## Step 1: Define the symbolic representation of the variables
The variables are 'milligrams of vitamin C', 'milligrams of vitamin A', and 'milligrams of vitamin B7'. Let's denote them as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Convert the natural language objects into symbolic notation
The symbolic representation of the variables is:
- $x_0$ : milligrams of vitamin C
- $x_1$ : milligrams of vitamin A
- $x_2$ : milligrams of vitamin B7

## 3: Define the objective function in symbolic notation
The objective function to maximize is $3.78x_0 + 3.66x_1 + 3.88x_2$.

## 4: Define the constraints in symbolic notation
The constraints are:
- $2x_0 \geq 12$ is not correct, it should be $2x_0 = 2$ (The kidney support index of milligrams of vitamin C is 2)
- $1x_0 \leq 113$ is not correct, it is not provided but $x_0$ has no upper bound from this, however $x_0$ has a muscle growth index of 1.
- $3x_1 \geq 0$ is not provided but we have $3x_1 \leq 52$ and $4x_1 \leq 113$ 
- $4x_1 \leq 113$ 
- $3x_2 \leq 52$ 
- $7x_2 \leq 113$ 
- $2x_0 + 3x_1 \geq 12$ (The total combined kidney support index from milligrams of vitamin C plus milligrams of vitamin A should be equal to or greater than 12)
- $4x_1 + 7x_2 \geq 35$ (The total combined muscle growth index from milligrams of vitamin A plus milligrams of vitamin B7 must be 35 at minimum)
- $3x_1 + 3x_2 \leq 48$ (The total combined kidney support index from milligrams of vitamin A, and milligrams of vitamin B7 must be no more than 48)
- $2x_0 + 3x_1 \leq 35$ (The total combined kidney support index from milligrams of vitamin C plus milligrams of vitamin A should be 35 at a maximum)
- $2x_0 + 3x_1 + 3x_2 \leq 35$ (The total combined kidney support index from milligrams of vitamin C, milligrams of vitamin A and milligrams of vitamin B7 has to be 35 at a maximum)
- $1x_0 + 4x_1 \leq 112$ (The total combined muscle growth index from milligrams of vitamin C plus milligrams of vitamin A must be less than or equal to 112)
- $1x_0 + 7x_2 \leq 79$ (The total combined muscle growth index from milligrams of vitamin C and milligrams of vitamin B7 has to be at most 79)
- $1x_0 + 4x_1 + 7x_2 \leq 79$ (The total combined muscle growth index from milligrams of vitamin C plus milligrams of vitamin A plus milligrams of vitamin B7 must be at most 79)
- $x_0$ is continuous
- $x_1$ is integer
- $x_2$ is continuous

## 5: Provide the symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x0', 'milligrams of vitamin C'), 
        ('x1', 'milligrams of vitamin A'), 
        ('x2', 'milligrams of vitamin B7')
    ], 
    'objective_function': '3.78*x0 + 3.66*x1 + 3.88*x2', 
    'constraints': [
        'x0 = 2',
        '2*x0 + 3*x1 >= 12',
        '4*x1 + 7*x2 >= 35',
        '3*x1 + 3*x2 <= 48',
        '2*x0 + 3*x1 <= 35',
        '2*x0 + 3*x1 + 3*x2 <= 35',
        'x0 + 4*x1 <= 112',
        'x0 + 7*x2 <= 79',
        'x0 + 4*x1 + 7*x2 <= 79'
    ]
}
```

## Step 6: Write the Gurobi code
```python
import gurobi

def solve_optimization_problem():
    # Create a new Gurobi model
    model = gurobi.Model()

    # Define the variables
    x0 = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="milligrams of vitamin C", vtype=gurobi.GRB.CONTINUOUS)
    x1 = model.addVar(lb=0, name="milligrams of vitamin A", vtype=gurobi.GRB.INTEGER)
    x2 = model.addVar(lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY, name="milligrams of vitamin B7", vtype=gurobi.GRB.CONTINUOUS)

    # Objective function
    model.setObjective(3.78 * x0 + 3.66 * x1 + 3.88 * x2, gurobi.GRB.MAXIMIZE)

    # Constraints
    model.addConstr(x0 == 2, name="kidney_support_index_vitamin_C")
    model.addConstr(2 * x0 + 3 * x1 >= 12, name="kidney_support_index_vitamin_C_and_A")
    model.addConstr(4 * x1 + 7 * x2 >= 35, name="muscle_growth_index_vitamin_A_and_B7")
    model.addConstr(3 * x1 + 3 * x2 <= 48, name="kidney_support_index_vitamin_A_and_B7")
    model.addConstr(2 * x0 + 3 * x1 <= 35, name="kidney_support_index_vitamin_C_and_A_max")
    model.addConstr(2 * x0 + 3 * x1 + 3 * x2 <= 35, name="kidney_support_index_all")
    model.addConstr(x0 + 4 * x1 <= 112, name="muscle_growth_index_vitamin_C_and_A")
    model.addConstr(x0 + 7 * x2 <= 79, name="muscle_growth_index_vitamin_C_and_B7")
    model.addConstr(x0 + 4 * x1 + 7 * x2 <= 79, name="muscle_growth_index_all")

    # Optimize the model
    model.optimize()

    # Print the solution
    if model.status == gurobi.GRB.OPTIMAL:
        print("Optimal solution found.")
        print(f"Milligrams of vitamin C: {x0.varValue}")
        print(f"Milligrams of vitamin A: {x1.varValue}")
        print(f"Milligrams of vitamin B7: {x2.varValue}")
        print(f"Objective function value: {model.objVal}")
    else:
        print("No optimal solution found.")

solve_optimization_problem()
```