| 1. |
- Jones, Benedict C, et al.
(author)
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To which world regions does the valence-dominance model of social perception apply?
- 2021
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In: Nature Human Behaviour. - : Springer Science and Business Media LLC. - 2397-3374. ; 5:1, s. 159-169
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Journal article (peer-reviewed)abstract
- Over the past 10 years, Oosterhof and Todorov's valence-dominance model has emerged as the most prominent account of how people evaluate faces on social dimensions. In this model, two dimensions (valence and dominance) underpin social judgements of faces. Because this model has primarily been developed and tested in Western regions, it is unclear whether these findings apply to other regions. We addressed this question by replicating Oosterhof and Todorov's methodology across 11 world regions, 41 countries and 11,570 participants. When we used Oosterhof and Todorov's original analysis strategy, the valence-dominance model generalized across regions. When we used an alternative methodology to allow for correlated dimensions, we observed much less generalization. Collectively, these results suggest that, while the valence-dominance model generalizes very well across regions when dimensions are forced to be orthogonal, regional differences are revealed when we use different extraction methods and correlate and rotate the dimension reduction solution. PROTOCOL REGISTRATION: The stage 1 protocol for this Registered Report was accepted in principle on 5 November 2018. The protocol, as accepted by the journal, can be found at https://doi.org/10.6084/m9.figshare.7611443.v1 .
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| 2. |
- Afshari, Ali, et al.
(author)
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Evaluation of the robustness of cerebral oximetry to variations in skin pigmentation using a tissue-simulating phantom
- 2022
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In: Biomedical Optics Express. - Washington, DC, United States : Optica Publishing Group. - 2156-7085. ; 13:5, s. 2909-2928
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Journal article (peer-reviewed)abstract
- Clinical studies have demonstrated that epidermal pigmentation level can affect cerebral oximetry measurements. To evaluate the robustness of these devices, we have developed a phantom-based test method that includes an epidermis-simulating layer with several melanin concentrations and a 3D-printed cerebrovascular module. Measurements were performed with neonatal, pediatric and adult sensors from two commercial oximeters, where neonatal probes had shorter source-detector separation distances. Referenced blood oxygenation levels ranged from 30 to 90%. Cerebral oximeter outputs exhibited a consistent decrease in saturation level with simulated melanin content; this effect was greatest at low saturation levels, producing a change of up to 15%. Dependence on pigmentation was strongest in a neonatal sensor, possibly due to its high reflectivity. Overall, our findings indicate that a modular channel-array phantom approach can provide a practical tool for assessing the impact of skin pigmentation on cerebral oximeter performance and that modifications to algorithms and/or instrumentation may be needed to mitigate pigmentation bias.
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| 3. |
- Vazquez, Sara E., et al.
(author)
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Autoantibody discovery across monogenic, acquired, and COVID-19-associated autoimmunity with scalable PhIP-seq
- 2022
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In: eLIFE. - : eLife Sciences Publications Ltd. - 2050-084X. ; 11
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Journal article (peer-reviewed)abstract
- Phage immunoprecipitation sequencing (PhIP-seq) allows for unbiased, proteome-wide autoantibody discovery across a variety of disease settings, with identification of disease-specific autoantigens providing new insight into previously poorly understood forms of immune dysregulation. Despite several successful implementations of PhIP-seq for autoantigen discovery, including our previous work (Vazquez et al., 2020), current protocols are inherently difficult to scale to accommodate large cohorts of cases and importantly, healthy controls. Here, we develop and validate a high throughput extension of PhIP-seq in various etiologies of autoimmune and inflammatory diseases, including APS1, IPEX, RAG1/2 deficiency, Kawasaki disease (KD), multisystem inflammatory syndrome in children (MIS-C), and finally, mild and severe forms of COVID-19. We demonstrate that these scaled datasets enable machine-learning approaches that result in robust prediction of disease status, as well as the ability to detect both known and novel autoantigens, such as prodynorphin (PDYN) in APS1 patients, and intestinally expressed proteins BEST4 and BTNL8 in IPEX patients. Remarkably, BEST4 antibodies were also found in two patients with RAG1/2 deficiency, one of whom had very early onset IBD. Scaled PhIP-seq examination of both MIS-C and KD demonstrated rare, overlapping antigens, including CGNL1, as well as several strongly enriched putative pneumonia-associated antigens in severe COVID-19, including the endosomal protein EEA1. Together, scaled PhIP-seq provides a valuable tool for broadly assessing both rare and common autoantigen overlap between autoimmune diseases of varying origins and etiologies.
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