The refraction testing app was developed with support in part from NIH grant EY034345 and the Harvard Catalyst award (National Center for Advancing Translational Sciences, NIH Award UL1 TR002541). The content is solely the responsibility of the authors and does not necessarily represent the official views of Harvard Catalyst, Harvard University and its affiliated academic healthcare centers, or the NIH.

The study was conducted in accordance with the tenets of the Declaration of Helsinki at Mass Eye and Ear Infirmary (Boston, MA). Informed consent was obtained from all the participants. The study was approved by the local institutional review boards of Mass Eye and Ear (Boston, MA). Subject inclusion criteria were diagnosis of myopia and no other eye conditions, such as cataracts and retinal disease, according to an optometrist.
1. Measuring spherical equivalent
<ol>
	<li>Launch the app and tap the Refraction button on the home page (Figure 1). Place the phone at least 2 m away from the patient.</li>
	<li>Select button E for Tumbling E stimuli (Figure 2). Select the Eye to be measured (Left or Right) and ask the patient to cover the other eye.</li>
	<li>Hold the phone with the screen facing the patient and tap the Start button. Ask the patient if he/she can tell the orientation of all the letters displayed on the phone screen.</li>
	<li>If the patient cannot tell the orientation of the letters, gradually move the phone towards the patient.</li>
	<li>While gradually approaching the patient, keep checking whether they can identify the letters. Stop as soon as the patient can tell the letter orientations.</li>
	<li>Tap the Verify button. The true letter orientations will be shown in text on the screen. Compare them with the patient&#39;s report. If all 3 answers match, tap the Correct button to conclude the testing. If the orientation of any of the letters is not correctly reported, tap the Wrong button to redo the testing.</li>
</ol>
2. Measuring astigmatism
<ol>
	<li>Launch the app and tap the Refraction button on the home page (Figure 1). Start from at least 2 m from the patient.</li>
	<li>Select Astigm 1 stimulus, which is a clock dial pattern (upper right inset in Figure 3). The stimulus consists of a series of line groups from one spot pointing toward different directions, like a clock. Each line group includes 3 parallel fine lines.</li>
	<li>Select the eye to be measured and ask the patient to cover the other eye. Hold the phone with the screen facing the patient and tap the Start button.</li>
	<li>Ask the patient whether the line group in any of the directions appears as 3 separate lines. If the patient cannot see separate lines in any of the directions, gradually move the phone towards the patient.</li>
	<li>Keep checking with the patient&#160;during the approaching movement. Stop as soon as the patient can see separated lines in at least one direction.</li>
	<li>Select Astigm 2 stimuli, which are two grating patches in red and green colors. These patches are wider on one end than the other (lower right inset in Figure 3).</li>
	<li>Rotate the phone around the axis perpendicular to the phone screen to a position where the grating is roughly the direction of the clearest line group of Astigm 1.</li>
	<li>Fine-tune the phone rotation to find the best spot where the patient&#160;can see the red and green grating patches equally clearly. Once the best spot is found, tap the Point 1 button to record the first far point.</li>
	<li>After Point 1 is recorded, the Astigm 2 stimulus will rotate 90&#730; automatically. From the first far point (Point 1 position), keep the phone orientation and move the phone closer until the patient can see the red and green grating patches equally clearly and tell the wider end.</li>
	<li>Tap the Point 2 button to record the second far point. With the two far points recorded, the app can calculate spherical refractive error and astigmatism and show the results on the screen.</li>
	<li>On the result message box, tap the Save button to save the result or, if needed, the Retake button to redo the measurement.</li>
</ol>
3. Measuring inter-pupillary distance (IPD)
<ol>
	<li>Launch the app and tap the IPD button on the home page (Figure 1). Place the phone approximately 40 cm away from the patient at eye level and ask the patient to look at the flashlight.</li>
	<li>Tap the round button on the right to take a picture of the patient&#39;s face. The app will then start processing the image.</li>
	<li>When two green crosshairs are plotted on the screen (Figure 4), examine if their locations are aligned with the center of the eyes. If yes, tap the Save button.</li>
	<li>If either of the cross hairs is apparently not at the center of the eye, reject the measurement by tapping the Retake button to go back to step 3.2 and redo the measurement.</li>
</ol>

