Can we use Pandas apply method to calculate the Mean squared error

I was quite wondering if we can use the apply method on the Dataframe that has actual and predicted value to calculate Mean squared error for each row by using MSE from sklearn?

I was trying to use something like this.
mae_ = df.apply(MSE(df['actual_value'], df['predicted_value'] ))