From stellar nebula to planetesimals

Solar and extrasolar comets and extrasolar planets are the subject of numerous studies in order to determine their chemical composition and internal structure. In the case of planetesimals, their compositions are important as they govern in part the composition of future planets. The present works aims at determining the chemical composition of icy planetesimals, believed to be similar to present day comets, formed in stellar systems of solar chemical composition. The main objective of this work is to provide valuable theoretical data on chemical composition for models of planetesimals and comets, and models of planet formation and evolution. We have developed a model that calculates the composition of ices formed during the cooling of the stellar nebula. Coupled with a model of refractory element formation, it allows us to determine the chemical composition and mass ratio of ices to rocks in icy planetesimals throughout in the protoplanetary disc. We provide relationships for ice line positions (for different volatile species) in the disc, and chemical compositions and mass ratios of ice relative to rock for icy planetesimals in stellar systems of solar chemical composition. From an initial homogeneous composition of the nebula, a wide variety of chemical compositions of planetesimals were produced as a function of the mass of the disc and distance to the star. Ices incorporated in planetesimals are mainly composed of H2O, CO, CO2, CH3OH, and NH3. The ice/rock mass ratio is equal to 1+-0.5 in icy planetesimals following assumptions. This last value is in good agreement with observations of solar system comets, but remains lower than usual assumptions made in planet formation models, taking this ratio to be of 2-3

Elemental ratios in stars vs planets

Context. The chemical composition of planets is an important constraint for planet formation and subsequent differentiation. While theoretical studies try to derive the compositions of planets from planet formation models in order to link the composition and formation process of planets, other studies assume that the elemental ratios in the formed planet and in the host star are the same. Aims. Using a chemical model combined with a planet formation model, we aim to link the composition of stars with solar mass and luminosity with the composition of the hosted planets. For this purpose, we study the three most important elemental ratios that control the internal structure of a planet: Fe/Si, Mg/Si, and C/O. Methods. A set of 18 different observed stellar compositions was used to cover a wide range of these elemental ratios. The Gibbs energy minimization assumption was used to derive the composition of planets, taking stellar abundances as proxies for nebular abundances, and to generate planets in a self-consistent planet formation model. We computed the elemental ratios Fe/Si, Mg/Si and C/O in three types of planets (rocky, icy, and giant planets) formed in different protoplanetary discs, and compared them to stellar abundances. Results. We show that the elemental ratios Mg/Si and Fe/Si in planets are essentially identical to those in the star. Some deviations are shown for planets that formed in specific regions of the disc, but the relationship remains valid within the ranges encompassed in our study. The C/O ratio shows only a very weak dependence on the stellar value.Comment: 8 pages, 5 figures, 3 tables. Accepted for publication in A&

From stellar nebula to planets: the refractory components

We computed the abundance of refractory elements in planetary bodies formed in stellar systems with solar chemical composition by combining models for chemical composition and planet formation. We also consider the formation of refractory organic compounds, which have been ignored in previous studies on this topic. We used the commercial software package HSC Chemistry in order to compute the condensation sequence and chemical composition of refractory minerals incorporated into planets. The problem of refractory organic material is approached with two distinct model calculations: the first considers that the fraction of atoms used in the formation of organic compounds is removed from the system (i.e. organic compounds are formed in the gas phase and are nonreactive); and the second assumes that organic compounds are formed by the reaction between different compounds that had previously condensed from the gas phase. Results show that refractory material represents more than 50 wt % of the mass of solids accreted by the simulated planets, with up to 30 wt % of the total mass composed of refractory organic compounds. Carbide and silicate abundances are consistent with C/O and Mg/Si elemental ratios of 0.5 and 1.02 for the Sun. Less than 1 wt % of carbides; pyroxene and olivine in similar quantities are formed. The model predicts planets that are similar in composition to those of the Solar system. It also shows that, starting from a common initial nebula composition, a wide variety of chemically different planets can form, which means that the differences in planetary compositions are due to differences in the planetary formation process. We show that a model in which refractory organic material is absent from the system is more compatible with observations. The use of a planet formation model is essential to form a wide diversity of planets in a consistent way.Comment: 18 pages, 29 figures. Accepted for publication in A&

Prediction of HIV status based on socio-behavioural characteristics in East and Southern Africa.