Smartphone App for Measuring Refractive Errors and Inter-Pupillary Distance

<ol>
	<li>Steinmetz, J. D., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Causes+of+blindness+and+vision+impairment+in+2020+and+trends+over+30+years,+and+prevalence+of+avoidable+blindness+in+relation+to+VISION+2020:+the+Right+to+Sight:+an+analysis+for+the+Global+Burden+of+Disease+Study.">Causes of blindness and vision impairment in 2020 and trends over 30 years, and prevalence of avoidable blindness in relation to VISION 2020: the Right to Sight: an analysis for the Global Burden of Disease Study.</a> Lancet Glob Health. 9 (2), e144-e160 (2021).</li><li>Flaxman, S. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+causes+of+blindness+and+distance+vision+impairment+1990-2020:+a+systematic+review+and+meta-analysis.">Global causes of blindness and distance vision impairment 1990-2020: a systematic review and meta-analysis.</a> Lancet Glob Health. 5 (12), e1221-e1234 (2017).</li><li>Holden, B. A., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+vision+impairment+due+to+uncorrected+presbyopia.">Global vision impairment due to uncorrected presbyopia.</a> Arch Ophthalmol. 126 (12), 1731-1739 (2008).</li><li>Fricke, T. R., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Global+cost+of+correcting+vision+impairment+from+uncorrected+refractive+error.">Global cost of correcting vision impairment from uncorrected refractive error.</a> Bull World Health Organ. 90 (10), 728-738 (2012).</li><li>Bechange, S., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Strengths+and+weaknesses+of+eye+care+services+in+sub-Saharan+Africa:+a+meta-synthesis+of+eye+health+system+assessments.">Strengths and weaknesses of eye care services in sub-Saharan Africa: a meta-synthesis of eye health system assessments.</a> BMC Health Serv Res. 20 (1), 381 (2020).</li><li>Pundlik, S., Luo, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preliminary+evaluation+of+a+mobile+device+for+dark+adaptation+measurement.">Preliminary evaluation of a mobile device for dark adaptation measurement.</a> Transl Vis Sci Technol. 8 (1), 1-11 (2019).</li><li>Pundlik, S., Shivshanker, P., Nigalye, A., Luo, G., Husain, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Evaluation+of+a+mobile+app+for+dark+adaptation+measurement+in+individuals+with+age-related+macular+degeneration.">Evaluation of a mobile app for dark adaptation measurement in individuals with age-related macular degeneration.</a> Sci Rep. 13 (1), 22191 (2023).</li><li>Luo, G., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Preliminary+evaluation+of+a+smartphone+app+for+refractive+error+measurement.">Preliminary evaluation of a smartphone app for refractive error measurement.</a> Transl Vis Sci Technol. 11 (2), 40 (2022).</li><li>Wang, Z., Kempen, J., Luo, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+smartphones+to+enhance+vision+screening+in+rural+areas:+Pilot+study.">Using smartphones to enhance vision screening in rural areas: Pilot study.</a> JMIR Format Research. 8, e55270 (2024).</li><li>Pundlik, S., Tomasi, M., Liu, R., Houston, K., Luo, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Development+and+preliminary+evaluation+of+a+smartphone+app+for+measuring+eye+alignment.">Development and preliminary evaluation of a smartphone app for measuring eye alignment.</a> Transl Vis Sci Technol. 8 (1), 19 (2019).</li><li>Luo, G., Pundlik, S., Tomasi, M., Houston, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Using+an+automated+Hirschberg+test+App+to+evaluate+ocular+alignment.">Using an automated Hirschberg test App to evaluate ocular alignment.</a> J Vis Exp. (157), e60908 (2020).</li><li>Cheng, W., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=A+smartphone+ocular+alignment+measurement+app+in+school+screening+for+strabismus.">A smartphone ocular alignment measurement app in school screening for strabismus.</a> BMC Ophthalmol. 21 (1), 150 (2021).</li><li>Marusic, S., Luo, G., Raghuram, A. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Myopia+screening+smartphone+App:+Validity+in+assessing+refractive+error+in+a+pediatric+cohort.">Myopia screening smartphone App: Validity in assessing refractive error in a pediatric cohort.</a> Invest Ophthalmol Vis Sci. 63 (7), 1447-F0405 (2022).</li><li>Andersen, T., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Implementing+a+school+vision+screening+program+in+Botswana+using+smartphone+technology.">Implementing a school vision screening program in Botswana using smartphone technology.</a> Telemed e-Health. 26 (2), 255-258 (2020).</li><li>Manus, M., van der Linde, J., Kuper, H., Olinger, R., Swanepoel De, W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Community-based+hearing+and+vision+screening+in+schools+in+low-income+communities+using+mobile+health+technologies.">Community-based hearing and vision screening in schools in low-income communities using mobile health technologies.</a> Lang Speech Hear Serv Sch. 52 (2), 568-580 (2021).</li><li>Eksteen, S., Eikelboom, R. H., Kuper, H., Launer, S., Swanepoel, D. W. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Prevalence+and+characteristics+of+hearing+and+vision+loss+in+preschool+children+from+low+income+South+African+communities:+results+of+a+screening+program+of+10,390+children.">Prevalence and characteristics of hearing and vision loss in preschool children from low income South African communities: results of a screening program of 10,390 children.</a> BMC Pediat. 22 (1), 22 (2022).</li><li>Salmer&#243;n-Campillo, R. M., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+visual+acuity+and+spherical+refraction+with+smartphone+screens+emitting+blue+light.">Measuring visual acuity and spherical refraction with smartphone screens emitting blue light.</a> J Optomet. 17 (1), 100494 (2024).</li><li>Tousignant, B., Garceau, M. C., Bouffard-Saint-Pierre, N., Bellemare, M. M., Hanssens, J. -. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Comparing+the+Netra+smartphone+refractor+to+subjective+refraction.">Comparing the Netra smartphone refractor to subjective refraction.</a> Clin Exp Optomet. 103 (4), 501-506 (2020).</li><li>Luo, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Measuring+eye+refraction.">Measuring eye refraction.</a> US patent. , (2024).</li><li>Thibos, L. N., Wheeler, W., Horner, D. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Power+vectors:+An+application+of+Fourier+analysis+to+the+description+and+statistical+analysis+of+refractive+error.">Power vectors: An application of Fourier analysis to the description and statistical analysis of refractive error.</a> Optomet Vis Sci. 74 (6), 367-375 (1997).</li><li>Lundh, B. I., Derefeldt, G., Nyberg, S., Lennerstrand, G. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=Picture+simulation+of+contrast+sensitivity+in+organic+and+functional+amblyopia.">Picture simulation of contrast sensitivity in organic and functional amblyopia.</a> Acta Ophthalmol. 59 (5), 774-783 (1981).</li><li>D'Souza, H., Kun, A., Martinson, S., Bejarano, L., McCole, S. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed&cmd=Search&doptcmdl=Citation&defaultField=Title+Word&term=The+positive+predictive+value+of+photoscreening+devices+for+amblyogenic+conditions.">The positive predictive value of photoscreening devices for amblyogenic conditions.</a> J Am Assoc Pediat Ophthalmol Strabismus. 25 (6), 342.e341-342.e344 (2021).</li></ol>

