Evaluation of knowledge, attitudes, and practices related to osteoporosis and correlates of perceived high risk among people living in two main districts of Lebanon

BACKGROUND: The prevalence of osteoporosis is increasing in Lebanon. AIM: We evaluated the knowledge, attitudes, and practices related to osteoporosis and correlates of its perceived high risk among people living in Beirut and Mount Lebanon districts of Lebanon. METHODS: This study is a cross-sectional study which consisted of 376 participants that were selected from the two districts within two or three households after two geographical areas were randomly selected from each stratum classified by education and altitude. They were then asked to fill a KAP survey on osteoporosis and provide information on factors likely related to its perceived high risk. RESULTS: The majority of participants had a low (20.2%) and moderate (65.4%) knowledge of osteoporosis, with a higher knowledge in females than in males. A higher percentage of young people perceived it as a serious health risk than that of older people. In contrast, 85.9% participants reported drinking caffeinated beverages and 51.6% participants reported that they do not exercise. Glucose intolerance due to epigenetic and genetic factors, female sex, and older age were risk factors of a perceived high risk of osteoporosis, while any physical exercise, abstention from caffeine for 48 to 72 hours, and higher education were protective factors. CONCLUSION: A nationwide KAP study should be conducted; likewise, awareness campaigns should be adopted

Five years MIQE guidelines: The case of the Arabian countries

The quantitative real time polymerase chain reaction (qPCR) has become a key molecular enabling technology with an immense range of research, clinical, forensic as well as diagnostic applications. Its relatively moderate instrumentation and reagent requirements have led to its adoption by numerous laboratories, including those located in the Arabian world, where qPCR, which targets DNA, and reverse transcription qPCR (RT-qPCR), which targets RNA, are widely used for region-specific biotechnology, agricultural and human genetic studies. However, it has become increasingly apparent that there are significant problems with both the quality of qPCR-based data as well as the transparency of reporting. This realisation led to the publication of the Minimum Information for Publication of Quantitative Real-Time PCR Experiments (MIQE) guidelines in 2009 and their more widespread adoption in the last couple of years. An analysis of the performance of biomedical research in the Arabian world between 2001-2005 suggests that the Arabian world is producing fewer biomedical publications of lower quality than other Middle Eastern countries. Hence we have analysed specifically the quality of RT-qPCR-based peer-reviewed papers published since 2009 from Arabian researchers using a bespoke iOS/Android app developed by one of the authors. Our results show that compliance with 15 essential MIQE criteria was low (median of 40%, range 0-93%) and few details on RNA quality controls (22% compliance), assays design (12%), RT strategies (32%), amplification efficiencies (30%) and the normalisation process (3%). These data indicate that one of the reasons for the poor performance of Arabian world biomedical research may be the low standard of any supporting qPCR experiments and identify which aspects of qPCR experiments require significant improvements

The Digital MIQE Guidelines Update: Minimum Information for Publication of Quantitative Digital PCR Experiments for 2020

Digital PCR (dPCR) has developed considerably since the publication of the Minimum Information for Publication of Digital PCR Experiments (dMIQE) guidelines in 2013, with advances in instrumentation, software, applications, and our understanding of its technological potential. Yet these developments also have associated challenges; data analysis steps, including threshold setting, can be difficult and preanalytical steps required to purify, concentrate, and modify nucleic acids can lead to measurement error. To assist independent corroboration of conclusions, comprehensive disclosure of all relevant experimental details is required. To support the community and reflect the growing use of dPCR, we present an update to dMIQE, dMIQE2020, including a simplified dMIQE table format to assist researchers in providing key experimental information and understanding of the associated experimental process. Adoption of dMIQE2020 by the scientific community will assist in standardizing experimental protocols, maximize efficient utilization of resources, and further enhance the impact of this powerful technology

Approche transcriptomique du bénéfice fonctionnel des folates et étude de l'effet de la Fumosine B1

PARIS-AgroParisTech Centre Paris (751052302) / SudocSudocFranceF

Shisha microbiota: the good, the bad and the not so ugly

Abstract Objective Over the last decade, there has been a rapid expansion of the trendy water pipe smoking around the world especially among younger adults. The initial objective of this study was to identify the microbiota of the shisha, which may either be of no harm for the smoker or enhance the threat on his well-being. The total DNA for the metagenomics study was conducted on three different shishas from three different delivery shops in Jounieh, Lebanon. The microbiota in two solid parts of the shisha, shaft and hose, were analysed including the fresh tobacco and the water in the bowl. All samples were analysed using high-throughput sequencing of 16S rRNA gene amplicons. Results Overall, more than 40 bacterial genera were found in the three investigated shishas, some are commensal others are pathogenic. All three shishas showed similar microbial content regarding the bacteria inhabiting in water, shaft, or hose. From the results of this study it appears that a very large quantity of bacteria was found in the water pipes, some are harmful and others beneficial. We assume that the presence of gut dependent microbiota is related to the loose hygienic conditions in which the shisha is prepared

