Search

Abstract Facial expression perception is influenced by body posture, with perception biased toward the body emotion. Previous research has suggested that the magnitude of this biasing influence of body posture is driven by individual differences in the precision of facial expression representations underlying discrimination abilities, where lower precision leads to a greater influence of body posture. It is unclear however whether similar mechanisms might drive the influence of contextual cues in Autism, which is often characterised by reduced facial expression discrimination abilities. Here, we addressed this question by using online psychophysical methods to determine the precision of isolated face and body expression representations of anger and disgust, and the influence of body on facial expression perception, in autistic and non-autistic adults. Both groups showed a strong influence of body context on facial expression perception, but this influence was larger in the autistic group, mirroring their lower overall precision of facial expression representations relative to non-autistic individuals. Crucially, the magnitude of the biasing influence of body posture in both groups was related to the precision of individuals’ facial expression representations. The results suggest that similar principles govern the integration of facial expression and body posture information in both autistic and non-autistic individuals.

Abstract Background Brief questionnaires that comprehensively capture key restricted and repetitive behaviours (RRBs) across different informants have potential to support autism diagnostic services. We tested the psychometric properties of the 20-item Repetitive Behaviours Questionnaire-3 (RBQ-3), a questionnaire that includes self-report and informant-report versions enabling use across the lifespan. Method In Study 1, adults referred to a specialised adult autism diagnostic service (N = 110) completed the RBQ-3 self-report version, and a relative or long-term friend completed the RBQ-3 informant-report version. Clinicians completed the abbreviated version of the Diagnostic Interview for Social and Communication Disorders (DISCO-Abbreviated) with the same adults as part of the diagnostic process. For half of the assessments, clinicians were blind to the RBQ-3 ratings. We tested internal consistency, cross-informant reliability and convergent validity of the RBQ-3. In Study 2, a follow-up online study with autistic (N = 151) and non-autistic (N = 151) adults, we further tested internal consistency of the RBQ-3 self-report version. We also tested group differences and response patterns in this sample. Results Study 1 showed good to excellent internal consistency for both self- and informant-report versions of the RBQ-3 (total score, α = 0.90, ω = 0.90, subscales, α = 0.76-0.89, ω = 0.77-0.88). Study 1 also showed cross-informant reliability as the RBQ-3 self-report scores significantly correlated with RBQ-3 informant-report scores for the total score (r s = 0.71) and subscales (r s = 0.69-0.72). Convergent validity was found for both self and informant versions of the RBQ-3, which significantly correlated with DISCO-Abbreviated RRB domain scores (r s = 0.45-0.54). Moreover, the RBQ-3 scores showed significantly weaker association with DISCO -Abbreviated scores for the Social Communication domain, demonstrating divergent validity. Importantly, these patterns of validity were found even when clinicians were blind to RBQ-3 items. In Study 2, for both autistic and non-autistic groups, internal consistency was found for the total score (α = 0.82-0.89, ω = 0.81-0.81) and for subscales (α = 0.68-0.85, ω = 0.69-0.85). A group difference was found between groups. Limitations Due to the characteristics and scope of the specialist autism diagnostic service, further testing is needed to include representative samples of age (including children) and intellectual ability, and those with a non-autistic diagnostic outcome. Conclusions The RBQ-3 is a questionnaire of RRBs that can be used across the lifespan. The current study tested its psychometric properties with autistic adults without intellectual disability and supported its utility for both clinical diagnostic and research settings.

Improving our understanding of autism, ADHD, dyslexia and other neurodevelopmental conditions requires collaborations between genetics, psychiatry, the social sciences and other fields of research.

Abstract Autism Spectrum Disorder (ASD) and Attention-Deficit Hyperactivity Disorder (ADHD) are both linked to internalising problems like anxiety and depression. ASD and ADHD also often co-occur, making their individual statistical contributions to internalising disorders difficult to investigate. To address this issue, we explored the unique associations of self-reported ASD traits and ADHD traits with internalising problems using a large general population sample of adults from the United Kingdom (N = 504, 49% male). Classical regression analyses indicated that both ASD traits and ADHD traits were uniquely associated with internalising problems. Dominance and Bayesian analyses confirmed that ADHD traits were a stronger, more important predictor of internalising problems. However, brief depression and anxiety measures may not provide a comprehensive index of internalising problems. Additionally, we focused on recruiting a sample that was representative of the UK population according to age and sex, but not ethnicity, a variable that may be linked to internalising disorders. Nevertheless, our findings indicate that while ASD and ADHD uniquely predict internalising problems, ADHD traits are a more important statistical predictor than ASD traits. We discuss potential mechanisms underlying this pattern of results and the implications for research and clinical practice concerning neurodevelopmental conditions.

