A Dopamine Detection Sensor Based on Au-Decorated NiS2 and Its Medical Application.

This article reports a simple hydrothermal method for synthesizing nickel disulfide (NiS2) on the surface of fluorine-doped tin oxide (FTO) glass, followed by the deposition of 5 nm Au nanoparticles on the electrode surface by physical vapor deposition. This process ensures the uniform distribution of Au nanoparticles on the NiS2 surface to enhance its conductivity. Finally, an Au@NiS2-FTO electrochemical biosensor is obtained for the detection of dopamine (DA). The composite material is characterized using transmission electron microscopy (TEM), UV-Vis spectroscopy, X-ray diffraction, and X-ray photoelectron spectroscopy. The electrochemical properties of the sensor are investigated using cyclic voltammetry (CV), differential pulse voltammetry (DPV), and time current curves in a 0.1 M PBS solution (pH = 7.3). In the detection of DA, Au@NiS2-FTO exhibits a wide linear detection range (0.1~1000 µM), low detection limit (1 nM), and fast response time (0.1 s). After the addition of interfering substances, such as glucose, L-ascorbic acid, uric acid, CaCl2, NaCl, and KCl, the electrode potential remains relatively unchanged, demonstrating its strong anti-interference capability. It also demonstrates strong sensitivity and reproducibility. The obtained Au@NiS2-FTO provides a simple and easy-to-operate example for constructing nanometer catalysts with enzyme-like properties. These results provide a promising method utilizing Au coating to enhance the conductivity of transition metal sulfides.

A molecularly informed field-theoretic study of the complexation of polycation PDADMA with mixed micelles of sodium dodecyl sulfate and ethoxylated surfactants.

The self-assembly and phase separation of mixtures of polyelectrolytes and surfactants are important to a range of applications, from formulating personal care products to drug encapsulation. In contrast to systems of oppositely charged polyelectrolytes, in polyelectrolyte-surfactant systems the surfactants micellize into structures that are highly responsive to solution conditions. In this work, we examine how the morphology of micelles and degree of polyelectrolyte adsorption dynamically change upon varying the mixing ratio of charged and neutral surfactants. Specifically, we consider a solution of the cationic polyelectrolyte polydiallyldimethylammonium, anionic surfactant sodium dodecyl sulfate, neutral ethoxylated surfactants (C[Formula: see text]EO[Formula: see text]), sodium chloride salt, and water. To capture the chemical specificity of these species, we leverage recent developments in constructing molecularly informed field theories via coarse-graining from all-atom simulations. Our results show how changing the surfactant mixing ratios and the identity of the nonionic surfactant modulates micelle size and surface charge, and as a result dictates the degree of polyelectrolyte adsorption. These results are in semi-quantitative agreement with experimental observations on the same system.

Molecularly informed field theory for estimating critical micelle concentrations of intrinsically disordered protein surfactants.

The critical micelle concentration (CMC) is a crucial parameter in understanding the self-assembly behavior of surfactants. In this study, we combine simulation and experiment to demonstrate the predictive capability of molecularly informed field theories in estimating the CMC of biologically based protein surfactants. Our simulation approach combines the relative entropy coarse-graining of small-scale atomistic simulations with large-scale field-theoretic simulations, allowing us to efficiently compute the free energy of micelle formation necessary for the CMC calculation while preserving chemistry-specific information about the underlying surfactant building blocks. We apply this methodology to a unique intrinsically disordered protein platform capable of a wide variety of tailored sequences that enable tunable micelle self-assembly. The computational predictions of the CMC closely match experimental measurements, demonstrating the potential of molecularly informed field theories as a valuable tool to investigate self-assembly in bio-based macromolecules systematically.

Detection of Breast Cancer-Specific Extracellular Vesicles with Fiber-Optic SPR Biosensor.

