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- An analysis of protein patterns present in the saliva of diabetic patients using pairwise relationship and hierarchical clusteringPublication . Soares, Airton; Esteves, Eduardo; Rosa, Nuno; Esteves, Ana Cristina; Lins, Anthony; Bastos-Filho, Carmelo J. A.Molecular diagnosis is based on the quantification of RNA, proteins, or metabolites whose concentration can be correlated to clinical situations. Usually, these molecules are not suitable for early diagnosis or to follow clinical evolution. Large-scale diagnosis using these types of molecules depends on cheap and preferably noninvasive strategies for screening. Saliva has been studied as a noninvasive, easily obtainable diagnosis fluid, and the presence of serum proteins in it enhances its use as a systemic health status monitoring tool. With a recently described automated capillary electrophoresis-based strategy that allows us to obtain a salivary total protein profile, it is possible to quantify and analyze patterns that may indicate disease presence or absence. The data of 19 persons with diabetes and 58 healthy donors obtained by capillary electrophoresis were transformed, treated, and grouped so that the structured values could be used to study individuals’ health state. After Pairwise Relationships and Hierarchical Clustering analysis were observed that amplitudes of protein peaks present in the saliva of these individuals could be used as differentiating parameters between healthy and unhealthy people. It indicates that these characteristics can serve as input for a future computational intelligence algorithm that will aid in the stratification of individuals that manifest changes in salivary proteins.
- Salivary diagnosis: miRNA’s new directionsPublication . Sousa, S.; Martins, J. E.; Martins, A.; Rosa, N.; Santos, L.; Correia, M. J.; Barros, M.
- SalivaTec: using xMAP® Multiplex Technology for saliva researchPublication . Rosa, Nuno; Correia, Maria; Barros, MarleneSalivaTec is an European laboratory using saliva in health research (salivaTec.viseu.ucp.pt). The main goal of SalivaTec is the clarification of molecular mechanisms of disease and the validation of biomarker panels proposed by in silico studies using bioinformatics tools developed in the laboratory. We demonstrate how SalivaTec uses xMAP ® Multiplex technology to quantify different molecules in saliva. These molecules are selected by an in silico analysis of the data deposited in our databases and quantified in samples chosen through the SalivaPrint algorithm, which identifies the molecules varying the most between groups of individuals. xMAP technology allows for the detection of salivary markers with high sensitivity and reliability although some challenges remain in the application of the commercial kits to saliva.
- OvisOme: atualização da base de dados de Ovis ariesPublication . Esteves, Eduardo; Fernandes, Mónica; Rosa, Nuno; Correia, Maria José; Vala, Helena; Barros, MarleneDatabases are essential to store, annotate and provide the scientific community with all the information gathered by different omics studies, so that it can be used to understand the physio-pathological mechanisms underlying sheep diseases, as well as to develop new and improved diagnostic, prognostic and therapeutic strategies. OvisOme is a database that integrates the information produced by proteomics and studies that identify and quantify specific proteins in diseases of Ovis aries. When compared to other proteomics databases, the OvisOme stores and displays more information than other databases not specific for sheep, such as UniPro.
- Molecular highlights in peri-implantitisPublication . Saavedra, Mariana; Silva, António; Rosa, Nuno; Correia, Maria; Barros, MarleneDental implants are one of the most frequently used treatment options for tooth replacement. Approximately 30% of patients with dental implants develop peri‐implantitis, which is an oral inflammatory disease. As established in 1993 at the First European Workshop on Periodontology, peri‐implant disease is a collective term for inflammatory processes in the implant surrounding tissues. Peri‐implant mucositis was defined as a reversible inflammatory process in the soft tissues surrounding a functioning implant, whereas peri‐implantitis is an inflammatory process additionally characterized by loss of peri‐implant bone. The diagnose of Peri‐implantitis is based on clinical, radiographic, microbiological and biological information. Several clinical studies use molecular biology assays to identify proteins in crevicular fluid that will be the initiation and progression of Peri‐implantitis disease, for the purpose of these study we used saliva sample. The aim of this study is to correlate the molecular and clinical characterization of peri‐implantar disease in order to improve our knowledge in the molecular pathophysiology of peri‐implant infections. For the development of future therapeutic strategies, it is essential to understand the molecular pathophysiology of human dental peri‐implant infections.
- Molecular cognition group strategyPublication . Martins, J. E.; Sousa, S.; Hipólito, I.; D'Alimonte, D.; Marques, T.; Rosa, N.; Correia, M. J.; Simões, M.; Barros, M.Neuronal functional protein networks found in the oral proteome are possibly useful to characterize a healthy phenome state and trait. Proteomics have extensively and objectively epitomized the understanding of healthy and pathological physiological states or conditions. Our group aims at the molecular characterization of cognition.
- A protein profiling strategy for periodontal disease applications: the Perio-SalivaPRINTPublication . Rosa, Nuno; Esteves, Eduardo; Esteves, Ana Cristina; Fernandes, Gustavo; Correia, Maria; Siqueira, Walter L.; Barros, MarleneObjectives: It is known that several clinical situations have characteristic molecular deregulations. Some molecular data underlying these deregulations can be found in saliva and have been annotated in databases (SalivaTecDB). Strategies are needed to identify the phenotypes characteristic of these deregulations. Our group has developed a strategy that allows the establishment of saliva protein profiles reflecting different conditions (health and disease). These profiles can be integrated to clinical data (SalivaPRINT Toolkit). The present work aims to identify the Periodontal Diseases (PD)-specific protein profiles. Methods: Unstimulated whole saliva was collected from a group of healthy subjects and a group of PD patients (with gingivitis, periodontitis or periimplantitis). Salivary proteins were separated by the Experion™ automated capillary electrophoresis. The protein profiles of each condition were integrated with the corresponding protein data retrieved from our in-house database (SalivaTecDB). Results: The strategy used enabled the determination of a total protein profile from saliva characteristic of each PDs -the Perio-SalivaPrint. The use of the SalivaPrint Toolkit allowed the identification of molecular weight ranges altered in PD. Using SalivaTecDB we were able to suggest proteins potentially involved in the underlying dysregulated mechanisms of the disease. Conclusions: This approach enabled the determination of a Perio-SalivaPrint – protein profiles specific for gingivitis, periodontitis or periimplantitis - that could empower the use of saliva as a simple and less expensive diagnostic and monitoring fluid. The strategy presented could be an important tool for future applications in the early diagnostic/ screening of Periodontal Disease patients with applications in chairside monitoring.