Results using Trabecular Metal™ augments in combination with acetabular impaction bone grafting in deficient acetabula

We examined whether the use of trabecular metal wedges to fill segmental defects is an effective method of socket reconstruction when used in combination with impaction grafting and implantation of a cemented socket. Fifteen hips in 14 patients underwent impaction grafting in combination with a TM wedge with a minimum of 2 years follow-up. All patients had their defects assessed using the Paprosky classification. Patients were reviewed with x-rays and migration of the implant was measured. Outcome scores were also collected. Mean follow-up was 39 months (25-83). The mean age at surgery was 67.8 (49-85) years. Seven of the patients had previously undergone impaction grafting with the use of a stainless steel rim mesh to constrain the graft. None of the patients had failed either clinically or radiologically.

Development and validation of anthropometric prediction equations for estimation of body fat in Indonesian men

Body composition of 292 males aged between 18 and 65 years was measured using the deuterium oxide dilution technique. Participants were divided into development (n=146) and cross-validation (n=146) groups. Stature, body weight, skinfold thickness at eight sites, girth at five sites, and bone breadth at four sites were measured and body mass index (BMI), waist-to-hip ratio (WHR), and waist-to-stature ratio (WSR) calculated. Equations were developed using multiple regression analyses with skinfolds, breadth and girth measures, BMI, and other indices as independent variables and percentage body fat (%BF) determined from deuterium dilution technique as the reference. All equations were then tested in the cross-validation group. Results from the reference method were also compared with existing prediction equations by Durnin and Womersley (1974), Davidson et al (2011), and Gurrici et al (1998). The proposed prediction equations were valid in our cross-validation samples with r=0.77- 0.86, bias 0.2-0.5%, and pure error 2.8-3.6%. The strongest was generated from skinfolds with r=0.83, SEE 3.7%, and AIC 377.2. The Durnin and Womersley (1974) and Davidson et al (2011) equations significantly (p<0.001) underestimated %BF by 1.0 and 6.9% respectively, whereas the Gurrici et al (1998) equation significantly (p<0.001) overestimated %BF by 3.3% in our cross-validation samples compared to the reference. Results suggest that the proposed prediction equations are useful in the estimation of %BF in Indonesian men.

TNF and TNF receptor expression and insulin sensitivity in human omental and subcutaneous adipose tissue--influence of BMI and adipose distribution

Tumour necrosis factor (TNF)alpha is implicated in the relationship between obesity and insulin resistance/ type 2 diabetes. In an effort to understand this association better we (i) profiled gene expression patterns of TNF, TNFR1 and TNFR2 and (ii) investigated the effects of TNF on glucose uptake in isolated adipocytes and adipose tissue explants from omental and subcutaneous depots from lean, overweight and obese individuals. TNF expression correlated with expression of TNFR2, but not TNFR1, and TNF and TNFR2 expression increased in obesity. TNFR1 expression was higher in omental than in subcutaneous adipocytes. Expression levels of TNF or either receptor did not differ between adipocytes from individuals with central and peripheral obesity. TNF only suppressed glucose uptake in insulin-stimulated subcutaneous tissue and this suppression was only observed in tissue from lean subjects. These data support a relationship between the TNF system and body mass index (BMI), but not fat distribution, and suggest depot specificity of the TNF effect on glucose uptake. Furthermore, adipose tissue from obese subjects already appears insulin 'resistant' and this may be a result of the increased TNF levels.

