P-Score: A Reference-Image-Based Clinical Grading Scale for Vascular Change in Retinopathy of Prematurity.

PURPOSE: The International Classification of Retinopathy of Prematurity Third Edition (ICROP3) acknowledged that plus-like ROP vascular changes occur along a spectrum. Historically, clinician-experts demonstrate variable agreement for plus diagnosis. We developed a 9-photo reference-image set for grading plus-like changes and compared intergrader agreement of the set to standard grading with no-plus/pre-plus/plus. DESIGN: Retinal photographic grading and expert consensus opinion PARTICIPANTS: Development: 34 international ICROP3 committee members. VALIDATION: 30 ophthalmologists with ROP expertise (15 ICROP3 committee members, 15 non-ICROP3 members) METHODS: Nine ROP fundus images (P1 through P9) representing increasing degrees of zone I vascular tortuosity and dilation, based on ICROP3-committee's 34 members' gradings and consensus image review, were used to establish standard photographs for the "Plus (P) Score." Study participants graded 150 fundus photographs two ways, separated by a 1-week washout period: (1) no-plus/pre-plus/plus disease, (2) choosing the closest P-Score image. MAIN OUTCOME MEASURES: Intergrader agreement measured by intraclass correlation coefficient (ICC) RESULTS: Intergrader agreement was higher using P-Score (ICC 0.75, 95% CI 0.71-0.79) than no-plus/pre-plus/plus (ICC 0.67, 95% CI 0.62-0.72). Mean P-Scores for images whose mode gradings were no-plus, pre-plus, and plus, were 2.5 (SD 0.7), 4.8 (SD 0.8), and 7.4 (SD 0.8), respectively. CONCLUSIONS: Intergrader agreement of plus-like vascular change in ROP using the P-Score is high. We recommend incorporation of this 9-image reference set into ICROP3 and clinician daily practice alongside zone/stage/plus. P-score is not yet meant to replace plus diagnosis for treatment decisions, but its use at our institutions has permitted better comparison between examinations for progression and regression, communication between examiners, and documentation of vascular change without fundus imaging. P-score also could provide more detailed ROP classification for clinical trials, consistent with the spectrum of plus-like change that is now formally part of ICROP.

Use of an artificial intelligence-generated vascular severity score improved plus disease diagnosis in retinopathy of prematurity.

OBJECTIVE: To evaluate whether providing clinicians with an artificial intelligence-based vascular severity score (AI-VSS) improves consistency in diagnosis of plus disease in retinopathy of prematurity (ROP). DESIGN: This is a multi-reader diagnostic accuracy imaging study. PARTICIPANTS: Eleven ROP experts (4 pediatric ophthalmologists, 7 retina specialists), 9 of which had been in practice for 10 or more years. METHODS: Retcam (Natus Medical Incorporated) fundus images were obtained from premature infants during routine ROP screening as part of the Imaging and Informatics in ROP study between January 2012 and July 2020. From all available exams, a subset of 150 eye exams from 110 infants were selected for grading. An AI-VSS was assigned to each set of images using the i-ROP DL system. The clinicians were asked to diagnose plus disease for each exam and assign an estimated VSS (range 1-9) at baseline, and then again one month later with AI-VSS assistance. A reference standard diagnosis (RSD) was assigned to each eye exam from the i-ROP study based on 3 masked expert labels and the ophthalmoscopic diagnosis. MAIN OUTCOME MEASURE: Mean linearly weighted kappa for plus disease diagnosis compared to the RSD. Area under the receiver operating characteristic and precision-recall curves (AUROC, AUPR) for 1-9 labels compared to RSD for plus disease. RESULTS: Expert agreement improved significantly from substantial (κ: 0.69 [0.59, 0.75]) to near perfect (κ: 0.81 [0.71, 0.86]) when AI-VSS was integrated. Additionally, there was a significant improvement in plus disease discrimination as measured by mean [95% confidence interval] AUROC (0.94 [0.92, 0.96] to 0.98 [0.96, 0.99], difference: 0.04 [0.01, 0.06]) and AUPR (0.86 [0.81, 0.90] to 0.95 [0.91, 0.97], difference: 0.09 [0.03, 0.14]). CONCLUSIONS: Providing ROP clinicians with an AI-based measurement of vascular severity in ROP was associated with both improved plus disease diagnosis and improved continuous severity labeling, as compared to a reference standard diagnosis for plus disease. If implemented in practice, AI-VSS could reduce inter-observer variability and standardize treatment for infants with ROP.

