diff --git a/.circleci/config.yml b/.circleci/config.yml
index d0e972cc2..00cd876cf 100644
--- a/.circleci/config.yml
+++ b/.circleci/config.yml
@@ -4,7 +4,7 @@ version: 2
 jobs:
     build_docs:
       docker:
-        - image: cimg/python:3.9
+        - image: cimg/python:3.10
       resource_class: medium
       steps:
         - checkout
diff --git a/RELEASES.md b/RELEASES.md
index 2f47f4095..595fecfb5 100644
--- a/RELEASES.md
+++ b/RELEASES.md
@@ -17,6 +17,8 @@
 - Make marginal parameters optional for (F)GW solvers in `._gw`, `._bregman` and `._semirelaxed` (PR #455)
 
 #### Closed issues
+
+- Fix change in scipy API for `cdist` (PR #487)
 - Fix circleci-redirector action and codecov (PR #460)
 - Fix issues with cuda for ot.binary_search_circle and with gradients for ot.sliced_wasserstein_sphere (PR #457)
 - Major documentation cleanup (PR #462, #467, #475)
diff --git a/docs/source/conf.py b/docs/source/conf.py
index e88804bd6..2131a9d0b 100644
--- a/docs/source/conf.py
+++ b/docs/source/conf.py
@@ -357,6 +357,7 @@ def __getattr__(cls, name):
 sphinx_gallery_conf = {
     'examples_dirs': ['../../examples', '../../examples/da'],
     'gallery_dirs': 'auto_examples',
+    'filename_pattern': 'plot_(?!barycenter_fgw)',
     'nested_sections' : False,
     'backreferences_dir':  'gen_modules/backreferences',
 	'inspect_global_variables'  : True,
diff --git a/examples/gromov/plot_barycenter_fgw.py b/examples/gromov/plot_barycenter_fgw.py
index 3b5db8b3b..40e5008c8 100644
--- a/examples/gromov/plot_barycenter_fgw.py
+++ b/examples/gromov/plot_barycenter_fgw.py
@@ -161,7 +161,7 @@ def graph_colors(nx_graph, vmin=0, vmax=7):
 
 #%% We compute the barycenter using FGW. Structure matrices are computed using the shortest_path distance in the graph
 # Features distances are the euclidean distances
-Cs = [shortest_path(nx.adjacency_matrix(x)) for x in X0]
+Cs = [shortest_path(nx.adjacency_matrix(x, dtype=np.int_)) for x in X0]
 ps = [np.ones(len(x.nodes())) / len(x.nodes()) for x in X0]
 Ys = [np.array([v for (k, v) in nx.get_node_attributes(x, 'attr_name').items()]).reshape(-1, 1) for x in X0]
 lambdas = np.array([np.ones(len(Ys)) / len(Ys)]).ravel()
diff --git a/ot/utils.py b/ot/utils.py
index 091b26813..1559eaaa6 100644
--- a/ot/utils.py
+++ b/ot/utils.py
@@ -285,7 +285,7 @@ def dist(x1, x2=None, metric='sqeuclidean', p=2, w=None):
         'sqeuclidean' or 'euclidean' on all backends. On numpy the function also
         accepts  from the scipy.spatial.distance.cdist function : 'braycurtis',
         'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice',
-        'euclidean', 'hamming', 'jaccard', 'kulsinski', 'mahalanobis',
+        'euclidean', 'hamming', 'jaccard', 'kulczynski1', 'mahalanobis',
         'matching', 'minkowski', 'rogerstanimoto', 'russellrao', 'seuclidean',
         'sokalmichener', 'sokalsneath', 'sqeuclidean', 'wminkowski', 'yule'.
     p : float, optional
diff --git a/test/test_utils.py b/test/test_utils.py
index 87f4dc48d..a726a588c 100644
--- a/test/test_utils.py
+++ b/test/test_utils.py
@@ -187,7 +187,7 @@ def test_dist():
     # tests that every metric runs correctly
     metrics_w = [
         'braycurtis', 'canberra', 'chebyshev', 'cityblock', 'correlation', 'cosine', 'dice',
-        'euclidean', 'hamming', 'jaccard', 'kulsinski',
+        'euclidean', 'hamming', 'jaccard',
         'matching', 'minkowski', 'rogerstanimoto', 'russellrao',
         'sokalmichener', 'sokalsneath', 'sqeuclidean', 'yule'
     ]  # those that support weights