Conducting accelerometer-based activity assessments in field-based research

Purpose The purpose of this review is to address important methodological issues related to conducting accelerometer-based assessments of physical activity in free-living individuals. Methods We review the extant scientific literature for empirical information related to the following issues: product selection, number of accelerometers needed, placement of accelerometers, epoch length, and days of monitoring required to estimate habitual physical activity. We also discuss the various options related to distributing and collecting monitors and strategies to enhance compliance with the monitoring protocol. Results No definitive evidence exists currently to indicate that one make and model of accelerometer is more valid and reliable than another. Selection of accelerometer therefore remains primarily an issue of practicality, technical support, and comparability with other studies. Studies employing multiple accelerometers to estimate energy expenditure report only marginal improvements in explanatory power. Accelerometers are best placed on hip or the lower back. Although the issue of epoch length has not been studied in adults, the use of count cut points based on 1-min time intervals maybe inappropriate in children and may result in underestimation of physical activity. Among adults, 3–5 d of monitoring is required to reliably estimate habitual physical activity. Among children and adolescents, the number of monitoring days required ranges from 4 to 9 d, making it difficult to draw a definitive conclusion for this population. Face-to-face distribution and collection of accelerometers is probably the best option in field-based research, but delivery and return by express carrier or registered mail is a viable option. Conclusion Accelerometer-based activity assessments requires careful planning and the use of appropriate strategies to increase compliance.

A nutrition and physical activity intervention for family child care homes

Background Family child care homes (FCCHs) provide child care to 1.9 million children in the U.S., but many do not meet established child care standards for healthy eating and physical activity. Purpose To determine the effects of a community-based train-the-trainer intervention on FCCHs policies and practices related to healthy eating and physical activity. Design Quasi-experimental design with replication in three independent cohorts of FCCHs. Setting/participants Registered FCCHs from 15 counties across Kansas participated in the Healthy Kansas Kids (HKK) program. Resource and referral agencies (RRAs) in each county recruited and enrolled between five and 15 child care providers in their service delivery area to participate in the program. The number of registered FCCHs participating in HKK in Years 1 (2006-2007); 2 (2007-2008); and 3 (2008-2009) of the program were 85, 64, and 87, respectively. A stratified random sample of registered FCCHs operating in Kansas (n=297) served as a normative comparison group. Interventions Child care trainers from each RRA completed a series of train-the-trainer workshops related to promotion of healthy eating and physical activity. FCCHs were subsequently guided through a four-step iterative process consisting of (1) self-evaluation; (2) goal setting; (3) developing an action plan; and (4) evaluating progress toward meeting goals. FCCHs also received U. S. Department of Agriculture resources related to healthy eating and physical activity. Main outcome measures Nutrition and Physical Activity Self-Assessment for Child Care (NAP SACC) self-assessment instrument (NAP SACC-SA). Analyses of outcome measures were conducted between 2008 and 2010. Results Healthy Kansas Kids FCCHs exhibited significant improvements in healthy eating (Delta=6.9%-7.1%) and physical activity (Delta=15.4%-19.2%) scores (p<0.05). Within each cohort, pre-intervention scores were not significantly different from the state average, whereas post-intervention scores were significantly higher than the state average. Conclusions Community-based train-the-trainer interventions to promote healthy eating and physical activity in FCCHs are feasible, sustainable, and effective.

LCC15-MB : a vimentin-positive human breast cancer cell line from a femoral bone metastasis

The LCC15-MB cell line was established from a femoral bone metastasis that arose in a 29-year-old woman initially diagnosed with an infiltrating ductal mammary adenocarcinoma. The tumor had a relatively high (8%) S-phase fraction and 1/23 positive lymph nodes (LN). Both the primary tumor and LN metastasis were positive for estrogen receptor (ER) and progesterone receptor (PgR), but lacked erbB2 expression. Approximately one year later, the patient presented with a 0.8 cm comedo-type intraductal mammary adenocarcinoma in the left breast that was negative for ER and PgR, but positive for erbB2. Thirty-five months after the initial diagnosis she was treated for acute skeletal metastasis, and stabilized with a hip replacement. At this time, tumor cells were removed from surplus involved bone, inoculated into cell culture, and developed into the LCC15-MB cell line. The bone metastasis was a poorly differentiated adenocarcinoma lacking ER, PgR, and erbB2, characteristics shared by the LCC15-MB cells, although ER can be re-expressed by treatment of the LCC15-MB cells for 5 days with 75 μM 5-aza-2'-deoxycytidine. The LCC15-MB cell line is tumorigenic when implanted subcutaneously in NCr nu/nu mice and produces long-bone metastases after intracardiac injection. Although the bone metastasis from which the LCC15-MB cell line was derived lacked vimentin (VIM) expression, the original primary tumor and lymph node metastasis were strongly VIM positive, as are LCC15-MB cells in vitro and in nude mice. The karyotype and isozyme profiles of LCC15-MB cells are consistent with its origin from a human female, with most chromosome counts in the hypertriploid range. Thirty-two marker chromosomes are present. These cells provide an in vitro/in vivo model in which to study the inter-relationships between ER, VIM, and bone metastasis in human breast cancer.

