Literature search on risk factors for sarcoma: PubMed and Google Scholar may be complementary sources

<p>Abstract</p> <p>Background</p> <p>Within the context of a European network dedicated to the study of sarcoma the relevant literature on sarcoma risk factors was collected by searching PubMed and Google Scholar, the two information storage and retrieval databases which can be accessed without charge. The present study aims to appraise the relative proficiency of PubMed and Google Scholar.</p> <p>Findings</p> <p>Unlike PubMed, Google Scholar does not allow a choice between "Human" and "Animal" studies, nor between "Classical" and other types of studies. As a result, searches with Google Scholar produced high numbers of citations that have to be filtered. Google Scholar resulted in a higher sensitivity (proportion of relevant articles, meeting the search criteria), while PubMed in a higher specificity (proportion of lower quality articles not meeting the criteria, that are not retrieved). Concordance between Google Scholar and PubMed was as low as 8%.</p> <p>Conclusions</p> <p>This study focused just on one topic. Although further studies are warranted, PM and GS appear to be complementary and their integration could greatly improve the search of references in medical research.</p

Estimating summary measures of health: a structured workbook approach

BACKGROUND: Summary measures of health that combine mortality and morbidity into a single indicator are being estimated in the Canadian context for approximately 200 diseases and conditions. To manage the large amount of data and calculations for this many diseases, we have developed a structured workbook system with easy to use tools. We expect this system will be attractive to researchers from other countries or regions of Canada who are interested in estimating the health-adjusted life years (HALYs) lost to premature mortality and year-equivalents lost to reduced functioning, as well as population attributable fractions (PAFs) associated with risk factors. This paper describes the workbook system using cancers as an example, and includes the entire system as a free, downloadable package. METHODS: The workbook system was developed in Excel and runs on a personal computer. It is a database system that stores data on population structure, mortality, incidence, distributions of cases entering a multitude of health states, durations of time spent in health states, preference scores that weight for severity, life table estimates of life expectancies, and risk factor prevalence and relative risks. The tools are Excel files with embedded macro programs. The main tool generates workbooks that estimate HALY, one per disease, by copying data from the database into a pre-defined template. Other tools summarize the HALY results across diseases for easy analysis. RESULTS: The downloadable zip file contains the database files initialized with Canadian data for cancers, the tools, templates and workbooks that estimate PAF and a user guide. The workbooks that estimate HALY are generated from the system at a rate of approximately one minute per disease. The resulting workbooks are self-contained and can be used directly to explore the details of a particular disease. Results can be discounted at different rates through simple parameter modification. CONCLUSION: The structured workbook approach offers researchers an efficient, easy to use, and easy to understand set of tools for estimating HALY and PAF summary measures for their country or region of interest

Absent otoacoustic emissions predict otitis media in young Aboriginal children: A birth cohort study in Aboriginal and non-Aboriginal children in an arid zone of Western Australia

AbstractBackground: Otitis media (OM) is the most common paediatric illness for which antibiotics areprescribed. In Australian Aboriginal children OM is frequently asymptomatic and starts at a youngerage, is more common and more likely to result in hearing loss than in non-Aboriginal children.Absent transient evoked otoacoustic emissions (TEOAEs) may predict subsequent risk of OM.Methods: 100 Aboriginal and 180 non-Aboriginal children in a semi-arid zone of WesternAustralia were followed regularly from birth to age 2 years. Tympanometry was conducted atroutine field follow-up from age 3 months. Routine clinical examination by an ENT specialist wasto be done 3 times and hearing assessment by an audiologist twice. TEOAEs were measured at ages&lt;1 and 1–2 months. Cox proportional hazards model was used to investigate the associationbetween absent TEOAEs and subsequent risk of OM.Results: At routine ENT specialist clinics, OM was detected in 55% of 184 examinations inAboriginal children and 26% of 392 examinations in non-Aboriginal children; peak prevalence was72% at age 5–9 months in Aboriginal children and 40% at 10–14 months in non-Aboriginal children.Moderate-severe hearing loss was present in 32% of 47 Aboriginal children and 7% of 120 non-Aboriginal children aged 12 months or more.TEOAE responses were present in 90% (46/51) of Aboriginal children and 99% (120/121) of non-Aboriginal children aged &lt;1 month and in 62% (21/34) and 93% (108/116), respectively, inAboriginal and non-Aboriginal children at age 1–2 months. Aboriginal children who failed TEOAEat age 1–2 months were 2.6 times more likely to develop OM subsequently than those who passed.Overall prevalence of type B tympanograms at field follow-up was 50% (n = 78) in Aboriginalchildren and 20% (n = 95) in non-Aboriginal children

