diff --git a/myst_nb/core/read.py b/myst_nb/core/read.py
index 84a6b35b..ec359238 100644
--- a/myst_nb/core/read.py
+++ b/myst_nb/core/read.py
@@ -8,6 +8,7 @@
 from pathlib import Path
 from typing import Callable, Iterator
 
+from docutils import nodes
 from docutils.parsers.rst import Directive
 from markdown_it.renderer import RendererHTML
 from myst_parser.config.main import MdParserConfig
@@ -67,7 +68,7 @@ def create_nb_reader(
     # get all possible readers
     readers = nb_config.custom_formats.copy()
     # add the default reader
-    readers.setdefault(".ipynb", (standard_nb_read, {}, False))  # type: ignore
+    readers.setdefault(".ipynb", (standard_nb_read, {}, False))
 
     # we check suffixes ordered by longest first, to ensure we get the "closest" match
     iterator = sorted(readers.items(), key=lambda x: len(x[0]), reverse=True)
@@ -406,6 +407,10 @@ def run(self):
         if hasattr(document.settings, "env"):
             logger = SphinxDocLogger(document)
         else:
-            logger = DocutilsDocLogger(document)  # type: ignore
+            logger = DocutilsDocLogger(document)
         logger.warning(message, line=self.lineno, subtype="nbcell")
-        return []
+        source = "\n".join(self.content)
+        node = nodes.literal_block(source, source)
+        if self.arguments:
+            node["language"] = self.arguments[0]
+        return [node]
diff --git a/pyproject.toml b/pyproject.toml
index ca4ea4af..b4ae5b13 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -107,6 +107,7 @@ testing = [
     "pytest-regressions",
     "pytest-param-files",
     "sympy>=1.10.1",
+    "sphinx_design",
 ]
 
 [project.scripts]
diff --git a/tests/notebooks/nested_code_cell_in_tab.md b/tests/notebooks/nested_code_cell_in_tab.md
new file mode 100644
index 00000000..348c16c5
--- /dev/null
+++ b/tests/notebooks/nested_code_cell_in_tab.md
@@ -0,0 +1,33 @@
+---
+file_format: mystnb
+kernelspec:
+  display_name: Python 3
+  language: python
+  name: python3
+---
+
+# Code cells in tab groups
+
+## Control: standalone code cell
+
+```{code-cell} python
+print("hello from standalone cell")
+```
+
+## Reproducer: code cells inside tab-set
+
+`````{tab-set}
+
+````{tab-item} Tab 1
+```{code-cell} python
+print("hello from tab 1")
+```
+````
+
+````{tab-item} Tab 2
+```{code-cell} python
+print("hello from tab 2")
+```
+````
+
+`````
diff --git a/tests/test_codecell_file/test_codecell_file.ipynb b/tests/test_codecell_file/test_codecell_file.ipynb
index dfab3618..a907bdfe 100644
--- a/tests/test_codecell_file/test_codecell_file.ipynb
+++ b/tests/test_codecell_file/test_codecell_file.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "77fd61dd",
+   "id": "98901a31",
    "metadata": {},
    "source": [
     "# a title"
@@ -11,7 +11,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "2e32aa7d",
+   "id": "2fa6ad55",
    "metadata": {
     "load": "mystnb_codecell_file.py"
    },
@@ -46,7 +46,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.13.5"
   },
   "source_map": [
    11,
@@ -55,4 +55,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}
\ No newline at end of file
diff --git a/tests/test_codecell_file/test_codecell_file.xml b/tests/test_codecell_file/test_codecell_file.xml
index 633dd369..6e5472e9 100644
--- a/tests/test_codecell_file/test_codecell_file.xml
+++ b/tests/test_codecell_file/test_codecell_file.xml
@@ -7,4 +7,4 @@
                 <literal_block language="ipython3" xml:space="preserve">
                     # flake8: noqa
                     
-                    import numpy as np
\ No newline at end of file
+                    import numpy as np
diff --git a/tests/test_codecell_file/test_codecell_file_warnings.ipynb b/tests/test_codecell_file/test_codecell_file_warnings.ipynb
index 8152749c..680dda3d 100644
--- a/tests/test_codecell_file/test_codecell_file_warnings.ipynb
+++ b/tests/test_codecell_file/test_codecell_file_warnings.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "daa53dc3",
+   "id": "9b7e13ff",
    "metadata": {},
    "source": [
     "# a title"
@@ -11,7 +11,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "d218bd29",
+   "id": "d579f8ea",
    "metadata": {
     "load": "mystnb_codecell_file.py"
    },
@@ -46,7 +46,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.13.5"
   },
   "source_map": [
    11,
@@ -55,4 +55,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}
\ No newline at end of file
diff --git a/tests/test_codecell_file/test_codecell_file_warnings.xml b/tests/test_codecell_file/test_codecell_file_warnings.xml
index fb6ab5fe..b5dca188 100644
--- a/tests/test_codecell_file/test_codecell_file_warnings.xml
+++ b/tests/test_codecell_file/test_codecell_file_warnings.xml
@@ -7,4 +7,4 @@
                 <literal_block language="ipython3" xml:space="preserve">
                     # flake8: noqa
                     
-                    import numpy as np
\ No newline at end of file
+                    import numpy as np
diff --git a/tests/test_execute/test_allow_errors_auto.ipynb b/tests/test_execute/test_allow_errors_auto.ipynb
index 42a41b44..12cd609e 100644
--- a/tests/test_execute/test_allow_errors_auto.ipynb
+++ b/tests/test_execute/test_allow_errors_auto.ipynb
@@ -21,7 +21,7 @@
      "traceback": [
       "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
       "\u001b[31mException\u001b[39m                                 Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33moopsie!\u001b[39m\u001b[33m\"\u001b[39m)\n",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m Exception(\u001b[33m\"oopsie!\"\u001b[39m)\n",
       "\u001b[31mException\u001b[39m: oopsie!"
      ]
     }
@@ -47,7 +47,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_execute/test_allow_errors_cache.ipynb b/tests/test_execute/test_allow_errors_cache.ipynb
index 42a41b44..12cd609e 100644
--- a/tests/test_execute/test_allow_errors_cache.ipynb
+++ b/tests/test_execute/test_allow_errors_cache.ipynb
@@ -21,7 +21,7 @@
      "traceback": [
       "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
       "\u001b[31mException\u001b[39m                                 Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33moopsie!\u001b[39m\u001b[33m\"\u001b[39m)\n",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m Exception(\u001b[33m\"oopsie!\"\u001b[39m)\n",
       "\u001b[31mException\u001b[39m: oopsie!"