Predictive validity of three ActiGraph energy expenditure equations for children

Purpose This Study evaluated the predictive validity of three previously published ActiGraph energy expenditure (EE) prediction equations developed for children and adolescents. Methods A total of 45 healthy children and adolescents (mean age: 13.7 +/- 2.6 yr) completed four 5-min activity trials (normal walking. brisk walking, easy running, and fast running) in ail indoor exercise facility. During each trial, participants were all ActiGraph accelerometer oil the right hip. EE was monitored breath by breath using the Cosmed K4b(2) portable indirect calorimetry system. Differences and associations between measured and predicted EE were assessed using dependent t-tests and Pearson correlations, respectively. Classification accuracy was assessed using percent agreement, sensitivity, specificity, and area under the receiver operating characteristic (ROC) curve. Results None of the equations accurately predicted mean energy expenditure during each of the four activity trials. Each equation, however, accurately predicted mean EE in at least one activity trial. The Puyau equation accurately predicted EE during slow walking. The Trost equation accurately predicted EE during slow running. The Freedson equation accurately predicted EE during fast running. None of the three equations accurately predicted EE during brisk walking. The equations exhibited fair to excellent classification accuracy with respect to activity intensity. with the Trost equation exhibiting the highest classification accuracy and the Puyau equation exhibiting the lowest. Conclusions These data suggest that the three accelerometer prediction equations do not accurately predict EE on a minute-by-minute basis in children and adolescents during overground walking and running. The equations maybe, however, for estimating participation in moderate and vigorous activity.

Artificial neural networks to predict activity type and energy expenditure in youth

Previous studies have demonstrated that pattern recognition approaches to accelerometer data reduction are feasible and moderately accurate in classifying activity type in children. Whether pattern recognition techniques can be used to provide valid estimates of physical activity (PA) energy expenditure in youth remains unexplored in the research literature. Purpose: The objective of this study is to develop and test artificial neural networks (ANNs) to predict PA type and energy expenditure (PAEE) from processed accelerometer data collected in children and adolescents. Methods: One hundred participants between the ages of 5 and 15 yr completed 12 activity trials that were categorized into five PA types: sedentary, walking, running, light-intensity household activities or games, and moderate-to-vigorous intensity games or sports. During each trial, participants wore an ActiGraph GTIM on the right hip, and (V) Over dotO(2) was measured using the Oxycon Mobile (Viasys Healthcare, Yorba Linda, CA) portable metabolic system. ANNs to predict PA type and PAEE (METs) were developed using the following features: 10th, 25th, 50th, 75th, and 90th percentiles and the lag one autocorrelation. To determine the highest time resolution achievable, we extracted features from 10-, 15-, 20-, 30-, and 60-s windows. Accuracy was assessed by calculating the percentage of windows correctly classified and root mean square en-or (RMSE). Results: As window size increased from 10 to 60 s, accuracy for the PA-type ANN increased from 81.3% to 88.4%. RMSE for the MET prediction ANN decreased from 1.1 METs to 0.9 METs. At any given window size, RMSE values for the MET prediction ANN were 30-40% lower than the conventional regression-based approaches. Conclusions: ANNs can be used to predict both PA type and PAEE in children and adolescents using count data from a single waist mounted accelerometer.

iNOS expression and osteocyte apoptosis in idiopathic, non- traumatic osteonecrosis