The effects of short-term, progressive exercise training on disease activity in smouldering multiple myeloma and monoclonal gammopathy of undetermined significance: a single-arm pilot study.

BACKGROUND: High levels of physical activity are associated with reduced risk of the blood cancer multiple myeloma (MM). MM is preceded by the asymptomatic stages of monoclonal gammopathy of undetermined significance (MGUS) and smouldering multiple myeloma (SMM) which are clinically managed by watchful waiting. A case study (N = 1) of a former elite athlete aged 44 years previously indicated that a multi-modal exercise programme reversed SMM disease activity. To build from this prior case study, the present pilot study firstly examined if short-term exercise training was feasible and safe for a group of MGUS and SMM patients, and secondly investigated the effects on MGUS/SMM disease activity. METHODS: In this single-arm pilot study, N = 20 participants diagnosed with MGUS or SMM were allocated to receive a 16-week progressive exercise programme. Primary outcome measures were feasibility and safety. Secondary outcomes were pre- to post-exercise training changes to blood biomarkers of MGUS and SMM disease activity- monoclonal (M)-protein and free light chains (FLC)- plus cardiorespiratory and functional fitness, body composition, quality of life, blood immunophenotype, and blood biomarkers of inflammation. RESULTS: Fifteen (3 MGUS and 12 SMM) participants completed the exercise programme. Adherence was 91 ± 11%. Compliance was 75 ± 25% overall, with a notable decline in compliance at intensities > 70% V̇O2PEAK. There were no serious adverse events. There were no changes to M-protein (0.0 ± 1.0 g/L, P =.903), involved FLC (+ 1.8 ± 16.8 mg/L, P =.839), or FLC difference (+ 0.2 ± 15.6 mg/L, P =.946) from pre- to post-exercise training. There were pre- to post-exercise training improvements to diastolic blood pressure (- 3 ± 5 mmHg, P =.033), sit-to-stand test performance (+ 5 ± 5 repetitions, P =.002), and energy/fatigue scores (+ 10 ± 15%, P =.026). Other secondary outcomes were unchanged. CONCLUSIONS: A 16-week progressive exercise programme was feasible and safe, but did not reverse MGUS/SMM disease activity, contrasting a prior case study showing that five years of exercise training reversed SMM in a 44-year-old former athlete. Longer exercise interventions should be explored in a group of MGUS/SMM patients, with measurements of disease biomarkers, along with rates of disease progression (i.e., MGUS/SMM to MM). REGISTRATION: https://www.isrctn.com/ISRCTN65527208 (14/05/2018).

Altered nucleus accumbens functional connectivity precedes apathy in Parkinson's disease.

Work in animal and human neuroscience has identified neural regions forming a network involved in the production of motivated, goal-directed behaviour. In particular, the nucleus accumbens and anterior cingulate cortex are recognized as key network nodes underlying decisions of whether to exert effort for reward, to drive behaviour. Previous work has convincingly shown that this cognitive mechanism, known as effort-based decision making, is altered in people with Parkinson's disease with a syndrome of reduced goal-directed behaviour-apathy. Building on this work, we investigated whether the neural regions implementing effort-based decision-making were associated with apathy in Parkinson's disease, and more importantly, whether changes to these regions were evident prior to apathy development. We performed a large, multimodal neuroimaging analysis in a cohort of people with Parkinson's disease (n = 199) with and without apathy at baseline. All participants had ∼2-year follow-up apathy scores, enabling examination of brain structure and function specifically in those with normal motivation who converted to apathy by ∼2-year follow-up. In addition, of the people with normal motivation, a subset (n = 56) had follow-up neuroimaging data, allowing for examination of the 'rate of change' in key nodes over time in those who did, and did not, convert to apathy. Healthy control (n = 54) data were also included to aid interpretation of findings. Functional connectivity between the nucleus accumbens and dorsal anterior cingulate cortex was higher in people with normal motivation who later converted to apathy compared to those who did not, whereas no structural differences were evident between these groups. In contrast, grey matter volume in these regions was reduced in the group with existing apathy. Furthermore, of those with normal motivation who had undergone longitudinal neuroimaging, converters to apathy showed a higher rate of change in grey matter volume within the nucleus accumbens. Overall, we show that changes in functional connectivity between nucleus accumbens and anterior cingulate cortex precedes apathy in people with Parkinson's disease, with conversion to apathy associated with higher rate of grey matter volume loss in nucleus accumbens, despite no baseline differences. These findings significantly add to an accumulating body of transdiagnostic evidence that apathy arises from disruption to key nodes within a network in which normal goal-directed behaviour is instantiated, and raise the possibility of identifying those at risk for developing apathy before overt motivational deficits have arisen.

