Capabilities of deep learning models on learning physical relationships: Case of rainfall-runoff modeling with LSTM.

This study investigates the relationships which deep learning methods can identify between the input and output data. As a case study, rainfall-runoff modeling in a snow-dominated watershed by means of a long short-term memory (LSTM) network is selected. Daily precipitation and mean air temperature were used as model input to estimate daily flow discharge.

Protective function of SLC30A10 induced via PERK-ATF4 pathway against 1-methyl-4-phenylpyridinium.

Solute carrier family 30 member 10 (SLC30A10) has been known as manganese transporter. It has been suggested that neurodegenerative diseases are related with cellular stress such as oxidative stress or endoplasmic reticulum (ER) stress. However, it remains unknown whether SLC30A10 is actually involved in several intracellular stress.

Protective roles of SLC30A3 against endoplasmic reticulum stress via ERK1/2 activation.

Endoplasmic reticulum (ER) stress has been thought to be involved to neurodegenerative diseases such as Alzheimer's disease (AD) or Amyotrophic lateral sclerosis (ALS). The previous studies have shown that SLC30A3 level is decreased in prefrontal cortex of AD patients. In addition, we have shown that level of zinc (Zn) is increased in cerebrospinal fluid and SLC30A3 level is decreased in spinal cord of ALS patients.