Gang Luo has a patent related to refraction measurement. Gang Luo and Shrinivas Pundlik are two of the co-founders of EyeNexo LLC, which is a startup company developing smartphone apps for vision tests. No financial conflict of interest for the other authors.

Using the app, it is feasible for a person without professional optometry training to perform subjective refractive error tests. Its application in vision screening has been demonstrated in a recent eye screening study among school-aged students in a rural area9. Compared to the other mass vision screening methods that are solely based on visual acuity testing21, this app can provide measurement of refraction in terms of spherical and cylindrical error values typically used...

Uncorrected refractive error (URE) is a major cause of blindness and vision impairment in the world, affecting 861 to 116 million individuals2, although it is treatable with glasses. Studies have shown that the prevalence of URE in remote areas is primarily driven by the low number of eye care professionals and the lack of an adequate health infrastructure to dispense glasses3. For instance, the prevalence of vision impairment due to URE among adults above 50 years of age in Sub-Saharan Africa is 10 times higher than that in high-income countries1.
With the current advancements in the industry, the cost of eyeglasses has dropped to just a few US dollars. However, training eye care professionals is costly and time-consuming -- requiring years of training4. A recent study concluded that low per capita spending on health continues to limit meaningful integration of eye care within the broader healthcare systems, particularly in remote areas5. These grim realities point out the great need to make the diagnosis of URE accessible.
Thanks to their affordability, ubiquity, and validity, smartphone-based vision screening tools can play a pivotal role in vision screening efforts6,7,8,9,10,11,12,13. These innovative tools may impact eye health care by providing a cost-effective and convenient solution for screening, identifying, and addressing vision issues, especially in underserved communities.
One example of such technology is the Peek Acuity app, which has made significant strides in the field of mobile vision screening. This app has been deployed to screen tens of thousands of individuals in some studies in Africa14,15,16. By offering an efficient way to measure visual acuity, the Peek Acuity app has empowered healthcare providers to reach more people, making it a useful tool for addressing visual impairment. In addition to visual acuity, smartphone-based technologies for measuring refractive error have also been proposed and evaluated17,18. Salmer&#243;n-Campillo et al. used a smartphone screen to present blue visual stimuli in a Badal optometer for visual acuity and refraction measurement17. Tousignant et al. tested the Netra smartphone refractor, which consists of a handheld binocular viewer with a smartphone inserted in it18. Compared with general smartphone apps, dedicated components or attachments other than smartphones in these systems may limit the accessibility of the technology because users have to purchase specially made devices.
To address the accessibility issue of mass URE screening, we have developed a smartphone-based refraction app (Figure 1), which employs computer vision and psychophysical methods to measure refractive error19. The app measures subjective refraction by finding the far points for given stimuli (tumbling E for spherical equivalent and grating for astigmatism) in myopic patients. A key feature of the app is that no specially made attachment is needed. All the processing needed to perform a measurement is carried out on-device within the app, and no cloud computing is involved. Thus, refraction can be measured without needing to connect the app to the network. With minimum training, laypersons can use the app to measure the refraction of patients if their smartphones are compatible. The accuracy of the app has been evaluated previously against standard clinical testing methods8. While the app may not be directly used for prescribing glasses, it has the potential to be used in myopia screening. Recently, it was successfully used in a vision screening among school students in a rural area9. This paper presents the protocols for using the app to measure subjective refraction.

