Summary
Background
The rs738409 GG variant in patatin‐like phospholipase 3 (PNPLA3) is associated with non‐alcoholic fatty liver disease (NAFLD) and disease severity. However, it remains unclear if ...it contributes to the development of NAFLD through affecting dietary pattern.
Aim
To examine the association among PNPLA3 gene polymorphism, dietary pattern, metabolic factors and NAFLD.
Methods
Liver fat and fibrosis were assessed by proton‐magnetic resonance spectroscopy and transient elastography in 920 subjects from a population screening project (251 had NAFLD). Dietary nutrient intake was recorded using a locally validated food‐frequency questionnaire.
Results
The prevalence of GG genotype in NAFLD subjects was 20.7%, compared to 10.6% in controls (P < 0.001). Macronutrient intake was similar among subjects with different PNPLA3 genotypes. The presence of G allele was a predictor of NAFLD independent of nutrient intake and other metabolic factors (adjusted odds ratio to CC: CG, 2.00; GG, 2.68). In subjects without metabolic syndrome, G allele was even more closely correlated with NAFLD diagnosis (adjusted odds ratio to CC: CG, 2.22; GG, 3.39). The prevalence of NAFLD was only 12% in subjects with CC genotype and no metabolic syndrome, and increased to 34% in those with GG genotype and no metabolic syndrome. While NAFLD subjects had significantly lower fibre intake, there was no significant interaction between PNPLA3 and dietary pattern.
Conclusions
The G allele in PNPLA3 rs738409 increases the risk of NAFLD in the general population, especially in subjects without metabolic syndrome, independent of dietary pattern and metabolic factors.
Throughout our lifespan, new sensory experiences and learning continually shape our neuronal circuits to form new memories. Plasticity at the level of synapses has been recognized and studied for ...decades, but recent work has revealed an additional form of plasticity - affecting oligodendrocytes and the myelin sheaths they produce - that plays a crucial role in learning and memory. In this Review, we summarize recent work characterizing plasticity in the oligodendrocyte lineage following sensory experience and learning, the physiological and behavioural consequences of manipulating that plasticity, and the evidence for oligodendrocyte and myelin dysfunction in neurodevelopmental disorders with cognitive symptoms. We also discuss the limitations of existing approaches and the conceptual and technical advances that are needed to move forward this rapidly developing field.
Retinopathy of prematurity (ROP) is a retinal vasoproliferative disease that affects premature infants. Despite improvements in neonatal care and management guidelines, ROP remains a leading cause of ...childhood blindness worldwide. Current screening guidelines are primarily based on two risk factors: birth weight and gestational age; however, many investigators have suggested other risk factors, including maternal factors, prenatal and perinatal factors, demographics, medical interventions, comorbidities of prematurity, nutrition, and genetic factors. We review the existing literature addressing various possible ROP risk factors. Although there have been contradictory reports, and the risk may vary between different populations, understanding ROP risk factors is essential to develop predictive models, to gain insights into pathophysiology of retinal vascular diseases and diseases of prematurity, and to determine future directions in management of and research in ROP.
