To solve this optimization problem, we will first create a symbolic representation of the problem and then implement it in Gurobi.

The symbolic representation is as follows:
```json
{
  'sym_variables': [('x1', 'milligrams of vitamin A'), ('x2', 'milligrams of vitamin B5')],
  'objective_function': '2.09*x1 + 2.11*x2',
  'constraints': [
    '7*x1 + 22*x2 >= 13',
    '5*x1 + 26*x2 >= 45',
    '16*x1 + 26*x2 >= 37',
    '-7*x1 + 3*x2 >= 0',
    '7*x1 + 22*x2 <= 58',
    '5*x1 + 26*x2 <= 133',
    '16*x1 + 26*x2 <= 61'
  ]
}
```

Here's a brief explanation of the conversion:
- `x1` represents 'milligrams of vitamin A' and `x2` represents 'milligrams of vitamin B5'.
- The objective function is to minimize `2.09*x1 + 2.11*x2`, which corresponds to minimizing 2.09 times the number of milligrams of vitamin A added to 2.11 multiplied by the quantity of milligrams of vitamin B5.
- Constraints are directly translated from the problem description.

Now, let's implement this in Gurobi:

```python
from gurobipy import *

# Create a model
m = Model("Optimization_Problem")

# Add variables
x1 = m.addVar(vtype=GRB.INTEGER, name="milligrams_of_vitamin_A")
x2 = m.addVar(vtype=GRB.CONTINUOUS, name="milligrams_of_vitamin_B5")

# Set the objective function
m.setObjective(2.09*x1 + 2.11*x2, GRB.MINIMIZE)

# Add constraints
m.addConstr(7*x1 + 22*x2 >= 13, "cognitive_performance_index_min")
m.addConstr(5*x1 + 26*x2 >= 45, "kidney_support_index_min")
m.addConstr(16*x1 + 26*x2 >= 37, "cardiovascular_support_index_min")
m.addConstr(-7*x1 + 3*x2 >= 0, "mixed_constraint_1")
m.addConstr(7*x1 + 22*x2 <= 58, "cognitive_performance_index_max")
m.addConstr(5*x1 + 26*x2 <= 133, "kidney_support_index_max")
m.addConstr(16*x1 + 26*x2 <= 61, "cardiovascular_support_index_max")

# Optimize the model
m.optimize()

# Print the results
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Milligrams of Vitamin A: {x1.x}")
    print(f"Milligrams of Vitamin B5: {x2.x}")
    print(f"Objective Function Value: {m.objVal}")
else:
    print("No optimal solution found")
```