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  1. Zhou R, Tong L
    Front Psychol, 2022;13:903023.
    PMID: 35615168 DOI: 10.3389/fpsyg.2022.903023
    With the deep popularity of mobile Internet, the "eyeball economy" is more active than ever. Driven by powerful modern media, livestreaming, as a new form of attracting public attention to obtain economic benefits, is worth studying its influence path on consumers. Based on the technology acceptance model and the mediating effect of emotion, this study constructs the consumer influencing factor model of livestreaming e-commerce. The research model and related hypotheses are verified by SPSS and linear multiple regression models. The research found that emotional trust and perceived emotional value could be regarded as mediating variables to stimulate consumers' purchase intention in livestreaming e-commerce. They have a full mediating effect on product and atmosphere and a partial mediating effect on homogeneity and promotion, which identifies that online celebrity's homogeneity, and sales promotion could influence consumers' purchase intention through the partial mediating role of emotional trust and perceived emotional value, while product and atmosphere induced by emotional contagion could exert influence on consumers' purchase intention through the full mediating effect of emotional trust and perceived emotional value.
  2. Thilagar S, Yew YC, Dhaliwal GK, Toh I, Tong LL
    Vet Rec, 2005 Oct 29;157(18):558-60.
    PMID: 16258139
  3. Tong L, Htoon HM, Hou A, Acharya RU, Tan JH, Wei QP, et al.
    BMJ Open Ophthalmol, 2018;3(1):e000150.
    PMID: 30123846 DOI: 10.1136/bmjophth-2018-000150
    Objective: Dry eye is a common disease with great health burden and no satisfactory treatment. Traditional Chinese medicine, an increasingly popular form of complementary medicine, has been used to treat dry eye but studies have been inconclusive. To address this issue, we conducted a randomised investigator-masked study which included the robust assessment of disease mechanisms.

    Methods and analysis: Eligible participants (total 150) were treated with artificial tear (AT) alone, with added eight sessions of acupuncture (AC) or additional daily oral herb (HB) over a month.

    Results: Participants treated with AC were more likely to respond symptomatically than those on AT (88% vs 72%, p=0.039) with a difference of 16% (95% CI: 0.18 to 31.1). The number-to-treat with AC to achieve response in one person was 7 (3 to 157). Participants in the AC group also had reduced conjunctival redness (automatic grading with Oculus keratograph) compared with AT (p=0.043) and reduced tear T helper cell (Th1)-cytokine tumour necrosis factor α (p=0.027) and Th2-cytokine interleukin 4 concentrations (p=0.038). AC was not significantly superior to AT in other outcomes such as tear osmolarity, tear evaporation rates, corneal staining and tear break-up times. No significant adverse effects were encountered. HB was not significantly different in the primary outcome from AT (80% vs 72%, p=0.26).

    Conclusions: AC is safe and provides additional benefit in mild to moderate dry eye up to 1 month, compared with ATs alone. Treatment is associated with demonstrable molecular evidence of reduced inflammation. Provided that suitably qualified practitioners are available to implement standardised treatment, AC may be recommended as adjunctive therapy to AT.

