics techniques, proteomic and metabolomic investigations, which are a potent means for examining a variety of metabolic enzymes as well as intermediate metabolites, might offer crucial information in this area. Therefore, this review intends to stress the major contribution these tools have made in GB clinical and preclinical research and highlights the crucial impacts made by the integrative “omics” approach in reducing some of the therapeutic challenges associated with GB research and treatment. Thus, our study can purvey the use of these powerful tools in research by serving as a hub that particularly summarizes studies employing metabolomics and proteomics in the realm of GB diagnosis, treatment, and prognosis.

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Sakallioglu, Isin Tuna, Bridget Tripp, Jacy Kubik, Carol A. Casey, Paul Thomes, and Robert Powers. "Multiomics Approach Captures Hepatic Metabolic Network Altered by Chronic Ethanol Administration." Biology 12, no. 1 (December 23, 2022): 28. http://dx.doi.org/10.3390/biology12010028.

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Using a multiplatform and multiomics approach, we identified metabolites, lipids, proteins, and metabolic pathways that were altered in the liver after chronic ethanol administration. A functional enrichment analysis of the multiomics dataset revealed that rats treated with ethanol experienced an increase in hepatic fatty acyl content, which is consistent with an initial development of steatosis. The nuclear magnetic resonance spectroscopy (NMR) and liquid chromatography–mass spectrometry (LC-MS) metabolomics data revealed that the chronic ethanol exposure selectively modified toxic substances such as an increase in glucuronidation tyramine and benzoyl; and a depletion in cholesterol-conjugated glucuronides. Similarly, the lipidomics results revealed that ethanol decreased diacylglycerol, and increased triacylglycerol, sterol, and cholesterol biosynthesis. An integrated metabolomics and lipidomics pathway analysis showed that the accumulation of hepatic lipids occurred by ethanol modulation of the upstream lipid regulatory pathways, specifically glycolysis and glucuronides pathways. A proteomics analysis of lipid droplets isolated from control EtOH-fed rats and a subsequent functional enrichment analysis revealed that the proteomics data corroborated the metabolomic and lipidomic findings that chronic ethanol administration altered the glucuronidation pathway.

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Chen, Zsu-Zsu, and Robert E. Gerszten. "Metabolomics and Proteomics in Type 2 Diabetes." Circulation Research 126, no. 11 (May 22, 2020): 1613–27. http://dx.doi.org/10.1161/circresaha.120.315898.

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The persistent increase in the worldwide burden of type 2 diabetes mellitus (T2D) and the accompanying rise of its complications, including cardiovascular disease, necessitates our understanding of the metabolic disturbances that cause diabetes mellitus. Metabolomics and proteomics, facilitated by recent advances in high-throughput technologies, have given us unprecedented insight into circulating biomarkers of T2D even over a decade before overt disease. These markers may be effective tools for diabetes mellitus screening, diagnosis, and prognosis. As participants of metabolic pathways, metabolite and protein markers may also highlight pathways involved in T2D development. The integration of metabolomics and proteomics with genomics in multiomics strategies provides an analytical method that can begin to decipher causal associations. These methods are not without their limitations; however, with careful study design and sample handling, these methods represent powerful scientific tools that can be leveraged for the study of T2D. In this article, we aim to give a timely overview of circulating metabolomics and proteomics findings with T2D observed in large human population studies to provide the reader with a snapshot into these emerging fields of research.

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Carulli, Lucia, Giulia Zanca, Filippo Schepis, and Erica Villa. "The OMICs Window into Nonalcoholic Fatty Liver Disease (NAFLD)." Metabolites 9, no. 2 (February 1, 2019): 25. http://dx.doi.org/10.3390/metabo9020025.

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Nonalcoholic fatty liver disease (NAFLD) is a common cause of hepatic abnormalities worldwide. Nonalcoholic steatohepatitis (NASH) is part of the spectrum of NAFLD and leads to progressive liver disease, such as cirrhosis and hepatocellular carcinoma. In NASH patient, fibrosis represents the major predictor of liver-related mortality; therefore, it is important to have an early and accurate diagnosis of NASH. The current gold standard for the diagnosis of NASH is still liver biopsy. The development of biomarkers able to predict disease severity, prognosis, as well as response to therapy without the need for a biopsy is the focus of most up-to-date genomic, transcriptomic, proteomic, and metabolomic research. In the future, patients might be diagnosed and treated according to their molecular signatures. In this short review, we discuss how information from genomics, proteomics, and metabolomics contribute to the understanding of NAFLD pathogenesis.

