ABSTRACT
The Dallas Heart Study dataset was used to examine relationships between menopausal symptoms and depressive symptom severity in 384 women (37-73 years old) self-reporting as menopausal. Self-reported menopausal symptoms were grouped based on the Menopause-specific Quality of Life Questionnaire (MENQOL). Depressive symptom severity was assessed using the Quick Inventory of Depressive Symptomatology - Self-Report (QIDS-SR). The relationship between menopause symptom groups, ethnicity and QIDS-SR was evaluated using multiple linear regression. Endorsement of sexual symptoms was positively associated with QIDS-SR score (ß = .12, p = .031), suggesting that sexual dysfunction during menopause may be a predictor of underlying depressive symptoms.
Subject(s)
Depression , Menopause , Sexual Dysfunction, Physiological , Adult , Aged , Black People , Depression/ethnology , Female , Hispanic or Latino , Humans , Menopause/ethnology , Middle Aged , Quality of Life , Self Report , Severity of Illness Index , Sexual Dysfunction, Physiological/ethnology , White PeopleABSTRACT
CASE: A 47-year-old woman with adamantinoma of the entire left tibia and distal fibula underwent resection and reconstruction using a total tibia allograft-prosthetic composite with rotating hinged knee replacement and ankle fusion. She is ambulating without tumor recurrence with 2-year follow-up. CONCLUSION: This case report offers a unique reconstruction option for extensive tibia bone primary malignancy. To our knowledge, this is the longest survival for total tibia allograft prosthetic composite reconstruction.
Subject(s)
Adamantinoma/surgery , Arthroplasty, Replacement, Knee , Tibia/transplantation , Allografts , Female , Humans , Middle AgedABSTRACT
Identifying oncogenic drivers and tumor suppressors remains a challenge in many forms of cancer, including rhabdomyosarcoma. Anticipating gene expression alterations resulting from DNA copy-number variants to be particularly important, we developed a computational and experimental strategy incorporating a Bayesian algorithm and CRISPR/Cas9 "mini-pool" screen that enables both genome-scale assessment of disease genes and functional validation. The algorithm, called iExCN, identified 29 rhabdomyosarcoma drivers and suppressors enriched for cell-cycle and nucleic-acid-binding activities. Functional studies showed that many iExCN genes represent rhabdomyosarcoma line-specific or shared vulnerabilities. Complementary experiments addressed modes of action and demonstrated coordinated repression of multiple iExCN genes during skeletal muscle differentiation. Analysis of two separate cohorts revealed that the number of iExCN genes harboring copy-number alterations correlates with survival. Our findings highlight rhabdomyosarcoma as a cancer in which multiple drivers influence disease biology and demonstrate a generalizable capacity for iExCN to unmask disease genes in cancer.
