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Abstract We demonstrate a new tomographic imaging device for 2D cross-sectional and 3D volumetric images of the anterior eye segment. The optical system combines optical sectioning with a stereoscopic camera setup to determine the true spatial location of the ocular structures. Moreover, we propose a calibration procedure to estimate the triangulation function that links the stereo camera pixel indices with the eye-referenced 3D spatial coordinates. The proposed instrument will image the entire anterior chamber and contiguous structures, including the corneal limbus, sclera and eyelids. Furthermore, the system can obtain corneal topography. Finally, we studied the repeatability of the instrument and its agreement with a commercial Scheimpflug imaging tomographer in a group of healthy subjects.

Purpose: To assess whether the combination of en face OCT and OCT angiography (OCTA) can capture observable, but subtle, structural changes that precede clinically evident retinal neovascularization (RNV) in eyes with diabetic retinopathy (DR). Design: Retrospective, longitudinal study. Participants: Patients with DR that had at least 2 visits. Methods: We obtained wide-field OCTA scans of 1 eye from each participant and generated en face OCT, en face OCTA, and cross-sectional OCTA. We identified eyes with RNV sprouts, defined as epiretinal hyperreflective materials on en face OCT with flow signals breaching the internal limiting membrane on the cross-sectional OCTA without recognizable RNV on en face OCTA and RNV fronds, defined as recognizable abnormal vascular structures on the en face OCTA. We examined the corresponding location from follow-up or previous visits for the presence or progression of the RNV. Main Outcome Measures: The characteristics and longitudinal observation of early signs of RNV. Results: From 71 eyes, we identified RNV in 20 eyes with the combination of OCT and OCTA, of which 13 (65%) were photographically graded as proliferative DR, 6 (30%) severe nonproliferative DR, and 1 (5%) moderate nonproliferative diabetic retinopathy. From these eyes, we identified 38 RNV sprouts and 26 RNV fronds at the baseline. Thirty-four RNVs (53%) originated from veins, 24 (38%) were from intraretinal microabnormalities, and 6 (9%) were from a nondilated capillary bed. At the final visit, 53 RNV sprouts and 30 RNV fronds were detected. Ten eyes (50%) showed progression, defined as having a new RNV lesion or the development of an RNV frond from an RNV sprout. Four (11%) RNV sprouts developed into RNV fronds with a mean interval of 7.0 months. Nineteen new RNV sprouts developed during the follow-up, whereas no new RNV frond was observed outside an identified RNV sprout. The eyes with progression were of younger age (P = 0.014) and tended to be treatment naive (P = 0.07) compared with eyes without progression. Conclusions: Longitudinal observation demonstrated that a combination of en face OCT and cross-sectional OCTA can identify an earlier form of RNV before it can be recognized on en face OCTA. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Abstract Non-accidental trauma (NAT) is deadly and difficult to predict. Transformer models pretrained on large datasets have recently produced state of the art performance on diverse prediction tasks, but the optimal pretraining strategies for diagnostic predictions are not known. Here we report the development and external validation of Pretrained and Adapted BERT for Longitudinal Outcomes (PABLO), a transformer-based deep learning model with multitask clinical pretraining, to identify patients who will receive a diagnosis of NAT in the next year. We develop a clinical interface to visualize patient trajectories, model predictions, and individual risk factors. In two comprehensive statewide databases, approximately 1% of patients experience NAT within one year of prediction. PABLO predicts NAT events with area under the receiver operating characteristic curve (AUROC) of 0.844 (95% CI 0.838–0.851) in the California test set, and 0.849 (95% CI 0.846–0.851) on external validation in Florida, outperforming comparator models. Multitask pretraining significantly improves model performance. Attribution analysis shows substance use, psychiatric, and injury diagnoses, in the context of age and racial demographics, as influential predictors of NAT. As a clinical decision support system, PABLO can identify high-risk patients and patient-specific risk factors, which can be used to target secondary screening and preventive interventions at the point-of-care.