    Trial registration number: ClinicalTrials.gov (NCT02219204)registered on 14 August 2014.
  4. Mookiah MR, Acharya UR, Fujita H, Tan JH, Chua CK, Bhandary SV, et al.
    Comput Biol Med, 2015 Nov 1;66:295-315.
    PMID: 26453760 DOI: 10.1016/j.compbiomed.2015.09.012
    Diabetic Macular Edema (DME) is caused by accumulation of extracellular fluid from hyperpermeable capillaries within the macula. DME is one of the leading causes of blindness among Diabetes Mellitus (DM) patients. Early detection followed by laser photocoagulation can save the visual loss. This review discusses various imaging modalities viz. biomicroscopy, Fluorescein Angiography (FA), Optical Coherence Tomography (OCT) and colour fundus photographs used for diagnosis of DME. Various automated DME grading systems using retinal fundus images, associated retinal image processing techniques for fovea, exudate detection and segmentation are presented. We have also compared various imaging modalities and automated screening methods used for DME grading. The reviewed literature indicates that FA and OCT identify DME related changes accurately. FA is an invasive method, which uses fluorescein dye, and OCT is an expensive imaging method compared to fundus photographs. Moreover, using fundus images DME can be identified and automated. DME grading algorithms can be implemented for telescreening. Hence, fundus imaging based DME grading is more suitable and affordable method compared to biomicroscopy, FA, and OCT modalities.
  5. Mookiah MR, Acharya UR, Chandran V, Martis RJ, Tan JH, Koh JE, et al.
    Med Biol Eng Comput, 2015 Dec;53(12):1319-31.
    PMID: 25894464 DOI: 10.1007/s11517-015-1278-7
    Diabetic macular edema (DME) is one of the most common causes of visual loss among diabetes mellitus patients. Early detection and successive treatment may improve the visual acuity. DME is mainly graded into non-clinically significant macular edema (NCSME) and clinically significant macular edema according to the location of hard exudates in the macula region. DME can be identified by manual examination of fundus images. It is laborious and resource intensive. Hence, in this work, automated grading of DME is proposed using higher-order spectra (HOS) of Radon transform projections of the fundus images. We have used third-order cumulants and bispectrum magnitude, in this work, as features, and compared their performance. They can capture subtle changes in the fundus image. Spectral regression discriminant analysis (SRDA) reduces feature dimension, and minimum redundancy maximum relevance method is used to rank the significant SRDA components. Ranked features are fed to various supervised classifiers, viz. Naive Bayes, AdaBoost and support vector machine, to discriminate No DME, NCSME and clinically significant macular edema classes. The performance of our system is evaluated using the publicly available MESSIDOR dataset (300 images) and also verified with a local dataset (300 images). Our results show that HOS cumulants and bispectrum magnitude obtained an average accuracy of 95.56 and 94.39% for MESSIDOR dataset and 95.93 and 93.33% for local dataset, respectively.
  6. Qiang S, Alsaeedi HA, Yuhong C, Yang H, Tong L, Kumar S, et al.
    J. Photochem. Photobiol. B, Biol., 2018 Jun;183:127-132.
    PMID: 29704860 DOI: 10.1016/j.jphotobiol.2018.04.003
    BACKGROUND: Retinal degeneration is a condition ensued by various ocular disorders such as artery occlusion, diabetic retinopathy, retrolental fibroplasia and retinitis pigmentosa which cause abnormal loss of photoreceptor cells and lead to eventual vision impairment. No efficient treatment has yet been found, however, the use of stem cell therapy such as bone marrow and embryonic stem cells has opened a new treatment modality for retinal degenerative diseases. The major goal of this study is to analyze the potential of endothelial progenitor cells derived from bone marrow to differentiate into retinal neural cells for regenerative medicine purposes.

    METHODS: In this study, endothelial progenitor cells were induced in-vitro with photoreceptor growth factor (taurine) for 21 days. Subsequently, the morphology and gene expression of CRX and RHO of the photoreceptors-induced EPCs were examined through immunostaining assay.

    FINDINGS: The results indicated that the induced endothelial progenitor cells demonstrated positive gene expression of CRX and RHO. Our findings suggested that EPC cells may have a high advantage in cell replacement therapy for treating eye disease, in addition to other neural diseases, and may be a suitable cell source in regenerative medicine for eye disorders.

  7. Hagiwara Y, Koh JEW, Tan JH, Bhandary SV, Laude A, Ciaccio EJ, et al.
    Comput Methods Programs Biomed, 2018 Oct;165:1-12.
    PMID: 30337064 DOI: 10.1016/j.cmpb.2018.07.012
    BACKGROUND AND OBJECTIVES: Glaucoma is an eye condition which leads to permanent blindness when the disease progresses to an advanced stage. It occurs due to inappropriate intraocular pressure within the eye, resulting in damage to the optic nerve. Glaucoma does not exhibit any symptoms in its nascent stage and thus, it is important to diagnose early to prevent blindness. Fundus photography is widely used by ophthalmologists to assist in diagnosis of glaucoma and is cost-effective.

