Collective Intelligence Increases Diagnostic Accuracy in a General Practice Setting.

BACKGROUND: General practitioners (GPs) work in an ill-defined environment where diagnostic errors are prevalent. Previous research indicates that aggregating independent diagnoses can improve diagnostic accuracy in a range of settings. We examined whether aggregating independent diagnoses can also improve diagnostic accuracy for GP decision making. In addition, we investigated the potential benefit of such an approach in combination with a decision support system (DSS). METHODS: We simulated virtual groups using data sets from 2 previously published studies. In study 1, 260 GPs independently diagnosed 9 patient cases in a vignette-based study. In study 2, 30 GPs independently diagnosed 12 patient actors in a patient-facing study. In both data sets, GPs provided diagnoses in a control condition and/or DSS condition(s). Each GP's diagnosis, confidence rating, and years of experience were entered into a computer simulation. Virtual groups of varying sizes (range: 3-9) were created, and different collective intelligence rules (plurality, confidence, and seniority) were applied to determine each group's final diagnosis. Diagnostic accuracy was used as the performance measure. RESULTS: Aggregating independent diagnoses by weighing them equally (i.e., the plurality rule) substantially outperformed average individual accuracy, and this effect increased with increasing group size. Selecting diagnoses based on confidence only led to marginal improvements, while selecting based on seniority reduced accuracy. Combining the plurality rule with a DSS further boosted performance. DISCUSSION: Combining independent diagnoses may substantially improve a GP's diagnostic accuracy and subsequent patient outcomes. This approach did, however, not improve accuracy in all patient cases. Therefore, future work should focus on uncovering the conditions under which collective intelligence is most beneficial in general practice. HIGHLIGHTS: We examined whether aggregating independent diagnoses of GPs can improve diagnostic accuracy.Using data sets of 2 previously published studies, we composed virtual groups of GPs and combined their independent diagnoses using 3 collective intelligence rules (plurality, confidence, and seniority).Aggregating independent diagnoses by weighing them equally substantially outperformed average individual GP accuracy, and this effect increased with increasing group size.Combining independent diagnoses may substantially improve GP's diagnostic accuracy and subsequent patient outcomes.

The Updated Mouse Universal Genotyping Array Bioinformatic Pipeline Improves Genetic QC in Laboratory Mice.

The MiniMUGA genotyping array is a popular tool for genetic QC of laboratory mice and genotyping of samples from most types of experimental crosses involving laboratory strains, particularly for reduced complexity crosses. The content of the production version of the MiniMUGA array is fixed; however, there is the opportunity to improve array's performance and the associated report's usefulness by leveraging thousands of samples genotyped since the initial description of MiniMUGA in 2020. Here we report our efforts to update and improve marker annotation, increase the number and the reliability of the consensus genotypes for inbred strains and increase the number of constructs that can reliably be detected with MiniMUGA. In addition, we have implemented key changes in the informatics pipeline to identify and quantify the contribution of specific genetic backgrounds to the makeup of a given sample, remove arbitrary thresholds, include the Y Chromosome and mitochondrial genome in the ideogram, and improve robust detection of the presence of commercially available substrains based on diagnostic alleles. Finally, we have made changes to the layout of the report, to simplify the interpretation and completeness of the analysis and added a table summarizing the ideogram. We believe that these changes will be of general interest to the mouse research community and will be instrumental in our goal of improving the rigor and reproducibility of mouse-based biomedical research.

Host Genetic Variation Impacts SARS-CoV-2 Vaccination Response in the Diversity Outbred Mouse Population.

The COVID-19 pandemic led to the rapid and worldwide development of highly effective vaccines against SARS-CoV-2. However, there is significant individual-to-individual variation in vaccine efficacy due to factors including viral variants, host age, immune status, environmental and host genetic factors. Understanding those determinants driving this variation may inform the development of more broadly protective vaccine strategies. While host genetic factors are known to impact vaccine efficacy for respiratory pathogens such as influenza and tuberculosis, the impact of host genetic variation on vaccine efficacy against COVID-19 is not well understood. To model the impact of host genetic variation on SARS-CoV-2 vaccine efficacy, while controlling for the impact of non-genetic factors, we used the Diversity Outbred (DO) mouse model. We found that DO mice immunized against SARS-CoV-2 exhibited high levels of variation in vaccine-induced neutralizing antibody responses. While the majority of the vaccinated mice were protected from virus-induced disease, similar to human populations, we observed vaccine breakthrough in a subset of mice. Importantly, we found that this variation in neutralizing antibody, virus-induced disease, and viral titer is heritable, indicating that the DO serves as a useful model system for studying the contribution of genetic variation of both vaccines and disease outcomes.

