The provided information gives us the coefficients for the objective function and the constraints.  We can use this to formulate the linear program in Gurobi. Redundant constraints (e.g., multiple constraints expressing the same upper bound) are combined for conciseness.

```python
import gurobipy as gp
from gurobipy import GRB

try:
    # Create a new model
    m = gp.Model("nutrition_optimization")

    # Create variables
    x0 = m.addVar(name="milligrams of vitamin B3")  # Vitamin B3
    x1 = m.addVar(name="grams of fiber")  # Fiber

    # Set objective function
    m.setObjective(9.44 * x0 + 6.86 * x1, GRB.MAXIMIZE)

    # Add constraints
    m.addConstr(3 * x0 + 2 * x1 >= 17, "digestive_support_lower")
    m.addConstr(4 * x0 + 5 * x1 >= 12, "kidney_support_lower")
    m.addConstr(2 * x0 + 1 * x1 >= 15, "cognitive_performance_lower")
    m.addConstr(1 * x0 + 3 * x1 >= 2, "muscle_growth_lower")
    m.addConstr(3 * x0 + 3 * x1 >= 8, "immune_support_lower")
    m.addConstr(5 * x0 - 3 * x1 >= 0, "custom_constraint")

    m.addConstr(3 * x0 + 2 * x1 <= 34, "digestive_support_upper") # Combined redundant constraints
    m.addConstr(4 * x0 + 5 * x1 <= 34, "kidney_support_upper") # Combined redundant constraints
    m.addConstr(2 * x0 + 1 * x1 <= 44, "cognitive_performance_upper") # Combined redundant constraints
    m.addConstr(1 * x0 + 3 * x1 <= 10, "muscle_growth_upper") # Combined redundant constraints
    m.addConstr(3 * x0 + 3 * x1 <= 20, "immune_support_upper") # Combined redundant constraints


    # Optimize model
    m.optimize()

    # Print results
    if m.status == GRB.OPTIMAL:
        print(f"Optimal objective value: {m.objVal}")
        print(f"Milligrams of vitamin B3: {x0.x}")
        print(f"Grams of fiber: {x1.x}")
    elif m.status == GRB.INFEASIBLE:
        print("The model is infeasible.")
    else:
        print(f"Optimization ended with status {m.status}")


except gp.GurobiError as e:
    print(f"Error code {e.errno}: {e}")

except AttributeError:
    print('Encountered an attribute error')
```
