317 research outputs found

    Distance Metric Learning using Graph Convolutional Networks: Application to Functional Brain Networks

    Full text link
    Evaluating similarity between graphs is of major importance in several computer vision and pattern recognition problems, where graph representations are often used to model objects or interactions between elements. The choice of a distance or similarity metric is, however, not trivial and can be highly dependent on the application at hand. In this work, we propose a novel metric learning method to evaluate distance between graphs that leverages the power of convolutional neural networks, while exploiting concepts from spectral graph theory to allow these operations on irregular graphs. We demonstrate the potential of our method in the field of connectomics, where neuronal pathways or functional connections between brain regions are commonly modelled as graphs. In this problem, the definition of an appropriate graph similarity function is critical to unveil patterns of disruptions associated with certain brain disorders. Experimental results on the ABIDE dataset show that our method can learn a graph similarity metric tailored for a clinical application, improving the performance of a simple k-nn classifier by 11.9% compared to a traditional distance metric.Comment: International Conference on Medical Image Computing and Computer-Assisted Interventions (MICCAI) 201

    Admission Levels of Interleukin 10 and Amyloid β 1–40 Improve the Outcome Prediction Performance of the Helsinki Computed Tomography Score in Traumatic Brain Injury

    Get PDF
    BACKGROUND: Blood biomarkers may enhance outcome prediction performance of head computed tomography scores in traumatic brain injury (TBI). OBJECTIVE: To investigate whether admission levels of eight different protein biomarkers can improve the outcome prediction performance of the Helsinki computed tomography score (HCTS) without clinical covariates in TBI. MATERIALS AND METHODS: ighty-two patients with computed tomography positive TBIs were included in this study. Plasma levels of β-amyloid isoforms 1–40 (Aβ40) and 1–42 (Aβ42), glial fibrillary acidic protein, heart fatty acid-binding protein, interleukin 10 (IL-10), neurofilament light, S100 calcium-binding protein B, and total tau were measured within 24 h from admission. The patients were divided into favorable (Glasgow Outcome Scale—Extended 5–8, n = 49) and unfavorable (Glasgow Outcome Scale—Extended 1–4, n = 33) groups. The outcome was assessed 6–12 months after injury. An optimal predictive panel was investigated with the sensitivity set at 90–100%. RESULTS: The HCTS alone yielded a sensitivity of 97.0% (95% CI: 90.9–100) and specificity of 22.4% (95% CI: 10.2–32.7) and partial area under the curve of the receiver operating characteristic of 2.5% (95% CI: 1.1–4.7), in discriminating patients with favorable and unfavorable outcomes. The threshold to detect a patient with unfavorable outcome was an HCTS > 1. The three best individually performing biomarkers in outcome prediction were Aβ40, Aβ42, and neurofilament light. The optimal panel included IL-10, Aβ40, and the HCTS reaching a partial area under the curve of the receiver operating characteristic of 3.4% (95% CI: 1.7–6.2) with a sensitivity of 90.9% (95% CI: 81.8–100) and specificity of 59.2% (95% CI: 40.8–69.4). CONCLUSION: Admission plasma levels of IL-10 and Aβ40 significantly improve the prognostication ability of the HCTS after TBI

    Stochastic Cytokine Expression Induces Mixed T Helper Cell States

    Get PDF
    During eukaryotic development, the induction of a lineage-specific transcription factor typically drives differentiation of multipotent progenitor cells, while repressing that of alternative lineages. This process is often mediated by some extracellular signaling molecules, such as cytokines that can bind to cell surface receptors, leading to activation and/or repression of transcription factors. We explored the early differentiation of naive CD4 T helper (Th) cells into Th1 versus Th2 states by counting single transcripts and quantifying immunofluorescence in individual cells. Contrary to mutually exclusive expression of antagonistic transcription factors, we observed their ubiquitous co-expression in individual cells at high levels that are distinct from basal-level co-expression during lineage priming. We observed that cytokines are expressed only in a small subpopulation of cells, independent from the expression of transcription factors in these single cells. This cell-to-cell variation in the cytokine expression during the early phase of T helper cell differentiation is significantly larger than in the fully differentiated state. Upon inhibition of cytokine signaling, we observed the classic mutual exclusion of antagonistic transcription factors, thus revealing a weak intracellular network otherwise overruled by the strong signals that emanate from extracellular cytokines. These results suggest that during the early differentiation process CD4 T cells acquire a mixed Th1/Th2 state, instructed by extracellular cytokines. The interplay between extracellular and intracellular signaling components unveiled in Th1/Th2 differentiation may be a common strategy for mammalian cells to buffer against noisy cytokine expression.National Cancer Institute (U.S.). Physical Sciences-Oncology Center (U54CA143874)National Institutes of Health (U.S.) (Pioneer Award)National Institutes of Health (U.S.) (Grant R01-GM068957

    Persistent Cell-Autonomous Circadian Oscillations in Fibroblasts Revealed by Six-Week Single-Cell Imaging of PER2::LUC Bioluminescence