Environmental knowledge is considered an important pre-cursor to pro-environmental behaviour. Though several tools have been designed to measure environmental knowledge, there remains no concise, psychometrically grounded measure. We validated an existing measure in a British sample, confirming that it had good one- and three-factor structures in line with previous literature. For the first time in this field, we built upon previous Classical Test Theory approaches and used discrimination values derived from Item Response Theory to select the best items, resulting in the 19-Item Environmental Knowledge Test (EKT-19). This measure retained a clear factor structure and had moderate-to-good internal reliability, indicating that it is a parsimonious and psychometrically robust measure for the assessment of overall and specific types of environmental knowledge. The theoretical implications and real-world applications of this measure are discussed.

Abstract Omics-based tools were coupled with bioinformatics for a systeomics analysis of two biopharma cell types: Chinese hamster ovary (M-CHO and CHO-K1) and SP2/0. Exponential and stationary phase samples revealed more than 10,000 transcripts and 6000 proteins across these two manufacturing cell lines. A statistical comparison of transcriptomics and proteomics data identified downregulated genes involved in protein folding, protein synthesis and protein metabolism, including PPIA-cyclophilin A, HSPD1, and EIF3K, in M-CHO compared to SP2/0 while cell cycle and actin cytoskeleton genes were reduced in SP2/0. KEGG pathway comparisons revealed glycerolipids, glycosphingolipids, ABC transporters, calcium signaling, cell adhesion, and secretion pathways depleted in M-CHO while retinol metabolism was upregulated. KEGG and IPA also indicated apoptosis, RNA degradation, and proteosomes enriched in CHO stationary phase. Alternatively, gene ontology analysis revealed an underrepresentation in ion and potassium channel activities, membrane proteins, and secretory granules including Stxbpt2, Syt1, Syt9, and Cma1 proteins in M-CHO. Additional enrichment strategies involving ultracentrifugation, biotinylation, and hydrazide chemistry identified over 4000 potential CHO membrane and secretory proteins, yet many secretory and membrane proteins were still depleted. This systeomics pipeline has revealed bottlenecks and potential opportunities for cell line engineering in CHO and SP2/0 to improve their production capabilities.

Abstract Cancer biomarker discovery is critically dependent on the integrity of biofluid and tissue samples acquired from study participants. Multi-omic profiling of candidate protein, lipid, and metabolite biomarkers is confounded by timing and fasting status of sample collection, participant demographics and treatment exposures of the study population. Contamination by hemoglobin, whether caused by hemolysis during sample preparation or underlying red cell fragility, contributes 0–10 g/L of extraneous protein to plasma, serum, and Buffy coat samples and may interfere with biomarker detection and validation. We analyzed 617 plasma, 701 serum, and 657 buffy coat samples from a 7-year longitudinal multi-omic biomarker discovery program evaluating 400+ participants with or at risk for pancreatic cancer, known as Project Survival. Hemolysis was undetectable in 93.1% of plasma and 95.0% of serum samples, whereas only 37.1% of buffy coat samples were free of contamination by hemoglobin. Regression analysis of multi-omic data demonstrated a statistically significant correlation between hemoglobin concentration and the resulting pattern of analyte detection and concentration. Although hemolysis had the greatest impact on identification and quantitation of the proteome, distinct differentials in metabolomics and lipidomics were also observed and correlated with severity. We conclude that quality control is vital to accurate detection of informative molecular differentials using OMIC technologies and that caution must be exercised to minimize the impact of hemolysis as a factor driving false discovery in large cancer biomarker studies.

