Europe as a secondary distribution hub in the worldwide invasion of the potato cyst nematode Globodera rostochiensis.

The potato cyst nematode Globodera rostochiensis originates from the Andean Mountain region in South America and has unintentionally been introduced to all inhabited continents. Several studies have examined the population genetic structure of this pest in various countries by using microsatellite markers. However, merging microsatellite data produced from different laboratories is challenging and can introduce uncertainty when interpreting the results. To overcome this challenge and to explore invasion routes of this pest, we have genotyped 22 G. rostochiensis populations from all continents. Within populations, the highest genetic diversity was observed in the South American populations, the European populations showed an intermediate level of genetic diversity and the remaining populations were the less diverse. This confirmed pre-existing knowledge such as a first introduction event from South America to Europe, but the less diverse populations could originate either from South America or from Europe. At the continental scale, STRUCTURE genetic clustering output indicated that North America and Asia have experienced at least two introduction events. Comparing different evolutionary scenarios, the Approximate Bayesian Computation analysis showed that Europe served as a secondary distribution centre for the invasion of G. rostochiensis into all other continents (North America, Africa, Asia and Oceania).

Trajectories of Host-Response Subphenotypes in Patients With COVID-19 Across the Spectrum of Respiratory Support.

BACKGROUND: Hospitalized patients with severe COVID-19 follow heterogeneous clinical trajectories, requiring different levels of respiratory support and experiencing diverse clinical outcomes. Differences in host immune responses to SARS-CoV-2 infection may account for the heterogeneous clinical course, but we have limited data on the dynamic evolution of systemic biomarkers and related subphenotypes. Improved understanding of the dynamic transitions of host subphenotypes in COVID-19 may allow for improved patient selection for targeted therapies. RESEARCH QUESTION: We examined the trajectories of host-response profiles in severe COVID-19 and evaluated their prognostic impact on clinical outcomes. STUDY DESIGN AND METHODS: In this prospective observational study, we enrolled 323 inpatients with COVID-19 receiving different levels of baseline respiratory support: (1) low-flow oxygen (37%), (2) noninvasive ventilation (NIV) or high-flow oxygen (HFO; 29%), (3) invasive mechanical ventilation (27%), and (4) extracorporeal membrane oxygenation (7%). We collected plasma samples on enrollment and at days 5 and 10 to measure host-response biomarkers. We classified patients by inflammatory subphenotypes using two validated predictive models. We examined clinical, biomarker, and subphenotype trajectories and outcomes during hospitalization. RESULTS: IL-6, procalcitonin, and angiopoietin 2 persistently were elevated in patients receiving higher levels of respiratory support, whereas soluble receptor of advanced glycation end products (sRAGE) levels displayed the inverse pattern. Patients receiving NIV or HFO at baseline showed the most dynamic clinical trajectory, with 24% eventually requiring intubation and exhibiting worse 60-day mortality than patients receiving invasive mechanical ventilation at baseline (67% vs 35%; P < .0001). sRAGE levels predicted NIV failure and worse 60-day mortality for patients receiving NIV or HFO, whereas IL-6 levels were predictive in all patients regardless of level of support (P < .01). Patients classified to a hyperinflammatory subphenotype at baseline (< 10%) showed worse 60-day survival (P < .0001) and 50% of them remained classified as hyperinflammatory at 5 days after enrollment. INTERPRETATION: Longitudinal study of the systemic host response in COVID-19 revealed substantial and predictive interindividual variability influenced by baseline levels of respiratory support.

The Correlation Between Gross Domestic Product Per Capita and the Success Rate of Assisted Reproductive Technologies Worldwide.

OBJECTIVE: Although there has been increased utilization of assisted reproductive technologies (ART) in the world, there is no conclusive definition about the relationship between the success rate of ART and national wealth. METHODS: In this study, using the data from the International Committee for Monitoring Assisted Reproductive Technologies (ICMART), we sought to determine whether there is a correlation between the success rate of ART (represented by pregnancy and delivery rates) and national wealth represented by the gross domestic product (GDP) per capita. Moreover, to further understand the effect of GDP per capita on ART effectiveness, we analyzed the association between ART success rate and GDP per capita in 50 US states. RESULTS: Our data showed that the number of ART treatment cycles increased as the GDP per capita increased. However, we found a negative correlation between ART success rates and GDP per capita in ICMART countries, although no correlation was seen in the US states. Using rough estimation, we derived that the success rate of ART was not related to GDP per capita in the ICMART countries with a GDP per capita greater than USD 13,000. CONCLUSIONS: In conclusion, for the first time, we showed that when the GDP per capita of an economic territory reaches (or exceeds) USD 13,000, ART pregnancy and delivery rates were not associated with GDP per capita, and ART success rates remained stable.

Adaptive vaccination strategies to mitigate pandemic influenza: Mexico as a case study.

BACKGROUND: We explore vaccination strategies against pandemic influenza in Mexico using an age-structured transmission model calibrated against local epidemiological data from the Spring 2009 A(H1N1) pandemic. METHODS AND FINDINGS: In the context of limited vaccine supplies, we evaluate age-targeted allocation strategies that either prioritize youngest children and persons over 65 years of age, as for seasonal influenza, or adaptively prioritize age groups based on the age patterns of hospitalization and death monitored in real-time during the early stages of the pandemic. Overall the adaptive vaccination strategy outperformed the seasonal influenza vaccination allocation strategy for a wide range of disease and vaccine coverage parameters. CONCLUSIONS: This modeling approach could inform policies for Mexico and other countries with similar demographic features and vaccine resources issues, with regard to the mitigation of the S-OIV pandemic. We also discuss logistical issues associated with the implementation of adaptive vaccination strategies in the context of past and future influenza pandemics.

Adaptive vaccination strategies to mitigate pandemic influenza: Mexico as a case study.

In this modeling work, we explore the effectiveness of various age-targeted vaccination strategies to mitigate hospitalization and mortality from pandemic influenza, assuming limited vaccine supplies. We propose a novel adaptive vaccination strategy in which vaccination is initiated during the outbreak and priority groups are identified based on real-time epidemiological data monitoring age-specific risk of hospitalization and death. We apply this strategy to detailed epidemiological and demographic data collected during the recent swine A/H1N1 outbreak in Mexico. We show that the adaptive strategy targeting age groups 6-59 years is the most effective in reducing hospitalizations and deaths, as compared with a more traditional strategy used in the control of seasonal influenza and targeting children under 5 and seniors over 65. Results are robust to a number of assumptions and could provide guidance to many nations facing a recrudescence of A/H1N1v pandemic activity in the fall and likely vaccine shortages.