Peptides are increasingly important resources for biological and therapeutic development, however, their intrinsic susceptibility to proteolytic degradation represents a big hurdle. As a natural agonist for GLP-1R, glucagon-like peptide 1 (GLP-1) is of significant clinical interest for the treatment of type-2 diabetes mellitus, but its in vivo instability and short half-life have largely prevented its therapeutic application. Here, we describe the rational design of a series of α/sulfono-γ-AA peptide hybrid analogues of GLP-1 as the GLP-1R agonists. Certain GLP-1 hybrid analogues exhibited enhanced stability (t1/2 > 14 days) compared to t1/2 (

Abstract Nuclear architecture underlies the transcriptional programs within the cell to establish cell identity. As previously demonstrated, long-range chromatin interactions of the Oct4 distal enhancer (DE) are correlated with active transcription in naïve state embryonic stem cells. Here, we identify and characterize extreme long-range interactions of the Oct4 DE through a novel CRISPR labeling technique we developed and chromosome conformation capture to identify lethal giant larvae 2 (Llgl2) and growth factor receptor-bound protein 7 (Grb7) as putative functional interacting target genes in different chromosomes. We show that the Oct4 DE directly regulates expression of Llgl2 and Grb7 in addition to Oct4. Expression of Llgl2 and Grb7 closely correlates with the pluripotent state, where knock down of either result in loss of pluripotency, and overexpression enhances somatic cell reprogramming. We demonstrated that biologically important interactions of the Oct4 DE can occur at extreme distances that are necessary for the maintenance of the pluripotent state.

The advancement of wireless networking has significantly enhanced beamforming capabilities in Autonomous Unmanned Aerial Systems (AUAS). This paper presents a simple and efficient classical algorithm to route a collection of AUAS or drone swarms extending our previous work on AUAS. The algorithm is based on the sparse factorization of frequency Vandermonde matrices that correspond to each drone, and its entries are determined through spatiotemporal data of drones in the AUAS. The algorithm relies on multibeam beamforming, making it suitable for large-scale AUAS networking in wireless communications. We show a reduction in the arithmetic and time complexities of the algorithm through theoretical and numerical results. Finally, we also present an ML-based AUAS routing algorithm using the classical AUAS algorithm and feed-forward neural networks. We compare the beamformed signals of the ML-based AUAS routing algorithm with the ground truth signals to minimize the error between them. The numerical error results show that the ML-based AUAS routing algorithm enhances the accuracy of the routing. This error, along with the numerical and theoretical results for over 100 drones, provides the basis for the scalability of the proposed ML-based AUAS algorithms for large-scale deployments.

ABSTRACT Ticks in the family Ixodidae are important vectors of zoonoses, including Lyme disease (LD), which is caused by spirochete bacteria from the Borreliella (Borrelia) burgdorferi sensu lato complex. The blacklegged tick (Ixodes scapularis) continues to expand across Canada, creating hot spots of elevated LD risk at the leading edge of its expanding range. Current efforts to understand the risk of pathogen transmission associated with I. scapularis in Canada focus primarily on targeted screens, while natural variation in the tick microbiome remains poorly understood. Using multiomics consisting of 16S metabarcoding and ribosome-depleted, whole-shotgun RNA transcriptome sequencing, we examined the microbial communities associated with adult I. scapularis (n = 32), sampled from four tissue types (whole tick, salivary glands, midgut, and viscera) and three geographical locations within a LD hot spot near Kingston, Ontario, Canada. The communities consisted of both endosymbiotic and known or potentially pathogenic microbes, including RNA viruses, bacteria, and a Babesia sp. intracellular parasite. We show that β-diversity is significantly higher between the bacterial communities of individual tick salivary glands and midguts than that of whole ticks. Linear discriminant analysis effect size (LEfSe) determined that the three potentially pathogenic bacteria detected by V4 16S rRNA sequencing also differed among dissected tissues only, including a Borrelia strain from the B. burgdorferi sensu lato complex, Borrelia miyamotoi, and Anaplasma phagocytophilum. Importantly, we find coinfection of I. scapularis by multiple microbes, in contrast to diagnostic protocols for LD, which typically focus on infection from a single pathogen of interest (B. burgdorferi sensu stricto). IMPORTANCE As a vector of human health concern, blacklegged ticks (Ixodes scapularis) transmit pathogens that cause tick-borne diseases (TBDs), including Lyme disease (LD). Several hot spots of elevated LD risk have emerged across Canada as I. scapularis expands its range. Focusing on a hot spot in southeastern Ontario, we used high-throughput sequencing to characterize the microbiome of whole ticks and dissected salivary glands and midguts. Compared with whole ticks, salivary glands and midguts were more diverse and associated with distinct bacterial communities that are less dominated by Rickettsia endosymbiont bacteria and are enriched for pathogenic bacteria, including a B. burgdorferi sensu lato-associated Borrelia sp., Borrelia miyamotoi, and Anaplasma phagocytophilum. We also found evidence of coinfection of I. scapularis by multiple pathogens. Overall, our study highlights the challenges and opportunities associated with the surveillance of the microbiome of I. scapularis for pathogen detection using metabarcoding and metatranscriptome approaches.