Extracellular vesicles (EVs) have attracted great attention as potential biomarkers for cancer diagnostics. Although several technologies have been developed for EV detection, many of them are still not applicable to clinical settings as they rely on complex EV isolation processes, while lacking sensitivity, specificity or standardization. To solve this problem, we have developed a sensitive breast cancer-specific EV detection bioassay directly in blood plasma using a fiber-optic surface plasmon resonance (FO-SPR) biosensor, previously calibrated with recombinant EVs. First, we established a sandwich bioassay to detect SK-BR-3 EVs by functionalizing the FO-SPR probes with anti-HER2 antibodies. A calibration curve was built using an anti-HER2/Banti-CD9 combination, resulting in an LOD of 2.1 × 107 particles/mL in buffer and 7 × 108 particles/mL in blood plasma. Next, we investigated the potential of the bioassay to detect MCF7 EVs in blood plasma using an anti-EpCAM/Banti-mix combination, obtaining an LOD of 1.1 × 10 8 particles/mL. Finally, the specificity of the bioassay was proven by the absence of signal when testing plasma samples from 10 healthy people unknown to be diagnosed with breast cancer. The remarkable sensitivity and specificity of the developed sandwich bioassay together with the advantages of the standardized FO-SPR biosensor highlight outstanding potential for the future of EV analysis.

Learning composition-transferable coarse-grained models: Designing external potential ensembles to maximize thermodynamic information.

Achieving thermodynamic faithfulness and transferability across state points is an outstanding challenge in the bottom-up coarse graining of molecular models, with many efforts focusing on augmenting the form of coarse-grained interaction potentials to improve transferability. Here, we revisit the critical role of the simulation ensemble and the possibility that even simple models can be made more predictive through a smarter choice of ensemble. We highlight the efficacy of coarse graining from ensembles where variables conjugate to the thermodynamic quantities of interest are forced to respond to applied perturbations. For example, to learn activity coefficients, it is natural to coarse grain from ensembles with spatially varying external potentials applied to one species to force local composition variations and fluctuations. We apply this strategy to coarse grain both an atomistic model of water and methanol and a binary mixture of spheres interacting via Gaussian repulsions and demonstrate near-quantitative capture of activity coefficients across the whole composition range. Furthermore, the approach is able to do so without explicitly measuring and targeting activity coefficients during the coarse graining process; activity coefficients are only computed after-the-fact to assess accuracy. We hypothesize that ensembles with applied thermodynamic potentials are more "thermodynamically informative." We quantify this notion of informativeness using the Fisher information metric, which enables the systematic design of optimal bias potentials that promote the learning of thermodynamically faithful models. The Fisher information is related to variances of structural variables, highlighting the physical basis underlying the Fisher information's utility in improving coarse-grained models.

Mechanisms of spontaneous chain formation and subsequent microstructural evolution in shear-driven strongly confined drop monolayers.

It was experimentally demonstrated by Migler and his collaborators [Phys. Rev. Lett., 2001, 86, 1023; Langmuir, 2003, 19, 8667] that a strongly confined drop monolayer sheared between two parallel plates can spontaneously develop a flow-oriented drop-chain morphology. Here we show that the formation of the chain-like microstructure is driven by far-field Hele-Shaw quadrupolar interactions between drops, and that drop spacing within chains is controlled by the effective drop repulsion associated with the existence of confinement-induced reversing streamlines, i.e., the swapping trajectory effect. Using direct numerical simulations and an accurate quasi-2D model that incorporates quadrupolar and swapping-trajectory contributions, we analyze microstructural evolution in a monodisperse drop monolayer. Consistent with experimental observations, we find that drop spacing within individual chains is usually uniform. Further analysis shows that at low area fractions all chains have the same spacing, but at higher area fractions there is a large spacing variation from chain to chain. These findings are explained in terms of uncompressed and compressed chains. At low area fractions most chains are uncompressed (spacing equals lst, which is the stable separation of an isolated pair). At higher area fractions compressed chains (with tighter spacing) are formed in a process of chain zipping along y-shaped structural defects. We also discuss the relevance of our findings to other shear-driven systems, such as suspensions of spheres in non-Newtonian fluids.

Electrostatic correlations and the polyelectrolyte self energy.

