Preeclampsia affects up to 8% of pregnancies worldwide and is a leading cause of both maternal and fetal morbidity and mortality. Our current understanding of the cause(s) of preeclampsia is far from complete, and the lack of a single reliable animal model that recapitulates all aspects of the disease further confounds our understanding. This is partially due to the heterogeneous nature of the disease, coupled with our evolving understanding of its etiology. Nevertheless, animal models are still highly relevant and useful tools that help us better understand the pathophysiology of specific aspects of preeclampsia. This review summarizes the various types and characteristics of animal models used to study preeclampsia, highlighting particular features of these models relevant to clinical translation. This review points out the strengths and limitations of these models to illustrate the importance of using the appropriate model depending on the research question.

Aim Phenomena within the psychosis continuum that varies in frequency/duration/intensity have been increasingly identified. Different terms describe these phenomena, however there is no standardization within the terminology. This review evaluated the definitions and assessment tools of seven terms – (i) ‘psychotic experiences’; (ii) ‘psychotic‐like experiences’; (iii) ‘psychotic‐like symptoms’; (iv) ‘attenuated psychotic symptoms’; (v) ‘prodromal psychotic symptoms’; (vi) ‘psychotic symptomatology’; and (vii) ‘psychotic symptoms’. Methods EMBASE, MEDLINE, and CINAHL were searched during February–March 2019. Inclusion criteria included 1989–2019, full text, human, and English. Papers with no explicit definition or assessment tool, duplicates, conference abstracts, systematic reviews, meta‐analyses, or no access were excluded. Results A total of 2238 papers were identified and of these, 627 were included. Definitions and assessment tools varied, but some trends were found. Psychotic experiences and psychotic‐like experiences were transient and mild, found in the general population and those at‐risk. Psychotic‐like symptoms were subthreshold and among at‐risk populations and non‐psychotic mental disorders. Attenuated psychotic symptoms were subthreshold but associated with distress, risk, and help‐seeking. Prodromal psychotic symptoms referred to the prodrome of psychotic disorders. Psychotic symptomatology included delusions and hallucinations within psychotic disorders. Psychotic symptoms was the broadest term, encompassing a range of populations but most commonly involving hallucinations, delusions, thought disorder, and disorganization. Discussion A model for conceptualizing the required terms is proposed and future directions needed to advance this field of research are discussed.

Background Preeclampsia (PE) is a leading cause of maternal and perinatal morbidity and mortality worldwide. Although predictive multiparametric screening is being developed, it is not applicable to nulliparous women, and is not applied to low-risk women. As PE is considered a heterogenous disorder, it is unlikely that any single multiparametric screening protocol containing a small group of biomarkers could have the required accuracy to predict all PE subgroups. Given the etiology of PE is complex and not fully understood, it begs the question, whether the search for biomarkers based on the predominant view of impaired placentation involving factors predominately implicated in angiogenesis and inflammation, has been too limiting. Here we highlight the enormous potential of state-of-the-art, high-throughput proteomics, to provide a comprehensive and unbiased approach to biomarker identification. Methods and findings Our literature search identified 1336 articles; after review, 45 studies with proteomic data from PE women that were eligible for inclusion. From 710 proteins with altered abundance, we identified 13 common circulating proteins, some of which had not been previously considered as prospective biomarkers of PE. An additional search of the literature for original publications testing any of the 13 common proteins using non-proteomic techniques was also undertaken. Strikingly, 9 of these common proteins had been independently evaluated in PE studies as potential biomarkers. Conclusion This study highlights the potential of using high-throughput data sets, which are comprehensive and without bias, to identify a profile of proteins that may improve predictions of PE and understanding of its etiology. We bring to the attention of the medical and research communities that the strengths and advantages of using data from high-throughput studies for biomarker discovery would be increased dramatically, if first and second trimester samples were collected for proteomics, and if standardized guidelines for patient reporting and data collection were implemented.

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