IMPORTANCE: Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The decision to treat is primarily based on the presence of plus disease, defined as dilation and ...tortuosity of retinal vessels. However, clinical diagnosis of plus disease is highly subjective and variable. OBJECTIVE: To implement and validate an algorithm based on deep learning to automatically diagnose plus disease from retinal photographs. DESIGN, SETTING, AND PARTICIPANTS: A deep convolutional neural network was trained using a data set of 5511 retinal photographs. Each image was previously assigned a reference standard diagnosis (RSD) based on consensus of image grading by 3 experts and clinical diagnosis by 1 expert (ie, normal, pre–plus disease, or plus disease). The algorithm was evaluated by 5-fold cross-validation and tested on an independent set of 100 images. Images were collected from 8 academic institutions participating in the Imaging and Informatics in ROP (i-ROP) cohort study. The deep learning algorithm was tested against 8 ROP experts, each of whom had more than 10 years of clinical experience and more than 5 peer-reviewed publications about ROP. Data were collected from July 2011 to December 2016. Data were analyzed from December 2016 to September 2017. EXPOSURES: A deep learning algorithm trained on retinal photographs. MAIN OUTCOMES AND MEASURES: Receiver operating characteristic analysis was performed to evaluate performance of the algorithm against the RSD. Quadratic-weighted κ coefficients were calculated for ternary classification (ie, normal, pre–plus disease, and plus disease) to measure agreement with the RSD and 8 independent experts. RESULTS: Of the 5511 included retinal photographs, 4535 (82.3%) were graded as normal, 805 (14.6%) as pre–plus disease, and 172 (3.1%) as plus disease, based on the RSD. Mean (SD) area under the receiver operating characteristic curve statistics were 0.94 (0.01) for the diagnosis of normal (vs pre–plus disease or plus disease) and 0.98 (0.01) for the diagnosis of plus disease (vs normal or pre–plus disease). For diagnosis of plus disease in an independent test set of 100 retinal images, the algorithm achieved a sensitivity of 93% with 94% specificity. For detection of pre–plus disease or worse, the sensitivity and specificity were 100% and 94%, respectively. On the same test set, the algorithm achieved a quadratic-weighted κ coefficient of 0.92 compared with the RSD, outperforming 6 of 8 ROP experts. CONCLUSIONS AND RELEVANCE: This fully automated algorithm diagnosed plus disease in ROP with comparable or better accuracy than human experts. This has potential applications in disease detection, monitoring, and prognosis in infants at risk of ROP.
Summary
Background
Patients with non‐alcoholic steatohepatitis (NASH) have increased intestinal permeability and small intestine bacterial overgrowth.
Aims
To test the hypothesis that endotoxemia is ...associated with non‐alcoholic fatty liver disease (NAFLD) in the general population, and to study dietary factors associated with endotoxemia.
Methods
Nine hundred and twenty adults were randomly selected from the government's census database and underwent proton‐magnetic resonance spectroscopy to assess hepatic steatosis. Endotoxemia was assessed using the limulus amebocyte lysate, lipopolysaccharide‐binding protein (LBP) and EndoCab immunoglobulin G (IgG) assays.
Results
Two hundred and sixty‐three (29%) subjects had NAFLD. Subjects with NAFLD had slightly higher LBP (P < 0.001) and EndoCab IgG (P = 0.013) levels. EndoCab IgG remained an independent factor associated with intrahepatic triglycerides after adjusting for other metabolic factors. Among 565 subjects without NAFLD at baseline who had repeated assessment at a median interval of 47 months, 78 (13.8%) developed incident NAFLD and they also had higher LBP (P = 0.016). Moreover, LBP was associated with insulin resistance and dyslipidaemia, and modestly increased with the cytokeratin‐18 fragment level but not liver stiffness measurement by transient elastography. Although total energy consumption and individual macronutrients were not associated with endotoxemia, current drinkers (mostly <140 g/week) had lower endotoxin, EndoCab IgG and fetuin‐A levels than nondrinkers.
Conclusions
Endotoxin markers are associated with NAFLD in the general population, but do not have a major effect on NASH and fibrosis. People with modest alcohol consumption have lower serum endotoxin. This may partly explain the lower risk of NAFLD and NASH in modest drinkers in previous observational studies.
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.
Review of evidence-based literature, along with expert consensus opinion.
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.
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.
Consensus statement.
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.
These principles may improve the quality and standardization of ROP care worldwide and may provide a foundation to improve research and clinical care.
The simultaneous maturation of multiple digital and telecommunications technologies in 2020 has created an unprecedented opportunity for ophthalmology to adapt to new models of care using tele-health ...supported by digital innovations. These digital innovations include artificial intelligence (AI), 5th generation (5G) telecommunication networks and the Internet of Things (IoT), creating an inter-dependent ecosystem offering opportunities to develop new models of eye care addressing the challenges of COVID-19 and beyond. Ophthalmology has thrived in some of these areas partly due to its many image-based investigations. Tele-health and AI provide synchronous solutions to challenges facing ophthalmologists and healthcare providers worldwide. This article reviews how countries across the world have utilised these digital innovations to tackle diabetic retinopathy, retinopathy of prematurity, age-related macular degeneration, glaucoma, refractive error correction, cataract and other anterior segment disorders. The review summarises the digital strategies that countries are developing and discusses technologies that may increasingly enter the clinical workflow and processes of ophthalmologists. Furthermore as countries around the world have initiated a series of escalating containment and mitigation measures during the COVID-19 pandemic, the delivery of eye care services globally has been significantly impacted. As ophthalmic services adapt and form a “new normal”, the rapid adoption of some of telehealth and digital innovation during the pandemic is also discussed. Finally, challenges for validation and clinical implementation are considered, as well as recommendations on future directions.
