285 research outputs found

    Diagnostic index: An open-source tool to classify TMJ OA condyles

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    Osteoarthritis (OA) of temporomandibular joints (TMJ) occurs in about 40% of the patients who present TMJ disorders. Despite its prevalence, OA diagnosis and treatment remain controversial since there are no clear symptoms of the disease, especially in early stages. Quantitative tools based on 3D imaging of the TMJ condyle have the potential to help characterize TMJ OA changes. The goals of the tools proposed in this study are to ultimately develop robust imaging markers for diagnosis and assessment of treatment efficacy. This work proposes to identify differences among asymptomatic controls and different clinical phenotypes of TMJ OA by means of Statistical Shape Modeling (SSM), obtained via clinical expert consensus. From three different grouping schemes (with 3, 5 and 7 groups), our best results reveal that that the majority (74.5%) of the classifications occur in agreement with the groups assigned by consensus between our clinical experts. Our findings suggest the existence of different disease-based phenotypic morphologies in TMJ OA. Our preliminary findings with statistical shape modeling based biomarkers may provide a quantitative staging of the disease. The methodology used in this study is included in an open source image analysis toolbox, to ensure reproducibility and appropriate distribution and dissemination of the solution proposed

    Zygomaticomaxillary suture maturation: Part IIâ The influence of sutural maturation on the response to maxillary protraction

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    Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/137741/1/ocr12191_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/137741/2/ocr12191.pd

    Positive thyroid transcription factor 1 staining strongly correlates with survival of patients with adenocarcinoma of the lung

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    This study investigated the relation between positive thyroid transcription factor 1 (TTF1) staining and survival of patients affected by primary adenocarcinoma (ADC) of the lung. Pathological tissue from consecutive ADC patients was collected from 2002 to 2004. The anti-TTF1 antibody (8G7G3/1, dilution of 1/200) was used. Thyroid transcription factor 1 staining was assessed for each tumour as positive or negative. Probability of survival was estimated by Kaplan–Meier and difference tested by log-rank test. A Cox's regression multivariate analysis was carried out. In all, 106 patients were studied (66% male, 69% PS0–1, 83% with stage III or IV). Tumours expressed positive TTF1 staining in 66% of cases. Multivariate analysis demonstrated an independent lower risk of death for patients whose tumour expresses positive TTF1 staining (HR=0.51, 95% CI 0.30–0.85; P=0.01) and higher grade of differentiation (HR=0.40, 95% CI 0.24–0.68; P=0.001). In conclusion, positive TTF1 staining strongly and independently correlates with survival of patients with primary ADC of the lung

    Osteoarthritis of the Temporomandibular Joint can be diagnosed earlier using biomarkers and machine learning

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    After chronic low back pain, Temporomandibular Joint (TMJ) disorders are the second most common musculoskeletal condition affecting 5 to 12% of the population, with an annual health cost estimated at $4 billion. Chronic disability in TMJ osteoarthritis (OA) increases with aging, and the main goal is to diagnosis before morphological degeneration occurs. Here, we address this challenge using advanced data science to capture, process and analyze 52 clinical, biological and high-resolution CBCT (radiomics) markers from TMJ OA patients and controls. We tested the diagnostic performance of four machine learning models: Logistic Regression, Random Forest, LightGBM, XGBoost. Headaches, Range of mouth opening without pain, Energy, Haralick Correlation, Entropy and interactions of TGF-β1 in Saliva and Headaches, VE-cadherin in Serum and Angiogenin in Saliva, VE-cadherin in Saliva and Headaches, PA1 in Saliva and Headaches, PA1 in Saliva and Range of mouth opening without pain; Gender and Muscle Soreness; Short Run Low Grey Level Emphasis and Headaches, Inverse Difference Moment and Trabecular Separation accurately diagnose early stages of this clinical condition. Our results show the XGBoost + LightGBM model with these features and interactions achieves the accuracy of 0.823, AUC 0.870, and F1-score 0.823 to diagnose the TMJ OA status. Thus, we expect to boost future studies into osteoarthritis patient-specific therapeutic interventions, and thereby improve the health of articular joints

    A web-based system for neural network based classification in temporomandibular joint osteoarthritis

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    Objective: The purpose of this study is to describe the methodological innovations of a web-based system for storage, integration and computation of biomedical data, using a training imaging dataset to remotely compute a deep neural network classifier of temporomandibular joint osteoarthritis (TMJOA). Methods: This study imaging dataset consisted of three-dimensional (3D) surface meshes of mandibular condyles constructed from cone beam computed tomography (CBCT) scans. The training dataset consisted of 259 condyles, 105 from control subjects and 154 from patients with diagnosis of TMJ OA. For the image analysis classification, 34 right and left condyles from 17 patients (39.9 ± 11.7 years), who experienced signs and symptoms of the disease for less than 5 years, were included as the testing dataset. For the integrative statistical model of clinical, biological and imaging markers, the sample consisted of the same 17 test OA subjects and 17 age and sex matched control subjects (39.4 ± 15.4 years), who did not show any sign or symptom of OA. For these 34 subjects, a standardized clinical questionnaire, blood and saliva samples were also collected. The technological methodologies in this study include a deep neural network classifier of 3D condylar morphology (ShapeVariationAnalyzer, SVA), and a flexible web-based system for data storage, computation and integration (DSCI) of high dimensional imaging, clinical, and biological data. Results: The DSCI system trained and tested the neural network, indicating 5 stages of structural degenerative changes in condylar morphology in the TMJ with 91% close agreement between the clinician consensus and the SVA classifier. The DSCI remotely ran with a novel application of a statistical analysis, the Multivariate Functional Shape Data Analysis, that computed high dimensional correlations between shape 3D coordinates, clinical pain levels and levels of biological markers, and then graphically displayed the computation results. Conclusions: The findings of this study demonstrate a comprehensive phenotypic characterization of TMJ health and disease at clinical, imaging and biological levels, using novel flexible and versatile open-source tools for a web-based system that provides advanced shape statistical analysis and a neural network based classification of temporomandibular joint osteoarthritis

