379 research outputs found

    A cyclic peptide inhibitor of HIF-1 heterodimerization that inhibits hypoxia signaling in cancer cells

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    Hypoxia inducible factor-1 (HIF-1) is a heterodimeric transcription factor that acts as the master regulator of cellular response to reduced oxygen levels, thus playing a key role in the adaptation, survival and progression of tumors. Here we report cyclo-CLLFVY, identified from a library of 3.2 million cyclic hexapeptides using a genetically encoded high-throughput screening platform, as an inhibitor of the HIF-1α/HIF-1β protein-protein interaction in vitro and in cells. The identified compound inhibits HIF-1 dimerization and transcription activity by binding to the PAS-B domain of HIF-1α, reducing HIF-1-mediated hypoxia response signaling in a variety of cell lines, without affecting the function of the closely related HIF-2 isoform. The reported cyclic peptide demonstrates the utility of our high-throughput screening platform for the identification of protein-protein interaction inhibitors, and forms the starting point for the development of HIF-1 targeted cancer therapeutics

    Advances in establishment and analysis of three-dimensional tumor spheroid-based functional assays for target validation and drug evaluation

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    There is overwhelming evidence that in vitro three-dimensional tumor cell cultures more accurately reflect the complex in vivo microenvironment than simple two-dimensional cell monolayers, not least with respect to gene expression profiles, signaling pathway activity and drug sensitivity. However, most currently available threedimensional techniques are time consuming and/or lack reproducibility; thus standardized and rapid protocols are urgently needed. To address this requirement, we have developed a versatile toolkit of reproducible three-dimensional tumor spheroid models for dynamic, automated, quantitative imaging and analysis that are compatible with routine high-throughput preclinical studies. Not only do these microplate methods measure three-dimensional tumor growth, but they have also been significantly enhanced to facilitate a range of functional assays exemplifying additional key hallmarks of cancer, namely cell motility and matrix invasion. Moreover, mutual tissue invasion and angiogenesis is accommodated by coculturing tumor spheroids with murine embryoid bodies within which angiogenic differentiation occurs. Highly malignant human tumor cells were selected to exemplify therapeutic effects of three specific molecularly-targeted agents: PI-103 (phosphatidylinositol-3-kinase (PI3K)- mammalian target of rapamycin (mTOR) inhibitor), 17-N-allylamino-17-demethoxygeldanamycin (17-AAG) (heat shock protein 90 (HSP90) inhibitor) and CCT130234 (in-house phospholipase C (PLC)g inhibitor). Fully automated analysis using a Celigo cytometer was validated for tumor spheroid growth and invasion against standard image analysis techniques, with excellent reproducibility and significantly increased throughput. In addition, we discovered key differential sensitivities to targeted agents between two-dimensional and three-dimensional cultures, and also demonstrated enhanced potency of some agents against cell migration/invasion compared with proliferation, suggesting their preferential utility in metastatic disease.: We have established and validated a suite of highly reproducible tumor microplate threedimensional functional assays to enhance the biological relevance of early preclinical cancer studies. We believe these assays will increase the translational predictive value of in vitro drug evaluation studies and reduce the need for in vivo studies by more effective triaging of compounds.This work was funded by The National Centre for the Replacement, Refinement and Reduction of Animals in Research (G1000121 ID no. 94513), Cancer Research UK (grant number C309/A8274), and by Red Tematica de Investigación Cooperativa en Cancer (RD06/0020/1022). We acknowledge NHS funding to the NIHR Biomedical Research Centre. MM is supported by a postdoctoral research contract (FIS, Program ‘Sara Borrell’, Instituto de Salud Carlos III), Ministerio de Ciencia e Innovación, Spain

    Beam energy metrics for the acceptance and quality assurance of Halcyon linear accelerator

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    PURPOSE: Establish and compare two metrics for monitoring beam energy changes in the Halcyon platform and evaluate the accuracy of these metrics across multiple Halcyon linacs. METHOD: The first energy metric is derived from the diagonal normalized flatness (F RESULTS: Five Halcyon linacs from five institutions were used to evaluate the accuracy of the D CONCLUSION: The

    1778-12-26 John Main vs. William Keating of York

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    https://digitalmaine.com/early_aa_history_me/1012/thumbnail.jp

    SynthEye: Investigating the Impact of Synthetic Data on Artificial Intelligence-assisted Gene Diagnosis of Inherited Retinal Disease

