Playing basketball and volleyball during adolescence is associated with higher bone mineral density in old age: the Bunkyo Health Study

Introduction: Exercise is beneficial for increasing areal bone mineral density (aBMD) in adolescence and maintaining it in old age. Moreover, high-impact sports are more effective than low-impact sports in increasing aBMD. This study aimed to determine the types of adolescent sports played in school-based sports clubs associated with aBMD in old age.Methods: In total, 1,596 older adults (681 men and 915 women, age: 65–84 years) living in an urban area of Japan were evaluated for the femoral neck and lumbar spine aBMD using dual-energy X-ray absorptiometry. The association between adolescent sports played in sports clubs and aBMD in old age was analyzed using multiple regression analysis, with femoral neck and lumbar spine aBMD as dependent variables, and sports type and participant characteristics such as age, body weight, and serum 25-hydroxyvitamin D [25(OH)D] level, as independent variables.Results: For the femoral neck, basketball was associated with aBMD in older men (β = 0.079, p < 0.05) and women (β = 0.08, p < 0.01), whereas current body weight and 25(OH)D level were associated with aBMD in both sexes. For the lumbar spine, volleyball (β = 0.08, p < 0.01) and swimming (β = 0.06, p < 0.05) was significantly associated with lumbar spine aBMD, whereas current body weight, 25(OH)D, and diabetes mellitus were associated with aBMD in older women.Conclusion: Both men and women who played basketball in adolescence had higher femoral neck aBMD in old age. Moreover, women who played volleyball in adolescence had higher lumbar spine aBMD in old age

The role of AmeloD in tooth development

The development of ectodermal organs, such as teeth, requires epithelial–mesenchymal interactions. Basic helix–loop–helix (bHLH) transcription factors regulate various aspects of tissue development, and we have previously identified a bHLH transcription factor, AmeloD, from a tooth germ cDNA library. Here, we provide both in vitro and in vivo evidence that AmeloD is important in tooth development. We created AmeloD-knockout (KO) mice to identify the in vivo functions of AmeloD that are critical for tooth morphogenesis. We found that AmeloD-KO mice developed enamel hypoplasia and small teeth because of increased expression of E-cadherin in inner enamel epithelial (IEE) cells, and it may cause inhibition of the cell migration. We used the CLDE dental epithelial cell line to conduct further mechanistic analyses to determine whether AmeloD overexpression in CLDE cells suppresses E-cadherin expression and promotes cell migration. Knockout of epiprofin (Epfn), another transcription factor required for tooth morphogenesis and development, and analysis of AmeloD expression and deletion revealed that AmeloD also contributed to multiple tooth formation in Epfn-KO mice by promoting the invasion of dental epithelial cells into the mesenchymal region. Thus, AmeloD appears to play an important role in tooth morphogenesis by modulating E-cadherin and dental epithelial–mesenchymal interactions. These findings provide detailed insights into the mechanism of ectodermal organ development

Reference values for the locomotive syndrome risk test quantifying mobility of 8681 adults aged 20–89 years: A cross-sectional nationwide study in Japan

Background The locomotive syndrome risk test was developed to quantify the decrease in mobility among adults, which could eventually lead to disability. The purpose of this study was to establish reference values for the locomotive syndrome risk test for adults and investigate the influence of age and sex. Methods We analyzed 8681 independent community dwellers (3607 men, 5074 women). Data pertaining to locomotive syndrome risk test (the two-step test, the stand-up test, and the 25-question geriatric locomotive function scale [GLFS-25]) scores were collected from seven administrative areas of Japan. Results The reference values of the three test scores were generated and all three test scores gradually decreased among young-to-middle-aged individuals and rapidly decreased in individuals aged over 60 years. The stand-up test score began decreasing significantly from the age of 30 years. The trajectories of decrease in the two-step test score with age was slightly different between men and women especially among the middle-aged individuals. The two physical test scores were more sensitive to aging than the self-reported test score. Conclusion The reference values generated in this study could be employed to determine whether an individual has mobility comparable to independent community dwellers of the same age and sex

Deep Learning for Predicting Progression of Patellofemoral Osteoarthritis Based on Lateral Knee Radiographs, Demographic Data and Symptomatic Assessments

