Cross-cultural adaptation and evaluation of the psychometric properties of the University of Wisconsin Running Injury and Recovery Index questionnaire in Spanish (UWRI-S)

ObjectiveTo cross-culturally adapt and evaluate the psychometric properties of the University of Wisconsin Running Injury and Recovery Index questionnaire in Spanish (UWRI-S) in Chilean runners with a running-related injury.DesignCross-cultural adaptation and validation study, following the Consensus-based Standards for selecting health Measurement Instruments (COSMIN) recommendations.SettingOutpatient sports medicine clinic and running clubs.ParticipantsUWRI was forward and backward translated, and culturally adapted. Thirty-one runners participated in the content validity of the UWRI-S; and fifty-seven in the assessment of psychometric properties.Main outcome measuresRunners seeking care from a physiotherapist completed the UWRI-S (baseline and after 48–72 h for reliability), Lower Extremity Functional Scale (LEFS), Patient Specific Functional Scale (PSFS), Global Rating of Change scale (GROC), and Numeric Pain Rating Scale (NPRS).ResultsSuggestions about accuracy of wording and understanding of items were incorporated. UWRI-S showed a positive moderate correlation with LEFS (r = 0.6; p < 0.05), positive fair with GROC (r = 0.5, p < 0.05), negative fair with NPRS (r = −0.4; p < 0.05) and no correlation with PSFS (r = 0.3; p = 0.1). UWRI-S demonstrated acceptable internal consistency (α = 0.87) and test-retest reliability (ICC = 0.87).ConclusionUWRI-S is a valid and reliable measure to evaluate running ability of Chilean runners during recovery from a running-related injury.     

Preoperative comprehensive malignancy risk estimation for thyroid nodules: Development and verification of a network-based prediction model

BackgroundIn order to avoid excessive treatment of thyroid nodules in the clinic, it is necessary to find a simple and practical analysis method to comprehensively and accurately reflect benign or malignant thyroid nodules. This study aimed to construct and validate a comprehensive and reliable network-based predictive model using a variety of imaging and laboratory criteria for thyroid nodules to stratify the risk of malignancy prior to surgery.MethodsWe retrospectively analyzed data from patients who underwent surgical treatment for thyroid nodules at the Thyroid and Breast Diagnosis and Treatment Center of Weifang Hospital of Traditional Chinese Medicine between January 2018 and December 2020. Binary logical regression analysis was performed to predict whether nodules were malignant or benign. The developmental dataset included 457 patients (January 2018–December 2020). The validation set included separate data points (n = 225, January 2018–December 2020).ResultsIn this study, criteria that showed significant predictive value for malignant nodules included TI-RADS: 4b (p = 0.065); Bethesda IV, Bethesda V, Bethesda VI (P < 0.0001); BRAF^V600E mutation (P < 0.0001); Calcitonin>5 pg/ml (p = 0.0037); and FNA-Tg>30 ng/ml (p = 0.0003). A 10-grade risk scoring system was developed. The risk of malignancy risk ranged from 2.06% to 100% and was positively associated with increasing risk grade. The areas under the receiver-operating characteristic curve of the development and validation sets were 0.972 and 0.946, respectively.ConclusionA simple, comprehensive and reliable web-based predictive model was designed using a variety of imaging and laboratory criteria to stratify thyroid nodules by probability of malignancy.     

Bayesian consensus clustering for multivariate longitudinal data

In clinical and epidemiological studies, there is a growing interest in studying the heterogeneity among patients based on longitudinal characteristics to identify subtypes of the study population. Compared to clustering a single longitudinal marker, simultaneously clustering multiple longitudinal markers allow additional information to be incorporated into the clustering process, which reveals co-existing longitudinal patterns and generates deeper biological insight. In the current study, we propose a Bayesian consensus clustering (BCC) model for multivariate longitudinal data. Instead of arriving at a single overall clustering, the proposed model allows each marker to follow marker-specific local clustering and these local clusterings are aggregated to find a global (consensus) clustering. To estimate the posterior distribution of model parameters, a Gibbs sampling algorithm is proposed. We apply our proposed model to the primary biliary cirrhosis study to identify patient subtypes that may be associated with their prognosis. We also perform simulation studies to compare the clustering performance between the proposed model and existing models under several scenarios. The results demonstrate that the proposed BCC model serves as a useful tool for clustering multivariate longitudinal data.     