We address the effects of chain connectivity on electrostaticfluctuations in polyelectrolyte solutions using a field-theoretic, renormalizedGaussian fluctuation (RGF) theory. As in simple electrolyte solutions [Z.-G. Wang,Phys. Rev. E 81, 021501 (2010)], the RGF provides a unified theory forelectrostatic fluctuations, accounting for both dielectric and charge correlationeffects in terms of the self-energy. Unlike simple ions, the polyelectrolyte self energydepends intimately on the chain conformation, and our theory naturally provides aself-consistent determination of the response of intramolecular chain structure topolyelectrolyte and salt concentrations. The effects of the chain-conformation on theself-energy and thermodynamics are especially pronounced for flexiblepolyelectrolytes at low polymer and salt concentrations, where application of thewrong chain structure can lead to a drastic misestimation of the electrostaticcorrelations. By capturing the expected scaling behavior of chain size from dilute tosemi-dilute regimes, our theory provides improved estimates of the self energy at lowpolymer concentrations and correctly predicts the eventual N-independenceof the critical temperature and concentration of salt-free solutions of flexiblepolyelectrolytes. We show that the self energy can be interpreted in terms of aninfinite-dilution energy µm,0el and a finite concentrationcorrelation correction µcorr which tends to cancel out the formerwith increasing concentration.

Transit Time Theory for a Droplet Passing through a Slit in Pressure-Driven Low Reynolds Number Flows.

Soft objects squeezing through small apertures are crucial for many in vivo and in vitro processes. Red blood cell transit time through splenic inter-endothelial slits (IESs) plays a crucial role in blood filtration and disease progression, while droplet velocity through constrictions in microfluidic devices is important for effective manipulation and separation processes. As these transit phenomena are not well understood, we sought to establish analytical and numerical solutions of viscous droplet transit through a rectangular slit. This study extends from our former theory of a circular pore because a rectangular slit is more realistic in many physiological and engineering applications. Here, we derived the ordinary differential equations (ODEs) of a droplet passing through a slit by combining planar Poiseuille flow, the Young-Laplace equations, and modifying them to consider the lubrication layer between the droplet and the slit wall. Compared to the pore case, we used the Roscoe solution instead of the Sampson one to account for the flow entering and exiting a rectangular slit. When the surface tension and lubrication layer were negligible, we derived the closed-form solutions of transit time. When the surface tension and lubrication layer were finite, the ODEs were solved numerically to study the impact of various parameters on the transit time. With our solutions, we identified the impact of prescribed pressure drop, slit dimensions, and droplet parameters such as surface tension, viscosity, and volume on transit time. In addition, we also considered the effect of pressure drop and surface tension near critical values. For this study, critical surface tension for a given pressure drop describes the threshold droplet surface tension that prevents transit, and critical pressure for a given surface tension describes the threshold pressure drop that prevents transit. Our solutions demonstrate that there is a linear relationship between pressure and the reciprocal of the transit time (referred to as inverse transit time), as well as a linear relationship between viscosity and transit time. Additionally, when the droplet size increases with respect to the slit dimensions, there is a corresponding increase in transit time. Most notably, we emphasize the initial antagonistic effect of surface tension which resists droplet passage but at the same time decreases the lubrication layer, thus facilitating passage. Our results provide quantitative calculations for understanding cells passing through slit-like constrictions and designing droplet microfluidic experiments.

Predicting surfactant phase behavior with a molecularly informed field theory.

HYPOTHESIS: The computational study of surfactants and self-assembly is challenging because 1) models need to reflect chemistry-specific interactions, and 2) self-assembled structures are difficult to equilibrate with conventional molecular dynamics. We propose to overcome these challenges with a multiscale simulation approach where relative entropy minimization transfers chemically-detailed information from all-atom (AA) simulations to coarse-grained (CG) models that can be simulated using field-theoretic methods. Field-theoretic simulations are not limited by intrinsic physical time scales like diffusion and allow for rigorous equilibration via free energy minimization. This approach should enable the study of properties that are difficult to obtain by particle-based simulations. SIMULATION WORK: We apply this workflow to sodium dodecylsulfate. To ensure chemical fidelity we present an AA force field calibrated against interfacial tension experiments. We generate CG models from AA simulation trajectories and show that particle-based and field-theoretic simulations of the CG model reproduce AA simulations and experimental measurements. FINDINGS: The workflow captures the complex balance of interactions in a multicomponent system ultimately described by an atomistic model. The resulting CG models can study complex 3D phases like double or alternating gyroids, and reproduce salt effects on properties like aggregation number and shape transitions.

Novel App knock-in mouse model shows key features of amyloid pathology and reveals profound metabolic dysregulation of microglia.

