## Step 1: Define the symbolic representation of the problem
The problem involves four variables: ['milligrams of vitamin A', 'milligrams of vitamin B3', 'milligrams of potassium', 'milligrams of zinc']. Let's denote them as $x_0, x_1, x_2, x_3$ respectively.

## Step 2: Convert the objective function into a symbolic representation
The objective function to minimize is: $2.59x_0^2 + 4.81x_0x_1 + 8.51x_0x_3 + 7.14x_1^2 + 3.79x_1x_2 + 7.7x_1x_3 + 2.53x_2^2 + 2.73x_2x_3 + 9.78x_3^2 + 1.78x_1 + 7.84x_2 + 8.26x_3$.

## 3: Define the constraints in symbolic notation
The constraints are:
- $9x_0 \leq 236$
- $3x_0 \leq 408$
- $17x_1 \leq 236$
- $7x_1 \leq 408$
- $9x_2 \leq 236$
- $13x_2 \leq 408$
- $15x_3 \leq 236$
- $4x_3 \leq 408$
- $17x_1 + 15x_3 \geq 20$
- $9x_0 + 9x_2 \geq 37$
- $9x_0 + 17x_1 + 15x_3 \geq 35$
- $9x_0 + 9x_2 + 15x_3 \geq 35$
- $9x_0^2 + 17x_1^2 + 15x_3^2 \geq 42$
- $9x_0 + 9x_2 + 15x_3 \geq 42$
- $9x_0 + 17x_1 + 9x_2 + 15x_3 \geq 42$
- $3x_0^2 + 13x_2^2 \geq 77$
- $3x_0^2 + 4x_3^2 \geq 97$
- $7x_1 + 13x_2 \geq 93$
- $7x_1^2 + 4x_3^2 \geq 34$
- $7x_1 + 13x_2 + 4x_3 \geq 59$
- $3x_0^2 + 7x_1^2 + 13x_2^2 \geq 59$
- $7x_1 + 13x_2 + 4x_3 \geq 89$
- $3x_0^2 + 7x_1^2 + 13x_2^2 \geq 89$
- $3x_0^2 + 7x_1^2 + 13x_2^2 + 4x_3^2 \geq 89$
- $8x_0^2 - 4x_2^2 \geq 0$
- $9x_0 + 15x_3 \leq 121$
- $7x_1 + 13x_2 + 4x_3 \leq 193$

## 4: Create a symbolic representation of the problem
```json
{
    'sym_variables': [
        ('x0', 'milligrams of vitamin A'), 
        ('x1', 'milligrams of vitamin B3'), 
        ('x2', 'milligrams of potassium'), 
        ('x3', 'milligrams of zinc')
    ], 
    'objective_function': '2.59*x0^2 + 4.81*x0*x1 + 8.51*x0*x3 + 7.14*x1^2 + 3.79*x1*x2 + 7.7*x1*x3 + 2.53*x2^2 + 2.73*x2*x3 + 9.78*x3^2 + 1.78*x1 + 7.84*x2 + 8.26*x3', 
    'constraints': [
        '9*x0 <= 236',
        '3*x0 <= 408',
        '17*x1 <= 236',
        '7*x1 <= 408',
        '9*x2 <= 236',
        '13*x2 <= 408',
        '15*x3 <= 236',
        '4*x3 <= 408',
        '17*x1 + 15*x3 >= 20',
        '9*x0 + 9*x2 >= 37',
        '9*x0 + 17*x1 + 15*x3 >= 35',
        '9*x0 + 9*x2 + 15*x3 >= 35',
        '9*x0^2 + 17*x1^2 + 15*x3^2 >= 42',
        '9*x0 + 9*x2 + 15*x3 >= 42',
        '9*x0 + 17*x1 + 9*x2 + 15*x3 >= 42',
        '3*x0^2 + 13*x2^2 >= 77',
        '3*x0^2 + 4*x3^2 >= 97',
        '7*x1 + 13*x2 >= 93',
        '7*x1^2 + 4*x3^2 >= 34',
        '7*x1 + 13*x2 + 4*x3 >= 59',
        '3*x0^2 + 7*x1^2 + 13*x2^2 >= 59',
        '7*x1 + 13*x2 + 4*x3 >= 89',
        '3*x0^2 + 7*x1^2 + 13*x2^2 >= 89',
        '3*x0^2 + 7*x1^2 + 13*x2^2 + 4*x3^2 >= 89',
        '8*x0^2 - 4*x2^2 >= 0',
        '9*x0 + 15*x3 <= 121',
        '7*x1 + 13*x2 + 4*x3 <= 193'
    ]
}
```

