Macular patterns of neuronal and visual field loss in recovered optic neuritis identified by machine learning.

We used machine learning to investigate the residual visual field (VF) deficits and macula retinal ganglion cell (RGC) thickness loss patterns in recovered optic neuritis (ON). We applied archetypal analysis (AA) to 377 same-day pairings of 10-2 VF and optical coherence tomography (OCT) macula images from 93 ON eyes and 70 normal fellow eyes ≥ 90 days after acute ON. We correlated archetype (AT) weights (total weight = 100%) of VFs and total retinal thickness (TRT), inner retinal thickness (IRT), and macular ganglion cell-inner plexiform layer (GCIPL) thickness.

Archetypal Analysis Reveals Consistent Visual Field Patterns for Stimulus Sizes III and V in Glaucoma and NAION.

Purpose: Disorders of the anterior optic nerve cause quantifiable patterns, or archetypes (AT), in visual fields (VFs) obtained using standardized automated perimetry using stimulus size III (size III). VFs with stimulus size V (size V) can reduce retest variability in eyes with moderate to severe loss. We postulated that VF testing using both stimuli would show similar ATs in eyes with glaucoma and nonarteritic anterior ischemic optic neuropathy (NAION).

Multi-omic network analysis identifies dysregulated neurobiological pathways in opioid addiction.

Background: Opioid addiction is a worldwide public health crisis. In the United States, for example, opioids cause more drug overdose deaths than any other substance. Yet, opioid addiction treatments have limited efficacy, meaning that additional treatments are needed.

Constitutive expression of CX3CR1-BAC-Cre introduces minimal off-target effects in microglia.

CX3CR1-Cre mouse lines have produced important advancements in our understanding of microglial biology. Recent studies have demonstrated the adverse effects of tamoxifen-induced CX3CR1-Cre expression during development, which include changes in microglial density, phenotype, and DNA damage, as well as anxiety-like behavior. However, the unintended effects of constitutive CX3CR1-BAC-Cre expression remain unexplored.

Limited Bedding and Nesting as a Model for Early-Life Adversity in Mice.

Early-life adversity (ELA), such as abuse, neglect, lack of resources, and an unpredictable home environment, is a known risk factor for developing neuropsychiatric disorders such as depression. Animal models for ELA have been used to study the impact of chronic stress on brain development, and typically rely on manipulating the quality and/or quantity of maternal care, as this is the major source of early-life experiences in mammals, including humans. Here, a detailed protocol for employing the Limited Bedding and Nesting (LBN) model in mice is provided.

A holistic platform for accelerating sorbent-based carbon capture.

Reducing carbon dioxide (CO) emissions urgently requires the large-scale deployment of carbon-capture technologies. These technologies must separate CO from various sources and deliver it to different sinks. The quest for optimal solutions for specific source-sink pairs is a complex, multi-objective challenge involving multiple stakeholders and depends on social, economic and regional contexts.

Novel Mito-Nuclear Combinations Facilitate the Global Invasion of a Major Agricultural Crop Pest.

A fundamental understanding of the underlying mechanisms involved in biological invasions is crucial to developing effective risk assessment and control measures against invasive species. The fall armyworm (FAW), Spodoptera frugiperda, is a highly invasive pest that has rapidly spread from its native Americas into much of the Eastern Hemisphere, with a highly homogeneous nuclear genetic background. However, the exact mechanism behind its rapid introduction and propagation remains unclear.

Classifying and quantifying changes in papilloedema using machine learning.

Background: Machine learning (ML) can differentiate papilloedema from normal optic discs using fundus photos. Currently, papilloedema severity is assessed using the descriptive, ordinal Frisén scale. We hypothesise that ML can quantify papilloedema and detect a treatment effect on papilloedema due to idiopathic intracranial hypertension.

Hybrid deep learning and optimal graph search method for optical coherence tomography layer segmentation in diseases affecting the optic nerve.

Accurate segmentation of retinal layers in optical coherence tomography (OCT) images is critical for assessing diseases that affect the optic nerve, but existing automated algorithms often fail when pathology causes irregular layer topology, such as extreme thinning of the ganglion cell-inner plexiform layer (GCIPL). Deep LOGISMOS, a hybrid approach that combines the strengths of deep learning and 3D graph search to overcome their limitations, was developed to improve the accuracy, robustness and generalizability of retinal layer segmentation. The method was trained on 124 OCT volumes from both eyes of 31 non-arteritic anterior ischemic optic neuropathy (NAION) patients and tested on three cross-sectional datasets with available reference tracings: Test-NAION (40 volumes from both eyes of 20 NAION subjects), Test-G (29 volumes from 29 glaucoma subjects/eyes), and Test-JHU (35 volumes from 21 multiple sclerosis and 14 control subjects/eyes) and one longitudinal dataset without reference tracings: Test-G-L (155 volumes from 15 glaucoma patients/eyes).

Exploring the Hawaiian Ala Wai Watershed with Zebrafish.

The Ala Wai Canal is an artificial waterway in the tourist district of Waikiki in Honolulu, HI. Originally built to collect runoff from industrial, residential, and green spaces dedicated to recreation, the Ala Wai Canal has since experienced potent levels of toxicity due to this runoff entering the watershed and making it hazardous for both marine life and humans at current concentration, including (zebrafish). A community of learners at educations levels from high school to postbaccalaureate from Oahu, HI was connected through the Consortium for Increasing Research and Collaborative Learning Experiences (CIRCLE) distance research program.