BACKGROUND: Genetic mutations underlying familial Alzheimer's disease (AD) were identified decades ago, but the field is still in search of transformative therapies for patients. While mouse models based on overexpression of mutated transgenes have yielded key insights in mechanisms of disease, those models are subject to artifacts, including random genetic integration of the transgene, ectopic expression and non-physiological protein levels. The genetic engineering of novel mouse models using knock-in approaches addresses some of those limitations. With mounting evidence of the role played by microglia in AD, high-dimensional approaches to phenotype microglia in those models are critical to refine our understanding of the immune response in the brain. METHODS: We engineered a novel App knock-in mouse model (AppSAA) using homologous recombination to introduce three disease-causing coding mutations (Swedish, Arctic and Austrian) to the mouse App gene. Amyloid-ß pathology, neurodegeneration, glial responses, brain metabolism and behavioral phenotypes were characterized in heterozygous and homozygous AppSAA mice at different ages in brain and/ or biofluids. Wild type littermate mice were used as experimental controls. We used in situ imaging technologies to define the whole-brain distribution of amyloid plaques and compare it to other AD mouse models and human brain pathology. To further explore the microglial response to AD relevant pathology, we isolated microglia with fibrillar Aß content from the brain and performed transcriptomics and metabolomics analyses and in vivo brain imaging to measure energy metabolism and microglial response. Finally, we also characterized the mice in various behavioral assays. RESULTS: Leveraging multi-omics approaches, we discovered profound alteration of diverse lipids and metabolites as well as an exacerbated disease-associated transcriptomic response in microglia with high intracellular Aß content. The AppSAA knock-in mouse model recapitulates key pathological features of AD such as a progressive accumulation of parenchymal amyloid plaques and vascular amyloid deposits, altered astroglial and microglial responses and elevation of CSF markers of neurodegeneration. Those observations were associated with increased TSPO and FDG-PET brain signals and a hyperactivity phenotype as the animals aged. DISCUSSION: Our findings demonstrate that fibrillar Aß in microglia is associated with lipid dyshomeostasis consistent with lysosomal dysfunction and foam cell phenotypes as well as profound immuno-metabolic perturbations, opening new avenues to further investigate metabolic pathways at play in microglia responding to AD-relevant pathogenesis. The in-depth characterization of pathological hallmarks of AD in this novel and open-access mouse model should serve as a resource for the scientific community to investigate disease-relevant biology.

Transcriptomic expression of AMPA receptor subunits and their auxiliary proteins in the human brain.

Receptors to glutamate of the AMPA type (AMPARs) serve as the major gates of excitation in the human brain, where they participate in fundamental processes underlying perception, cognition and movement. Due to their central role in brain function, dysregulation of these receptors has been implicated in neuropathological states associated with a large variety of diseases that manifest with abnormal behaviors. The participation of functional abnormalities of AMPARs in brain disorders is strongly supported by genomic, transcriptomic and proteomic studies. Most of these studies have focused on the expression and function of the subunits that make up the channel and define AMPARs (GRIA1-GRIA4), as well of some accessory proteins. However, it is increasingly evident that native AMPARs are composed of a complex array of accessory proteins that regulate their trafficking, localization, kinetics and pharmacology, and a better understanding of the diversity and regional expression of these accessory proteins is largely needed. In this review we will provide an update on the state of current knowledge of AMPA receptors subunits in the context of their accessory proteins at the transcriptome level. We also summarize the regional expression in the human brain and its correlation with the channel forming subunits. Finally, we discuss some of the current limitations of transcriptomic analysis and propose potential ways to overcome them.

Molecularly Informed Field Theories from Bottom-up Coarse-Graining.

Polymer formulations possessing mesostructures or phase coexistence are challenging to simulate using atomistic particle-explicit approaches due to the disparate time and length scales, while the predictive capability of field-based simulations is hampered by the need to specify interactions at a coarser scale (e.g., χ-parameters). To overcome the weaknesses of both, we introduce a bottom-up coarse-graining methodology that leverages all-atom molecular dynamics to molecularly inform coarser field-theoretic models. Specifically, we use relative-entropy coarse-graining to parametrize particle models that are directly and analytically transformable into statistical field theories. We demonstrate the predictive capability of this approach by reproducing experimental aqueous poly(ethylene oxide) (PEO) cloud-point curves with no parameters fit to experimental data. This synergistic approach to multiscale polymer simulations opens the door to de novo exploration of phase behavior across a wide variety of polymer solutions and melt formulations.