INTRODUCTION High yield HIV testing strategies are critical to reach epidemic control in high prevalence and low-resource settings such as East and Southern Africa. In this study, we aimed to predict the HIV status of individuals living in Angola, Burundi, Ethiopia, Lesotho, Malawi, Mozambique, Namibia, Rwanda, Zambia and Zimbabwe with the highest precision and sensitivity for different policy targets and constraints based on a minimal set of socio-behavioural characteristics. METHODS We analysed the most recent Demographic and Health Survey from these 10 countries to predict individual's HIV status using four different algorithms (a penalized logistic regression, a generalized additive model, a support vector machine, and a gradient boosting trees). The algorithms were trained and validated on 80% of the data, and tested on the remaining 20%. We compared the predictions based on the F1 score, the harmonic mean of sensitivity and positive predictive value (PPV), and we assessed the generalization of our models by testing them against an independent left-out country. The best performing algorithm was trained on a minimal subset of variables which were identified as the most predictive, and used to 1) identify 95% of people living with HIV (PLHIV) while maximising precision and 2) identify groups of individuals by adjusting the probability threshold of being HIV positive (90% in our scenario) for achieving specific testing strategies. RESULTS Overall 55,151 males and 69,626 females were included in the analysis. The gradient boosting trees algorithm performed best in predicting HIV status with a mean F1 score of 76.8% [95% confidence interval (CI) 76.0%-77.6%] for males (vs [CI 67.8%-70.6%] for SVM) and 78.8% [CI 78.2%-79.4%] for females (vs [CI 73.4%-75.8%] for SVM). Among the ten most predictive variables for each sex, nine were identical: longitude, latitude and, altitude of place of residence, current age, age of most recent partner, total lifetime number of sexual partners, years lived in current place of residence, condom use during last intercourse and, wealth index. Only age at first sex for male (ranked 10th) and Rohrer's index for female (ranked 6th) were not similar for both sexes. Our large-scale scenario, which consisted in identifying 95% of all PLHIV, would have required testing 49.4% of males and 48.1% of females while achieving a precision of 15.4% for males and 22.7% for females. For the second scenario, only 4.6% of males and 6.0% of females would have had to be tested to find 55.7% of all males and 50.5% of all females living with HIV. CONCLUSIONS We trained a gradient boosting trees algorithm to find 95% of PLHIV with a precision twice higher than with general population testing by using only a limited number of socio-behavioural characteristics. We also successfully identified people at high risk of infection who may be offered pre-exposure prophylaxis or voluntary medical male circumcision. These findings can inform the implementation of new high-yield HIV tests and help develop very precise strategies based on low-resource settings constraints

Hospital Outcomes of Community-Acquired SARS-CoV-2 Omicron Variant Infection Compared With Influenza Infection in Switzerland

IMPORTANCE: With the ongoing COVID-19 pandemic, it is crucial to assess the current burden of disease of community-acquired SARS-CoV-2 Omicron variant in hospitalized patients to tailor appropriate public health policies. Comparisons with better-known seasonal influenza infections may facilitate such decisions. OBJECTIVE: To compare the in-hospital outcomes of patients hospitalized with the SARS-CoV-2 Omicron variant with patients with influenza. DESIGN, SETTING, AND PARTICIPANTS: This cohort study was based on a national COVID-19 and influenza registry. Hospitalized patients aged 18 years and older with community-acquired SARS-CoV-2 Omicron variant infection who were admitted between January 15 and March 15, 2022 (when B.1.1.529 Omicron predominance was >95%), and hospitalized patients with influenza A or B infection from January 1, 2018, to March 15, 2022, where included. Patients without a study outcome by August 30, 2022, were censored. The study was conducted at 15 hospitals in Switzerland. EXPOSURES: Community-acquired SARS-CoV-2 Omicron variant vs community-acquired seasonal influenza A or B. MAIN OUTCOMES AND MEASURES: Primary and secondary outcomes were defined as in-hospital mortality and admission to the intensive care unit (ICU) for patients with the SARS-CoV-2 Omicron variant or influenza. Cox regression (cause-specific and Fine-Gray subdistribution hazard models) was used to account for time-dependency and competing events, with inverse probability weighting to adjust for confounders with right-censoring at day 30. RESULTS: Of 5212 patients included from 15 hospitals, 3066 (58.8%) had SARS-CoV-2 Omicron variant infection in 14 centers and 2146 patients (41.2%) had influenza A or B in 14 centers. Of patients with the SARS-CoV-2 Omicron variant, 1485 (48.4%) were female, while 1113 patients with influenza (51.9%) were female (P = .02). Patients with the SARS-CoV-2 Omicron variant were younger (median [IQR] age, 71 [53-82] years) than those with influenza (median [IQR] age, 74 [59-83] years; P < .001). Overall, 214 patients with the SARS-CoV-2 Omicron variant (7.0%) died during hospitalization vs 95 patients with influenza (4.4%; P < .001). The final adjusted subdistribution hazard ratio (sdHR) for in-hospital death for SARS-CoV-2 Omicron variant vs influenza was 1.54 (95% CI, 1.18-2.01; P = .002). Overall, 250 patients with the SARS-CoV-2 Omicron variant (8.6%) vs 169 patients with influenza (8.3%) were admitted to the ICU (P = .79). After adjustment, the SARS-CoV-2 Omicron variant was not significantly associated with increased ICU admission vs influenza (sdHR, 1.08; 95% CI, 0.88-1.32; P = .50). CONCLUSIONS AND RELEVANCE: The data from this prospective, multicenter cohort study suggest a significantly increased risk of in-hospital mortality for patients with the SARS-CoV-2 Omicron variant vs those with influenza, while ICU admission rates were similar

Social, Behavioral, and Cultural factors of HIV in Malawi: Semi-Automated Systematic Review.

