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Fear is an adaptive response in the presence of danger. However, when threat is uncertain and continuous, as in the current coronavirus (COVID-19) pandemic, fear can become chronic and burdensome. To better understand predictors of fear of the coronavirus, we conducted an online survey (N = 439) between March 14 and 17, 2020, which started three days after the World Health Organization declared the coronavirus outbreak a pandemic. Fear of the coronavirus was assessed with eight questions pertaining to different dimensions of fear (e.g., subjective worry, avoidance, preferential attention) and an open-ended question. The predictors included measures of psychological vulnerability factors (i.e., intolerance of uncertainty, worry, health anxiety), media exposure, and personal relevance (i.e., personal health, risk for loved ones, and risk control). We found that respondents reported a wide range of concerns relating to the coronavirus outbreak, such as the health of their loved ones, collapse of health care systems, and economic consequences. Four predictors for fear of the coronavirus were retained after backward selection in a simultaneous regression analysis: health anxiety, intolerance of uncertainty, media use, and risks for loved ones (R2 = .37). We discuss the relevance of our findings for managing people’s fear of the coronavirus.

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Leading biological hypotheses propose that biological changes may underlie major depressive disorder onset and relapse/recurrence. Here, we investigate if there is prospective evidence for biomarkers derived from leading theories. We focus on neuroimaging, gastrointestinal factors, immunology, neurotrophic factors, neurotransmitters, hormones, and oxidative stress. Searches were performed in Pubmed, Embase and PsychInfo for articles published up to 06/2019. References and citations of included articles were screened to identify additional articles. Inclusion criteria were having an MDD diagnosis as outcome, a biomarker as predictor, and prospective design search terms were formulated accordingly. PRISMA guidelines were applied. Meta-analyses were performed using a random effect model when three or more comparable studies were identified, using a random effect model. Our search resulted in 67,464 articles, of which 75 prospective articles were identified on: Neuroimaging (N = 24), Gastrointestinal factors (N = 1), Immunology (N = 8), Neurotrophic (N = 2), Neurotransmitters (N = 1), Hormones (N = 39), Oxidative stress (N = 1). Meta-analyses on brain volumes and immunology markers were not significant. Only cortisol (N = 19, OR = 1.294, p = 0.024) showed a predictive effect on onset/relapse/recurrence of MDD, but not on time until MDD onset/relapse/recurrence. However, this effect disappeared when studies including participants with a baseline clinical diagnosis were removed from the analyses. Other studies were too heterogeneous to compare. Thus, there is a lack of evidence for leading biological theories for onset and maintenance of depression. Only cortisol was identified as potential predictor for MDD, but results are influenced by the disease state. High-quality (prospective) studies on MDD are needed to disentangle the etiology and maintenance of MDD.

Background An international Delphi panel has defined a harmonized protocol (HarP) for the manual segmentation of the hippocampus on MR. The aim of this study is to study the concurrent validity of the HarP toward local protocols, and its major sources of variance. Methods Fourteen tracers segmented 10 Alzheimer's Disease Neuroimaging Initiative (ADNI) cases scanned at 1.5 T and 3T following local protocols, qualified for segmentation based on the HarP through a standard web-platform and resegmented following the HarP. The five most accurate tracers followed the HarP to segment 15 ADNI cases acquired at three time points on both 1.5 T and 3T. Results The agreement among tracers was relatively low with the local protocols (absolute left/right ICC 0.44/0.43) and much higher with the HarP (absolute left/right ICC 0.88/0.89). On the larger set of 15 cases, the HarP agreement within (left/right ICC range: 0.94/0.95 to 0.99/0.99) and among tracers (left/right ICC range: 0.89/0.90) was very high. The volume variance due to different tracers was 0.9% of the total, comparing favorably to variance due to scanner manufacturer (1.2), atrophy rates (3.5), hemispheric asymmetry (3.7), field strength (4.4), and significantly smaller than the variance due to atrophy (33.5%, P < .001), and physiological variability (49.2%, P < .001). Conclusions The HarP has high measurement stability compared with local segmentation protocols, and good reproducibility within and among human tracers. Hippocampi segmented with the HarP can be used as a reference for the qualification of human tracers and automated segmentation algorithms.

Background This study aimed to have international experts converge on a harmonized definition of whole hippocampus boundaries and segmentation procedures, to define standard operating procedures for magnetic resonance (MR)-based manual hippocampal segmentation. Methods The panel received a questionnaire regarding whole hippocampus boundaries and segmentation procedures. Quantitative information was supplied to allow evidence-based answers. A recursive and anonymous Delphi procedure was used to achieve convergence. Significance of agreement among panelists was assessed by exact probability on Fisher’s and binomial tests. Results Agreement was significant on the inclusion of alveus/fimbria (P =.021), whole hippocampal tail (P =.013), medial border of the body according to visible morphology (P =.0006), and on this combined set of features (P =.001). This definition captures 100% of hippocampal tissue, 100% of Alzheimer’s disease-related atrophy, and demonstrated good reliability on preliminary intrarater (0.98) and inter-rater (0.94) estimates. Discussion Consensus was achieved among international experts with respect to hippocampal segmentation using MR resulting in a harmonized segmentation protocol.

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