111 research outputs found
Constructing Agency: The Role of Language
Is agency a straightforward and universal feature of human experience? Or is the construction of agency (including attention to and memory for people involved in events) guided by patterns in culture? In this paper we focus on one aspect of cultural experience: patterns in language. We examined English and Japanese speakers’ descriptions of intentional and accidental events. English and Japanese speakers described intentional events similarly, using mostly agentive language (e.g., “She broke the vase”). However, when it came to accidental events English speakers used more agentive language than did Japanese speakers. We then tested whether these different patterns found in language may also manifest in cross-cultural differences in attention and memory. Results from a non-linguistic memory task showed that English and Japanese speakers remembered the agents of intentional events equally well. However, English speakers remembered the agents of accidents better than did Japanese speakers, as predicted from patterns in language. Further, directly manipulating agency in language during another laboratory task changed people’s eye-witness memory, confirming a possible causal role for language. Patterns in one’s linguistic environment may promote and support how people instantiate agency in context
Virtual finger boosts three-dimensional imaging and microsurgery as well as terabyte volume image visualization and analysis
Three-dimensional (3D) bioimaging, visualization and data analysis are in strong need of powerful 3D exploration techniques. We develop virtual finger (VF) to generate 3D curves, points and regions-of-interest in the 3D space of a volumetric image with a single finger operation, such as a computer mouse stroke, or click or zoom from the 2D-projection plane of an image as visualized with a computer. VF provides efficient methods for acquisition, visualization and analysis of 3D images for roundworm, fruitfly, dragonfly, mouse, rat and human. Specifically, VF enables instant 3D optical zoom-in imaging, 3D free-form optical microsurgery, and 3D visualization and annotation of terabytes of whole-brain image volumes. VF also leads to orders of magnitude better efficiency of automated 3D reconstruction of neurons and similar biostructures over our previous systems. We use VF to generate from images of 1,107 Drosophila GAL4 lines a projectome of a Drosophila brain. © 2014 Macmillan Publishers Limited. All rights reserved
COVID-19 in patients with thoracic malignancies (TERAVOLT): first results of an international, registry-based, cohort study
Background: Early reports on patients with cancer and COVID-19 have suggested a high mortality rate compared with the general population. Patients with thoracic malignancies are thought to be particularly susceptible to COVID-19 given their older age, smoking habits, and pre-existing cardiopulmonary comorbidities, in addition to cancer treatments. We aimed to study the effect of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection on patients with thoracic malignancies.
Methods: The Thoracic Cancers International COVID-19 Collaboration (TERAVOLT) registry is a multicentre observational study composed of a cross-sectional component and a longitudinal cohort component. Eligibility criteria were the presence of any thoracic cancer (non-small-cell lung cancer [NSCLC], small-cell lung cancer, mesothelioma, thymic epithelial tumours, and other pulmonary neuroendocrine neoplasms) and a COVID-19 diagnosis, either laboratory confirmed with RT-PCR, suspected with symptoms and contacts, or radiologically suspected cases with lung imaging features consistent with COVID-19 pneumonia and symptoms. Patients of any age, sex, histology, or stage were considered eligible, including those in active treatment and clinical follow-up. Clinical data were extracted from medical records of consecutive patients from Jan 1, 2020, and will be collected until the end of pandemic declared by WHO. Data on demographics, oncological history and comorbidities, COVID-19 diagnosis, and course of illness and clinical outcomes were collected. Associations between demographic or clinical characteristics and outcomes were measured with odds ratios (ORs) with 95% CIs using univariable and multivariable logistic regression, with sex, age, smoking status, hypertension, and chronic obstructive pulmonary disease included in multivariable analysis. This is a preliminary analysis of the first 200 patients. The registry continues to accept new sites and patient data.
Findings: Between March 26 and April 12, 2020, 200 patients with COVID-19 and thoracic cancers from eight countries were identified and included in the TERAVOLT registry; median age was 68·0 years (61·8-75·0) and the majority had an Eastern Cooperative Oncology Group performance status of 0-1 (142 [72%] of 196 patients), were current or former smokers (159 [81%] of 196), had non-small-cell lung cancer (151 [76%] of 200), and were on therapy at the time of COVID-19 diagnosis (147 [74%] of 199), with 112 (57%) of 197 on first-line treatment. 152 (76%) patients were hospitalised and 66 (33%) died. 13 (10%) of 134 patients who met criteria for ICU admission were admitted to ICU; the remaining 121 were hospitalised, but were not admitted to ICU. Univariable analyses revealed that being older than 65 years (OR 1·88, 95% 1·00-3·62), being a current or former smoker (4·24, 1·70-12·95), receiving treatment with chemotherapy alone (2·54, 1·09-6·11), and the presence of any comorbidities (2·65, 1·09-7·46) were associated with increased risk of death. However, in multivariable analysis, only smoking history (OR 3·18, 95% CI 1·11-9·06) was associated with increased risk of death.
