Recent global events demonstrate that analytical frameworks to aid professionals in healthcare ethics must consider the pervasive role of social structures in the emergence of bioethical issues. To address this, the authors propose a new sociologically informed approach to healthcare ethics that they term “social bioethics.” Their approach is animated by the interpretive social sciences to highlight how social structures operate vis-à-vis the everyday practices and moral reasoning of individuals, a phenomenon known as social discourse. As an exemplar, the authors use social bioethics to reframe common ethical issues in psychiatric services and discuss potential implications. Lastly, the authors discuss how social bioethics illuminates the ways healthcare ethics consultants in both policy and clinical decision-making participate in and shape broader social, political, and economic systems, which then cyclically informs the design and delivery of healthcare.

Aspect-based sentiment analysis (ABSA) provides an opportunity to systematically generate user's opinions of specific aspects to enrich the idea creation process in the early stage of product/service design process. Yet, the current ABSA task has two major limitations. First, existing research mostly focusing on the subsets of ABSA task, e.g. aspect-sentiment extraction, extract aspect, opinion, and sentiment in a unified model is still an open problem. Second, the implicit opinion and sentiment are ignored in the current ABSA task. This article tackles these gaps by (1) creating a new annotated dataset comprised of five types of labels, including aspect, category, opinion, sentiment, and implicit indicator (ACOSI) and (2) developing a unified model which could extract all five types of labels simultaneously in a generative manner. Numerical experiments conducted on the manually labeled dataset originally scraped from three major e-Commerce retail stores for apparel and footwear products indicate the performance, scalability, and potentials of the framework developed. Several directions are provided for future exploration in the area of automated aspect-based sentiment analysis for user-centered design.

OBJECTIVES/GOALS: The characterization of the zebrafish as an animal model for Cockayne Syndrome may guide us towards role of Transcription-Coupled Nucleotide Excision Repair (TC-NER) defects in sensorineural hearing loss. METHODS/STUDY POPULATION: To examine our model, we have developed a zebrafish line with a 9+1 base-pair deletion in the ercc6 gene using TALENs. Mutation has since been confirmed by PCR and subsequent restriction digest with StuI. A series of assays evaluating hair cell morphology, structure and function, as well as ribbon synapse structure, will be used to analyze potential differences between the ercc6 mutant zebrafish line a their wild-type siblings. Additionally, electron microscopy will be used to assess differences in hair cell ultrastructure between the ercc6 mutant zebrafish line a their wild-type siblings. Finally, UVC exposure assays will be used to determine the role TC-NER plays in our novel zebrafish model, and evaluate its potential implications in sensorineural hearing loss. RESULTS/ANTICIPATED RESULTS: We anticipate that biallelic loss of function mutations in the zebrafish ercc6 gene will result in abnormalities in hair cell structure, mechanotransduction, or cell number. Additionally, we anticipate that hair cell ultrastructure and ribbon synapse structure will be impacted by loss of ercc6 expression. DISCUSSION/SIGNIFICANCE: Hearing loss mechanisms associated with defects in TC-NER are yet to be described. We believe our model will provide the tools for a faster and efficient way to carry out Cockayne Syndrome studies while laying the groundwork for the association between TC-NER and hearing loss.

Religious belief is a topic of longstanding interest to psychological science, but the psychology of religious disbelief is a relative newcomer. One prominently discussed model is analytic atheism, wherein cognitive reflection, as measured with the Cognitive Reflection Test, overrides religious intuitions and instruction. Consistent with this model, performance-based measures of cognitive reflection predict religious disbelief in WEIRD (Western, Educated, Industrialized, Rich, & Democratic) samples. However, the generality of analytic atheism remains unknown. Drawing on a large global sample (N = 3461) from 13 religiously, demographically, and culturally diverse societies, we find that analytic atheism as usually assessed is in fact quite fickle cross-culturally, appearing robustly only in aggregate analyses and in three individual countries. The results provide additional evidence for culture’s effects on core beliefs.

The authors present the results of a drone-based airborne LiDAR survey of the fifth century AD Tsukuriyama mounded tomb group in Okayama Prefecture, Japan, revealing the relationship between tomb building and the surrounding landscape during Japan's period of ancient state formation.

