| 1. |
- Abelev, Betty, et al.
(author)
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Long-range angular correlations on the near and away side in p-Pb collisions at root S-NN=5.02 TeV
- 2013
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In: Physics Letters. Section B: Nuclear, Elementary Particle and High-Energy Physics. - : Elsevier BV. - 0370-2693. ; 719:1-3, s. 29-41
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Journal article (peer-reviewed)abstract
- Angular correlations between charged trigger and associated particles are measured by the ALICE detector in p-Pb collisions at a nucleon-nucleon centre-of-mass energy of 5.02 TeV for transverse momentum ranges within 0.5 < P-T,P-assoc < P-T,P-trig < 4 GeV/c. The correlations are measured over two units of pseudorapidity and full azimuthal angle in different intervals of event multiplicity, and expressed as associated yield per trigger particle. Two long-range ridge-like structures, one on the near side and one on the away side, are observed when the per-trigger yield obtained in low-multiplicity events is subtracted from the one in high-multiplicity events. The excess on the near-side is qualitatively similar to that recently reported by the CMS Collaboration, while the excess on the away-side is reported for the first time. The two-ridge structure projected onto azimuthal angle is quantified with the second and third Fourier coefficients as well as by near-side and away-side yields and widths. The yields on the near side and on the away side are equal within the uncertainties for all studied event multiplicity and p(T) bins, and the widths show no significant evolution with event multiplicity or p(T). These findings suggest that the near-side ridge is accompanied by an essentially identical away-side ridge. (c) 2013 CERN. Published by Elsevier B.V. All rights reserved.
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| 2. |
- Abelev, Betty, et al.
(author)
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Measurement of prompt J/psi and beauty hadron production cross sections at mid-rapidity in pp collisions at root s=7 TeV
- 2012
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In: Journal of High Energy Physics. - 1029-8479. ; :11
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Journal article (peer-reviewed)abstract
- The ALICE experiment at the LHC has studied J/psi production at mid-rapidity in pp collisions at root s = 7 TeV through its electron pair decay on a data sample corresponding to an integrated luminosity L-int = 5.6 nb(-1). The fraction of J/psi from the decay of long-lived beauty hadrons was determined for J/psi candidates with transverse momentum p(t) > 1,3 GeV/c and rapidity vertical bar y vertical bar < 0.9. The cross section for prompt J/psi mesons, i.e. directly produced J/psi and prompt decays of heavier charmonium states such as the psi(2S) and chi(c) resonances, is sigma(prompt J/psi) (p(t) > 1.3 GeV/c, vertical bar y vertical bar < 0.9) = 8.3 +/- 0.8(stat.) +/- 1.1 (syst.)(-1.4)(+1.5) (syst. pol.) mu b. The cross section for the production of b-hadrons decaying to J/psi with p(t) > 1.3 GeV/c and vertical bar y vertical bar < 0.9 is a sigma(J/psi <- hB) (p(t) > 1.3 GeV/c, vertical bar y vertical bar < 0.9) = 1.46 +/- 0.38 (stat.)(-0.32)(+0.26) (syst.) mu b. The results are compared to QCD model predictions. The shape of the p(t) and y distributions of b-quarks predicted by perturbative QCD model calculations are used to extrapolate the measured cross section to derive the b (b) over bar pair total cross section and d sigma/dy at mid-rapidity.
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| 3. |
- Abelev, Betty, et al.
(author)
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Underlying Event measurements in pp collisions at root s=0.9 and 7 TeV with the ALICE experiment at the LHC
- 2012
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In: Journal of High Energy Physics. - 1029-8479. ; :7
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Journal article (peer-reviewed)abstract
- We present measurements of Underlying Event observables in pp collisions at root s = 0 : 9 and 7 TeV. The analysis is performed as a function of the highest charged-particle transverse momentum p(T),L-T in the event. Different regions are defined with respect to the azimuthal direction of the leading (highest transverse momentum) track: Toward, Transverse and Away. The Toward and Away regions collect the fragmentation products of the hardest partonic interaction. The Transverse region is expected to be most sensitive to the Underlying Event activity. The study is performed with charged particles above three different p(T) thresholds: 0.15, 0.5 and 1.0 GeV/c. In the Transverse region we observe an increase in the multiplicity of a factor 2-3 between the lower and higher collision energies, depending on the track p(T) threshold considered. Data are compared to PYTHIA 6.4, PYTHIA 8.1 and PHOJET. On average, all models considered underestimate the multiplicity and summed p(T) in the Transverse region by about 10-30%.
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| 4. |
- Gonzalez-Ericsson, Paula, et al.
