To solve this optimization problem using Gurobi, we first need to define the variables, the objective function, and all the constraints as described. The problem involves four variables: milligrams of vitamin B7 (\(x_0\)), grams of fat (\(x_1\)), milligrams of vitamin K (\(x_2\)), and milligrams of vitamin B2 (\(x_3\)).

The objective function to minimize is:
\[ 9x_0 + x_1 + 4x_2 + 6x_3 \]

## Step 1: Define the Variables
We start by defining the variables \(x_0, x_1, x_2, x_3\).

## Step 2: Define the Objective Function
The objective function is \( 9x_0 + x_1 + 4x_2 + 6x_3 \).

## Step 3: Define the Constraints
We need to define all the constraints based on the given problem description.

### Constraints for Individual Variables
- \( 6x_0 + 5x_1 + 5x_2 + 6x_3 \leq 195 \) (cardiovascular support index)
- \( 2x_0 + 12x_1 + 13x_2 + 11x_3 \leq 140 \) (kidney support index)
- \( 2x_0 + 8x_1 + 3x_2 + 5x_3 \leq 87 \) (cognitive performance index)

### Constraints for Combinations of Variables
- \( 5x_1 + 6x_3 \geq 39 \)
- \( 5x_1 + 5x_2 \geq 19 \)
- \( 6x_0 + 5x_1 \geq 27 \)
- \( 6x_0 + 5x_2 \geq 22 \)
- \( 5x_2 + 6x_3 \geq 18 \)
- \( 6x_0 + 5x_1 + 6x_3 \geq 33 \)
- \( 6x_0 + 5x_1 + 5x_2 + 6x_3 \geq 33 \)
- \( 2x_0 + 13x_2 \geq 25 \)
- \( 12x_1 + 11x_3 \geq 22 \)
- \( 13x_2 + 11x_3 \geq 34 \)
- \( 12x_1 + 13x_2 \geq 21 \)
- \( 2x_0 + 12x_1 + 11x_3 \geq 35 \)
- \( 2x_0 + 13x_2 + 11x_3 \geq 21 \)
- \( 2x_0 + 12x_1 + 13x_2 \geq 21 \)
- \( 2x_0 + 12x_1 + 11x_3 \geq 17 \)
- \( 2x_0 + 13x_2 + 11x_3 \geq 17 \)
- \( 2x_0 + 12x_1 + 13x_2 \geq 17 \)
- \( 2x_0 + 12x_1 + 11x_3 \geq 35 \)
- \( 2x_0 + 13x_2 + 11x_3 \geq 35 \)
- \( 2x_0 + 12x_1 + 13x_2 \geq 35 \)
- \( 2x_0 + 12x_1 + 13x_2 + 11x_3 \geq 35 \)
- \( 2x_0 + 3x_2 \geq 21 \)
- \( 8x_1 + 3x_2 \geq 20 \)
- \( 2x_0 + 5x_3 \geq 16 \)
- \( 8x_1 + 5x_3 \geq 17 \)
- \( 2x_0 + 8x_1 \geq 20 \)
- \( 2x_0 + 8x_1 + 3x_2 + 5x_3 \geq 20 \)
- \( 6x_1 - 9x_3 \geq 0 \)
- \( 6x_0 + 6x_3 \leq 156 \)
- \( 5x_1 + 6x_3 \leq 139 \)
- \( 5x_2 + 6x_3 \leq 167 \)
- \( 6x_0 + 5x_1 \leq 104 \)
- \( 6x_0 + 5x_2 \leq 161 \)
- \( 5x_1 + 5x_2 \leq 177 \)
- \( 5x_1 + 5x_2 + 6x_3 \leq 123 \)
- \( 2x_0 + 5x_3 \leq 86 \)
- \( 3x_2 + 5x_3 \leq 23 \)
- \( 2x_0 + 8x_1 \leq 63 \)
- \( 8x_1 + 3x_2 \leq 57 \)
- \( 8x_1 + 5x_3 \leq 87 \)
- \( 2x_0 + 3x_2 \leq 64 \)
- \( 2x_0 + 3x_2 + 5x_3 \leq 45 \)
- \( 2x_0 + 8x_1 + 3x_2 \leq 66 \)