Abstract Background Approximately 3.8% of adults worldwide have used cannabis in the past year. Understanding how cannabis use is associated with other health conditions is crucial for healthcare providers seeking to understand the needs of their patients, and for health policymakers. This paper analyzes the relationship between documented cannabis use disorders (CUD), cannabis use (CU) and other health diagnoses among primary care patients during a time when medical use of marijuana was permitted by state law in California, United States of America. Methods The study utilized primary care electronic health record (EHR) data from an academic health system, using a case–control design to compare diagnoses among individuals with CUD/CU to those of matched controls, and those of individuals with CUD diagnoses with individuals who had CU otherwise documented. Associations of documented CU and CUD with general medical conditions and health conditions associated with cannabis use (both medical and behavioral) were analyzed using conditional logistic regression. Results Of 1,047,463 patients with ambulatory encounters from 2013–2017, 729 (0.06%) had CUD diagnoses and 3,731 (0.36%) had CU documented in their EHR. Patients with documented CUD and CU patients had significantly (p

Purpose: Timely diagnosis of eye diseases is paramount to obtaining the best treatment outcomes. OCT and OCT angiography (OCTA) have several advantages that lend themselves to early detection of ocular pathology; furthermore, the techniques produce large, feature-rich data volumes. However, the full clinical potential of both OCT and OCTA is stymied when complex data acquired using the techniques must be manually processed. Here, we propose an automated diagnostic framework based on structural OCT and OCTA data volumes that could substantially support the clinical application of these technologies. Design: Cross sectional study. Participants: Five hundred twenty-six OCT and OCTA volumes were scanned from the eyes of 91 healthy participants, 161 patients with diabetic retinopathy (DR), 95 patients with age-related macular degeneration (AMD), and 108 patients with glaucoma. Methods: The diagnosis framework was constructed based on semisequential 3-dimensional (3D) convolutional neural networks. The trained framework classifies combined structural OCT and OCTA scans as normal, DR, AMD, or glaucoma. Fivefold cross-validation was performed, with 60% of the data reserved for training, 20% for validation, and 20% for testing. The training, validation, and test data sets were independent, with no shared patients. For scans diagnosed as DR, AMD, or glaucoma, 3D class activation maps were generated to highlight subregions that were considered important by the framework for automated diagnosis. Main Outcome Measures: The area under the curve (AUC) of the receiver operating characteristic curve and quadratic-weighted kappa were used to quantify the diagnostic performance of the framework. Results: For the diagnosis of DR, the framework achieved an AUC of 0.95 ± 0.01. For the diagnosis of AMD, the framework achieved an AUC of 0.98 ± 0.01. For the diagnosis of glaucoma, the framework achieved an AUC of 0.91 ± 0.02. Conclusions: Deep learning frameworks can provide reliable, sensitive, interpretable, and fully automated diagnosis of eye diseases. Financial Disclosure(s): Proprietary or commercial disclosure may be found after the references.

