Search

•The PUL-Br is valid for assessing upper limb function in Brazilian patients with DMD.•The PUL-Br presents excellent inter-rater reliability.•The PUL-Br will standardise the clinical assessment of Brazilian patients with DMD.•The PUL-Br may guide rehabilitation professionals’ therapeutic decisions.

Poisson and negative binomial distributions are frequently used to fit count data. A limitation of the Poisson distribution is that the mean and the variance are assumed to be equal, but this assumption is far from being realistic in many practical applications. The negative binomial distribution is more used in cases of overdispersion, given that their variance is higher than the mean. The two-parameter double Poisson distribution introduced by Efron may be considered as a useful alternative to the Poisson and negative binomial distributions, given that it can account for both overdispersion and under-dispersion. In this article, we obtain maximum likelihood and Bayesian estimates for the double Poisson distribution. We also extend the proposed methodology for the situation in which there is an excess of zeros in a sample. Applications of the double Poisson distribution are considered assuming simulated and real data sets.

In this article we introduce a new distribution, namely, the defective Dagum distribution (DDD). This improper distribution can be seen as an extension of the Type I Dagum distribution and it is useful to accommodate survival data in the presence of a cure fraction. In the applications of survival methods to medical data, the cure fraction is defined as the proportion of patients who are cured of disease and become long-term survivors. The great advantage of the DDD is that the cure fraction can be written as a function of only one parameter. We also considered the presence of censored data and covariates. Maximum likelihood and Bayesian methods for estimation of the model parameters are presented. A simulation study is provided to evaluate the performance of the maximum likelihood method in estimating parameters. In the Bayesian analysis, posterior distributions of the parameters are estimated using the Markov-chain Monte Carlo (MCMC) method. An example involving a real data set is presented. The model based on the new distribution is easy to use and it is a good alternative for the analysis of real time-to-event data in the presence of censored information and a cure fraction.

Excessive telomere shortening caused by pathogenic germline variants in telomere-biology genes may result in bone marrow failure, hematopoietic malignancy and extramedullary complications, such as idiopathic pulmonary fibrosis (IPF), liver cirrhosis, and solid tumors. Patients with short telomeres also may develop immunodeficiency with low counts of T-cell receptor excision circles (TRECs), kappa-deleting excision circles (KRECs), and CD4 +T cells. The aim of the present study was to comprehensively determine the immune system changes in human patients with telomeropathies by deep-phenotyping peripheral blood mononuclear cells (PBMCs) and quantifying cytokine serum levels. We applied a 39-marker panel of metal-labeled antibodies and employed mass cytometry (CyTOF) to assess the subsets of lymphocytes, monocytes, and dendritic cells (DC) in 20 patients and 10 healthy individuals. High-dimensional analysis was conducted using automated clustering ( Flow-SOM) to identify subpopulations and cell states, whereas t-SNEwas employed as a visualization tool. A total of 32 serum cytokines, chemokines and growth factors were quantified by a bead-based immunoassay (Luminex™). First, we confirmed previous findings of low CD4/CD8 ratio (0.73±0.56 vs. 1.3±0.69 in controls, p=0.05), and reduced absolute naïve (CD45RA +CCR7 +) CD4 +and CD8 +cell counts ( p<0.01), with effector memory cell accumulation in patients with telomere diseases, and the current study further showed a reduction in naïve B (CD19 +IgD +CD27 -) and in recent thymic emigrants (RTE), characterized by CD31 +CD45RA +( p<0.01), indicating a consistent aged B and T cell profile. T H1, T H17 and T H17.1 CD4 +lymphocytes were reduced ( p<0.05), whereas the T H2/T H1 ratio was increased (1.6±0.83 vs. 0.82±0.39 in controls; p=0.013), demonstrating a dysregulated T helper cell diversity. T regs, on the other hand, did not appear to be affected. Plasmacytoid DCs (CD3 -CD141 +CD123 +CD1c -), which are known inducers of T helper differentiation, were reduced in patients ( p=0.014). A double negative T cell (DNT) population, characterized as CD3 +CD4 -CD8 -Vd2 -Tbet +Granzyme B +, was significantly increased ( p=0.0002). Activated effector memory and TEMRA CD4 +cells, also expressing exhaustion markers PD-1 and TIGIT (CD4 +CD45RA +/-CCR7 -CD38 +HLADR +Ki67 +PD-1 +TIGIT low) and proliferating switched memory B cells (CD3 -CD19 +IgD -CD27 +Ki67 +) were higher ( p=0.046 and p=0.041, respectively) suggesting the occurrence of an environment prone to immune activation, also supported by the prevalence of CD14 +CD16 +CXCR3 +CCR4 +classical monocytes ( p=0.0042). Additionally, mucosal-associated invariant T (MAIT) cells (CD3 +CD161 highVɑ7.2 +) were markedly reduced in patients ( p<0.0001), possibly due to their recruitment to other tissues as a response to inflammation. Conversely, immature NK cells (CD3 -CD19 -CD56 brightCD16 -) were more frequent in patients as compared to controls ( p=0.026), and individuals with the shortest telomere lengths had an even higher frequency of these cells. In addition to the previously described CD4 +immunodeficiency, the predominance of immature NK cells may potentially impact the immunosurveillance of malignant transformations. When an unsupervised clustering algorithm using cell subpopulations as variables was applied, patients and controls were correctly identified in 100% of cases. Telomere length positively correlated with some cytokine levels in serum. This was observed for angiopoietin-1, IL-1 superfamily, IL-3, IL-4, IL-7, IL-23, IL-27, M-CSF, MCP-1, MIP-3a and PDGF-BB. Taken together, our results reveal a distinct immunophenotype in telomeropathies, which comprises deficient or skewed maturation of certain subsets, an aged phenotype of B and T cells, aberrant lymphocyte activation and very low levels of circulating MAIT cells, which might be indicators of ongoing inflammatory processes, tied with dysregulated cytokine levels. This immune perturbance may contribute to the clinical onset of telomeropathies and increase the risk of infections, cirrhosis, IPF and cancer development.