Detection of occult thrombosis in individuals with Fontan circulation by cardiac MRI.

OBJECTIVE: Identifying thrombus formation in Fontan circulation has been highly variable, with reports between 17 and 33%. Initially, thrombus detection was mainly done through echocardiograms. Delayed-enhancement cardiac MRI is emerging as a more effective imaging technique for thrombus identification. This study aims to determine the prevalence of occult cardiac thrombosis in patients undergoing clinically indicated cardiac MRI. METHODS: A retrospective chart review of children and adults in the Duke University Hospital Fontan registry who underwent delayed-enhancement cardiac MRI. Individuals were excluded if they never received a delayed-enhancement cardiac MRI or had insufficient data. Demographic characteristics, native heart anatomy, cardiac MRI measurements, and thromboembolic events were collected for all patients. RESULTS: In total, 119 unique individuals met inclusion criteria with a total of 171 scans. The median age at Fontan procedure was 3 (interquartile range 1, 4) years. The majority of patients had dominant systemic right ventricle. Cardiac function was relatively unchanged from the first cardiac MRI to the third cardiac MRI. While 36.4% had a thrombotic event by history, only 0.5% (1 patient) had an intracardiac thrombus detected by delayed-enhancement cardiac MRI. CONCLUSIONS: Despite previous echocardiographic reports of high prevalence of occult thrombosis in patients with Fontan circulation, we found very low prevalence using delayed-enhancement cardiac MRI. As more individuals are reaching adulthood after requiring early Fontan procedures in childhood, further work is needed to develop thrombus-screening protocols as a part of anticoagulation management.

A Retrospective, Observational Study of 12 Cases of Expanded-Access Customized Phage Therapy: Production, Characteristics, and Clinical Outcomes.

BACKGROUND: Antimicrobial resistance (AMR) is undermining modern medicine, a problem compounded by bacterial adaptation to antibiotic pressures. Phages are viruses that infect bacteria. Their diversity and evolvability offer the prospect of their use as a therapeutic solution. Reported are outcomes of customized phage therapy for patients with difficult-to-treat antimicrobial resistant infections. METHODS: We retrospectively assessed 12 cases of customized phage therapy from a phage production center. Phages were screened, purified, sequenced, characterized, and Food and Drug Administration-approved via the IND (investigational new drug) compassionate-care route. Outcomes were assessed as favorable or unfavorable by microbiologic and clinical standards. Infections were device-related or systemic. Other experiences such as time to treatment, antibiotic synergy, and immune responses were recorded. RESULTS: Fifty requests for phage therapy were received. Customized phages were generated for 12 patients. After treatment, 42% (5/12) of cases showed bacterial eradication and 58% (7/12) showed clinical improvement, with two-thirds of all cases (66%) showing favorable responses. No major adverse reactions were observed. Antibiotic-phage synergy in vitro was observed in most cases. Immunological neutralization of phages was reported in 5 cases. Several cases were complicated by secondary infections. Complete characterization of the phages (morphology, genomics, and activity) and their production (methods, sterility, and endotoxin tests) are reported. CONCLUSIONS: Customized phage production and therapy was safe and yielded favorable clinical or microbiological outcomes in two-thirds of cases. A center or pipeline dedicated to tailoring the phages against a patient's specific AMR bacterial infection may be a viable option where standard treatment has failed.

