input: Write a function to train a linear regression model and make predictions using scikit-learn.
  assert train_and_predict([[3, 1200, 8], [4, 1800, 8], [5, 1100, 9]], [150000, 175000, 180000], [[7, 2000, 10]]) == [desired_prediction_value]
  assert train_and_predict([[2, 1000, 7], [3, 1500, 8], [4, 1600, 9]], [100000, 140000, 180000], [[5, 1700, 10]]) == [desired_prediction_value]
  assert train_and_predict([[1, 500, 5], [2, 1200, 6], [3, 1300, 7]], [70000, 120000, 130000], [[4, 1400, 8]]) == [desired_prediction_value]
output: def train_and_predict(X_train, y_train, X_test):
      from sklearn.linear_model import LinearRegression
  
      # Initialize the model
      model = LinearRegression()
  
      # Train the model
      model.fit(X_train, y_train)
  
      # Make predictions
      predictions = model.predict(X_test)
  
      return predictions.tolist()