Individual differences in Theory of Mind (ToM)-the ability to understand the mental states of others-are theorised to be predicted by socio-demographic and political factors. However, inconsistent findings on the relationships between various socio-demographic predictors and ToM, as well as a paucity of research on political predictors of ToM, have left a gap in the literature. Using a recently validated self-report measure of ToM in a large sample (N = 4202) we investigated the unique contributions of age, sex, socio-economic status, and political beliefs to ToM in adults. Except for age, all variables were correlated with ToM, but when accounting for the variance of other predictors in statistical analyses, political beliefs was no longer associated with ToM. Dominance analysis revealed that participant sex was the most important predictor of ToM. These findings help to address theoretical discrepancies in the existing literature and inform future methods and directions in social cognition research.

Abstract Prostate cancer (PCa) is a heterogeneous group of tumors with variable clinical courses. In order to improve patient outcomes, it is critical to clinically separate aggressive PCa (AG) from non-aggressive PCa (NAG). Although recent genomic studies have identified a spectrum of molecular abnormalities associated with aggressive PCa, it is still challenging to separate AG from NAG. To better understand the functional consequences of PCa progression and the unique features of the AG subtype, we studied the proteomic signatures of primary AG, NAG and metastatic PCa. 39 PCa and 10 benign prostate controls in a discovery cohort and 57 PCa in a validation cohort were analyzed using a data-independent acquisition (DIA) SWATH–MS platform. Proteins with the highest variances (top 500 proteins) were annotated for the pathway enrichment analysis. Functional analysis of differentially expressed proteins in NAG and AG was performed. Data was further validated using a validation cohort; and was also compared with a TCGA mRNA expression dataset and confirmed by immunohistochemistry (IHC) using PCa tissue microarray (TMA). 4,415 proteins were identified in the tumor and benign control tissues, including 158 up-regulated and 116 down-regulated proteins in AG tumors. A functional analysis of tumor-associated proteins revealed reduced expressions of several proteinases, including dipeptidyl peptidase 4 (DPP4), carboxypeptidase E (CPE) and prostate specific antigen (KLK3) in AG and metastatic PCa. A targeted analysis further identified that the reduced expression of DPP4 was associated with the accumulation of DPP4 substrates and the reduced ratio of DPP4 cleaved peptide to intact substrate peptide. Findings were further validated using an independently-collected tumor cohort, correlated with a TCGA mRNA dataset, and confirmed by immunohistochemical stains of PCa tumor microarray (TMA). Our study is the first large-scale proteomics analysis of PCa tissue using a DIA SWATH-MS platform. It provides not only an interrogative proteomic signature of PCa subtypes, but also indicates the critical roles played by certain proteinases during tumor progression. The spectrum map and protein profile generated in the study can be used to investigate potential biological mechanisms involved in PCa and for the development of a clinical assay to distinguish aggressive from indolent PCa.

Abstract Background The male preponderance in autism diagnoses is widely reported, yet the psychological mechanisms (e.g., emotion processing) underlying this sex difference are poorly understood. Contributing to this gap in knowledge, most research has not been designed to investigate the intermediary (i.e., mediating) role of psychological processes in the relationship between sex and autism. Compounding this issue, concerns that autism measures are not reliably measuring the same constructs in males and females, and bias against females in clinical samples, make it difficult to investigate the psychological mechanisms underlying sex differences in autism. Methods Over two cross‐sectional studies, 1656 young adults from the general population reported their sex (as assigned at birth) and completed questionnaires indexing their emotion processing differences, as well as a measure of autistic traits suggested to tap into the same psychometric construct in males and females. Results Emotion processing differences mediated the relationship between sex and autistic traits, whereby being male was associated with more emotion processing differences, which were subsequently linked with greater levels of autistic traits. There remained a direct effect of sex on autistic traits after accounting for emotion processing differences. Conclusions Emotion processing differences are a potential psychological mechanism underpinning higher prevalence of autism in males, which may serve a compensatory function in females; for example, females may seek out emotion‐inducing experiences to help compensate for social‐emotional difficulties. These findings inform our understanding of autism‐related sex differences and have potential implications for clinical practice, where the need for sex‐specific support and diagnostic processes is increasingly being recognised.

