Inferring introduction routes of invasive species using approximate Bayesian computation on microsatellite data

Determining the routes of introduction provides not only information about the history of an invasion process, but also information about the origin and construction of the genetic composition of the invading population. It remains difficult, however, to infer introduction routes from molecular data because of a lack of appropriate methods. We evaluate here the use of an approximate Bayesian computation (ABC) method for estimating the probabilities of introduction routes of invasive populations based on microsatellite data. We considered the crucial case of a single source population from which two invasive populations originated either serially from a single introduction event or from two independent introduction events. Using simulated datasets, we found that the method gave correct inferences and was robust to many erroneous beliefs. The method was also more efficient than traditional methods based on raw values of statistics such as assignment likelihood or pairwise F(ST). We illustrate some of the features of our ABC method, using real microsatellite datasets obtained for invasive populations of the western corn rootworm, Diabrotica virgifera virgifera. Most computations were performed with the DIYABC program (http://www1.montpellier.inra.fr/CBGP/diyabc/)

Outcomes in patients with gunshot wounds to the brain.

Introduction:Gunshot wounds to the brain (GSWB) confer high lethality and uncertain recovery. It is unclear which patients benefit from aggressive resuscitation, and furthermore whether patients with GSWB undergoing cardiopulmonary resuscitation (CPR) have potential for survival or organ donation. Therefore, we sought to determine the rates of survival and organ donation, as well as identify factors associated with both outcomes in patients with GSWB undergoing CPR. Methods:We performed a retrospective, multicenter study at 25 US trauma centers including dates between June 1, 2011 and December 31, 2017. Patients were included if they suffered isolated GSWB and required CPR at a referring hospital, in the field, or in the trauma resuscitation room. Patients were excluded for significant torso or extremity injuries, or if pregnant. Binomial regression models were used to determine predictors of survival/organ donation. Results:825 patients met study criteria; the majority were male (87.6%) with a mean age of 36.5 years. Most (67%) underwent CPR in the field and 2.1% (n=17) survived to discharge. Of the non-survivors, 17.5% (n=141) were considered eligible donors, with a donation rate of 58.9% (n=83) in this group. Regression models found several predictors of survival. Hormone replacement was predictive of both survival and organ donation. Conclusion:We found that GSWB requiring CPR during trauma resuscitation was associated with a 2.1% survival rate and overall organ donation rate of 10.3%. Several factors appear to be favorably associated with survival, although predictions are uncertain due to the low number of survivors in this patient population. Hormone replacement was predictive of both survival and organ donation. These results are a starting point for determining appropriate treatment algorithms for this devastating clinical condition. Level of evidence:Level II

Routine Laboratory Results and Thirty Day and One-Year Mortality Risk Following Hospitalization with Acute Decompensated Heart Failure

INTRODUCTION: Several blood tests are performed uniformly in patients hospitalized with acute decompensated heart failure and are predictive of the outcomes: complete blood count, electrolytes, renal function, glucose, albumin and uric acid. We sought to evaluate the relationship between routine admission laboratory tests results, patient characteristics and 30-day and one-year mortality of patients admitted for decompensated heart failure and to construct a simple mortality prediction tool. METHODS: A retrospective population based study. Data from seven tertiary hospitals on all admissions with a principal diagnosis of heart failure during the years 2002-2005 throughout Israel were captured. RESULTS: 8,246 patients were included in the study cohort. Thirty day mortality rate was 8.5% (701 patients) and one-year mortality rate was 28.7% (2,365 patients). Addition of five routine laboratory tests results (albumin, sodium, blood urea, uric acid and WBC) to a set of clinical and demographic characteristics improved c-statistics from 0.76 to 0.81 for 30-days and from 0.72 to 0.76 for one-year mortality prediction (both p-values <0.0001). Three dichotomized abnormal laboratory results with highest odds ratio for one-year mortality (hypoalbuminaemia, hyponatremia and elevated blood urea) were used to construct a simple prediction score, capable of discriminating from 1.1% to 21.4% in 30-day and from 11.6% to 55.6% in one-year mortality rates between patients with a score of 0 (1,477 patients) vs. score of 3 (544 patients). DISCUSSION: A small set of abnormal routine laboratory results upon admission can risk-stratify and independently predict 30-day and one-year mortality in patients hospitalized with acute decompensated heart failure

A multi-platform approach to identify a blood-based host protein signature for distinguishing between bacterial and viral infections in febrile children (PERFORM): a multi-cohort machine learning study.