Abstract This study reports the development of prototype swept-source optical coherence tomography (SS-OCT) technology for imaging the anterior eye. Advances in vertical-cavity surface-emitting laser (VCSEL) light sources, signal processing, optics and mechanical designs, enable a unique combination of high speed, long range, and deep penetration that addresses the challenges of anterior eye imaging. We demonstrate SS-OCT with a 325 kHz A-scan rate, 12.2 µm axial resolution (in air), and 15.5 mm depth range (in air) at 1310 nm wavelength. The ultrahigh 325 kHz A-scan rate not only facilitates biometry measurements by minimizing acquisition time and thus reducing motion, but also enables volumetric OCT for comprehensive structural analysis and OCT angiography (OCTA) for visualizing vasculature. The 15.5 mm (~ 11.6 mm in tissue) depth range spans all optical surfaces from the anterior cornea to the posterior lens capsule. The 1310 nm wavelength range enables structural OCT and OCTA deep in the sclera and through the iris. Achieving high speed and long range requires linearizing the VCSEL wavenumber sweep to efficiently utilize analog-to-digital conversion bandwidth. Dual channel recording of the OCT and calibration interferometer fringe signals, as well as sweep to sweep wavenumber compensation, is used to achieve invariant 12.2 µm (~ 9.1 µm in tissue) axial resolution and optimum point spread function throughout the depth range. Dynamic focusing using a tunable liquid lens extends the effective depth of field while preserving the lateral resolution. Improved optical and mechanical design, including parallax “split view” iris cameras and stable, ergonomic patient interface, facilitates accurate instrument positioning, reduces patient motion, and leads to improved imaging data yield and measurement accuracy. We present structural and angiographic OCT images of the anterior eye, demonstrating the unique imaging capabilities using representative scanning protocols which may be relevant to future research and clinical applications.

Purpose: To report the distinct pattern of retinal perfusion loss captured on optical coherence tomographic angiography (OCTA) in a case of compressive optic neuropathy associated with pituitary adenoma. Observations: A 51-year-old male had bitemporal hemianopia caused by a pituitary adenoma that compressed the optic chiasm. OCTA scans in both eyes showed peripapillary nerve fiber layer plexus defects in the nasal hemispheres and papillomacular corridors. On macular scans, the ganglion cell layer plexus showed papillomacular defects. The perfusion defects corresponded with thinning on structural OCT measurement and loss of sensitivity on visual field tests. Conclusions and importance: Chiasm compression produces a characteristic pattern of perfusion loss that can be recognized OCTA. This knowledge may be useful in the diagnosis and classification of optic neuropathies.

Optical coherence tomography (OCT) has changed the standard of care for diagnosis and management of macular diseases in adults. Current commercially available OCT systems, including handheld OCT for pediatric use, have a relatively narrow field of view (FOV), which has limited the potential application of OCT to retinal diseases with primarily peripheral pathology, including many of the most common pediatric retinal conditions. More broadly, diagnosis of all types of retinal detachment (exudative, tractional, and rhegmatogenous) may be improved with OCT-based assessment of retinal breaks, identification of proliferative vitreoretinopathy (PVR) membranes, and the pattern of subretinal fluid. Intraocular tumors both benign and malignant often occur outside of the central macula and may be associated with exudation, subretinal and intraretinal fluid, and vitreoretinal traction. The development of wider field OCT systems thus has the potential to improve the diagnosis and management of myriad diseases in both adult and pediatric retina. In this paper, we present a case series of pediatric patients with complex vitreoretinal pathology undergoing examinations under anesthesia (EUA) using a portable widefield (WF) swept-source (SS)-OCT device.