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D’Alessandro, Angelo, and Lello Zolla. "Proteomics and metabolomics in cancer drug development." Expert Review of Proteomics 10, no. 5 (October 2013): 473–88. http://dx.doi.org/10.1586/14789450.2013.840440.

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Liessi, Nara, Nicoletta Pedemonte, Andrea Armirotti, and Clarissa Braccia. "Proteomics and Metabolomics for Cystic Fibrosis Research." International Journal of Molecular Sciences 21, no. 15 (July 30, 2020): 5439. http://dx.doi.org/10.3390/ijms21155439.

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The aim of this review article is to introduce the reader to the state-of-the-art of the contribution that proteomics and metabolomics sciences are currently providing for cystic fibrosis (CF) research: from the understanding of cystic fibrosis transmembrane conductance regulator (CFTR) biology to biomarker discovery for CF diagnosis. Our work particularly focuses on CFTR post-translational modifications and their role in cellular trafficking as well as on studies that allowed the identification of CFTR molecular interactors. We also show how metabolomics is currently helping biomarker discovery in CF. The most recent advances in these fields are covered by this review, as well as some considerations on possible future scenarios for new applications.

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Walton, Thomas E. F., and Samuel P. Desbruslais. "Omics and anaesthesia: pharmacogenomics, proteomics and metabolomics." Anaesthesia & Intensive Care Medicine 23, no. 3 (March 2022): 188–93. http://dx.doi.org/10.1016/j.mpaic.2021.11.011.

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Yau, Yunki, Rupert W. Leong, Ming Zeng, and Valerie C. Wasinger. "Proteomics and metabolomics in inflammatory bowel disease." Journal of Gastroenterology and Hepatology 28, no. 7 (June 20, 2013): 1076–86. http://dx.doi.org/10.1111/jgh.12193.

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Vora, Niraj, Ram Kalagiri, Lea H. Mallett, Jin Ho Oh, Umaima Wajid, Saef Munir, Natalie Colon, Venkata Nakta Raju, Madhava R. Beeram, and M. Nasir Uddin. "Proteomics and Metabolomics in Pregnancy—An Overview." Obstetrical & Gynecological Survey 74, no. 2 (February 2019): 111–25. http://dx.doi.org/10.1097/ogx.0000000000000646.

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Banks, David. "Proteomics: A Frontier between Genomics and Metabolomics." CHANCE 16, no. 4 (September 2003): 6–7. http://dx.doi.org/10.1080/09332480.2003.10554867.

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Mayr, Manuel, Basetti Madhu, and Qingbo Xu. "Proteomics and Metabolomics Combined in Cardiovascular Research." Trends in Cardiovascular Medicine 17, no. 2 (February 2007): 43–48. http://dx.doi.org/10.1016/j.tcm.2006.11.004.

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Mayr, Manuel, Ursula Mayr, Yuen-Li Chung, Xiaoke Yin, John R. Griffiths, and Qingbo Xu. "Combining proteomics and metabolomics in vascular research." Vascular Pharmacology 45, no. 3 (September 2006): 185. http://dx.doi.org/10.1016/j.vph.2006.08.032.

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Lambert, David G. "Omics and anaesthesia: pharmacogenomics, proteomics and metabolomics." Anaesthesia & Intensive Care Medicine 17, no. 4 (April 2016): 209–13. http://dx.doi.org/10.1016/j.mpaic.2016.01.002.

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Walton, Thomas E. F., and Jonathan N. Rajan. "Omics and anaesthesia: pharmacogenomics, proteomics and metabolomics." Anaesthesia & Intensive Care Medicine 20, no. 4 (April 2019): 248–53. http://dx.doi.org/10.1016/j.mpaic.2019.01.019.

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Horgan, Richard P., and Louise C. Kenny. "‘Omic’ technologies: genomics, transcriptomics, proteomics and metabolomics." Obstetrician & Gynaecologist 13, no. 3 (July 2011): 189–95. http://dx.doi.org/10.1576/toag.13.3.189.27672.

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Rigobello-Masini, Marilda, José Carlos Pires Penteado, and Jorge Cesar Masini. "Monolithic columns in plant proteomics and metabolomics." Analytical and Bioanalytical Chemistry 405, no. 7 (December 7, 2012): 2107–22. http://dx.doi.org/10.1007/s00216-012-6574-6.

