Results 261 to 270 of about 4,496,142 (349)

A sudden shift for Pain Medicine fellowships - A recount of the 2024 match. [PDF]

open access: yesInterv Pain Med
Christiansen S   +3 more
europepmc   +1 more source

Viscoelasticity, Lubricity, and Wear Prevention of Cross‐Linked Mucin Gels

open access: yesAdvanced Materials Interfaces, EarlyView.
Physiologically, biolubrication by mucus reduces friction and protects tissues from tribological stress, with mucins playing a key role. This study compares mucin‐based gels with distinct crosslinking architectures to explore their effect on the lubrication and wear prevention abilities of reconstituted mucin gels.
Chiara Gunnella   +2 more
wiley   +1 more source

Implantable Microarray Patch: Engineering at the Nano and Macro Scale for Sustained Therapeutic Release via Synthetic Biodegradable Polymers

open access: yesAdvanced Materials Technologies, Volume 10, Issue 6, March 18, 2025.
This review focuses on the application of synthetic biodegradable microarray patches (MAPs) in sustained drug delivery. Compared to conventional MAPs which release drugs into the skin in an immediate manner, these implantable MAPs release drugs into skin microcirculation gradually as the biodegradable polymers degrade, thus offering sustained release ...
Li Zhao   +6 more
wiley   +1 more source

Prevalence of Burnout Among Pain Medicine Physicians and Its Potential Effect upon Clinical Outcomes in Patients with Oncologic Pain or Chronic Pain of Nononcologic Origin

open access: yesPain medicine (Malden, Mass.), 2018
I. Riquelme   +6 more
semanticscholar   +1 more source

AI‐Enhanced Gait Analysis Insole with Self‐Powered Triboelectric Sensors for Flatfoot Condition Detection

open access: yesAdvanced Materials Technologies, Volume 10, Issue 6, March 18, 2025.
The given research presents an innovative insole‐based device employing self‐powered triboelectric nanogenerators (TENG) for flatfoot detection. By integrating TENG tactile sensors within an insole, the device converts mechanical energy from foot movements to electrical signals analyzed via machine learning, achieving an 82% accuracy rate in flatfoot ...
Moldir Issabek   +7 more
wiley   +1 more source

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