    METHODS: The morphological features of the disc that is characteristic of glaucoma are clearly seen in the fundus images. However, manual inspection of the acquired fundus images may be prone to inter-observer variation. Therefore, a computer-aided detection (CAD) system is proposed to make an accurate, reliable and fast diagnosis of glaucoma based on the optic nerve features of fundus imaging. In this paper, we reviewed existing techniques to automatically diagnose glaucoma.

    RESULTS: The use of CAD is very effective in the diagnosis of glaucoma and can assist the clinicians to alleviate their workload significantly. We have also discussed the advantages of employing state-of-art techniques, including deep learning (DL), when developing the automated system. The DL methods are effective in glaucoma diagnosis.

    CONCLUSIONS: Novel DL algorithms with big data availability are required to develop a reliable CAD system. Such techniques can be employed to diagnose other eye diseases accurately.

  8. Lim EWL, Chee ML, Sabanayagam C, Majithia S, Tao Y, Wong TY, et al.
    Invest Ophthalmol Vis Sci, 2019 05 01;60(6):1889-1897.
    PMID: 31042796 DOI: 10.1167/iovs.19-26810
    Purpose: The purpose of this study was to investigate the association between sleep (duration and quality) and symptoms of dry eye in Singapore Malay and Indian adults.

    Methods: This was a prospective cross-sectional study. A total of 3303 subjects aged 40 years and above from two large population-based cohorts, the Singapore Malay Eye Study-2 (n = 1191, 2011-2013) and the Singapore Indian Eye Study-2 (n = 2112, 2013-2015), were included. The presence of symptoms of dry eye was defined as having at least one of six symptoms often or all the time. Sleep questionnaires included the Epworth Sleepiness Scale, Berlin Questionnaire, STOP-bang questionnaire, and Insomnia Severity Index. Poor sleep quality was defined as meeting the respective questionnaire thresholds. General health questionnaires (including sleep duration) and standardized ocular and systemic tests were also used.

    Results: Of 3303 participants, 6.4% had excessive sleepiness, 20.5% had high risk for sleep apnea, 2.7% had clinical insomnia, and 7.8% had <5 hours of sleep. These sleep factors were associated with symptoms of dry eye. After adjusting for relevant demographic, medical, and social factors, the following were associated with higher odds of symptoms of dry eye: excessive sleepiness (Epworth Sleepiness Scale: odds ratio [OR] = 1.77 [1.15-2.71]), high risk of sleep apnea (Berlin Questionnaire: OR = 1.55 [1.17-2.07], STOP-Bang Questionnaire: OR = 2.66 [1.53-4.61]), clinical insomnia (Insomnia Severity Index: OR = 3.68 [2.17-6.26]) and <5 hours of sleep (OR = 1.73 [1.17-2.57], reference sleep duration 5-9 hours). Sleep apnea, insomnia, and sleep duration were each shown to be independently associated with symptoms of dry eye.

    Conclusion: Short sleep duration and poor quality are both significantly and independently associated with symptoms of dry eye.