<table border="1" fo:keep-together.within-page="1" fo:keep-with-next.within-page="always">
	<tbody>
		<tr>
			<td>Smartphone</td>
			<td>Samsung</td>
			<td>Galaxy</td>
			<td>commercially available smartphone</td>
		</tr>
	</tbody>
</table>

subjective refraction test using a smartphone for vision screening

To improve access to vision care and to enable mass vision screening, a smartphone app has been developed to measure refractive errors. Without needing any external attachment, the app running on a standalone phone can be used by lay personnel to measure subjective refraction. Its validity has been pilot-tested in clinical settings and underserved communities. The app estimates the refractive error by measuring the distances of far points for discerning visual stimuli. Spherical equivalent refraction and astigmatism can be measured using Tumbling E letters and grating patterns, respectively. The purpose of this paper is to describe the measurement protocols for performing subjective refraction using the app. Experimental results with 34 subjects (30 eyes for spherical equivalent and 38 eyes for astigmatism assessment) are presented. Measurement with the app was compared with standard clinical methods. The average absolute error of spherical equivalent refraction was 0.63D, and the average absolute error of astigmatism measurement was 0.28D. In addition, 22 subjects were enrolled to evaluate inter-pupillary distance (IPD) measurement with the app. The average absolute error in IPD measurement with the app was 1.2 mm. The protocol for measuring IPD with the app is also described.

For this study, the interface of the refraction test is shown in Figure 2. Depending on the selected stimuli, the app performs a spherical equivalent or full refraction test. When Tumbling E is selected, the app measures the spherical equivalent (Figure 2). When grating stimuli Astigma 1 or 2 is selected, the app measures refractive error, including astigmatism (Figure 3).
To demonstrate the app&#39;s eff...

Subjective Refraction Test Using a Smartphone for Vision Screening

This paper presents the protocols and clinical validation data for using a smartphone app to subjectively measure refractive error.

To improve access to vision care and to enable mass vision screening, a smartphone app has been developed to measure refractive errors. Without needing ...

subjective-refraction-test-using-a-smartphone-for-vision-screening

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533 Views.  Schepens Eye Research Institute, Mass Eye & Ear. This paper presents the protocols and clinical validation data for using a smartphone app to subjectively measure refractive error.

Video: Subjective Refraction Test Using a Smartphone for Vision Screening

The Trier Social Stress Test Protocol for Inducing Psychological Stress

This article demonstrates a psychological stress protocol for use in a laboratory setting. Protocols that allow researchers to study the biological pathways of the stress response in health and disease are fundamental to the progress of research in stress and anxiety.1 Although numerous protocols exist for inducing stress response in the laboratory, many neglect to provide a naturalistic context or to incorporate aspects of social and psychological stress. Of psychological stress protocols, meta-analysis suggests that the Trier Social Stress Test (TSST) is the most useful and appropriate standardized protocol for studies of stress hormone reactivity.2 In the original description of the TSST, researchers sought to design and evaluate a procedure capable of inducing a reliable stress response in the majority of healthy volunteers.3 These researchers found elevations in heart rate, blood pressure and several endocrine stress markers in response to the TSST (a psychological stressor) compared to a saline injection (a physical stressor).3 Although the TSST has been modified to meet the needs of various research groups, it generally consists of a waiting period upon arrival, anticipatory speech preparation, speech performance, and verbal arithmetic performance periods, followed by one or more recovery periods. The TSST requires participants to prepare and deliver a speech, and verbally respond to a challenging arithmetic problem in the presence of a socially evaluative audience.3 Social evaluation and uncontrollability have been identified as key components of stress induction by the TSST.4 In use for over a decade, the goal of the TSST is to systematically induce a stress response in order to measure differences in reactivity, anxiety and activation of the hypothalamic-pituitary-adrenal (HPA) or sympathetic-adrenal-medullary (SAM) axis during the task.1 Researchers generally assess changes in self-reported anxiety, physiological measures (e.g. heart rate), and/or neuroendocrine indices (e.g. the stress hormone cortisol) in response to the TSST. Many investigators have adopted salivary sampling for stress markers such as cortisol and alpha-amylase (a marker of autonomic nervous system activation) as an alternative to blood sampling to reduce the confounding stress of blood-collection techniques. In addition to changes experienced by an individual completing the TSST, researchers can compare changes between different treatment groups (e.g. clinical versus healthy control samples) or the effectiveness of stress-reducing interventions.1

This article describes a protocol for inducing psychological stress in participants, which enables researchers to measure psychological, physiological and neuroendocrine responses to stress within single participants or between groups.

This article demonstrates a psychological stress protocol for use in a laboratory setting.  Protocols that allow researchers to study the biological ...

