To solve the given optimization problem using Gurobi, we first need to understand and possibly simplify or clarify the constraints provided. The objective function to maximize is \(1.18x_0 + 8.37x_1\), where \(x_0\) represents the milligrams of vitamin B9 and \(x_1\) represents the milligrams of vitamin B5.

Given constraints:
- Immune support index for vitamin B9: 7
- Energy stability index for vitamin B9: 14
- Digestive support index for vitamin B9: 4
- Immune support index for vitamin B5: 5
- Energy stability index for vitamin B5: 13
- Digestive support index for vitamin B5: 6
- Combined immune support index must be at least 31.
- Combined energy stability index must be at least 21.
- Combined digestive support index must be at least 42.
- \(-7x_0 + 8x_1 \geq 0\)
- Combined immune support index must be no more than 101.
- Combined energy stability index must be no more than 61.
- Combined digestive support index must be no more than 113.

The resources/attributes provided in the context seem to offer additional constraints but appear somewhat redundant or incorrectly specified, so we'll focus on the explicitly stated constraints for our model.

Here is how you can represent this problem in Gurobi:

```python
from gurobipy import *

# Create a new model
m = Model("Vitamin_Optimization")

# Define variables
x0 = m.addVar(lb=0, name="milligrams_of_vitamin_B9")  # Vitamin B9
x1 = m.addVar(lb=0, name="milligrams_of_vitamin_B5")  # Vitamin B5

# Objective function: Maximize 1.18*x0 + 8.37*x1
m.setObjective(1.18*x0 + 8.37*x1, GRB.MAXIMIZE)

# Constraints
# Combined immune support index must be at least 31 and no more than 101
m.addConstr(7*x0 + 5*x1 >= 31, name="immune_support_min")
m.addConstr(7*x0 + 5*x1 <= 101, name="immune_support_max")

# Combined energy stability index must be at least 21 and no more than 61
m.addConstr(14*x0 + 13*x1 >= 21, name="energy_stability_min")
m.addConstr(14*x0 + 13*x1 <= 61, name="energy_stability_max")

# Combined digestive support index must be at least 42 and no more than 113
m.addConstr(4*x0 + 6*x1 >= 42, name="digestive_support_min")
m.addConstr(4*x0 + 6*x1 <= 113, name="digestive_support_max")

# Additional constraint: -7x0 + 8x1 >= 0
m.addConstr(-7*x0 + 8*x1 >= 0, name="additional_constraint")

# Optimize model
m.optimize()

# Print solution
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Milligrams of Vitamin B9: {x0.x}")
    print(f"Milligrams of Vitamin B5: {x1.x}")
    print(f"Objective Function Value: {m.objVal}")
else:
    print("No optimal solution found")
```