  9. Peng Z, Xue H, Liu X, Wang S, Liu G, Jia X, et al.
    Front Bioeng Biotechnol, 2023;11:1222088.
    PMID: 37539434 DOI: 10.3389/fbioe.2023.1222088
    The development of cost-effective, biocompatible soft wound dressings is highly desirable; however, conventional dressings are only designed for flat wounds, which creates difficulty with promising healing efficiency in complex practical conditions. Herein, we developed a tough, adhesive biomimetic hyaluronic acid methacryloyl hydrogels composed of chemically crosslinked hyaluronic acid methacryloyl (HAMA) network and poly(N-hydroxyethyl acrylamide) (PHEAA) network rich in multiple hydrogen bonding. Due to the multiple chemical crosslinking sites (acrylamide groups) of HAMA; the bulk HEMA/PHEAA hydrogels presented significant enhancements in mechanical properties (∼0.45 MPa) than common hyaluronic acid hydrogels (<0.1 MPa). The abundant hydrogen bonding also endowed the resultant hydrogels with extremely high adhesiveness on many nonporous substrates, including glass and biological tissues (e.g., heart, liver, lung, kidney, stomach, and muscle), with a considerable interfacial toughness of ∼1432 J m-2. Accordingly, since both natural hyaluronic acid derivative polymers and hydrophilic PHEAA networks are highly biocompatible, the hydrogel matrix possesses good blood compatibility (<5% of hemolysis ratio) and satisfies the general dressing requirements (>99% of cell viability). Based on these physicochemical features, we have demonstrated that this adhesive hydrogel, administered in the form of a designed patch, could be applied to wound tissue healing by promoting epithelialization, angiogenesis, and collagen deposition. We believe that our proposed biomimetic hydrogel design holds great potential for wound repair and our developed HAMA/PHEAA hydrogels are extremely promising for the next-generation tissue healings in emergency situations.
  10. Martinez J, Ross PA, Gu X, Ant TH, Murdochy SM, Tong L, et al.
    Appl Environ Microbiol, 2022 Nov 22;88(22):e0141222.
    PMID: 36318064 DOI: 10.1128/aem.01412-22
    The intracellular bacterium Wolbachia inhibits virus replication and is being harnessed around the world to fight mosquito-borne diseases through releases of mosquitoes carrying the symbiont. Wolbachia strains vary in their ability to invade mosquito populations and suppress viruses in part due to differences in their density within the insect and associated fitness costs. Using whole-genome sequencing, we demonstrate the existence of two variants in wAlbB, a Wolbachia strain being released in natural populations of Aedes aegypti mosquitoes. The two variants display striking differences in genome architecture and gene content. Differences in the presence/absence of 52 genes between variants include genes located in prophage regions and others potentially involved in controlling the symbiont's density. Importantly, we show that these genetic differences correlate with variation in wAlbB density and its tolerance to heat stress, suggesting that different wAlbB variants may be better suited for field deployment depending on local environmental conditions. Finally, we found that the wAlbB genome remained stable following its introduction in a Malaysian mosquito population. Our results highlight the need for further genomic and phenotypic characterization of Wolbachia strains in order to inform ongoing Wolbachia-based programs and improve the selection of optimal strains in future field interventions. IMPORTANCE Dengue is a viral disease transmitted by Aedes mosquitoes that threatens around half of the world population. Recent advances in dengue control involve the introduction of Wolbachia bacterial symbionts with antiviral properties into mosquito populations, which can lead to dramatic decreases in the incidence of the disease. In light of these promising results, there is a crucial need to better understand the factors affecting the success of such strategies, in particular the choice of Wolbachia strain for field releases and the potential for evolutionary changes. Here, we characterized two variants of a Wolbachia strain used for dengue control that differ at the genomic level and in their ability to replicate within the mosquito. We also found no evidence for the evolution of the symbiont within the 2 years following its deployment in Malaysia. Our results have implications for current and future Wolbachia-based health interventions.
