To solve the given optimization problem using Gurobi, we need to define the variables, objective function, and constraints according to the provided specifications.

First, let's break down the problem into its components:
- Variables: `pathfinder_teams` (x0) and `reconnaissance_troops` (x1)
- Objective Function: Minimize `1.09 * pathfinder_teams + 7.7 * reconnaissance_troops`
- Constraints:
  1. Total combined offensive capability rating ≥ 45
  2. Total combined mobility rating ≥ 65
  3. `6 * pathfinder_teams - 2 * reconnaissance_troops ≥ 0`
  4. Total combined offensive capability rating ≤ 188
  5. Total combined mobility rating ≤ 141
  6. `pathfinder_teams` and `reconnaissance_troops` must be integers

Given the resource/attribute limits:
- `r0`: Offensive capability rating upper bound = 210, with `x0` (pathfinder teams) contribution = 23 and `x1` (reconnaissance troops) contribution = 10
- `r1`: Mobility rating upper bound = 196, with `x0` (pathfinder teams) contribution = 21 and `x1` (reconnaissance troops) contribution = 19

Now, let's write the Gurobi code to solve this optimization problem:

```python
from gurobipy import *

# Create a new model
m = Model("Optimization_Problem")

# Define variables
pathfinder_teams = m.addVar(vtype=GRB.INTEGER, name="pathfinder_teams")
reconnaissance_troops = m.addVar(vtype=GRB.INTEGER, name="reconnaissance_troops")

# Objective function: Minimize 1.09 * pathfinder_teams + 7.7 * reconnaissance_troops
m.setObjective(1.09 * pathfinder_teams + 7.7 * reconnaissance_troops, GRB.MINIMIZE)

# Constraints
# Total combined offensive capability rating >= 45
m.addConstr(23 * pathfinder_teams + 10 * reconnaissance_troops >= 45, "offensive_capability_min")

# Total combined mobility rating >= 65
m.addConstr(21 * pathfinder_teams + 19 * reconnaissance_troops >= 65, "mobility_rating_min")

# 6 * pathfinder_teams - 2 * reconnaissance_troops >= 0
m.addConstr(6 * pathfinder_teams - 2 * reconnaissance_troops >= 0, "custom_constraint")

# Total combined offensive capability rating <= 188
m.addConstr(23 * pathfinder_teams + 10 * reconnaissance_troops <= 188, "offensive_capability_max")

# Total combined mobility rating <= 141
m.addConstr(21 * pathfinder_teams + 19 * reconnaissance_troops <= 141, "mobility_rating_max")

# Optimize model
m.optimize()

# Print results
if m.status == GRB.OPTIMAL:
    print("Optimal solution found:")
    print(f"Pathfinder Teams: {pathfinder_teams.x}")
    print(f"Reconnaissance Troops: {reconnaissance_troops.x}")
    print(f"Objective Function Value: {m.objVal}")
else:
    print("No optimal solution found")
```