To solve this optimization problem, we first need to translate the natural language description into a symbolic representation. Let's denote:

- $x_1$ as the amount invested in the film industry.
- $x_2$ as the amount invested in the healthcare industry.

The objective is to maximize the return on investment, which can be calculated as follows:
- The return from the film industry is $0.08x_1$ (8% of $x_1$).
- The return from the healthcare industry is $0.10x_2$ (10% of $x_2$).

Thus, the objective function to maximize is: $0.08x_1 + 0.10x_2$.

The constraints based on the problem description are:
1. The total amount invested cannot exceed $200,000: $x_1 + x_2 \leq 200,000$.
2. At least 25% of the investment must be in the film industry: $x_1 \geq 0.25(200,000)$, which simplifies to $x_1 \geq 50,000$.
3. No more than 60% of the investment can be in the healthcare industry: $x_2 \leq 0.60(200,000)$, which simplifies to $x_2 \leq 120,000$.
4. Non-negativity constraints: $x_1 \geq 0$ and $x_2 \geq 0$, since the amount invested cannot be negative.

Now, let's represent this problem symbolically:
```json
{
    'sym_variables': [('x1', 'amount invested in film industry'), ('x2', 'amount invested in healthcare industry')],
    'objective_function': '0.08*x1 + 0.10*x2',
    'constraints': ['x1 + x2 <= 200000', 'x1 >= 50000', 'x2 <= 120000', 'x1 >= 0', 'x2 >= 0']
}
```

To solve this problem using Gurobi in Python, we can use the following code:
```python
from gurobipy import *

# Create a model
m = Model("Investment_Optimization")

# Define variables
x1 = m.addVar(lb=0, name="film_investment")
x2 = m.addVar(lb=0, name="healthcare_investment")

# Set objective function
m.setObjective(0.08*x1 + 0.10*x2, GRB.MAXIMIZE)

# Add constraints
m.addConstr(x1 + x2 <= 200000, "total_investment")
m.addConstr(x1 >= 50000, "min_film_investment")
m.addConstr(x2 <= 120000, "max_healthcare_investment")

# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print("Invest in film industry: $", x1.x)
    print("Invest in healthcare industry: $", x2.x)
    print("Maximum return: $", m.objVal)
else:
    print("No optimal solution found")
```