Local cryostimulation acutely preserves maximum isometric handgrip strength following fatigue in young women

Several types of cryostimulation have been recently proposed to rapidly lower skin temperature therefore gaining a possible neuro/muscular recovery after strenuous exercise or, more generally, in sports. Local cryostimulation may be a viable and relatively portable tool to obtain physiological benefits in previously-efforted muscular districts. However, cohesive and standardized cryo-exposure protocols are lacking as well as the righteous procedure to efficaciously combine duration, treatments and temperature in relation to desirable effects on muscular strength. In this randomized-controlled study, fifty young women were tested for maximum isometric handgrip strength, before and after exhausting contractions.Following the fatiguing protocol, the intervention group (cryo, n = 25, 24.7 ± 2.5 years, BMI 21.7 ± 1.8 kg/m²) underwent a 6-min local cryostimulation (−160 °C) on the extensor-flexor muscles of the dominant arm, while control-matched peers sat rested in a thermo-neutral room (22 ± 0.5 °C). Handgrip tests were repeated at baseline (T0), after cryostimulation (T1), and 15 min after T1 (T2). Throughout the protocol, the AUC of the strength performance was significantly higher in the cryo- compared to control group (P = 0.006). In particular, following fatigue and cryostimulation, the cryo group preserved higher strength at T1 with respect to controls (26.8 ± 2.8 vs 23.9 ± 2.8 kg, Bonferroni's post-hoc, P < 0.01). Likewise, ventral and dorsal temperature, recorded with a thermal camera, were lower in cryo- than control group (P < 0.0001).In conclusion, a brief session of local cryostimulation may acutely preserve maximal isometric force in young women following a fatiguing protocol. These findings may have implications in orchestrating strategies of district muscular recovery.     

Generalized estimating equations for ordinal categorical data: arbitrary patterns of missing responses and missingness in a key covariate

We propose methods for regression analysis of repeatedly measured ordinal categorical data when there is nonmonotone missingness in these responses and when a key covariate is missing depending on observables. The methods use ordinal regression models in conjunction with generalized estimating equations (GEEs). We extend the GEE methodology to accommodate arbitrary patterns of missingness in the responses when this missingness is independent of the unobserved responses. We further extend the methodology to provide correction for possible bias when missingness in knowledge of a key covariate may depend on observables. The approach is illustrated with the analysis of data from a study in diagnostic oncology in which multiple correlated receiver operating characteristic curves are estimated and corrected for possible verification bias when the true disease status is missing depending on observables.     

The treatment of glucocorticoid-induced osteoporosis

Glucocorticoid use results in an increase risk for fractures. Over the past 10 years, we have a greater understanding of the epidemiology, pathophysiology, prevention and treatment of glucocorticoid induced osteoporosis. This article reviews these recent findings and selective practice guidelines.     

Bayesian latent variable models for median regression on multiple outcomes

Often a response of interest cannot be measured directly and it is necessary to rely on multiple surrogates, which can be assumed to be conditionally independent given the latent response and observed covariates. Latent response models typically assume that residual densities are Gaussian. This article proposes a Bayesian median regression modeling approach, which avoids parametric assumptions about residual densities by relying on an approximation based on quantiles. To accommodate within-subject dependency, the quantile response categories of the surrogate outcomes are related to underlying normal variables, which depend on a latent normal response. This underlying Gaussian covariance structure simplifies interpretation and model fitting, without restricting the marginal densities of the surrogate outcomes. A Markov chain Monte Carlo algorithm is proposed for posterior computation, and the methods are applied to single-cell electrophoresis (comet assay) data from a genetic toxicology study.     

Use of spot measurements for assessing residential ELF magnetic field exposure: a validity study

The purpose of this study was to evaluate residential short term "spot" measurements as surrogates for long term personal magnetic field (MF) exposure. In an epidemiological study on birth weight and pregnancy delay, MF exposure was assessed by taking five spot measurements in each room. For a subsample of 30 subjects 24 h personal MF measurements were made, and the following exposure metrics were calculated: 24 h arithmetic mean, 24 h median, percentage of time above 0.15 microT, and percentage of time above 0.29 microT. The 24 h exposure metrics were used as gold standards, when evaluating the validity of various summary measures calculated from spot measurements for assessing personal exposure. Based on Spearman correlation coefficient (r), specificity and sensitivity, the average of the spot measurements of a residence resulted in least exposure measurement error (misclassification). Also the above bed spot value correlated better with the 24 h metrics than any room average. Spot measurements performed about equally well in predicting different types of exposure metrics.     

Generalized character process models: estimating the genetic basis of traits that cannot be observed and that change with age or environmental conditions

The genetic analysis of characters that change as a function of some independent and continuous variable has received increasing attention in the biological and statistical literature. Previous work in this area has focused on the analysis of normally distributed characters that are directly observed. We propose a framework for the development and specification of models for a quantitative genetic analysis of function-valued characters that are not directly observed, such as genetic variation in age-specific mortality rates or complex threshold characters. We employ a hybrid Markov chain Monte Carlo algorithm involving a Monte Carlo EM algorithm coupled with a Markov chain approximation to the likelihood, which is quite robust and provides accurate estimates of the parameters in our models. The methods are investigated using simulated data and are applied to a large data set measuring mortality rates in the fruit fly, Drosophila melanogaster.     

Composite grafts in the treatment of osteosarcoma of the proximal humerus

Treatment of osteosarcoma (OSA) of the proximal humerus poses many difficulties and challenges to the treating team. Between 1993 and 2000, we treated 11 patients (three women, eight men; age range, 17–74 years) suffering from OSA of the proximal humerus by composite: massive allografts and long humeral prosthesis. At presentation, 10 patients were at stage 2-B and one at stage 3-B of OSA. One patient presented with a pathologic fracture. All patients except patient No. 6, received preoperative chemotherapy followed by limb salvage surgery and postoperative chemotherapy.Surgical margins were graded as wide in all patients. Postoperative complications included non-union at the allograft/host junction (which united after auto grafting) and superficial wound infections that resolved after antibiotic therapy. All surgical procedures were performed by a team headed by an orthopedic oncologist and shoulder surgeon. At latest follow-up (December 2001) all patients, with the exception of one (who was at stage 3-B at presentation) were alive, and had good function of the upper limb. It is our opinion that the team approach comprising an orthopedic oncologist and shoulder surgeon greatly contributed to the good surgical outcome, and hence the good survival and functional results of the patients. Bone allograft offers a modular malleable durable solution to the resected bone segment.