Evolving drug regulatory landscape in China: A clinical pharmacology perspective.

In order to encourage innovative medicine to address Chinese unmet medical needs, China has changed its drug regulatory landscape to speed up access to new medicines. In order to understand the fast-changing landscape and to enable planning of more global drug development programs and study designs in China, we reviewed 15 published clinical pharmacology-related guidances by the National Medical Products Administration (NMPA), and compared them with reference guidances from the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), or the International Conference on Harmonization (ICH), to understand the similarities and differences, especially any China-specific requirements, such as ethnic sensitivity analysis. Overall, by reviewing these clinical pharmacology-related NMPA guidances, it is clear that NMPA guidances are very similar to FDA, EMA, and ICH guidances. There are no relevant differences in the major principles, but some differences in structure, contents, and focus were noted. The NMPA is adapting flexibility statements into newly published guidances. Ethnic sensitivity analysis needs to be implemented early in drug development plans. The NMPA encourages sponsors to conduct early clinical trials in China or include China early in multiregional clinical trials, and to obtain safety, efficacy, and pharmacokinetic data for ethnic sensitivity analysis. Depending on the stage of development, ethnic sensitivity analysis can be conducted using in vitro or literature data, other Asian clinical data, or Chinese clinical data.

Physician's experience on managing asthma in adolescents: results of the International AMADO (Asthma Management in ADOlescents) survey.

BACKGROUND: Worldwide prevalence of asthma seems to be increasing in adolescents, but limited data is available regarding the management of asthma in this age group. OBJECTIVE: Therefore, we conducted an international survey focused on physicians who manage asthma in order to understand how Asthma Management in ADOlescents (AMADO) is currently performed. METHODS: The AMADO survey is a web-based global survey of physician's attitudes towards the management of asthma in adolescents, circulated for 17 weeks. The survey had an anonymous and voluntary standard. The questionnaire consisted in 27 questions covering the training background of respondents, difficulties in diagnosis, and in management of asthma in adolescents. RESULTS: Two hundred forty-four responses were received from 46 countries, from all continents. Most (65%) of participants indicated allergy as being their main specialty. The majority of participants (62%) had more than 5 years of clinical practice, but 62% have no formal training in management of adolescents with asthma. Most of participants (96%) indicated having at least one case of asthma in adolescents per month. 60% of respondents mentioned that the asthmatic adolescents only had the consultation due to the family imposition. All respondents mentioned having difficulties in the management of asthma in adolescents due to patient poor adherence. Overall, 44% of participants have no specific health care resources for adolescents in their departments. Main suggestions from the participants were: optimization of time and personalized communication to these cohort, and standardization of multidisciplinary actions to improve adherence to asthma control treatment. CONCLUSION: Management of asthma in adolescents is still a challenge in clinical practice. The results from this survey helped us to identify the key issues to improve clinical outcomes in the future. This survey is the first step of the international AMADO initiative, which intends to optimize diagnosis and control of asthma and prevent avoidable deaths.

Regional transcriptome analysis of AMPA and GABAA receptor subunit expression generates E/I signatures of the human brain.

Theoretical and experimental work has demonstrated that excitatory (E) and inhibitory (I) currents within cortical circuits stabilize to a balanced state. This E/I balance, observed from single neuron to network levels, has a fundamental role in proper brain function and its impairment has been linked to numerous brain disorders. Over recent years, large amount of microarray and RNA-Sequencing datasets have been collected, however few studies have made use of these resources for exploring the balance of global gene expression levels between excitatory AMPA receptors (AMPARs) and inhibitory GABAA receptors. Here, we analyzed the relative relationships between these receptors to generate a basic transcriptional marker of E/I ratio. Using publicly available data from the Allen Brain Institute, we generated whole brain and regional signatures of AMPAR subunit gene expression in healthy human brains as well as the transcriptional E/I (tE/I) ratio. Then we refined the tE/I ratio to cell-type signatures in the mouse brain using data from the Gene Expression Omnibus. Lastly, we applied our workflow to developmental data from the Allen Brain Institute and revealed spatially and temporally controlled changes in the tE/I ratio during the embryonic and early postnatal stages that ultimately lead to the tE/I balance in adults.

Isolated Pancreatic Tail Injury in Paediatrics; A Case Report and Literature Review.