      ]
     }
@@ -47,7 +47,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_execute/test_basic_failing_auto.ipynb b/tests/test_execute/test_basic_failing_auto.ipynb
index 42a41b44..12cd609e 100644
--- a/tests/test_execute/test_basic_failing_auto.ipynb
+++ b/tests/test_execute/test_basic_failing_auto.ipynb
@@ -21,7 +21,7 @@
      "traceback": [
       "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
       "\u001b[31mException\u001b[39m                                 Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33moopsie!\u001b[39m\u001b[33m\"\u001b[39m)\n",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m Exception(\u001b[33m\"oopsie!\"\u001b[39m)\n",
       "\u001b[31mException\u001b[39m: oopsie!"
      ]
     }
@@ -47,7 +47,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_execute/test_basic_failing_cache.ipynb b/tests/test_execute/test_basic_failing_cache.ipynb
index 42a41b44..12cd609e 100644
--- a/tests/test_execute/test_basic_failing_cache.ipynb
+++ b/tests/test_execute/test_basic_failing_cache.ipynb
@@ -21,7 +21,7 @@
      "traceback": [
       "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
       "\u001b[31mException\u001b[39m                                 Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33moopsie!\u001b[39m\u001b[33m\"\u001b[39m)\n",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m Exception(\u001b[33m\"oopsie!\"\u001b[39m)\n",
       "\u001b[31mException\u001b[39m: oopsie!"
      ]
     }
@@ -47,7 +47,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_execute/test_basic_failing_inline.ipynb b/tests/test_execute/test_basic_failing_inline.ipynb
index 42a41b44..12cd609e 100644
--- a/tests/test_execute/test_basic_failing_inline.ipynb
+++ b/tests/test_execute/test_basic_failing_inline.ipynb
@@ -21,7 +21,7 @@
      "traceback": [
       "\u001b[31m---------------------------------------------------------------------------\u001b[39m",
       "\u001b[31mException\u001b[39m                                 Traceback (most recent call last)",
-      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mException\u001b[39;00m(\u001b[33m\"\u001b[39m\u001b[33moopsie!\u001b[39m\u001b[33m\"\u001b[39m)\n",
+      "\u001b[36mCell\u001b[39m\u001b[36m \u001b[39m\u001b[32mIn[1]\u001b[39m\u001b[32m, line 1\u001b[39m\n\u001b[32m----> \u001b[39m\u001b[32m1\u001b[39m \u001b[38;5;28;01mraise\u001b[39;00m Exception(\u001b[33m\"oopsie!\"\u001b[39m)\n",
       "\u001b[31mException\u001b[39m: oopsie!"
      ]
     }
@@ -47,7 +47,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_execute/test_basic_unrun_auto.ipynb b/tests/test_execute/test_basic_unrun_auto.ipynb
index 493dc282..7ff02be9 100644
--- a/tests/test_execute/test_basic_unrun_auto.ipynb
+++ b/tests/test_execute/test_basic_unrun_auto.ipynb
@@ -44,7 +44,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_execute/test_basic_unrun_cache.ipynb b/tests/test_execute/test_basic_unrun_cache.ipynb
index 493dc282..7ff02be9 100644
--- a/tests/test_execute/test_basic_unrun_cache.ipynb
+++ b/tests/test_execute/test_basic_unrun_cache.ipynb
@@ -44,7 +44,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_execute/test_basic_unrun_inline.ipynb b/tests/test_execute/test_basic_unrun_inline.ipynb
index 493dc282..7ff02be9 100644
--- a/tests/test_execute/test_basic_unrun_inline.ipynb
+++ b/tests/test_execute/test_basic_unrun_inline.ipynb
@@ -44,7 +44,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_execute/test_complex_outputs_unrun_auto.ipynb b/tests/test_execute/test_complex_outputs_unrun_auto.ipynb
index bcc7a382..c9b8fb49 100644
--- a/tests/test_execute/test_complex_outputs_unrun_auto.ipynb
+++ b/tests/test_execute/test_complex_outputs_unrun_auto.ipynb