High Content Screening in Neurodegenerative Diseases

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be addressed as a matter of great urgency1-4. Multiple complementary 'omics' approaches have provided clues as to the genetic risk factors and pathogenic mechanisms underlying numerous neurodegenerative diseases, but most findings still require functional validation5. For example, a recent genome wide association study for Parkinson's Disease (PD), identified many new loci as risk factors for the disease, but the underlying causative variant(s) or pathogenic mechanism is not known6, 7. As each associated region can contain several genes, the functional evaluation of each of the genes on phenotypes associated with the disease, using traditional cell biology techniques would take too long. 
	There is also a need to understand the molecular networks that link genetic mutations to the phenotypes they cause. It is expected that disease phenotypes are the result of multiple interactions that have been disrupted. Reconstruction of these networks using traditional molecular methods would be time consuming. Moreover, network predictions from independent studies of individual components, the reductionism approach, will probably underestimate the network complexity8. This underestimation could, in part, explain the low success rate of drug approval due to undesirable or toxic side effects. Gaining a network perspective of disease related pathways using HT/HC cellular screening approaches, and identifying key nodes within these pathways, could lead to the identification of targets that are more suited for therapeutic intervention.
	High-throughput screening (HTS) is an ideal methodology to address these issues9-12. but traditional methods were one dimensional whole-well cell assays, that used simplistic readouts for complex biological processes. They were unable to simultaneously quantify the many phenotypes observed in neurodegenerative diseases such as axonal transport deficits or alterations in morphology properties13, 14. This approach could not be used to investigate the dynamic nature of cellular processes or pathogenic events that occur in a subset of cells. To quantify such features one has to move to multi-dimensional phenotypes termed high-content screening (HCS)4, 15-17. HCS is the cell-based quantification of several processes simultaneously, which provides a more detailed representation of the cellular response to various perturbations compared to HTS. 
	HCS has many advantages over HTS18, 19, but conducting a high-throughput (HT)-high-content (HC) screen in neuronal models is problematic due to high cost, environmental variation and human error. In order to detect cellular responses on a 'phenomics' scale using HC imaging one has to reduce variation and error, while increasing sensitivity and reproducibility. 
	Herein we describe a method to accurately and reliably conduct shRNA screens using automated cell culturing20 and HC imaging in neuronal cellular models. We describe how we have used this methodology to identify modulators for one particular protein, DJ1, which when mutated causes autosomal recessive parkinsonism21. 
	Combining the versatility of HC imaging with HT methods, it is possible to accurately quantify a plethora of phenotypes. This could subsequently be utilized to advance our understanding of the genome, the pathways involved in disease pathogenesis as well as identify potential therapeutic targets.

We describe a methodology combining automated cell culturing with high-content imaging to visualize and quantify multiple cellular processes and structures, in a high-throughput manner. Such methods can aid in the further functional annotation of genomes as well as identify disease gene networks and potential drug targets.

The functional annotation of genomes, construction of molecular networks and novel drug target identification, are important challenges that need to be ...

The &alpha;-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva

There is an urgent need for affordable CD4 enumeration to monitor HIV disease. CD4 enumeration is out of reach in resource-limited regions due to the time and temperature restrictions, technical sophistication, and cost of reagents, in particular monoclonal antibodies to measure CD4 on blood cells, the only currently acceptable method. A commonly used cost-saving and time-saving laboratory strategy is to calculate, rather than measure certain blood values. For example, LDL levels are calculated using the measured levels of total cholesterol, HDL, and triglycerides1. Thus, identification of cell-free correlates that directly regulate the number of CD4+ T cells could provide an accurate method for calculating CD4 counts due to the physiological relevance of the correlates.
The number of stem cells that enter blood and are destined to become circulating CD4+ T cells is determined by the chemokine CXCL12 and its receptor CXCR4 due to their influence on locomotion2. The process of stem cell locomotion into blood is additionally regulated by cell surface human leukocyte elastase (HLECS) and the HLECS-reactive active &alpha;1proteinase inhibitor (&alpha;1PI, &alpha;1antitrypsin, SerpinA1)3. In HIV-1 disease, &alpha;1PI is inactivated due to disease processes 4. In the early asymptomatic categories of HIV-1 disease, active &alpha;1PI was found to be below normal in 100% of untreated HIV-1 patients (median=12 &mu;M, and to achieve normal levels during the symptomatic categories4, 5. This pattern has been attributed to immune inactivation, not to insufficient synthesis, proteolytic inactivation, or oxygenation. We observed that in HIV-1 subjects with &gt;220 CD4 cells/&mu;l, CD4 counts were correlated with serum levels of active &alpha;1PI (r2=0.93, p&lt;0.0001, n=26) and inactive &alpha;1PI (r2=0.91, p&lt;0.0001, n=26) 5. Administration of &alpha;1PI to HIV-1 infected and uninfected subjects resulted in dramatic increases in CD4 counts suggesting &alpha;1PI participates in regulating the number of CD4+ T cells in blood 3.
With stimulation, whole saliva contains sufficient serous exudate (plasma containing proteinaceous material that passes through blood vessel walls into saliva) to allow measurement of active &alpha;1PI and the correlation of this measurement is evidence that it is an accurate method for calculating CD4 counts. Briefly, sialogogues such as chewing gum or citric acid stimulate the exudation of serum into whole mouth saliva. After stimulating serum exudation, the activity of serum &alpha;1PI in saliva is measured by its capacity to inhibit elastase activity. Porcine pancreatic elastase (PPE) is a readily available inexpensive source of elastase. PPE binds to &alpha;1PI forming a one-to-one complex that prevents PPE from cleaving its specific substrates, one of which is the colorimetric peptide, succinyl-L-Ala-L-Ala-L-Ala-p-nitroanilide (SA3NA). Incubating saliva with a saturating concentration of PPE for 10 min at room temperature allows the binding of PPE to all the active &alpha;1PI in saliva. The resulting inhibition of PPE by active &alpha;1PI can be measured by adding the PPE substrate SA3NA. (Figure 1). Although CD4 counts are measured in terms of blood volume (CD4 cells/&mu;l), the concentration of &alpha;1PI in saliva is related to the concentration of serum in saliva, not to volume of saliva since volume can vary considerably during the day and person to person6. However, virtually all the protein in saliva is due to serum content, and the protein content of saliva is measurable7. Thus, active &alpha;1PI in saliva is calculated as a ratio to saliva protein content and is termed the &alpha;1PI Index. Results presented herein demonstrate that the &alpha;1PI Index provides an accurate and precise physiologic method for calculating CD4 counts.