Epidemiologic Evaluation of Retinopathy of Prematurity Severity in a Large Telemedicine Program in India Using Artificial Intelligence.

PURPOSE: Epidemiological changes in retinopathy of prematurity (ROP) depend on neonatal care, neonatal mortality, and the ability to carefully titrate and monitor oxygen. We evaluate whether an artificial intelligence (AI) algorithm for assessing ROP severity in babies can be used to evaluate changes in disease epidemiology in babies from South India over a 5-year period. DESIGN: Retrospective cohort study. PARTICIPANTS: Babies (3093) screened for ROP at neonatal care units (NCUs) across the Aravind Eye Care System (AECS) in South India. METHODS: Images and clinical data were collected as part of routine tele-ROP screening at the AECS in India over 2 time periods: August 2015 to October 2017 and March 2019 to December 2020. All babies in the original cohort were matched 1:3 by birthweight (BW) and gestational age (GA) with babies in the later cohort. We compared the proportion of eyes with moderate (type 2) or treatment-requiring (TR) ROP, and an AI-derived ROP vascular severity score (from retinal fundus images) at the initial tele-retinal screening exam for all babies in a district, VSS), in the 2 time periods. MAIN OUTCOME MEASURES: Differences in the proportions of type 2 or worse and TR-ROP cases, and VSS between time periods. RESULTS: Among BW and GA matched babies, the proportion [95% confidence interval {CI}] of babies with type 2 or worse and TR-ROP decreased from 60.9% [53.8%-67.7%] to 17.1% [14.0%-20.5%] (P < 0.001) and 16.8% [11.9%-22.7%] to 5.1% [3.4%-7.3%] (P < 0.001), over the 2 time periods. Similarly, the median [interquartile range] VSS in the population decreased from 2.9 [1.2] to 2.4 [1.8] (P < 0.001). CONCLUSIONS: In South India, over a 5-year period, the proportion of babies developing moderate to severe ROP has dropped significantly for babies at similar demographic risk, strongly suggesting improvements in primary prevention of ROP. These results suggest that AI-based assessment of ROP severity may be a useful epidemiologic tool to evaluate temporal changes in ROP epidemiology. FINANCIAL DISCLOSURE(S): Proprietary or commercial disclosure may be found after the references.

Large historical growth in global terrestrial gross primary production.

Growth in terrestrial gross primary production (GPP)-the amount of carbon dioxide that is 'fixed' into organic material through the photosynthesis of land plants-may provide a negative feedback for climate change. It remains uncertain, however, to what extent biogeochemical processes can suppress global GPP growth. As a consequence, modelling estimates of terrestrial carbon storage, and of feedbacks between the carbon cycle and climate, remain poorly constrained. Here we present a global, measurement-based estimate of GPP growth during the twentieth century that is based on long-term atmospheric carbonyl sulfide (COS) records, derived from ice-core, firn and ambient air samples. We interpret these records using a model that simulates changes in COS concentration according to changes in its sources and sinks-including a large sink that is related to GPP. We find that the observation-based COS record is most consistent with simulations of climate and the carbon cycle that assume large GPP growth during the twentieth century (31% ± 5% growth; mean ± 95% confidence interval). Although this COS analysis does not directly constrain models of future GPP growth, it does provide a global-scale benchmark for historical carbon-cycle simulations.

The effect of a novel, digital physical activity and emotional well-being intervention on health-related quality of life in people with chronic kidney disease: trial design and baseline data from a multicentre prospective, wait-list randomised controlled trial (kidney BEAM).

