Project description:BackgroundIn the last decade, several large-scale, clinical trials evaluating the efficacy of novel HIV prevention products have been completed, and eight are currently underway or about to be reported. Little attention has been given in the literature to the level of protection sufficient to warrant introduction, and there is concern that using the term "efficacy" to describe the effect of user-controlled methods such as microbicides may mislead policymakers.DesignWe review how the fields of family planning, vaccine science and mathematical modelling understand and use the terms efficacy and effectiveness, and explore with simple mathematical models how trial results of user-controlled products relate to common understandings of these terms.ResultsEach field brings different assumptions, a different evidence base and different expectations to interpretations of efficacy and effectiveness - a reality that could cloud informed assessment of emerging data.ConclusionWhen making judgments on the utility of new health technologies, it is important to use standards that yield appropriate comparisons for the innovation and that take into account the local epidemic and available alternatives.
Project description:Sensory systems often detect multiple types of inputs. For example, a receptor in a cell-signaling system often binds multiple kinds of ligands, and sensory neurons can respond to different types of stimuli. How do sensory systems compare these different kinds of signals? Here, we consider this question in a class of sensory systems - including bacterial chemotaxis- which have a property known as fold-change detection: their output dynamics, including amplitude and response time, depends only on the relative changes in signal, rather than absolute changes, over a range of several decades of signal. We analyze how fold-change detection systems respond to multiple signals, using mathematical models. Suppose that a step of fold F1 is made in input 1, together with a step of F2 in input 2. What total response does the system provide? We show that when both input signals impact the same receptor with equal number of binding sites, the integrated response is multiplicative: the response dynamics depend only on the product of the two fold changes, F1F2. When the inputs bind the same receptor with different number of sites n1 and n2, the dynamics depend on a product of power laws, [Formula: see text]. Thus, two input signals which vary over time in an inverse way can lead to no response. When the two inputs affect two different receptors, other types of integration may be found and generally the system is not constrained to respond according to the product of the fold-change of each signal. These predictions can be readily tested experimentally, by providing cells with two simultaneously varying input signals. The present study suggests how cells can compare apples and oranges, namely by comparing each to its own background level, and then multiplying these two fold-changes.
Project description:BackgroundOne of the challenges of bioinformatics remains the recognition of short signal sequences in genomic DNA such as donor or acceptor splice sites, splicing enhancers or silencers, translation initiation sites, transcription start sites, transcription factor binding sites, nucleosome binding sites, miRNA binding sites, or insulator binding sites. During the last decade, a wealth of algorithms for the recognition of such DNA sequences has been developed and compared with the goal of improving their performance and to deepen our understanding of the underlying cellular processes. Most of these algorithms are based on statistical models belonging to the family of Markov random fields such as position weight matrix models, weight array matrix models, Markov models of higher order, or moral Bayesian networks. While in many comparative studies different learning principles or different statistical models have been compared, the influence of choosing different prior distributions for the model parameters when using different learning principles has been overlooked, and possibly lead to questionable conclusions.ResultsWith the goal of allowing direct comparisons of different learning principles for models from the family of Markov random fields based on the same a-priori information, we derive a generalization of the commonly-used product-Dirichlet prior. We find that the derived prior behaves like a Gaussian prior close to the maximum and like a Laplace prior in the far tails. In two case studies, we illustrate the utility of the derived prior for a direct comparison of different learning principles with different models for the recognition of binding sites of the transcription factor Sp1 and human donor splice sites.ConclusionsWe find that comparisons of different learning principles using the same a-priori information can lead to conclusions different from those of previous studies in which the effect resulting from different priors has been neglected. We implement the derived prior is implemented in the open-source library Jstacs to enable an easy application to comparative studies of different learning principles in the field of sequence analysis.
Project description:Cancer cells and non-cancer cells differ in their metabolism and they emit distinct volatile compound profiles, allowing to recognise cancer cells by their scent. Insect odorant receptors are excellent chemosensors with high sensitivity and a broad receptive range unmatched by current gas sensors. We thus investigated the potential of utilising the fruit fly's olfactory system to detect cancer cells. Using in vivo calcium imaging, we recorded an array of olfactory receptor neurons on the fruit fly's antenna. We performed multidimensional analysis of antenna responses, finding that cell volatiles from different cell types lead to characteristic response vectors. The distances between these response vectors are conserved across flies and can be used to discriminate healthy mammary epithelial cells from different types of breast cancer cells. This may expand the repertoire of clinical diagnostics, and it is the first step towards electronic noses equipped with biological sensors, integrating artificial and biological olfaction.
Project description:Rapid advancements in sequencing technologies along with falling costs present widespread opportunities for microbiome studies across a vast and diverse array of environments. These impressive technological developments have been accompanied by a considerable growth in the number of methodological variables, including sampling, storage, DNA extraction, primer pairs, sequencing technology, chemistry version, read length, insert size, and analysis pipelines, amongst others. This increase in variability threatens to compromise both the reproducibility and the comparability of studies conducted. Here we perform the first reported study comparing both amplicon and shotgun sequencing for the three leading next-generation sequencing technologies. These were applied to six human stool samples using Illumina HiSeq, MiSeq and Ion PGM shotgun sequencing, as well as amplicon sequencing across two variable 16S rRNA gene regions. Notably, we found that the factor responsible for the greatest variance in microbiota composition was the chosen methodology rather than the natural inter-individual variance, which is commonly one of the most significant drivers in microbiome studies. Amplicon sequencing suffered from this to a large extent, and this issue was particularly apparent when the 16S rRNA V1-V2 region amplicons were sequenced with MiSeq. Somewhat surprisingly, the choice of taxonomic binning software for shotgun sequences proved to be of crucial importance with even greater discriminatory power than sequencing technology and choice of amplicon. Optimal N50 assembly values for the HiSeq was obtained for 10 million reads per sample, whereas the applied MiSeq and PGM sequencing depths proved less sufficient for shotgun sequencing of stool samples. The latter technologies, on the other hand, provide a better basis for functional gene categorisation, possibly due to their longer read lengths. Hence, in addition to highlighting methodological biases, this study demonstrates the risks associated with comparing data generated using different strategies. We also recommend that laboratories with particular interests in certain microbes should optimise their protocols to accurately detect these taxa using different techniques.
