Developing sero-diagnostic tests to facilitate Plasmodium vivax Serological Test-and-Treat approaches: modeling the balance between public health impact and overtreatment.

BACKGROUND: Eliminating Plasmodium vivax will require targeting the hidden liver-stage reservoir of hypnozoites. This necessitates new interventions balancing the benefit of reducing vivax transmission against the risk of over-treating some individuals with drugs which may induce haemolysis. By measuring antibodies to a panel of vivax antigens, a strategy of serological-testing-and-treatment (PvSeroTAT) can identify individuals with recent blood-stage infections who are likely to carry hypnozoites and target them for radical cure. This provides a potential solution to selectively treat the vivax reservoir with 8-aminoquinolines. METHODS: PvSeroTAT can identify likely hypnozoite carriers with ~80% sensitivity and specificity. Diagnostic test sensitivities and specificities ranging 50-100% were incorporated into a mathematical model of vivax transmission to explore how they affect the risks and benefits of different PvSeroTAT strategies involving hypnozoiticidal regimens. Risk was measured as the rate of overtreatment and benefit as reduction of community-level vivax transmission. RESULTS: Across a wide range of combinations of diagnostic sensitivity and specificity, PvSeroTAT was substantially more effective than bloodstage mass screen and treat strategies and only marginally less effective than mass drug administration. The key test characteristic determining of the benefit of PvSeroTAT strategies is diagnostic sensitivity, with higher values leading to more hypnozoite carriers effectively treated and greater reductions in vivax transmission. The key determinant of risk is diagnostic specificity: higher specificity ensures that a lower proportion of uninfected individuals are unnecessarily treated with primaquine. These relationships are maintained in both moderate and low transmission settings (qPCR prevalence 10% and 2%). Increased treatment efficacy and adherence can partially compensate for lower test performance. Multiple rounds of PvSeroTAT with a lower performing test may lead to similar or higher reductions in vivax transmission than fewer rounds with a higher performing test, albeit with higher rate of overtreatment. CONCLUSIONS: At current performance, PvSeroTAT is predicted to be a safe and efficacious option for targeting the hypnozoite reservoir towards vivax elimination. P. vivax sero-diagnostic tests should aim for both high performance and ease of use in the field. The target product profiles informing such development should thus reflect the trade-offs between impact, overtreatment, and ease of programmatic implementation

The optimal treatment strategy for secondary mitral regurgitation: a subject of ongoing debate

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Zika vector competence data reveals risks of outbreaks: the contribution of the European ZIKAlliance project

First identified in 1947, Zika virus took roughly 70 years to cause a pandemic unusually associated with virus-induced brain damage in newborns. Zika virus is transmitted by mosquitoes, mainly Aedes aegypti, and secondarily, Aedes albopictus, both colonizing a large strip encompassing tropical and temperate regions. As part of the international project ZIKAlliance initiated in 2016, 50 mosquito populations from six species collected in 12 countries were experimentally infected with different Zika viruses. Here, we show that Ae. aegypti is mainly responsible for Zika virus transmission having the highest susceptibility to viral infections. Other species play a secondary role in transmission while Culex mosquitoes are largely non-susceptible. Zika strain is expected to significantly modulate transmission efficiency with African strains being more likely to cause an outbreak. As the distribution of Ae. aegypti will doubtless expand with climate change and without new marketed vaccines, all the ingredients are in place to relive a new pandemic of Zika.info:eu-repo/semantics/publishedVersio

Zika vector competence data reveals risks of outbreaks: the contribution of the European ZIKAlliance project

First identified in 1947, Zika virus took roughly 70 years to cause a pandemic unusually associated with virus-induced brain damage in newborns. Zika virus is transmitted by mosquitoes, mainly Aedes aegypti, and secondarily, Aedes albopictus, both colonizing a large strip encompassing tropical and temperate regions. As part of the international project ZIKAlliance initiated in 2016, 50 mosquito populations from six species collected in 12 countries were experimentally infected with different Zika viruses. Here, we show that Ae. aegypti is mainly responsible for Zika virus transmission having the highest susceptibility to viral infections. Other species play a secondary role in transmission while Culex mosquitoes are largely non-susceptible. Zika strain is expected to significantly modulate transmission efficiency with African strains being more likely to cause an outbreak. As the distribution of Ae. aegypti will doubtless expand with climate change and without new marketed vaccines, all the ingredients are in place to relive a new pandemic of Zika