Background and purpose Non-traumatic osteonecrosis is a progressive disease with multiple etiologies. It affects younger individuals more and more, often leading to total hip arthroplasty. We investigated whether there is a correlation between inducible nitric oxide synthase (iNOS) expression and osteocyte apoptosis in non-traumatic osteonecrosis. Patients and methods We collected and studied 20 human idiopathic, non-traumatic osteonecrosis femoral heads. Subchondral bone samples in the non-sclerotic region (n = 30), collected from osteoarthritis patients, were used as controls. Spontaneously hypertensive rats were used as a model for osteonecrosis in the study. We used scanning electron microscopy, TUNEL assay, and immunohistochemical staining to study osteocyte changes and apoptosis. Results The morphology of osteocytes in the areas close to the necrotic region changed and the number of apoptotic osteocytes increased in comparison with the same region in control groups. The expression of iNOS and cytochrome C in osteocytes increased while Bax expression was not detectable in osteonecrosis samples. Using spontaneously hypertensive rats, we found a positive correlation between iNOS expression and osteocyte apoptosis in the osteonecrotic region. iNOS inhibitor (aminoguanidine) added to the drinking water for 5 weeks reduced the production of iNOS and osteonecrosis compared to a control group without aminoguanidine. Interpretation Our findings show that increased iNOS expression can lead to osteocyte apopotosis in idiopathic, non-traumatic osteonecrosis and that an iNOS inhibitor may prevent the progression of the disease.

Proximal femoral morphology in regions of hard and soft water

This study compared proximal femoral morphology in patients living in soft and hard water regions. The proximal femoral morphology of two groups of 70 patients living in hard and soft water regions with a mean age of 72.3 (range 50 to 87 years) were measured using an antero-posterior radiograph of the non-operated hip with magnification adjusted. The medullary canal diameter at the level of the lesser trochanter (LT) was significantly wider in patients living in the hard water region (mean width 1.9 mm wider; p= 0.003). No statistical significant difference was found in the medullary canal width at 10 cm below the level of LT, Dorr index, or Canal Bone Ratio (CBR). In conclusion, the proximal femoral morphology does differ in patients living in soft and hard water areas. These results may have an important clinical bearing in patients undergoing total hip replacement surgery. Further research is needed to determine whether implant survivorship is affected in patients living in hard and soft water regions.

Measuring reliability and validity of the ActiGraph GT3X accelerometer for children with cerebral palsy : a feasibility study

PURPOSE The purposes of this study were to: 1) establish inter-instrument reliability between left and right hip accelerometer placement; 2) examine procedural reliability of a walking protocol used to measure physical activity (PA), and; 3) confirm concurrent validity of accelerometers in measuring PA intensity as compared to the gold standard of oxygen consumption measured by indirect calorimetry. METHODS Eight children (mean age: 11.9; SD: 3.2, 75% male) with CP (GMFCS levels I-III) wore ActiGraph GT3X accelerometers on each hip and the Cosmed K4b^{2} portable indirect calorimeter during two measurement sessions in which they performed the six minute walk test (6MWT) at three self-selected speeds (comfortable/slow, brisk, fast). Oxygen consumption (VO2) and accelerometer step and activity count data were recorded. RESULTS Inter-instrument reliability of ActiGraph GT3X accelerometers placed on left and right hips was excellent (ICC=0.96-0.99, CI_{95}: 0.81-0.99). Reproducibility of the protocol was good/excellent (ICC=0.75-0.95, CI_{95}: 0.75-0.98). Concurrent validity of accelerometer count data and VO2 was fair/good (rho=0.67, p< 0.001). The correlation between step count and VO2 was not significant (rho=0.29, p=0.2). CONCLUSION This preliminary research suggests that ActiGraph GT3X accelerometers are reliable and valid devices to monitor PA during walking in children with CP and may be appropriate in rehabilitation research and clinical practice. ActiGraph GTX3 step counts were not valid for this sample and further research is warranted.

How are falls and fear of falling associated with objectively measured physical activity in a cohort of community-dwelling older men?