Project description:CoViD-19 deaths to population size ratios fail to account for well-documented age and sex differences in CoViD-19 mortality. To assess trends across populations for which CoViD-19 deaths might not be available by age and sex, an indirect age-and-sex adjustment can still be performed. The corresponding Comparative CoViD-19 Mortality Ratio (CCMR) only requires population age and sex compositions. To compare CoViD-19 and overall mortality levels, the Crude Death Rate (CDR) and life expectancy at birth for recent calendar years are the most widely available overall mortality indicators. Readily comparable to an annual CDR, a Crude CoViD-19 Death Rate (CCDR) can be calculated for periods of any duration. CoViD-19-induced declines in projected life expectancy at birth for 2020 can also be calculated from existing life tables. We calculate the CCMR and CCDR for the period from their first CoViD-19 death to the present using US age and sex data and current estimates of CoViD-19 deaths in 166 Countries whose population composition is available from the UN, 28 Provinces in China, the 50 United States and DC. Across these 245 populations, 14 States and 11 Countries have CCMR values above 1--the US value by construction. Most affected to date, the period CCDR in New York exceeds its CDR for the most recent year available (7.83 per thousand in 2017). We also calculate CCMR and CCDR values corresponding to projections for the 50 States and DC, and for 49 countries, for which we can additionally calculate reductions in 2020 life expectancy at birth using UN life tables. This suggests life-expectancy reductions between .5 and 1 year for 7 European Countries, 3 South-American Countries and the US. The .55 reduction in the U.S. amounts to nearly twice the largest single-year decline induced by HIV/AIDS (-.3 between 1992 and 1993) or the total decline induced by opioid overdoses (also -.3 between 2014 and 2017), and would bring US life expectancy at birth down to its lowest level since 2008. As current CoViD-19 death counts likely underestimate the total increase in deaths and current projections do not account for possible new infection waves later this year, the impact on 2020 life expectancies at birth should be expected to exceed these figures.
Project description:PurposeTo assess whether intensive care unit (ICU) outcomes for patients not affected by coronavirus disease 2019 (COVID-19) worsened during the COVID-19 pandemic.MethodsRetrospective cohort study including prospectively collected information of patients admitted to 165 ICUs in a hospital network in Brazil between 2011 and 2020. Association between admission in 2020 and worse hospital outcomes was performed using different techniques, including assessment of changes in illness severity of admitted patients, a variable life-adjusted display of mortality during 2020, a multivariate mixed regression model with admission year as both fixed effect and random slope adjusted for SAPS 3 score, an analysis of trends in performance using standardized mortality ratio (SMR) and standardized resource use (SRU), and perturbation analysis.ResultsA total of 644,644 admissions were considered. After excluding readmissions and patients with COVID-19, 514,219 patients were available for analysis. Non-COVID-19 patients admitted in 2020 had slightly lower age and SAPS 3 score but a higher mortality (6.4%) when compared with previous years (2019: 5.6%; 2018: 6.1%). Variable-adjusted life display (VLAD) in 2020 increased but started to decrease as the number of COVID-19 cases increased; this trend reversed as number of COVID cases reduced but recurred on the second wave. After logistic regression, being admitted in 2020 was associated with higher mortality when compared to previous years from 2016 and 2019. Individual ICUs standardized mortality ratio also increased during 2020 (higher SMR) while resource use remained constant, suggesting worsening performance. A perturbation analysis further confirmed changes in ICU outcomes for non-COVID-19 patients.ConclusionHospital outcomes of non-COVID-19 critically ill patients worsened during the pandemic in 2020, possibly resulting in an increased number of deaths in critically ill non-COVID patients.
Project description:Background: The COVID 19 epidemic submerged many health systems in the Amazon. The objective of the present study was to focus on the epidemic curves of the COVID 19 epidemic in different centers, and to look at testing and mortality data. Methods: Publicly available datasets were used. The log10 of the daily cumulated number of cases starting from the day the territory reached 100 cumulated cases was plotted to compare the magnitude, shape and slope of the different curves. The maximum daily testing efforts were plotted for each territory in relation to the maximum daily number of diagnoses. The case fatality rate was computed by dividing the number of COVID 19 deaths by the number of confirmed cases. Results: In the Amazonian regions in general the speed of growth was generally lower than in Europe or the USA, or Southern Brazil. Whereas, countries like South Korea or New Zealand "broke" the curve relatively rapidly the log linear trajectory seemed much longer with signs of a decline in growth rate as of early July 2020. After a very slow start, French Guiana had the lowest slope when compared to other Amazonian territories with significant epidemics. The Amazonian states of Roraima, Amazonas, Parà, and Amapà had among the highest number of cases and deaths per million inhabitants in the world. French Guiana had significantly fewer deaths relative to its number of confirmed cases than other Amazonian territories. French Guiana had a late epidemic surge with intense testing scale-up often exceeding 4,000 persons tested daily per million inhabitants. Brazil was an outlier with low daily testing levels in relation to the number of daily diagnoses. Conclusions: There were marked heterogeneities mortality rates suggesting that socioeconomic, political factors, and perhaps ethnic vulnerability led to striking outcome differences in this Amazonian context.