Cross-linked Triblock Peptide Capsules as Potential Oxygen Carriers.

Perfluorodecalin (PFD)-filled capsules have been studied for over 15 years as artificial oxygen carriers. However, none of these capsules combines good biocompatibility, good mechanical stability and dispersion stability. Here we propose to use synthetic triblock peptides containing a central block of cysteine units as a cross-linking shell material for capsules with both good biocompatibility and stability.

Radiation effects on retinal layers revealed by OCT, OCT-A, and perimetry as a function of dose and time from treatment.

Optical coherence tomography (OCT) has become a key method for diagnosing and staging radiation retinopathy, based mainly on the presence of fluid in the central macula. A robust retinal layer segmentation method is required for identification of the specific layers involved in radiation-induced pathology in individual eyes over time, in order to determine damage driven by radiation injury to the microvessels and to the inner retinal neurons. Here, we utilized OCT, OCT-angiography, visual field testing, and patient-specific dosimetry models to analyze abnormal retinal layer thickening and thinning relative to microvessel density, visual function, radiation dose, and time from radiotherapy in a cross-sectional cohort of uveal melanoma patients treated with I-plaque brachytherapy.

Visualization of Optic Nerve Structural Patterns in Papilledema Using Deep Learning Variational Autoencoders.

Purpose: To visualize and quantify structural patterns of optic nerve edema encountered in papilledema during treatment.

Methods: A novel bi-channel deep-learning variational autoencoder (biVAE) model was trained using 1498 optical coherence tomography (OCT) scans of 125 subjects over time from the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT) and 791 OCT scans of 96 control subjects from the University of Iowa. An independent test dataset of 70 eyes from 70 papilledema subjects was used to evaluate the ability of the biVAE model to quantify and reconstruct the papilledema spatial patterns from input OCT scans using only two variables.

Substance Misuse in Elite Athletes: Early Detection, Brief Intervention and Referral to Treatment.

Sports medicine physicians and athletic trainers regularly encounter athletes who misuse substances that put them at risk for adverse health, social, interpersonal, academic, psychological, and performance effects. The three most encountered substances are alcohol (binge drinking), cannabis (marijuana), and tobacco/nicotine vaping. Early detection using self-report screening instruments, adverse consequences questionnaires, and urine testing are reviewed.

A remote monitoring-enabled home exercise prescription for patients with interstitial lung disease at risk for exercise-induced desaturation.

Rationale: Alternatives to center-based pulmonary rehabilitation are needed to improve patient access to this important therapy. A critical challenge to overcome is how to maximize safety of unsupervised exercise for at-risk patients. We investigated if a novel remote monitoring-enabled mobile health (mHealth) program is safe, feasible, and effective for patients who experience exercise-induced hemoglobin desaturation.

Highly selective CO photoreduction to CO on MOF-derived TiO.

Metal-Organic Framework (MOF)-derived TiO, synthesised through the calcination of MIL-125-NH, is investigated for its potential as a CO photoreduction catalyst. The effect of the reaction parameters: irradiance, temperature and partial pressure of water was investigated. Using a two-level design of experiments, we were able to evaluate the influence of each parameter and their potential interactions on the reaction products, specifically the production of CO and CH.

Archetypal analysis of longitudinal visual fields for idiopathic intracranial hypertension patients presenting in a clinic setting.

We previously applied archetypal analysis (AA) using visual fields (VF) from the Idiopathic Intracranial Hypertension Treatment Trial (IIHTT) to derive a model, which quantified patterns (or archetypes [ATs] of VF loss), anticipated recovery, and identified residual VF deficits. We hypothesized that AA could produce similar results using IIH VFs collected in clinical practice. We applied AA to 803 VFs from 235 eyes with IIH from an outpatient neuro-ophthalmology clinic and created a clinic-derived model of ATs, with the relative weight (RW) and average total deviation (TD) for each AT.

Plasma proteomics of SARS-CoV-2 infection and severity reveals impact on Alzheimer's and coronary disease pathways.

Identification of proteins dysregulated by COVID-19 infection is critically important for better understanding of its pathophysiology, building prognostic models, and identifying new targets. Plasma proteomic profiling of 4,301 proteins was performed in two independent datasets and tested for the association for three COVID-19 outcomes (infection, ventilation, and death). We identified 1,449 proteins consistently associated in both datasets with any of these three outcomes.

AxoNet 2.0: A Deep Learning-Based Tool for Morphometric Analysis of Retinal Ganglion Cell Axons.

Purpose: Assessment of glaucomatous damage in animal models is facilitated by rapid and accurate quantification of retinal ganglion cell (RGC) axonal loss and morphologic change. However, manual assessment is extremely time- and labor-intensive. Here, we developed AxoNet 2.

Genetics of varicose veins reveals polygenic architecture and genetic overlap with arterial and venous disease.

Varicose veins represent a common cause of cardiovascular morbidity, with limited available medical therapies. Although varicose veins are heritable and epidemiologic studies have identified several candidate varicose vein risk factors, the molecular and genetic basis remains uncertain. Here we analyzed the contribution of common genetic variants to varicose veins using data from the Veterans Affairs Million Veteran Program and four other large biobanks.