A Coupled FEM-BEM Approach for the Solution of the Free-Boundary Axi-Symmetric Plasma Equilibrium Problem

In this paper we present a coupled Finite Element Method – Boundary Element Method (FEM-BEM) approach for the solution of the free-boundary axi-symmetric plasma equilibrium problem. The proposed method, obtained from an improvement of the Hagenow-Lackner coupling method, allows to efficiently model the equilibrium problem in unbounded domains by discretizing only the plasma region; the external conductors can be modelled either as 2D or 3D models, according to the problem of interest. The paper explores different iterative methods for the solution of the nonlinear Grad-Shafranov equation, such as Picard, Newton-Raphson and Newton-Krylov, in order to provide a robust and reliable tool, able to handle large-scale problems (e.g. high resolution equilibria). This method has been implemented in the FRIDA code (FRee-boundary Integro-Differential Axisimmetric – https://github. om/matteobonotto/ FRIDA), together with a suitable Adaptive Integration Technique (AIT) for the computation of the source term. FRIDA has been successfully tested and validated against experimental data from RFX-mod device, and numerical equilibria of an ITER-like device.     

Use and Applicability of the Gail Model to Calculate Breast Cancer Risk: A Scoping Review

Objective: To perform a scoping review of the applicability of the Gail model in different countries for different ethnicities. Methods: The review was conducted based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) checklist and search strategies based on the PICOS approach. The reviewed articles were included if they were published between 2013 and 2018 in English, Portuguese, or Spanish; were original articles available in full online; and described the use of the Gail model. The PubMed, Embase, and Web of Science data bases were searched. Results: A total of 38 articles eligible for analysis were identified, of which 16 used the Gail model to assess breast cancer risk in women, eight analyzed the applicability of this tool in their population, seven compared the tool and/or modified it according to the specific risk factors of their population, and seven cited the model in determining eligibility for chemoprevention. Conclusion: The Gail model has different applicabilities Greater effectiveness and breast cancer risk are found in developed countries.     

骨质疏松症动物模型的构建及实验方法研究进展

骨质疏松症是一种全身性骨代谢病,由多种因素引起,其特点是骨量、骨密度和骨组织的显微结构恶化,骨脆性增强和易发生骨折。骨质疏松症已严重威胁人类健康,最终将导致患者日常活动减少,生活质量降低,死亡率增加。针对不同的研究对象,选择一个正确、理想的动物骨质疏松的模型和实验方法以尽可能再现人类骨质疏松的状态,是开展动物实验的关键。我们综述了当前原发性和继发性骨质疏松等动物模型的构建,以及利用这些模型进行给药实验的研究方法,并对研发治疗骨质疏松的新型药物的选择提供了一些参考建议,以期对后续关于药物的作用机制、研发新药、药物的改良等研究提供思路。     

Prolyl and lysyl hydroxylases in collagen synthesis

Collagens are the most abundant proteins in the extracellular matrix. They provide a framework to build organs and tissues and give structural support to make them resistant to mechanical load and forces. Several intra‐ and extracellular modifications are needed to make functional collagen molecules, intracellular post‐translational modifications of proline and lysine residues having key roles in this. In this article, we provide a review on the enzymes responsible for the proline and lysine modifications, that is collagen prolyl 4‐hydroxylases, 3‐hydroxylases and lysyl hydroxylases, and discuss their biological functions and involvement in diseases.     

Enhancing medical radiation science education through a design science research methodology

Recently, there has been a call for research-informed and research-developed practice in health sciences education. This prompts the consideration of alternative suitable research approaches that could be used to enhance health sciences education practice, including medical radiation sciences education (MRSE) practice. In this discussion paper, the authors uphold design science research (DSR) methodology as a suitable research approach to enhance MRSE practice and research. An overview of the DSR methodology and an example of a project that used DSR methodology are presented to demonstrate the application of this methodology in MRSE practice and research. The paper concludes that the use of DSR methodology could be instrumental in addressing practice related challenges while developing a theoretical contribution to the discipline.