Abstract Background There is growing recognition that some autistic people engage in ‘compensation’, showing few behavioural symptoms (e.g. neurotypical social skills), despite continuing to experience autism-related cognitive difficulties (e.g. difficulties in social cognition). One way this might be achieved is by individuals consciously employing ‘compensatory strategies’ during everyday social interaction. However, very little is currently known about the broad range of these strategies, their mechanisms and consequences for clinical presentation and diagnosis. Methods We aimed to measure compensatory strategies in autism for the first time. Using a novel checklist, we quantified self-reported social compensatory strategies in 117 adults (58 with autism, 59 without autism) and explored the relationships between compensation scores and autism diagnostic status, autistic traits, education level, sex and age at diagnosis. Results Higher compensation scores—representing a greater repertoire of compensatory strategies—were associated with having an autism diagnosis, more autistic traits and a higher education level. The link between autism diagnostic status and compensation scores was, however, explained by autistic traits and education level. Compensation scores were unrelated to sex or age at diagnosis. Limitations Our sample was self-selected and predominantly comprised of intellectually able females; therefore, our findings may not generalise to the wider autistic population. Conclusions Together, our findings suggest that many intellectually able adults, with and without a clinical diagnosis of autism, report using compensatory strategies to modify their social behaviour. We discuss the clinical utility of measuring self-reported compensation (e.g., using our checklist), with important implications for the accurate diagnosis and management of autism and related conditions.

When asked to evaluate their probability of experiencing a negative life event, healthy individuals update their beliefs more following good news than bad. This is referred to as optimistic belief updating. By contrast, individuals with depression update their beliefs by a similar amount, showing reduced optimism. We conducted the first independent replication of this effect and extended this work to examine whether reduced optimistic belief updating in depression also occurs for positive life events. Replicating previous research, healthy and depression groups differed in belief updating for negative events (β = 0.71, 95% CI: 0.24, 1.18). Whereas healthy participants updated their beliefs more following good news than bad, individuals experiencing depression lacked this bias. However, our findings for positive events were inconclusive. While we did not find statistical evidence that patterns of belief updating between groups varied by valence (β = −0.51, 95% CI: −1.16, 0.15), mean update scores suggested that both groups showed largely similar updating for positive life events. Our results add confidence to previous findings that depression is characterized by negative future expectations maintained by reduced updating in response to good news. However, further research is required to understand the specificity of this to negative events, and into refining methods for quantifying belief updating in clinical and non-clinical research.

Developmental prosopagnosia (DP) is a neurodevelopmental condition characterized by face recognition problems. Psychometrically sound self-report measures of face recognition problems are important tools in classification of DP. A widely used measure of such problems is the 20-item prosopagnosia index (PI20). Here, we present a Danish translation of the PI20 (PI20DK). We administered the PI20DK alongside three objective measures of face and object processing performance to 119 participants to validate the PI20DK. Further, we assess the underlying factor structure of the PI20DK. Finally, as the first study in the field, we investigate the association between self-reported face recognition ability and face perception performance. The project was preregistered prior to data collection. The results suggest excellent convergent validity, discriminant validity and internal consistency for the PI20DK. A confirmatory factor analysis, however, indicates a suboptimal fit of the PI20DK to a one factor solution. An investigation of the association between the PI20DK and face perception suggests that the poor fit may reflect that the PI20DK measures problems with face recognition in general and not specifically face memory problems.

The 10-item Autism-Spectrum Quotient (AQ10) is a measure of autistic traits used in research and clinical practice. Recently, the AQ10 has garnered critical attention, with research questioning its psychometric properties and clinical cutoff value. To help inform the utility of the measure, we conducted the first network analysis of the AQ10, with a view to gain a better understanding of its individual items. Using a large dataset of 6,595 participants who had completed the AQ10, we found strongest inter-subscale connections between communication, imagination, and socially relevant items. The nodes with greatest centrality concerned theory of mind differences. Together, these findings align with cognitive explanations of autism and provide clues about which AQ10 items show greatest utility for informing autism-related clinical practice.

