Results 191 to 200 of about 86,128 (293)

e0644 Establishment of contrast induced nephropathy model in rats [PDF]

open access: bronze, 2010
F. Xianghua   +7 more
openalex   +1 more source

Extracellular Vesicles: Biology, Intercellular Communication and Therapeutic Potential in Diabetes

open access: yesAdvanced Therapeutics, Volume 9, Issue 2, February 2026.
Exosome packaging in diabetes mellitus is depicted. Induced expression levels of RBP4, WNT related proteins, TGFB1, BMPs, VEGFs, STAT3, Calpain2 and altered expression levels of microRNAs in the exosomes are responsible for the inflammatory actions, defective central metabolism, myofibroblasts proliferation, dysregulated cell migration, cell ...
Swayam Prakash Srivastava   +9 more
wiley   +1 more source

The predictive value of AGEF score for contrast-induced nephropathy in patients with lower extremity peripheral artery disease. [PDF]

open access: yesBMC Cardiovasc Disord
Ilis D   +9 more
europepmc   +1 more source

Engineering Ultrasound Contrast Agents for Targeted Therapeutics: A Theranostic Approach to Drug Delivery, Gene Therapy, and Immunomodulation

open access: yesAdvanced NanoBiomed Research, Volume 6, Issue 2, February 2026.
Ultrasound contrast agents, including microbubbles and nanobubbles, transform imaging and targeted therapy through precise engineering of size, shell composition, and surface properties. This review explores how these innovations enable tissue‐specific delivery, enhance therapeutic efficacy, and extend applications from vascular imaging to tumor ...
Ashkan Seza   +2 more
wiley   +1 more source

Efficacy of Coronary Sinus Aspiration in Reducing Contrast-Induced Nephropathy in High-Risk Patients. [PDF]

open access: yesJACC Adv
Verma S   +6 more
europepmc   +1 more source

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

open access: yesBritish Journal of Clinical Pharmacology, Volume 92, Issue 2, Page 422-444, February 2026.
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   +8 more
wiley   +1 more source

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