34 research outputs found

    Investigating the Impact of a Dual Musical Brain-Computer Interface on Interpersonal Synchrony: A Pilot Study

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    This study looked into how effective a Musical Brain-Computer Interface (MBCI) can be in providing feedback about synchrony between two people. Using a double EEG setup, we compared two types of musical feedback; one that adapted in real-time based on the inter-brain synchrony between participants (Neuroadaptive condition), and another music that was randomly generated (Random condition). We evaluated how these two conditions were perceived by 8 dyads (n = 16) and whether the generated music could influence the perceived connection and EEG synchrony between them. The findings indicated that Neuroadaptive musical feedback could potentially boost synchrony levels between people compared to Random feedback, as seen by a significant increase in EEG phase-locking values. Additionally, the real-time measurement of synchrony was successfully validated and musical neurofeedback was generally well-received by the participants. However, more research is needed for conclusive results due to the small sample size. This study is a stepping stone towards creating music that can audibly reflect the level of synchrony between individuals.Comment: 6 pages, 4 figure

    Are the effects of cognitive behavior therapy for severe fatigue in cancer survivors sustained up to 14 years after therapy?

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    © 2018, The Author(s). Purpose: Cognitive behavior therapy (CBT) reduces cancer-related fatigue (CRF) in cancer survivors in the short term. We examined fatigue levels up to 14 years after CBT. Methods: Eligible participants of two randomized controlled trials who had completed CBT for CRF and a post-treatment assessment were contacted (n = 81). Fatigue was assessed with the subscale “fatigue severity” of the Checklist Individual Strength (CIS-fatigue). The course of fatigue over time was examined with linear mixed model analyses. Fatigue levels of participants were compared to matched population controls at long-term follow-up. We tested with multiple regression analysis if fatigue at follow-up was predicted by the patients’ fatigue level and fatigue-perpetuating factors directly after CBT (post-CBT). Results: Seventy-eight persons completed a follow-up assessment (response rate = 96%, mean time after CBT = 10 years). The mean level of fatigue increased from 23.7 (SD = 11.1) at post-CBT to 34.4 (SD = 12.4) at follow-up (p <0.001). Population controls (M = 23,9, SD = 11.4) reported lower fatigue levels than participants. Half of the patients (52%) who were recovered from severe fatigue at post-CBT (CIS-fatigue <35) were still recovered at long-term follow-up. Patients with lower fatigue levels at post-CBT were less likely to show relapse. Conclusion: Despite initial improvement after CBT, levels of fatigue deteriorated over time. Half of the patients who were recovered from severe fatigue after CBT still scored within normal ranges of fatigue at long-term follow-up. Implications for Cancer Survivors: It should be explored how to help patients with a relapse of severe fatigue following an initially successful CBT. They may profit from CBT again, or another evidence-based intervention for fatigue (like mindfulness or exercise therapy). Future research to gain insight into reasons for relapse is warranted

    Comparison of the Cancer Gene Targeting and Biochemical Selectivities of All Targeted Kinase Inhibitors Approved for Clinical Use

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    <div><p>The anti-proliferative activities of all twenty-five targeted kinase inhibitor drugs that are in clinical use were measured in two large assay panels: (1) a panel of proliferation assays of forty-four human cancer cell lines from diverse tumour tissue origins; and (2) a panel of more than 300 kinase enzyme activity assays. This study provides a head-on comparison of all kinase inhibitor drugs in use (status Nov. 2013), and for six of these drugs, the first kinome profiling data in the public domain. Correlation of drug activities with cancer gene mutations revealed novel drug sensitivity markers, suggesting that cancers dependent on mutant <i>CTNNB1</i> will respond to trametinib and other MEK inhibitors, and cancers dependent on <i>SMAD4</i> to small molecule EGFR inhibitor drugs. Comparison of cellular targeting efficacies reveals the most targeted inhibitors for EGFR, ABL1 and BRAF(V600E)-driven cell growth, and demonstrates that the best targeted agents combine high biochemical potency with good selectivity. For ABL1 inhibitors, we computationally deduce optimized kinase profiles for use in a next generation of drugs. Our study shows the power of combining biochemical and cellular profiling data in the evaluation of kinase inhibitor drug action.</p></div

    Selective Targeting of <i>CTNNB1-</i>, <i>KRAS-</i> or <i>MYC-</i>Driven Cell Growth by Combinations of Existing Drugs

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    <div><p>The aim of combination drug treatment in cancer therapy is to improve response rate and to decrease the probability of the development of drug resistance. Preferably, drug combinations are synergistic rather than additive, and, ideally, drug combinations work synergistically only in cancer cells and not in non-malignant cells. We have developed a workflow to identify such targeted synergies, and applied this approach to selectively inhibit the proliferation of cell lines with mutations in genes that are difficult to modulate with small molecules. The approach is based on curve shift analysis, which we demonstrate is a more robust method of determining synergy than combination matrix screening with Bliss-scoring. We show that the MEK inhibitor trametinib is more synergistic in combination with the BRAF inhibitor dabrafenib than with vemurafenib, another BRAF inhibitor. In addition, we show that the combination of MEK and BRAF inhibitors is synergistic in <i>BRAF</i>-mutant melanoma cells, and additive or antagonistic in, respectively, <i>BRAF</i>-wild type melanoma cells and non-malignant fibroblasts. This combination exemplifies that synergistic action of drugs can depend on cancer genotype. Next, we used curve shift analysis to identify new drug combinations that specifically inhibit cancer cell proliferation driven by difficult-to-drug cancer genes. Combination studies were performed with compounds that as single agents showed preference for inhibition of cancer cells with mutations in either the <i>CTNNB1</i> gene (coding for β-catenin), <i>KRAS</i>, or cancer cells expressing increased copy numbers of <i>MYC</i>. We demonstrate that the Wnt-pathway inhibitor ICG-001 and trametinib acted synergistically in Wnt-pathway-mutant cell lines. The ERBB2 inhibitor TAK-165 was synergistic with trametinib in <i>KRAS</i>-mutant cell lines. The EGFR/ERBB2 inhibitor neratinib acted synergistically with the spindle poison docetaxel and with the Aurora kinase inhibitor GSK-1070916 in cell lines with <i>MYC</i> amplification. Our approach can therefore efficiently discover novel drug combinations that selectively target cancer genes.</p></div
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