Abstract Background Predicting the clinical course of prostate cancer is challenging due to the wide biological spectrum of the disease. The objective of our study was to identify prostate cancer prognostic markers in patients ‘sera using a multi-omics discovery platform. Methods Pre-surgical serum samples collected from a longitudinal, racially diverse, prostate cancer patient cohort (N = 382) were examined. Linear Regression and Bayesian computational approaches integrated with multi-omics, were used to select markers to predict biochemical recurrence (BCR). BCR-free survival was modeled using unadjusted Kaplan–Meier estimation curves and multivariable Cox proportional hazards analysis, adjusted for key pathologic variables. Receiver operating characteristic (ROC) curve statistics were used to examine the predictive value of markers in discriminating BCR events from non-events. The findings were further validated by creating a training set (N = 267) and testing set (N = 115) from the cohort. Results Among 382 patients, 72 (19%) experienced a BCR event in a median follow-up time of 6.9 years. Two proteins—Tenascin C (TNC) and Apolipoprotein A1V (Apo-AIV), one metabolite—1-Methyladenosine (1-MA) and one phospholipid molecular species phosphatidic acid (PA) 18:0-22:0 showed a cumulative predictive performance of AUC = 0.78 [OR (95% CI) = 6.56 (2.98–14.40), P 80%) for BCR. The combination of pTstage and Gleason score with the analytes, further increased the sensitivity [AUC = 0.89, 95% (CI) = 4.45–32.05, P

The ten-item short form of the Autism-Spectrum Quotient (AQ-10) has been used to efficiently assess autistic traits in the general population; however, the psychometric properties of the AQ-10 in terms of its internal reliability and its unifactorial structure have recently been questioned. In the present study (N = 797), whether the internal reliability is increased when the AQ-10 is applied with six rather than the conventional four response categories has been investigated. Moreover, correlational and confirmatory factor analyses were conducted to examine the reason for potential inhomogeneity within the AQ-10. The results suggest that the internal reliability of the AQ-10 was slightly increased but is still unsatisfactory, likely due to the incompatibility of items from two subdimensions: attention to detail and imagination. With six of the AQ-10 items, crucial aspects of the autistic personality may be measured, but other important aspects would be neglected; thus, the measure requires further psychometric development.

Summary: Many gene products exhibit great structural heterogeneity because of an array of modifications. These modifications are not directly encoded in the genomic template but often affect the functionality of proteins. Protein glycosylation plays a vital role in proper protein functions. However, the analysis of glycoproteins has been challenging compared with other protein modifications, such as phosphorylation. Here, we perform an integrated proteomic and glycoproteomic analysis of 83 prospectively collected high-grade serous ovarian carcinoma (HGSC) and 23 non-tumor tissues. Integration of the expression data from global proteomics and glycoproteomics reveals tumor-specific glycosylation, uncovers different glycosylation associated with three tumor clusters, and identifies glycosylation enzymes that were correlated with the altered glycosylation. In addition to providing a valuable resource, these results provide insights into the potential roles of glycosylation in the pathogenesis of HGSC, with the possibility of distinguishing pathological outcomes of ovarian tumors from non-tumors, as well as classifying tumor clusters.

Although XPO5 has been characterized to have tumor-suppressor features in the miRNA biogenesis pathway, the impact of altered expression of XPO5 in cancers is unexplored. Here we report a novel “oncogenic” role of XPO5 in advanced prostate cancer. Using prostate cancer models, we found that excess levels of XPO5 override the inhibitory effect of the canoncial miRNA-mRNA regulation, resulting in a global increase in proteins expression. Importantly, we found that decreased expression of XPO5 could promote an increase in proteasome degradation, whereas overexpression of XPO5 leads to altered protein posttranslational modification via hyperglycosylation, resulting in cellular protein stability. We evaluated the therapeutic advantage of targeting XPO5 in prostate cancer and found that knocking down XPO5 in prostate cancer cells suppressed cellular proliferation and tumor development without significantly impacting normal fibroblast cells survival. To our knowledge, this is the first report describing the oncogenic role of XPO5 in overriding the miRNAs regulation control. Furthermore, we believe that these findings will provide an explanation as to why, in some cancers that express higher abundance of mature miRNAs, fail to suppress their potential protein targets.