The Psychology of COVID-19 Booster Hesitancy, Acceptance and Resistance in Australia.

COVID-19 booster vaccinations have been recommended as a primary line of defence against serious illness and hospitalisation. This study identifies and characterises distinct profiles of attitudes towards vaccination, particularly the willingness to get a booster dose. A sample of 582 adults from Australia completed an online survey capturing COVID-related behaviours, beliefs and attitudes and a range of sociodemographic, psychological, political, social and cultural variables. Latent Profile Analysis (LPA) identified three subgroups: Acceptant (61%), Hesitant (30%) and Resistant (9%). Compared to the Acceptant group, the Hesitant and Resistant groups were less worried about catching COVID-19, used fewer official COVID-19 information sources, checked the news less, were lower on the agreeableness personality dimension and reported more conservatism, persecutory thinking, amoral attitudes and need for chaos. The Hesitant group also reported checking the legitimacy of information sources less, scored lower on the openness to new experiences personality dimension and were more likely than the Resistant and Acceptant groups to report regaining freedoms (e.g., travel) and work requirements or external pressures as reasons to get a booster. The Resistant group were higher on reactance, held more conspiratorial beliefs and rated their culture as being less tolerant of deviance than the Hesitant and Acceptant groups. This research can inform tailored approaches to increasing booster uptake and optimal strategies for public health messaging.

Are two naïve and distributed heads better than one? Factors influencing the performance of teams in a challenging real-time task.

Introduction: Collective decisions in dynamic tasks can be influenced by multiple factors, including the operational conditions, quality and quantity of communication, and individual differences. These factors may influence whether two heads perform better than one. This study examined the "two heads are better than one" effect (2HBT1) in distributed two-person driver-navigator teams with asymmetrical roles performing a challenging simulated driving task. We also examined the influence of communication quality and quantity on team performance under different operational conditions. In addition to traditional measures of communication volume (duration and speaking turns), patterns of communication quality (optimality of timing and accuracy of instructions) were captured. Methods: Participants completed a simulated driving task under two operational conditions (normal and fog) either as individual drivers (N = 134; 87 females, mean age = 19.80, SD = 3.35) or two-person teams (driver and navigator; N = 80; 109 females, mean age = 19.70, SD = 4.69). The normal condition was characterized by high visibility for both driver and navigator. The fog condition was characterized by reduced visibility for the driver but not for the navigator. Participants were also measured on a range of cognitive and personality constructs. Results: Teams had fewer collisions than individuals during normal conditions but not during fog conditions when teams had an informational advantage over individuals. Furthermore, teams drove slower than individuals during fog conditions but not during normal conditions. Communication that was poorly timed and/or inaccurate was a positive predictor of accuracy (i.e., collisions) during the normal condition and communication that was well timed and accurate was a negative predictor of speed during the fog condition. Our novel measure of communication quality (i.e., content of communication) was a stronger predictor of accuracy, but volume of communication was a stronger predictor of time (i.e., speed). Discussion: Results indicate when team performance thrives and succumbs compared with individual performance and informs theory about the 2HBT1 effect and team communication.

To comply or not comply? A latent profile analysis of behaviours and attitudes during the COVID-19 pandemic.

How and why do people comply with protective behaviours during COVID-19? The emerging literature employs a variable-centered approach, typically using a narrow selection of constructs within a study. This study is the first to adopt a person-centred approach to identify complex patterns of compliance, and holistically examine underlying psychological differences, integrating multiple psychology paradigms and epidemiology. 1575 participants from Australia, US, UK, and Canada indicated their behaviours, attitudes, personality, cognitive/decision-making ability, resilience, adaptability, coping, political and cultural factors, and information consumption during the pandemic's first wave. Using Latent Profile Analysis, two broad groups were identified. The compliant group (90%) reported greater worries, and perceived protective measures as effective, whilst the non-compliant group (about 10%) perceived them as problematic. The non-compliant group were lower on agreeableness and cultural tightness-looseness, but more extraverted, and reactant. They utilised more maladaptive coping strategies, checked/trusted the news less, and used official sources less. Females showed greater compliance than males. By promoting greater appreciation of the complexity of behaviour during COVID-19, this research provides a critical platform to inform future studies, public health policy, and targeted behaviour change interventions during pandemics. The results also challenge age-related stereotypes and assumptions.

