Publications by authors named "C C Annunziata"

Background: Cell-free DNA (cfDNA) sequence analysis to screen for fetal aneuploidy can incidentally detect maternal cancer. Additional data are needed to identify DNA-sequencing patterns and other biomarkers that can identify pregnant persons who are most likely to have cancer and to determine the best approach for follow-up.

Methods: In this ongoing study we performed cancer screening in pregnant or postpartum persons who did not perceive signs or symptoms of cancer but received unusual clinical cfDNA-sequencing results or results that were nonreportable (i.

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Background: As machine learning becomes increasingly utilized in orthopaedic clinical research, the application of machine learning methodology to cohort data from the Multicenter ACL Revision Study (MARS) presents a valuable opportunity to translate data into patient-specific insights.

Purpose: To apply novel machine learning methodology to MARS cohort data to determine a predictive model of revision anterior cruciate ligament reconstruction (rACLR) graft failure and features most predictive of failure.

Study Design: Cohort study; Level of evidence, 3.

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Background: Revision anterior cruciate ligament (ACL) reconstruction has been documented to have inferior outcomes compared with primary ACL reconstruction. The reasons why remain unknown.

Purpose: To determine whether surgical factors performed at the time of revision ACL reconstruction can influence a patient's outcome at 6-year follow-up.

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Ovarian cancer, a significant contributor to cancer-related mortality, exhibits limited responsiveness to hormonal therapies targeting the estrogen receptor (ERα). This study aimed to elucidate the mechanisms behind ERα resistance to the therapeutic drug Fulvestrant (ICI182780 or ICI). Notably, compared to the cytoplasmic version, nuclear ERα was minimally degraded by ICI, suggesting a mechanism for drug resistance via the protective confines of the nuclear substructures.

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