ABSTRACTPoisson and negative binomial distributions are frequently used to fit count data. A limitation of the Poisson distribution is that the mean and the variance are assumed to be equal, but this assumption is far from being realistic in many practical applications. The negative binomial distribution is more used in cases of overdispersion, given that their variance is higher than the mean. The two-parameter double Poisson distribution introduced by Efron may be considered as a useful alternative to the Poisson and negative binomial distributions, given that it can account for both overdispersion and underdispersion. In this article, we obtain maximum likelihood and Bayesian estimates for the double Poisson distribution. We also extend the proposed methodology for the situation in which there is an excess of zeros in a sample. Applications of the double Poisson distribution are considered assuming simulated and real data sets.

ABSTRACTIn this article we introduce a new distribution, namely, the defective Dagum distribution (DDD). This improper distribution can be seen as an extension of the Type I Dagum distribution and it is useful to accommodate survival data in the presence of a cure fraction. In the applications of survival methods to medical data, the cure fraction is defined as the proportion of patients who are cured of disease and become long-term survivors. The great advantage of the DDD is that the cure fraction can be written as a function of only one parameter. We also considered the presence of censored data and covariates. Maximum likelihood and Bayesian methods for estimation of the model parameters are presented. A simulation study is provided to evaluate the performance of the maximum likelihood method in estimating parameters. In the Bayesian analysis, posterior distributions of the parameters are estimated using the Markov-chain Monte Carlo (MCMC) method. An example involving a real data set is presented. The model based on the new distribution is easy to use and it is a good alternative for the analysis of real time-to-event data in the presence of censored information and a cure fraction.

Subjects exposed to laboratory animals are at a heightened risk of developing respiratory and allergic diseases. These diseases can be prevented by simple measures such as the use of personal protective equipment. We report here the primary findings of the Laboratory Animals and Respiratory Allergies Study regarding the prevalence of allergic diseases among laboratory animal workers, the routine use of preventive measures in laboratories and animal facilities, and the need for prevention programs.

To compare the prevalence of menopause symptoms, sexual activity, and quality of life in women with and without breast cancer.