  11. Mookiah MR, Acharya UR, Koh JE, Chandran V, Chua CK, Tan JH, et al.
    Comput Biol Med, 2014 Oct;53:55-64.
    PMID: 25127409 DOI: 10.1016/j.compbiomed.2014.07.015
    Age-related Macular Degeneration (AMD) is one of the major causes of vision loss and blindness in ageing population. Currently, there is no cure for AMD, however early detection and subsequent treatment may prevent the severe vision loss or slow the progression of the disease. AMD can be classified into two types: dry and wet AMDs. The people with macular degeneration are mostly affected by dry AMD. Early symptoms of AMD are formation of drusen and yellow pigmentation. These lesions are identified by manual inspection of fundus images by the ophthalmologists. It is a time consuming, tiresome process, and hence an automated diagnosis of AMD screening tool can aid clinicians in their diagnosis significantly. This study proposes an automated dry AMD detection system using various entropies (Shannon, Kapur, Renyi and Yager), Higher Order Spectra (HOS) bispectra features, Fractional Dimension (FD), and Gabor wavelet features extracted from greyscale fundus images. The features are ranked using t-test, Kullback-Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance (CBBD), Receiver Operating Characteristics (ROC) curve-based and Wilcoxon ranking methods in order to select optimum features and classified into normal and AMD classes using Naive Bayes (NB), k-Nearest Neighbour (k-NN), Probabilistic Neural Network (PNN), Decision Tree (DT) and Support Vector Machine (SVM) classifiers. The performance of the proposed system is evaluated using private (Kasturba Medical Hospital, Manipal, India), Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) datasets. The proposed system yielded the highest average classification accuracies of 90.19%, 95.07% and 95% with 42, 54 and 38 optimal ranked features using SVM classifier for private, ARIA and STARE datasets respectively. This automated AMD detection system can be used for mass fundus image screening and aid clinicians by making better use of their expertise on selected images that require further examination.
  12. Mookiah MR, Acharya UR, Fujita H, Koh JE, Tan JH, Noronha K, et al.
    Comput Biol Med, 2015 Aug;63:208-18.
    PMID: 26093788 DOI: 10.1016/j.compbiomed.2015.05.019
    Age-related Macular Degeneration (AMD) is an irreversible and chronic medical condition characterized by drusen, Choroidal Neovascularization (CNV) and Geographic Atrophy (GA). AMD is one of the major causes of visual loss among elderly people. It is caused by the degeneration of cells in the macula which is responsible for central vision. AMD can be dry or wet type, however dry AMD is most common. It is classified into early, intermediate and late AMD. The early detection and treatment may help one to stop the progression of the disease. Automated AMD diagnosis may reduce the screening time of the clinicians. In this work, we have introduced LCP to characterize normal and AMD classes using fundus images. Linear Configuration Coefficients (CC) and Pattern Occurrence (PO) features are extracted from fundus images. These extracted features are ranked using p-value of the t-test and fed to various supervised classifiers viz. Decision Tree (DT), Nearest Neighbour (k-NN), Naive Bayes (NB), Probabilistic Neural Network (PNN) and Support Vector Machine (SVM) to classify normal and AMD classes. The performance of the system is evaluated using both private (Kasturba Medical Hospital, Manipal, India) and public domain datasets viz. Automated Retinal Image Analysis (ARIA) and STructured Analysis of the Retina (STARE) using ten-fold cross validation. The proposed approach yielded best performance with a highest average accuracy of 97.78%, sensitivity of 98.00% and specificity of 97.50% for STARE dataset using 22 significant features. Hence, this system can be used as an aiding tool to the clinicians during mass eye screening programs to diagnose AMD.
  13. Man REK, Veerappan AR, Tan SP, Fenwick EK, Sabanayagam C, Chua J, et al.
    Ocul Surf, 2017 Oct;15(4):742-748.
    PMID: 28442380 DOI: 10.1016/j.jtos.2017.04.004
    PURPOSE: To evaluate the incidence of symptomatic dry eye disease (SDED) and associated risk factors in a well-characterized cohort of ethnic Malays in Singapore.

