Triphala inhibits alpha-synuclein fibrillization and their interaction study by NMR provides insights into the self-association of the protein

The process of assembly and accumulation of the intrinsically disordered protein (IDP), alpha-synuclein (αSyn) into amyloid fibrils is a pathogenic process leading to several neurodegenerative disorders such as Parkinson''s disease, multiple system atrophy and others. Although several molecules are known to inhibit αSyn fibrillization, the mechanism of inhibition is just beginning to emerge. Here, we report the inhibition of fibrillization of αSyn by Triphala, a herbal preparation in the traditional Indian medical system of Ayurveda. Triphala was found to be a rich source of polyphenols which are known to act as amyloid inhibitors. ThT fluorescence and TEM studies showed that Triphala inhibited the fibrillization of αSyn. However, it was observed that Triphala does not disaggregate preformed αSyn fibrils. Further, native-PAGE showed that Triphala reduces the propensity of αSyn to oligomerize during the lag phase of fibrillization. Our NMR results showed that certain stretches of residues in the N-terminal and NAC regions of αSyn play an anchor role in the self-association process of the protein, thereby providing mechanistic insights into the early events during αSyn fibrillization.

Triphala inhibits αSyn self-association by interacting with anchoring regions which are responsible for αSyn oligomerization.     

Decision support system for age-related macular degeneration using discrete wavelet transform

Age-related macular degeneration (AMD) affects the central vision and subsequently may lead to visual loss in people over 60 years of age. There is no permanent cure for AMD, but early detection and successive treatment may improve the visual acuity. AMD is mainly classified into dry and wet type; however, dry AMD is more common in aging population. AMD is characterized by drusen, yellow pigmentation, and neovascularization. These lesions are examined through visual inspection of retinal fundus images by ophthalmologists. It is laborious, time-consuming, and resource-intensive. Hence, in this study, we have proposed an automated AMD detection system using discrete wavelet transform (DWT) and feature ranking strategies. The first four-order statistical moments (mean, variance, skewness, and kurtosis), energy, entropy, and Gini index-based features are extracted from DWT coefficients. We have used five (t test, Kullback–Lieber Divergence (KLD), Chernoff Bound and Bhattacharyya Distance, receiver operating characteristics curve-based, and Wilcoxon) feature ranking strategies to identify optimal feature set. A set of supervised classifiers namely support vector machine (SVM), decision tree, \(k\) -nearest neighbor ( \(k\) -NN), Naive Bayes, and probabilistic neural network were used to evaluate the highest performance measure using minimum number of features in classifying normal and dry AMD classes. The proposed framework obtained an average accuracy of 93.70 %, sensitivity of 91.11 %, and specificity of 96.30 % using KLD ranking and SVM classifier. We have also formulated an AMD Risk Index using selected features to classify the normal and dry AMD classes using one number. The proposed system can be used to assist the clinicians and also for mass AMD screening programs.     

Hla type as a predictor of mixed connective tissue disease differentiation ten-year clinical and immunogenetic followup of 46 patients

Objective. To determine any clinical or genetic markers of differentiation and outcome in a previously described cohort of 46 patients with mixed connective tissue disease (MCTD). Methods. Patients were clinically evaluated, chart notes reviewed, and HLA subtyping and immunology profiles performed where possible. Eleven had died and 7 were lost to followup. Results. MCTD had differentiated into systemic lupus erythematosus in 12 patients and into systemic sclerosis in 13. The latter was associated with HLA-DR5 (P = 0.038), and nondifferentiation was associated with HLA-DR2 or DR4 (P = 0.007). Three HLA-DR4 positive patients had MCTD that evolved into rheumatoid arthritis. Erosive and/or deforming arthritis was associated with HLA-DR1 or DR4 (P = 0.015). HLA-DR3 was associated with interstitial lung fibrosis (P = 0.044) and keratoconjunctivitis sicca (0.001 < P < 0.01). Severe Raynaud's phenomenon predicted higher mortality (0.01 < P < 0.05). Conclusion. We suggest that MCTD is, for most patients, an intermediate stage in a genetically determined progression to a recognized connective tissue disease. Those whose disease remains undifferentiated might be considered a distinct subset.     

Expression and shedding of intercellular adhesion molecule 1 and lymphocyte function–associated antigen 3 by normal and scleroderma fibroblasts.

Objective. To examine intercellular adhesion molecule 1 (ICAM-1) and lymphocyte function-associated antigen 3 (LFA-3) in cultures of normal and systemic sclerosis (SSc) dermal fibroblasts. Methods. The surface and soluble forms of ICAM-1 and LFA-3 were measured by flow cytometry and capture enzyme-linked immunosorbent assay, respectively. Results. Surface ICAM-1 was significantly higher on SSc fibroblasts compared with normal controls. β-estradiol did not directly enhance ICAM-1 or LFA-3 expression in either normal or SSc cells, but significantly augmented the cytokine-induced increase in ICAM-1. Soluble ICAM-1 (sICAM-1) and sLFA-3 were detected in fibroblast cultures. While no difference was found in the level of sLFA-3, the shedding of sICAM-1 was significantly increased (P < 0.001) in cells from SSc patients. Conclusion. SSc fibroblasts express intrinsically elevated levels of surface ICAM-1 and release higher levels of sICAM-1 in vitro. Increased expression of ICAM-1 by interferon-γ and tumor necrosis factor α alone, and the further induction in combination with β-estradiol may underlie an aspect of fibroblast dysfunction in SSc and the female predisposition to the disease.