Abstract Background Epithelial ovarian carcinomas encompass a heterogeneous group of diseases with a poor 5-year survival rate. Serous carcinoma is the most common type. Most FDA-approved serum tumor markers are glycoproteins. These glycoproteins on cell surface or shed into the bloodstream could serve as therapeutic targets as well as surrogates of tumor. In addition to glycoprotein expressions, the analysis of protein glycosylation occupancy could be important for the understanding of cancer biology as well as the identification of potential glycoprotein changes in cancer. In this study, we used an integrated proteomics and glycoproteomics approach to analyze global glycoprotein abundance and glycosylation occupancy for proteins from high-grade ovarian serous carcinoma (HGSC) and serous cystadenoma, a benign epithelial ovarian tumor, by using LC–MS/MS-based technique. Methods Fresh-frozen ovarian HGSC tissues and benign serous cystadenoma cases were quantitatively analyzed using isobaric tags for relative and absolute quantitation for both global and glycoproteomic analyses by two dimensional fractionation followed by LC–MS/MS analysis using a Orbitrap Velos mass spectrometer. Results Proteins and N-linked glycosite-containing peptides were identified and quantified using the integrated global proteomic and glycoproteomic approach. Among the identified N-linked glycosite-containing peptides, the relative abundances of glycosite-containing peptide and the glycoprotein levels were compared using glycoproteomic and proteomic data. The glycosite-containing peptides with unique changes in glycosylation occupancies rather than the protein expression levels were identified. Conclusion In this study, we presented an integrated proteomics and glycoproteomics approach to identify changes of glycoproteins in protein expression and glycosylation occupancy in HGSC and serous cystadenoma and determined the changes of glycosylation occupancy that are associated with malignant and benign tumor tissues. Specific changes in glycoprotein expression or glycosylation occupancy have the potential to be used in the discrimination between benign and malignant epithelial ovarian tumors and to improve our understanding of ovarian cancer biology.

Understanding individual differences in attitudes to autism is crucial for improving attitudes and reducing stigma towards autistic people, yet there is limited and inconsistent research on this topic. This is compounded by a lack of appropriate measures and multivariate analyses. Addressing these issues, using up-to-date measures and multiple linear regression, we examined the relative contributions of participant age, sex, autism knowledge, level of contact with autistic people, and autistic traits to attitudes towards autistic people. We found that greater autism knowledge and higher levels of contact, but no other variables, were uniquely predictive of attitudes towards autistic people. We conclude that, in addition to public awareness campaigns to raise knowledge of autism, it may be important to increase contact between autistic and non-autistic people to improve public attitudes towards autistic people.

There is growing interest in quantifying attitudes towards autistic people, however there is relatively little research on psychometric properties of the only existing measure and its ability to predict engagement with people with autism. To begin addressing these issues, we compared three scales measuring attitudes towards autistic people following the development of two new measures. Exploratory factor analysis, across two datasets, revealed that the factor-structure of an established 16-item scale is unclear. Further, its predictive validity of intended engagement with autistic people was comparable to our novel and psychometrically robust 1- and 4-item measures of attitudes towards autistic people. We therefore conclude that a 1- or 4-item scale is sufficient to measure general attitudes towards autistic people in future research. Equally, we propose that additional research is required to develop measures that are grounded in theoretical models of attitude formation and therefore distinguish between different components of attitudes.

The 10-item Autism-Spectrum Quotient (AQ10) is a self-report questionnaire used in clinical and research settings as a diagnostic screening tool for autism in adults. The AQ10 is also increasingly being used to quantify trait autism along a unitary dimension and correlated against performance on other psychological/medical tasks. However, its psychometric properties have yet to be examined when used in this way. By analysing AQ10 data from a large non-clinical sample of adults (n = 6,595), we found that the AQ10 does not have a unifactorial factor structure, and instead appears to have several factors. The AQ10 also had poor internal reliability. Taken together, whilst the AQ10 has important clinical utility in screening for diagnosable autism, it may not be a psychometrically robust measure when administered in non-clinical samples from the general population. Therefore, we caution against its use as a measure of trait autism in future research.

The emergence of COVID-19 progressed into a global pandemic that has functionally put the world at a standstill and catapulted major healthcare systems into an overburdened state. The dire need for therapeutic strategies to mitigate and successfully treat COVID-19 is now a public health crisis with national security implications for many countries. The current study employed Bayesian networks to a longitudinal proteomic dataset generated from Caco-2 cells transfected with SARS-CoV-2 (isolated from patients returning from Wuhan to Frankfurt). Two different approaches were employed to assess the Bayesian models, a titer-center topology analysis and a drug signature enrichment analysis. Topology analysis identified a set of proteins directly linked to the SAR-CoV2 titer, including ACE2, a SARS-CoV-2 binding receptor, MAOB and CHECK1. Aligning with the topology analysis, MAOB and CHECK1 were also identified within the enriched drug-signatures. Taken together, the data output from this network has identified nodal host proteins that may be connected to 18 chemical compounds, some already marketed, which provides an immediate opportunity to rapidly triage these assets for safety and efficacy against COVID-19.