    METHODS: We included 1682 participants (mean age [SD]: 57 [10]years; 55.4% female) without SDED from the Singapore Malay Eye Study (SiMES), a population-based longitudinal study with baseline examination (SiMES-1) conducted between 2004 and 2006, and follow-up examination (SiMES-2) conducted between 2010 and 2013. SDED was considered to be present if a participant answered "often" or "all the time" to any of the six questions from the Salisbury Eye Evaluation Study dry eye questionnaire. Age-standardized incidence of SDED was calculated as the crude 6-year cumulative incidence standardized to Singapore's population census. Gender-stratified multivariable log-binomial regression models were utilized to determine the independent risk factors of incident SDED.

    RESULTS: At the 6-year follow-up, 86 of 1682 participants had developed SDED, which was equivalent to an age-standardized 6-year incidence of 5.1% (95% CI 4.1-6.4%). There were no differences in the incidence of SDED between men and women (P = 0.9). Multivariable models revealed that presence of glaucoma and poorer self-rated health were independently associated with incident SDED in men (P = 0.003 and 0.03, respectively), while contact lens wear (P = 0.002), history of thyroid disease (P = 0.03), and having had cataract surgery (P = 0.02) were predictive of incident SDED in women.

    CONCLUSION: One in twenty adult Malays developed SDED over a 6-year period. Risk factors for incident SDED were different between men and women. Future studies and public health interventions should consider this gender-specific difference in risk factors.
  14. Koh JEW, Acharya UR, Hagiwara Y, Raghavendra U, Tan JH, Sree SV, et al.
    Comput Biol Med, 2017 05 01;84:89-97.
    PMID: 28351716 DOI: 10.1016/j.compbiomed.2017.03.008
    Vision is paramount to humans to lead an active personal and professional life. The prevalence of ocular diseases is rising, and diseases such as glaucoma, Diabetic Retinopathy (DR) and Age-related Macular Degeneration (AMD) are the leading causes of blindness in developed countries. Identifying these diseases in mass screening programmes is time-consuming, labor-intensive and the diagnosis can be subjective. The use of an automated computer aided diagnosis system will reduce the time taken for analysis and will also reduce the inter-observer subjective variabilities in image interpretation. In this work, we propose one such system for the automatic classification of normal from abnormal (DR, AMD, glaucoma) images. We had a total of 404 normal and 1082 abnormal fundus images in our database. As the first step, 2D-Continuous Wavelet Transform (CWT) decomposition on the fundus images of two classes was performed. Subsequently, energy features and various entropies namely Yager, Renyi, Kapoor, Shannon, and Fuzzy were extracted from the decomposed images. Then, adaptive synthetic sampling approach was applied to balance the normal and abnormal datasets. Next, the extracted features were ranked according to the significances using Particle Swarm Optimization (PSO). Thereupon, the ranked and selected features were used to train the random forest classifier using stratified 10-fold cross validation. Overall, the proposed system presented a performance rate of 92.48%, and a sensitivity and specificity of 89.37% and 95.58% respectively using 15 features. This novel system shows promise in detecting abnormal fundus images, and hence, could be a valuable adjunct eye health screening tool that could be employed in polyclinics, and thereby reduce the workload of specialists at hospitals.
  15. Sugrue E, Wickenhagen A, Mollentze N, Aziz MA, Sreenu VB, Truxa S, et al.
    PLoS Pathog, 2022 Nov;18(11):e1010973.
    PMID: 36399512 DOI: 10.1371/journal.ppat.1010973
    HIV-1 transmission via sexual exposure is an inefficient process. When transmission does occur, newly infected individuals are colonized by the descendants of either a single virion or a very small number of establishing virions. These transmitted founder (TF) viruses are more interferon (IFN)-resistant than chronic control (CC) viruses present 6 months after transmission. To identify the specific molecular defences that make CC viruses more susceptible to the IFN-induced 'antiviral state', we established a single pair of fluorescent TF and CC viruses and used arrayed interferon-stimulated gene (ISG) expression screening to identify candidate antiviral effectors. However, we observed a relatively uniform ISG resistance of transmitted HIV-1, and this directed us to investigate possible underlying mechanisms. Simple simulations, where we varied a single parameter, illustrated that reduced growth rate could possibly underly apparent interferon sensitivity. To examine this possibility, we closely monitored in vitro propagation of a model TF/CC pair (closely matched in replicative fitness) over a targeted