Purpose: To propose a deep-learning−based method to differentiate arteries from veins in montaged widefield OCT angiography (OCTA). Design: Cross-sectional study. Participants: A total of 232 participants, including 109 participants with diabetic retinopathy (DR), 64 participants with branch retinal vein occlusion (BRVO), 27 participants with diabetes but without DR, and 32 healthy participants. Methods: We propose a convolutional neural network (CAVnet) to classify retinal blood vessels on montaged widefield OCTA en face images as arteries and veins. A total of 240 retinal angiograms from 88 eyes were used to train CAVnet, and 302 retinal angiograms from 144 eyes were used for testing. This method takes the OCTA images as input and outputs the segmentation results with arteries and veins down to the level of precapillary arterioles and postcapillary venules. The network also identifies their intersections. We evaluated the agreement (in pixels) between segmentation results and the manually graded ground truth using sensitivity, specificity, F1-score, and Intersection over Union (IoU). Measurements of arterial and venous caliber or tortuosity are made on our algorithm’s output of healthy and diseased eyes. Main Outcome Measures: Classification of arteries and veins, arterial and venous caliber, and arterial and venous tortuosity. Results: For classification and identification of arteries, the algorithm achieved average sensitivity of 95.3%, specificity of 99.6%, F1 score of 94.2%, and IoU of 89.3%. For veins, the algorithm achieved average sensitivity of 94.4%, specificity of 99.7%, F1 score of 94.1%, and IoU of 89.2%. We also achieved an average sensitivity of 76.3% in identifying intersection points. The results show CAVnet has high accuracy on differentiating arteries and veins in DR and BRVO cases. These classification results are robust across 2 instruments and multiple scan volume sizes. Outputs of CAVnet were used to measure arterial and venous caliber or tortuosity, and pixel-wise caliber and tortuosity maps were generated. Differences between healthy and diseased eyes were demonstrated, indicating potential clinical utility. Conclusions: The CAVnet can classify arteries and veins and their branches with high accuracy and is potentially useful in the analysis of vessel type-specific features on diseases such as branch retinal artery occlusion and BRVO.

Purpose: To determine whether handheld widefield OCT can be used to document retinopathy of prematurity (ROP) stage while using scleral depression to improve peripheral views. Design: Prospective, observational study. Participants: Consecutive neonates admitted to the neonatal intensive care unit in a single academic medical center who also met criteria for ROP screening and whose parents or guardians consented for them to undergo research imaging. Methods: Scleral depression was combined with widefield OCT using an investigational 400-kHz, 55° field of view, handheld OCT during routine ROP screening from October 28, 2020, through March 3, 2021. Main Outcome Measures: Acquisition of en face and B-scan imaging of the peripheral retina to assess early vitreoretinal pathologic features objectively, including the demarcation between vascularized and anterior avascular retina, the presence of early ridge formation, and small neovascular tufts. Results: Various stages of ROP were detected using a rapid-acquisition OCT system. In 1 neonate, serial OCT imaging over a 5-week period demonstrated accumulation of neovascular tufts with progression to stage 3 ROP with extraretinal fibrovascular proliferation along the ridge. Videography of this technique is included in this report for instructional purposes. Conclusions: Serial examinations using widefield OCT and scleral depression are feasible and may improve detection and documentation of ROP disease progression. Earlier detection of ROP-related proliferation may prevent vitreoretinal traction, retinal detachment, and blindness.

This study identifies women college engineering students' perception of online Science, technology, engineering, and mathematics (STEM) learning and factors that influence their learning motivation during the COVID-19 period. By conducting interviews with ten women engineering students and applying attention, relevance, confidence, and satisfaction (ARCS) model, this study aims to answer two questions: (1) How did women college engineering students perceive their experience with online STEM learning during the pandemic? (2) What category/categories based on ARCS motivational design model primarily account for women college engineering students' learning motivation with online STEM learning during the pandemic? The results show that the online learning format influenced women college engineering students' perception regarding their academic plans, learning styles, learning environments, peer learning, and learning satisfaction. The most influential categories from ARCS model were 'confidence' and 'attention'. Findings suggest that the online STEM learning format influenced women college engineering students' learning motivation. The online format led to (1) low expectations for attention category when analyzed using ARCS model, (2) anticipation of more self-control, and (3) a desire for more peer interactions in their online STEM learning. As students would have new expectations for the role of online learning due to their experience during the pandemic, assessing women students' emerging motivational needs for STEM online learning is critical in developing a more inclusive instructional system design process in the future.

