Rotator cuff (RC) injuries are characterized by tendon rupture, muscle atrophy, retraction, and fatty infiltration, which increase injury severity and jeopardize adequate tendon repair. Epigenetic drugs, such as histone deacetylase inhibitors (HDACis), possess the capacity to redefine the molecular signature of cells, and they may have the potential to inhibit the transformation of the fibro-adipogenic progenitors (FAPs) within the skeletal muscle into adipocyte-like cells, concurrently enhancing the myogenic potential of the satellite cells. HDACis were added to FAPs and satellite cell cultures isolated from mice. The HDACi vorinostat was additionally administered into a RC injury animal model. Histological analysis was carried out on the isolated supra- and infraspinatus muscles to assess vorinostat anti-muscle degeneration potential.Aims
Methods
The optimal choice of management for proximal humerus fractures (PHFs) has been increasingly discussed in the literature, and this work aimed to answer the following questions: 1) what are the incidence rates of PHF in the geriatric population in the USA; 2) what is the mortality rate after PHF in the elderly population, specifically for distinct treatment procedures; and 3) what factors influence the mortality rate? PHFs occurring between 1 January 2009 and 31 December 2019 were identified from the Medicare physician service records. Incidence rates were determined, mortality rates were calculated, and semiparametric Cox regression was applied, incorporating 23 demographic, clinical, and socioeconomic covariates, to compare the mortality risk between treatments.Aims
Methods
An objective technological solution for tracking adherence to at-home shoulder physiotherapy is important for improving patient engagement and rehabilitation outcomes, but remains a significant challenge. The aim of this research was to evaluate performance of machine-learning (ML) methodologies for detecting and classifying inertial data collected during in-clinic and at-home shoulder physiotherapy exercise. A smartwatch was used to collect inertial data from 42 patients performing shoulder physiotherapy exercises for rotator cuff injuries in both in-clinic and at-home settings. A two-stage ML approach was used to detect out-of-distribution (OOD) data (to remove non-exercise data) and subsequently for classification of exercises. We evaluated the performance impact of grouping exercises by motion type, inclusion of non-exercise data for algorithm training, and a patient-specific approach to exercise classification. Algorithm performance was evaluated using both in-clinic and at-home data.Aims
Methods
Objectives. To report the five-year results of a randomised controlled trial
examining the