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    PURPOSE: Rare disease diagnosis is challenging in medical image-based artificial intelligence due to a natural class imbalance in datasets, leading to biased prediction models. Inherited retinal diseases (IRDs) are a research domain that particularly faces this issue. This study investigates the applicability of synthetic data in improving artificial intelligence-enabled diagnosis of IRDs using generative adversarial networks (GANs). DESIGN: Diagnostic study of gene-labeled fundus autofluorescence (FAF) IRD images using deep learning. PARTICIPANTS: Moorfields Eye Hospital (MEH) dataset of 15 692 FAF images obtained from 1800 patients with confirmed genetic diagnosis of 1 of 36 IRD genes. METHODS: A StyleGAN2 model is trained on the IRD dataset to generate 512 × 512 resolution images. Convolutional neural networks are trained for classification using different synthetically augmented datasets, including real IRD images plus 1800 and 3600 synthetic images, and a fully rebalanced dataset. We also perform an experiment with only synthetic data. All models are compared against a baseline convolutional neural network trained only on real data. MAIN OUTCOME MEASURES: We evaluated synthetic data quality using a Visual Turing Test conducted with 4 ophthalmologists from MEH. Synthetic and real images were compared using feature space visualization, similarity analysis to detect memorized images, and Blind/Referenceless Image Spatial Quality Evaluator (BRISQUE) score for no-reference-based quality evaluation. Convolutional neural network diagnostic performance was determined on a held-out test set using the area under the receiver operating characteristic curve (AUROC) and Cohen's Kappa (κ). RESULTS: An average true recognition rate of 63% and fake recognition rate of 47% was obtained from the Visual Turing Test. Thus, a considerable proportion of the synthetic images were classified as real by clinical experts. Similarity analysis showed that the synthetic images were not copies of the real images, indicating that copied real images, meaning the GAN was able to generalize. However, BRISQUE score analysis indicated that synthetic images were of significantly lower quality overall than real images (P < 0.05). Comparing the rebalanced model (RB) with the baseline (R), no significant change in the average AUROC and κ was found (R-AUROC = 0.86[0.85-88], RB-AUROC = 0.88[0.86-0.89], R-k = 0.51[0.49-0.53], and RB-k = 0.52[0.50-0.54]). The synthetic data trained model (S) achieved similar performance as the baseline (S-AUROC = 0.86[0.85-87], S-k = 0.48[0.46-0.50]). CONCLUSIONS: Synthetic generation of realistic IRD FAF images is feasible. Synthetic data augmentation does not deliver improvements in classification performance. However, synthetic data alone deliver a similar performance as real data, and hence may be useful as a proxy to real data. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references

    Measurement of Angular Distributions and R= sigma_L/sigma_T in Diffractive Electroproduction of rho^0 Mesons

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    Production and decay angular distributions were extracted from measurements of exclusive electroproduction of the rho^0(770) meson over a range in the virtual photon negative four-momentum squared 0.5< Q^2 <4 GeV^2 and the photon-nucleon invariant mass range 3.8< W <6.5 GeV. The experiment was performed with the HERMES spectrometer, using a longitudinally polarized positron beam and a ^3He gas target internal to the HERA e^{+-} storage ring. The event sample combines rho^0 mesons produced incoherently off individual nucleons and coherently off the nucleus as a whole. The distributions in one production angle and two angles describing the rho^0 -> pi+ pi- decay yielded measurements of eight elements of the spin-density matrix, including one that had not been measured before. The results are consistent with the dominance of helicity-conserving amplitudes and natural parity exchange. The improved precision achieved at 47 GeV, reveals evidence for an energy dependence in the ratio R of the longitudinal to transverse cross sections at constant Q^2.Comment: 15 pages, 15 embedded figures, LaTeX for SVJour(epj) document class Revision: Fig. 15 corrected, recent data added to Figs. 10,12,14,15; minor changes to tex

    Determination of the Deep Inelastic Contribution to the Generalised Gerasimov-Drell-Hearn Integral for the Proton and Neutron

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    The virtual photon absorption cross section differences [sigma_1/2-sigma_3/2] for the proton and neutron have been determined from measurements of polarised cross section asymmetries in deep inelastic scattering of 27.5 GeV longitudinally polarised positrons from polarised 1H and 3He internal gas targets. The data were collected in the region above the nucleon resonances in the kinematic range nu < 23.5 GeV and 0.8 GeV**2 < Q**2 < 12 GeV**2. For the proton the contribution to the generalised Gerasimov-Drell-Hearn integral was found to be substantial and must be included for an accurate determination of the full integral. Furthermore the data are consistent with a QCD next-to-leading order fit based on previous deep inelastic scattering data. Therefore higher twist effects do not appear significant.Comment: 6 pages, 3 figures, 1 table, revte
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