فهرست مطالب

Journal of Ophthalmic and Optometric Sciences
Volume:5 Issue: 1, Winter 2021

  • تاریخ انتشار: 1401/09/30
  • تعداد عناوین: 7
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  • Alireza Meshkin, Ehsan Pournoor Pages 1-11
    Background

    Eye diseases (EDs) are disorders of the ocular system, causing visual damage and sightlessness. Different studies have specified a wide range of biological functions of LncRNAs; consequently, their dysfunction directs to several diseases such as EDs. Growing evidence suggests that LncRNAs might be a new class of molecules for disease diagnosis and treatment in the future. Due to the importance and the detection of a large number of LncRNAs, genome-wide analyses are essential to identify which LncRNAs are associated with different diseases. For this purpose, it is vital to collect experimentally validated LncRNAs and predict novel LncRNAs associated with various eye diseases in a systematic manner.

    Material and Methods

    In the present study, researchers attempted to expand the current data using a powerful bioinformatics pipeline. We integrated the different resources of eye-related LncRNA information to provide a customized entry point for LncRNA-target research.

    Results

    As a result, 429 mRNAs related to 25 humans EDs were identified, and 151 new experimentally validated physical interactions associated with these mRNA were identified. Finally, after organizing all the identified LncRNAs, respectively, 1038 and 89 experimentally validated and predicted LncRNAs were obtained.

    Conclusion

    Here, we propose EyeLncDB (http://eyelncedb.databanks.behrc.ir/), a web-based platform of eye-related validated LncRNA data that contains the mentioned integrated information. EyeLncDB provides information on LncRNA-related diseases, pathways, genes, and targets with external links to the original data sources.

    Keywords: Biomarker, Web-Based Platform, Eye Diseases (EDs), LncRNA
  • Azadeh Kavianfar, Hamidreza Taherkhani, Fatemeh Ghorbani Pages 12-23
    Background

    Metaorganism or microbial communities of eukaryotic organisms provide an inclusive set of functions related to immunity, host metabolism, and stress tolerance. Ocular microbiota refers to pathogenic and commensal microorganisms in or on the eye. On the one hand, antibiotic treatment can give rise to pathogen overgrowth due to an imbalance of microbiota and cause various ophthalmic diseases. On the other, antibiotic therapy is considered the leading cause of antibiotic resistance. The present study aimed to describe the bacterial community changes following antibiotic treatment in the ocular surface microbiome.

    Material and Methods

    In this scenario, we evaluated the composition of thirteen canine ocular microbiomes during treatment with a typical mixture of antibiotics, neomycin-polymyxin-bacitracin. Microbiome taxonomy and downstream bacterial richness and evenness were analyzed using microbiome bioinformatics platforms.

    Results

    Accordingly, bacterial taxonomy at the level of phyla and genus was mapped, and alter of antibiotic resistance genes werereported. An increase in the Staphylococcus genus traced during the time and one month following antibiotic treatment. Bacterial network, alpha, and beta diversity indicated a significant microbiota change at the genus level.

    Conclusion

    This study highlights the effect of commonly used ocular antibiotics on commensal microbiota and the emergence of the antibiotic-resistant genus.

    Keywords: Microbiota, Antibiotic Resistance, Ocular Microbiome, Ophthalmic Diseases
  • Mazaher Maghsoudloo, Farhad Adhami Moghadam Pages 24-40
    Background

    Retinal detachment (RD), separation of the neurosensory retina away from its underlying layer of support tissue (retinal pigment epithelium), can be a severe eye condition that affects on vision and can lead to blindness if not treated. Understanding the pathological mechanism of RD help us to the treatment of RD patients.

    Material and Methods

    In this study, the gene expression profile was downloaded from the GEO database and were analyzed in the samples of patients with RD and control cases. Then, the STRING online database was used for the reconstruction protein-protein interaction network, and then the important signaling pathways and critical biomarkers involved in RD were assessed by resulting network analysis and extraction of functional modules. Furthermore, we used the miRWalk online database to extract miRNAs related to identified genes. Finally, the DGIdb online database was used for extracting drug-target interactions.