Interpretation: With an ongoing global pandemic of COVID-19, our data suggest high mortality and low admission to intensive care in patients with thoracic cancer. Whether mortality could be reduced with treatment in intensive care remains to be determined. With improved cancer therapeutic options, access to intensive care should be discussed in a multidisciplinary setting based on cancer specific mortality and patients' preference
Whole-body tissue stabilization and selective extractions via tissue-hydrogel hybrids for high-resolution intact circuit mapping and phenotyping
To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue fixation-embedding, detergent-clearing and staining protocols that can be used to transform excised organs and whole organisms into optically transparent samples within 1–2 weeks without compromising their cellular architecture or endogenous fluorescence. PACT (passive CLARITY technique) and PARS (perfusion-assisted agent release in situ) use tissue-hydrogel hybrids to stabilize tissue biomolecules during selective lipid extraction, resulting in enhanced clearing efficiency and sample integrity. Furthermore, the macromolecule permeability of PACT- and PARS-processed tissue hybrids supports the diffusion of immunolabels throughout intact tissue, whereas RIMS (refractive index matching solution) grants high-resolution imaging at depth by further reducing light scattering in cleared and uncleared samples alike. These methods are adaptable to difficult-to-image tissues, such as bone (PACT-deCAL), and to magnified single-cell visualization (ePACT). Together, these protocols and solutions enable phenotyping of subcellular components and tracing cellular connectivity in intact biological networks
Convalescent plasma in patients admitted to hospital with COVID-19 (RECOVERY): a randomised controlled, open-label, platform trial
SummaryBackground Azithromycin has been proposed as a treatment for COVID-19 on the basis of its immunomodulatoryactions. We aimed to evaluate the safety and efficacy of azithromycin in patients admitted to hospital with COVID-19.Methods In this randomised, controlled, open-label, adaptive platform trial (Randomised Evaluation of COVID-19Therapy [RECOVERY]), several possible treatments were compared with usual care in patients admitted to hospitalwith COVID-19 in the UK. The trial is underway at 176 hospitals in the UK. Eligible and consenting patients wererandomly allocated to either usual standard of care alone or usual standard of care plus azithromycin 500 mg once perday by mouth or intravenously for 10 days or until discharge (or allocation to one of the other RECOVERY treatmentgroups). Patients were assigned via web-based simple (unstratified) randomisation with allocation concealment andwere twice as likely to be randomly assigned to usual care than to any of the active treatment groups. Participants andlocal study staff were not masked to the allocated treatment, but all others involved in the trial were masked to theoutcome data during the trial. The primary outcome was 28-day all-cause mortality, assessed in the intention-to-treatpopulation. The trial is registered with ISRCTN, 50189673, and ClinicalTrials.gov, NCT04381936.Findings Between April 7 and Nov 27, 2020, of 16 442 patients enrolled in the RECOVERY trial, 9433 (57%) wereeligible and 7763 were included in the assessment of azithromycin. The mean age of these study participants was65·3 years (SD 15·7) and approximately a third were women (2944 [38%] of 7763). 2582 patients were randomlyallocated to receive azithromycin and 5181 patients were randomly allocated to usual care alone. Overall,561 (22%) patients allocated to azithromycin and 1162 (22%) patients allocated to usual care died within 28 days(rate ratio 0·97, 95% CI 0·87–1·07; p=0·50). No significant difference was seen in duration of hospital stay (median10 days [IQR 5 to >28] vs 11 days [5 to >28]) or the proportion of patients discharged from hospital alive within 28 days(rate ratio 1·04, 95% CI 0·98–1·10; p=0·19). Among those not on invasive mechanical ventilation at baseline, nosignificant difference was seen in the proportion meeting the composite endpoint of invasive mechanical ventilationor death (risk ratio 0·95, 95% CI 0·87–1·03; p=0·24).Interpretation In patients admitted to hospital with COVID-19, azithromycin did not improve survival or otherprespecified clinical outcomes. Azithromycin use in patients admitted to hospital with COVID-19 should be restrictedto patients in whom there is a clear antimicrobial indication
Texform Size-Stroop Repository
Repository for: "A familiar-size Stroop effect in the absence of basic-level recognition
Recommended from our members
The role of language in eye-witness memory: Remembering who did it in English and Japanese
Mid-level visual features underlie the high-level categorical organization of the ventral stream
Repository for unpublished manuscrip
Real-world size is automatically encoded in preschoolers’ object representations
When adults see a picture of an object, they automatically process how big the object typically is in the real world (Konkle & Oliva, 2012a). How much life experience is needed for this automatic size processing to emerge? Here, we ask whether preschoolers show this same signature of automatic size processing. We showed 3- and 4-year-olds displays with two pictures of objects and asked them to touch the picture that was smaller on the screen. Critically, the relative visual sizes of the objects could either be congruent with their relative real-world sizes (e.g., a small picture of a shoe next to a big picture of a car) or incongruent with their relative real-world sizes (e.g., a big picture of a shoe next to a small picture of a car). Across two experiments, we found that preschoolers were worse at making visual size judgments on incongruent trials, suggesting that real-world size was automatically activated and interfered with their performance. In a third experiment, we found that both 4-year-olds and adults showed similar item-pair effects (i.e., showed larger Size-Stroop effects for the pairs of items, relative to other pairs). Furthermore, the magnitude of the item-pair Stroop effects in 4-year-olds did not depend on whether they could recognize the pictured objects, suggesting that the perceptual features of these objects were sufficient to trigger the processing of real-world size information. These results indicate that, by 3–4 years of age, children automatically extract real-world size information from depicted objects
- …