@@ -405,7 +405,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "iVBORw0KGgoAAAANSUhEUgAAAcMAAAAaCAYAAADLwDeNAAAAOnRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjEwLjcsIGh0dHBzOi8vbWF0cGxvdGxpYi5vcmcvTLEjVAAAAAlwSFlzAAASdAAAEnQB3mYfeAAACrVJREFUeJztXQusXUUVXa8CLfIRJH4iAbSiKH6oKILfggj4pIpFCImgoMSIiVRRQFHIcqugIsaaoEJEBWvRGEWNpRUVqi1BNCLFD1ZBxYofELQiglbLM7vua847nfObM3POXO5Zyct997z7ZvbZs9edPXv27DM1MzMDF0RkDoAlJJeiAUTE3aAnSE7l2l8EYD3JW0P2k2n/ZQDuI3l1jPYnBSKyA4B7Y9lBaIjIswE8nOQ3kBB8eRio76hcjs3ngcvjZQt983mqZDJ8P4BlJG9uIMAzARxA8iJEgoioEj8N4DSSGwO3/WQAZ5B8Xch2Jw1d2EEMiMiHAXyW5E1IBD48HKcxjMXngcvhIBPC5zkFjTwPwHYeBDwSwJWICJI6e38MwHsjeOCfBPDOkO1OKKLbQSS8B8DHReQhSAAteDg2YxiDzwOXg+PISeCzczIEoN7oJR6d70nyd4gMkj8EcJCIPDZgsycCuJ3knwK2OanoxA5Cg+TfAPwUwElIA748HKsxjMDngcthseck8HmryVBEjgAwj+TPm3QsIo8C0OVE8gUAZwcM1Zxl4ZoB7XTZtR2Exqf+dxsyr08hfHk4xmMYhM8Dl8NCJojPrpWh7pd9x6PTaQAr0R3WADhORB4aoK2D1fsBcE2AtiYdXdtBUJD8AYDtAby8Z1F8eTiuYxiKzwOXw2J6Uvi8TfaNxVZfAuAUj34P1M1KdIef2E0uBLCqYNP3fADPBfB7+3J5NIA3k9S9mCyO0fZI/qc78R+06NoOYuBGs4kv9tF5Sx6O6xgW8nngcq84cFL4nF8ZPhXAzgAaZdOJyLYANpN8wEvU6vbfqqm9IvKq0TWS/wTwS5vs8p8/AMBaAKsBPB3A9XoZwLsAnOPoYqEpbEC7cercDiLhR2YTfcGLh+M8hkV8HrjcH2TC+DxrZQhgH3v9c8POng/g2qI/ishtAPYq+PMdJHXFVoZn2atutGdxF4AnOj6vKbVfJ/k+6/9yfa+hGJKzQqEish0APVJxeYn8x5gyFwDYD8BOAJaTPKFmzP0PmtVkX26amfU0ALsD2GQe8Wf0J5bRVci3G4DFgeTqyw5m6ZnkqS37+y2AR2qbJO9A9/DlYQj0NoYFfE6Vy+8OyJsUudybLQTmcm0+5ydDVZ7iHjSDbvZ/sOIzmtnjOjhc52D2OyxN9pbc9XsyMm+BiKhSXgDgkMzlTbYKdq0K97K/qXxFONuIo7LeDuBJqI+jrP2b7ejGH23FugGADvrRljE4LSLHWqp5lzgWwCcCydWXHWT1fEWA/ka28DglGrqHLw9DoM8xnMXnhLl8RWDehEJomY7oyRZCcnn0f5V8zk+GWjVkE8l/lZzfmePYW9uV5F8rBNpIUr2pxiCpg1p0k7MmQ/MM896Getq/IOnycnat8cVzmhHnVvMq1dDqQj21uy0EpJu4V2a9MxHRc426yftKM9ovo1s0litBO8jqeU2A/ka2sAs8ICInmSd+CEmfJJhSHoZAomOY53OqXFYbm4rB55a24/Udk6AtLA7I5dp8zk+GD5QcxFdD+7z9XJa5Ph/ArxAJIqJeoYZDLiB5hkP+zblresMzo+sispPtFRalB8+11/uKZCD5f8KISBPZdd/nRRq2KSrvpucaRUQrO5xrmXCdTob5UFOVXCnaQU7PeXvwwcgW+jpeUcjDEEhxDAv4nCqXVZ5GvEmRyynagoTncm0+5yfDv+s1TW8mmTeop9gSc1FWafa+TnWCuSJygh1h+AeAH1vcv+qG989sguaxs8mcxTrz2s4SkeUAPmRhg71F5Akk80vy++11R4SH6kb3Mb5S8bl/22tq2awuuVK0gzI9+/S3Y842ukYZD0MgxTF08XkcuZwqn4tkSs0WFgXmcm0+573PDRmjnAULS+gm9uGWZTTCviR/hmpo/H+ZeSdLzSu4RUQWtpwMZy21Sf7GvMc3WsKKkuvFVongOkcbf8m0FRqLbdC+WfQBEVGH5DX2Npki0UVyJWoHZXr26W9kCxqq6QOFPAyBRMdwKz6PG5dT5XOZTAnawuLAXK7N5/xkOLr5/D7cFpgnpiGKF2aeTKCCV0Fj4IfazexgmU4XA9DyS6tERDe0y5R2r8XD83hMRuasnOeRfARJreBxvMa99WyhXnO0scG8pYchIKzigZ4VW2Vp40X4gKXSryR5FdJBoVwp2UGFnn37G9lCtDBRBUp5GAIpjWEZn8eMy6nyuVSmVGxB4nC5Np9nhUn1MSoiokp5BoAbCv5nhS1lrzYv7dtlHVi7+eC8enaniIgq422ZNOVZsEHRVOvr8hlQIrKLKULPE3pDN41FROXZG2FxmC3PC8MqIrLE7n89gFfXabQixdiFWmnjHnIlYQdlevbtz2zhthrJA1XjsdqxL3UZydJaiVU8DGgDqYxhED73yWUfPsewnRYyrUjAFmJwuTaf83uGiq9mlrBFSrvYsrIOtpqevrjIbmSLR+LAfrZ6dYVVFthZlO+jPVabAYTE0ZYG7oy7i8ibAHzUjlwcSnIU4qmCejdV3mkWqqPaaCBXKnZQqmfP/vZvkGW41JGltsDSw3UPRr/wkNsHq4MyHoaygVTGMCSfO+dyCz7Hsh0fmVYkYAsxuFybz67JUBXyJS14W3AeZa0dYNQU57k1wgZlGB0qVk/BhdGXgas6jC6nLwl0sFXL9JwqItuTvD9QOS19SPA1Vjk9//e3APiIeTdqpHfWbZukhgqioKFcvdtBlZ59+rM0cyXrlkPeVXA9dNfS4/UL7VLPoxWlPAxoA72PYQQ+d8rlNnyOaDs+Mq3t0xZicLkpn7dK3ya5zs6kOGdaO4tylR1ebeSpOHCQvf66ySar3eC0VadoDZLXWzjqpSHaM93t5lrui8jbzUjX2Vmi2hNhTDSVKwU7KNNzi/40rfvOOmGimKjiYaA+UhjDoHzuksup8tlHJvZvCzG43IjPRWeZNIPr9RVL6uPrVDPXJ05bjDh/XfcHLrS3nytRmnoo+YebHmVPMA5ZoeNMAK8N1JbGrtXD/Vr2ooicY5vZN5i3puWnekcLufq2A6eeW/anBd3PDXjGqQ2qeBgCfY9hDD5H53KqfG4p04oebSEGlxvx2RUm3ZLSLCKaoTNNcqsnQpiybiSplRyqcJzGdEVkjdWI0/Tox1v9vHnW1gX5fxIRPUC7r3op2coIIqIbrIcD0Hh4MJBco6EF1/klEXkFAP1RjGrgPUdELrXf7yJ5un12yj77vWwdPBE50UoPbbaQxBLHBrlu8o7a7AQt5erTDpx6btOfiOxuGY3Z81a9oQYPQ6C3MYzF59hcTpXPAWRa2YctxOCyD5+dk6GC5HKtY1fwt7tFREv71IFuXO5jmXH66CSd4TdaAVg9M7KsYG9SU4G3dYRVtKr9mZE89zdoLT4ROTknk25qq6FlMd9+YAN0eqb47B6OGnpaF0+hsXGN57vwXd0rQLfwlqtnOyjSc5v+9MnyJ/dRMN2Hh4Ha73MMY/I5JpdT5XMrmdifLcTgcmM+T83MdF0XOm2IiBbu3YPktzz//zzLxJpvh4YHREBoPYuIFoTeJluua8B4Y+DyeEAifGf68Dla/cNxBcn1LZMnNPZ90zARRkdoPV87TIQPLgxcHhssjvCd2ZjPw8pwwIABAwZMPIaV4YABAwYMwKTjv4gv68xd5avjAAAAAElFTkSuQmCC",
       "text/latex": [
        "$\\displaystyle \\left(\\sqrt{5} i\\right)^{\\alpha} \\left(\\frac{1}{2} - \\frac{2 \\sqrt{5} i}{5}\\right) + \\left(- \\sqrt{5} i\\right)^{\\alpha} \\left(\\frac{1}{2} + \\frac{2 \\sqrt{5} i}{5}\\right)$"
       ],
@@ -547,7 +547,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,
diff --git a/tests/test_execute/test_complex_outputs_unrun_auto.xml b/tests/test_execute/test_complex_outputs_unrun_auto.xml
index e36b6aeb..e9cf5875 100644
--- a/tests/test_execute/test_complex_outputs_unrun_auto.xml
+++ b/tests/test_execute/test_complex_outputs_unrun_auto.xml
@@ -214,7 +214,7 @@
                             (√5⋅ⅈ)      ⋅⎜─ - ──────⎟ + (-√5⋅ⅈ)      ⋅⎜─ + ──────⎟
                                          ⎝2     5   ⎠                 ⎝2     5   ⎠
                     <container mime_type="image/png">
