BUG: .query() using uint64 column fails with TypeError "dtype could not be cast"
#### Code Sample, a copy-pastable example

```python
import pandas as pd
df = pd.DataFrame({'x': [1,2,3]}, dtype='uint64')
df = df.query('x > 1')
print(df)
```

#### Problem description

```
---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-44-168c7ec0f5d8> in <module>
      1 import pandas as pd
      2 df = pd.DataFrame({'x': [1,2,3]}, dtype='uint64')
----> 3 df = df.query('x > 1')
      4 print(df)

~\.conda\envs\digital-activity\lib\site-packages\pandas\core\frame.py in query(self, expr, inplace, **kwargs)
   3464         kwargs["level"] = kwargs.pop("level", 0) + 1
   3465         kwargs["target"] = None
-> 3466         res = self.eval(expr, **kwargs)
   3467 
   3468         try:

~\.conda\envs\digital-activity\lib\site-packages\pandas\core\frame.py in eval(self, expr, inplace, **kwargs)
   3594         kwargs["resolvers"] = kwargs.get("resolvers", ()) + tuple(resolvers)
   3595 
-> 3596         return _eval(expr, inplace=inplace, **kwargs)
   3597 
   3598     def select_dtypes(self, include=None, exclude=None) -> DataFrame:

~\.conda\envs\digital-activity\lib\site-packages\pandas\core\computation\eval.py in eval(expr, parser, engine, truediv, local_dict, global_dict, resolvers, level, target, inplace)
    345         eng = ENGINES[engine]
    346         eng_inst = eng(parsed_expr)
--> 347         ret = eng_inst.evaluate()
    348 
    349         if parsed_expr.assigner is None:

~\.conda\envs\digital-activity\lib\site-packages\pandas\core\computation\engines.py in evaluate(self)
     71 
     72         # make sure no names in resolvers and locals/globals clash
---> 73         res = self._evaluate()
     74         return reconstruct_object(
     75             self.result_type, res, self.aligned_axes, self.expr.terms.return_type

~\.conda\envs\digital-activity\lib\site-packages\pandas\core\computation\engines.py in _evaluate(self)
    112         scope = env.full_scope
    113         _check_ne_builtin_clash(self.expr)
--> 114         return ne.evaluate(s, local_dict=scope)
    115 
    116 

~\.conda\envs\digital-activity\lib\site-packages\numexpr\necompiler.py in evaluate(ex, local_dict, global_dict, out, order, casting, **kwargs)
    834     _numexpr_last = dict(ex=compiled_ex, argnames=names, kwargs=kwargs)
    835     with evaluate_lock:
--> 836         return compiled_ex(*arguments, **kwargs)
    837 
    838 

TypeError: Iterator operand 1 dtype could not be cast from dtype('uint64') to dtype('int64') according to the rule 'safe'
```

Failure when using an unsigned dtype should work (and worked in earlier versions, for example 1.0.3).

#### Expected Output

   x
1  2
2  3

#### Output of ``pd.show_versions()``

<details>

INSTALLED VERSIONS
------------------
commit           : 9d598a5e1eee26df95b3910e3f2934890d062caa
python           : 3.8.6.final.0
python-bits      : 64
OS               : Windows
OS-release       : 2012ServerR2
Version          : 6.3.9600
machine          : AMD64
processor        : Intel64 Family 6 Model 26 Stepping 5, GenuineIntel
byteorder        : little
LC_ALL           : None
LANG             : None
LOCALE           : English_United Kingdom.1252

pandas           : 1.2.1
numpy            : 1.19.4
pytz             : 2020.5
dateutil         : 2.8.1
pip              : 21.0.1
setuptools       : 49.6.0.post20210108
Cython           : None
pytest           : None
hypothesis       : None
sphinx           : None
blosc            : None
feather          : None
xlsxwriter       : None
lxml.etree       : None
html5lib         : None
pymysql          : None
psycopg2         : 2.8.6 (dt dec pq3 ext lo64)
jinja2           : 2.11.3
IPython          : 7.19.0
pandas_datareader: None
bs4              : None
bottleneck       : None
fsspec           : 0.8.5
fastparquet      : None
gcsfs            : None
matplotlib       : None
numexpr          : 2.7.2
odfpy            : None
openpyxl         : None
pandas_gbq       : None
pyarrow          : None
pyxlsb           : None
s3fs             : 0.5.2
scipy            : 1.6.0
sqlalchemy       : None
tables           : None
tabulate         : None
xarray           : None
xlrd             : 2.0.1
xlwt             : None
numba            : None
</details>