    Tracing ancestry with methylation patterns: most crypts appear distantly related in normal adult human colon

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    BACKGROUND: The ability to discern ancestral relationships between individual human colon crypts is limited. Widely separated crypts likely trace their common ancestors to a time around birth, but closely spaced adult crypts may share more recent common ancestors if they frequently divide by fission to form clonal patches. Alternatively, adult crypts may be long-lived structures that infrequently divide or die. METHODS: Methylation patterns (the 5' to 3' order of methylation) at CpG sites that exhibit random changes with aging were measured from isolated crypts by bisulfite genomic sequencing. This epigenetic drift may be used to infer ancestry because recently related crypts should have similar methylation patterns. RESULTS: Methylation patterns were different between widely separated ("unrelated") crypts greater than 15 cm apart. Evidence for a more recent relationship between directly adjacent or branched crypts could not be found because their methylation pattern distances were not significantly different than widely separated crypt pairs. Methylation patterns are essentially equally different between two adult human crypts regardless of their relative locations. CONCLUSIONS: Methylation patterns appear to record somatic cell trees. Starting from a single cell at conception, sequences replicate and may drift apart. Most adult human colon crypts appear to be long-lived structures that become mosaic with respect to methylation during aging

    Age-related human small intestine methylation: evidence for stem cell niches

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    BACKGROUND: The small intestine is constructed of many crypts and villi, and mouse studies suggest that each crypt contains multiple stem cells. Very little is known about human small intestines because mouse fate mapping strategies are impractical in humans. However, it is theoretically possible that stem cell histories are inherently written within their genomes. Genomes appear to record histories (as exemplified by use of molecular clocks), and therefore it may be possible to reconstruct somatic cell dynamics from somatic cell errors. Recent human colon studies suggest that random somatic epigenetic errors record stem cell histories (ancestry and total numbers of divisions). Potentially age-related methylation also occurs in human small intestines, which would allow characterization of their stem cells and comparisons with the colon. METHODS: Methylation patterns in individual crypts from 13 small intestines (17 to 78 years old) were measured by bisulfite sequencing. The methylation patterns were analyzed by a quantitative model to distinguish between immortal or niche stem cell lineages. RESULTS: Age-related methylation was observed in the human small intestines. Crypt methylation patterns were more consistent with stem cell niches than immortal stem cell lineages. Human large and small intestine crypt niches appeared to have similar stem cell dynamics, but relatively less methylation accumulated with age in the small intestines. There were no apparent stem cell differences between the duodenum and ileum, and stem cell survival did not appear to decline with aging. CONCLUSION: Crypt niches containing multiple stem cells appear to maintain human small intestines. Crypt niches appear similar in the colon and small intestine, and the small intestinal stem cell mitotic rate is the same as or perhaps slower than that of the colon. Although further studies are needed, age-related methylation appears to record somatic cell histories, and a somatic epigenetic molecular clock strategy may potentially be applied to other human tissues to reconstruct otherwise occult stem cell histories

    Role of Heterozygous APC Mutation in Niche Succession and Initiation of Colorectal Cancer – A Computational Study

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    Mutations in the adenomatous polyposis coli (APC) gene are found in most colorectal cancers. They cause constitutive activation of proliferative pathways when both alleles of the gene are mutated. However studies on individuals with familial adenomatous polyposis (FAP) have shown that a single mutated APC allele can also create changes in the precancerous colon crypt, like increased number of stem cells, increased crypt fission, greater variability of DNA methylation patterns, and higher somatic mutation rates. In this paper, using a computational model of colon crypt dynamics, we evolve and investigate a hypothesis on the effect of heterozygous APC mutation that explains these different observations. Based on previous reports and the results from the computational model we propose the hypothesis that heterozygous APC mutation has the effect of increasing the chances for a stem cell to divide symmetrically, producing two stem cell daughters. We incorporate this hypothesis into the model and perform simulation experiments to investigate the consequences of the hypothesis. Simulations show that this hypothesis links together the changes in FAP crypts observed in previous studies. The simulations also show that an APC+/− stem cell gets selective advantages for dominating the crypt and progressing to cancer. This explains why most colon cancers are initiated by APC mutation. The results could have implications for preventing or retarding the onset of colon cancer in people with inherited or acquired mutation of one APC allele. Experimental validation of the hypothesis as well as investigation into the molecular mechanisms of this effect may therefore be worth undertaking
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