-                        <image candidates="{'*': '_build/jupyter_execute/c8709f293454a3bd1403356f37bbab536df1c4d65becfd4cdcf84adf951c6820.png'}" uri="_build/jupyter_execute/c8709f293454a3bd1403356f37bbab536df1c4d65becfd4cdcf84adf951c6820.png">
+                        <image candidates="{'*': '_build/jupyter_execute/a159f4b0f56a614322caef9dd10fcbe6f0348a2277e2c78013b34838532e6ab4.png'}" uri="_build/jupyter_execute/a159f4b0f56a614322caef9dd10fcbe6f0348a2277e2c78013b34838532e6ab4.png">
                     <container mime_type="text/latex">
                         <math_block classes="output text_latex" nowrap="0" number="True" xml:space="preserve">
                             \displaystyle \left(\sqrt{5} i\right)^{\alpha} \left(\frac{1}{2} - \frac{2 \sqrt{5} i}{5}\right) + \left(- \sqrt{5} i\right)^{\alpha} \left(\frac{1}{2} + \frac{2 \sqrt{5} i}{5}\right)
diff --git a/tests/test_execute/test_complex_outputs_unrun_cache.ipynb b/tests/test_execute/test_complex_outputs_unrun_cache.ipynb
index bcc7a382..c9b8fb49 100644
--- a/tests/test_execute/test_complex_outputs_unrun_cache.ipynb
+++ b/tests/test_execute/test_complex_outputs_unrun_cache.ipynb
@@ -405,7 +405,7 @@
    "outputs": [
     {
      "data": {
-      "image/png": "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",
+      "image/png": "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",
       "text/latex": [
        "$\\displaystyle \\left(\\sqrt{5} i\\right)^{\\alpha} \\left(\\frac{1}{2} - \\frac{2 \\sqrt{5} i}{5}\\right) + \\left(- \\sqrt{5} i\\right)^{\\alpha} \\left(\\frac{1}{2} + \\frac{2 \\sqrt{5} i}{5}\\right)$"
       ],
@@ -547,7 +547,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "latex_envs": {
    "LaTeX_envs_menu_present": true,
diff --git a/tests/test_execute/test_complex_outputs_unrun_cache.xml b/tests/test_execute/test_complex_outputs_unrun_cache.xml
index e36b6aeb..e9cf5875 100644
--- a/tests/test_execute/test_complex_outputs_unrun_cache.xml
+++ b/tests/test_execute/test_complex_outputs_unrun_cache.xml
@@ -214,7 +214,7 @@
                             (√5⋅ⅈ)      ⋅⎜─ - ──────⎟ + (-√5⋅ⅈ)      ⋅⎜─ + ──────⎟
                                          ⎝2     5   ⎠                 ⎝2     5   ⎠
                     <container mime_type="image/png">
-                        <image candidates="{'*': '_build/jupyter_execute/c8709f293454a3bd1403356f37bbab536df1c4d65becfd4cdcf84adf951c6820.png'}" uri="_build/jupyter_execute/c8709f293454a3bd1403356f37bbab536df1c4d65becfd4cdcf84adf951c6820.png">
+                        <image candidates="{'*': '_build/jupyter_execute/a159f4b0f56a614322caef9dd10fcbe6f0348a2277e2c78013b34838532e6ab4.png'}" uri="_build/jupyter_execute/a159f4b0f56a614322caef9dd10fcbe6f0348a2277e2c78013b34838532e6ab4.png">
                     <container mime_type="text/latex">
                         <math_block classes="output text_latex" nowrap="0" number="True" xml:space="preserve">
                             \displaystyle \left(\sqrt{5} i\right)^{\alpha} \left(\frac{1}{2} - \frac{2 \sqrt{5} i}{5}\right) + \left(- \sqrt{5} i\right)^{\alpha} \left(\frac{1}{2} + \frac{2 \sqrt{5} i}{5}\right)
diff --git a/tests/test_execute/test_custom_convert_auto.ipynb b/tests/test_execute/test_custom_convert_auto.ipynb
index 495e5134..5395b7c4 100644
--- a/tests/test_execute/test_custom_convert_auto.ipynb
+++ b/tests/test_execute/test_custom_convert_auto.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "raw",
-   "id": "01cb5fd4",
+   "id": "f027c0d8",
    "metadata": {},
    "source": [
     "---\n",
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "77b6b8f6",
+   "id": "fd28e00a",
    "metadata": {},
    "source": [
     "# Custom Formats"
@@ -23,7 +23,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "c71bb0d2",
+   "id": "4233dc27",
    "metadata": {
     "echo": true
    },
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "6caa0f88",
+   "id": "3aec2899",
    "metadata": {
     "fig.height": 5,
     "fig.width": 8,
@@ -59,7 +59,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -95,7 +95,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,
diff --git a/tests/test_execute/test_custom_convert_auto.xml b/tests/test_execute/test_custom_convert_auto.xml
index 38935da1..41019b2a 100644
