'Nano' Morphology and Element Signatures of Early Life on Earth: A New Tool for Assessing Biogenicity

The relatively young technology of NanoSIMS is unlocking an exciting new level of information from organic matter in ancient sediments. We are using this technique to characterize Proterozoic organic material that is clearly biogenic as a guide for interpreting controversial organic structures in either terrestrial or extraterrestrial samples. NanoSIMS is secondary ion mass spectrometry for trace element and isotope analysis at sub-micron resolution. In 2005, Robert et al. [1] combined NanoSIMS element maps with optical microscopic imagery in an effort to develop a new method for assessing biogenicity of Precambrian structures. The ability of NanoSIMS to map simultaneously the distribution of organic elements with a 50 nm spatial resolution provides new biologic markers that could help define the timing of life s development on Earth. The current study corroborates the work of Robert et al. and builds on their study by using NanoSIMS to map C, N (as CN), S, Si and O of both excellently preserved microfossils and less well preserved, non-descript organics in Proterozoic chert from the ca. 0.8 Ga Bitter Springs Formation of Australia

Projections of epidemic transmission and estimation of vaccination impact during an ongoing Ebola virus disease outbreak in Northeastern Democratic Republic of Congo, as of Feb. 25, 2019.

BackgroundAs of February 25, 2019, 875 cases of Ebola virus disease (EVD) were reported in North Kivu and Ituri Provinces, Democratic Republic of Congo. Since the beginning of October 2018, the outbreak has largely shifted into regions in which active armed conflict has occurred, and in which EVD cases and their contacts have been difficult for health workers to reach. We used available data on the current outbreak, with case-count time series from prior outbreaks, to project the short-term and long-term course of the outbreak.MethodsFor short- and long-term projections, we modeled Ebola virus transmission using a stochastic branching process that assumes gradually quenching transmission rates estimated from past EVD outbreaks, with outbreak trajectories conditioned on agreement with the course of the current outbreak, and with multiple levels of vaccination coverage. We used two regression models to estimate similar projection periods. Short- and long-term projections were estimated using negative binomial autoregression and Theil-Sen regression, respectively. We also used Gott's rule to estimate a baseline minimum-information projection. We then constructed an ensemble of forecasts to be compared and recorded for future evaluation against final outcomes. From August 20, 2018 to February 25, 2019, short-term model projections were validated against known case counts.ResultsDuring validation of short-term projections, from one week to four weeks, we found models consistently scored higher on shorter-term forecasts. Based on case counts as of February 25, the stochastic model projected a median case count of 933 cases by February 18 (95% prediction interval: 872-1054) and 955 cases by March 4 (95% prediction interval: 874-1105), while the auto-regression model projects median case counts of 889 (95% prediction interval: 876-933) and 898 (95% prediction interval: 877-983) cases for those dates, respectively. Projected median final counts range from 953 to 1,749. Although the outbreak is already larger than all past Ebola outbreaks other than the 2013-2016 outbreak of over 26,000 cases, our models do not project that it is likely to grow to that scale. The stochastic model estimates that vaccination coverage in this outbreak is lower than reported in its trial setting in Sierra Leone.ConclusionsOur projections are concentrated in a range up to about 300 cases beyond those already reported. While a catastrophic outbreak is not projected, it is not ruled out, and prevention and vigilance are warranted. Prospective validation of our models in real time allowed us to generate more accurate short-term forecasts, and this process may prove useful for future real-time short-term forecasting. We estimate that transmission rates are higher than would be seen under target levels of 62% coverage due to contact tracing and vaccination, and this model estimate may offer a surrogate indicator for the outbreak response challenges

"Nano" Scale Biosignatures and the Search for Extraterrestrial Life

A critical step in the search for remnants of potential life forms on other planets lies in our ability to recognize indigenous fragments of ancient microbes preserved in some of Earth's oldest rocks. To this end, we are building a database of nano-scale chemical and morphological characteristics of some of Earth's oldest organic microfossils. We are primarily using the new technology of Nano-Secondary ion mass spectrometry (NanoSIMS) which provides in-situ, nano-scale elemental analysis of trace quantities of organic residues. The initial step was to characterize element composition of well-preserved, organic microfossils from the late Proterozoic (0.8 Ga) Bitter Springs Formation of Australia. Results from that work provide morphologic detail and nitrogen/carbon ratios that appear to reflect the well-established biological origin of these 0.8 Ga fossils

Projections of Ebola outbreak size and duration with and without vaccine use in Équateur, Democratic Republic of Congo, as of May 27, 2018.