Although exposure therapy (ET) is an effective treatment for anxiety disorders and obsessive-compulsive disorder, many clinicians report not utilizing it. The present study targeted common utilization barriers by evaluating an intensive ET training experience in a relatively inexperienced sample of pre-professionals. Thirty-two individuals at the undergraduate or college graduate level without formal clinical experience participated as camp counsellors in a 5day exposure-based therapeutic summer camp for youth with anxiety disorders and/or obsessive-compulsive disorder. Participants were trained in ET through a progressive cascading model and answered questionnaires before and after camp. Repeated measure MANOVA revealed significantly increased feelings of self-efficacy conducting exposures, and significantly decreased feelings of disgust sensitivity and contamination-related disgust from pre-camp to post-camp. A subset of individuals providing data 1 month after the camp maintained a significant gain in ET self-efficacy. Regression analyses revealed that contamination-related disgust, but not disgust sensitivity, significantly predicted post-camp ET self-efficacy. These findings suggest that individuals early into their post-secondary education can learn ET, and the progressive cascading model holds promise in its utility across experience levels and warrants further investigation. Disgust may also play a role in feelings of competency conducting ET. Implications on dissemination and implementation efforts are also discussed.

ABSTRACT IMPACT: Despite its importance in systemic diseases such as diabetes, the eye is notably difficult to examine for non-specialists; this study introduces a fully automated approach for eye disease screening, coupling a deep learning algorithm with a robotically-aligned optical coherence tomography system to improve eye care in non-ophthalmology settings. OBJECTIVES/GOALS: This study aims to develop and test a deep learning (DL) method to classify images acquired from a robotically-aligned optical coherence tomography (OCT) system as normal vs. abnormal. The long-term goal of our study is to integrate artificial intelligence and robotic eye imaging to fully automate eye disease screening in diverse clinical settings. METHODS/STUDY POPULATION: Between August and October 2020, patients seen at the Duke Eye Center and healthy volunteers (age ≥18) were imaged with a custom, robotically-aligned OCT (RAOCT) system following routine eye exam. Using transfer learning, we adapted a preexisting convolutional neural network to train a DL algorithm to classify OCT images as normal vs. abnormal. The model was trained and validated on two publicly available OCT datasets and two of our own RAOCT volumes. For external testing, the top-performing model based on validation was applied to a representative averaged B-scan from each of the remaining RAOCT volumes. The model’s performance was evaluated against a reference standard of clinical diagnoses by retina specialists. Saliency maps were created to visualize the areas contributing most to the model predictions. RESULTS/ANTICIPATED RESULTS: The training and validation datasets included 87,697 OCT images, of which 59,743 were abnormal. The top-performing DL model had a training accuracy of 96% and a validation accuracy of 99%. For external testing, 43 eyes of 27 subjects were imaged with the robotically-aligned OCT system. Compared to clinical diagnoses, the model correctly labeled 18 out of 22 normal averaged B-scans and 18 out of 21 abnormal averaged B-scans. Overall, in the testing set, the model had an AUC for the detection of pathology of 0.92, an accuracy of 84%, a sensitivity of 86%, and a specificity of 82%. For the correctly predicted scans, saliency maps identified the areas contributing most to the DL algorithm’s predictions, which matched the regions of greatest clinical importance. DISCUSSION/SIGNIFICANCE OF FINDINGS: This is the first study to develop and apply a DL model to images acquired from a self-aligning OCT system, demonstrating the potential of integrating DL and robotic eye imaging to automate eye disease screening. We are working to translate this technology for use in emergency departments and primary care, where it will have the greatest impact.

This two-part article examines the global public health (GPH) information system deficits emerging in the coronavirus disease 2019 (COVID-19) pandemic. It surveys past, missed opportunities for public health (PH) information system and operational improvements, examines current megatrend changes to information management, and describes a new multi-disciplinary model for population-based management (PBM) supported by a GPH Database applicable to pandemics and GPH crises.

Pure and Nb-doped zirconium germanate materials of composition K2-xZr1-xNbxGe3O9.H2O where x = 0, 0.1, 0.2 and 0.25 with the structure of the mineral umbite have been successfully synthesised. The parent material displays negligible ion exchange of K+ for Cs+ but the doped materials shows much improved exchange. Synchrotron X-ray diffraction shows substantial peak splitting which varies with increasing niobium content. Preliminary Rietveld refinements suggest a two phase model with a caesium and potassium rich doped umbite phase.

Hyperbolic polariton modes are highly appealing for a broad range of applications in nanophotonics, including surfaced enhanced sensing, sub-diffractional imaging, and reconfigurable metasurfaces. Here we show that attenuated total reflectance (ATR) micro-spectroscopy using standard spectroscopic tools can launch hyperbolic polaritons in a Kretschmann–Raether configuration. We measure multiple hyperbolic and dielectric modes within the naturally hyperbolic material hexagonal boron nitride as a function of different isotopic enrichments and flake thickness. This overcomes the technical challenges of measurement approaches based on nanostructuring, or scattering scanning near-field optical microscopy. Ultimately, our ATR approach allows us to compare the optical properties of small-scale materials prepared by different techniques systematically.

