Estimating pros and cons of statistical downscaling based on EQM bias adjustment as a complementary method to dynamical downscaling.

The increasing availability of coarse-scale climate simulations and the need for ready-to-use high-resolution variables drive the climate community to the challenge of reducing computational resources and time for downscaling purposes. To this end, statistical downscaling is gaining interest as a potential strategy for integrating high-resolution climate information obtained through dynamical downscaling over limited years, providing a clear understanding of the gains and losses in combining dynamical and statistical downscaling. In this regard, several questions can be raised: (i) what is the performance of statistical downscaling, assuming dynamical downscaling as a reference over a shared time window; (ii) how much the performance of statistical downscaling is affected by changes in the number of years available for training; (iii) how does the climate normal considered for the training affect the predictions.

Biosimilar versus originator etanercept: a real-life clinical study.

Background: Over the last few years, novel therapeutic approaches based on the use of monoclonal antibodies against cytokines, or their cognate receptors, involved in psoriasis progression have shown remarkable results, being capable to reduce disease progression and increase patient's quality of life. Among these is etanercept (Enbrel, Pfizer, Sandwich, UK) and its biosimilar compound SB4 (Benepali, Samsung Bioepis, Delft, The Netherlands), both approved for the treatment of moderate to severe psoriasis. Aim of the present study was to evaluate in a less controlled environment, such as real-life, the actual bioequivalence between the etanercept (ETN) and the SB4 in term of safety, efficacy and patient's quality of life.