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- Buchanan, E. M., et al.
(författare)
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The Psychological Science Accelerator's COVID-19 rapid-response dataset
- 2023
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Ingår i: Scientific Data. - : Springer Science and Business Media LLC. - 2052-4463. ; 10:1
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Tidskriftsartikel (refereegranskat)abstract
- In response to the COVID-19 pandemic, the Psychological Science Accelerator coordinated three large-scale psychological studies to examine the effects of loss-gain framing, cognitive reappraisals, and autonomy framing manipulations on behavioral intentions and affective measures. The data collected (April to October 2020) included specific measures for each experimental study, a general questionnaire examining health prevention behaviors and COVID-19 experience, geographical and cultural context characterization, and demographic information for each participant. Each participant started the study with the same general questions and then was randomized to complete either one longer experiment or two shorter experiments. Data were provided by 73,223 participants with varying completion rates. Participants completed the survey from 111 geopolitical regions in 44 unique languages/dialects. The anonymized dataset described here is provided in both raw and processed formats to facilitate re-use and further analyses. The dataset offers secondary analytic opportunities to explore coping, framing, and self-determination across a diverse, global sample obtained at the onset of the COVID-19 pandemic, which can be merged with other time-sampled or geographic data.
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| 6. |
- Armengaud, E., et al.
(författare)
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Physics potential of the International Axion Observatory (IAXO)
- 2019
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Ingår i: Journal of Cosmology and Astroparticle Physics. - : IOP Publishing. - 1475-7516. ; :6
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Tidskriftsartikel (refereegranskat)abstract
- We review the physics potential of a next generation search for solar axions: the International Axion Observatory (IAXO). Endowed with a sensitivity to discover axion-like particles (ALPs) with a coupling to photons as small as g(a gamma) similar to 10(-12) GeV-1, or to electrons g(ae) similar to 10(-13), IAXO has the potential to find the QCD axion in the 1 meV similar to 1 eV mass range where it solves the strong CP problem, can account for the cold dark matter of the Universe and be responsible for the anomalous cooling observed in a number of stellar systems. At the same time, IAXO will have enough sensitivity to detect lower mass axions invoked to explain: 1) the origin of the anomalous transparency of the Universe to gamma-rays, 2) the observed soft X-ray excess from galaxy clusters or 3) some inflationary models. In addition, we review string theory axions with parameters accessible by IAXO and discuss their potential role in cosmology as Dark Matter and Dark Radiation as well as their connections to the above mentioned conundrums.
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| 8. |
- Didion, JP, et al.
(författare)
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R2d2 Drives Selfish Sweeps in the House Mouse
- 2016
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Ingår i: Molecular biology and evolution. - : Oxford University Press (OUP). - 1537-1719 .- 0737-4038. ; 33:6, s. 1381-1395
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Tidskriftsartikel (refereegranskat)
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| 9. |
- Silver Karcioglu, Amanda L., et al.
(författare)
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Emerging Imaging Technologies for Parathyroid Gland Identification and Vascular Assessment in Thyroid Surgery : A Review from the American Head and Neck Society Endocrine Surgery Section
- 2023
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Ingår i: JAMA Otolaryngology - Head and Neck Surgery. - : American Medical Association (AMA). - 2168-6181. ; 149:3, s. 253-260
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Forskningsöversikt (refereegranskat)abstract
- Importance: Identification and preservation of parathyroid glands (PGs) remain challenging despite advances in surgical techniques. Considerable morbidity and even mortality result from hypoparathyroidism caused by devascularization or inadvertent removal of PGs. Emerging imaging technologies hold promise to improve identification and preservation of PGs during thyroid surgery. Observation: This narrative review (1) comprehensively reviews PG identification and vascular assessment using near-infrared autofluorescence (NIRAF) - both label free and in combination with indocyanine green - based on a comprehensive literature review and (2) offers a manual for possible implementation these emerging technologies in thyroid surgery. Conclusions and Relevance: Emerging technologies hold promise to improve PG identification and preservation during thyroidectomy. Future research should address variables affecting the degree of fluorescence in NIRAF, standardization of signal quantification, definitions and standardization of parameters of indocyanine green injection that correlate with postoperative PG function, the financial effect of these emerging technologies on near-term and longer-term costs, the adoption learning curve and effect on surgical training, and long-term outcomes of key quality metrics in adequately powered randomized clinical trials evaluating PG preservation.
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| 10. |
- Strom, Peter, et al.
(författare)
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Artificial intelligence for diagnosis and grading of prostate cancer in biopsies : a population-based, diagnostic study
- 2020
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Ingår i: The Lancet Oncology. - : Elsevier. - 1470-2045 .- 1474-5488. ; 21:2, s. 222-232
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Tidskriftsartikel (refereegranskat)abstract
- BackgroundAn increasing volume of prostate biopsies and a worldwide shortage of urological pathologists puts a strain on pathology departments. Additionally, the high intra-observer and inter-observer variability in grading can result in overtreatment and undertreatment of prostate cancer. To alleviate these problems, we aimed to develop an artificial intelligence (AI) system with clinically acceptable accuracy for prostate cancer detection, localisation, and Gleason grading.MethodsWe digitised 6682 slides from needle core biopsies from 976 randomly selected participants aged 50–69 in the Swedish prospective and population-based STHLM3 diagnostic study done between May 28, 2012, and Dec 30, 2014 (ISRCTN84445406), and another 271 from 93 men from outside the study. The resulting images were used to train deep neural networks for assessment of prostate biopsies. The networks were evaluated by predicting the presence, extent, and Gleason grade of malignant tissue for an independent test dataset comprising 1631 biopsies from 246 men from STHLM3 and an external validation dataset of 330 biopsies from 73 men. We also evaluated grading performance on 87 biopsies individually graded by 23 experienced urological pathologists from the International Society of Urological Pathology. We assessed discriminatory performance by receiver operating characteristics and tumour extent predictions by correlating predicted cancer length against measurements by the reporting pathologist. We quantified the concordance between grades assigned by the AI system and the expert urological pathologists using Cohen's kappa.FindingsThe AI achieved an area under the receiver operating characteristics curve of 0·997 (95% CI 0·994–0·999) for distinguishing between benign (n=910) and malignant (n=721) biopsy cores on the independent test dataset and 0·986 (0·972–0·996) on the external validation dataset (benign n=108, malignant n=222). The correlation between cancer length predicted by the AI and assigned by the reporting pathologist was 0·96 (95% CI 0·95–0·97) for the independent test dataset and 0·87 (0·84–0·90) for the external validation dataset. For assigning Gleason grades, the AI achieved a mean pairwise kappa of 0·62, which was within the range of the corresponding values for the expert pathologists (0·60–0·73).InterpretationAn AI system can be trained to detect and grade cancer in prostate needle biopsy samples at a ranking comparable to that of international experts in prostate pathology. Clinical application could reduce pathology workload by reducing the assessment of benign biopsies and by automating the task of measuring cancer length in positive biopsy cores. An AI system with expert-level grading performance might contribute a second opinion, aid in standardising grading, and provide pathology expertise in parts of the world where it does not exist.
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