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Patti, Gary J., Ralf Tautenhahn, Bryan R. Fonslow, Yonghoon Cho, Adam Deutschbauer, Adam Arkin, Trent Northen, and Gary Siuzdak. "Meta-analysis of global metabolomics and proteomics data to link alterations with phenotype." Spectroscopy 26, no. 3 (2011): 151–54. http://dx.doi.org/10.1155/2011/923017.

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Global metabolomics has emerged as a powerful tool to interrogate cellular biochemistry at the systems level by tracking alterations in the levels of small molecules. One approach to define cellular dynamics with respect to this dysregulation of small molecules has been to consider metabolic flux as a function of time. While flux measurements have proven effective for model organisms, acquiring multiple time points at appropriate temporal intervals for many sample types (e.g., clinical specimens) is challenging. As an alternative, meta-analysis provides another strategy for delineating metabolic cause and effect perturbations. That is, the combination of untargeted metabolomic data from multiple pairwise comparisons enables the association of specific changes in small molecules with unique phenotypic alterations. We recently developed metabolomic software called metaXCMS to automate these types of higher order comparisons. Here we discuss the potential of metaXCMS for analyzing proteomic datasets and highlight the biological value of combining meta-results from both metabolomic and proteomic analyses. The combined meta-analysis has the potential to facilitate efforts in functional genomics and the identification of metabolic disruptions related to disease pathogenesis.

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Guo, Zhaojuan, Yuanyuan Shi, Bingqian Jiang, Xiyi Peng, Lin Zhang, Can Tu, and Ting Wang. "Psoraleae Fructus Ethanol Extract Induced Hepatotoxicity via Impaired Lipid Metabolism Caused by Disruption of Fatty Acid β-Oxidation." Oxidative Medicine and Cellular Longevity 2023 (January 7, 2023): 1–17. http://dx.doi.org/10.1155/2023/4202861.

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Herb-induced liver injury (HILI) is gradually increasing, and Psoraleae Fructus (PF) has been reported to induce hepatotoxicity. However, its underlying toxicity mechanism has been only poorly revealed. In this paper, we attempted to explore the liver injury and mechanism caused by Psoraleae Fructus ethanol extract (PFE). First, we administered PFE to mice for 4 weeks and evaluated their serum liver function indices. H&E staining was performed to observe the pathological changes of the livers. Oil red O staining was used to visualize hepatic lipids. Serum-untargeted metabolomics and liver proteomics were used to explore the mechanism of PF hepatotoxicity, and transmission electron microscopy was determined to assess mitochondria and western blot to determine potential target proteins expression. The results showed that PFE caused abnormal liver biochemical indicators and liver tissue injury in mice, and there was substantial fat accumulation in liver tissue in this group. Furthermore, metabolomic analysis showed that PFE changed bile acid synthesis, lipid metabolism, etc., and eight metabolites, including linoleic acid, which could be used as potential biomarkers of PFE hepatotoxicity. Proteomic analysis revealed that differential proteins were clustered in the mitochondrial transmembrane transport, the long-chain fatty acid metabolic process and purine ribonucleotide metabolic process. Multiomics analysis showed that eight pathways were enriched in both metabolomics and proteomics, such as bile secretion, unsaturated fatty acid biosynthesis, and linoleic acid metabolism. The downregulation of SLC27A5, CPT1A, NDUFB5, and COX6A1 and upregulation of cytochrome C and ABCC3 expressions also confirmed the impaired fatty acid oxidative catabolism. Altogether, this study revealed that PFE induced hepatotoxicity by damaging mitochondria, reducing fatty acid β-oxidation levels, and inhibiting fatty acids ingested by bile acids.

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Raja, Ganesan, Yoon-Kwan Jang, Jung-Soo Suh, Heon-Su Kim, Sang Hyun Ahn, and Tae-Jin Kim. "Microcellular Environmental Regulation of Silver Nanoparticles in Cancer Therapy: A Critical Review." Cancers 12, no. 3 (March 12, 2020): 664. http://dx.doi.org/10.3390/cancers12030664.

