735 research outputs found

    Investigating the role of the fusiform face area and occipital face area using multifocal transcranial direct current stimulation.

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    The functional role of the occipital face area (OFA) and the fusiform face area (FFA) in face recognition is inconclusive to date. While some research has shown that the OFA and FFA are involved in early (i.e., featural processing) and late (i.e., holistic processing) stages of face recognition respectively, other research suggests that both regions are involved in both early and late stages of face recognition. Thus, the current study aims to further examine the role of the OFA and the FFA using multifocal transcranial direct current stimulation (tDCS). In Experiment 1, we used computer-generated faces. Thirty-five participants completed whole face and facial features (i.e., eyes, nose, mouth) recognition tasks after OFA and FFA stimulation in a within-subject design. No difference was found in recognition performance after either OFA or FFA stimulation. In Experiment 2 with 60 participants, we used real faces, provided stimulation following a between-subjects design and included a sham control group. Results showed that FFA stimulation led to enhanced efficiency of facial features recognition. Additionally, no effect of OFA stimulation was found for either facial feature or whole face recognition. These results suggest the involvement of FFA in the recognition of facial features

    Fluvial organic carbon fluxes from oil palm plantations on tropical peatland

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    Intact tropical peatlands are dense long-term stores of carbon. However, the future security of these ecosystems is at risk from land conversion and extensive peatland drainage. This can enhance peat oxidation and convert long-term carbon sinks into significant carbon sources. In Southeast Asia, the largest land use on peatland is for oil palm plantation agriculture. Here, we present the first annual estimate of exported fluvial organic carbon in the drainage waters of four peatland oil palm plantation areas in Sarawak, Malaysia. Total organic carbon (TOC) fluxes from the plantation second- and third-order drains were dominated (91 %) by dissolved organic carbon (DOC) and ranged from 34.4 ± 9.7 C m−2 yr−1 to 57.7 %, 16.3 g C m−2 yr−1 (± 95 % confidence interval). These fluxes represent a single-year survey which was strongly influenced by an El Ninõ event and therefore lower discharge than usual was observed. The magnitude of the flux was found to be influenced by water table depth, with higher TOC fluxes observed from more deeply drained sites. Radiocarbon dating on the DOC component indicated the presence of old (pre-1950s) carbon in all samples collected, with DOC at the most deeply drained site having a mean age of 735 years. Overall, our estimates suggest fluvial TOC contributes ∼ 5 % of total carbon losses from oil palm plantations on peat. Maintenance of high and stable water tables in oil palm plantations appears to be key to minimising TOC losses. This reinforces the importance of considering all carbon loss pathways, rather than just CO2 emissions from the peat surface, in studies of tropical peatland land conversion

    A unified approach for the solution of the Fokker-Planck equation

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    This paper explores the use of a discrete singular convolution algorithm as a unified approach for numerical integration of the Fokker-Planck equation. The unified features of the discrete singular convolution algorithm are discussed. It is demonstrated that different implementations of the present algorithm, such as global, local, Galerkin, collocation, and finite difference, can be deduced from a single starting point. Three benchmark stochastic systems, the repulsive Wong process, the Black-Scholes equation and a genuine nonlinear model, are employed to illustrate the robustness and to test accuracy of the present approach for the solution of the Fokker-Planck equation via a time-dependent method. An additional example, the incompressible Euler equation, is used to further validate the present approach for more difficult problems. Numerical results indicate that the present unified approach is robust and accurate for solving the Fokker-Planck equation.Comment: 19 page

    Quantitative model for inferring dynamic regulation of the tumour suppressor gene p53

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    Background: The availability of various "omics" datasets creates a prospect of performing the study of genome-wide genetic regulatory networks. However, one of the major challenges of using mathematical models to infer genetic regulation from microarray datasets is the lack of information for protein concentrations and activities. Most of the previous researches were based on an assumption that the mRNA levels of a gene are consistent with its protein activities, though it is not always the case. Therefore, a more sophisticated modelling framework together with the corresponding inference methods is needed to accurately estimate genetic regulation from "omics" datasets. Results: This work developed a novel approach, which is based on a nonlinear mathematical model, to infer genetic regulation from microarray gene expression data. By using the p53 network as a test system, we used the nonlinear model to estimate the activities of transcription factor (TF) p53 from the expression levels of its target genes, and to identify the activation/inhibition status of p53 to its target genes. The predicted top 317 putative p53 target genes were supported by DNA sequence analysis. A comparison between our prediction and the other published predictions of p53 targets suggests that most of putative p53 targets may share a common depleted or enriched sequence signal on their upstream non-coding region. Conclusions: The proposed quantitative model can not only be used to infer the regulatory relationship between TF and its down-stream genes, but also be applied to estimate the protein activities of TF from the expression levels of its target genes

    Transcriptome-scale similarities between mouse and human skeletal muscles with normal and myopathic phenotypes

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    BACKGROUND: Mouse and human skeletal muscle transcriptome profiles vary by muscle type, raising the question of which mouse muscle groups have the greatest molecular similarities to human skeletal muscle. METHODS: Orthologous (whole, sub-) transcriptome profiles were compared among four mouse-human transcriptome datasets: (M) six muscle groups obtained from three mouse strains (wildtype, mdx, mdx(5cv)); (H1) biopsied human quadriceps from controls and Duchenne muscular dystrophy patients; (H2) four different control human muscle types obtained at autopsy; and (H3) 12 different control human tissues (ten non-muscle). RESULTS: Of the six mouse muscles examined, mouse soleus bore the greatest molecular similarities to human skeletal muscles, independent of the latters' anatomic location/muscle type, disease state, age and sampling method (autopsy versus biopsy). Significant similarity to any one mouse muscle group was not observed for non-muscle human tissues (dataset H3), indicating this finding to be muscle specific. CONCLUSION: This observation may be partly explained by the higher type I fiber content of soleus relative to the other mouse muscles sampled

    Protocol adherence for continuously titrated interventions in randomized trials: an overview of the current methodology and case study.

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    BACKGROUND: The standard definition for protocol adherence is the proportion of all scheduled doses that are delivered. In clinical research, this definition has several limitations when evaluating protocol adherence in trials that study interventions requiring continuous titration. DISCUSSION: Building upon a specific case study, we analyzed a recent trial of a continuously titrated intervention to assess the impact of different definitions of protocol deviations on the interpretation of protocol adherence. The OVATION pilot trial was an open-label randomized controlled trial of higher (75-80 mmHg) versus lower (60-65 mmHg) mean arterial pressure (MAP) targets for vasopressor therapy in shock. In this trial, potential protocol deviations were defined as MAP values outside the targeted range for \u3e4 consecutive hours during vasopressor therapy without synchronous and consistent adjustments of vasopressor doses. An adjudication committee reviewed each potential deviation to determine if it was clinically-justified or not. There are four reasons for this contextual measurement and reporting of protocol adherence. First, between-arm separation is a robust measure of adherence to complex protocols. Second, adherence assessed by protocol deviations varies in function of the definition of deviations and the frequency of measurements. Third, distinguishing clinically-justified vs. not clinically-justified protocol deviations acknowledges clinically sensible bedside decision-making and offers a clear terminology before the trial begins. Finally, multiple metrics exist to report protocol deviations, which provides different information but complementary information on protocol adherence. CONCLUSIONS: In trials of interventions requiring continuous titration, metrics used for defining protocol deviations have a considerable impact on the interpretation of protocol adherence. Definitions for protocol deviations should be prespecified and correlated with between-arm separation, if it can be measured
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