Results 141 to 150 of about 117,548 (332)

Use of Restricted Nursing and a Bovine Appeasing Substance on the Welfare, Growth Performance, and Response to Vaccination of Beef Calves at Weaning

Animal Research and One Health, EarlyView.
The effects of restricted nursing (RN) and the administration of a bovine appeasing substance (BAS) on days −8 and 0 in relation to weaning were evaluated. Both strategies were effective in improving the growth performance of beef calves. Regarding welfare, BAS ‐especially on day 0‐ was more effective than RN.
Denise E. Mussalafo, Marcelo Vedovatto, Aylpy R. D. Santos, Dalton M. Oliveira, Fabiana A. M. Sterza, Mariana Santos, Helena B. C. R. Batista, Jaíne G. Garcia, Andréa R. D. L. Souza   +8 more
wiley   +1 more source

Rehabilitation Interventions Delivered via Telehealth to Support Self‐Management of Rheumatic and Musculoskeletal Disease: A Scoping Review

Arthritis &Rheumatology, EarlyView.
Objective To identify and summarize existing telerehabilitation interventions for people living with rheumatic and musculoskeletal diseases (RMDs), including the rehabilitation components, the technology used, the type of health care professional (HCP) interaction, and how the effectiveness is evaluated.
Thomas A. Ingram, Rosemarie Barnett, Nuzhat Shakaib, Simon Jones, Raj Sengupta, Peter C. Rouse   +5 more
wiley   +1 more source

Neoplastic Jaw Diseases Giant Cell Tumors of the Medullary Space [PDF]

, 1943
Conrad C. Gilkison
openalex   +1 more source

Genome‐Wide DNA Methylation Study Reveals Specific Signatures in the Affected Arterial Tissue of Patients With Giant Cell Arteritis

Arthritis &Rheumatology, EarlyView.
Objective Giant cell arteritis (GCA) is a large‐vessel vasculitis, potentially causing complications such as blindness and strokes. This study aims to gain insights into the pathogenesis of GCA by identifying specific DNA methylation signatures in the arterial tissue of patients with this vasculitis. Methods DNA methylation profiling was analyzed in 79
Gonzalo Borrego‐Yaniz, Ana Márquez, Elkyn Estupiñán‐Moreno, Laura C. Terrón‐Camero, Miguel A. González‐Gay, Santos Castañeda, Giuliana Guggino, David Saadoun, Pietro Lio, Simona Fontana, Martina Bonacini, Alessandro Rossi, Alberto Cavazza, Francesco Muratore, Carlo Salvarani, Nicolo Pipitone, Javier Martin, Stefania Croci, Lourdes Ortiz‐Fernández   +18 more
wiley   +1 more source

Effect of time to start of biologic therapy on treatment response in childhood arthritis: Results from the UCAN CAN‐DU study

Arthritis &Rheumatology, Accepted Article.
Objective To estimate the effect of time from symptom onset to start of biologic treatment on achieving inactive arthritis within six months in a cohort of juvenile idiopathic arthritis (JIA) patients. Methods The international UCAN CAN‐DU study prospectively enrolls JIA patients across Canada and the Netherlands.
Jelleke B. de Jonge, Sytze de Roock, Dieneke Schonenberg‐Meinema, J. Merlijn van den Berg, Deborah A. Marshall, Sebastiaan J. Vastert, Rae S.M. Yeung, Joost F. Swart, Susanne M. Benseler, The UCAN CAN‐DU and UCAN CURE consortia, Adam Huber, Alan Rosenberg, Alexander Mosoiu, Alisa Rachlis, Amy Xu, Andrea Human, Annet van Royen‐Kerkhof, Arthur Cheng, Berent Prakken, Bianca Lang, Brenleigh Jebb, Brian Feldman, Bruno Pereira, Chelsea DeCoste, Ciarán Duffy, Claire LeBlanc, Clare Hutchinson, Daniah Basodan, Danielle Brinkman, David Cabral, Dax G. Rumsey, Deborah Levy, Dilan Dissanayake, Elizabeth Legger, Elizabeth Stringer, Elizaveta Limenis, Ellen Schatorje, Elodie Boudes, Erika Van Nieuwenhove, Erkan Demirkaya, Esther Hoppenreijs, Evelyn Rozenblyum, Gaëlle Chédeville, Gillian Currie, Giske Biesbroek, Gordon Soon, Harper Cheng, Heinrike Schmeling, Herman Tam, Hon Yan Ng, Jaime Guzman, Jeanine McColl, Jennifer Ji Young Lee, Jonathan Park, Joseph Cafazzo, Kate Neufeld, Kim Morishita, Kristin Houghton, Liane Heale, Lillian Lim, Lily Lim, Lori Tucker, Lynn Spiegel, Maarten IJzerman, Marc Jansen, Mariken Gruppen, Marinka Twilt, Marleen Verkaaik, Mehul Jariwala, Mercedes Chan, Michelle Batthish, Michelle Kip, Muhammed Dhalla, Nadia Luca, Nickolas Blanchette, Nico Wulffraat, Nicole Johnson, Paivi Miettunen, Paul Dancey, Petra Hissink Muller, Philomine van Pelt, Piya Lahiry, Ravneet Sran, Rayfel Schneider, Rebeka Stevenson, Regina de Geus, Roberta Berard, Roman Jurencak, Ronald Laxer, Rosie Scuccimarri, Ross Petty, Ruud Verstegen, Sarah Campillo, Shirley Tse, Suzanne Ramsey, Sylvia Kamphuis, Tala El Tal, Tania Cellucci, Tara McGrath, Tommy Gerschman, Trang Duong, Tristan Kerr, Wineke Armbrust   +102 more
wiley   +1 more source

Disease-specific risk for an osteonecrosis of the jaw under bisphosphonate therapy

, 2009
T. Jung, Falk Hoffmann, Gerd Glaeske, Dieter Felsenberg   +3 more
openalex   +2 more sources

The issues caused by misinformation—How workers and organizations deal with it: A systematic literature review. An Annual Review of Information Science and Technology (ARIST) paper

Journal of the Association for Information Science and Technology, EarlyView.
Abstract In today's digital age, misinformation propagates rapidly through digital channels, blurring the lines between truth and fiction, and challenging the foundations of trust in information sources. Although affecting all spheres of life, misinformation poses a significant threat to workers highlighting a critical intersection between ...
Ashwani Malhotra, Nina Evans, Jing Gao, Jia Tina Du, Connie Zheng   +4 more
wiley   +1 more source

A Mysterious Disease - Osteonecrosis of the Jaw [PDF]

, 2017
Yi-Fang Huang
openalex   +1 more source

Evaluating and leveraging large language models in clinical pharmacology and therapeutics assessment: From exam takers to exam shapers

British Journal of Clinical Pharmacology, EarlyView.
Aims In medical education, the ability of large language models (LLMs) to match human performance raises questions about their potential as educational tools. This study evaluates LLMs' performance on Clinical Pharmacology and Therapeutics (CPT) exams, comparing their results to medical students and exploring their ability to identify poorly formulated
Alexandre O. Gérard, Diane Merino, Marc Labriffe, Fanny Rocher, Delphine Viard, Laurence Zemori, Thibaud Lavrut, Erik M. Donker, Joost D. Piët, Jean‐Paul Fournier, Milou‐Daniel Drici, Alexandre Destere   +11 more
wiley   +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