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Diabetes has become one of the common health issues in people of all age groups. The disease is responsible for many difficulties in lifestyle and is represented by imbalance in hyperglycemia. If kept untreated, diabetes can raise the chance of heart attack, diabetic nephropathy, and other disorders. Early diagnosis of diabetes helps to maintain a healthy lifestyle. Machine learning is a capability of machine to learn from past pattern and occurrences and converge with experience to optimise and give decision. In the current research, the authors have employed machine learning techniques and used multi-criteria decision-making approach in Pima Indian diabetes dataset. To classify the patients, they examined several different supervised and unsupervised predictive models. After detailed analysis, it has been observed that the supervised learning algorithms outweigh the unsupervised algorithms due to the output class being a nominal classified domain.

Aims of Study: 1. To determine the choroidal thickness CT in eyes of subjects with high refractive errors, using SD-OCT.; 2. To correlate the CT with the refractive error and the axial length in these eyes. Materials and Methods: In this cross-sectional observational study 87 subjects with high myopia, i.e., spherical equivalents (SE) >-6.0D and high hypermetropia, i.e., SE> +3.0 D, aged between 5 to 50 years and with a best-corrected visual acuity (BCVA) of 6/9 or better, were included. In each eye, the CT was measured using SD-OCT scanning at seven retinal points, i.e., subfovea and 0.5 mm, 1.0 mm and 1.5 mm nasal as well as temporal to the fovea. Results: The CT in high myopic eyes was significantly less and in high hypermetropic eyes significantly more than in the controls, with the thinnest choroid present 1.5 mm nasal to the fovea in high myopic eyes and the thickest choroid present subfoveally in high hypermetropic eyes. The subfoveal CT in high myopic eyes had the strongest positive correlation with the SE of refractive error. In high hypermetropic eyes, the strongest positive correlation was found 1.5 mm temporal to the fovea, the point that also showed the strongest negative correlation between the axial length (AL) and the CT. Conclusions: High myopic eyes, i.e., with SE>-6D, have significantly thinner choroids than emmetropes. The CT decreases with an increase in the degree of myopia. High hypermetropes (i.e., SE > + 3 D) have significantly thicker choroids than emmetropes. Higher degrees of hypermetropia and shorter eyeballs are associated with thicker choroids. Keywords: Choroidal thickness, High myopia, High hypermetropia, Optical coherence tomography.

Acute spinal cord injury (SCI) results in catastrophic neurological impairment. We aimed to examine the temporal profile and severity correlation of biomarkers, and their relationship with the American Spinal Injury Association Scale (AIS) improvement in human SCI. 15 SCI and 10 non-SCI healthy subjects were classified according to the initial and discharge AIS grade. Serial cerebrospinal fluid (CSF) and serum samples were collected. Spectrin breakdown products (SBDP) 150, SBDP145, glial fibrillary acidic protein (GFAP), and GFAP breakdown product (GBDP) 38/44K were found to be elevated in the acute phase CSF samples in SCI patients on immunoblotting. SBDP150, ubiquitin C-terminal hydrolase-L1 (UCH-L1), GFAP, S100B, neurofilament light chain protein (NF-L), Tau & interleukin (IL) -6 were elevated in the acute phase CSF and serum samples on ELISA. CSF SBDP150, UCH-L1, GFAP, S100B and Tau were seen to peak on day 1 after injury, while CSF IL-6 and NF-L peaked on day 5. Serum SBDP150, IL-6, S100B, GFAP, UCHL-1 and Tau peaked on day 1, while serum NF-L peaked on day 5 post-injury. CSF alpha II-spectrin, SBDP150/145, and GBDP 44-38K levels (by immunoblots), CSF SBDP150, S100B, GFAP, UCHL-1 and Tau (ELISA) and serum UCHL-1 and Tau (ELISA) at specific time points showed SCI severity-correlation. CSF SBDP150, GFAP, and Tau and serum UCHL-1 and Tau (ELISA) were seen to have the best correlation with the severity at discharge. Receiver Operating Characteristic Curve analysis showed that CSF and serum biomarkers (SBDP150, IL-6, S100B, GFAP, NF-L, UCHL-1 and Tau) were associated with the severity of SCI.

To determine macular and choroidal thickness in healthy north Indian eyes and determine its variation with age and height using SD-OCT. The macula of 400 randomly selected healthy subjects (800 eyes) with no retinal and choroidal pathology was imaged with Cirrus SD-OCT. Macular thickness from all 9 regions of Early Treatment Diabetic Retinopathy Study was evaluated. Choroid was visualized by enhanced depth imaging technique. Choroidal thickness was measured sub foveally and at 500 microns intervals upto 1500 microns temporal and nasal to the fovea. The mean age of the subjects was 33.60 years ± 14.033 and mean height was 163.5 cms ± 11.715. Mean central macular thickness (CMT) was 242.59 µm ± 16.802 and mean sub foveal choroidal thickness was 325.18 µm ± 47.087. CMT correlated significantly (Pearson’s correlation coefficient) with age (r=0.120, p