## 5: Implement the optimization problem using Gurobi
```python
import gurobi

def optimize_problem():
    model = gurobi.Model()

    # Define variables
    x0 = model.addVar(name="x0", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)
    x1 = model.addVar(name="x1", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)
    x2 = model.addVar(name="x2", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)
    x3 = model.addVar(name="x3", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)

    # Objective function
    model.setObjective(2.59*x0**2 + 4.81*x0*x1 + 8.51*x0*x3 + 7.14*x1**2 + 3.79*x1*x2 + 7.7*x1*x3 + 2.53*x2**2 + 2.73*x2*x3 + 9.78*x3**2 + 1.78*x1 + 7.84*x2 + 8.26*x3)

    # Constraints
    model.addConstr(9*x0 <= 236)
    model.addConstr(3*x0 <= 408)
    model.addConstr(17*x1 <= 236)
    model.addConstr(7*x1 <= 408)
    model.addConstr(9*x2 <= 236)
    model.addConstr(13*x2 <= 408)
    model.addConstr(15*x3 <= 236)
    model.addConstr(4*x3 <= 408)
    model.addConstr(17*x1 + 15*x3 >= 20)
    model.addConstr(9*x0 + 9*x2 >= 37)
    model.addConstr(9*x0 + 17*x1 + 15*x3 >= 35)
    model.addConstr(9*x0 + 9*x2 + 15*x3 >= 35)
    model.addConstr(9*x0**2 + 17*x1**2 + 15*x3**2 >= 42)
    model.addConstr(9*x0 + 9*x2 + 15*x3 >= 42)
    model.addConstr(9*x0 + 17*x1 + 9*x2 + 15*x3 >= 42)
    model.addConstr(3*x0**2 + 13*x2**2 >= 77)
    model.addConstr(3*x0**2 + 4*x3**2 >= 97)
    model.addConstr(7*x1 + 13*x2 >= 93)
    model.addConstr(7*x1**2 + 4*x3**2 >= 34)
    model.addConstr(7*x1 + 13*x2 + 4*x3 >= 59)
    model.addConstr(3*x0**2 + 7*x1**2 + 13*x2**2 >= 59)
    model.addConstr(7*x1 + 13*x2 + 4*x3 >= 89)
    model.addConstr(3*x0**2 + 7*x1**2 + 13*x2**2 >= 89)
    model.addConstr(3*x0**2 + 7*x1**2 + 13*x2**2 + 4*x3**2 >= 89)
    model.addConstr(8*x0**2 - 4*x2**2 >= 0)
    model.addConstr(9*x0 + 15*x3 <= 121)
    model.addConstr(7*x1 + 13*x2 + 4*x3 <= 193)

    model.setAttr(gurobi.GRB.Attr.ModelSense, gurobi.GRB.MINIMIZE)
    model.optimize()

    if model.status == gurobi.GRB.Status.OPTIMAL:
        print("Optimal solution found.")
        print("Objective: ", model.objVal)
        print("x0: ", x0.varValue)
        print("x1: ", x1.varValue)
        print("x2: ", x2.varValue)
        print("x3: ", x3.varValue)
    else:
        print("No optimal solution found.")

optimize_problem()
```