Applying Evidence-Centered Design to Measure Psychological Resilience: The Development and Preliminary Validation of a Novel Simulation-Based Assessment Methodology.

Modern technologies have enabled the development of dynamic game- and simulation-based assessments to measure psychological constructs. This has highlighted their potential for supplementing other assessment modalities, such as self-report. This study describes the development, design, and preliminary validation of a simulation-based assessment methodology to measure psychological resilience-an important construct for multiple life domains. The design was guided by theories of resilience, and principles of evidence-centered design and stealth assessment. The system analyzed log files from a simulated task to derive individual trajectories in response to stressors. Using slope analyses, these trajectories were indicative of four types of responses to stressors: thriving, recovery, surviving, and succumbing. Using Machine Learning, the trajectories were predictive of self-reported resilience (Connor-Davidson Resilience Scale) with high accuracy, supporting construct validity of the simulation-based assessment. These findings add to the growing evidence supporting the utility of gamified assessment of psychological constructs. Importantly, these findings address theoretical debates about the construct of resilience, adding to its theory, supporting the combination of the "trait" and "process" approaches to its operationalization.

Content and Performance of the MiniMUGA Genotyping Array: A New Tool To Improve Rigor and Reproducibility in Mouse Research.

The laboratory mouse is the most widely used animal model for biomedical research, due in part to its well-annotated genome, wealth of genetic resources, and the ability to precisely manipulate its genome. Despite the importance of genetics for mouse research, genetic quality control (QC) is not standardized, in part due to the lack of cost-effective, informative, and robust platforms. Genotyping arrays are standard tools for mouse research and remain an attractive alternative even in the era of high-throughput whole-genome sequencing. Here, we describe the content and performance of a new iteration of the Mouse Universal Genotyping Array (MUGA), MiniMUGA, an array-based genetic QC platform with over 11,000 probes. In addition to robust discrimination between most classical and wild-derived laboratory strains, MiniMUGA was designed to contain features not available in other platforms: (1) chromosomal sex determination, (2) discrimination between substrains from multiple commercial vendors, (3) diagnostic SNPs for popular laboratory strains, (4) detection of constructs used in genetically engineered mice, and (5) an easy-to-interpret report summarizing these results. In-depth annotation of all probes should facilitate custom analyses by individual researchers. To determine the performance of MiniMUGA, we genotyped 6899 samples from a wide variety of genetic backgrounds. The performance of MiniMUGA compares favorably with three previous iterations of the MUGA family of arrays, both in discrimination capabilities and robustness. We have generated publicly available consensus genotypes for 241 inbred strains including classical, wild-derived, and recombinant inbred lines. Here, we also report the detection of a substantial number of XO and XXY individuals across a variety of sample types, new markers that expand the utility of reduced complexity crosses to genetic backgrounds other than C57BL/6, and the robust detection of 17 genetic constructs. We provide preliminary evidence that the array can be used to identify both partial sex chromosome duplication and mosaicism, and that diagnostic SNPs can be used to determine how long inbred mice have been bred independently from the relevant main stock. We conclude that MiniMUGA is a valuable platform for genetic QC, and an important new tool to increase the rigor and reproducibility of mouse research.

Whole Genome Sequencing and Progress Toward Full Inbreeding of the Mouse Collaborative Cross Population.

Two key features of recombinant inbred panels are well-characterized genomes and reproducibility. Here we report on the sequenced genomes of six additional Collaborative Cross (CC) strains and on inbreeding progress of 72 CC strains. We have previously reported on the sequences of 69 CC strains that were publicly available, bringing the total of CC strains with whole genome sequence up to 75. The sequencing of these six CC strains updates the efforts toward inbreeding undertaken by the UNC Systems Genetics Core. The timing reflects our competing mandates to release to the public as many CC strains as possible while achieving an acceptable level of inbreeding. The new six strains have a higher than average founder contribution from non-domesticus strains than the previously released CC strains. Five of the six strains also have high residual heterozygosity (>14%), which may be related to non-domesticus founder contributions. Finally, we report on updated estimates on residual heterozygosity across the entire CC population using a novel, simple and cost effective genotyping platform on three mice from each strain. We observe a reduction in residual heterozygosity across all previously released CC strains. We discuss the optimal use of different genetic resources available for the CC population.