BACKGROUND Demographic and sociobehavioral factors are strong drivers of HIV infection rates in sub-Saharan Africa. These factors are often studied in qualitative research but ignored in quantitative analyses. However, they provide in-depth insight into the local behavior and may help to improve HIV prevention. OBJECTIVE To obtain a comprehensive overview of the sociobehavioral factors influencing HIV prevalence and incidence in Malawi, we systematically reviewed the literature using a newly programmed tool for automatizing part of the systematic review process. METHODS Due to the choice of broad search terms ("HIV AND Malawi"), our preliminary search revealed many thousands of articles. We, therefore, developed a Python tool to automatically extract, process, and categorize open-access articles published from January 1, 1987 to October 1, 2019 in the PubMed, PubMed Central, JSTOR, Paperity, and arXiV databases. We then used a topic modelling algorithm to classify and identify publications of interest. RESULTS Our tool extracted 22,709 unique articles; 16,942 could be further processed. After topic modelling, 519 of these were clustered into relevant topics, of which 20 were kept after manual screening. We retrieved 7 more publications after examining the references so that 27 publications were finally included in the review. Reducing the 16,942 articles to 519 potentially relevant articles using the software took 5 days. Several factors contributing to the risk of HIV infection were identified, including religion, gender and relationship dynamics, beliefs, and sociobehavioral attitudes. CONCLUSIONS Our software does not replace traditional systematic reviews, but it returns useful results to broad queries of open-access literature in under a week, without a priori knowledge. This produces a "seed dataset" of relevance that could be further developed. It identified known factors and factors that may be specific to Malawi. In the future, we aim to expand the tool by adding more social science databases and applying it to other sub-Saharan African countries

Isotopic ratios D/H and ¹⁵ N/¹⁴N in giant planets

The determination of isotopic ratios in planets is important since it allows us to investigate the origins and initial composition of materials. The present work aims to determine the possible range of values for isotopic ratios D/H and ¹⁵N/¹⁴N in giant planets. The main objective is to provide valuable theoretical assumptions on the isotopic composition of giant planets, their internal structure, and the main reservoirs of species. We use models of ice formation and planet formation that compute the composition of ices and gas accreted in the core and the envelope of planets. Assuming a single initial value for isotopic ratios in volatile species, and disruption of planetesimals in the envelope of gaseous planets, we obtain a wide variety of D/H and ¹⁵N/¹⁴N ratios in low-mass planets (≤100 Mearth) due to the migration pathway of planets, the accretion time of gas species whose relative abundance evolves with time, and isotope exchanges among species. If giant planets with mass greater than 100 Mearth have solar isotopic ratios such as Jupiter and Saturn due to their higher envelope mass, Neptune-type planets present values ranging between one and three times the solar value. It seems therefore difficult to use isotopic ratios in the envelope of these planets to get information about their formation in the disc. For giant planets, the ratios allow us to constrain the mass fraction of volatile species in the envelope needed to reproduce the observational data by assuming initial values for isotopic ratios in volatile species

Gas composition of the main volatile elements in protoplanetary discs and its implication for planet formation

Context. Direct observations of gaseous exoplanets reveal that their gas envelope has a higher C/O ratio than that of the host star (e.g., Wasp 12-b). This has been explained by considering that the gas phase of the disc could be inhomogeneous, exceeding the stellar C/O ratio in regions where these planets formed; but few studies have considered the drift of the gas and planet migration. Aims. We aim to derive the gas composition in planets through planet formation to evaluate if the formation of giant planets with an enriched C/O ratio is possible. The study focusses on the effects of different processes on the C/O ratio, such as the disc evolution, the drift of gas, and planet migration. Methods. We used our previous models for computing the chemical composition, together with a planet formation model, to which we added the composition and drift of the gas phase of the disc, which is composed of the main volatile species H2O, CO, CO2, NH3, N2, CH3OH, CH4, and H2S, H2 and He. The study focusses on the region where ice lines are present and influence the C/O ratio of the planets. Results. Modelling shows that the condensation of volatile species as a function of radial distance allows for C/O enrichment in specific parts of the protoplanetary disc of up to four times the solar value. This leads to the formation of planets that can be enriched in C/O in their envelope up to three times the solar value. Planet migration, gas phase evolution and disc irradiation enables the evolution of the initial C/O ratio that decreases in the outer part of the disc and increases in the inner part of the disc. The total C/O ratio of the planets is governed by the contribution of ices accreted, suggesting that high C/O ratios measured in planetary atmospheres are indicative of a lack of exchange of material between the core of a planet and its envelope or an observational bias. It also suggests that the observed C/O ratio is not representative of the total C/O ratio of the planet

