Results 141 to 150 of about 5,153,703 (360)

ODP560 Thyroid Hormones membrane receptor, Integrin αvβ3, as a potential prognostic marker of chemotherapy response in breast cancer

, 2022
Mateo Campos Haedo, M Florencia Cayrol, Graciela Cremaschi, M Mercedes Debernardi, Johanna Diaz Albuja, M Celeste Díaz Albuja, M Alejandra Paulazo, Cinthia Rosemblit, Helena Sterle   +8 more
openalex   +1 more source

Pregnancy Outcomes in Women With Systemic Sclerosis Before and/or After Diagnosis and by Parity: A Swedish Population‐Based Cohort Study

Arthritis &Rheumatology, EarlyView.
Objective To assess risks of adverse pregnancy outcomes (APOs) in a contemporary cohort of women with systemic sclerosis (SSc) in relation to the timing of SSc diagnosis and by parity. Methods From the nationwide Swedish Medical Birth Register, we assembled pregnancies with births in women with SSc and in comparator women from the general population ...
Weng Ian Che, Luigi Annicchiarico, Laura Andreoli, Olof Stephansson, Marie Holmqvist, Karin Hellgren   +5 more
wiley   +1 more source

Multi-disease transcriptomic analysis of sex hormone genes reveals a novel prognostic model for thyroid cancer with breast cancer correlations

Frontiers in Oncology
BackgroundThere is a potential bidirectional pathogenicity between thyroid and breast cancers. The association between sex hormones and two types of malignant tumors has emerged as a topic of intense academic debate in recent years.
Lixue Qiao, Hao Li, Keyu Yin, Runsheng Ma, Runsheng Ma, Runsheng Ma, Yifei Zhang, Yifei Zhang, Yue Guo, Detao Yin, Detao Yin, Detao Yin   +11 more
doaj   +1 more source

Integrated analysis of bulk and single cell datasets with experimental validation of cancer stemness function in thyroid cancer prognosis and immunotherapy [PDF]

Zhanrong Feng, Yue Xu, Ying Ding, Xiaoxiao Sun, Qian Zhao, Jingjing Zhu, Qiang Chen, Yang Zhang, Yilai Zhang   +8 more
openalex   +1 more source

Dissection of the VI cervical lymph collector for papillary thyroid cancer

, 2022
Yuriy Aleksandrov, A. D. Dyakiv
openalex   +2 more sources

lncRNA RUNDC3A-AS1 Regulates Proliferation and Apoptosis of Thyroid Cancer Cells via the miR-151b/SNRPB Axis [PDF]

, 2022
Yan Deng, Jie Wu, Xin Li
openalex   +1 more source

Long‐Term Outcomes of Reduced Intensity Conditioning Hematopoietic Stem Cell Transplantation for Systemic Sclerosis Patients with Impaired Cardiac Function

Arthritis &Rheumatology, Accepted Article.
Objective High intensity conditioning autologous hematopoietic stem cell transplantation (AHSCT) is standard of care for patients with advanced SSc. The role of reduced intensity conditioning (RIC) prior to AHSCT in this population remains unclear. We conducted this study to determine the long‐term outcomes of RIC AHSCT in SSc patients with cardiac ...
Yonatan Lean, Carrie Richardson, Anthony Esposito, Katy Bedjeti, George E. Georges   +4 more
wiley   +1 more source

Pharmacokinetic profiles of sertraline in pregnancy as a predictor of postpartum depressive symptoms

British Journal of Clinical Pharmacology, EarlyView.
Aim To characterize pharmacokinetic changes of sertraline and its metabolite during pregnancy and postpartum, and their relationship to maternal postpartum depressive symptoms. Methods This was a prospective observational, longitudinal study of pregnant women with a major depressive disorder treated with sertraline (N = 185 women, 205 pregnancies ...
Sílvia M. Illamola, Zachary N. Stowe, Marc L. Kalin, Michael D. Evans, Catherine M. Sherwin, Maged M. Costantine, D. Jeffrey Newport, James C. Ritchie, Angela K. Birnbaum   +8 more
wiley   +1 more source

Male Sex as a Factor for Larger Size of Nodal Recurrence and More Tumor Burden (Advanced Disease Stage) in Recurrent Well Differentiated Thyroid Cancer [PDF]

, 2018
M.Sc. HAITHAM FEKRY HOSSAM M. FAREED, M.D. MAGDY KOTB TAREK EL-BARADIE, M.D. ISMAEEL A. MORAD INAS EL-ATAR   +2 more
openalex   +1 more source

Machine learning methods for predicting adverse drug events: A systematic review

British Journal of Clinical Pharmacology, EarlyView.
Abstract Predicting adverse drug events (ADEs) in outpatient settings is crucial for improving medication safety, identifying high‐risk patients and reducing health‐care costs. While traditional methods struggle with the complexity of health‐care data, machine learning (ML) models offer improved prediction capabilities; however, their effectiveness in ...
Niaz Chalabianloo, Fatemeh Ahmadi, Mohammad Ali Omrani, Sheikh S. Abdullah, Neda Rostamzadeh, Atefeh Jafari, Lujain Izzedin, Kamran Sedig, Flory T. Muanda   +8 more
wiley   +1 more source