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Silver nanoparticles (AgNPs) play significant roles in various cancer cells such as functional heterogeneity, microenvironmental differences, and reversible changes in cell properties (e.g., chemotherapy). There is a lack of targets for processes involved in tumor cellular heterogeneity, such as metabolic clampdown, cytotoxicity, and genotoxicity, which hinders microenvironmental biology. Proteogenomics and chemical metabolomics are important tools that can be used to study proteins/genes and metabolites in cells, respectively. Chemical metabolomics have many advantages over genomics, transcriptomics, and proteomics in anticancer therapy. However, recent studies with AgNPs have revealed considerable genomic and proteomic changes, particularly in genes involved in tumor suppression, apoptosis, and oxidative stress. Metabolites interact biochemically with energy storage, neurotransmitters, and antioxidant defense systems. Mechanobiological studies of AgNPs in cancer metabolomics suggest that AgNPs may be promising tools that can be exploited to develop more robust and effective adaptive anticancer therapies. Herein, we present a proof-of-concept review for AgNPs-based proteogenomics and chemical metabolomics from various tumor cells with the help of several technologies, suggesting their promising use as drug carriers for cancer therapy.

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Matysiak, Jan, Paweł Dereziński, Agnieszka Klupczyńska, Joanna Hajduk, Agata Światły, Szymon Plewa, Agnieszka Horała, et al. "Proteomic and metabolomic strategy of searching for biomarkers of genital cancer diseases using mass spectrometry methods." Journal of Medical Science 85, no. 4 (December 29, 2016): 330–33. http://dx.doi.org/10.20883/jms.2016.180.

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The project entitled ”Proteomic and metabolomic strategy of searching for biomarkers of genital cancer diseases using mass spectrometry methods” is a study based on novel omics techniques. The main assumption of this research is the development of innovative model of searching of biomarkers in ovarian and prostate cancers using proteomics and metabolomics methodologies supported by bioinformatics analysis. The innovatory strategy based on the latest achievements in the field of mass spectrometry will allow for the implementation of the unique studies for discovery new biomarkers, which are useful in prediction, diagnosis and treatment of the genital cancers. To date, there is no comprehensive data including set of proteins and other endogenous compounds involved in the development and differentiation of these diseases. Therefore, the proposed approach may contribute to the discovery of biomarkers with high sensitivity and specificity, which will provide new information about genital cancers characterization.

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Matysiak, Jan, Paweł Dereziński, Agnieszka Klupczyńska, Joanna Hajduk, Agata Światły, Szymon Plewa, Agnieszka Horała, et al. "Proteomic and metabolomic strategy of searching for biomarkers of genital cancer diseases using mass spectrometry methods." Journal of Medical Science 85, no. 4 (December 29, 2016): 330. http://dx.doi.org/10.20883/180.

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The project entitled ”Proteomic and metabolomic strategy of searching for biomarkers of genital cancer diseases using mass spectrometry methods” is a study based on novel omics techniques. The main assumption of this research is the development of innovative model of searching of biomarkers in ovarian and prostate cancers using proteomics and metabolomics methodologies supported by bioinformatics analysis. The innovatory strategy based on the latest achievements in the field of mass spectrometry will allow for the implementation of the unique studies for discovery new biomarkers, which are useful in prediction, diagnosis and treatment of the genital cancers. To date, there is no comprehensive data including set of proteins and other endogenous compounds involved in the development and differentiation of these diseases. Therefore, the proposed approach may contribute to the discovery of biomarkers with high sensitivity and specificity, which will provide new information about genital cancers characterization.

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Tshikhudo, Phumudzo, Khayalethu Ntushelo, Fhatuwani Mudau, Bahare Salehi, Mehdi Sharifi-Rad, Natália Martins, Miquel Martorell, and Javad Sharifi-Rad. "Understanding Camellia sinensis using Omics Technologies along with Endophytic Bacteria and Environmental Roles on Metabolism: A Review." Applied Sciences 9, no. 2 (January 14, 2019): 281. http://dx.doi.org/10.3390/app9020281.

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Camellia sinensis is the most consumed beverage worldwide. It contains a wide variety of secondary metabolites, such as alkaloids, saponins, tannins, catechins, and polyphenols, generated through a condensation reaction of cinnamic acid with three malonyl-CoA groups. In addition to the metabolic processes occurring within this plant, there are also some plant-associated bacterial endophytes. These bacteria reside in the living tissues of the host plants without causing any harmful effect to them, thereby stimulating secondary metabolite production with a diverse range of biological effects. Omics technologies reveal understanding of the biological phenomena of transcriptomics, proteomics, and metabolomics. In this sense, the present review aims to provide a comprehensive review of various methods used to identify distinct plant compounds, namely transcriptomic, proteomic, and metabolomic analysis. The role of endophytic bacteria in C. sinensis metabolism, and C. sinensis antioxidant and antimicrobial effects, are also carefully highlighted.