BACKGROUND: Physical activity and emotional self-management has the potential to enhance health-related quality of life (HRQoL), but few people with chronic kidney disease (CKD) have access to resources and support. The Kidney BEAM trial aims to evaluate whether an evidence-based physical activity and emotional wellbeing self-management programme (Kidney BEAM) leads to improvements in HRQoL in people with CKD. METHODS: This was a prospective, multicentre, randomised waitlist-controlled trial, with health economic analysis and nested qualitative studies. In total, three hundred and four adults with established CKD were recruited from 11 UK kidney units. Participants were randomly assigned to the intervention (Kidney BEAM) or a wait list control group (1:1). The primary outcome was the between-group difference in Kidney Disease Quality of Life (KDQoL) mental component summary score (MCS) at 12 weeks. Secondary outcomes included the KDQoL physical component summary score, kidney-specific scores, fatigue, life participation, depression and anxiety, physical function, clinical chemistry, healthcare utilisation and harms. All outcomes were measured at baseline and 12 weeks, with long-term HRQoL and adherence also collected at six months follow-up. A nested qualitative study explored experience and impact of using Kidney BEAM. RESULTS: 340 participants were randomised to Kidney BEAM (n = 173) and waiting list (n = 167) groups. There were 96 (55%) and 89 (53%) males in the intervention and waiting list groups respectively, and the mean (SD) age was 53 (14) years in both groups. Ethnicity, body mass, CKD stage, and history of diabetes and hypertension were comparable across groups. The mean (SD) of the MCS was similar in both groups, 44.7 (10.8) and 45.9 (10.6) in the intervention and waiting list groups respectively. CONCLUSION: Results from this trial will establish whether the Kidney BEAM self management programme is a cost-effective method of enhancing mental and physical wellbeing of people with CKD. TRIAL REGISTRATION: NCT04872933. Registered 5th May 2021.

Addressing Domestic Violence in Antenatal Care Environments in Nepal (ADVANCE) - study protocol for a randomized controlled trial evaluating a video intervention on domestic violence among pregnant women.

BACKGROUND: Domestic violence (DV) prior to, and during pregnancy is associated with increased risks for morbidity and mortality. As pregnant women routinely attend antenatal care this environment can be used to offer support to women experiencing DV. We have developed a video intervention that focuses on the use of behavioral coping strategies, particularly regarding disclosure of DV experiences. The effectiveness of this intervention will be evaluated through a randomized controlled trial (RCT) and a concurrent process evaluation. METHODS: All pregnant women between 12-22 weeks of gestation attending routine antenatal care at two tertiary level hospitals in Nepal are invited to participate. DV is measured using the Nepalese version of the Abuse Assessment Screen (N-AAS). Additionally, we measure participants' mental health, use of coping strategies, physical activity, and food security through a Color-coded Audio Computer Assisted Self Interview (C-ACASI). Irrespective of DV status, women are randomized into the intervention or control arm using a computer-generated randomization program. The intervention arm views a short video providing information on DV, safety improving actions women can take with an emphasis on disclosing the violence to a trusted person along with utilizing helplines available in Nepal. The control group watches a video on maintaining a healthy pregnancy and when to seek healthcare. The primary outcome is the proportion of women disclosing their DV status to someone. Secondary outcomes are symptoms of anxiety and depression, coping strategies, the use of safety measures and attitudes towards acceptance of abuse. Follow-up is conducted after 32 weeks of gestation, where both the intervention and control group participants view the intervention video after completing the follow-up questionnaire. Additionally, a mixed methods process evaluation of the intervention will be carried out to explore factors influencing the acceptability of the intervention and the disclosure of DV, including a review of project documents, individual interviews, and focus group discussions with members of the research team, healthcare providers, and participants. DISCUSSION: This study will provide evidence on whether pregnant women attending regular antenatal visits can enhance their safety by disclosing their experiences of violence to a trusted person after receiving a video intervention. TRIAL REGISTRATION: The study is registered in ClinicalTrial.gov with identifier NCT05199935.

Artificial Intelligence for Retinopathy of Prematurity: Validation of a Vascular Severity Scale against International Expert Diagnosis.

