## Step 1: Define the symbolic representation of the variables
The variables are ['milligrams of magnesium', 'milligrams of vitamin B4', 'milligrams of vitamin B5']. Let's denote them as $x_0$, $x_1$, and $x_2$ respectively.

## Step 2: Define the symbolic representation of the problem
The objective function to maximize is: $1x_0^2 + 9x_0x_1 + 8x_0x_2 + 5x_1^2 + 2x_1x_2 + 4x_2^2 + 3x_0 + 2x_1$.

## Step 3: List the constraints
The constraints are:
- $23x_0 = 23$ (immune support index of $x_0$)
- $18x_0 = 18$ (digestive support index of $x_0$)
- $10x_1 = 10$ (immune support index of $x_1$)
- $19x_1 = 19$ (digestive support index of $x_1$)
- $22x_2 = 22$ (immune support index of $x_2$)
- $17x_2 = 17$ (digestive support index of $x_2$)
- $23x_0 + 10x_1 + 22x_2 \geq 40$ (total combined immune support index)
- $18x_0 + 19x_1 + 17x_2 \geq 67$ (total combined digestive support index)
- $18^2x_0^2 + 17^2x_2^2 \geq 50$ (total combined digestive support index from $x_0^2$ and $x_2^2$)
- $-10x_0 + x_2 \geq 0$
- $23x_0 + 22x_2 \leq 116$ (total combined immune support index from $x_0$ and $x_2$)
- $10^2x_1^2 + 22^2x_2^2 \leq 76$ (total combined immune support index from $x_1^2$ and $x_2^2$)
- $23^2x_0^2 + 10^2x_1^2 \leq 85$ (total combined immune support index from $x_0^2$ and $x_1^2$)
- $23x_0 + 10x_1 + 22x_2 \leq 85$ (total combined immune support index from $x_0$, $x_1$, and $x_2$)
- $18^2x_0^2 + 17^2x_2^2 \leq 111$ (total combined digestive support index from $x_0^2$ and $x_2^2$)
- $18x_0 + 19x_1 \leq 231$ (total combined digestive support index from $x_0$ and $x_1$)
- $19x_1 + 17x_2 \leq 154$ (total combined digestive support index from $x_1$ and $x_2$)
- $18x_0 + 19x_1 + 17x_2 \leq 154$ (total combined digestive support index)

## 4: Convert the problem into Gurobi code
```python
import gurobi

# Define the model
model = gurobi.Model()

# Define the variables
x0 = model.addVar(name="milligrams_of_magnesium", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)
x1 = model.addVar(name="milligrams_of_vitamin_B4", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)
x2 = model.addVar(name="milligrams_of_vitamin_B5", lb=-gurobi.GRB.INFINITY, ub=gurobi.GRB.INFINITY)

# Objective function
model.setObjective(1*x0**2 + 9*x0*x1 + 8*x0*x2 + 5*x1**2 + 2*x1*x2 + 4*x2**2 + 3*x0 + 2*x1, gurobi.GRB.MAXIMIZE)

# Constraints
model.addConstr(23*x0 == 23, name="immune_support_index_magnesium")
model.addConstr(18*x0 == 18, name="digestive_support_index_magnesium")
model.addConstr(10*x1 == 10, name="immune_support_index_vitamin_B4")
model.addConstr(19*x1 == 19, name="digestive_support_index_vitamin_B4")
model.addConstr(22*x2 == 22, name="immune_support_index_vitamin_B5")
model.addConstr(17*x2 == 17, name="digestive_support_index_vitamin_B5")
model.addConstr(23*x0 + 10*x1 + 22*x2 >= 40, name="total_immune_support_index")
model.addConstr(18*x0 + 19*x1 + 17*x2 >= 67, name="total_digestive_support_index")
model.addConstr(18**2*x0**2 + 17**2*x2**2 >= 50, name="total_digestive_support_index_squared")
model.addConstr(-10*x0 + x2 >= 0, name="magnesium_vitamin_B5_constraint")
model.addConstr(23*x0 + 22*x2 <= 116, name="magnesium_vitamin_B5_immune_support")
model.addConstr(10**2*x1**2 + 22**2*x2**2 <= 76, name="vitamin_B4_vitamin_B5_immune_support_squared")
model.addConstr(23**2*x0**2 + 10**2*x1**2 <= 85, name="magnesium_vitamin_B4_immune_support_squared")
model.addConstr(23*x0 + 10*x1 + 22*x2 <= 85, name="total_immune_support_index_squared")
model.addConstr(18**2*x0**2 + 17**2*x2**2 <= 111, name="total_digestive_support_index_squared_2")
model.addConstr(18*x0 + 19*x1 <= 231, name="magnesium_vitamin_B4_digestive_support")
model.addConstr(19*x1 + 17*x2 <= 154, name="vitamin_B4_vitamin_B5_digestive_support")
model.addConstr(18*x0 + 19*x1 + 17*x2 <= 154, name="total_digestive_support_index_max")

# Optimize the model
model.optimize()

# Print the solution
print("Objective: ", model.objVal)
print("x0: ", x0.varValue)
print("x1: ", x1.varValue)
print("x2: ", x2.varValue)
```

## 5: Symbolic representation of the problem
```json
{
    "sym_variables": [
        ["x0", "milligrams of magnesium"],
        ["x1", "milligrams of vitamin B4"],
        ["x2", "milligrams of vitamin B5"]
    ],
    "objective_function": "1*x0^2 + 9*x0*x1 + 8*x0*x2 + 5*x1^2 + 2*x1*x2 + 4*x2^2 + 3*x0 + 2*x1",
    "constraints": [
        "23*x0 == 23",
        "18*x0 == 18",
        "10*x1 == 10",
        "19*x1 == 19",
        "22*x2 == 22",
        "17*x2 == 17",
        "23*x0 + 10*x1 + 22*x2 >= 40",
        "18*x0 + 19*x1 + 17*x2 >= 67",
        "18^2*x0^2 + 17^2*x2^2 >= 50",
        "-10*x0 + x2 >= 0",
        "23*x0 + 22*x2 <= 116",
        "10^2*x1^2 + 22^2*x2^2 <= 76",
        "23^2*x0^2 + 10^2*x1^2 <= 85",
        "23*x0 + 10*x1 + 22*x2 <= 85",
        "18^2*x0^2 + 17^2*x2^2 <= 111",
        "18*x0 + 19*x1 <= 231",
        "19*x1 + 17*x2 <= 154",
        "18*x0 + 19*x1 + 17*x2 <= 154"
    ]
}
```