(author)
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The path to a better biomarker: application of a risk management framework for the implementation of PD‐L1 and TILs as immuno‐oncology biomarkers into breast cancer clinical trials and daily practice
- 2020
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In: Journal of Pathology. - : Wiley. - 1096-9896 .- 0022-3417. ; 250:5, s. 667-684
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Research review (peer-reviewed)abstract
- Immune checkpoint inhibitor therapies targeting PD‐1/PD‐L1 are now the standard of care in oncology across several hematologic and solid tumor types, including triple negative breast cancer (TNBC). Patients with metastatic or locally advanced TNBC with PD‐L1 expression on immune cells occupying ≥1% of tumor area demonstrated survival benefit with the addition of atezolizumab to nab‐paclitaxel. However, concerns regarding variability between immunohistochemical PD‐L1 assay performance and inter‐reader reproducibility have been raised. High tumor‐infiltrating lymphocytes (TILs) have also been associated with response to PD‐1/PD‐L1 inhibitors in patients with breast cancer (BC). TILs can be easily assessed on hematoxylin and eosin–stained slides and have shown reliable inter‐reader reproducibility. As an established prognostic factor in early stage TNBC, TILs are soon anticipated to be reported in daily practice in many pathology laboratories worldwide. Because TILs and PD‐L1 are parts of an immunological spectrum in BC, we propose the systematic implementation of combined PD‐L1 and TIL analyses as a more comprehensive immuno‐oncological biomarker for patient selection for PD‐1/PD‐L1 inhibition‐based therapy in patients with BC. Although practical and regulatory considerations differ by jurisdiction, the pathology community has the responsibility to patients to implement assays that lead to optimal patient selection. We propose herewith a risk‐management framework that may help mitigate the risks of suboptimal patient selection for immuno‐therapeutic approaches in clinical trials and daily practice based on combined TILs/PD‐L1 assessment in BC.
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| 5. |
- Kattge, Jens, et al.
(author)
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TRY plant trait database - enhanced coverage and open access
- 2020
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In: Global Change Biology. - : Wiley-Blackwell. - 1354-1013 .- 1365-2486. ; 26:1, s. 119-188
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Journal article (peer-reviewed)abstract
- Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.
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| 6. |
- Leon-Ferre, Roberto A., et al.
(author)
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Automated mitotic spindle hotspot counts are highly associated with clinical outcomes in systemically untreated early-stage triple-negative breast cancer
- 2024
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In: npj Breast Cancer. - : NATURE PORTFOLIO. - 2374-4677. ; 10:1
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Journal article (peer-reviewed)abstract
- Operable triple-negative breast cancer (TNBC) has a higher risk of recurrence and death compared to other subtypes. Tumor size and nodal status are the primary clinical factors used to guide systemic treatment, while biomarkers of proliferation have not demonstrated value. Recent studies suggest that subsets of TNBC have a favorable prognosis, even without systemic therapy. We evaluated the association of fully automated mitotic spindle hotspot (AMSH) counts with recurrence-free (RFS) and overall survival (OS) in two separate cohorts of patients with early-stage TNBC who did not receive systemic therapy. AMSH counts were obtained from areas with the highest mitotic density in digitized whole slide images processed with a convolutional neural network trained to detect mitoses. In 140 patients from the Mayo Clinic TNBC cohort, AMSH counts were significantly associated with RFS and OS in a multivariable model controlling for nodal status, tumor size, and tumor-infiltrating lymphocytes (TILs) (p < 0.0001). For every 10-point increase in AMSH counts, there was a 16% increase in the risk of an RFS event (HR 1.16, 95% CI 1.08-1.25), and a 7% increase in the risk of death (HR 1.07, 95% CI 1.00-1.14). We corroborated these findings in a separate cohort of systemically untreated TNBC patients from Radboud UMC in the Netherlands. Our findings suggest that AMSH counts offer valuable prognostic information in patients with early-stage TNBC who did not receive systemic therapy, independent of tumor size, nodal status, and TILs. If further validated, AMSH counts could help inform future systemic therapy de-escalation strategies.
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| 7. |
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| 8. |
- Dittrich, Christian, et al.
