The Impact of Job Conditions on Health-Related Quality of Life among Working Japanese Older Adults: A Five-Year Longitudinal Study Using J-MICC Okazaki Study Data

ObjectivesThe number of older adults who continue working after retirement is increasing in Japan. Little is known about how job conditions affect older adults’ health. We examined the association between job conditions and health-related quality of life (HRQOL) during a five-year follow-up study.MethodsThis study included participants aged 65 years or older from the Japan Multi-Institutional Collaborative Cohort Study in the Okazaki area recruited at baseline between 2007 and 2011 and followed up five years later. Participants completed a self-reported questionnaire on the physical and mental health aspects of HRQOL (SF-8™), employment status, and job conditions (job satisfaction, skill use, and job suitability).ResultsData of 1,146 men and 522 women were analyzed (mean age: 69.1 and 68.6 years, respectively). Generalized mixed linear regression analysis revealed that, compared to the not-working group, skill use was positively associated with mental health aspects among men (skill use × time: β = 0.16, SE = 0.08, p < 0.05), while poor job satisfaction and job suitability were negatively associated with mental health aspects among women (job satisfaction, not satisfied × time: β = -0.93, SE = 0.47, p < 0.05; job suitability, not suitable × time: β = -1.06, SE = 0.50, p < 0.05).ConclusionsRegarding job conditions among older adults, skill use in men was marginally associated with mental health, and poor job satisfaction and suitability in women were negatively associated with mental health. Considering the job conditions of older workers is necessary to protect their mental health.     

Mikania micrantha extract enhances cutaneous wound healing activity through the activation of FAK/Akt/mTOR cell signaling pathway

Mikania micrantha (MM) has been traditionally used for various health benefits, including mental health, anti-inflammatory, wound dressing, and healing of sores. However, the molecular mechanisms and dose required for the wound healing activity of MM have yet to be reported. Therefore, a study was conducted to evaluate the wound healing potential of a cold methanolic extract of MM through in vitro and in vivo studies. Human dermal fibroblast adult (HDFa) cells were treated with 0 (control), 75 ng/ml, 125 ng/ml, 250 ng/ml, and 500 ng/ml of MMmethanolic extract (MME) for 24 h. MME at 75 ng/ml has significantly (p˂0.05) promoted HDFa cell proliferation and migration. Further, MME has also been shown to enhance the invasiveness of human umbilical vascular endothelial cells (HUVECs), indicating the neovasculature for wound healing. The tube formation assay demonstrated a significant (p<0.05) increase in the angiogenic effect of the MME starting at a concentration of 75 ng/ml as compared to the control. Treatment of excision wounds in Wistar rats with 5% and 10% MME ointment significantly enhanced wound contraction compared to control animals. Incision wounds in rats treated with 5% and 10% MME showed a significant (p<0.01) increase in tensile strength compared to control. HDFa cells, and granulation tissue collected on day 14 post-wounding, revealed the modulation of the FAK/Akt/mTOR cell signaling pathway during the enhancement of wound healing. The results of gel zymography showed increased activity of MMP-2 and MMP-9 in the HDFa cells after treatment with the extract.  It is concluded that MMEcan potentially accelerate cutaneous wound healing.     

Patient-Centered Framework for Rehabilitation Research in Outpatient Settings

Conducting high-quality clinical research is dependent on merging scientific rigor with the clinical environment. This is often a complex endeavor that may include numerous barriers and competing interests. Overcoming these challenges and successfully integrating clinical research programs into clinical practice settings serving rehabilitation outpatients is beneficial from both a logistical perspective (eg, supports efficient and successful research procedures) and the establishment of a truly patient-centered research approach. Leveraging our experience with navigating this research-clinical care relationship, this article (1) proposes the Patient-Centered Framework for Rehabilitation Research, a model for integrating patient-centered research in an outpatient clinical setting that incorporates a collaborative, team-based model encompassing patient-centered values, as well as strategies for recruitment and retention, with a focus on populations living with disabilities or chronic diseases; (2) describes application of this framework in a comprehensive specialty multiple sclerosis center with both general strategies and specific examples to guide adaptation and implementation in other settings; and (3) discusses the effect of the framework as a model in 1 center, as well as the need for additional investigation and adaptation for other populations. The 5 interconnected principles incorporated in the Framework and which prioritize patient-centeredness include identifying shared values, partnering with the clinical setting, engaging with the population, building relationships with individuals, and designing accessible procedures. The Patient-Centered Framework for Rehabilitation Research is a model presented as an adaptable roadmap to guide researchers in hopes of not only improving individual patients’ experiences but also the quality and relevance of rehabilitation research as a whole. Future investigation is needed to test the Framework in other settings.     

Analysis of the fluid biochemistry in patients with prolonged wound drainage after hip hemiarthroplasty