## Step 4: Implement in Gurobi
```python
import gurobi

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

    # Define variables
    x0 = model.addVar(lb=-gurobi.GRB.INFINITY, name="milligrams of vitamin B7")
    x1 = model.addVar(lb=-gurobi.GRB.INFINITY, name="grams of fat")
    x2 = model.addVar(lb=-gurobi.GRB.INFINITY, name="milligrams of vitamin K")
    x3 = model.addVar(lb=-gurobi.GRB.INFINITY, name="milligrams of vitamin B2")

    # Objective function
    model.setObjective(9 * x0 + x1 + 4 * x2 + 6 * x3, gurobi.GRB.MINIMIZE)

    # Constraints
    # Individual Variables
    model.addConstr(6 * x0 + 5 * x1 + 5 * x2 + 6 * x3 <= 195)
    model.addConstr(2 * x0 + 12 * x1 + 13 * x2 + 11 * x3 <= 140)
    model.addConstr(2 * x0 + 8 * x1 + 3 * x2 + 5 * x3 <= 87)

    # Combination Constraints
    model.addConstr(5 * x1 + 6 * x3 >= 39)
    model.addConstr(5 * x1 + 5 * x2 >= 19)
    model.addConstr(6 * x0 + 5 * x1 >= 27)
    model.addConstr(6 * x0 + 5 * x2 >= 22)
    model.addConstr(5 * x2 + 6 * x3 >= 18)
    model.addConstr(6 * x0 + 5 * x1 + 6 * x3 >= 33)
    model.addConstr(6 * x0 + 5 * x1 + 5 * x2 + 6 * x3 >= 33)
    model.addConstr(2 * x0 + 13 * x2 >= 25)
    model.addConstr(12 * x1 + 11 * x3 >= 22)
    model.addConstr(13 * x2 + 11 * x3 >= 34)
    model.addConstr(12 * x1 + 13 * x2 >= 21)
    model.addConstr(2 * x0 + 12 * x1 + 11 * x3 >= 35)
    model.addConstr(2 * x0 + 13 * x2 + 11 * x3 >= 21)
    model.addConstr(2 * x0 + 12 * x1 + 13 * x2 >= 21)
    model.addConstr(2 * x0 + 12 * x1 + 11 * x3 >= 17)
    model.addConstr(2 * x0 + 13 * x2 + 11 * x3 >= 17)
    model.addConstr(2 * x0 + 12 * x1 + 13 * x2 >= 17)
    model.addConstr(2 * x0 + 12 * x1 + 11 * x3 >= 35)
    model.addConstr(2 * x0 + 13 * x2 + 11 * x3 >= 35)
    model.addConstr(2 * x0 + 12 * x1 + 13 * x2 >= 35)
    model.addConstr(2 * x0 + 12 * x1 + 13 * x2 + 11 * x3 >= 35)
    model.addConstr(2 * x0 + 3 * x2 >= 21)
    model.addConstr(8 * x1 + 3 * x2 >= 20)
    model.addConstr(2 * x0 + 5 * x3 >= 16)
    model.addConstr(8 * x1 + 5 * x3 >= 17)
    model.addConstr(2 * x0 + 8 * x1 >= 20)
    model.addConstr(2 * x0 + 8 * x1 + 3 * x2 + 5 * x3 >= 20)
    model.addConstr(6 * x1 - 9 * x3 >= 0)
    model.addConstr(6 * x0 + 6 * x3 <= 156)
    model.addConstr(5 * x1 + 6 * x3 <= 139)
    model.addConstr(5 * x2 + 6 * x3 <= 167)
    model.addConstr(6 * x0 + 5 * x1 <= 104)
    model.addConstr(6 * x0 + 5 * x2 <= 161)
    model.addConstr(5 * x1 + 5 * x2 <= 177)
    model.addConstr(5 * x1 + 5 * x2 + 6 * x3 <= 123)
    model.addConstr(2 * x0 + 5 * x3 <= 86)
    model.addConstr(3 * x2 + 5 * x3 <= 23)
    model.addConstr(2 * x0 + 8 * x1 <= 63)
    model.addConstr(8 * x1 + 3 * x2 <= 57)
    model.addConstr(8 * x1 + 5 * x3 <= 87)
    model.addConstr(2 * x0 + 3 * x2 <= 64)
    model.addConstr(2 * x0 + 3 * x2 + 5 * x3 <= 45)
    model.addConstr(2 * x0 + 8 * x1 + 3 * x2 <= 66)

    model.optimize()

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

optimize_problem()
```