Maternal morbidity and mortality continue to rise, and pre-eclampsia is a major driver of this burden1. Yet the ability to assess underlying pathophysiology before clinical presentation to enable identification of pregnancies at risk remains elusive. Here we demonstrate the ability of plasma cell-free RNA (cfRNA) to reveal patterns of normal pregnancy progression and determine the risk of developing pre-eclampsia months before clinical presentation. Our results centre on comprehensive transcriptome data from eight independent prospectively collected cohorts comprising 1,840 racially diverse pregnancies and retrospective analysis of 2,539 banked plasma samples. The pre-eclampsia data include 524 samples (72 cases and 452 non-cases) from two diverse independent cohorts collected 14.5 weeks (s.d., 4.5 weeks) before delivery. We show that cfRNA signatures from a single blood draw can track pregnancy progression at the placental, maternal and fetal levels and can robustly predict pre-eclampsia, with a sensitivity of 75% and a positive predictive value of 32.3% (s.d., 3%), which is superior to the state-of-the-art method2. cfRNA signatures of normal pregnancy progression and pre-eclampsia are independent of clinical factors, such as maternal age, body mass index and race, which cumulatively account for less than 1% of model variance. Further, the cfRNA signature for pre-eclampsia contains gene features linked to biological processes implicated in the underlying pathophysiology of pre-eclampsia.
SummaryOne of the key research areas surrounding HIV-1 concerns the regulation of the fusion event that occurs between the virus particle and the host cell during entry. Even if it is universally accepted that the large GTPase dynamin-2 is important during HIV-1 entry, its exact role during the first steps of HIV-1 infection is not well characterized. Here, we have utilized a multidisciplinary approach to study the DNM2 role during fusion of HIV-1 in primary resting CD4 T and TZM-bl cells. We have combined advanced light microscopy and functional cell-based assays to experimentally assess the role of dynamin-2 during these processes. Overall, our data suggest that dynamin-2, as a tetramer, might help to establish hemi-fusion and stabilizes the pore during HIV-1 fusion.
This paper applies genetic algorithms to the problem of induction motor parameter determination. Generally available manufacturers published data like starting torque, breakdown torque, full load torque, full load power factor etc, are used to determine the motor parameters for subsequent use in studying machine transients. Results from several versions of the genetic algorithm are presented as well as a comparison with the Newton-Raphson method.
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