```json
{
  "sym_variables": [
    ("x0", "milligrams of vitamin B5"),
    ("x1", "milligrams of vitamin B12")
  ],
  "objective_function": "5*x0 + 5*x1",
  "constraints": [
    "3*x0 + 32*x1 >= 32",
    "11*x0 + 10*x1 >= 36",
    "6*x0 + 8*x1 >= 28",
    "-10*x0 + 9*x1 >= 0",
    "3*x0 + 32*x1 <= 44",
    "11*x0 + 10*x1 <= 88",
    "6*x0 + 8*x1 <= 86"
  ]
}
```

```python
import gurobipy as gp

# Create a new model
m = gp.Model("vitamin_optimization")

# Create variables
vitamin_b5 = m.addVar(lb=0, name="vitamin_b5")  # milligrams of vitamin B5
vitamin_b12 = m.addVar(lb=0, name="vitamin_b12") # milligrams of vitamin B12

# Set objective function
m.setObjective(5 * vitamin_b5 + 5 * vitamin_b12, gp.GRB.MINIMIZE)

# Add constraints
m.addConstr(3 * vitamin_b5 + 32 * vitamin_b12 >= 32, "cardiovascular_min")
m.addConstr(11 * vitamin_b5 + 10 * vitamin_b12 >= 36, "cognitive_min")
m.addConstr(6 * vitamin_b5 + 8 * vitamin_b12 >= 28, "digestive_min")
m.addConstr(-10 * vitamin_b5 + 9 * vitamin_b12 >= 0, "custom_constraint")
m.addConstr(3 * vitamin_b5 + 32 * vitamin_b12 <= 44, "cardiovascular_max")
m.addConstr(11 * vitamin_b5 + 10 * vitamin_b12 <= 88, "cognitive_max")
m.addConstr(6 * vitamin_b5 + 8 * vitamin_b12 <= 86, "digestive_max")


# Optimize model
m.optimize()

# Print results
if m.status == gp.GRB.OPTIMAL:
    print('Optimal solution found:')
    print(f'Vitamin B5: {vitamin_b5.x}')
    print(f'Vitamin B12: {vitamin_b12.x}')
    print(f'Objective Value: {m.objVal}')
elif m.status == gp.GRB.INFEASIBLE:
    print('Model is infeasible.')
else:
    print(f'Optimization ended with status {m.status}.')

```