In this study, we propose a novel framework that utilizes deep learning (DL) and attention mechanisms to predict the radiographic progression of patellofemoral osteoarthritis (PFOA) over a period of seven years. This study included subjects (1832 subjects, 3276 knees) from the baseline of the MOST study. PF joint regions-of-interest were identified using an automated landmark detection tool (BoneFinder) on lateral knee X-rays. An end-to-end DL method was developed for predicting PFOA progression based on imaging data in a 5-fold cross-validation setting. A set of baselines based on known risk factors were developed and analyzed using gradient boosting machine (GBM). Risk factors included age, sex, BMI and WOMAC score, and the radiographic osteoarthritis stage of the tibiofemoral joint (KL score). Finally, we trained an ensemble model using both imaging and clinical data. Among the individual models, the performance of our deep convolutional neural network attention model achieved the best performance with an AUC of 0.856 and AP of 0.431; slightly outperforming the deep learning approach without attention (AUC=0.832, AP= 0.4) and the best performing reference GBM model (AUC=0.767, AP= 0.334). The inclusion of imaging data and clinical variables in an ensemble model allowed statistically more powerful prediction of PFOA progression (AUC = 0.865, AP=0.447), although the clinical significance of this minor performance gain remains unknown. This study demonstrated the potential of machine learning models to predict the progression of PFOA using imaging and clinical variables. These models could be used to identify patients who are at high risk of progression and prioritize them for new treatments. However, even though the accuracy of the models were excellent in this study using the MOST dataset, they should be still validated using external patient cohorts in the future

Clinical Efficacy of Melon GliSODin® for the Treatment of Aging-Related Dysfunction in Motor Organs—A Double Blind, Randomized Placebo-Controlled Study

Background: Locomotive syndrome is a concept proposed in Japan involving decreased mobility due to osteoarthritis, osteoporosis, and sarcopenia. This double-blind, randomized study aimed to investigate the effects of superoxide dismutase (SOD)-rich melon extract (Melon GliSODin®) on locomotive syndrome. Methods: For 6 months, we administered oral Melon GliSODin® (500.4 mg/day) or a placebo to 24 and 22 women, respectively (aged 50–80 years), with knee or lower back discomfort or pain. Using baseline and 6-month data, changes in the Verbal Rating Scale and in subjective symptoms (determined using the Japanese Knee Osteoarthritis Measure, Locomo 25, the Roland–Morris Disability questionnaire, and the Chalder Fatigue Scale) were assessed, along with various oxidative markers, antioxidants, inflammatory markers, renal and liver function biochemical markers, bone metabolism markers, body composition, and motor function. Results: Oral Melon GliSODin® administration tended to be associated with a larger improvement in subjective symptom scores, a reduction in oxidative markers (malondialdehyde and diacron reactive oxygen metabolites) and tumor necrosis factor-α, and a significant increase in non-fat mass between baseline and 6 months. However, no statistically significant differences were observed between the groups for outcomes at 6 months. Conclusions: Melon GliSODin® tended to improve the subjective symptoms of participants who had knee or lower back pain or discomfort. Melon GliSODin® administration may help to prevent the progression of locomotive syndrome. Future studies involving larger sample sizes and more stringent randomization protocols are needed to determine differences between the placebo and Melon GliSODin® groups

Imaging Evaluation of Intervertebral Disc Degeneration and Painful Discs—Advances and Challenges in Quantitative MRI

In recent years, various quantitative and functional magnetic resonance imaging (MRI) sequences have been developed and used in clinical practice for the diagnosis of patients with low back pain (LBP). Until now, T2-weighted imaging (T2WI), a visual qualitative evaluation method, has been used to diagnose intervertebral disc (IVD) degeneration. However, this method has limitations in terms of reproducibility and inter-observer agreement. Moreover, T2WI observations do not directly relate with LBP. Therefore, new sequences such as T2 mapping, T1ρ mapping, and MR spectroscopy have been developed as alternative quantitative evaluation methods. These new quantitative MRIs can evaluate the anatomical and physiological changes of IVD degeneration in more detail than conventional T2WI. However, the values obtained from these quantitative MRIs still do not directly correlate with LBP, and there is a need for more widespread use of techniques that are more specific to clinical symptoms such as pain. In this paper, we review the state-of-the-art methodologies and future challenges of quantitative MRI as an imaging diagnostic tool for IVD degeneration and painful discs