Vogt-Koyanagi-Harada Disease: Current Diagnosis and Management

Vogt-Koyanagi-Harada (VKH) disease is a rare granulomatous inflammatory disease that affects pigmented structures, such as eye, inner ear, meninges, skin, and hair. This disease is mainly a T1 lymphocyte-mediated aggression to melanocytes. The availability of new investigational methods has improved our knowledge of the pathogenesis, clinical approach, diagnosis, and management of VKH disease. The disease has an acute onset of bilateral blurred vision with hyperemia in the absence of prior ocular trauma or any previous intraocular surgery. The chronic phase comprises of ocular and integumentary system pigmentary changes. Ocular findings may be accompanied by meningismus, hearing impairment, and skin lesions in a variable proportion of patients. Prompt diagnosis with early, aggressive, and long-term treatment of high-dose corticosteroids ensures good visual outcomes. The aim of this chapter is to present the clinicopathology, classification, recent imaging, investigations, and management of VKH disease

A novel computational framework for deducing muscle synergies from experimental joint moments

Prior experimental studies have hypothesized the existence of a “muscle synergy” based control scheme for producing limb movements and locomotion in vertebrates. Such synergies have been suggested to consist of fixed muscle grouping schemes with the co-activation of all muscles in a synergy resulting in limb movement. Quantitative representations of these groupings (termed muscle weightings) and their control signals (termed synergy controls) have traditionally been derived by the factorization of experimentally measured EMG. This study presents a novel approach for deducing these weightings and controls from inverse dynamic joint moments that are computed from an alternative set of experimental measurements—movement kinematics and kinetics. This technique was applied to joint moments for healthy human walking at 0.7 and 1.7 m/s, and two sets of “simulated” synergies were computed based on two different criteria (1) synergies were required to minimize errors between experimental and simulated joint moments in a musculoskeletal model (pure-synergy solution) (2) along with minimizing joint moment errors, synergies also minimized muscle activation levels (optimal-synergy solution). On comparing the two solutions, it was observed that the introduction of optimality requirements (optimal-synergy) to a control strategy solely aimed at reproducing the joint moments (pure-synergy) did not necessitate major changes in the muscle grouping within synergies or the temporal profiles of synergy control signals. Synergies from both the simulated solutions exhibited many similarities to EMG derived synergies from a previously published study, thus implying that the analysis of the two different types of experimental data reveals similar, underlying synergy structures

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Language models demonstrate both quantitative improvement and new qualitative capabilities with increasing scale. Despite their potentially transformative impact, these new capabilities are as yet poorly characterized. In order to inform future research, prepare for disruptive new model capabilities, and ameliorate socially harmful effects, it is vital that we understand the present and near-future capabilities and limitations of language models. To address this challenge, we introduce the Beyond the Imitation Game benchmark (BIG- bench). BIG-bench currently consists of 204 tasks, contributed by 450 authors across 132 institutions. Task topics are diverse, drawing problems from linguistics, childhood develop- ment, math, common-sense reasoning, biology, physics, social bias, software development, and beyond. BIG-bench focuses on tasks that are believed to be beyond the capabilities of current language models. We evaluate the behavior of OpenAI's GPT models, Google- internal dense transformer architectures, and Switch-style sparse transformers on BIG-bench, across model sizes spanning millions to hundreds of billions of parameters. In addition, a team of human expert raters performed all tasks in order to provide a strong baseline. Findings include: model performance and calibration both improve with scale, but are poor in absolute terms (and when compared with rater performance); performance is remarkably similar across model classes, though with benefits from sparsity; tasks that improve gradually and predictably commonly involve a large knowledge or memorization component, whereas tasks that exhibit "breakthrough" behavior at a critical scale often involve multiple steps or components, or brittle metrics; social bias typically increases with scale in settings with ambiguous context, but this can be improved with prompting

Risk factors in patients with macular telangiectasia 2A in an Asian population: A case–control study

Purpose: The aim of this study was to evaluate risk factors in patients with macular telangiectasia (MacTel) 2A in an Asian population. This was a hospital-based case–control study. Methods: We reviewed the case records of patients in our hospital, diagnosed as MacTel 2A over a 3-year period from April 2011 to March 2014. Controls were selected from patients seen in the hospital at the same time for visual defects after matching for age and sex. A multivariate logistic regression model was constructed using the variables that showed a statistically significant association (P < 0.05) with MacTel 2A in the univariate analysis. Results: The mean age of the patients with MacTel 2A was 58.63 years. A majority (76; 73.8%) of the patients were female. Of the patients with MacTel 2A, 61 (59.2%) patients had diabetes mellitus, and 50 (48.5%) revealed hypertension. Multivariate logistic regression analysis revealed the presence of diabetes mellitus to be the risk factor with the highest odds ratio (OR) of 5.7 followed by hypertension with an OR of 2.6. Binary logistic regression showed hypermetropia to have a greater risk factor compared to emmetropia, OR 2.64. Conclusion: Our case–control study revealed that MacTel 2A is significantly associated with systemic diseases. Diabetes mellitus was found to have the strongest association with MacTel 2A, showing a high OR of 5.7. Systemic hypertension followed by an OR of 2.6. Compared to emmetropia, hypermetropia was significantly associated with MacTel 2A. There could be a genetic link between the two. Determining risk factors draws us close to the goal of identifying the etiopathogenesis of MacTel 2A