Temperature during the day, but not during the night, controls flowering of Phalaenopsis orchids.

Phalaenopsis orchids are among the most valuable potted flowering crops commercially produced throughout the world because of their long flower life and ease of crop scheduling to meet specific market dates. During commercial production, Phalaenopsis are usually grown at an air temperature > or =28 degrees C to inhibit flower initiation, and a cooler night than day temperature regimen (e.g. 25/20 degrees C day/night) is used to induce flowering. However, the specific effect of day and night temperature on flower initiation has not been well described, and the reported requirement for a diurnal temperature fluctuation to elicit flowering is unclear. Two Phalaenopsis clones were grown in glass greenhouse compartments with constant temperature set points of 14, 17, 20, 23, 26, or 29 degrees C and fluctuating day/night (12 h/12 h) temperatures of 20/14, 23/17, 26/14, 26/20, 29/17, or 29/23 degrees C. The photoperiod was 12 h, and the maximum irradiance was controlled to < or =150 micromol m(-2) s(-1). After 20 weeks, > or =80% of plants of both clones had a visible inflorescence when grown at constant 14, 17, 20, or 23 degrees C and at fluctuating day/night temperatures of 20/14 degrees C or 23/17 degrees C. None of the plants were reproductive within 20 weeks when grown at a constant 29 degrees C or at 29/17 degrees C or 29/23 degrees C day/night temperature regimens. The number of inflorescences per plant and the number of flower buds on the first inflorescence were greatest when the average daily temperature was 14 degrees C or 17 degrees C. These results indicate that a day/night fluctuation in temperature is not required for inflorescence initiation in these two Phalaenopsis clones. Furthermore, the inhibition of flowering when the day temperature was 29 degrees C and the night temperature was 17 degrees C or 23 degrees C suggests that a warm day temperature inhibits flower initiation in Phalaenopsis.

Role of CYP1A2 and CYP2E1 in the pentoxifylline ciprofloxacin drug interaction.

In this study the drug interaction between ciprofloxacin (CIPRO) and pentoxifylline (PTX) was investigated and the role of CYP1A2 in the drug interaction was determined with the aid of a selective CYP1A2 inhibitor, furafylline (FURA), and the Cyp1A2 knockout mouse. Serum concentrations of PTX (83.4+/-1 micromol/l) and metabolite-1 (M-1) (13.7+/-2.8 micromol/l) following a single injection of PTX (100 mg/kg i.p.) were significantly higher (P<0.05) in mice treated with CIPRO (25 mg/kg i.p. 9 days) compared to serum concentrations of PTX (46.3+/-0.5 micromol/l) and M-1 (6.4+/-1.1 micromol/l) in mice administered saline. Murine hepatic microsomes were incubated with PTX alone or the combination of PTX and CIPRO. The metabolism of PTX in the murine hepatic microsomes containing both CIPRO and PTX was significantly decreased compared to microsomes incubated with PTX alone, suggesting that CIPRO may inhibit the metabolism of PTX. To further clarify the role of CYP1A2 in the metabolism of PTX in mice, the effect of a selective CYP1A2 mechanism based inhibitor, FURA, on the metabolism of PTX was investigated and our results indicate that FURA inhibited metabolism of PTX. We then investigated PTX elimination in the Cyp1A2 knockout mouse. Blood levels of PTX were assessed at 2 and 20 min following a single injection of PTX (32 mg/kg i.v). Serum concentration of PTX was determined in Cyp1A2 knockout mice compared to Cyp1A2 wild type control mice. The serum concentration of PTX in Cyp1A2 wild type mice (n=9) was 22.2+/-3.2 micromol/l at 20 min following injection of PTX. The serum concentration of PTX in Cyp1A2 knockout mice (n=11) was significantly elevated at 20 min following injection of PTX compared to Cyp1A2 wild type mice. These results clearly indicate that inhibition of CYP1A2 catalytic activity that occurs in the Cyp1A2 knockout mice is sufficient to alter metabolism of PTX and result in markedly elevated levels in serum of Cyp1A2 knockout mice. The results of Western analysis in murine microsomes suggest that CYP1A2 protein levels were not altered by CIPRO indicating that CIPRO did not downregulate Cyp1A2. The results of Western analysis also indicated that CIPRO treatment increased CYP2E1 in mouse microsomes and the implications of these will be discussed.