Embryonic retinal ganglion cell (RGC) axons must extend toward and grow through the optic disc to exit the eye into the optic nerve. In the embryonic mouse eye, we found that immunoreactivity for the axon guidance molecule netrin-1 was specifically on neuroepithelial cells at the disk surrounding exiting RGC axons, and RGC axons express the netrin receptor, DCC (deleted in colorectal cancer). In vitro, anti-DCC antibodies reduced RGC neurite outgrowth responses to netrin-1. In netrin-1- and DCC-deficient embryos, RGC axon pathfinding to the disc was unaffected; however, axons failed to exit into the optic nerve, resulting in optic nerve hypoplasia. Thus, netrin-1 through DCC appears to guide RGC axons locally at the optic disc rather than at long range, apparently reflecting the localization of netrin-1 protein to the vicinity of netrin-1-producing cells at the optic disc.

Abstract. Agrin is thought to be the nerve-derived factor that initiates acetylcholine receptor (AChR) clustering at the developing neuromuscular junction. We have investigated the signaling pathway in mouse C2 myotubes and report that agrin induces a rapid but transient tyrosine phosphorylation of the AChR 13 subunit. As the 13-subunit tyrosine phosphorylation occurs before the formation of AChR clusters, it may serve as a precursor step in the clustering mechanism. Consistent with this, we observed that tyrosine phosphorylation of the [3 subunit correlated precisely with the presence or absence of clustering under several experimental conditions. Moreover, two tyrosine kinase inhibitors, herbimycin and staurosporine, that blocked B-subunit phosphorylation also blocked agrin-induced clustering. Surprisingly, the inhibitors also dispersed preformed AChR clusters, suggesting that the tyrosine phosphorylation of other proteins may be required for the maintenance of receptor clusters. These findings indicate that in mammalian muscle, agrin-induced AChR clustering occurs through a mechanism that requires tyrosine phosphorylation and may involve tyrosine phosphorylation of the AChR itself.

Optic nerve formation in mouse involves interactions between netrin-1 at the optic disk and the netrin-1 receptor DCC (deleted in colorectal cancer) expressed on retinal ganglion cell (RGC) axons. Deficiency in either protein causes RGC pathfinding defects at the disk leading to optic nerve hypoplasia (). Here we show that further along the visual pathway, RGC axons in netrin-1- or DCC-deficient mice grow in unusually angular trajectories within the ventral hypothalamus. In heterozygous Sey(neu) mice that also have a small optic nerve, RGC axon trajectories appear normal, indicating that the altered RGC axon trajectories in netrin-1 and DCC mutants are not secondarily caused by optic nerve hypoplasia. Intrinsic hypothalamic patterning is also affected in netrin-1 and DCC mutants, including a severe reduction in the posterior axon projections of gonadotropin-releasing hormone neurons. In addition to axon pathway defects, antidiuretic hormone and oxytocin neurons are found ectopically in the ventromedial hypothalamus, apparently no longer confined to the supraoptic nucleus in mutants. In summary, netrin-1 and DCC, presumably via direct interactions, govern both axon pathway formation and neuronal position during hypothalamic development, and loss of netrin-1 or DCC function affects both visual and neuroendocrine systems. Netrin protein localization also indicates that unlike in more caudal CNS, guidance about the hypothalamic ventral midline does not require midline expression of netrin.

Social media posts regarding measles vaccination were classified as pro-vaccination, expressing vaccine hesitancy, uncertain, or irrelevant. Spearman correlations with Centers for Disease Control and Prevention-reported measles cases and differenced smoothed cumulative case counts over this period were reported (using time series bootstrap confidence intervals). A total of 58,078 Facebook posts and 82,993 tweets were identified from 4 January 2009 to 27 August 2016. Pro-vaccination posts were correlated with the US weekly reported cases (Facebook: Spearman correlation 0.22 (95% confidence interval: 0.09 to 0.34), Twitter: 0.21 (95% confidence interval: 0.06 to 0.34)). Vaccine-hesitant posts, however, were uncorrelated with measles cases in the United States (Facebook: 0.01 (95% confidence interval: -0.13 to 0.14), Twitter: 0.0011 (95% confidence interval: -0.12 to 0.12)). These findings may result from more consistent social media engagement by individuals expressing vaccine hesitancy, contrasted with media- or event-driven episodic interest on the part of individuals favoring current policy.

Due to the COVID-19 pandemic, many key neglected tropical disease (NTD) activities have been postponed. This hindrance comes at a time when the NTDs are progressing towards their ambitious goals for 2030. Mathematical modelling on several NTDs, namely gambiense sleeping sickness, lymphatic filariasis, onchocerciasis, schistosomiasis, soil-transmitted helminthiases (STH), trachoma, and visceral leishmaniasis, shows that the impact of this disruption will vary across the diseases. Programs face a risk of resurgence, which will be fastest in high-transmission areas. Furthermore, of the mass drug administration diseases, schistosomiasis, STH, and trachoma are likely to encounter faster resurgence. The case-finding diseases (gambiense sleeping sickness and visceral leishmaniasis) are likely to have fewer cases being detected but may face an increasing underlying rate of new infections. However, once programs are able to resume, there are ways to mitigate the impact and accelerate progress towards the 2030 goals.