BACKGROUND Differentiating between self-resolving viral infections and bacterial infections in children who are febrile is a common challenge, causing difficulties in identifying which individuals require antibiotics. Studying the host response to infection can provide useful insights and can lead to the identification of biomarkers of infection with diagnostic potential. This study aimed to identify host protein biomarkers for future development into an accurate, rapid point-of-care test that can distinguish between bacterial and viral infections, by recruiting children presenting to health-care settings with fever or a history of fever in the previous 72 h. METHODS In this multi-cohort machine learning study, patient data were taken from EUCLIDS, the Swiss Pediatric Sepsis study, the GENDRES study, and the PERFORM study, which were all based in Europe. We generated three high-dimensional proteomic datasets (SomaScan and two via liquid chromatography tandem mass spectrometry, referred to as MS-A and MS-B) using targeted and untargeted platforms (SomaScan and liquid chromatography mass spectrometry). Protein biomarkers were then shortlisted using differential abundance analysis, feature selection using forward selection-partial least squares (FS-PLS; 100 iterations), along with a literature search. Identified proteins were tested with Luminex and ELISA and iterative FS-PLS was done again (25 iterations) on the Luminex results alone, and the Luminex and ELISA results together. A sparse protein signature for distinguishing between bacterial and viral infections was identified from the selected proteins. The performance of this signature was finally tested using Luminex assays and by calculating disease risk scores. FINDINGS 376 children provided serum or plasma samples for use in the discovery of protein biomarkers. 79 serum samples were collected for the generation of the SomaScan dataset, 147 plasma samples for the MS-A dataset, and 150 plasma samples for the MS-B dataset. Differential abundance analysis, and the first round of feature selection using FS-PLS identified 35 protein biomarker candidates, of which 13 had commercial ELISA or Luminex tests available. 16 proteins with ELISA or Luminex tests available were identified by literature review. Further evaluation via Luminex and ELISA and the second round of feature selection using FS-PLS revealed a six-protein signature: three of the included proteins are elevated in bacterial infections (SELE, NGAL, and IFN-γ), and three are elevated in viral infections (IL18, NCAM1, and LG3BP). Performance testing of the signature using Luminex assays revealed area under the receiver operating characteristic curve values between 89·4% and 93·6%. INTERPRETATION This study has led to the identification of a protein signature that could be ultimately developed into a blood-based point-of-care diagnostic test for rapidly diagnosing bacterial and viral infections in febrile children. Such a test has the potential to greatly improve care of children who are febrile, ensuring that the correct individuals receive antibiotics. FUNDING European Union's Horizon 2020 research and innovation programme, the European Union's Seventh Framework Programme (EUCLIDS), Imperial Biomedical Research Centre of the National Institute for Health Research, the Wellcome Trust and Medical Research Foundation, Instituto de Salud Carlos III, Consorcio Centro de Investigación Biomédica en Red de Enfermedades Respiratorias, Grupos de Refeencia Competitiva, Swiss State Secretariat for Education, Research and Innovation

Recurrence of iga nephropathy after kidney transplantation in adults

Background and objectives: In patients with kidney failure due to IgA nephropathy, IgA deposits can recur in a subsequent kidney transplant. The incidence, effect, and risk factors of IgA nephropathy recurrence is unclear, because most studies have been single center and sample sizes are relatively small. Design, setting, participants, & measurements: We performed a multicenter, international, retrospective study to determine the incidence, risk factors, and treatment response of recurrent IgA nephropathy after kidney transplantation. Data were collected from all consecutive patients with biopsy-proven IgA nephropathy transplanted between 2005 and 2015, across 16 “The Post-Transplant Glomerular Disease” study centers in Europe, North America, and South America. Results: Out of 504 transplant recipients with IgA nephropathy, recurrent IgA deposits were identified by kidney biopsy in 82 patients; cumulative incidence of recurrence was 23% at 15 years (95% confidence interval, 14 to 34). Multivariable Cox regression revealed a higher risk for recurrence of IgA deposits in patients with a pre-emptive kidney transplant (hazard ratio, 3.45; 95% confidence interval, 1.31 to 9.17) and in patients with preformed donorspecific antibodies (hazardratio, 2.59; 95%confidence interval, 1.09 to 6.19).Afterkidneytransplantation,development of de novo donor-specific antibodies was associated with subsequent higher risk of recurrence of IgA nephropathy (hazard ratio, 6.65; 95% confidence interval, 3.33 to 13.27). Immunosuppressive regimen was not associated with recurrent IgA nephropathy in multivariable analysis, including steroid use. Graft loss was higher in patients with recurrence of IgA nephropathy compared with patients without (hazard ratio, 3.69; 95% confidence interval, 2.04 to 6.66), resulting in 32% (95% confidence interval, 50 to 82) graft loss at 8 years after diagnosis of recurrence. Conclusions: In our international cohort, cumulative risk of IgA nephropathy recurrence increased after transplant and was associated with a 3.7-fold greater risk of graft loss