A Systems Approach for Tumor Pharmacokinetics

Recent advances in genome inspired target discovery, small molecule screens, development of biological and nanotechnology have led to the introduction of a myriad of new differently sized agents into the clinic. The differences in small and large molecule delivery are becoming increasingly important in combination therapies as well as the use of drugs that modify the physiology of tumors such as anti-angiogenic treatment. The complexity of targeting has led to the development of mathematical models to facilitate understanding, but unfortunately, these studies are often only applicable to a particular molecule, making pharmacokinetic comparisons difficult. Here we develop and describe a framework for categorizing primary pharmacokinetics of drugs in tumors. For modeling purposes, we define drugs not by their mechanism of action but rather their rate-limiting step of delivery. Our simulations account for variations in perfusion, vascularization, interstitial transport, and non-linear local binding and metabolism. Based on a comparison of the fundamental rates determining uptake, drugs were classified into four categories depending on whether uptake is limited by blood flow, extravasation, interstitial diffusion, or local binding and metabolism. Simulations comparing small molecule versus macromolecular drugs show a sharp difference in distribution, which has implications for multi-drug therapies. The tissue-level distribution differs widely in tumors for small molecules versus macromolecular biologic drugs, and this should be considered in the design of agents and treatments. An example using antibodies in mouse xenografts illustrates the different in vivo behavior. This type of transport analysis can be used to aid in model development, experimental data analysis, and imaging and therapeutic agent design.National Institutes of Health (U.S.) (grant T32 CA079443

Evaluating the Effects of SARS-CoV-2 Spike Mutation D614G on Transmissibility and Pathogenicity.

Global dispersal and increasing frequency of the SARS-CoV-2 spike protein variant D614G are suggestive of a selective advantage but may also be due to a random founder effect. We investigate the hypothesis for positive selection of spike D614G in the United Kingdom using more than 25,000 whole genome SARS-CoV-2 sequences. Despite the availability of a large dataset, well represented by both spike 614 variants, not all approaches showed a conclusive signal of positive selection. Population genetic analysis indicates that 614G increases in frequency relative to 614D in a manner consistent with a selective advantage. We do not find any indication that patients infected with the spike 614G variant have higher COVID-19 mortality or clinical severity, but 614G is associated with higher viral load and younger age of patients. Significant differences in growth and size of 614G phylogenetic clusters indicate a need for continued study of this variant

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells.

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity.This work is supported by the UK Medical Research Council (MRC); Chinese Academy of Medical Sciences(CAMS) Innovation Fund for Medical Sciences (CIFMS), China; National Institute for Health Research (NIHR)Oxford Biomedical Research Centre, and UK Researchand Innovation (UKRI)/NIHR through the UK Coro-navirus Immunology Consortium (UK-CIC). Sequencing of SARS-CoV-2 samples and collation of data wasundertaken by the COG-UK CONSORTIUM. COG-UK is supported by funding from the Medical ResearchCouncil (MRC) part of UK Research & Innovation (UKRI),the National Institute of Health Research (NIHR),and Genome Research Limited, operating as the Wellcome Sanger Institute. T.I.d.S. is supported by a Well-come Trust Intermediate Clinical Fellowship (110058/Z/15/Z). L.T. is supported by the Wellcome Trust(grant number 205228/Z/16/Z) and by theUniversity of Liverpool Centre for Excellence in Infectious DiseaseResearch (CEIDR). S.D. is funded by an NIHR GlobalResearch Professorship (NIHR300791). L.T. and S.C.M.are also supported by the U.S. Food and Drug Administration Medical Countermeasures Initiative contract75F40120C00085 and the National Institute for Health Research Health Protection Research Unit (HPRU) inEmerging and Zoonotic Infections (NIHR200907) at University of Liverpool inpartnership with Public HealthEngland (PHE), in collaboration with Liverpool School of Tropical Medicine and the University of Oxford.L.T. is based at the University of Liverpool. M.D.P. is funded by the NIHR Sheffield Biomedical ResearchCentre (BRC – IS-BRC-1215-20017). ISARIC4C is supported by the MRC (grant no MC_PC_19059). J.C.K.is a Wellcome Investigator (WT204969/Z/16/Z) and supported by NIHR Oxford Biomedical Research Centreand CIFMS. The views expressed are those of the authors and not necessarily those of the NIHR or MRC