The importance of efficiency-correction in qPCR

Yes the story is continuing! More and more researchers, biological journals, academic and commercial institutions worldwide, are supporting the MIQE guidelines. The recitation record of Scopus and Google Scholar documents this. As for May 2019, we count multiple thousand citations (1) for the qPCR MIQE guideline (2) (6.150 by Scopus and 8.200 by Google Scholar) as well as for the digital MIQE guideline (3) (295 by Scopus and 365 by Google Scholar). Hence, the qPCR and dPCR MIQE guidelines are a worldwide standardisation success story, which are driven forward by scientific validity and credibility in the PCR community. The present third edition of the MIQE & qPCR iBook will push the ‘MIQE idea’ even further in any laboratory worldwide and beyond in the scientists’ workflow and minds. It should clearly show how to apply the guidelines and serve as a handy, visual, interactive and practical guide. Since the second edition in July 2016, we provided an additional MIQE & qPCR eBook version, which is readable on any eBook reader device (ePub file). This leaded to more than 2.500 extra downloads of the MIQE & qPCR iBook and eBook from over 40 countries worldwide. Our goal for the third edition is to update the existing content by new topics, and to create an overall fancy interactive tool, by interfacing scientific publications with educating pictures, videos and scientific talks. The editors implemented multiple new chapters, describing the significance of the efficiency correction in qPCR, and how to compare results between multiple plates or qPCR runs (both authored by Jan M. Ruijter and Maurice van der Hoff). As well, new chapters around digital PCR were authored by Afif Abdel Nour and scientists from Eppendorf and Stilla Technologies (will follow in autumn 2019). Finally we implemented a chapter about RT and qPCR Troubleshooting and how to improve your data authored by application researchers from Analytik-Jena. In summary, we are proud to present a selection of international highly recognized authors from the academic field and from industrial research presenting their latest research applications. The described qPCR and dPCR methods and applications are tightly linked to the MIQE context, and show it clearly based on educational questionnaires or interactive ‘how to do’ instruction sheets. The at-hand MIQE & qPCR iBook & eBook should deliver the MIQE guidelines directly to the researcher and help to solve the daily problems in the molecular biology laboratory using quantitative PCR, digital PCR, single-cell qPCR, microRNA applications or any comparable techniques using PCR. The editors hope you like our explanatory, interactive and educational iBook, eBook and ePub concept, showing the advantages of the MIQE guidelines in an easy and understandable way. The proper application and recommendation mentioned in that publication should guarantee the successful qPCR or dPCR application in the lab, and will help authors, reviewers, editors, and researchers to evaluate the quality of the presented publication

Weekly Nowcasting of New COVID-19 Cases Using Past Viral Load Measurements

The rapid spread of the coronavirus disease COVID-19 has imposed clinical and financial burdens on hospitals and governments attempting to provide patients with medical care and implement disease-controlling policies. The transmissibility of the disease was shown to be correlated with the patient’s viral load, which can be measured during testing using the cycle threshold (Ct). Previous models have utilized Ct to forecast the trajectory of the spread, which can provide valuable information to better allocate resources and change policies. However, these models combined other variables specific to medical institutions or came in the form of compartmental models that rely on epidemiological assumptions, all of which could impose prediction uncertainties. In this study, we overcome these limitations using data-driven modeling that utilizes Ct and previous number of cases, two institution-independent variables. We collected three groups of patients (n = 6296, n = 3228, and n = 12,096) from different time periods to train, validate, and independently validate the models. We used three machine learning algorithms and three deep learning algorithms that can model the temporal dynamic behavior of the number of cases. The endpoint was 7-week forward number of cases, and the prediction was evaluated using mean square error (MSE). The sequence-to-sequence model showed the best prediction during validation (MSE = 0.025), while polynomial regression (OLS) and support vector machine regression (SVR) had better performance during independent validation (MSE = 0.1596, and MSE = 0.16754, respectively), which exhibited better generalizability of the latter. The OLS and SVR models were used on a dataset from an external institution and showed promise in predicting COVID-19 incidences across institutions. These models may support clinical and logistic decision-making after prospective validation

Overall compliance with MIQE guidelines of category A papers (journals with IF<5, n = 402) compared to category B papers (journals with IF>5, n = 59).

<p>Neither dataset passed the D'Agostino & Pearson and Shapiro&Wilks normality tests, hence the nonparametric Mann-Whitney test was used for data analysis).</p