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KOLCH, Walter, Harald MISCHAK, and Andrew R. PITT. "The molecular make-up of a tumour: proteomics in cancer research." Clinical Science 108, no. 5 (April 22, 2005): 369–83. http://dx.doi.org/10.1042/cs20050006.

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The enormous progress in proteomics, enabled by recent advances in MS (mass spectrometry), has brought protein analysis back into the limelight of cancer research, reviving old areas as well as opening new fields of study. In this review, we discuss the basic features of proteomic technologies, including the basics of MS, and we consider the main current applications and challenges of proteomics in cancer research, including (i) protein expression profiling of tumours, tumour fluids and tumour cells; (ii) protein microarrays; (iii) mapping of cancer signalling pathways; (iv) pharmacoproteomics; (v) biomarkers for diagnosis, staging and monitoring of the disease and therapeutic response; and (vi) the immune response to cancer. All these applications continue to benefit from further technological advances, such as the development of quantitative proteomics methods, high-resolution, high-speed and high-sensitivity MS, functional protein assays, and advanced bioinformatics for data handling and interpretation. A major challenge will be the integration of proteomics with genomics and metabolomics data and their functional interpretation in conjunction with clinical results and epidemiology.

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Dubin, Ruth F., and Eugene P. Rhee. "Proteomics and Metabolomics in Kidney Disease, including Insights into Etiology, Treatment, and Prevention." Clinical Journal of the American Society of Nephrology 15, no. 3 (October 21, 2019): 404–11. http://dx.doi.org/10.2215/cjn.07420619.

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In this review of the application of proteomics and metabolomics to kidney disease research, we review key concepts, highlight illustrative examples, and outline future directions. The proteome and metabolome reflect the influence of environmental exposures in addition to genetic coding. Circulating levels of proteins and metabolites are dynamic and modifiable, and thus amenable to therapeutic targeting. Design and analytic considerations in proteomics and metabolomics studies should be tailored to the investigator’s goals. For the identification of clinical biomarkers, adjustment for all potential confounding variables, particularly GFR, and strict significance thresholds are warranted. However, this approach has the potential to obscure biologic signals and can be overly conservative given the high degree of intercorrelation within the proteome and metabolome. Mass spectrometry, often coupled to up-front chromatographic separation techniques, is a major workhorse in both proteomics and metabolomics. High-throughput antibody- and aptamer-based proteomic platforms have emerged as additional, powerful approaches to assay the proteome. As the breadth of coverage for these methodologies continues to expand, machine learning tools and pathway analyses can help select the molecules of greatest interest and categorize them in distinct biologic themes. Studies to date have already made a substantial effect, for example elucidating target antigens in membranous nephropathy, identifying a signature of urinary peptides that adds prognostic information to urinary albumin in CKD, implicating circulating inflammatory proteins as potential mediators of diabetic nephropathy, demonstrating the key role of the microbiome in the uremic milieu, and highlighting kidney bioenergetics as a modifiable factor in AKI. Additional studies are required to replicate and expand on these findings in independent cohorts. Further, more work is needed to understand the longitudinal trajectory of select protein and metabolite markers, perform transomics analyses within merged datasets, and incorporate more kidney tissue–based investigation.

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Castellano-Escuder, Pol, Raúl González-Domínguez, Francesc Carmona-Pontaque, Cristina Andrés-Lacueva, and Alex Sánchez-Pla. "POMAShiny: A user-friendly web-based workflow for metabolomics and proteomics data analysis." PLOS Computational Biology 17, no. 7 (July 1, 2021): e1009148. http://dx.doi.org/10.1371/journal.pcbi.1009148.

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Metabolomics and proteomics, like other omics domains, usually face a data mining challenge in providing an understandable output to advance in biomarker discovery and precision medicine. Often, statistical analysis is one of the most difficult challenges and it is critical in the subsequent biological interpretation of the results. Because of this, combined with the computational programming skills needed for this type of analysis, several bioinformatic tools aimed at simplifying metabolomics and proteomics data analysis have emerged. However, sometimes the analysis is still limited to a few hidebound statistical methods and to data sets with limited flexibility. POMAShiny is a web-based tool that provides a structured, flexible and user-friendly workflow for the visualization, exploration and statistical analysis of metabolomics and proteomics data. This tool integrates several statistical methods, some of them widely used in other types of omics, and it is based on the POMA R/Bioconductor package, which increases the reproducibility and flexibility of analyses outside the web environment. POMAShiny and POMA are both freely available at https://github.com/nutrimetabolomics/POMAShiny and https://github.com/nutrimetabolomics/POMA, respectively.

