valid_low_IDs contains character vectors that appear to be file names:
valid_low_IDs
valid_low_IDs = 
    {'5beeea64a79efb0001faf30a.csv'         }
    {'5db9e0044a8eb40431d5e782.csv'         }
    {'5e8ef2059eeb7a1af7502f3c - edited.csv'}
    {'5e67640d82b4784eb93f1a32.csv'         }
    {'5ed5aeea88fecc14779b4a29 - edited.csv'}
    {'5f8998f6bfe9d6067c4b8a72.csv'         }
    {'5fc959ba27fabf4111b918ec - edited.csv'}
    {'5ff0a3d22c2ee6fa5d47c312 - edited.csv'}
    {'59a9c0291b7a550001d6392e.csv'         }
    {'60b43c11dcee60f547e013ba.csv'         }
    {'60fdf891d19fd767ebc5eefc.csv'         }
    {'598fa1b80675b100014dacf3.csv'         }
    {'614e51ba8bd7590a59e92f9c.csv'         }
    {'6019ec157baab31e1ad590fc.csv'         }
    {'6079c41a26b231701ceb1e0a.csv'         }
    {'6089aa8120d7418a70f3eba7.csv'         }
    {'60243c357e64550d96eb47f6.csv'         }
So the non-ID parts of those file names need to be removed. Here's one way:
IDs = strrep(strrep(valid_low_IDs,' - edited',''),'.csv','')
IDs = 
    {'5beeea64a79efb0001faf30a'}
    {'5db9e0044a8eb40431d5e782'}
    {'5e8ef2059eeb7a1af7502f3c'}
    {'5e67640d82b4784eb93f1a32'}
    {'5ed5aeea88fecc14779b4a29'}
    {'5f8998f6bfe9d6067c4b8a72'}
    {'5fc959ba27fabf4111b918ec'}
    {'5ff0a3d22c2ee6fa5d47c312'}
    {'59a9c0291b7a550001d6392e'}
    {'60b43c11dcee60f547e013ba'}
    {'60fdf891d19fd767ebc5eefc'}
    {'598fa1b80675b100014dacf3'}
    {'614e51ba8bd7590a59e92f9c'}
    {'6019ec157baab31e1ad590fc'}
    {'6079c41a26b231701ceb1e0a'}
    {'6089aa8120d7418a70f3eba7'}
    {'60243c357e64550d96eb47f6'}
On the other hand, low_condition(:,1) is a cell array of (scalar) string arrays:
disp(low_condition(:,1))
    {["59a9c0291b7a550001d6392e"          ]}
    {["60243c357e64550d96eb47f6"          ]}
    {["6019ec157baab31e1ad590fc"          ]}
    {["614e51ba8bd7590a59e92f9c"          ]}
    {["60fdf891d19fd767ebc5eefc"          ]}
    {["5beeea64a79efb0001faf30a"          ]}
    {["5fc959ba27fabf4111b918ec"          ]}
    {["6079c41a26b231701ceb1e0a"          ]}
    {["5d6069f53f69fd0001c0e77f"          ]}
    {["6033acf84fec17043ffef374"          ]}
    {["5efd8bbe8f20d51cd2ab9327"          ]}
    {["608d4e91d08ff4d32dbba3ad"          ]}
    {["60b43c11dcee60f547e013ba"          ]}
    {["615d8b5b98addf4b3d65c41d"          ]}
    {["5ff0a3d22c2ee6fa5d47c312"          ]}
    {["60cef6bc855784dee78ffffd"          ]}
    {["6089aa8120d7418a70f3eba7"          ]}
    {["5c6400cbcb937d00012d8866"          ]}
    {["611cf405ca55c42b27807c3c"          ]}
    {["60b65dd419636fbf792d4470"          ]}
    {["5db9e0044a8eb40431d5e782"          ]}
    {["5dc32687547c1f24648b7c23"          ]}
    {["61742bd3cd78a9f853168cef"          ]}
    {["615c343a80f9bb6fd7362271"          ]}
    {["615db68d9d021708b6e64603"          ]}
    {["5e67640d82b4784eb93f1a32"          ]}
    {["5f8998f6bfe9d6067c4b8a72"          ]}
    {["60ac8807aaad354f950dd131"          ]}
    {["608ac09acb49bef04cade936"          ]}
    {["https://we.tl/t-eeVxbz35Vq?src=dnl"]}
    {["5e83b43765a5720e30b71b37"          ]}
    {["5ed5aeea88fecc14779b4a29"          ]}
    {["5d175bfe7a5f6d001a64b545"          ]}
    {["598fa1b80675b100014dacf3"          ]}
    {["5aa67d76f053610001726e65"          ]}
    {["61133a6bb907d515d390d08b"          ]}
    {["5e8ef2059eeb7a1af7502f3c"          ]}
    {[""                                  ]}
Convert it to a cell array of character vectors, stored here as cond:
cond = cellstr(low_condition(:,1));
disp(cond)
    {'59a9c0291b7a550001d6392e'          }
    {'60243c357e64550d96eb47f6'          }
    {'6019ec157baab31e1ad590fc'          }
    {'614e51ba8bd7590a59e92f9c'          }
    {'60fdf891d19fd767ebc5eefc'          }
    {'5beeea64a79efb0001faf30a'          }
    {'5fc959ba27fabf4111b918ec'          }
    {'6079c41a26b231701ceb1e0a'          }
    {'5d6069f53f69fd0001c0e77f'          }
    {'6033acf84fec17043ffef374'          }
    {'5efd8bbe8f20d51cd2ab9327'          }
    {'608d4e91d08ff4d32dbba3ad'          }
    {'60b43c11dcee60f547e013ba'          }
    {'615d8b5b98addf4b3d65c41d'          }
    {'5ff0a3d22c2ee6fa5d47c312'          }
    {'60cef6bc855784dee78ffffd'          }
    {'6089aa8120d7418a70f3eba7'          }
    {'5c6400cbcb937d00012d8866'          }
    {'611cf405ca55c42b27807c3c'          }
    {'60b65dd419636fbf792d4470'          }
    {'5db9e0044a8eb40431d5e782'          }
    {'5dc32687547c1f24648b7c23'          }
    {'61742bd3cd78a9f853168cef'          }
    {'615c343a80f9bb6fd7362271'          }
    {'615db68d9d021708b6e64603'          }
    {'5e67640d82b4784eb93f1a32'          }
    {'5f8998f6bfe9d6067c4b8a72'          }
    {'60ac8807aaad354f950dd131'          }
    {'608ac09acb49bef04cade936'          }
    {'https://we.tl/t-eeVxbz35Vq?src=dnl'}
    {'5e83b43765a5720e30b71b37'          }
    {'5ed5aeea88fecc14779b4a29'          }
    {'5d175bfe7a5f6d001a64b545'          }
    {'598fa1b80675b100014dacf3'          }
    {'5aa67d76f053610001726e65'          }
    {'61133a6bb907d515d390d08b'          }
    {'5e8ef2059eeb7a1af7502f3c'          }
    {0×0 char                            }
Now you can compare the two using ismember, and keep the relevant rows of low_condition:
to_keep = ismember(cond,IDs);
low_condition_keep = low_condition(to_keep,:)