Traditional ambulatory rhythm monitoring in children can have limitations, including cumbersome leads and limited monitoring duration. The ZioTM patch ambulatory monitor is a small, adhesive, single-channel rhythm monitor that can be worn up to 2 weeks. In this study, we present a retrospective cross-sectional analysis of the ZioTM monitor’s impact in clinical practice. Patients aged 0–18 years were included in the study. A total of 373 studies were reviewed in 332 patients. In all, 28.4% had structural heart disease, and 16.9% had a prior surgical, catheterisation, or electrophysiology procedure. The most common indication for monitoring was tachypalpitations (41%); 93.5% of these patients had their symptoms captured during the study window. The median duration of monitoring was 5 days. Overall, 5.1% of ZioTM monitoring identified arrhythmias requiring new intervention or increased medical management; 4.0% identified arrhythmias requiring increased clinical surveillance. The remainder had either normal-variant rhythm or minor rhythm findings requiring no change in management. For patients with tachypalpitations and no structural heart disease, 13.2% had pathological arrhythmias, but 72.9% had normal-variant rhythm during symptoms, allowing discharge from cardiology care. Notably, for patients with findings requiring intervention or increased surveillance, 56% had findings first identified beyond 24 hours, and only 62% were patient-triggered findings. Seven studies (1.9%) were associated with complications or patient intolerance. The ZioTM is a well-tolerated device that may improve what traditional Holter and event monitoring would detect in paediatric cardiology patients. This study shows a positive clinical impact on the management of patients within a paediatric cardiology practice.

We examine the role of status quo bias in the ballot wording of social issues that affect the rights of minority groups. We test the salience of this framing bias by conducting an experiment that randomly assigns different ballot wordings for five policies across survey respondents. We find that status quo bias changes the percent of individuals who vote for the ballot measure by 5–8 percentage points with the least informed individuals being the most affected by status quo bias.

Molecular assays are often implemented by weed scientists for detection of herbicide-resistant individuals; however, the utility of these assays can be limited if multiple mechanisms of evolved resistance exist. Waterhemp resistant to protoporphyrinogen oxidase (PPO)– inhibiting herbicides is conferred by a target-site mutation in PPX2L (a gene coding for PPO), resulting in the loss of a glycine at position 210 (ΔG210). This ΔG210 mutation of PPX2L is the only known mechanism responsible for PPO-inhibitor resistance (PPO-R) in waterhemp from five states (Illinois, Indiana, Iowa, Kansas, and Missouri); however, a limited number of populations have been tested, especially in Illinois. To verify the ubiquity of the ΔG210 in PPO-R waterhemp populations in Illinois, a previously published allele-specific PCR (asPCR) was used for the detection of the ΔG210 mutation to associate this mutation with phenotypic resistance in 94 Illinois waterhemp populations. The ΔG210 mutation was detected in all populations displaying phenotypic resistance to lactofen (220 g ai ha−1), indicating the deletion is likely the only mechanism of resistance. With evidence that the ΔG210 mutation dominates PPO-R waterhemp biotypes, molecular detection techniques have considerable utility. Unfortunately, the previously published asPCR is time consuming, very sensitive to PCR conditions, and requires additional steps to eliminate the possibility of false negatives. To overcome these limitations, a streamlined molecular method using the TaqMan® technique was developed, utilizing allele-specific, fluorescent probes for high-throughput, robust discrimination of each allele (resistant and susceptible) at the 210th amino acid position of PPX2L.

Pure and Nb-doped zirconium germanate materials of composition K2-xZr1-xNbxGe3O9.H2O where x = 0, 0.1, 0.2 and 0.3 with the structure of the natural mineral umbite have been prepared in high yield using hydrothermal synthesis methods. The parent material displays virtually no ion exchange of the K+ for Cs+ but the doped materials show rapidly enhanced exchange with replacement of ca. 70% of the K+ by Cs+ for the 30% doped material. Rietveld analysis of the powder X-ray diffraction data is consistent with no change in the unit cell parameters or K+ bonding prior to the exchange, hence we propose the improved property is due to the creation of cation defect sites within the pores of the material that facilities greater cation mobility and leads to exchange.