A question about document tokenization

Hi, I found a very interesting result to tokenize a document. The example code is:

```
import spacy

nlp = spacy.load("en_core_web_sm")
# doc = nlp("Apple is looking at. startup for $1 billion.")
# for token in doc:
# print(token.text, token.pos_, token.dep_)
# Example text
text = '''Panel C: Gene Associations in LUAD and NATs

In LUAD tumors, ZNF71 is associated with JUN, SAMHD1, RNASEL, IFNGR1, IKKB, and EIF2A.
In non-cancerous adjacent tissues (NATs), the associated genes are OAS1, MP3K7, and IFNAR2.'''

# Process the text
doc = nlp(text)
out_sen = []
# Iterate over the sentences
for sent in doc.sents:
if len(sent) != 0:
print(sent.text)
out_sen.append(sent)
```

The result out_sen's length is 1, and it is treated as a whole sentence. Is this a bug or sth by default? Thanks.

The spacy version is 3.7.6