range of IFN concentrations. Fitting standard four-parameter logistic growth models, in which experimental variables were regressed against growth rate and carrying capacity, to our in vitro growth curves, further highlighted that small differences in replicative growth rates could recapitulate our in vitro observations. We reasoned that if growth rate underlies apparent interferon resistance, transmitted HIV-1 would be similarly resistant to any growth rate inhibitor. Accordingly, we show that two transmitted founder HIV-1 viruses are relatively resistant to antiretroviral drugs, while their matched chronic control viruses were more sensitive. We propose that, when present, the apparent IFN resistance of transmitted HIV-1 could possibly be explained by enhanced replicative fitness, as opposed to specific resistance to individual IFN-induced defences. However, further work is required to establish how generalisable this mechanism of relative IFN resistance might be.
  16. Tsubota K, Yokoi N, Watanabe H, Dogru M, Kojima T, Yamada M, et al.
    Eye Contact Lens, 2020 Jan;46 Suppl 1:S2-S13.
    PMID: 31425351 DOI: 10.1097/ICL.0000000000000643
    The 2017 consensus report of the Asia Dry Eye Society (ADES) on the definition and diagnosis of dry eyes described dry eye disease as "Dry eye is a multifactorial disease characterized by unstable tear film causing a variety of symptoms and/or visual impairment, potentially accompanied by ocular surface damage." The report emphasized the instability of tear film and the importance of visual dysfunction in association with dry eyes, highlighting the importance of the evaluation of tear film stability. This report also discussed the concept of tear film-oriented therapy, which stemmed from the definition, and which is centered on provision of insufficient components in each tear film layer and ocular surface epithelium. The current ADES report proposes a simple classification of dry eyes based on the concept of tear film-oriented diagnosis and suggests that there are three types of dry eye: aqueous-deficient, decreased wettability, and increased evaporation. It is suggested that these three types respectively coincide with the problems of each layer: aqueous, membrane-associated mucins, and lipid/secretory mucin. Although each component cannot be quantitatively evaluated with the current technology, a practical diagnosis based on the patterns of fluorescein breakup is recommended. The Asia Dry Eye Society classification report suggests that for a practical use of the definition, diagnostic criteria and classification system should be integrated and be simple to use. The classification system proposed by ADES is a straightforward tool and simple to use, only through use of fluorescein, which is available even to non-dry eye specialists, and which is believed to contribute to an effective diagnosis and treatment of dry eyes.
  17. Milne RL, Kuchenbaecker KB, Michailidou K, Beesley J, Kar S, Lindström S, et al.
    Nat Genet, 2017 Dec;49(12):1767-1778.
    PMID: 29058716 DOI: 10.1038/ng.3785
    Most common breast cancer susceptibility variants have been identified through genome-wide association studies (GWAS) of predominantly estrogen receptor (ER)-positive disease. We conducted a GWAS using 21,468 ER-negative cases and 100,594 controls combined with 18,908 BRCA1 mutation carriers (9,414 with breast cancer), all of European origin. We identified independent associations at P < 5 × 10-8 with ten variants at nine new loci. At P < 0.05, we replicated associations with 10 of 11 variants previously reported in ER-negative disease or BRCA1 mutation carrier GWAS and observed consistent associations with ER-negative disease for 105 susceptibility variants identified by other studies. These 125 variants explain approximately 16% of the familial risk of this breast cancer subtype. There was high genetic correlation (0.72) between risk of ER-negative breast cancer and breast cancer risk for BRCA1 mutation carriers. These findings may lead to improved risk prediction and inform further fine-mapping and functional work to better understand the biological basis of ER-negative breast cancer.
  18. Michailidou K, Lindström S, Dennis J, Beesley J, Hui S, Kar S, et al.
    Nature, 2017 Nov 02;551(7678):92-94.
    PMID: 29059683 DOI: 10.1038/nature24284
    Breast cancer risk is influenced by rare coding variants in susceptibility genes, such as BRCA1, and many common, mostly non-coding variants. However, much of the genetic contribution to breast cancer risk remains unknown. Here we report the results of a genome-wide association study of breast cancer in 122,977 cases and 105,974 controls of European ancestry and 14,068 cases and 13,104 controls of East Asian ancestry. We identified 65 new loci that are associated with overall breast cancer risk at P 
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