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Tounta, Vivian, Yi Liu, Ashleigh Cheyne, and Gerald Larrouy-Maumus. "Metabolomics in infectious diseases and drug discovery." Molecular Omics 17, no. 3 (2021): 376–93. http://dx.doi.org/10.1039/d1mo00017a.

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Rukayadi, Yaya. "THE ROLE OF OMICS RESEARCH IN GERMPLASM CONSERVATION." Prosiding Seminar Nasional Biotik 9, no. 2 (June 29, 2022): 1. http://dx.doi.org/10.22373/pbio.v9i2.11355.

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The word omics refers to a field of study in biological sciences that ends with -omics, such as genomics, transcriptomics, proteomics, or metabolomics. The ending -ome is used to address the objects of study of such fields, such as the genome, proteome, transcriptome, or metabolome, respectively. In relation to the conservation of germplasm, genomics-based plant germplasm research has been carried out and has been proven to be able to conserve germplasm. Recently, to conserve germplasm using only genomics-based plant germplasm research, it is felt to be incomplete, because not all genes can be expressed under certain conditions. For this reason, other omics such as proteomics and metabolomics play an important role in the conservation of germplasm. In this paper, the role of other omics research, especially metabolomics is described.

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Zhang, Aihua, Xiaohang Zhou, Hongwei Zhao, Shiyu Zou, Chung Wah Ma, Qi Liu, Hui Sun, Liang Liu, and Xijun Wang. "Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry." Molecular BioSystems 13, no. 2 (2017): 320–29. http://dx.doi.org/10.1039/c6mb00677a.

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Jiang, Will, Jennifer C. Jones, Uma Shankavaram, Mary Sproull, Kevin Camphausen, and Andra V. Krauze. "Analytical Considerations of Large-Scale Aptamer-Based Datasets for Translational Applications." Cancers 14, no. 9 (April 29, 2022): 2227. http://dx.doi.org/10.3390/cancers14092227.

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The development and advancement of aptamer technology has opened a new realm of possibilities for unlocking the biocomplexity available within proteomics. With ultra-high-throughput and multiplexing, alongside remarkable specificity and sensitivity, aptamers could represent a powerful tool in disease-specific research, such as supporting the discovery and validation of clinically relevant biomarkers. One of the fundamental challenges underlying past and current proteomic technology has been the difficulty of translating proteomic datasets into standards of practice. Aptamers provide the capacity to generate single panels that span over 7000 different proteins from a singular sample. However, as a recent technology, they also present unique challenges, as the field of translational aptamer-based proteomics still lacks a standardizing methodology for analyzing these large datasets and the novel considerations that must be made in response to the differentiation amongst current proteomic platforms and aptamers. We address these analytical considerations with respect to surveying initial data, deploying proper statistical methodologies to identify differential protein expressions, and applying datasets to discover multimarker and pathway-level findings. Additionally, we present aptamer datasets within the multi-omics landscape by exploring the intersectionality of aptamer-based proteomics amongst genomics, transcriptomics, and metabolomics, alongside pre-existing proteomic platforms. Understanding the broader applications of aptamer datasets will substantially enhance current efforts to generate translatable findings for the clinic.

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Versura, Piera, and Emilio C. Campos. "Disease Update on Human Tear Proteome." European Ophthalmic Review 07, no. 01 (2013): 36. http://dx.doi.org/10.17925/eor.2013.07.01.36.

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Tear film is a thin layer of non-newtonian fluid covering and protecting cornea and conjunctiva epithelia. The multifaced functions of tears are reflected by their complex structure and advances in proteomics/metabolomics/lipidomics technologies have greatly deepened the knowledge of the chemical composition of tears. The purpose of this article is to survey recent advances in proteomic analysis of human tears and to summarise the most relevant proteins proposed as biomarkers in dry eye. Besides, the potential clinical application of these biomarkers is discussed.

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Kanda, Katsuhiro. "Liquid chromatograph mass spectrometer for proteomics and metabolomics." SEIBUTSU BUTSURI KAGAKU 51, no. 1 (2007): 37–44. http://dx.doi.org/10.2198/sbk.51.37.

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Journal articles on the topic 'Proteomics and metabolomics'

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