PURPOSE: To validate a vascular severity score as an appropriate output for artificial intelligence (AI) Software as a Medical Device (SaMD) for retinopathy of prematurity (ROP) through comparison with ordinal disease severity labels for stage and plus disease assigned by the International Classification of Retinopathy of Prematurity, Third Edition (ICROP3), committee. DESIGN: Validation study of an AI-based ROP vascular severity score. PARTICIPANTS: A total of 34 ROP experts from the ICROP3 committee. METHODS: Two separate datasets of 30 fundus photographs each for stage (0-5) and plus disease (plus, preplus, neither) were labeled by members of the ICROP3 committee using an open-source platform. Averaging these results produced a continuous label for plus (1-9) and stage (1-3) for each image. Experts were also asked to compare each image to each other in terms of relative severity for plus disease. Each image was also labeled with a vascular severity score from the Imaging and Informatics in ROP deep learning system, which was compared with each grader's diagnostic labels for correlation, as well as the ophthalmoscopic diagnosis of stage. MAIN OUTCOME MEASURES: Weighted kappa and Pearson correlation coefficients (CCs) were calculated between each pair of grader classification labels for stage and plus disease. The Elo algorithm was also used to convert pairwise comparisons for each expert into an ordered set of images from least to most severe. RESULTS: The mean weighted kappa and CC for all interobserver pairs for plus disease image comparison were 0.67 and 0.88, respectively. The vascular severity score was found to be highly correlated with both the average plus disease classification (CC = 0.90, P < 0.001) and the ophthalmoscopic diagnosis of stage (P < 0.001 by analysis of variance) among all experts. CONCLUSIONS: The ROP vascular severity score correlates well with the International Classification of Retinopathy of Prematurity committee member's labels for plus disease and stage, which had significant intergrader variability. Generation of a consensus for a validated scoring system for ROP SaMD can facilitate global innovation and regulatory authorization of these technologies.

Deeply Virtual Compton Scattering Cross Section at High Bjorken x_{B}.

We report high-precision measurements of the deeply virtual Compton scattering (DVCS) cross section at high values of the Bjorken variable x_{B}. DVCS is sensitive to the generalized parton distributions of the nucleon, which provide a three-dimensional description of its internal constituents. Using the exact analytic expression of the DVCS cross section for all possible polarization states of the initial and final electron and nucleon, and final state photon, we present the first experimental extraction of all four helicity-conserving Compton form factors (CFFs) of the nucleon as a function of x_{B}, while systematically including helicity flip amplitudes. In particular, the high accuracy of the present data demonstrates sensitivity to some very poorly known CFFs.

Form Factors and Two-Photon Exchange in High-Energy Elastic Electron-Proton Scattering.

We present new precision measurements of the elastic electron-proton scattering cross section for momentum transfer (Q^{2}) up to 15.75 (GeV/c)^{2}. Combined with existing data, these provide an improved extraction of the proton magnetic form factor at high Q^{2} and double the range over which a longitudinal or transverse separation of the cross section can be performed. The difference between our results and polarization data agrees with that observed at lower Q^{2} and attributed to hard two-photon exchange (TPE) effects, extending to 8 (GeV/c)^{2} the range of Q^{2} for which a discrepancy is established at >95% confidence. We use the discrepancy to quantify the size of TPE contributions needed to explain the cross section at high Q^{2}.

Rapid separation of cannabinoid isomer sets using differential mobility spectrometry and mass spectrometry.

With legalization and decriminalization of cannabis in many parts of the world comes the need for rapid separation and quantitation of the psychoactive ingredients. Here, we demonstrate the use of differential mobility spectrometry (DMS) mass spectrometry for the analysis of five cannabinoid molecules: the isomer set of Δ9-tetrahydrocannabinol (THC), cannabidiol (CBD), and cannabichromine (CBC), and the (-)-tetrahydrocannabinolic acid (THCA) and cannabidiolic acid (CBDA) isomer pair. Analytes were investigated under a variety of gas-phase environments to identify optimal separation conditions based on ion differential mobilities. Separation of the isomers was complicated by the formation of ion-solvent adducts during electrospray ionization (ESI). The observation of ion-solvent adducts correlated with calculated intermolecular binding energies. Introducing 1.5% (v/v) isopropyl alcohol into the N2 carrier gas resulted in strong clustering with the cannabinoid isomers, displacing ESI solvent from the adducts and enabling separation and quantitation of the cannabinoid isomer sets within seconds. Quantification of the carboxylated isomers in marijuana flower was performed to demonstrate analysis of cannabis samples.

Determining Collision Cross Sections from Differential Ion Mobility Spectrometry.

