3,166 research outputs found
The wisdom of crowds and the repurposing of artesunate as an anticancer drug.
Artesunate, a semi-synthetic and water-soluble artemisinin-derivative used as an anti-malarial agent, has attracted the attention of cancer researchers due to a broad range of anti-cancer activity including anti-angiogenic, immunomodulatory and treatment-sensitisation effects. In addition to pre-clinical evidence in a range of cancers, a recently completed randomised blinded trial in colorectal cancer has provided a positive signal for further clinical investigation. Used perioperatively artesunate appears to reduce the rate of disease recurrence - and the Neo-Art trial, a larger Phase II RCT, is seeking to confirm this positive effect. However, artesunate is a generic medication, and as with other trials of repurposed drugs, the Neo-Art trial does not have commercial sponsorship. In an innovative move, the trial is seeking funds directly from members of the public via a crowd-funding strategy that may have resonance beyond this single trial
Next Generation Sequencing Assay for Detection of Circulating HPV DNA (cHPV-DNA) in Patients Undergoing Radical (Chemo)Radiotherapy in Anal Squamous Cell Carcinoma (ASCC).
Background: Following chemo-radiotherapy (CRT) for human papilloma virus positive (HPV+) anal squamous cell carcinoma (ASCC), detection of residual/recurrent disease is challenging. Patients frequently undergo unnecessary repeated biopsies for abnormal MRI/clinical findings. In a pilot study we assessed the role of circulating HPV-DNA in identifying "true" residual disease. Methods: We prospectively collected plasma samples at baseline (n = 21) and 12 weeks post-CRT (n = 17). Circulating HPV-DNA (cHPV DNA) was measured using a novel next generation sequencing (NGS) assay, panHPV-detect, comprising of two primer pools covering distinct regions of eight high-risk HPV genomes (16, 18, 31, 33, 35, 45, 52, and 58) to detect circulating HPV-DNA (cHPV DNA). cHPV-DNA levels post-CRT were correlated to disease response. Results: In pre-CRT samples, panHPV-detect demonstrated 100% sensitivity and specificity for HPV associated ASCC. PanHPV-detect was able to demonstrate cHPV-DNA in 100% (9/9) patients with T1/T2N0 cancers. cHPV-DNA was detectable 12 weeks post CRT in just 2/17 patients, both of whom relapsed. 1/16 patients who had a clinical complete response (CR) at 3 months post-CRT but relapsed at 9 months and 1/1 patient with a partial response (PR). PanHPV-detect demonstrated 100% sensitivity and specificity in predicting response to CRT. Conclusion: We demonstrate that panHPV-detect, an NSG assay is a highly sensitive and specific test for the identification of cHPV-DNA in plasma at diagnosis. cHPV-DNA post-treatment may predict clinical response to CRT
Deep learning-based fully automatic segmentation of wrist cartilage in MR images
The study objective was to investigate the performance of a dedicated
convolutional neural network (CNN) optimized for wrist cartilage segmentation
from 2D MR images. CNN utilized a planar architecture and patch-based (PB)
training approach that ensured optimal performance in the presence of a limited
amount of training data. The CNN was trained and validated in twenty
multi-slice MRI datasets acquired with two different coils in eleven subjects
(healthy volunteers and patients). The validation included a comparison with
the alternative state-of-the-art CNN methods for the segmentation of joints
from MR images and the ground-truth manual segmentation. When trained on the
limited training data, the CNN outperformed significantly image-based and
patch-based U-Net networks. Our PB-CNN also demonstrated a good agreement with
manual segmentation (Sorensen-Dice similarity coefficient (DSC) = 0.81) in the
representative (central coronal) slices with large amount of cartilage tissue.
Reduced performance of the network for slices with a very limited amount of
cartilage tissue suggests the need for fully 3D convolutional networks to
provide uniform performance across the joint. The study also assessed inter-
and intra-observer variability of the manual wrist cartilage segmentation
(DSC=0.78-0.88 and 0.9, respectively). The proposed deep-learning-based
segmentation of the wrist cartilage from MRI could facilitate research of novel
imaging markers of wrist osteoarthritis to characterize its progression and
response to therapy
Avenues of cognition of nongravitational local gauge field theories
This controbution is devoted to present basic fearures of a unifying local gauge field theory, prevailing up to a mass scale of approximately 10 16 GeV , allowing the neglect of gravitational curvature effects – indicated by the attribute : ’nongravitational’ in the title above
Compendio de las memorias para servir a la historia del Jacobinismo
Copia digital. Valladolid : Junta de Castilla y León. Consejería de Cultura y Turismo, 2009-201
Quark-Resonance model
We construct an effective Lagrangian for low energy hadronic interactions
through an infinite expansion in inverse powers of the low energy cutoff
of all possible chiral invariant non-renormalizable interactions
between quarks and mesons degrees of freedom. We restrict our analysis to the
leading terms in the expansion. The effective expansion is in
(\mu^2/\cutoff^2 )^P \ln (\cutoff^2/\mu^2 )^Q. Concerning the next-to-leading
order, we show that, while the pure \mu^2/\cutoff^2 corrections cannot be
traced back to a finite number of non renormalizable interactions, those of
order (\mu^2/\cutoff^2 ) \ln (\cutoff^2/\mu^2 ) receive contributions from a
finite set of 1/\cutoff^2 terms. Their presence modifies the behaviour of
observable quantities in the intermediate region. We explicitely discuss
their relevance for the two point vector currents Green's function.Comment: 41 pages, 11 figures, preprint ROM2F 93/3
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