BACKGROUND: Falls affect approximately one third of community-dwelling older adults each year and have serious health and social consequences. Fear of falling (FOF) (lack of confidence in maintaining balance during normal activities) affects many older adults, irrespective of whether they have actually experienced falls. Both falls and fear of falls may result in restrictions of physical activity, which in turn have health consequences. To date the relation between (i) falls and (ii) fear of falling with physical activity have not been investigated using objectively measured activity data which permits examination of different intensities of activity and sedentary behaviour. METHODS: Cross-sectional study of 1680 men aged 71-92 years recruited from primary care practices who were part of an on-going population-based cohort. Men reported falls history in previous 12 months, FOF, health status and demographic characteristics. Men wore a GT3x accelerometer over the hip for 7 days. RESULTS: Among the 12% of men who had recurrent falls, daily activity levels were lower than among non-fallers; 942 (95% CI 503, 1381) fewer steps/day, 12(95% CI 2, 22) minutes less in light activity, 10(95% CI 5, 15) minutes less in moderate to vigorous PA [MVPA] and 22(95% CI 9, 35) minutes more in sedentary behaviour. 16% (n = 254) of men reported FOF, of whom 52% (n = 133) had fallen in the past year. Physical activity deficits were even greater in the men who reported that they were fearful of falling than in men who had fallen. Men who were fearful of falling took 1766(95% CI 1391, 2142) fewer steps/day than men who were not fearful, and spent 27(95% CI 18, 36) minutes less in light PA, 18(95% CI 13, 22) minutes less in MVPA, and 45(95% CI 34, 56) minutes more in sedentary behaviour. The significant differences in activity levels between (i) fallers and non-fallers and (ii) men who were fearful of falling or not fearful, were mediated by similar variables; lower exercise self-efficacy, fewer excursions from home and more mobility difficulties. CONCLUSIONS: Falls and in particular fear of falling are important barriers to older people gaining health benefits of walking and MVPA. Future studies should assess the longitudinal associations between falls and physical activity.

Prediction of activity type in preschool children using machine learning techniques

Objectives Recent research has shown that machine learning techniques can accurately predict activity classes from accelerometer data in adolescents and adults. The purpose of this study is to develop and test machine learning models for predicting activity type in preschool-aged children. Design Participants completed 12 standardised activity trials (TV, reading, tablet game, quiet play, art, treasure hunt, cleaning up, active game, obstacle course, bicycle riding) over two laboratory visits. Methods Eleven children aged 3–6 years (mean age = 4.8 ± 0.87; 55% girls) completed the activity trials while wearing an ActiGraph GT3X+ accelerometer on the right hip. Activities were categorised into five activity classes: sedentary activities, light activities, moderate to vigorous activities, walking, and running. A standard feed-forward Artificial Neural Network and a Deep Learning Ensemble Network were trained on features in the accelerometer data used in previous investigations (10th, 25th, 50th, 75th and 90th percentiles and the lag-one autocorrelation). Results Overall recognition accuracy for the standard feed forward Artificial Neural Network was 69.7%. Recognition accuracy for sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running was 82%, 79%, 64%, 36% and 46%, respectively. In comparison, overall recognition accuracy for the Deep Learning Ensemble Network was 82.6%. For sedentary activities, light activities and games, moderate-to-vigorous activities, walking, and running recognition accuracy was 84%, 91%, 79%, 73% and 73%, respectively. Conclusions Ensemble machine learning approaches such as Deep Learning Ensemble Network can accurately predict activity type from accelerometer data in preschool children.

Repeatability of static load bearing exercises during rehabilitation of individuals with transfemoral amputation fitted with osseointegrated implant

Bone-anchored prostheses, relying on implants to attach the prosthesis directly to the residual skeleton, are the ultimate resort for patients with transfemoral amputations (TFA) experiencing severe socket discomfort. The first patient receiving a bone-anchored prosthesis underwent the surgery in 1990 in the Sahlgrenska University Hospital (Sweden). To date, there are two commercially available implants: OPRA (Integrum, Sweden) and ILP (Orthodynamics, Germany). The key to success to this technique is a firm bone-implant bonding, depending on increasing mechanical stress applied daily during load bearing exercises (LBE). The loading data could be analysed through different biomechanical variables. The intra-tester reliability of these exercises will be presented here. Moreover the effect of increase of loading, axes of application of the load and body weight as well as the difference between force and moment variables will be discussed.