ECMO for COVID-19 patients in Europe and Israel

Since March 15th, 2020, 177 centres from Europe and Israel have joined the study, routinely reporting on the ECMO support they provide to COVID-19 patients. The mean annual number of cases treated with ECMO in the participating centres before the pandemic (2019) was 55. The number of COVID-19 patients has increased rapidly each week reaching 1531 treated patients as of September 14th. The greatest number of cases has been reported from France (n = 385), UK (n = 193), Germany (n = 176), Spain (n = 166), and Italy (n = 136) .The mean age of treated patients was 52.6 years (range 16–80), 79% were male. The ECMO configuration used was VV in 91% of cases, VA in 5% and other in 4%. The mean PaO2 before ECMO implantation was 65 mmHg. The mean duration of ECMO support thus far has been 18 days and the mean ICU length of stay of these patients was 33 days. As of the 14th September, overall 841 patients have been weaned from ECMO support, 601 died during ECMO support, 71 died after withdrawal of ECMO, 79 are still receiving ECMO support and for 10 patients status n.a. . Our preliminary data suggest that patients placed on ECMO with severe refractory respiratory or cardiac failure secondary to COVID-19 have a reasonable (55%) chance of survival. Further extensive data analysis is expected to provide invaluable information on the demographics, severity of illness, indications and different ECMO management strategies in these patients

LES DISSECTIONS ARTERIELLES MULTIPLES CERVICO-ENCEPHALIQUES (ETUDE DE 18 CAS)

PARIS6-Bibl.Pitié-Salpêtrie (751132101) / SudocPARIS-BIUM (751062103) / SudocSudocFranceF

Applying Machine Learning and Time-Series Analysis on Sentinel-1A SAR/InSAR for Characterizing Arctic Tundra Hydro-Ecological Conditions

Synthetic aperture radar (SAR) is a widely used tool for Earth observation activities. It is particularly effective during times of persistent cloud cover, low light conditions, or where in situ measurements are challenging. The intensity measured by a polarimetric SAR has proven effective for characterizing Arctic tundra landscapes due to the unique backscattering signatures associated with different cover types. However, recently, there has been increased interest in exploiting novel interferometric SAR (InSAR) techniques that rely on both the amplitude and absolute phase of a pair of acquisitions to produce coherence measurements, although the simultaneous use of both intensity and interferometric coherence in Arctic tundra image classification has not been widely tested. In this study, a time series of dual-polarimetric (VV, VH) Sentinel-1 SAR/InSAR data collected over one growing season, in addition to a digital elevation model (DEM), was used to characterize an Arctic tundra study site spanning a hydrologically dynamic coastal delta, open tundra, and high topographic relief from mountainous terrain. SAR intensity and coherence patterns based on repeat-pass interferometry were analyzed in terms of ecological structure (i.e., graminoid, or woody) and hydrology (i.e., wet, or dry) using machine learning methods. Six hydro-ecological cover types were delineated using time-series statistical descriptors (i.e., mean, standard deviation, etc.) as model inputs. Model evaluations indicated SAR intensity to have better predictive power than coherence, especially for wet landcover classes due to temporal decorrelation. However, accuracies improved when both intensity and coherence were used, highlighting the complementarity of these two measures. Combining time-series SAR/InSAR data with terrain derivatives resulted in the highest per-class F1 score values, ranging from 0.682 to 0.955. The developed methodology is independent of atmospheric conditions (i.e., cloud cover or sunlight) as it does not rely on optical information, and thus can be regularly updated over forthcoming seasons or annually to support ecosystem monitoring