The &#945;-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva

A CD4 enumeration method, the &#x03B1;-test, is described which uses whole saliva to provide rapid and accurate CD4 counts. The &alpha;-test costs pennies and eliminates the need for technical training, costly reagents such as monoclonal antibodies, instrumentation, refrigeration, transport of samples, as well as collection and handling of blood.

There is an urgent need for affordable CD4 enumeration to monitor HIV disease. CD4 enumeration is out of reach in resource-limited regions due to the time ...

Screening for Melanoma Modifiers using a Zebrafish Autochthonous Tumor Model

Genomic studies of human cancers have yielded a wealth of information about genes that are altered in tumors1,2,3. A challenge arising from these studies is that many genes are altered, and it can be difficult to distinguish genetic alterations that drove tumorigenesis from that those arose incidentally during transformation. To draw this distinction it is beneficial to have an assay that can quantitatively measure the effect of an altered gene on tumor initiation and other processes that enable tumors to persist and disseminate. Here we present a rapid means to screen large numbers of candidate melanoma modifiers in zebrafish using an autochthonous tumor model4 that encompasses steps required for melanoma initiation and maintenance. A key reagent in this assay is the miniCoopR vector, which couples a wild-type copy of the mitfa melanocyte specification factor to a Gateway recombination cassette into which candidate melanoma genes can be recombined5. The miniCoopR vector has a mitfa rescuing minigene which contains the promoter, open reading frame and 3'-untranslated region of the wild-type mitfa gene. It allows us to make constructs using full-length open reading frames of candidate melanoma modifiers. These individual clones can then be injected into single cell Tg(mitfa:BRAFV600E);p53(lf);mitfa(lf)zebrafish embryos. The miniCoopR vector gets integrated by Tol2-mediated transgenesis6 and rescues melanocytes. Because they are physically coupled to the mitfa rescuing minigene, candidate genes are expressed in rescued melanocytes, some of which will transform and develop into tumors. The effect of a candidate gene on melanoma initiation and melanoma cell properties can be measured using melanoma-free survival curves, invasion assays, antibody staining and transplantation assays.

A rapid way to screen for melanoma modifiers using a zebrafish autochthonous tumor model is presented. It takes advantage of the miniCoopR vector which allows for expression of candidate melanoma genes in melanocytes. A method to obtain melanoma-free survival curves, an invasion assay, a protocol for antibody staining of scale melanocytes and a melanoma transplantation assay are described.

Genomic studies of  human cancers have yielded a wealth of information about genes that are altered  in tumors1,2,3. A challenge arising from these ...

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

We describe an indoor, portable, standardized course that can be used to evaluate obstacle avoidance in persons who have ultralow vision. Six sighted controls and 36 completely blind but otherwise healthy adult male (n=29) and female (n=13) subjects (age range 19-85 years), were enrolled in one of three studies involving testing of the BrainPort sensory substitution device. Subjects were asked to navigate the course prior to, and after, BrainPort training. They completed a total of 837 course runs in two different locations. Means and standard deviations were calculated across control types, courses, lights, and visits. We used a linear mixed effects model to compare different categories in the PPWS (percent preferred walking speed) and error percent data to show that the course iterations were properly designed. The course is relatively inexpensive, simple to administer, and has been shown to be a feasible way to test mobility function. Data analysis demonstrates that for the outcome of percent error as well as for percentage preferred walking speed, that each of the three courses is different, and that within each level, each of the three iterations are equal. This allows for randomization of the courses during administration.
Abbreviations: 
preferred walking speed (PWS) 
course speed (CS) 
percentage preferred walking speed (PPWS)

We describe an indoor, portable, standardized course that can be used to evaluate obstacle avoidance in persons who have ultralow vision. The course is relatively inexpensive, simple to administer, and has been shown to be reliable and reproducible.

