Results 161 to 170 of about 6,097,379 (251)

Somatic cell reprogramming for Parkinson's disease treatment

Ibrain, Volume 11, Issue 1, Page 59-73, Spring 2025.
The fundamental purpose of cell reprogramming to treat Parkinson's disease is to generate dopaminergic neurons (DAN) and do transplantation. There are two ways to accomplish this. One method is to induce cells into induced DA neurons (iDAN) directly or to induce cells into induced pluripotent stem cells and ultimately into iDAN in vitro. Another option
Xiaozhuo Li, Kevin Fang, Fengping Wang
wiley   +1 more source

Commissioning a single photon counting CT simulator for radiotherapy planning: Methods, challenges, and initial results. [PDF]

J Appl Clin Med Phys
Basran PS, Richtsmeier D.
europepmc   +1 more source

Living at genetic risk: The patient experience of Lynch syndrome

International Journal of Cancer, EarlyView.
Abstract Lynch syndrome is a germline cancer predisposition syndrome caused by a variant in one of four genes. Lynch syndrome places individuals at significantly higher risk for a range of cancers, especially colorectal and endometrial. Depending on which gene is affected, the risk of ovarian, gastric, small bowel, pancreatic, biliary urothelial, brain,
Nicola Reents, Georgina Hoffmann, Kelly Kohut   +2 more
wiley   +1 more source

Real-world clinical impact of implementing and updating a deep learning-based automatic contouring system in rectal cancer radiotherapy. [PDF]

J Appl Clin Med Phys
Wang N, Xu T, Kang Y, Liang Y, Wang W, Nie W, Dai J, Tang Y, Men K.   +8 more
europepmc   +1 more source

Assessment of Cancer‐Related Cognitive Impairments Across Anti‐Cancer Therapies in a Predominantly Breast Cancer Cohort

International Journal of Cancer, EarlyView.
ABSTRACT Cancer survivors frequently experience cancer‐related cognitive impairment (CRCI), but the contributions of different anti‐cancer therapies remain unclear. Patients with breast or gynaecological cancer were recruited before any anti‐cancer treatment.
Qiqi Lei, Martina E. Schmidt, Philipp Zimmer, Patric Meyer, Andreas Schneeweiss, Karen Steindorf   +5 more
wiley   +1 more source

Synthetic CT artifacts in MR-only brain radiotherapy: Clinical implementation experience. [PDF]

J Appl Clin Med Phys
Lee H, Ayan AS, Beyer S, Blakaj D, DiCostanzo D, Grecula JC, Palmer J, Raval R, Singh R, Thomas E, Weldon M, Yang X, Zoller W, Gupta N.   +13 more
europepmc   +1 more source

Pretreatment EBV‐DNA/TLG‐Based Risk Stratification Is Associated With Survival Outcomes in Nonmetastatic Nasopharyngeal Carcinoma: An Exploratory Study

International Journal of Cancer, EarlyView.
ABSTRACT Whether combining pretreatment plasma Epstein–Barr virus DNA (EBV‐DNA) with 18F‐FDG PET/CT‐derived total lesion glycolysis (TLG) improves prognostic stratification in nonmetastatic nasopharyngeal carcinoma (NPC) is unclear, particularly in nonendemic populations.
Mehmet Çağrı Duymaz, Ece Özkaya Duymaz, Nazlı Ünsal, Recep Bekiş, Büşra Tozduman, Özgür Appak, Ayşe Demiral, Oğuz Çetinayak   +7 more
wiley   +1 more source

Advancing Tumor Treatment Through Artificial Intelligence and Mathematical Modeling: A Comprehensive Review. [PDF]

Health Sci Rep
Kamran M, Majeed A, Haque ASMR, Abdullah JY.   +3 more
europepmc   +1 more source

Longitudinal Associations of Oxaliplatin Treatment With Chemotherapy‐Induced Peripheral Neuropathy in Colorectal cancer Survivors up to 2 Years Post‐Treatment

International Journal of Cancer, EarlyView.
ABSTRACT Chemotherapy‐induced peripheral neuropathy (CIPN) is a potentially long‐term consequence of oxaliplatin‐based chemotherapy for colorectal cancer (CRC). Oxaliplatin dosing is based on body surface area (BSA), but lean body mass (LBM) may influence susceptibility to long‐term CIPN.
Nadira R. Querido, Martijn J. L. Bours, Liselot Valkenburg‐van Iersel, Antoinetta J. M. Beijers, Stephanie O. Breukink, Maryska L. G. Janssen‐Heijnen, Eric T. P. Keulen, Joop L. M. Konsten, Judith de Vos‐Geelen, Matty P. Weijenberg, Colinda C. J. M. Simons   +10 more
wiley   +1 more source

Pulmonary ventilation images from planning CT images using deep learning on locally-advanced NSCLC patients. [PDF]

J Appl Clin Med Phys
Katsuta Y, Hoshino T, Yamamoto T, Kadoya N, Tanaka S, Arai K, Umezawa R, Takahashi N, Jingu K.   +8 more
europepmc   +1 more source