--- a/tests/test_execute/test_custom_convert_auto.xml
+++ b/tests/test_execute/test_custom_convert_auto.xml
@@ -19,4 +19,4 @@
                         <literal_block classes="output text_plain" language="myst-ansi" xml:space="preserve">
                             <Figure size 640x480 with 1 Axes>
                     <container mime_type="image/png">
-                        <image candidates="{'*': '_build/jupyter_execute/9af310c61f9e96d898144e35f0dc3bf6757626c2072ad98732a4d71c1ec5ec59.png'}" uri="_build/jupyter_execute/9af310c61f9e96d898144e35f0dc3bf6757626c2072ad98732a4d71c1ec5ec59.png">
+                        <image candidates="{'*': '_build/jupyter_execute/b9d3d90a9968c7fb6f966f8c1b55dff80df38bd15052a845b270a25002d1be72.png'}" uri="_build/jupyter_execute/b9d3d90a9968c7fb6f966f8c1b55dff80df38bd15052a845b270a25002d1be72.png">
diff --git a/tests/test_execute/test_custom_convert_cache.ipynb b/tests/test_execute/test_custom_convert_cache.ipynb
index 9d56496a..20c026fd 100644
--- a/tests/test_execute/test_custom_convert_cache.ipynb
+++ b/tests/test_execute/test_custom_convert_cache.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "raw",
-   "id": "a19ab5d4",
+   "id": "3037717b",
    "metadata": {},
    "source": [
     "---\n",
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "e3fef28d",
+   "id": "afe843d8",
    "metadata": {},
    "source": [
     "# Custom Formats"
@@ -23,7 +23,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "07d6dc8a",
+   "id": "2e3cfb8e",
    "metadata": {
     "echo": true
    },
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "5273c524",
+   "id": "6369e3d2",
    "metadata": {
     "fig.height": 5,
     "fig.width": 8,
@@ -59,7 +59,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -95,7 +95,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,
diff --git a/tests/test_execute/test_custom_convert_cache.xml b/tests/test_execute/test_custom_convert_cache.xml
index 38935da1..41019b2a 100644
--- a/tests/test_execute/test_custom_convert_cache.xml
+++ b/tests/test_execute/test_custom_convert_cache.xml
@@ -19,4 +19,4 @@
                         <literal_block classes="output text_plain" language="myst-ansi" xml:space="preserve">
                             <Figure size 640x480 with 1 Axes>
                     <container mime_type="image/png">
-                        <image candidates="{'*': '_build/jupyter_execute/9af310c61f9e96d898144e35f0dc3bf6757626c2072ad98732a4d71c1ec5ec59.png'}" uri="_build/jupyter_execute/9af310c61f9e96d898144e35f0dc3bf6757626c2072ad98732a4d71c1ec5ec59.png">
+                        <image candidates="{'*': '_build/jupyter_execute/b9d3d90a9968c7fb6f966f8c1b55dff80df38bd15052a845b270a25002d1be72.png'}" uri="_build/jupyter_execute/b9d3d90a9968c7fb6f966f8c1b55dff80df38bd15052a845b270a25002d1be72.png">
diff --git a/tests/test_execute/test_custom_convert_multiple_extensions_auto.ipynb b/tests/test_execute/test_custom_convert_multiple_extensions_auto.ipynb
index 7c7df80d..928ef056 100644
--- a/tests/test_execute/test_custom_convert_multiple_extensions_auto.ipynb
+++ b/tests/test_execute/test_custom_convert_multiple_extensions_auto.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "raw",
-   "id": "13d0726e",
+   "id": "0ccf146d",
    "metadata": {},
    "source": [
     "---\n",
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8ca3f821",
+   "id": "6b817c5e",
    "metadata": {},
    "source": [
     "# Custom Formats"
@@ -23,7 +23,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "474022f9",
+   "id": "290ec462",
    "metadata": {
     "echo": true
    },
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "bb063562",
+   "id": "11af3b44",
    "metadata": {
     "fig.height": 5,
     "fig.width": 8,
@@ -59,7 +59,7 @@
     },
     {
      "data": {
-      "image/png": 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",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -95,7 +95,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,
diff --git a/tests/test_execute/test_custom_convert_multiple_extensions_auto.xml b/tests/test_execute/test_custom_convert_multiple_extensions_auto.xml
index fe18cdc5..aadb1bae 100644
--- a/tests/test_execute/test_custom_convert_multiple_extensions_auto.xml
