Cup is essential for mRNA translational repression during early oogenesis.

Study of the timing and location for mRNA translation across model systems has begun to shed light on molecular events fundamental to such processes as intercellular communication, morphogenesis, and body pattern formation. In , the posterior mRNA determinant, , is transcribed maternally but translated only when properly localized at the oocyte's posterior cortex. Two effector proteins, Bruno1 and Cup, mediate steps of mRNA regulation.

Chimeric forecasting: combining probabilistic predictions from computational models and human judgment.

Forecasts of the trajectory of an infectious agent can help guide public health decision making. A traditional approach to forecasting fits a computational model to structured data and generates a predictive distribution. However, human judgment has access to the same data as computational models plus experience, intuition, and subjective data.

Aggregating Human Judgment Probabilistic Predictions of Coronavirus Disease 2019 Transmission, Burden, and Preventive Measures.

Aggregated human judgment forecasts for coronavirus disease 2019 (COVID-19) targets of public health importance are accurate, often outperforming computational models. Our work shows that aggregated human judgment forecasts for infectious agents are timely, accurate, and adaptable, and can be used as a tool to aid public health decision making during outbreaks.

Aggregating human judgment probabilistic predictions of COVID-19 transmission, burden, and preventative measures.

Aggregated human judgment forecasts for COVID-19 targets of public health importance are accurate, often outperforming computational models. Our work shows aggregated human judgment forecasts for infectious agents are timely, accurate, and adaptable, and can be used as tool to aid public health decision making during outbreaks.

Aggregating human judgment probabilistic predictions of the safety, efficacy, and timing of a COVID-19 vaccine.

Safe, efficacious vaccines were developed to reduce the transmission of SARS-CoV-2 during the COVID-19 pandemic. But in the middle of 2020, vaccine effectiveness, safety, and the timeline for when a vaccine would be approved and distributed to the public was uncertain. To support public health decision making, we solicited trained forecasters and experts in vaccinology and infectious disease to provide monthly probabilistic predictions from July to September of 2020 of the efficacy, safety, timing, and delivery of a COVID-19 vaccine.