Health information prescription system for non communicable diseases: A systematic review and thematic analysis

Objective - Prescribing health information is very important to empower informed patients. The goal of present study is to recognize challenges for developing health information prescription on non-communicable diseases. Material and Methods - Six data bases related to health information prescription were investigated. They included Web of Science, Scopus, PubMed, Google Scholar, Ovid and EMBASE. The investigated studies were published from 2000 to 2019. The language of the articles was English and the access to full text was one of the inclusion criteria. The research was evaluated by Prisma checklist and critical apprising. Different dimensions of health Information prescription system were recognized by thematic analysis. Results - 54 studies were recognized based on the inclusion criteria. The results showed that there were three main concepts related to primary dimensions of the system in designing health information prescription system: determination of system functional goals, recognition of implementation barriers and recognition of developmental sub-structures. There were 16 subcategories including primary goals for accessibility, the concerns related to patients information confidentiality, individual differences and interests and personalizing the process of information prescription, the lack of integrity in health Information system for providing pattern of health Information system related to diabetic patients. Conclusion - The goals, implementing barriers and functional substructures of health information prescription system should be recognized in order to improve self-care behaviors of diabetic patients in clinic. It is recommended that the future investigations focus on research gaps in personalizing health information prescription and integration of health information prescription process in health care system. © 2020, LLC Science and Innovations

The Association between Presence of Comorbidities and COVID-19 Severity: A Systematic Review and Meta-Analysis

Aim: Several studies reported the accompaniment of severe COVID-19 with comorbidities. However, there is not a systematic evaluation of all aspects of this association. Therefore, this meta-analysis aimed to assess the association between all underlying comorbidities in COVID-19 infection severity. Methods: Electronic literature search was performed via scientific search engines. After the removal of duplicates and selection of articles of interest, 28 studies were included. A fixed-effects model was used; however, if heterogeneity was high (I2 > 50) a random-effects model was applied to combine the data. Results: A total of 6,270 individuals were assessed (1,615 severe and 4,655 non-severe patients). The median age was 63 (95 confidence interval CI: 49-74) and 47 (95% CI: 19-63) years in the severe and non-severe groups, respectively. Moreover, about 41% of patients had comorbidities. Severity was higher in patients with a history of cerebrovascular disease: OR 4.85 (95% CI: 3.11-7.57). The odds of being in a severe group increase by 4.81 (95% CI: 3.43-6.74) for a history of cardiovascular disease (CVD). This was 4.19 (95% CI: 2.84-6.19) for chronic lung disease and 3.18, 95% CI: 2.09-4.82 for cancer. The odds ratios of diabetes and hypertension were 2.61 (95% CI: 2.02-3.3) and 2.37 (95% CI: 1.80-3.13), respectively. Conclusions: The presence of comorbidities is associated with severity of COVID-19 infection. The strongest association was observed for cerebrovascular disease, followed by CVD, chronic lung disease, cancer, diabetes, and hypertension. © 2021 S. Karger AG, Basel. All rights reserved

DNA isolation protocol effects on nuclear DNA analysis by microarrays, droplet digital PCR, and whole genome sequencing, and on mitochondrial DNA copy number estimation.

Potential bias introduced during DNA isolation is inadequately explored, although it could have significant impact on downstream analysis. To investigate this in human brain, we isolated DNA from cerebellum and frontal cortex using spin columns under different conditions, and salting-out. We first analysed DNA using array CGH, which revealed a striking wave pattern suggesting primarily GC-rich cerebellar losses, even against matched frontal cortex DNA, with a similar pattern on a SNP array. The aCGH changes varied with the isolation protocol. Droplet digital PCR of two genes also showed protocol-dependent losses. Whole genome sequencing showed GC-dependent variation in coverage with spin column isolation from cerebellum. We also extracted and sequenced DNA from substantia nigra using salting-out and phenol / chloroform. The mtDNA copy number, assessed by reads mapping to the mitochondrial genome, was higher in substantia nigra when using phenol / chloroform. We thus provide evidence for significant method-dependent bias in DNA isolation from human brain, as reported in rat tissues. This may contribute to array "waves", and could affect copy number determination, particularly if mosaicism is being sought, and sequencing coverage. Variations in isolation protocol may also affect apparent mtDNA abundance

On the constraints violation in forward dynamics of multibody systems

It is known that the dynamic equations of motion for constrained mechanical multibody systems are frequently formulated using the Newton-Euler’s approach, which is augmented with the acceleration constraint equations. This formulation results in the establishment of a mixed set of partial differential and algebraic equations, which are solved in order to predict the dynamic behavior of general multibody systems. The classical resolution of the equations of motion is highly prone to constraints violation because the position and velocity constraint equations are not fulfilled. In this work, a general and comprehensive methodology to eliminate the constraints violation at the position and velocity levels is offered. The basic idea of the described approach is to add corrective terms to the position and velocity vectors with the intent to satisfy the corresponding kinematic constraint equations. These corrective terms are evaluated as function of the Moore-Penrose generalized inverse of the Jacobian matrix and of the kinematic constraint equations. The described methodology is embedded in the standard method to solve the equations of motion based on the technique of Lagrange multipliers. Finally, the effectiveness of the described methodology is demonstrated through the dynamic modeling and simulation of different planar and spatial multibody systems. The outcomes in terms of constraints violation at the position and velocity levels, conservation of the total energy and computational efficiency are analyzed and compared with those obtained with the standard Lagrange multipliers method, the Baumgarte stabilization method, the augmented Lagrangian formulation, the index-1 augmented Lagrangian and the coordinate partitioning method.The first author expresses his gratitude to the Portuguese Foundation for Science and Technology through the PhD grant (PD/BD/114154/2016). This work has been supported by the Portuguese Foundation for Science and Technology with the reference project UID/EEA/04436/2013, by FEDER funds through the COMPETE 2020 – Programa Operacional Competitividade e Internacionalização (POCI) with the reference project POCI-01-0145-FEDER-006941.info:eu-repo/semantics/publishedVersio