Background: The sensitivity and specificity of 18S rRNA polymerase chain reaction (PCR) in the detection of fungal aetiology of microbial keratitis was determined in thirty patients with clinical diagnosis of microbial keratitis. Methods: Corneal scrapings from patients were used for Gram stain, culture and PCR analysis. PCR was performed with primer pairs targeted to the 18S rRNA gene. The result of the PCR was compared with conventional culture and Gram staining method. The PCR positive samples were identified by DNA sequencing of the internal transcribed spacer (ITS) region of the rRNA gene. Main outcome measures were sensitivity and specificity of PCR in the detection of fungus in corneal keratitis. Results: Combination of microscopy and culture gave a positive result in 11 of 30 samples of microbial keratitis. PCR detected 10 of 11 samples that were positive by conventional method. One of the 19 samples that was negative by conventional method was positive by PCR. Statistical analysis revealed that the PCR to have a sensitivity of 90.9% and specificity of 94.7% in the detection of a fungal aetiology in microbial keratitis. Conclusion: PCR is a rapid, sensitive and useful method to detect fungal aetiology in microbial keratitis.

Background: Alkali injury is one of the most devastating injuries to the eye. It results in permanent unilateral or bilateral visual impairment. Chemical eye injury is accompanied by an increase in the oxidative stress. Anti-inflammatory and antioxidant agents play a major role in the treatment of chemical eye injuries. The purpose of this study is to evaluate the anti-inflammatory (clinical and histopathological) and antioxidant effects of Tualang honey versus conventional treatment in alkali injury on the eyes of rabbits. Methods: A preliminary study was carried out prior to the actual study to establish the alkali chemical injury on rabbit's cornea and we found that alkali chemical injury with 2 N NaOH showed severe clinical inflammatory features. In actual study, alkali injury with 2 N NaOH was induced in the right eye of 10 New Zealand White rabbits' cornea. The rabbits were divided into two groups, Group A was given conventional treatment and Group B was treated with both topical and oral Tualang honey. Clinical inflammatory features of the right eye were recorded at 12 hours, 24 hours, 72 hours, 5^th day and 7^th day post induction of alkali burn on the cornea. The histopathological inflammatory features of the right corneas of all rabbits were also evaluated on day-7. The level of total antioxidant status and lipid peroxidation products in the aqueous humour, vitreous humour and serum at day-7 were estimated biochemically. Fisher's Exact, Chi-Square and Mann-Whitney test were used to analyse the data. Results: There was no statistically significant difference in clinical inflammatory features (p > 0.05) between honey treated and the conventional treated group at different times of examination. Histopathological examination of the cornea showed the number of polymorphonuclear leucocytes was below 50 for both groups (mild grade). There was also no significant difference in the level of total antioxidant status as well as lipid peroxidation products in aqueous humour (p = 0.117, p = 0.382 respectively), vitreous humour (p = 0.917, p = 0.248 respectively) and serum (p = 0.917, p = 0.332 respectively) between honey treated and the conventional treated group. Conclusion: Tualang honey has almost the equal effects when compared with the conventional treatment in treating alkali injury on rabbit's eye. Future research with more number of rabbits and control group is warranted to explore the anti-inflammatory and antioxidant effects of Tualang honey.

Optometrists, ophthalmologists, orthoptists, and other trained medical professionals use fundus photography to monitor the progression of certain eye conditions or diseases. Segmentation of the vessel tree is an essential process of retinal analysis. In this paper, an interactive blood vessel segmentation from retinal fundus image based on Canny edge detection is proposed. Semi-automated segmentation of specific vessels can be done by simply moving the cursor across a particular vessel. The pre-processing stage includes the green color channel extraction, applying Contrast Limited Adaptive Histogram Equalization (CLAHE), and retinal outline removal. After that, the edge detection techniques, which are based on the Canny algorithm, will be applied. The vessels will be selected interactively on the developed graphical user interface (GUI). The program will draw out the vessel edges. After that, those vessel edges will be segmented to bring focus on its details or detect the abnormal vessel. This proposed approach is useful because different edge detection parameter settings can be applied to the same image to highlight particular vessels for analysis or presentation.