As of May 27, 2018, 6 suspected, 13 probable and 35 confirmed cases of Ebola virus disease (EVD) had been reported in Équateur Province, Democratic Republic of Congo. We used reported case counts and time series from prior outbreaks to estimate the total outbreak size and duration with and without vaccine use. We modeled Ebola virus transmission using a stochastic branching process model that included reproduction numbers from past Ebola outbreaks and a particle filtering method to generate a probabilistic projection of the outbreak size and duration conditioned on its reported trajectory to date; modeled using high (62%), low (44%), and zero (0%) estimates of vaccination coverage (after deployment). Additionally, we used the time series for 18 prior Ebola outbreaks from 1976 to 2016 to parameterize the Thiel-Sen regression model predicting the outbreak size from the number of observed cases from April 4 to May 27. We used these techniques on probable and confirmed case counts with and without inclusion of suspected cases. Probabilistic projections were scored against the actual outbreak size of 54 EVD cases, using a log-likelihood score. With the stochastic model, using high, low, and zero estimates of vaccination coverage, the median outbreak sizes for probable and confirmed cases were 82 cases (95% prediction interval [PI]: 55, 156), 104 cases (95% PI: 58, 271), and 213 cases (95% PI: 64, 1450), respectively. With the Thiel-Sen regression model, the median outbreak size was estimated to be 65.0 probable and confirmed cases (95% PI: 48.8, 119.7). Among our three mathematical models, the stochastic model with suspected cases and high vaccine coverage predicted total outbreak sizes closest to the true outcome. Relatively simple mathematical models updated in real time may inform outbreak response teams with projections of total outbreak size and duration

Enhanced distance-dependent fluorescence quenching using size tuneable core shell silica nanoparticles

Silica nanoparticles (SNPs) have been used as favoured platforms for sensor, drug delivery and biological imaging applications, due to their ease of synthesis, size-control and bespoke physico-chemical properties. In this study, we have developed a protocol for the synthesis of size-tuneable SNPs, with diameters ranging from 20 nm to 500 nm, through the optimisation of experimental components required for nanoparticle synthesis. This protocol was also used to prepare fluorescent SNPs, via covalent linkages of fluorophores, to the nanoparticle matrix using 3-aminopropyltriethoxysilane (APTES). This enabled the fabrication of ratiometric, fluorescent, pH-sensitive nanosensors (75 nm diameter) composed SNPs covalently linked to two pH-sensitive fluorescent dyes Oregon Green (OG) and 5(6)-carboxyfluorescein (FAM) and a reference fluorescent dye 5-(6)-carboxytetramethylrhodamine (TAMRA), extending the dynamic range of measurement from pH 3.5 to 7.5. In addition, size-tuneable, core-shell SNPs, covalently linked to a fluorescent TAMRA core were synthesised to investigate distance-dependant fluorescence quenching between TAMRA and black hole quencher 2 (BHQ2®) using nanometre-sized silica shells as physical spacers. The results showed a significant fluorescence quenching could be observed over greater distances than that reported for the classical distance-dependent molecular fluorescence quenching techniques, e.g. the Förster (fluorescence) resonance energy transfer (FRET). The methods and protocols we have detailed in this manuscript will provide the basis for the reproducible production of size tunable SNPs, which will find broad utility in the development of sensors for biological applications

Inability to predict postpartum hemorrhage: insights from Egyptian intervention data

<p>Abstract</p> <p>Background</p> <p>Knowledge on how well we can predict primary postpartum hemorrhage (PPH) can help policy makers and health providers design current delivery protocols and PPH case management. The purpose of this paper is to identify risk factors and determine predictive probabilities of those risk factors for primary PPH among women expecting singleton vaginal deliveries in Egypt.</p> <p>Methods</p> <p>From a prospective cohort study, 2510 pregnant women were recruited over a six-month period in Egypt in 2004. PPH was defined as blood loss ≥ 500 ml. Measures of blood loss were made every 20 minutes for the first 4 hours after delivery using a calibrated under the buttocks drape. Using all variables available in the patients' charts, we divided them in ante-partum and intra-partum factors. We employed logistic regression to analyze socio-demographic, medical and past obstetric history, and labor and delivery outcomes as potential PPH risk factors. Post-model predicted probabilities were estimated using the identified risk factors.</p> <p>Results</p> <p>We found a total of 93 cases of primary PPH. In multivariate models, ante-partum hemoglobin, history of previous PPH, labor augmentation and prolonged labor were significantly associated with PPH. Post model probability estimates showed that even among women with three or more risk factors, PPH could only be predicted in 10% of the cases.</p> <p>Conclusions</p> <p>The predictive probability of ante-partum and intra-partum risk factors for PPH is very low. Prevention of PPH to all women is highly recommended.</p