Complete mtDNA genomes of Anopheles darlingi and an approach to anopheline divergence time

Abstract Background The complete sequences of the mitochondrial genomes (mtDNA) of members of the northern and southern genotypes of Anopheles (Nyssorhynchus) darlingi were used for comparative studies to estimate the time to the most recent common ancestor for modern anophelines, to evaluate differentiation within this taxon, and to seek evidence of incipient speciation. Methods The mtDNAs were sequenced from mosquitoes from Belize and Brazil and comparative analyses of structure and base composition, among others, were performed. A maximum likelihood approach linked with phylogenetic information was employed to detect evidence of selection and a Bayesian approach was used to date the split between the subgenus Nyssorhynchus and other Anopheles subgenera. Results The comparison of mtDNA sequences within the Anopheles darlingi taxon does not provide sufficient resolution to establish different units of speciation within the species. In addition, no evidence of positive selection in any protein-coding gene of the mtDNA was detected, and purifying selection likely is the basis for this lack of diversity. Bayesian analysis supports the conclusion that the most recent ancestor of Nyssorhynchus and Anopheles+Cellia was extant ~94 million years ago. Conclusion Analyses of mtDNA genomes of Anopheles darlingi do not provide support for speciation in the taxon. The dates estimated for divergence among the anopheline groups tested is in agreement with the geological split of western Gondwana (95 mya), and provides additional support for explaining the absence of Cellia in the New World, and Nyssorhynchus in the Afro-Eurasian continents

Social media in undergraduate medical education: A systematic review.

INTRODUCTION: There are over 3.81 billion worldwide active social media (SoMe) users. SoMe are ubiquitous in medical education, with roles across undergraduate programmes, including professionalism, blended learning, well being and mentoring. Previous systematic reviews took place before recent explosions in SoMe popularity and revealed a paucity of high-quality empirical studies assessing its effectiveness in medical education. This review aimed to synthesise evidence regarding SoMe interventions in undergraduate medical education, to identify features associated with positive and negative outcomes. METHODS: Authors searched 31 key terms through seven databases, in addition to references, citation and hand searching, between 16 June and 16 July 2020. Studies describing SoMe interventions and research on exposure to existing SoMe were included. Title, abstract and full paper screening were undertaken independently by two reviewers. Included papers were assessed for methodological quality using the Medical Education Research Study Quality Instrument (MERSQI) and/or the Standards for Reporting Qualitative Research (SRQR) instrument. Extracted data were synthesised using narrative synthesis. RESULTS: 112 studies from 26 countries met inclusion criteria. Methodological quality of included studies had not significantly improved since 2013. Engagement and satisfaction with SoMe platforms in medical education are described. Students felt SoMe flattened hierarchies and improved communication with educators. SoMe use was associated with improvement in objective knowledge assessment scores and self-reported clinical and professional performance, however evidence for long term knowledge retention was limited. SoMe use was occasionally linked to adverse impacts upon mental and physical health. Professionalism was heavily investigated and considered important, though generally negative correlations between SoMe use and medical professionalism may exist. CONCLUSIONS: Social media is enjoyable for students who may improve short term knowledge retention and can aid communication between learners and educators. However, higher-quality study is required to identify longer-term impact upon knowledge and skills, provide clarification on professionalism standards and protect against harms

Comparing different NTCP models that predict the incidence of radiation pneumonitis

Purpose: To compare different normal tissue complication probability (NTCP) models to predict the incidence of radiation pneumonitis on the basis of the dose distribution in the lung. Methods and Materials: The data from 382 breast cancer, malignant lymphoma, and inoperable non-small-cell lung cancer patients from two centers were studied. Radiation pneumonitis was scored using the Southwestern Oncology Group criteria. Dose-volume histograms of the lungs were calculated from the dose distributions that were corrected for dose per fraction effects. The dose-volume histogram of each patient was reduced to a single parameter using different local dose-effect relationships. Examples of single parameters were the mean lung dose (MLD) and the volume of lung receiving more than a threshold dose (V-Dth). The parameters for the different NTCP models were fit to patient data using a maximum likelihood analysis. Results: The best fit resulted in a linear local dose-effect relationship, with the MLD as the resulting single parameter. The relationship between the MLD and NTCP could be described with a median toxic dose (TD50) of 30.8 Gy and a steepness parameter m of 0.37. The best fit for the relationship between the V-Dth and the NTCP was obtained with a D-th of 13 Gy. The MLD model was found to be significantly better than the VIth model (p 35%. For arbitrary dose distributions, an estimate of the uncertainty in the NTCP could be determined using the probability distribution of the parameter values of the Lyman-Kutcher-Burman model. Conclusion: The maximum likelihood method revealed that the underlying local dose-effect relation for radiation pneumonitis was linear (the MLD model), rather than a step function (the V-Dth model). Thus, for the studied patient population, the MLD was the most accurate predictor for the incidence of radiation pneumonitis. (C) 2003 Elsevier Science Inc