+++ b/tests/test_execute/test_custom_convert_multiple_extensions_auto.xml
@@ -19,4 +19,4 @@
                         <literal_block classes="output text_plain" language="myst-ansi" xml:space="preserve">
                             <Figure size 640x480 with 1 Axes>
                     <container mime_type="image/png">
-                        <image candidates="{'*': '_build/jupyter_execute/9af310c61f9e96d898144e35f0dc3bf6757626c2072ad98732a4d71c1ec5ec59.png'}" uri="_build/jupyter_execute/9af310c61f9e96d898144e35f0dc3bf6757626c2072ad98732a4d71c1ec5ec59.png">
+                        <image candidates="{'*': '_build/jupyter_execute/b9d3d90a9968c7fb6f966f8c1b55dff80df38bd15052a845b270a25002d1be72.png'}" uri="_build/jupyter_execute/b9d3d90a9968c7fb6f966f8c1b55dff80df38bd15052a845b270a25002d1be72.png">
diff --git a/tests/test_execute/test_custom_convert_multiple_extensions_cache.ipynb b/tests/test_execute/test_custom_convert_multiple_extensions_cache.ipynb
index 41bfa6d1..53ba12a2 100644
--- a/tests/test_execute/test_custom_convert_multiple_extensions_cache.ipynb
+++ b/tests/test_execute/test_custom_convert_multiple_extensions_cache.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "raw",
-   "id": "76233962",
+   "id": "236122f5",
    "metadata": {},
    "source": [
     "---\n",
@@ -14,7 +14,7 @@
   },
   {
    "cell_type": "markdown",
-   "id": "8822bbed",
+   "id": "d7ff2b28",
    "metadata": {},
    "source": [
     "# Custom Formats"
@@ -23,7 +23,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "e4638ed2",
+   "id": "41a5afab",
    "metadata": {
     "echo": true
    },
@@ -37,7 +37,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "9cdca50e",
+   "id": "f571ef08",
    "metadata": {
     "fig.height": 5,
     "fig.width": 8,
@@ -59,7 +59,7 @@
     },
     {
      "data": {
-      "image/png": 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Op/z8/BoyLtAidfv9VtMjNBtfLog3PQLQ5JSXl8vf3/+6f789umbkirS0NG3ZskUHDhzwKEQkqU2bNho4cKBOnjxZ7zZ2u112u70howEAgCbGo5dpLMtSWlqa3nvvPe3Zs0fdu3f3+IA1NTU6fvy4QkJCPN4XAAA0Px6dGUlNTdXq1au1ceNG+fr6qrS0VJLk7++vtm3bSpKSkpIUGhoqh8MhSZo/f76GDx+uHj166NKlS1q4cKEKCws1derURn4oAACgKfIoRlauXClJGjVqlNv6VatW6amnnpIkFRUVycvrpxMuFy9eVEpKikpLS9WpUydFR0crLy9PkZGRNzc5AABoFhp8AevtdKMXwABwxwWsjYcLWAHP3ejfb76bBgAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwCiPYsThcGjIkCHy9fVVYGCgEhMTVVBQcN391q1bp169esnHx0f9+vXTtm3bGjwwAABoXjyKkf379ys1NVUfffSRdu3apR9++EFjx45VZWVlvfvk5eVp0qRJmjJlio4eParExEQlJibqxIkTNz08AABo+myWZVkN3fncuXMKDAzU/v37df/999e5zcSJE1VZWaktW7a41g0fPlwDBgxQZmbmDR2nvLxc/v7+cjqd8vPza+i4QIvT7fdbTY/QbHy5IN70CECTc6N/v2/qmhGn0ylJ6ty5c73b5OfnKzY21m1dXFyc8vPz692nqqpK5eXlbgsAAGieWjd0x9raWs2cOVP33Xef+vbtW+92paWlCgoKclsXFBSk0tLSevdxOByaN29eQ0cDANzBOGPXOJrT2boGnxlJTU3ViRMntGbNmsacR5KUkZEhp9PpWoqLixv9GAAA4M7QoDMjaWlp2rJliw4cOKCuXbtec9vg4GCVlZW5rSsrK1NwcHC9+9jtdtnt9oaMBgAAmhiPzoxYlqW0tDS999572rNnj7p3737dfWJiYpSbm+u2bteuXYqJifFsUgAA0Cx5dGYkNTVVq1ev1saNG+Xr6+u67sPf319t27aVJCUlJSk0NFQOh0OS9Nxzz2nkyJFatGiR4uPjtWbNGh06dEhZWVmN/FAAAEBT5NGZkZUrV8rpdGrUqFEKCQlxLWvXrnVtU1RUpJKSEtftESNGaPXq1crKylJUVJTWr1+vDRs2XPOiVwAA0HJ4dGbkRj6SZN++fVete+yxx/TYY495cigAANBC8N00AADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACjiBEAAGAUMQIAAIwiRgAAgFHECAAAMMrjGDlw4IASEhLUpUsX2Ww2bdiw4Zrb79u3Tzab7aqltLS0oTMDAIBmxOMYqaysVFRUlJYvX+7RfgUFBSopKXEtgYGBnh4aAAA0Q6093WH8+PEaP368xwcKDAxUx44dPd4PAAA0b7ftmpEBAwYoJCREY8aM0Ycffni7DgsAAO5wHp8Z8VRISIgyMzM1ePBgVVVV6Y033tCoUaP0r3/9S4MGDapzn6qqKlVVVblul5eX3+oxAQCAIbc8RiIiIhQREeG6PWLECJ06dUpLlizRW2+9Vec+DodD8+bNu9WjAQCAO4CRt/YOHTpUJ0+erPf+jIwMOZ1O11JcXHwbpwMAALfTLT8zUpdjx44pJCSk3vvtdrvsdvttnAgAAJjicYxcvnzZ7azGmTNndOzYMXXu3Fl33323MjIy9PXXX+tvf/ubJGnp0qXq3r27+vTpo++//15vvPGG9uzZo/fff7/xHgUAAGiyPI6RQ4cO6YEHHnDdTk9PlyQlJycrJydHJSUlKioqct1fXV2t3/3ud/r666/Vrl079e/fX7t373b7GQAAoOXyOEZGjRoly7LqvT8nJ8ft9qxZszRr1iyPBwMAAC0D300DAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABglMcxcuDAASUkJKhLly6y2WzasGHDdffZt2+fBg0aJLvdrh49eignJ6cBowIAgObI4xiprKxUVFSUli9ffkPbnzlzRvHx8XrggQd07NgxzZw5U1OnTtXOnTs9HhYAADQ/rT3dYfz48Ro/fvwNb5+Zmanu3btr0aJFkqTevXvrgw8+0JIlSxQXF+fp4QEAQDNzy68Zyc/PV2xsrNu6uLg45efn17tPVVWVysvL3RYAANA8eXxmxFOlpaUKCgpyWxcUFKTy8nJ99913atu27VX7OBwOzZs371aP1ui6/X6r6RGajS8XxJseAQBwm9yR76bJyMiQ0+l0LcXFxaZHAgAAt8gtPzMSHByssrIyt3VlZWXy8/Or86yIJNntdtnt9ls9GgAAuAPc8jMjMTExys3NdVu3a9cuxcTE3OpDAwCAJsDjGLl8+bKOHTumY8eOSfrxrbvHjh1TUVGRpB9fYklKSnJt/5vf/EanT5/WrFmz9Pnnn2vFihX6xz/+od/+9reN8wgAAECT5nGMHDp0SAMHDtTAgQMlSenp6Ro4cKDmzJkjSSopKXGFiSR1795dW7du1a5duxQVFaVFixbpjTfe4G29AABAUgOuGRk1apQsy6r3/ro+XXXUqFE6evSop4cCAAAtwB35bhoAANByECMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwihgBAABGESMAAMAoYgQAABhFjAAAAKOIEQAAYBQxAgAAjCJGAACAUcQIAAAwqkExsnz5cnXr1k0+Pj4aNmyYDh48WO+2OTk5stlsbouPj0+DBwYAAM2LxzGydu1apaena+7cuTpy5IiioqIUFxens2fP1ruPn5+fSkpKXEthYeFNDQ0AAJoPj2Nk8eLFSklJ0eTJkxUZGanMzEy1a9dO2dnZ9e5js9kUHBzsWoKCgm5qaAAA0Hx4FCPV1dU6fPiwYmNjf/oBXl6KjY1Vfn5+vftdvnxZ4eHhCgsL04QJE/TZZ59d8zhVVVUqLy93WwAAQPPkUYycP39eNTU1V53ZCAoKUmlpaZ37REREKDs7Wxs3btTbb7+t2tpajRgxQl999VW9x3E4HPL393ctYWFhnowJAACakFv+bpqYmBglJSVpwIABGjlypN59910FBATo9ddfr3efjIwMOZ1O11JcXHyrxwQAAIa09mTju+66S61atVJZWZnb+rKyMgUHB9/Qz2jTpo0GDhyokydP1ruN3W6X3W73ZDQAANBEeXRmxNvbW9HR0crNzXWtq62tVW5urmJiYm7oZ9TU1Oj48eMKCQnxbFIAANAseXRmRJLS09OVnJyswYMHa+jQoVq6dKkqKys1efJkSVJSUpJCQ0PlcDgkSfPnz9fw4cPVo0cPXbp0SQsXLlRhYaGmTp3auI8EAAA0SR7HyMSJE3Xu3DnNmTNHpaWlGjBggHbs2OG6qLWoqEheXj+dcLl48aJSUlJUWlqqTp06KTo6Wnl5eYqMjGy8RwEAAJosj2NEktLS0pSWllbnffv27XO7vWTJEi1ZsqQhhwEAAC0A300DAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAo4gRAABgFDECAACMIkYAAIBRxAgAADCKGAEAAEYRIwAAwChiBAAAGEWMAAAAoxoUI8uXL1e3bt3k4+OjYcOG6eDBg9fcft26derVq5d8fHzUr18/bdu2rUHDAgCA5sfjGFm7dq3S09M1d+5cHTlyRFFRUYqLi9PZs2fr3D4vL0+TJk3SlClTdPToUSUmJioxMVEnTpy46eEBAEDT53GMLF68WCkpKZo8ebIiIyOVmZmpdu3aKTs7u87tX331VY0bN07PP/+8evfurZdeekmDBg3SsmXLbnp4AADQ9HkUI9XV1Tp8+LBiY2N/+gFeXoqNjVV+fn6d++Tn57ttL0lxcXH1bg8AAFqW1p5sfP78edXU1CgoKMhtfVBQkD7//PM69yktLa1z+9LS0nqPU1VVpaqqKtdtp9MpSSovL/dk3Nuutupb0yM0G3f6f9ZNBc/JxsNzsvHwvGwcTeE5eWVGy7KuuZ1HMXK7OBwOzZs376r1YWFhBqaBCf5LTU8AuOM5iTtNU3pOVlRUyN/fv977PYqRu+66S61atVJZWZnb+rKyMgUHB9e5T3BwsEfbS1JGRobS09Ndt2tra3XhwgX94he/kM1m82Rk/Ex5ebnCwsJUXFwsPz8/0+MAknhe4s7Dc7LxWJaliooKdenS5ZrbeRQj3t7eio6OVm5urhITEyX9GAq5ublKS0urc5+YmBjl5uZq5syZrnW7du1STExMvcex2+2y2+1u6zp27OjJqLgGPz8//guGOw7PS9xpeE42jmudEbnC45dp0tPTlZycrMGDB2vo0KFaunSpKisrNXnyZElSUlKSQkND5XA4JEnPPfecRo4cqUWLFik+Pl5r1qzRoUOHlJWV5emhAQBAM+RxjEycOFHnzp3TnDlzVFpaqgEDBmjHjh2ui1SLiork5fXTm3RGjBih1atX64UXXtDs2bPVs2dPbdiwQX379m28RwEAAJosm3W9S1zRbFRVVcnhcCgjI+Oql8EAU3he4k7Dc/L2I0YAAIBRfFEeAAAwihgBAABGESMAAMAoYqSF4luTAQB3CmKkBamoqFBWVpaGDh2qqKgo0+MAgHF79uxRZGRknd/z4nQ61adPH/3zn/80MFnLQoy0AAcOHFBycrJCQkL0yiuvaPTo0froo49Mj4UW7L///a/r38XFxZozZ46ef/55/kcft93SpUuVkpJS5yet+vv7a9q0aVq8eLGByVoW3trbTJWWlionJ0dvvvmmysvL9fjjjyszM1OffPKJIiMjTY+HFur48eNKSEhQcXGxevbsqTVr1mjcuHGqrKyUl5eXKisrtX79etfXTQC3Wnh4uHbs2KHevXvXef/nn3+usWPHqqio6DZP1rJwZqQZSkhIUEREhD799FMtXbpU33zzjV577TXTYwGaNWuW+vXrpwMHDmjUqFF66KGHFB8fL6fTqYsXL2ratGlasGCB6THRgpSVlalNmzb13t+6dWudO3fuNk7UMnn8cfC4823fvl3PPvuspk+frp49e5oeB3D5+OOPtWfPHvXv319RUVHKysrSM8884/oKiRkzZmj48OGGp0RLEhoaqhMnTqhHjx513v/pp58qJCTkNk/V8nBmpBn64IMPVFFRoejoaA0bNkzLli3T+fPnTY8F6MKFCwoODpYkdejQQe3bt1enTp1c93fq1EkVFRWmxkML9Mtf/lJ//OMf9f33319133fffae5c+fqoYceMjBZy8I1I81YZWWl1q5dq+zsbB08eFA1NTVavHixnn76afn6+poeDy2Ql5eXysrKFBAQIEny9fXVp59+qu7du0v68ZR5ly5dVFNTY3JMtCBlZWUaNGiQWrVqpbS0NEVEREj68VqR5cuXq6amRkeOHHF9GSxuDWKkhSgoKNCbb76pt956S5cuXdKYMWO0adMm02OhhfHy8tL48eNdXz62efNmjR49Wu3bt5f04xeU7dixgxjBbVVYWKjp06dr586duvIn0WazKS4uTsuXL3fFMm4dYqSFqamp0ebNm5WdnU2M4LabPHnyDW23atWqWzwJcLWLFy/q5MmTsixLPXv2dHsJEbcWMQIAAIziAlYAAGAUMQIAAIwiRgAAgFHECAAAMIoYAQAARhEjAADAKGIEAAAYRYwAAACj/g9tifv6kyRFaAAAAABJRU5ErkJggg==",
+      "image/png": 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",
       "text/plain": [
        "<Figure size 640x480 with 1 Axes>"
       ]
@@ -95,7 +95,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   }
  },
  "nbformat": 4,
diff --git a/tests/test_execute/test_custom_convert_multiple_extensions_cache.xml b/tests/test_execute/test_custom_convert_multiple_extensions_cache.xml
index fe18cdc5..aadb1bae 100644
--- a/tests/test_execute/test_custom_convert_multiple_extensions_cache.xml
+++ b/tests/test_execute/test_custom_convert_multiple_extensions_cache.xml
@@ -19,4 +19,4 @@
                         <literal_block classes="output text_plain" language="myst-ansi" xml:space="preserve">
                             <Figure size 640x480 with 1 Axes>
                     <container mime_type="image/png">
