Idiopathic tumoral calcinosis in children: Case report

Tumoral calcinosis is a rare, benign entity characterized by the deposition of calcium in periarticular soft tissues. We report the original case of an idiopathic tumoral calcinosis of the elbow in a 6-year-old girl successfully treated by drainage with no signs of recurrence after a 3-year follow-up. We discuss the particularities of this joint location and our therapeutic management.

Prevention and Management of Platinum Compounds-Induced Neurotoxicity

Oncologists considered platinum-based medicines as potent cytotoxic agents. Despite their efficacy in combination chemotherapy regimens for many solid tumors, they have many substantial side effects that limit their use. There is no known prophylactic strategy for platinum drugs-induced neurotoxicity, which limit a therapeutic dose benefit. This review highlights the etiology of platinum-drugs-induced neuropathy, and covers the preventative and therapeutic options for cancer patients. It focuses on clinical studies conducted between 2010 and 2020. Loss of functional indications such as touch, vibration and joint location, as well as diminished or missing deep tendon reflexes in the upper and lower limbs are all markers of neurotoxicity. These side effects may last for months or years after treatment, lower quality of life, and creating a substantial survivorship issue. DNA damage, oxidative stress, mitochondrial dysfunction, dysregulation of intracellular signaling, impairment of voltage gated ion channel function, and neuro-inflammation have all been proposed as mechanisms for chemotherapy-induced peripheral neuropathy (CIPN). There are no proven pharmaceutical or nutritional therapies to prevent CIPN. Several anti-CIPN medications have been investigated, but either had no effect or had an effect in a limited sample study. Supportive care medications such anti-epileptics and antidepressants are used to treat CIPN.

gJLS2: A generalized joint location and scale analysis tool for X-inclusive genome-wide discoveries

A joint analysis of location and scale can be a powerful tool in genome-wide association studies to uncover previously overlooked markers that influence a quantitative trait through both mean and variance, as well as to prioritize candidates for gene-environment interactions. This approach has recently been generalized to handle related samples, dosage data, and the analytically challenging X-chromosome. We disseminate the latest advances in methodology through a user-friendly software package. The implemented R package (https://cran.r-project.org/web/packages/gJLS2) can be called via PLINK to enable a streamlined population-based analysis genome-wide, or called directly as a front end R script for inter-mediate gene-set based analyses, or used in any R GUI for smaller analyses targeting specific variants of interest.

Variable selection for skew-normal mixture of joint location and scale models

Although there are many papers on variable selection methods based on mean model in the finite mixture of regression models, little work has been done on how to select significant explanatory variables in the modeling of the variance parameter. In this paper, we propose and study a novel class of models: a skew-normal mixture of joint location and scale models to analyze the heteroscedastic skew-normal data coming from a heterogeneous population. The problem of variable selection for the proposed models is considered. In particular, a modified Expectation-Maximization(EM) algorithm for estimating the model parameters is developed. The consistency and the oracle property of the penalized estimators is established. Simulation studies are conducted to investigate the finite sample performance of the proposed methodologies. An example is illustrated by the proposed methodologies.

Canadian Rheumatologists’ Perspectives on Moderate Psoriatic Arthritis and Oligoarticular Psoriatic Arthritis

Objective Psoriatic arthritis (PsA) substantially impairs quality of life. Clinical trials generally focus on polyarticular PsA, but less is known about the assessment and management of oligoarticular and moderate PsA. An online survey was conducted to determine Canadian rheumatologists’ perspectives on the definition and treatment of oligoarticular and moderate PsA. Methods Regional and national experts treating patients with PsA were asked to complete an online survey to assess their approach to identifying and managing patients with PsA. Survey questions were developed based on guidance from a committee of Canadian rheumatologists. Results Sixty-four of 78 rheumatologists responded, representing 6 major Canadian provinces. Nearly half of respondents were in practice >20 years. The majority of rheumatologists reported using swollen joint count (SJC) to describe moderate PsA (86.4%) and oligoarticular PsA (96.7%), and considered location of inflammation in PsA assessments. SJC cutoff scores for reporting moderate PsA varied among rheumatologists, suggesting lack of an agreed-upon definition for moderate PsA. Sixty-eight percent of rheumatologists identified access to treatment as the greatest challenge with oligoarticular PsA. Conclusion According to the surveyed rheumatologists, SJC remains a key assessment when defining oligoarticular and moderate PsA. Although the number of joints is considered when determining the impact of PsA on patients, joint location and functional impairment are also considered when describing the disease as moderate. Access to treatment for patients with <5 affected joints is challenging.

Development of a Deep Neural Network Model for Estimating Joint Location of Occupant Indoor Activities for Providing Thermal Comfort

The type of occupant activities is a significantly important factor to determine indoor thermal comfort; thus, an accurate method to estimate occupant activity needs to be developed. The purpose of this study was to develop a deep neural network (DNN) model for estimating the joint location of diverse human activities, which will be used to provide a comfortable thermal environment. The DNN model was trained with images to estimate 14 joints of a person performing 10 common indoor activities. The DNN contained numerous shortcut connections for efficient training and had two stages of sequential and parallel layers for accurate joint localization. Estimation accuracy was quantified using the mean squared error (MSE) for the estimated joints and the percentage of correct parts (PCP) for the body parts. The results show that the joint MSEs for the head and neck were lowest, and the PCP was highest for the torso. The PCP for individual activities ranged from 0.71 to 0.92, while typing and standing in a relaxed manner were the activities with the highest PCP. Estimation accuracy was higher for relatively still activities and lower for activities involving wide-ranging arm or leg motion. This study thus highlights the potential for the accurate estimation of occupant indoor activities by proposing a novel DNN model. This approach holds significant promise for finding the actual type of occupant activities and for use in target indoor applications related to thermal comfort in buildings.