    Result

    We extracted differentially expressed genes (DEGs) using the independent t-test with adj.P.Val<.05 and |log2-fold change|>=2. So, 196 DEGs were obtained for RD (36 and 160 genes were identified as down and upregulated genes, respectively). There is significant evidence that activation of the phototransduction cascade, interferon signaling, immune response, and cytokine signaling in the immune system are involved pathways that have a significant role in RD. as well as our finding indicates that up-regulation of HLA-C, HLA-A, HLA –B and HLA –E involved in the inflammatory response and C1QA, C1QB the members of the complement pathway are strictly correlated with RD. Subsequently, the PPI network was extracted from STRING. This network showed 196 genes and 183 interactions and alsoextracted three functional modules from the PPI network. Then, we used the miRWalk database and extracted 30 miRNAs. Finally, we proposed three miRNAs for the treatment of RD.

    Conclusion

    Our results indicate activation of some inflammatory signaling and cell death in RD. Hence, we suggested some mRNAs,miRNAs, and drugs as potential biomarkers and therapeutic targets in RD.

    Keywords: Retinal Detachment, System Biology, Biological Networks
  • Bahareh kermani, Mohsen pourshahrokhi, Rasoul Raesi, Akbar Mehralizadeh, Rezvan Sadat Maleki, Eisa Nazar, Salman Daneshi Pages 41-51
    Background

    The central thickness of the cornea, as one of the parameters of the anterior segment of the eye, is one of the important factors in the evaluation of patients with eye disorders. This research was conducted to investigate the effect of age, gender, and refractive errors on the central thickness of the cornea in the ophthalmology centers of Jiroft city.

    Material and methods

    This cross-sectional study was conducted by census method in the summer of 1400 on 255 patients referred to Jiroft ophthalmology centers. Data were collected using a researcher-made checklist and analyzed using SPSS version 22 statistical software and Student’s t-tests, one-way analysis of variance, and Pearson’s correlation coefficient at a significance level of P < 0.05.

    Results

    159 people (62.3 %) of the participants were women, and the average age of all people was 34.99 ± 7.33 years. The average central thickness of the cornea in the right eye in the three myopic, binocular and emmetropic groups was 501.93, 519.76, and 512.10, respectively, with the highest average central corneal thickness scores corresponding to the binocular group and the lowest average central thickness scores. The cornea of the myopic group is observed and the results of the analysis of variance showed that there is a statistically significant difference between the three groups in terms of the average scores obtained (P < 0.001).

    Conclusion

    This study showed that age, gender, and refractive errors had a significant effect on the central thickness of the cornea in ophthalmology centers of Jiroft city, and there was a wide range of central corneal thickness values with normal distribution.

    Keywords: Central Corneal Thickness, Refractive Error, Ophthalmology
  • Zahra Alaeddini Pages 52-66

    Ocular disorders have a broad spectrum. Some of them, such as Diabetic Retinopathy, are more common in low-income or low-resource countries. Diabetic Retinopathy is a cause related to vision loss and ocular impairment in the world. By identifying the symptoms in the early stages, it is possible to prevent the progress of the disease and also reach blindness. Considering the prevalence of different branches of Artificial Intelligence in many fields, including medicine, and the significant progress achieved in the use of big data to investigate ocular impairments, the potential of Artificial Intelligence algorithms to process and analyze Fundus images was used to identify symptoms associated with Diabetic Retinopathy. Under the studies, the proposed models for transformers provide better interpretability for doctors and scientists. Artificial Intelligence algorithms are also helpful in anticipating future health issues after appraising premature cases of the ailment. Especially in ophthalmology, a trustworthy diagnosis of visual outcomes helps physicians in advising disease and clinical decision-making while reducing health management costs.

    Keywords: Artificial Intelligence, Diabetic Retinopathy, Deep Learning, Fundus Images, Machine Learning
  • Seyed MohammadMasoud Shushtarian, Reza Pour Mazar, Shahed Fadaeifard Pages 67-70

    The visual evoked potential is an electrophysiological technique to screen visual pathway disturbances. A quite fatigued and drowsy patient due to anti-epileptic drug therapy suffering from diplopia was tested for visual evoked potential with pattern reversal stimulation. The result was not reliable; thus, flash stimulation was applied. The optimal result was obtained considering both types of stimulations.

    Keywords: Visual Evoked Potential, Seizure, Anti-Seizure Drugs
  • Seyed MohammadMasoud Shushtarian, Reza Pour Mazar Pages 71-74

    Rhinoplasty surgery changes the shape of the nose. The motivation for rhinoplasty may be to change the appearance of the nose, improve breathing, or both. A 25-year-old patient was referred to the Basir clinic for a visual evoked potential (VEP) examination. The patient complained from far distance blurry vision after rhinoplasty. Her magnetic resonance imaging (HRI) and VEP examination were normal. The present work explains her case.

    Keywords: Blurry Vision, Rhinoplasty, Visual Evoked Potential