Thoracic myelopathy due to ossified hypertrophied ligamentum flavum

Calcification of ligamentum flavum is a rare disease that was found to occur almost exclusively in Japanese population. However the disease is now being increasingly recognized as a cause of thoracic myeloradiculopathy in Indian Population. We report a case of thoracic myelopathy at multiple levels due to ossified and hypertrophied ligamentum flavum

Licofelone in osteoarthritis: is this the awaited drug? a systematic review

Osteoarthritis is a progressive joint disease associated with aging in elderly is, characterized by pain, inflammation, and difficulty in movement. The pathways involved in the progression of this disease remain unclear. The mediators, eicosanoids and leukotrienes are produced by COX-1/COX-2 or 5-LOX. Physicians have always used nonsteroidal anti-inflammatory drugs to treat the pain associated with osteoarthritis. A competitive inhibitor of LOX-5 and COX-2 that has both analgesic and anti-inflammatory activity is licofelone; one of the most promising candidates for the treatment of osteoarthritis is under clinical trial in treatment. A significant reduction in cartilage volume was displayed. A significant improvement over baseline on the WOMAC index and GI tolerance was also observed. Improving the symptoms related pain sensation with a happier life. With new strategies in OA, new methods to target pain, inflammation and movement restrictions would be the ultimate goal in patient satisfaction for the future. Licofelone was found to be effective compared to NSAIDs or coxibs in the treatment of OA. Does this mean this could be the answer

Attending to Discriminative Certainty for Domain Adaptation

In this paper, we aim to solve for unsupervised domain adaptation of classifiers where we have access to label information for the source domain while these are not available for a target domain. While various methods have been proposed for solving these including adversarial discriminator based methods, most approaches have focused on the entire image based domain adaptation. In an image, there would be regions that can be adapted better, for instance, the foreground object may be similar in nature. To obtain such regions, we propose methods that consider the probabilistic certainty estimate of various regions and specify focus on these during classification for adaptation. We observe that just by incorporating the probabilistic certainty of the discriminator while training the classifier, we are able to obtain state of the art results on various datasets as compared against all the recent methods. We provide a thorough empirical analysis of the method by providing ablation analysis, statistical significance test, and visualization of the attention maps and t-SNE embeddings. These evaluations convincingly demonstrate the effectiveness of the proposed approach.Comment: CVPR 2019 Accepted, Project: https://delta-lab-iitk.github.io/CADA