Is Artificial Intelligence a Useful Tool for Clinical Practice of Oral and Maxillofacial Surgery?

This study aimed to assess the usefulness of ChatGPT Plus generated responses to clinical-specific questions in oral and maxillofacial surgery. This cross-sectional study was conducted with questions composed according to the Clinical Practise Guide of Ege University, School of Dentistry, and with different subjects of oral and maxillofacial surgery at the undergraduate level. These questions were classified according to their difficulty level (easy, medium, and hard) and inputted into ChatGPT Plus. Three researchers evaluated the responses using a 7-point Likert-type accuracy scale and a modified global quality scale (range: 1-5). Also, error analysis was carried out for the questions scored ≤4 according to the accuracy assessment. A total of 66 questions were enrolled in this study. The questions included dental anesthesia, tooth extraction, preoperative and postoperative complications, suturing, writing prescriptions, and temporomandibular joint examination. The median accuracy score of ChatGPT Plus responses was 5, with 75% of the responses scoring 4 or above. The median quality score was 4, with 75% of the responses scoring 3 or above. There was a significant difference among the 3 difficulty levels, both in accuracy and quality scores (P<0.001 and 0.001, respectively). The median scores of hard-level questions were found to be lower than the easy-level and medium-level questions. The study outcomes emphasized high accuracy and quality in ChatGPT Plus's responses, except for the questions requiring a detailed response or a comment.

SAP domain-dependent Mkl1 signaling stimulates proliferation and cell migration by induction of a distinct gene set indicative of poor prognosis in breast cancer patients.

BACKGROUND: The main cause of death of breast cancer patients is not the primary tumor itself but the metastatic disease. Identifying breast cancer-specific signatures for metastasis and learning more about the nature of the genes involved in the metastatic process would 1) improve our understanding of the mechanisms of cancer progression and 2) reveal new therapeutic targets. Previous studies showed that the transcriptional regulator megakaryoblastic leukemia-1 (Mkl1) induces tenascin-C expression in normal and transformed mammary epithelial cells. Tenascin-C is known to be expressed in metastatic niches, is highly induced in cancer stroma and promotes breast cancer metastasis to the lung. METHODS: Using HC11 mammary epithelial cells overexpressing different Mkl1 constructs, we devised a subtractive transcript profiling screen to identify the mechanism by which Mkl1 induces a gene set co-regulated with tenascin-C. We performed computational analysis of the Mkl1 target genes and used cell biological experiments to confirm the effect of these gene products on cell behavior. To analyze whether this gene set is prognostic of accelerated cancer progression in human patients, we used the bioinformatics tool GOBO that allowed us to investigate a large breast tumor data set linked to patient data. RESULTS: We discovered a breast cancer-specific set of genes including tenascin-C, which is regulated by Mkl1 in a SAP domain-dependent, serum response factor-independent manner and is strongly implicated in cell proliferation, cell motility and cancer. Downregulation of this set of transcripts by overexpression of Mkl1 lacking the SAP domain inhibited cell growth and cell migration. Many of these genes are direct Mkl1 targets since their promoter-reporter constructs were induced by Mkl1 in a SAP domain-dependent manner. Transcripts, most strongly reduced in the absence of the SAP domain were mechanoresponsive. Finally, expression of this gene set is associated with high-proliferative poor-outcome classes in human breast cancer and a strongly reduced survival rate for patients independent of tumor grade. CONCLUSIONS: This study highlights a crucial role for the transcriptional regulator Mkl1 and its SAP domain during breast cancer progression. We identified a novel gene set that correlates with bad prognosis and thus may help in deciding the rigor of therapy.

CCN4/WISP1 (WNT1 inducible signaling pathway protein 1): a focus on its role in cancer.

The matricellular protein WISP1 is a member of the CCN protein family. It is induced by WNT1 and is a downstream target of ß-catenin. WISP1 is expressed during embryonic development, wound healing and tissue repair. Aberrant WISP1 expression is associated with various pathologies including osteoarthritis, fibrosis and cancer. Its role in tumor progression and clinical outcome makes WISP1 an emerging candidate for the detection and treatment of tumors.