BackgroundDifferentiated service delivery (DSD) models are recommended for stable people living with HIV on antiretroviral therapy (ART) but there are few rigorous evaluations of patient outcomes.MethodsAdherence clubs (ACs) are a form of DSD run by community health workers at community venues with 2-4 monthly ART refills and annual nurse assessments). Clinic-based care involves 2-monthly ART refills and 4-monthly nurse/doctor assessments. We compared virologic outcomes in stable adults randomised to ACs at four months post-ART initiation to those randomised to primary health care (PHC) ART clinics through 12 months on ART in Cape Town, South Africa (NCT03199027). We hypothesised that adults randomised to ACs would be more likely to be virally suppressed at 12 months post-ART initiation, versus adults randomised to continued PHC care. We enrolled consecutive adults on ART for 3-5 months who met local DSD ['adherence clubs' (AC)] eligibility (clinically stable, VLResultsBetween January 2017 and April 2018, 220 adults were randomised (mean age 35 years; 67% female; median ART duration 18 weeks); 85% and 94% of participants randomised to ACs and PHCs attended their first service visit on schedule respectively. By 12 months on ART, 91% and 93% randomised to ACs and PHCs had a VLConclusionStable adults referred to DSDs at 4 months post-ART initiation had comparable virologic outcomes at 12 months on ART versus PHC clinics, with no evidence of superiority. Further research on long-term outcomes is required.

Recent advances in portable optical coherence tomography (OCT) and OCT angiography (OCTA) have resulted in wider fields of view (FOV) and shorter capture times, further expanding the potential clinical role of OCT technology in the diagnosis and management of retinopathy of prematurity (ROP). Using a prototype, handheld OCT device, retinal imaging was obtained in non-sedated infants in the neonatal intensive care unit (NICU) as well as sedated infants in the operating room of Oregon Health & Science University (OHSU) Hospital. In this observational study, we provide an overview of potential advantages of OCT-based disease assessment in ROP. We observed that next-generation OCT imaging (a) may be sufficient for objective diagnosis and zone/stage/plus disease categorization, (b) allows for minimally-invasive longitudinal monitoring of disease progression and post-treatment course, (c) provides three-dimensional mapping of the vitreoretinal interface, and (d) with OCTA, enables dye-free visualization of normal and pathologic vascular development.

Climate finance institutions have been tasked with effectively and efficiently allocating funds to spur the transition to low-carbon, climate-resilient economies. The Green Climate Fund (GCF) is expected to assist the most vulnerable adapt to and mitigate climate change because of its mandate to contribute to a paradigm shift. To understand if the GCF’s portfolio is on track to achieve this aim, we review the project documents of GCF investments through March 2020 (N = 125 projects). We examine attributes of these investments by applying a framework for potential transformational change, comprised of eight components. We use bivariate statistics and multivariate cluster analysis to examine the GCF’s project portfolio of mitigation, cross-cutting and adaptation projects. Bivariate tests find that adaptation projects show the greater intention to integrate policy change into national planning processes and that both adaptation and cross-cutting projects require a greater need for and expectation of behaviour change. Results from cluster analysis shows how adaptation projects dominate clusters with high and medium potential for transformational change (with 47% and 78% of projects, respectively). However, even the high potential cluster only displays the highest average scores for four of the eight components in our framework of transformational change. These findings present learning opportunities for the GCF’s future project selection. The GCF should leverage its current resources carefully to attain transformational impacts especially within adaptation where the Fund has a greater market share compared to mitigation projects.