(author)
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ESMO / ASCO Recommendations for a Global Curriculum in Medical Oncology Edition 2016
- 2016
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In: ESMO Open. - : Elsevier BV. - 2059-7029. ; 1:5
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Journal article (peer-reviewed)abstract
- The European Society for Medical Oncology (ESMO) and the American Society of Clinical Oncology (ASCO) are publishing a new edition of the ESMO/ ASCO Global Curriculum (GC) thanks to contribution of 64 ESMOappointed and 32 ASCO-appointed authors. First published in 2004 and updated in 2010, the GC edition 2016 answers to the need for updated recommendations for the training of physicians in medical oncology by defining the standard to be fulfilled to qualify as medical oncologists. At times of internationalisation of healthcare and increased mobility of patients and physicians, the GC aims to provide state-of-the-art cancer care to all patients wherever they live. Recent progress in the field of cancer research has indeed resulted in diagnostic and therapeutic innovations such as targeted therapies as a standard therapeutic approach or personalised cancer medicine specialised training for medical oncology trainees. Thus, several new chapters on technical contents such as molecular pathology, translational research or molecular imaging and on conceptual attitudes towards human principles like genetic counselling or survivorship have been integrated in the GC. The GC edition 2016 consists of 12 sections with 17 subsections, 44 chapters and 35 subchapters, respectively. Besides renewal in its contents, the GC underwent a principal formal change taking into consideration modern didactic principles. It is presented in a template-based format that subcategorises the detailed outcome requirements into learning objectives, awareness, knowledge and skills. Consecutive steps will be those of harmonising and implementing teaching and assessment strategies.
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| 9. |
- Elfer, Katherine, et al.
(author)
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Pilot study to evaluate tools to collect pathologist annotations for validating machine learning algorithms
- 2022
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In: Journal of Medical Imaging. - 2329-4302. ; 9:4, s. 1-14
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Journal article (peer-reviewed)abstract
- Purpose: Validation of artificial intelligence (AI) algorithms in digital pathology with a reference standard is necessary before widespread clinical use, but few examples focus on creating a reference standard based on pathologist annotations. This work assesses the results of a pilot study that collects density estimates of stromal tumor-infiltrating lymphocytes (sTILs) in breast cancer biopsy specimens. This work will inform the creation of a validation dataset for the evaluation of AI algorithms fit for a regulatory purpose. Approach: Collaborators and crowdsourced pathologists contributed glass slides, digital images, and annotations. Here, "annotations" refer to any marks, segmentations, measurements, or labels a pathologist adds to a report, image, region of interest (ROI), or biological feature. Pathologists estimated sTILs density in 640 ROIs from hematoxylin and eosin stained slides of 64 patients via two modalities: an optical light microscope and two digital image viewing platforms. Results: The pilot study generated 7373 sTILs density estimates from 29 pathologists. Analysis of annotations found the variability of density estimates per ROI increases with the mean; the root mean square differences were 4.46, 14.25, and 26.25 as the mean density ranged from 0% to 10%, 11% to 40%, and 41% to 100%, respectively. The pilot study informs three areas of improvement for future work: technical workflows, annotation platforms, and agreement analysis methods. Upgrades to the workflows and platforms will improve operability and increase annotation speed and consistency. Conclusions: Exploratory data analysis demonstrates the need to develop new statistical approaches for agreement. The pilot study dataset and analysis methods are publicly available to allow community feedback. The development and results of the validation dataset will be publicly available to serve as an instructive tool that can be replicated by developers and researchers.
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| 10. |
- Elfer, Katherine, et al.
(author)
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Reproducible Reporting of the Collection and Evaluation of Annotations for Artificial Intelligence Models
- 2024
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In: Modern Pathology : an official journal of the United States and Canadian Academy of Pathology, Inc. - 1530-0285. ; 37:4
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Journal article (peer-reviewed)abstract
- This work advances and demonstrates the utility of a reporting framework for collecting and evaluating annotations of medical images used for training and testing artificial intelligence (AI) models in assisting detection and diagnosis. AI has unique reporting requirements, as shown by the AI extensions to the CONSORT (Consolidated Standards of Reporting Trials) and SPIRIT (Standard Protocol Items: Recommendations for Interventional Trials) checklists and the proposed AI extensions to the STARD (Standards for Reporting Diagnostic Accuracy) and TRIPOD (Transparent Reporting of a multivariable prediction model for Individual Prognosis Or Diagnosis) checklists. AI for detection and/or diagnostic image analysis requires complete, reproducible, and transparent reporting of the annotations and metadata used in training and testing datasets. Prior work by Wahab et al. proposed an annotation workflow and quality checklist for computational pathology annotations. In this manuscript, we operationalize this workflow into an evaluable quality checklist that applies to any reader-interpreted medical images, and we demonstrate its use for an annotation effort in digital pathology. We refer to this quality framework as CLEARR-AI: The Collection and Evaluation of Annotations for Reproducible Reporting of Artificial Intelligence.
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