The experimental determination of ion-neutral collision cross sections (CCSs) is generally confined to ion mobility spectrometry (IMS) technologies that operate under the so-called low-field limit or those that enable empirical calibration strategies (e.g., traveling wave IMS; TWIMS). Correlation of ion trajectories to CCS in other non-linear IMS techniques that employ dynamic electric fields, such as differential mobility spectrometry (DMS), has remained a challenge since its inception. Here, we describe how an ion's CCS can be measured from DMS experiments using a machine learning (ML)-based calibration. The differential mobility of 409 molecular cations (m/z: 86-683 Da and CCS 110-236 Å2) was measured in a N2 environment to train the ML framework. Several open-source ML routines were tested and trained using DMS-MS data in the form of the parent ion's m/z and the compensation voltage required for elution at specific separation voltages between 1500 and 4000 V. The best performing ML model, random forest regression, predicted CCSs with a mean absolute percent error of 2.6 ± 0.4% for analytes excluded from the training set (i.e., out-of-the-bag external validation). This accuracy approaches the inherent statistical error of ∼2.2% for the MobCal-MPI CCS calculations employed for training purposes and the <2% threshold for matching literature CCSs with those obtained on a TWIMS platform.

Evaluation of a Deep Learning-Derived Quantitative Retinopathy of Prematurity Severity Scale.

PURPOSE: To evaluate the clinical usefulness of a quantitative deep learning-derived vascular severity score for retinopathy of prematurity (ROP) by assessing its correlation with clinical ROP diagnosis and by measuring clinician agreement in applying a novel scale. DESIGN: Analysis of existing database of posterior pole fundus images and corresponding ophthalmoscopic examinations using 2 methods of assigning a quantitative scale to vascular severity. PARTICIPANTS: Images were from clinical examinations of patients in the Imaging and Informatics in ROP Consortium. Four ophthalmologists and 1 study coordinator evaluated vascular severity on a scale from 1 to 9. METHODS: A quantitative vascular severity score (1-9) was applied to each image using a deep learning algorithm. A database of 499 images was developed for assessment of interobserver agreement. MAIN OUTCOME MEASURES: Distribution of deep learning-derived vascular severity scores with the clinical assessment of zone (I, II, or III), stage (0, 1, 2, or 3), and extent (<3 clock hours, 3-6 clock hours, and >6 clock hours) of stage 3 evaluated using multivariate linear regression and weighted κ values and Pearson correlation coefficients for interobserver agreement on a 1-to-9 vascular severity scale. RESULTS: For deep learning analysis, a total of 6344 clinical examinations were analyzed. A higher deep learning-derived vascular severity score was associated with more posterior disease, higher disease stage, and higher extent of stage 3 disease (P < 0.001 for all). For a given ROP stage, the vascular severity score was higher in zone I than zones II or III (P < 0.001). Multivariate regression found zone, stage, and extent all were associated independently with the severity score (P < 0.001 for all). For interobserver agreement, the mean ± standard deviation weighted κ value was 0.67 ± 0.06, and the Pearson correlation coefficient ± standard deviation was 0.88 ± 0.04 on the use of a 1-to-9 vascular severity scale. CONCLUSIONS: A vascular severity scale for ROP seems feasible for clinical adoption; corresponds with zone, stage, extent of stage 3, and plus disease; and facilitates the use of objective technology such as deep learning to improve the consistency of ROP diagnosis.

International Classification of Retinopathy of Prematurity, Third Edition.