Proliferative Diabetic Retinopathy (PDR) is a severe retinal disease that threatens diabetic patients. It is characterized by neovascularization in the retina and the optic disk. PDR clinical features contain highly intense retinal neovascularization and fibrous spreads, leading to visual distortion if not controlled. Different image processing techniques have been proposed to detect and diagnose neovascularization from fundus images. Recently, deep learning methods are getting popular in neovascularization detection due to artificial intelligence advancement in biomedical image processing. This paper presents a semantic segmentation convolutional neural network architecture for neovascularization detection. First, image pre-processing steps were applied to enhance the fundus images. Then, the images were divided into small patches, forming a training set, a validation set, and a testing set. A semantic segmentation convolutional neural network was designed and trained to detect the neovascularization regions on the images. Finally, the network was tested using the testing set for performance evaluation. The proposed model is entirely automated in detecting and localizing neovascularization lesions, which is not possible with previously published methods. Evaluation results showed that the model could achieve accuracy, sensitivity, specificity, precision, Jaccard similarity, and Dice similarity of 0.9948, 0.8772, 0.9976, 0.8696, 0.7643, and 0.8466, respectively. We demonstrated that this model could outperform other convolutional neural network models in neovascularization detection.

Detection of vascular endothelial growth factor (VEGF) levels in ocular tissue may perhaps provide insight into the role of VEGF in the pathogenesis and progression of diabetic retinopathy (DR). The aim of this study was to evaluate the levels of VEGF in tears and serum amongst type 2 diabetes mellitus (DM) patients. A comparative cross-sectional study was conducted between August 2016 and May 2018 involving type 2 DM patients with no DR, non-proliferative DR (NPDR), and proliferative DR (PDR). Tear samples were collected using no.41 Whatman filter paper (Schirmer strips) and 5 mL blood samples were drawn by venous puncture. VEGF levels in tears and serum were measured by enzyme-linked immunosorbent assay. A total of 88 type 2 DM patients (no DR: 30 patients, NPDR: 28 patients, PDR: 30 patients) were included in the study. Mean tear VEGF levels were significantly higher in the NPDR and PDR groups (114.4 SD 52.5 pg/mL and 150.8 SD 49.7 pg/mL, respectively) compared to the no DR group (40.4 SD 26.5 pg/mL, p < 0.001). There was no significant difference in the mean serum VEGF levels between the three groups. There was a fair correlation between serum and tear VEGF levels (p = 0.015, r = 0.263). VEGF levels in tears were significantly higher amongst diabetic patients with DR compared to those without DR and were significantly associated with the severity of DR. There was a fair correlation between serum and tear VEGF levels. Detection of VEGF in tears is a good non-invasive predictor test for the severity of DR. A large cohort study is needed for further evaluation.

The purpose of this study is to determine the prevalence of falls and its associated factors among elderly diabetes type 2 patients attending a tertiary center in Malaysia. We conducted a cross-sectional study among 288 elderly diabetes type 2. The data collected includes data on sociodemographic, diabetes history, comorbid diseases, drug use, and activity of daily living (Barthel’s index). The patient also was examined physically, and balance and gait assessment was carried out. Prevalence of falls among elderly diabetes was 18.8%. Female gender (OR: 2.54,P<0.05), age group more than 75 (OR: 2.97,P<0.05), retinopathy (OR: 2.19,P<0.05), and orthostatic hypotension (OR: 2.87,P<0.05) were associated with higher risk for falls. High balance and gait score was associated with reduced risk of fall in elderly diabetes (OR: 0.89,P<0.05). In conclusion, the factors that are associated with higher risk for falls among elderly diabetes were female sex, age group more than 75, presence of retinopathy, and orthostatic hypotension. Those who had higher balance and gait score were found to be less likely to fall compared with those with lower score.