    Get PDF
    Biological oscillators naturally exhibit stochastic fluctuations in period and amplitude due to the random nature of molecular reactions. Accurately measuring the precision of noisy oscillators and the heterogeneity in period and strength of rhythmicity across a population of cells requires single-cell recordings of sufficient length to fully represent the variability of oscillations. We found persistent, independent circadian oscillations of clock gene expression in 6-week-long bioluminescence recordings of 80 primary fibroblast cells dissociated from PER2::LUC mice and kept in vitro for 6 months. Due to the stochastic nature of rhythmicity, the proportion of cells appearing rhythmic increases with the length of interval examined, with 100% of cells found to be rhythmic when using 3-week windows. Mean period and amplitude are remarkably stable throughout the 6-week recordings, with precision improving over time. For individual cells, precision of period and amplitude are correlated with cell size and rhythm amplitude, but not with period, and period exhibits much less cycle-to-cycle variability (CV 7.3%) than does amplitude (CV 37%). The time series are long enough to distinguish stochastic fluctuations within each cell from differences among cells, and we conclude that the cells do exhibit significant heterogeneity in period and strength of rhythmicity, which we measure using a novel statistical metric. Furthermore, stochastic modeling suggests that these single-cell clocks operate near a Hopf bifurcation, such that intrinsic noise enhances the oscillations by minimizing period variability and sustaining amplitude

    IFNAR1-Signalling Obstructs ICOS-mediated Humoral Immunity during Non-lethal Blood-Stage Plasmodium Infection

    Get PDF
    Funding: This work was funded by a Career Development Fellowship (1028634) and a project grant (GRNT1028641) awarded to AHa by the Australian National Health & Medical Research Council (NHMRC). IS was supported by The University of Queensland Centennial and IPRS Scholarships. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

    Physicians' preference values for hepatitis C health states and antiviral therapy: A survey

    Get PDF
    BACKGROUND: Physicians' perspectives regarding hepatitis C shape their approach to patient management. We used utility analysis to evaluate physicians' perceptions of hepatitis C-related health states (HS) and their threshold to recommend treatment. METHODS: A written questionnaire was administered to practicing physicians. They were asked to rate hepatitis C health states on a visual analog scale ranging from 0% (death) to 100% (health without hepatitis C). Physicians then judged quality of life associated with the side effects of antiviral therapy for hepatitis C and indicated the sustained virological response rate that they would require to recommend treatment. RESULTS: One hundred and thirteen physicians from five states were included. Median utility ratings for hepatitis C health states declined significantly with increasing severity of symptoms: HS1-No Symptoms, No Cirrhosis (88%; 12% reduction from good health), HS2-Mild Symptoms, No Cirrhosis (66%), HS3-Moderate Symptoms, No Cirrhosis (49%), HS4-Mild Symptoms, Cirrhosis (40%), HS5-Severe Symptoms, Cirrhosis (18%) [p < 0.001]. The median rating for life with side effects of antiviral therapy was 47%, suggesting a 53% reduction from good health. That was similar to the utility value for HS3-Moderate Symptoms, No Cirrhosis. The median threshold value for recommending treatment was a sustained response rate of 60%. CONCLUSIONS: 1) Physicians' utility ratings for hepatitis C health states were inversely related to the severity of disease manifestations described. 2) Physicians viewed side effects of therapy unfavorably and indicated that on average, they would require a 60% sustained response rate before recommending treatment, which far exceeds the efficacy of current antiviral therapy for hepatitis C in the majority of patients

    Identification of a potent herbal molecule for the treatment of breast cancer

    Get PDF
    <p>Abstract</p> <p>Background</p> <p>Breast cancer (BCa)-related mortality still remains the second leading cause of cancer-related deaths worldwide. Patients with BCa have increasingly shown resistance and high toxicity to current chemotherapeutic drugs for which identification of novel targeted therapies are required.</p> <p>Methods</p> <p>To determine the effect of PDBD on BCa cells, estrogen-receptor positive (ER<sup>+</sup>)-MCF-7 and estrogen-receptor negative (ER<sup>-</sup>)-MDA 231 cells were treated with PDBD and the cell viability, apoptotic, cell cycle, Western blot and Promoter assays were performed.</p> <p>Results</p> <p>PDBD inhibits cell viability of ER<sup>+ </sup>and ER<sup>- </sup>BCa cells by inducing apoptosis without causing significant toxicity in normal breast epithelial cells. While dissecting the mechanism of action of PDBD on BCa, we found that PDBD inhibits Akt signaling and its downstream targets such as NF-κB activation, IAP proteins and Bcl-2 expression. On the other hand, activation of JNK/p38 MAPK-mediated pro-apoptotic signaling was observed in both ER<sup>+ </sup>and ER<sup>- </sup>BCa cells.</p> <p>Conclusion</p> <p>These findings suggest that PDBD may have wide therapeutic application in the treatment of BCa.</p

    Pleosporales

    Get PDF
    One hundred and five generic types of Pleosporales are described and illustrated. A brief introduction and detailed history with short notes on morphology, molecular phylogeny as well as a general conclusion of each genus are provided. For those genera where the type or a representative specimen is unavailable, a brief note is given. Altogether 174 genera of Pleosporales are treated. Phaeotrichaceae as well as Kriegeriella, Zeuctomorpha and Muroia are excluded from Pleosporales. Based on the multigene phylogenetic analysis, the suborder Massarineae is emended to accommodate five families, viz. Lentitheciaceae, Massarinaceae, Montagnulaceae, Morosphaeriaceae and Trematosphaeriaceae
    corecore