PURPOSE: The International Classification of Retinopathy of Prematurity is a consensus statement that creates a standard nomenclature for classification of retinopathy of prematurity (ROP). It was initially published in 1984, expanded in 1987, and revisited in 2005. This article presents a third revision, the International Classification of Retinopathy of Prematurity, Third Edition (ICROP3), which is now required because of challenges such as: (1) concerns about subjectivity in critical elements of disease classification; (2) innovations in ophthalmic imaging; (3) novel pharmacologic therapies (e.g., anti-vascular endothelial growth factor agents) with unique regression and reactivation features after treatment compared with ablative therapies; and (4) recognition that patterns of ROP in some regions of the world do not fit neatly into the current classification system. DESIGN: Review of evidence-based literature, along with expert consensus opinion. PARTICIPANTS: International ROP expert committee assembled in March 2019 representing 17 countries and comprising 14 pediatric ophthalmologists and 20 retinal specialists, as well as 12 women and 22 men. METHODS: The committee was initially divided into 3 subcommittees-acute phase, regression or reactivation, and imaging-each of which used iterative videoconferences and an online message board to identify key challenges and approaches. Subsequently, the entire committee used iterative videoconferences, 2 in-person multiday meetings, and an online message board to develop consensus on classification. MAIN OUTCOME MEASURES: Consensus statement. RESULTS: The ICROP3 retains current definitions such as zone (location of disease), stage (appearance of disease at the avascular-vascular junction), and circumferential extent of disease. Major updates in the ICROP3 include refined classification metrics (e.g., posterior zone II, notch, subcategorization of stage 5, and recognition that a continuous spectrum of vascular abnormality exists from normal to plus disease). Updates also include the definition of aggressive ROP to replace aggressive-posterior ROP because of increasing recognition that aggressive disease may occur in larger preterm infants and beyond the posterior retina, particularly in regions of the world with limited resources. ROP regression and reactivation are described in detail, with additional description of long-term sequelae. CONCLUSIONS: These principles may improve the quality and standardization of ROP care worldwide and may provide a foundation to improve research and clinical care.

105° field of view non-contact handheld swept-source optical coherence tomography.

We demonstrate a handheld swept-source optical coherence tomography (OCT) system with a 400 kHz vertical-cavity surface-emitting laser (VCSEL) light source, a non-contact approach, and an unprecedented single shot 105° field of view (FOV). We also implemented a spiral scanning pattern allowing real-time visualization with improved scanning efficiency. To the best of our knowledge, this is the widest FOV achieved in a portable non-contact OCT retinal imaging system to date. Improvements to the FOV may aid the evaluation of retinal diseases such as retinopathy of prematurity, where important vitreoretinal changes often occur in the peripheral retina.

Deep Exclusive Electroproduction of π

We report measurements of the exclusive neutral pion electroproduction cross section off protons at large values of x_{B} (0.36, 0.48, and 0.60) and Q^{2} (3.1 to 8.4 GeV^{2}) obtained from Jefferson Lab Hall A experiment E12-06-014. The corresponding structure functions dσ_{T}/dt+εdσ_{L}/dt, dσ_{TT}/dt, dσ_{LT}/dt, and dσ_{LT^{'}}/dt are extracted as a function of the proton momentum transfer t-t_{min}. The results suggest the amplitude for transversely polarized virtual photons continues to dominate the cross section throughout this kinematic range. The data are well described by calculations based on transversity generalized parton distributions coupled to a helicity flip distribution amplitude of the pion, thus providing a unique way to probe the structure of the nucleon.

Predicting differential ion mobility behaviour in silico using machine learning.

Although there has been a surge in popularity of differential mobility spectrometry (DMS) within analytical workflows, determining separation conditions within the DMS parameter space still requires manual optimization. A means of accurately predicting differential ion mobility would benefit practitioners by significantly reducing the time associated with method development. Here, we report a machine learning (ML) approach that predicts dispersion curves in an N2 environment, which are the compensation voltages (CVs) required for optimal ion transmission across a range of separation voltages (SVs) between 1500 to 4000 V. After training a random-forest based model using the DMS information of 409 cationic analytes, dispersion curves were reproduced with a mean absolute error (MAE) of ≤ 2.4 V, approaching typical experimental peak FWHMs of ±1.5 V. The predictive ML model was trained using only m/z and ion-neutral collision cross section (CCS) as inputs, both of which can be obtained from experimental databases before being extensively validated. By updating the model via inclusion of two CV datapoints at lower SVs (1500 V and 2000 V) accuracy was further improved to MAE ≤ 1.2 V. This improvement stems from the ability of the "guided" ML routine to accurately capture Type A and B behaviour, which was exhibited by only 2% and 17% of ions, respectively, within the dataset. Dispersion curve predictions of the database's most common Type C ions (81%) using the unguided and guided approaches exhibited average errors of 0.6 V and 0.1 V, respectively.