We describe an indoor, portable, standardized course that can be used to evaluate obstacle avoidance in persons who have ultralow vision. Six sighted ...

Using Adeno-associated Virus as a Tool to Study Retinal Barriers in Disease

M&#252;ller cells are the principal glial cells of the retina. Their end-feet form the limits of the retina at the outer and inner limiting membranes (ILM), and in conjunction with astrocytes, pericytes and endothelial cells they establish the blood-retinal barrier (BRB). BRB limits material transport between the bloodstream and the retina while the ILM acts as a basement membrane that defines histologically the border between the retina and the vitreous cavity. Labeling M&#252;ller cells is particularly relevant to study the physical state of the retinal barriers, as these cells are an integral part of the BRB and ILM. Both BRB and ILM are frequently altered in retinal disease and are responsible for disease symptoms.
There are several well-established methods to study the integrity of the BRB, such as the Evans blue assay or fluorescein angiography. However these methods do not provide information on the extent of BRB permeability to larger molecules, in nanometer range. Furthermore, they do not provide information on the state of other retinal barriers such as the ILM. To study BRB permeability alongside retinal ILM, we used an AAV based method that provides information on permeability of BRB to larger molecules while indicating the state of the ILM and extracellular matrix proteins in disease states. Two AAV variants are useful for such study: AAV5 and ShH10. AAV5&#160;has a natural tropism for photoreceptors but it cannot get across to the outer retina when administered into the vitreous when the ILM is intact (i.e., in wild-type retinas). ShH10 has a strong tropism towards glial cells and will selectively label M&#252;ller glia in both healthy and diseased retinas. ShH10 provides more efficient gene delivery in retinas where ILM is compromised. These viral tools coupled with immunohistochemistry and blood-DNA analysis shed light onto the state of retinal barriers in disease.

To investigate the blood-retinal barrier permeability and the inner limiting membrane integrity in animal models of retinal disease, we used several adeno-associated virus (AAV) variants as tools to label retinal neurons and glia. Virus mediated reporter gene expression is then used as an indicator of retinal barrier permeability.

M&#252;ller cells are the principal glial cells of the retina. Their end-feet form the limits of the retina at the outer and inner limiting membranes ...

Smartphone Fundus Photography

Smartphone fundus photography is a simple technique to obtain ocular fundus pictures using a smartphone camera and a conventional handheld indirect ophthalmoscopy lens. This technique is indispensable when picture documentation of optic nerve, retina, and retinal vessels is necessary but a fundus camera is not available. The main advantage of this technique is the widespread&#160;availability of smartphones that allows documentation of macula and optic nerve changes in many settings that was not previously possible. Following the well-defined steps detailed here, such as proper alignment of the phone camera, handheld lens, and the patient&#39;s pupil, is the key for obtaining a clear retina picture with no interfering light reflections and aberrations. In this paper, the optical principles of indirect ophthalmoscopy and fundus photography will be reviewed first. Then, the step-by-step method to record a good quality retinal image using a smartphone will be explained.

Fundus photography normally requires specialized fundus cameras that are not always available in all clinical settings.&#160;Here, a simple method to record ocular fundus images using a smartphone camera and a conventional high-plus handheld indirect ophthalmoscopy lens is described.

Smartphone fundus photography is a simple technique to obtain ocular fundus pictures using a smartphone camera and a conventional handheld indirect ...

Regenerative Therapy by Suprachoroidal Cell Autograft in Dry Age-related Macular Degeneration: Preliminary In Vivo Report

This study is aimed at examining whether a suprachoroidal graft of autologous cells can improve best corrected visual acuity (BCVA) and responses to microperimetry (MY) in eyes affected by dry Age-related Macular Degeneration (AMD) over time through the production and secretion of growth factors (GFs) on surrounding tissue. Patients were randomly assigned to each study group. All patients were diagnosed with dry AMD and with BCVA equal to or greater than 1 logarithm of the minimum angle of resolution (logMAR). A suprachoroidal autologous graft by Limoli Retinal Restoration Technique (LRRT) was carried out on group A, which included 11 eyes from 11 patients. The technique was performed by implanting adipocytes, adipose-derived stem cells obtained from the stromal vascular fraction, and platelets from platelet-rich plasma in the suprachoroidal space. Conversely, group B, including 14 eyes of 14 patients, was used as a control group. For each patient, diagnosis was verified by confocal scanning laser ophthalmoscope and spectral domain-optical coherence tomography (SD-OCT). In group A, BCVA improved by 0.581 to 0.504 at 90 days and to 0.376 logMAR at 180 days (+32.20%) postoperatively. Furthermore, MY test increased by 11.44 dB to 12.59 dB at 180 days. The different cell types grafted behind the choroid were able to ensure constant GF secretion in the choroidal flow. Consequently, the results indicate that visual acuity (VA) in the grafted group can increase more than in the control group after six months.

