University of California, San Francisco

About: University of California, San Francisco is a education organization based out in San Francisco, California, United States. It is known for research contribution in the topics: Population & Health care. The organization has 83381 authors who have published 186236 publications receiving 12068420 citations. The organization is also known as: UCSF & UC San Francisco.

Approaching a state shift in Earth’s biosphere

Abstract: There is evidence that human influence may be forcing the global ecosystem towards a rapid, irreversible, planetary-scale shift into a state unknown in human experience. Most forecasts of how the biosphere will change in response to human activity are rooted in projecting trajectories. Such models tend not anticipate critical transitions or tipping points, although recent work indicates a high probability of those taking place. And, at a local scale, ecosystems are known to shift abruptly between states when critical thresholds are passed. These authors review the evidence from across ecology and palaeontology that such a transition is being approached on the scale of the entire biosphere. They go on to suggest how biological forecasting might be improved to allow us to detect early warning signs of critical transitions on a global, as well as local, scale. Localized ecological systems are known to shift abruptly and irreversibly from one state to another when they are forced across critical thresholds. Here we review evidence that the global ecosystem as a whole can react in the same way and is approaching a planetary-scale critical transition as a result of human influence. The plausibility of a planetary-scale ‘tipping point’ highlights the need to improve biological forecasting by detecting early warning signs of critical transitions on global as well as local scales, and by detecting feedbacks that promote such transitions. It is also necessary to address root causes of how humans are forcing biological changes.

T-helper Type 2–driven Inflammation Defines Major Subphenotypes of Asthma

Abstract: Rationale: T-helper type 2 (Th2) inflammation, mediated by IL-4, IL-5, and IL-13, is considered the central molecular mechanism underlying asthma, and Th2 cytokines are emerging therapeutic targets. However, clinical studies increasingly suggest that asthma is heterogeneous.Objectives: To determine whether this clinical heterogeneity reflects heterogeneity in underlying molecular mechanisms related to Th2 inflammation.Methods: Using microarray and polymerase chain reaction analyses of airway epithelial brushings from 42 patients with mild-to-moderate asthma and 28 healthy control subjects, we classified subjects with asthma based on high or low expression of IL-13–inducible genes. We then validated this classification and investigated its clinical implications through analyses of cytokine expression in bronchial biopsies, markers of inflammation and remodeling, responsiveness to inhaled corticosteroids, and reproducibility on repeat examination.Measurements and Main Results: Gene expression analyses ident...

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping

Abstract: Background Radiomic features may quantify characteristics present in medical imaging. However, the lack of standardized definitions and validated reference values have hampered clinical use. Purpose To standardize a set of 174 radiomic features. Materials and Methods Radiomic features were assessed in three phases. In phase I, 487 features were derived from the basic set of 174 features. Twenty-five research teams with unique radiomics software implementations computed feature values directly from a digital phantom, without any additional image processing. In phase II, 15 teams computed values for 1347 derived features using a CT image of a patient with lung cancer and predefined image processing configurations. In both phases, consensus among the teams on the validity of tentative reference values was measured through the frequency of the modal value and classified as follows: less than three matches, weak; three to five matches, moderate; six to nine matches, strong; 10 or more matches, very strong. In the final phase (phase III), a public data set of multimodality images (CT, fluorine 18 fluorodeoxyglucose PET, and T1-weighted MRI) from 51 patients with soft-tissue sarcoma was used to prospectively assess reproducibility of standardized features. Results Consensus on reference values was initially weak for 232 of 302 features (76.8%) at phase I and 703 of 1075 features (65.4%) at phase II. At the final iteration, weak consensus remained for only two of 487 features (0.4%) at phase I and 19 of 1347 features (1.4%) at phase II. Strong or better consensus was achieved for 463 of 487 features (95.1%) at phase I and 1220 of 1347 features (90.6%) at phase II. Overall, 169 of 174 features were standardized in the first two phases. In the final validation phase (phase III), most of the 169 standardized features could be excellently reproduced (166 with CT; 164 with PET; and 164 with MRI). Conclusion A set of 169 radiomics features was standardized, which enabled verification and calibration of different radiomics software. © RSNA, 2020 Online supplemental material is available for this article. See also the editorial by Kuhl and Truhn in this issue.