Pancreatic injury in paediatrics is a rare condition and can be difficult to diagnose. The diagnostic challenge is due to its symptom of vague abdominal pain which usually results in late presentation. Elevated biochemical markers such as amylase and lipase can aid in the evaluation of pancreatic injury, however, it is not specific and is only evident after several hours of trauma. Ultrasound is commonly used as a primary modality to evaluate abdominal organ injuries, but its role in detecting pancreatic injury is limited due to low sensitivity. High index of suspicion is needed to avoid undiagnosed pancreatic injury which could be lethal to children. We herein report a case of delayed presentation of isolated pancreatic tail injury in a child who was sufficiently diagnosed with ultrasound and treated conservatively. Proper initial assessment and diagnosis will allow appropriate management of pancreatic injury. Conservative management should include serial imaging to look at the evolution of pancreatic injury and detect complications such as pseudocyst or abscess formation.

Human brain transcriptome analysis finds region- and subject-specific expression signatures of GABAAR subunits.

Altered expression of GABA receptors (GABAARs) has been implicated in neurological and psychiatric disorders, but limited information about region-specific GABAAR subunit expression in healthy human brains, heteromeric assembly of major isoforms, and their collective organization across healthy individuals, are major roadblocks to understanding their role in non-physiological states. Here, by using microarray and RNA-Seq datasets-from single cell nuclei to global brain expression-from the Allen Institute, we find that transcriptional expression of GABAAR subunits is anatomically organized according to their neurodevelopmental origin. The data show a combination of complementary and mutually-exclusive expression patterns that delineate major isoforms, and which is highly stereotypical across brains from control donors. We summarize the region-specific signature of GABAR subunits per subject and its variability in a control population sample that can be used as a reference for remodeling changes during homeostatic rearrangements of GABAAR subunits after physiological, pharmacological or pathological challenges.

Accuracy of Detection and Grading of Diabetic Retinopathy and Diabetic Macular Edema Using Teleretinal Screening.

PURPOSE: To determine the accuracy of a county teleretinal screening program of detecting referable diabetic retinopathy (DR) and treatable diabetic macular edema (DME), as well as to evaluate patient compliance with clinic follow-up after referral from teleretinal screening. DESIGN: Retrospective observational study. PARTICIPANTS: Patients in the Harris Health System (HHS, Houston, TX) older than 18 years of age who underwent teleretinal screening between July 2014 and July 2016. METHODS: Teleretinal imaging (TRI) consisting of single-field 45-degree nonmydriatic color fundus photography with referral thresholds of severe nonproliferative DR, proliferative DR, and significant DME. Teleretinal imaging results for all referred subjects were obtained and cross-referenced with dilated fundus examination findings with regard to DR severity and the presence of DME. Follow-up status was also noted. Subjects underwent OCT if deemed necessary by the examining specialist. Agreement between TRI and dilated fundus examination (DFE) findings was determined by calculating the Cohen κ coefficient. MAIN OUTCOME MEASURES: The primary outcome measure is agreement between TRI results and DFE findings with regard to DR severity and the presence of DME. The secondary outcome measure is compliance with follow-up. RESULTS: Of 1767 patients who were screened and referred for clinical examination, 935 (52.9%) attended their clinic appointment. Overall agreement between DFE and TRI was moderate (weighted κ 0.45) in terms of DR severity. There was agreement within one DR severity level in 86.2% of patients. The positive predictive value for detecting referable disease was 71.3%. Of patients referred for DME, 30.4% were deemed to have treatable DME. CONCLUSIONS: The HHS teleretinal screening program demonstrates a high level of accuracy in the detection and classification of referable DR, but a lesser degree of accuracy in the detection of treatable DME. Only slightly more than half of participants were compliant with follow-up after a TRI referral. This large-scale study provides insight into the utility of teleretinal screening in a county health care system.

Clinical Pearl: The "Rule of 8".

Preschool-aged children typically perform worse than 20/20 on visual acuity testing in the absence of ocular or visual pathway abnormalities due to non-ocular issues, including concentration, cooperation, and/or confidence. As a result, vision screening for this age group can be a challenge. The "Rule of 8" is an easy-to-remember, highly effective mnemonic that clinicians can use to help differentiate children who are performing visual acuity testing at age-appropriate levels from those who may need further evaluation. [J Pediatric Ophthalmol Strabismus. 2017;54:e75-e76.].