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IMPORTANCE Internet-based search engine and social media data may provide a novel complementary source for better understanding the epidemiologic factors of infectious eye diseases, which could better inform eye health care and disease prevention.OBJECTIVE To assess whether data from internet-based social media and search engines are associated with objective clinic-based diagnoses of conjunctivitis.DESIGN, SETTING, AND PARTICIPANTS Data from encounters of 4143 patients diagnosed with conjunctivitis from June 3, 2012, to April 26, 2014, at the University of California San Francisco (UCSF) Medical Center, were analyzed using Spearman rank correlation of each weekly observation to compare demographics and seasonality of nonallergic conjunctivitis with allergic conjunctivitis. Data for patient encounters with diagnoses for glaucoma and influenza were also obtained for the same period and compared with conjunctivitis. Temporal patterns of Twitter and Google web search data, geolocated to the United States and associated with these clinical diagnoses, were compared with the clinical encounters. The a priori hypothesis was that weekly internet-based searches and social media posts about conjunctivitis may reflect the true weekly clinical occurrence of conjunctivitis.MAIN OUTCOMES AND MEASURES Weekly total clinical diagnoses at UCSF of nonallergic conjunctivitis, allergic conjunctivitis, glaucoma, and influenza were compared using Spearman rank correlation with equivalent weekly data on Tweets related to disease or disease-related keyword searches obtained from Google Trends.RESULTS Seasonality of clinical diagnoses of nonallergic conjunctivitis among the 4143 patients (2364 females [57.1%] and 1776 males [42.9%]) with 5816 conjunctivitis encounters at UCSF correlated strongly with results of Google searches in the United States for the term pink eye (ρ, 0.68 [95% CI, 0.52 to 0.78]; P < .001) and correlated moderately with Twitter results about pink eye (ρ, 0.38 [95% CI, 0.16 to 0.56]; P < .001) and with clinical diagnosis of influenza (ρ, 0.33 [95% CI, 0.12 to 0.49]; P < .001), but did not significantly correlate with seasonality of clinical diagnoses of allergic conjunctivitis diagnosis at UCSF (ρ, 0.21 [95% CI, −0.02 to 0.42]; P = .06) or with results of Google searches in the United States for the term eye allergy (ρ, 0.13 [95% CI, −0.06 to 0.32]; P = .19). Seasonality of clinical diagnoses of allergic conjunctivitis at UCSF correlated strongly with results of Google searches in the United States for the term eye allergy (ρ, 0.44 [95% CI, 0.24 to 0.60]; P < .001) and eye drops (ρ, 0.47 [95% CI, 0.27 to 0.62]; P < .001). CONCLUSIONS AND RELEVANCEInternet-based search engine and social media data may reflect the occurrence of clinically diagnosed conjunctivitis, suggesting that these data sources can be leveraged to better understand the epidemiologic factors of conjunctivitis.

5 years and countries worldwide were obtained. Country and term were masked. Temporal scan statistics were applied to identify candidate epidemics. Candidates then were assessed for geotemporal concordance with an a priori defined collection of known reported conjunctivitis outbreaks, as a measure of sensitivity.Participants: Populations by country that searched Google's search engine using our study terms. Main Outcome Measures: Percent of known conjunctivitis outbreaks also found in the same country and period by our candidate epidemics, identified from conjunctivitis-related searches.Results: We identified 135 candidate conjunctivitis epidemic periods from 77 countries. Compared with our a priori defined collection of known reported outbreaks, candidate conjunctivitis epidemics identified 18 of 26 (69% sensitivity) of the reported country-wide or island nationwide outbreaks, or both; 9 of 20 (45% sensitivity) of the reported region or district-wide outbreaks, or both; but far fewer nosocomial and reported smaller outbreaks. Similar overall and individual sensitivity, as well as specificity, were found on a country-level basis. We also found that 83% of our candidate epidemics had start dates before (of those, 20% were more than 12 weeks before) their concurrent reported outbreak's report issuance date. Permutation tests provided evidence that on average, conjunctivitis candidate epidemics occurred geotemporally closer to outbreak reports than chance alone suggests (P < 0.001) unlike control term candidates (P ¼ 0.40).Conclusions: Conjunctivitis outbreaks can be detected using temporal scan analysis of Google search data alone, with more than 80% detected before an outbreak report's issuance date, some as early as the reported outbreak's start date. Future approaches using data from smaller regions, social media, and more search terms may improve sensitivity further and cross-validate detected candidates, allowing identification of candidate conjunctivitis epidemics from Internet search data potentially to complementarily benefit traditional reporting and detection systems to improve epidemic awareness.