Current and Future Drug Targets in Weight Management

Obesity will continue to be one of the leading causes of chronic disease unless the ongoing rise in the prevalence of this condition is reversed. Accumulating morbidity figures and a shortage of effective drugs have generated substantial research activity with several molecular targets being investigated. However, pharmacological modulation of body weight is extremely complex, since it is essentially a battle against one of the strongest human instincts and highly efficient mechanisms of energy uptake and storage. This review provides an overview of the different molecular strategies intended to lower body weight or adipose tissue mass. Weight-loss drugs in development include molecules intended to reduce the absorption of lipids from the GI tract, various ways to limit food intake, and compounds that increase energy expenditure or reduce adipose tissue size. A number of new preparations, including combinations of the existing drugs topiramate plus phentermine, bupropion plus naltrexone, and the selective 5-HT2C agonist lorcaserin have recently been filed for approval. Behind these leading candidates are several other potentially promising compounds and combinations currently undergoing phase II and III testing. Some interesting targets further on the horizon are also discussed

Redescription of Cestode Circumoncobothrium shindei in Freshwater Fish Mastacembelus armatus from Gangapur Dam Dist. Nasik (M.S) India

The study deals with the redescription of the Circumoncobothrium shindei (1977) in freshwater fish Mastacembelus armatus from Gangapur dam, Dist. Nasik. The scolex is large well developed, which is narrow anteriorly and broad posteriorly, the anterior end of the scolex is bluntly triangular. Gravid segment is broader then longer. Ovary is bilobed and dumbbell- shaped. Vitellaria are follicular arranged in 2-3 rows, eggs are operculated, oval in shape. As the characters are minor. It is redescribed here as Circumoncobothrium shindei, 1977.</jats:p

Hybrid forecasting of geopolitical events

Sound decision-making relies on accurate prediction for tangible outcomes ranging from military conflict to disease outbreaks. To improve crowdsourced forecasting accuracy, we developed SAGE, a hybrid forecasting system that combines human and machine generated forecasts. The system provides a platform where users can interact with machine models and thus anchor their judgments on an objective benchmark. The system also aggregates human and machine forecasts weighting both for propinquity and based on assessed skill while adjusting for overconfidence. We present results from the Hybrid Forecasting Competition (HFC)—larger than comparable forecasting tournaments—including 1085 users forecasting 398 real-world forecasting problems over 8 months. Our main result is that the hybrid system generated more accurate forecasts compared to a human-only baseline, which had no machine generated predictions. We found that skilled forecasters who had access to machine-generated forecasts outperformed those who only viewed historical data. We also demonstrated the inclusion of machine-generated forecasts in our aggregation algorithms improved performance, both in terms of accuracy and scalability. This suggests that hybrid forecasting systems, which potentially require fewer human resources, can be a viable approach for maintaining a competitive level of accuracy over a larger number of forecasting questions