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Periodontal diseases are the largest cause of tooth loss among people of all ages and are also correlated with systemic diseases such as endocarditis. Advanced periodontal disease comprises degradation of surrounding tooth structures, severe inflammation and gingival bleeding. Inflammation is an early indicator of periodontal disease. Early detection and preventive measures can help prevent serious...
With the advent of precision medicine, biomarkers have recently come into focus as a promising tool for early cancer detection and treatment individualization. In particular, much interest has been shown in the oral microbiome as a promising potential cancer biomarker, especially for head and neck cancers. The American Cancer Society estimates that there will be nearly 50,000 new cases and roughly...
This work examines the validity of facial phenotypes as Autism Spectrum Disorders (ASD) biomarkers in boys with essential autism. A family-based association analysis framework is presented that uses previously identified facially-delineated (FD) clusters to examine relationship between FD clusters and known ASD genes. The hypothesis is that there are certain genetic variants, single nucleotide polymorphisms...
Ginger is a well-known traditional Chinese medicine which has been identified with positive digestive function regulations e.g. vomit prevention and warming interior. 6-shogaol is one of ginger's major bioactive constituents. In this study, digestive functions regulated by 6-shogaol towards stomach and small intestine were investigated. Started with biomarkers regulated by 6-shogaol reported in PubMed...
Biomarkers have tremendous potential in different phases of treatment such as risk assessment, screening/detection, diagnosis and patient's response prediction. In this paper, we present an approach for development of a generic tool for an end to end analysis of expression data to identify the probable biomarkers. We follow machine learning as well as network analysis approaches in parallel. We use...
Alzheimer's Disease (AD) is a neurodegenerative syndrome affecting millions of people worldwide. Also, individuals with mild cognitive impairment (MCI) are in a group of risk that should be followed and treated since there is a high probability of evolution to AD. In this study we carried out an Event-Related Potential (ERP) analysis on patient and control groups from 32-channel EEG recorded during...
Glioblastoma multiforme (GBM) is the most malignant brain tumor with rapid relapse, and an early biomarker identification in GBM is of high importance. We introduced our computational methodologies to identify serum microRNAs (miRNAs) as novel biomarkers in GBM. Differentially expressed miRNAs (DEMs) in GBM were analyzed from the Gene Expression Omnibus (GEO) repository; we then combined Venn diagrams...
Biomarkers discovery research requires the integrated analyses of a variety of the data across multiple domains, including clinical data, pathology data, gene expression, epigenetic data. Proper analysis can help understand the biological mechanism and better interpret the impact of the markers to disease. Realising the nature of the data in biomedical research and translational biomedicine, we developed...
Anti-cancer therapies have different responses to different patients. There is a need to identify biomarkers for effectiveness of drugs beside the biomarkers for the diseases like cancer to advance the field personalized medicine. We have used a panel of cancer cell lines from Genomics of Drug Sensitivity in Cancer (GDSC) to capture the sensitivity of drugs. By combining the genetic information such...
Recently, microRNAs were found to have potential as both diagnostic biomarkers and therapeutic targets for lung cancer, especially in identifying early-stage cancer. However, a miRNA biomarker derived from the standard normal v.s tumor differential expression analysis is not robust, as its functional interactions with messenger-RNA targets may change between different lung cancer subtypes. Furthermore,...
Machine learning classifiers help physicians to make near-perfect diagnoses, minimizing costs and time. Since medical data usually contains a high degree of uncertainty and ambiguity, proper ordering and classification require a proper comparative performance analysis of machine learning classifiers. Machine learning classifiers are applied on the Ovarian Cancer Dataset. Ovarian cancer is the fifth...
Point-of-Care (PoC) diagnostic devices, such as lateral flow tests, are often used in low and middle-income countries (LMIC) for low-cost disease detection. Most commercial lateral flow tests use colorimetric detection on a nitrocellulose substrate. In this paper, we present a multistep, fluorescence-based assay detection system, which can detect antibodies in plasma to recombinant protein. Fluorescence-based...
In this paper, we present a biosensor chip to study two important biomarkers, lactoferrin (LCF) and beta-2-microglubin (B2M) present in our tear fluid. LCF and B2M have direct relevance with dry eye syndrome and diabetic retinopathy in patients respectively. We have developed a multi-layer paper-based biosensor chip connected with handheld printed circuit board (PCB) to monitor the effectiveness of...
Diabetes is one of the most prevalent diseases worldwide, and hundreds of millions of patients are suffering from diabetes and its serious complications. Early detection and early treatment are urgent needed for clinical diagnosis of diabetics. In this work, we establish a gene coexpression network framework to identify biomarkers of transcripts with highly different gene coexpression patterns in...
Aphasia is an acquired language disorder resulting from damage to language related networks of the brain, most often as a result of ischemic stroke or traumatic brain injury. Within the European Union, over 580000 people are affected each year. Both assessment and treatment of aphasia require the analysis of language, in particular of spontaneous speech. Factoring in therapy and diagnosis sessions,...
We report a novel technique for simultaneous detection of nucleic acid and protein biomarkers using multimode interference (MMI) waveguides on an optofluidic chip. Multiplex detection of Zika virus nucleic acids and proteins using two-color multi-spot excitation is demonstrated with excellent specificity.
Biomarkers are objective indications of a medical state that can be measured accurately and reproducibly. Traditional biomarkers enable diagnosis of disease through detection of disease-specific molecular signatures or distinct physiological or anatomical signatures. This work provides a framework for selecting biomarkers that are most likely to provide useful information about a patient's disease...
Identifying effective cancer biomarkers is crucial in precision medicine. Based on the high-throughput available omics data such as microarray, this paper aims to identify potential biomarker genes for hepatocellular carcinoma by bioinformatics and machine learning. We describe the gene coexpressions with network model and detect out the genes that are closely related to liver cancer infected by hepatitis...
Carotid plaque rupture is a primary cause of ischemic strokes and transient ischemic attacks (TIAs). Probability of stroke and TIAs depend on the mechanical stability of plaque. Ultrasound strain can provide a non-invasive assessment of plaque stiffness to assess mechanical stability. We report on ultrasound strain indices from multiple regions of interest (ROI) in plaque as biomarkers for plaque...
Bone quality encompasses bone properties that contribute to fracture risk, such as bone stiffness, microstructure, matrix constituents or tissue material properties. These aspects cannot be quantified in-vivo except for stiffness, a surrogate biomarker of strength, which can be assessed using quantitative ultrasound techniques. To better predict bone fracture risk, investigating the relationships...
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