Regenerative Therapy by Suprachoroidal Cell Autograft in Dry Age-related Macular Degeneration: Preliminary In Vivo Report

The goal of this study is to assess whether the suprachoroidal graft of adipose-derived stem cells included in the stromal vascular fraction and platelets derived from platelet-rich plasma by the Limoli Retinal Restoration Technique can improve visual acuity and retinal sensitivity responses in eyes affected by dry age-related macular degeneration.

This study is aimed at examining whether a suprachoroidal graft of autologous cells can improve best corrected visual acuity (BCVA) and responses to ...

A Blood-based Test for the Detection of ROS1 and RET Fusion Transcripts from Circulating Ribonucleic Acid Using Digital Polymerase Chain Reaction

We have developed novel methods for the isolation and characterization of tumor-derived circulating ribonucleic acid (cRNA) for blood-based liquid biopsy. Robust detection of cRNA recovered from blood represents a solution to a critical unmet need in clinical diagnostics. The test begins with the collection of whole blood into blood collection tubes containing preservatives that stabilize cRNA. Cell-free, exosomal, and platelet-associated RNA is isolated from plasma in this test system. The cRNA is reverse transcribed to complementary DNA (cDNA) and amplified using digital polymerase chain reaction (dPCR). Samples are evaluated for both the target biomarker as well as a control gene. Test validation included limit of detection, accuracy, and robustness studies with analytic samples. The method developed as a result of these studies reproducibly detect multiple fusion variants for ROS1 (C-Ros proto-oncogene 1; 8 variants) and RET (rearranged during transfection proto-oncogene; 8 variants). The sample processing workflow has been optimized so that test results can consistently be generated within 72 hours of sample receipt.

Detection of circulating ribonucleic acid (cRNA) from blood is an unmet need in clinical diagnostics. Here we describe methods that characterize cRNA from non-small cell lung cancer patients using sensitive and specific digital polymerase chain reaction. The tests meet design requirements to detect fusion variants within 72 hours.

We have developed novel methods for the isolation and characterization of tumor-derived circulating ribonucleic acid (cRNA) for blood-based liquid biopsy. ...

Puncture-Induced Iris Neovascularization as a Mouse Model of Rubeosis Iridis

We describe a model of puncture-induced iris neovascularization as a general model for noninvasive evaluation of angiogenesis. The model is also relevant for targeting neovascular glaucoma, a sight-threatening complication of diabetic retinopathy. This method is based on the induction of iris vascular response by a series of self-sealing uveal punctures on BALB/c mice and takes advantage of the postpartum maturation of mouse ocular vasculature. Mouse pups undergo uveal punctures from postnatal day 12.5, when the pups naturally open their eyes, until postnatal day 24.5. Due to the transparency of the cornea, iris vasculature can be analyzed easily through time by noninvasive in vivo methods. Furthermore, the semitransparent iris of BALB/c mice can be flatmounted for detailed immunohistologic analysis with minimal non-specific background staining. In this model, angiogenesis is mainly driven by the inflammatory and plasminogen activating systems. The puncture-induced model is the first to induce iris neovascularization in small rodents, and has the advantage of allowing direct noninvasive in vivo analysis of the angiogenic process. Moreover, the model can be combined with angiogenic modulating substances, which highlights its potential in the study of angiogenesis with an in vivo perspective.

Iris neovascularization, a common complication of ischemic retinal disease, may lead to sight-threatening neovascular glaucoma. Here, we describe a murine protocol for inducing experimental iris neovascularization that may be used for noninvasive evaluation of angiogenesis-modulating substances.

We describe a model of puncture-induced iris neovascularization as a general model for noninvasive evaluation of angiogenesis. The model is also relevant ...

Subjective Refraction Test Using a Smartphone for Vision Screening

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Chapters in this video

The Trier Social Stress Test Protocol for Inducing Psychological Stress

High Content Screening in Neurodegenerative Diseases

The α-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva

Screening for Melanoma Modifiers using a Zebrafish Autochthonous Tumor Model

A Standardized Obstacle Course for Assessment of Visual Function in Ultra Low Vision and Artificial Vision

Using Adeno-associated Virus as a Tool to Study Retinal Barriers in Disease

Smartphone Fundus Photography

Regenerative Therapy by Suprachoroidal Cell Autograft in Dry Age-related Macular Degeneration: Preliminary In Vivo Report

A Blood-based Test for the Detection of ROS1 and RET Fusion Transcripts from Circulating Ribonucleic Acid Using Digital Polymerase Chain Reaction

Puncture-Induced Iris Neovascularization as a Mouse Model of Rubeosis Iridis