IntroductionThe origin and content of prolonged wound drainage (PWD) after arthroplasty remain uncertain. In this study, we performed the biochemical, biological and advanced proteomic analysis of the drainage fluid collected from PWD patients following hip hemiarthroplasty (HA).MethodsData of 28 patients who developed PWD after HA were prospectively analyzed. After examining the biochemical content of the drainage fluid collected on postoperative day 6, to find out if the drainage fluid was transudate or exudate, it was compared with the patient's serum values according to the Light criteria. Subsequently, biological and proteomic analyzes of both drainage fluid and serum were performed. The similarities and differences in terms of protein concentrations, protein identities were examined. In the drainage fluid, we analyzed lymph-specific proteins.Results16 patients with PWD were male (61.1%), 12 were female (38.9%), and the mean age of all patients was 79.64 ± 8.44 (65-95). Biochemical test results of the drainage fluid / serum were as follows: Total protein: 2.1 / 5.2 g/dl, albumin: 1.3 / 3.1 g/dl, lactate dehydrogenase (LDH): 121/324 U/l, cholesterol: 28/160 mg/dl, triglyceride: 37/122 mg/dl, sodium (Na): 140/ 140mg/dl, potassium (K): 4.1/ 4.1 mg/dl. pH of the drainage fluid was 7.6. According to these biochemical values, drainage fluid was classified as transudate. As a result of protein identification, fibrinogen beta chain, keratin type 1, creatine kinase M-type protein were detected in drainage fluid. Subsequent western analysis revealed that, gliseraldehyde-3-phosphate dehydrogenase (GAPDH) and beta actin antibody were detected in the drainage fluid but not in serum.ConclusionDespite the similarity in serum and transudative PWD fluid in terms of biochemical content, we found that when we carried out further proteomic analysis, PWD contains lymph-specific proteins. Unlike PWD, these proteins were not determined in serum. PWD fluid can be also called as lymphorrhea. PWD fluid with abundant proteins may also provide an appropriate environment for the growth of microorganisms.     

Machine learning models for Parkinson’s disease detection and stage classification based on spatial-temporal gait parameters

BackgroundParkinson’s disease (PD) is a chronic and progressive neurodegenerative disease with no cure, presenting a challenging diagnosis and management. However, despite a significant number of criteria and guidelines have been proposed to improve the diagnosis of PD and to determine the PD stage, the gold standard for diagnosis and symptoms monitoring of PD is still mainly based on clinical evaluation, which includes several subjective factors. The use of machine learning (ML) algorithms in spatial-temporal gait parameters is an interesting advance with easy interpretation and objective factors that may assist in PD diagnostic and follow up.Research questionThis article studies ML algorithms for: i) distinguish people with PD vs. matched-healthy individuals; and ii) to discriminate PD stages, based on selected spatial-temporal parameters, including variability and asymmetry.MethodsGait data acquired from 63 people with PD with different levels of PD motor symptoms severity, and 63 matched-control group individuals, during self-selected walking speed, was study in the experiments.ResultsIn the PD diagnosis, a classification accuracy of 84.6 %, with a precision of 0.923 and a recall of 0.800, was achieved by the Naïve Bayes algorithm. We found four significant gait features in PD diagnosis: step length, velocity and width, and step width variability. As to the PD stage identification, the Random Forest outperformed the other studied ML algorithms, by reaching an Area Under the ROC curve of 0.786. We found two relevant gait features in identifying the PD stage: stride width variability and step double support time variability.SignificanceThe results showed that the studied ML algorithms have potential both to PD diagnosis and stage identification by analysing gait parameters.     

Biomechanical comparison of three internal fixation configurations for low transcondylar fractures of the distal humerus

BackgroundWe aimed to evaluate the biomechanical stiffness and strength of different internal fixation configurations and find suitable treatment strategies for low transcondylar fractures of the distal humerus.Methods and materialsThirty 4^th generation composite humeri were used to create low transcondylar fracture models that were fixed by orthogonal and parallel double plates as well as posterolateral plate and medial screw (PPMS) configurations (n=10 in each group) using an anatomical locking compression plate-screw system and fully threaded medial cortical screws. Posterior bending (maximum 50 N), axial loading (maximum 200 N) and internal rotation (maximum 10 N·m) were tested, in that order, for each specimen. Stiffness under different biomechanical settings among different configurations were compared. Another 18 sets of fracture models were created using these three configurations (n=6 in each group) and the load to failure under axial loading among different configurations was compared.ResultsUnder posterior bending, the stiffness of parallel group was higher than orthogonal group (P<0.001), and orthogonal group was higher than PPMS group (P<0.001). Under axial loading, the stiffness of parallel group was higher than orthogonal group (P=0.001) and PPMS group (P<0.001); however, the difference between orthogonal and PPMS group was not statistically significant (P>0.05). Under internal rotation, the stiffness of parallel group was higher than orthogonal group (P=0.044), and orthogonal group was higher than PPMS group (P=0.029). In failure test under axial loading, the load to failure in the orthogonal group was lower than parallel group (P=0.009) and PPMS group (P=0.021), but the difference between parallel group and PPMS group was not statistically significant (P>0.05). All specimens in orthogonal group demonstrated “distal medial failure”; most specimens had “distal medial and trochlear failure” in the parallel group; most specimens exhibited “contact failure” in the PPMS group.ConclusionFor treating low transcondylar fractures, the overall stiffness and strength of the parallel configuration were superior to those of the orthogonal and PPMS configurations. Nevertheless, the PPMS configuration can provide adequate stability and stiffness comparable to double-plate configurations under axial loading. Therefore, the PPMS construct may have certain clinical value.     

Development of a trail running injury screening instrument: A multiple methods approach

ObjectiveTo develop a trail running injury screening instrument (TRISI) for utilisation as clinical decision aid in determining if a trail runner is at an increased risk for injury.DesignMultiple methods approach.MethodsThe study utilised five phases 1) identification of injury risk factors 2) determining the relevance of each identified risk factor in a trail running context, 3) creating the content of the Likert scale points from 0 to 4, 4) rescaling the Likert scale points to determine numerical values for the content of each Likert scale point, and 5) determining a weighted score for each injury risk factor that contributes to the overall combined composite score.ResultsOf the 77 identified injury risk factors, 26 were deemed relevant in trail running. The weighted score for each injury risk factor ranged from 2.21 to 5.53 with the highest calculated score being 5.53. The final TRISI includes risk categories of training, running equipment, demographics, previous injury, behavioural, psychological, nutrition, chronic disease, physiological, and biomechanical factors.ConclusionThe developed TRISI aims to assist the clinician during pre-race injury screening or during a training season to identify meaningful areas to target in designing injury risk management strategies and/or continuous health education.