Abstract Background The importance of quality-of-life (QoL) research has been recognised over the past two decades in patients with head and neck (H&N) cancer. The aims of this systematic review are ...to evaluate the QoL status of H&N cancer survivors one year after treatment and to identify the determinants affecting their QoL. Methods Pubmed, Medline, Scopus, Sciencedirect and CINAHL (2000–2011) were searched for relevant studies, and two of the present authors assessed their methodological quality. The characteristics and main findings of the studies were extracted and reported. Results Thirty-seven studies met the inclusion criteria, and the methodological quality of the majority was moderate to high. While patients of the group in question recover their global QoL by 12 months after treatment, a number of outstanding issues persist – deterioration in physical functioning, fatigue, xerostomia and sticky saliva. Age, cancer site, stage of disease, social support, smoking, feeding tube placement and alcohol consumption are the significant determinants of QoL at 12 months, while gender has little or no influence. Conclusions Regular assessments should be carried out to monitor physical functioning, degree of fatigue, xerostomia and sticky saliva. Further research is required to develop appropriate and effective interventions to deal with these issues, and thus to promote the patients’ QoL.
Experience-dependent myelination is hypothesized to shape neural circuit function and subsequent behavioral output. Using a contextual fear memory task in mice, we demonstrate that fear learning ...induces oligodendrocyte precursor cells to proliferate and differentiate into myelinating oligodendrocytes in the medial prefrontal cortex. Transgenic animals that cannot form new myelin exhibit deficient remote, but not recent, fear memory recall. Recording population calcium dynamics by fiber photometry, we observe that the neuronal response to conditioned context cues evolves over time in the medial prefrontal cortex, but not in animals that cannot form new myelin. Finally, we demonstrate that pharmacological induction of new myelin formation with clemastine fumarate improves remote memory recall and promotes fear generalization. Thus, bidirectional manipulation of myelin plasticity functionally affects behavior and neurophysiology, which suggests that neural activity during fear learning instructs the formation of new myelin, which in turn supports the consolidation and/or retrieval of remote fear memories.
Childhood blindness from retinopathy of prematurity (ROP) is increasing as a result of improvements in neonatal care worldwide. We evaluate the effectiveness of artificial intelligence (AI)-based ...screening in an Indian ROP telemedicine program and whether differences in ROP severity between neonatal care units (NCUs) identified by using AI are related to differences in oxygen-titrating capability.
External validation study of an existing AI-based quantitative severity scale for ROP on a data set of images from the Retinopathy of Prematurity Eradication Save Our Sight ROP telemedicine program in India. All images were assigned an ROP severity score (1-9) by using the Imaging and Informatics in Retinopathy of Prematurity Deep Learning system. We calculated the area under the receiver operating characteristic curve and sensitivity and specificity for treatment-requiring retinopathy of prematurity. Using multivariable linear regression, we evaluated the mean and median ROP severity in each NCU as a function of mean birth weight, gestational age, and the presence of oxygen blenders and pulse oxygenation monitors.
The area under the receiver operating characteristic curve for detection of treatment-requiring retinopathy of prematurity was 0.98, with 100% sensitivity and 78% specificity. We found higher median (interquartile range) ROP severity in NCUs without oxygen blenders and pulse oxygenation monitors, most apparent in bigger infants (>1500 g and 31 weeks' gestation: 2.7 2.5-3.0 vs 3.1 2.4-3.8;
= .007, with adjustment for birth weight and gestational age).
Integration of AI into ROP screening programs may lead to improved access to care for secondary prevention of ROP and may facilitate assessment of disease epidemiology and NCU resources.
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