-                        <image candidates="{'*': '_build/jupyter_execute/9af310c61f9e96d898144e35f0dc3bf6757626c2072ad98732a4d71c1ec5ec59.png'}" uri="_build/jupyter_execute/9af310c61f9e96d898144e35f0dc3bf6757626c2072ad98732a4d71c1ec5ec59.png">
+                        <image candidates="{'*': '_build/jupyter_execute/b9d3d90a9968c7fb6f966f8c1b55dff80df38bd15052a845b270a25002d1be72.png'}" uri="_build/jupyter_execute/b9d3d90a9968c7fb6f966f8c1b55dff80df38bd15052a845b270a25002d1be72.png">
diff --git a/tests/test_execute/test_jupyter_cache_path.ipynb b/tests/test_execute/test_jupyter_cache_path.ipynb
index 493dc282..7ff02be9 100644
--- a/tests/test_execute/test_jupyter_cache_path.ipynb
+++ b/tests/test_execute/test_jupyter_cache_path.ipynb
@@ -44,7 +44,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.12.12"
+   "version": "3.13.5"
   },
   "test_name": "notebook1"
  },
diff --git a/tests/test_text_based.py b/tests/test_text_based.py
index 5140de47..ade675a7 100644
--- a/tests/test_text_based.py
+++ b/tests/test_text_based.py
@@ -68,3 +68,25 @@ def test_basic_nometadata(sphinx_run):
     sphinx_run.build()
     # print(sphinx_run.status())
     assert "Found an unexpected `code-cell`" in sphinx_run.warnings()
+
+
+@pytest.mark.sphinx_params(
+    "nested_code_cell_in_tab.md",
+    conf={
+        "nb_execution_mode": "off",
+        "source_suffix": {".md": "myst-nb"},
+        "extensions": ["myst_nb", "sphinx_design"],
+    },
+)
+def test_nested_code_cell_in_tab(sphinx_run):
+    """Code cells nested inside a tab-set should render their source as code blocks."""
+    sphinx_run.build()
+    # Warnings are expected since the cells are nested (not converted to notebook cells)
+    assert "Found an unexpected `code-cell`" in sphinx_run.warnings()
+    # But the code content must still appear in the HTML output
+    html = sphinx_run.get_html()
+    code_blocks = html.find_all("div", class_="highlight")
+    sources = [block.get_text() for block in code_blocks]
+    assert any("hello from standalone cell" in s for s in sources)
+    assert any("hello from tab 1" in s for s in sources)
+    assert any("hello from tab 2" in s for s in sources)
diff --git a/tests/test_text_based/test_basic_run.ipynb b/tests/test_text_based/test_basic_run.ipynb
index 80081d47..d3962895 100644
--- a/tests/test_text_based/test_basic_run.ipynb
+++ b/tests/test_text_based/test_basic_run.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "f0dc5a7d",
+   "id": "53c25963",
    "metadata": {},
    "source": [
     "# a title\n",
@@ -13,7 +13,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "49a06520",
+   "id": "f359604f",
    "metadata": {},
    "outputs": [
     {
@@ -32,14 +32,7 @@
  ],
  "metadata": {
   "author": "Chris",
-  "jupytext": {
-   "text_representation": {
-    "extension": ".md",
-    "format_name": "myst",
-    "format_version": "0.8",
-    "jupytext_version": "1.4.1+dev"
-   }
-  },
+  "file_format": "mystnb",
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
@@ -55,13 +48,13 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.8.10"
+   "version": "3.13.5"
   },
   "source_map": [
-   13,
-   19
+   8,
+   14
   ]
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}
\ No newline at end of file
diff --git a/tests/test_text_based/test_basic_run_exec_off.ipynb b/tests/test_text_based/test_basic_run_exec_off.ipynb
index b07af311..f87f59c5 100644
--- a/tests/test_text_based/test_basic_run_exec_off.ipynb
+++ b/tests/test_text_based/test_basic_run_exec_off.ipynb
@@ -2,7 +2,7 @@
  "cells": [
   {
    "cell_type": "markdown",
-   "id": "f1b10cf9",
+   "id": "310298e4",
    "metadata": {},
    "source": [
     "# a title\n",
@@ -13,7 +13,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "9daa25c2",
+   "id": "51c8920a",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -24,24 +24,17 @@
  ],
  "metadata": {
   "author": "Chris",
-  "jupytext": {
-   "text_representation": {
-    "extension": ".md",
-    "format_name": "myst",
-    "format_version": "0.8",
-    "jupytext_version": "1.4.1+dev"
-   }
-  },
+  "file_format": "mystnb",
   "kernelspec": {
    "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
   "source_map": [
-   13,
-   19
+   8,
+   14
   ]
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}
\ No newline at end of file