Facilitators and barriers of adaptation to diabetes: experiences of Iranian patients

Background: Diabetes mellitus is one of the most challenging and burdensome chronic diseases of the 21st century and More than 1% of the Iranian urban population older than 20 years develops Type 2 diabetes each year. Living with diabetes mellitus has been described as a dynamic personal transitional adaptation, based on restructuring of the illness perceived experience and management of the self. Adaptation to Type 2 Diabetes mellitus is an integral part of diabetes care.This study explored the experiences of facilitators and barriers adaptation to Type 2 Diabetes by Iranian patients.Methods: This study was conducted by using qualitative content analysis. Data were collected via in-depth, semi-structured and face to face interviews with 15 patients with type2 diabetes.Results: Three themes emerged from collected data, including a) individual context with Beliefs, personal background, and previous experience subthemes. b) supportive system with Family, Society and Health organizations subthemes and c) self-comparison with comparison with other diabetes and comparison with other diseases subthemes.Conclusions: Identifying and managing Facilitators and Barriers adaptation to Type 2 Diabetes mellitus are an integral part of diabetes care. This study provides a better understanding of the factors from perspective of patients and it can be utilized by health care providers to adapt their health care and education contents to better meet the needs of people with diabetes. © 2014 Karimi Moonaghi et al.; licensee BioMed Central Ltd

Struggling towards diagnosis: Experiences of Iranian diabetes

Background: Healthcare-seeking behavior is one of the factors determining the uptake and outcome of healthcare. However, few studies have discussed how and why diabetics seek healthcare assistance before meeting a physician. Objectives: In this study, we explored the subjective experiences of healthcare-seeking behavior among Iranian patients with type 2 diabetes mellitus. Patients and Methods: A qualitative approach was adopted using a conventional content analysis of semi-structured interviews carried out in the Diabetes Association in Tabriz (Iran) with 15 participants suffering from type 2 diabetes. Participants were recruited by the purposeful sampling method. Results: Five themes emerged from the study: 1) warning by physical signs; 2) personal processing; 3) self-remedy and its outcomes; 4) seeking information, and; 5) diagnosis and verification of information by healthcare staff. Conclusions: Individual social context plays an important role in the decision-making process when seeking healthcare for diabetes. The results of this study can be utilized by healthcare providers to facilitate interventions to increase diabetics' active involvement in their healthcare, and encourage a wider knowledge of its symptoms and outcomes to facilitate appropriate healthcare-seeking and service use. © 2014, Iranian Red Crescent Medical Journal

Closed-Loop Recycling of Copper from Waste Printed Circuit Boards Using Bioleaching and Electrowinning Processes

International audienceIn the present study, a model of closed-loop recycling of copper from PCBs is demonstrated, which involves the sequential application of bioleaching and electrowinning to selectively extract copper. This approach is proposed as part of the solution to resolve the challenging ever-increasing accumulation of electronic waste, e-waste, in the environment. This work is targeting copper, the most abundant metal in e-waste that represents up to 20% by weight of printed circuit boards (PCBs). In the first stage, bioleaching was tested for different pulp densities (0.25–1.00% w/v) and successfully used to extract multiple metals from PCBs using the acidophilic bacterium, Acidithiobacillus ferrooxidans. In the second stage, the method focused on the recovery of copper from the bioleachate by electrowinning. Metallic copper foils were formed, and the results demonstrated that 75.8% of copper available in PCBs had been recovered as a high quality copper foil, with 99 + % purity, as determined by energy dispersive X-ray analysis and Inductively-Coupled Plasma Optical Emission Spectrometry. This model of copper extraction, combining bioleaching and electrowinning, demonstrates a closed-loop method of recycling that illustrates the application of bioleaching in the circular economy. The copper foils have the potential to be reused, to form new, high value copper clad laminate for the production of complex printed circuit boards for the electronics manufacturing industry. Graphic Abstract: [Figure not available: see fulltext.] © 2020, The Author(s)

ANMM4CBR: a case-based reasoning method for gene expression data classification

<p>Abstract</p> <p>Background</p> <p>Accurate classification of microarray data is critical for successful clinical diagnosis and treatment. The "curse of dimensionality" problem and noise in the data, however, undermines the performance of many algorithms.</p> <p>Method</p> <p>In order to obtain a robust classifier, a novel Additive Nonparametric Margin Maximum for Case-Based Reasoning (ANMM4CBR) method is proposed in this article. ANMM4CBR employs a case-based reasoning (CBR) method for classification. CBR is a suitable paradigm for microarray analysis, where the rules that define the domain knowledge are difficult to obtain because usually only a small number of training samples are available. Moreover, in order to select the most informative genes, we propose to perform feature selection via additively optimizing a nonparametric margin maximum criterion, which is defined based on gene pre-selection and sample clustering. Our feature selection method is very robust to noise in the data.</p> <p>Results</p> <p>The effectiveness of our method is demonstrated on both simulated and real data sets. We show that the ANMM4CBR method performs better than some state-of-the-art methods such as support vector machine (SVM) and <it>k </it>nearest neighbor (<it>k</it>NN), especially when the data contains a high level of noise.</p> <p>Availability</p> <p>The source code is attached as an additional file of this paper.</p

Pre-treatment and extraction techniques for recovery of added value compounds from wastes throughout the agri-food chain

The enormous quantity of food wastes discarded annually force to look for alternatives for this interesting feedstock. Thus, food bio-waste valorisation is one of the imperatives of the nowadays society. This review is the most comprehensive overview of currently existing technologies and processes in this field. It tackles classical and innovative physical, physico-chemical and chemical methods of food waste pre-treatment and extraction for recovery of added value compounds and detection by modern technologies and are an outcome of the COST Action EUBIS, TD1203 Food Waste Valorisation for Sustainable Chemicals, Materials and Fuels

COVID-19 research progress: Bibliometrics and visualization analysis

Background: Coronavirus primarily targets the human respiratory system, COVID-19 (Coronavirus disease 2019) triggered in China in the late 2019. In March 2020, WHO announced the COVID-19 pandemic. This study aims to analyze and visualize the scientific structure of the COVID-19 publications using co-citation and co-authorship. Methods: This is a scientometric study. Web of Science Core Collection (WoSCC) was searched for all documents regarding COVID-19, MERS-Cov, and SARS-Cov from the beginning to 2020. An Excel spreadsheet was applied to gather and analyze the data and the CiteSpace was used to visualize and analyze the data. Results: A total of 5159 records were retrieved in WoSCC. The structure of the network indicated that the network mean silhouette was low (0.1444), implying that the network clusters� identity is not identifiable with high confidence. The network modularity was 0.7309. The cluster analysis of the co-citation network on documents from 2003 to 2020 provided 188 clusters. The largest cluster entitled, �the Middle East respiratory syndrome coronavirus� had 255 nodes. The coauthorship network illustrated that the most prolific countries, USA, China, and Saudi Arabia, have focused on a specific field and have formed separate clusters. Conclusion: The present study identified the important topics of research in the field of COVID-19 based on co-citation networks as well as the analysis of clusters of countries' collaborations. Despite the similarities in the production behavior in prolific countries, their thematic focus varies so that a country like China plays a role in �Quantitative Detection� cluster, while USA is the leading country in the �Biological Evaluation� cluster. © 2021. Iran University of Medical Science