It was recently reported that learning one is autistic earlier in life is associated with greater quality of life and well-being in university students. In a pre-registered extension of this work, we addressed several limitations of this study by: (1) recruiting a larger sample of more diverse ages and education levels; (2) distinguishing between learning about and receiving an autism diagnosis; (3) accounting for additional confounding variables; and (4) studying different quality of life dimensions. Autistic adults (N = 300) reported when they first learned they were autistic, as well as when they actually received an autism diagnosis, and provided detailed socio-demographic information. Participants also completed measures of their autistic traits, as well as well-being and quality of life across multiple domains. In contrast to recent research, we found the age participants first learned they were autistic did not significantly and uniquely predict their quality of life and well-being. Rather, having more autistic traits was the strongest predictor of poorer quality of life and well-being, while other socio-demographic factors were also relevant. We discuss the implications of these findings for understanding and improving outcomes in autistic adults and call for higher quality open science on this important topic.

The 20 item prosopagnosia index (PI20) was recently developed to identify individuals with developmental prosopagnosia. While the PI20’s principal purpose is to aid researchers and clinicians, it was suggested that it may serve as a useful screening tool to identify people with face recognition difficulties in applied settings where face matching is a critical part of their occupation. Although the PI20 has been validated using behavioural measures of face recognition, it has yet to be validated against a measure of face-matching ability that is more representative of applied settings. In this study, the PI20 was therefore administered with the Glasgow face-matching test (GFMT). A strong correlation was observed between PI20 and GFMT scores, providing further validation for the PI20, indicating that it is likely to be of value in applied settings.

Self-report plays a key role in the identification of developmental prosopagnosia (DP), providing complementary evidence to computer-based tests of face recognition ability, aiding interpretation of scores. However, the lack of standardized self-report instruments has contributed to heterogeneous reporting standards for self-report evidence in DP research. The lack of standardization prevents comparison across samples and limits investigation of the relationship between objective tests of face processing and self-report measures. To address these issues, this paper introduces the PI20; a 20-item self-report measure for quantifying prosopagnosic traits. The new instrument successfully distinguishes suspected prosopagnosics from typically developed adults. Strong correlations were also observed between PI20 scores and performance on objective tests of familiar and unfamiliar face recognition ability, confirming that people have the necessary insight into their own face recognition ability required by a self-report instrument. Importantly, PI20 scores did not correlate with recognition of non-face objects, indicating that the instrument measures face recognition, and not a general perceptual impairment. These results suggest that the PI20 can play a valuable role in identifying DP. A freely available self-report instrument will permit more effective description of self-report diagnostic evidence, thereby facilitating greater comparison of prosopagnosic samples, and more reliable classification.

Objectives. To compare the ability of endodontists to determine the size of apical pathological lesions and select the most appropriate choice of treatment based on lesions’ projected image characteristics using 2 D and 3 D images. Study Design. Twenty-four subjects were selected. Radiographic examination of symptomatic study teeth with an intraoral periapical radiograph revealed periapical lesions equal to or greater than 3 mm in the greatest diameter. Cone-beam Computed tomography (CBCT) images were made of the involved teeth after the intraoral periapical radiograph confirmed the size of lesion to be equal to greater than 3 mm. Six observers (endodontists) viewed both the periapical and CBCT images. Upon viewing each of the images from the two imaging modalities, observers (1) measured lesion size and (2) made decisions on treatment based on each radiograph. Chi-square test was used to look for differences in the choice of treatment among observers. Results. No significant difference was noted in the treatment plan selected by observers using the two modalities (χ2(3)=.036, P>0.05). Conclusion. Lesion size and choice of treatment of periapical lesions based on CBCT radiographs do not change significantly from those made on the basis of 2 D radiographs.