Mechanisms Establishing TLR4-Responsive Activation States of Inflammatory Response Genes

Precise control of the innate immune response is required for resistance to microbial infections and maintenance of normal tissue homeostasis. Because this response involves coordinate regulation of hundreds of genes, it provides a powerful biological system to elucidate the molecular strategies that underlie signal- and time-dependent transitions of gene expression. Comprehensive genome-wide analysis of the epigenetic and transcription status of the TLR4-induced transcriptional program in macrophages suggests that Toll-like receptor 4 (TLR4)-dependent activation of nearly all immediate/early- (I/E) and late-response genes results from a sequential process in which signal-independent factors initially establish basal levels of gene expression that are then amplified by signal-dependent transcription factors. Promoters of I/E genes are distinguished from those of late genes by encoding a distinct set of signal-dependent transcription factor elements, including TATA boxes, which lead to preferential binding of TBP and basal enrichment for RNA polymerase II immediately downstream of transcriptional start sites. Global nuclear run-on (GRO) sequencing and total RNA sequencing further indicates that TLR4 signaling markedly increases the overall rates of both transcriptional initiation and the efficiency of transcriptional elongation of nearly all I/E genes, while RNA splicing is largely unaffected. Collectively, these findings reveal broadly utilized mechanisms underlying temporally distinct patterns of TLR4-dependent gene activation required for homeostasis and effective immune responses

Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system

Challenges for Sustained Observing and Forecasting Systems in the Mediterranean Sea

The Mediterranean community represented in this paper is the result of more than 30 years of EU and nationally funded coordination, which has led to key contributions in science concepts and operational initiatives. Together with the establishment of operational services, the community has coordinated with universities, research centers, research infrastructures and private companies to implement advanced multi-platform and integrated observing and forecasting systems that facilitate the advancement of operational services, scientific achievements and mission-oriented innovation. Thus, the community can respond to societal challenges and stakeholders needs, developing a variety of fit-for-purpose services such as the Copernicus Marine Service. The combination of state-of-the-art observations and forecasting provides new opportunities for downstream services in response to the needs of the heavily populated Mediterranean coastal areas and to climate change. The challenge over the next decade is to sustain ocean observations within the research community, to monitor the variability at small scales, e.g., the mesoscale/submesoscale, to resolve the sub-basin/seasonal and inter-annual variability in the circulation, and thus establish the decadal variability, understand and correct the model-associated biases and to enhance model-data integration and ensemble forecasting for uncertainty estimation. Better knowledge and understanding of the level of Mediterranean variability will enable a subsequent evaluation of the impacts and mitigation of the effect of human activities and climate change on the biodiversity and the ecosystem, which will support environmental assessments and decisions. Further challenges include extending the science-based added-value products into societal relevant downstream services and engaging with communities to build initiatives that will contribute to the 2030 Agenda and more specifically to SDG14 and the UN's Decade of Ocean Science for sustainable development, by this contributing to bridge the science-policy gap. The Mediterranean observing and forecasting capacity was built on the basis of community best practices in monitoring and modeling, and can serve as a basis for the development of an integrated global ocean observing system

A terrestrial planet candidate in a temperate orbit around Proxima Centauri

At a distance of 1.295 parsecs, the red dwarf Proxima Centauri (α Centauri C, GL 551, HIP 70890 or simply Proxima) is the Sun’s closest stellar neighbour and one of the best-studied low-mass stars. It has an effective temperature of only around 3,050 kelvin, a luminosity of 0.15 per cent of that of the Sun, a measured radius of 14 per cent of the radius of the Sun and a mass of about 12 per cent of the mass of the Sun. Although Proxima is considered a moderately active star, its rotation period is about 83 days and its quiescent activity levels and X-ray luminosity are comparable to those of the Sun. Here we report observations that reveal the presence of a small planet with a minimum mass of about 1.3 Earth masses orbiting Proxima with a period of approximately 11.2 days at a semi-major-axis distance of around 0.05 astronomical units. Its equilibrium temperature is within the range where water could be liquid on its surface