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.

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.

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.

A new instrument for high-resolution optical logging has been built and tested in Antarctica. Its purpose is to obtain records of volcanic products and other scattering features, such as bubbles and impurities, preserved in polar ice sheets, and it achieves this by using long wavelength near-infrared light that is absorbed by the ice before many scattering events occur. Longer wavelengths ensure that the return signal is composed primarily of a single or few backscattering event(s) that limit its spatial spread. The compact optical logger features no components on its body that draw power, which minimizes its size and weight. A prototype of the logger was built and tested at Siple Dome A borehole, and the results were correlated with prior optical logging profiles and records of volcanic products from collected ice core samples.

Non-destructive investigation, chemically fingerprinting, and authentication of ceramic cultural artifacts is a challenging analytical problem. Electron paramagnetic resonance (EPR) spectroscopy is capable of distinguishing between clays based on the paramagnetic metals present, and firing temperature (TF) based on the complexes of these metals formed at different TF values. Unfortunately, the 9 GHz frequency of conventional X-band EPR restricts sample size to a few mm and limits its applicability to small fragments. Low frequency EPR (LFEPR) is based on an EPR spectrometer operating at a few hundred MHz. LFEPR can utilize larger samples on the order of a few cm, but has a lower sensitivity due to the smaller Boltzmann ratio. Additionally, LFEPR may not be capable of detecting a spectral transition if the LFEPR operating frequency is less then the zero-field splitting of the paramagnetic metal complex. We utilized an LFEPR operating at 300 MHz which scans the applied magnetic field between the local Earth’s magnetic field and 26 mT to determine the feasibility of detecting EPR signals from clays, pigments, and glazes. Various clay samples were studied at 100 < TF < 1200 °C. Spectral differences were seen as a function of both clay type and TF. Differences in the LFEPR spectra of Han, Egyptian, and Ultramarine blue support the ability to distinguish among pigments. Paramagnetic impurities in glass may allow distinction between glaze spectra. We have also explored the utility of LFESR by the use of a radio frequency surface coil rather than an enclosed resonator. Although the active volume of the surface coil is ∼1 cm3, objects as large as 20 cm in diameter might be easily characterized with our spectrometer.

Nanoscale metal–insulator–metal (MIM) diodes consisting of a nanoscale-thickness insulator layer sandwiched between two dissimilar metal layers offer the potential for very high frequency alternating current to direct current signal rectification. Active nanoscale tuning of electronic tunneling through the insulator layer to form point contact diodes has previously been limited to barriers composed of soft organic films due to the force limitations of conductive-atomic force microscopy. In this paper, MIM diodes with oxide-based insulators are formed in situ with sub-nanometer depth precision and characterized using a nanoindenter equipped with electrical testing capabilities. Simultaneous measurement of both electrical and nano-mechanical information is accomplished in an MIM stack of the form Nb/Nb2O5/boron-doped diamond nanoindenter tip. Using this technique, we show that the diode behavior can be electromechanically tuned over a range of more than 1 V at equivalent currents via small changes in indentation depth and the results can be modeled using a Fowler–Nordheim approximation.

Alzheimer's disease (AD) is an urgent public health challenge that is rapidly approaching epidemic proportions. New therapies that defer or prevent the onset, delay the decline, or improve the symptoms are urgently needed. All phase 3 drug development programs for disease-modifying agents have failed thus far. New approaches to drug development are needed. Translational neuroscience focuses on the linkages between basic neuroscience and the development of new diagnostic and therapeutic products that will improve the lives of patients or prevent the occurrence of brain disorders. Translational neuroscience includes new preclinical models that may better predict human efficacy and safety, improved clinical trial designs and outcomes that will accelerate drug development, and the use of biomarkers to more rapidly provide information regarding the effects of drugs on the underlying disease biology. Early translational research is complemented by later stage translational approaches regarding how best to use evidence to impact clinical practice and to assess the influence of new treatments on the public health. Funding of translational research is evolving with an increased emphasis on academic and NIH involvement in drug development. Translational neuroscience provides a framework for advancing development of new therapies for AD patients.