An Automated Literature Review Tool (LiteRev) for Streamlining and Accelerating Research Using Natural Language Processing and Machine Learning: Descriptive Performance Evaluation Study

Background: Literature reviews (LRs) identify, evaluate, and synthesize relevant papers to a particular research question to advance understanding and support decision-making. However, LRs, especially traditional systematic reviews, are slow, resource-intensive, and become outdated quickly. Objective: LiteRev is an advanced and enhanced version of an existing automation tool designed to assist researchers in conducting LRs through the implementation of cutting-edge technologies such as natural language processing and machine learning techniques. In this paper, we present a comprehensive explanation of LiteRev's capabilities, its methodology, and an evaluation of its accuracy and efficiency to a manual LR, highlighting the benefits of using LiteRev. Methods: Based on the user's query, LiteRev performs an automated search on a wide range of open-access databases and retrieves relevant metadata on the resulting papers, including abstracts or full texts when available. These abstracts (or full texts) are text processed and represented as a term frequency-inverse document frequency matrix. Using dimensionality reduction (pairwise controlled manifold approximation) and clustering (hierarchical density-based spatial clustering of applications with noise) techniques, the corpus is divided into different topics described by a list of the most important keywords. The user can then select one or several topics of interest, enter additional keywords to refine its search, or provide key papers to the research question. Based on these inputs, LiteRev performs a k-nearest neighbor (k-NN) search and suggests a list of potentially interesting papers. By tagging the relevant ones, the user triggers new k-NN searches until no additional paper is suggested for screening. To assess the performance of LiteRev, we ran it in parallel to a manual LR on the burden and care for acute and early HIV infection in sub-Saharan Africa. We assessed the performance of LiteRev using true and false predictive values, recall, and work saved over sampling. Results: LiteRev extracted, processed, and transformed text into a term frequency-inverse document frequency matrix of 631 unique papers from PubMed. The topic modeling module identified 16 topics and highlighted 2 topics of interest to the research question. Based on 18 key papers, the k-NNs module suggested 193 papers for screening out of 613 papers in total (31.5% of the whole corpus) and correctly identified 64 relevant papers out of the 87 papers found by the manual abstract screening (recall rate of 73.6%). Compared to the manual full text screening, LiteRev identified 42 relevant papers out of the 48 papers found manually (recall rate of 87.5%). This represents a total work saved over sampling of 56%. Conclusions: We presented the features and functionalities of LiteRev, an automation tool that uses natural language processing and machine learning methods to streamline and accelerate LRs and support researchers in getting quick and in-depth overviews on any topic of interest.</p

Grippenet: A New Tool for the Monitoring, Risk-Factor and Vaccination Coverage Analysis of Influenza-Like Illness in Switzerland

Implemented in Switzerland in November 2016, Grippenet provides Internet-based participatory surveillance of influenza-like illness (ILI). The aim of this research is to test the feasibility of such a system and its ability to detect risk factors and to assess ILI-related behaviors. Participants filled in a web-based socio-demographic and behavioral questionnaire upon registration, and a weekly symptoms survey during the influenza season. ILI incidence was calculated weekly, and risk factors associated to ILI were analyzed at the end of each season. From November 2016 to May 2019, 1247 participants were included. The crossing of the Sentinel System (Sentinella) epidemic threshold was associated with an increase or decrease of Grippenet ILI incidence, within the same week or earlier. The number of active users varied according to ILI incidence. Factors associated with ILI were: ages 0-4 compared with 5-14 (adjusted odds ratio (AOR) 0.6, 95% confidence interval (CI) 0.19-0.99), 15-29 (AOR 0.29, 95% CI 0.15-0.60), and 65+ (AOR 0.38, 95% CI 0.16-0.93); female sex (male AOR 0.81, 95% CI 0.7-0.95); respiratory allergies (AOR 1.58, 95% CI 1.38-1.96), not being vaccinated (AOR 2.4, 95% CI 1.9-3.04); and self-employment (AOR 1.97, 95% CI 1.33-3.03). Vaccination rates were higher than those of the general population but not high enough to meet the Swiss recommendations. Approximately, 36.2% to 42.5% of users who reported one or more ILIs did not seek medical attention. These results illustrate the potential of Grippenet in complementing Sentinella for ILI monitoring in Switzerland