Pituitary Adenylate Cyclase-Activating Polypeptide (PACAP) Signaling in The Prefrontal Cortex Modulates Cued Fear Learning, But Not Spatial Working Memory, in Female Rats

A genetic polymorphism within the gene encoding the pituitary adenylate cyclase- activating polypeptide (PACAP) receptor type I (PAC1R) has recently been associated with hyper-reactivity to threat-related cues in women, but not men, with post-traumatic stress disorder (PTSD). PACAP is a highly conserved peptide, whose role in mediating adaptive physiological stress responses is well established. Far less is understood about the contribution of PACAP signaling in emotional learning and memory, particularly the encoding of fear to discrete cues. Moreover, a neurobiological substrate that may account for the observed link between PAC1R and PTSD in women, but not men, has yet to be identified. Sex differences in PACAP signaling during emotional learning could provide novel targets for the treatment of PTSD. Here we investigated the contribution of PAC1R signaling within the prefrontal cortex to the acquisition of cued fear in female and male rats. We used a variant of fear conditioning called trace fear conditioning, which requires sustained attention to fear cues and depends on working-memory like neuronal activity within the prefrontal cortex. We found that cued fear learning, but not spatial working memory, was impaired by administration of a PAC1R antagonist directly into the prelimbic area of the prefrontal cortex. This effect was specific to females. We also found that levels of mRNA for the PAC1R receptor in the prelimbic cortex were greater in females compared with males, and were highest during and immediately following the proestrus stage of the estrous cycle. Together, these results demonstrate a sex-specific role of PAC1R signaling in learning about threat-related cues

Towards Reliable Concurrent Software

As the use of concurrent software is increasing, we urgently need techniques to establish the correctness of such applications. Over the last years, significant progress has been made in the area of software verification, making verification techniques usable for realistic applications. However, much of this work concentrates on sequential software, and a next step is necessary to apply these results also on realistic concurrent software. In this paper, we outline a research agenda to realise this goal. We argue that current techniques for verification of concurrent software need to be further developed in multiple directions: extending the class of properties that can be established, improving the level of automation that is available for this kind of verification, and enlarging the class of concurrent programs that can be verified

Early Warning Signals Based on Momentary Affect Dynamics can Expose Nearby Transitions in Depression:A Confirmatory Single-Subject Time-Series Study

Background: In complex systems early warning signals such as rising autocorrelation, variance and network connectivity are hypothesized to anticipate relevant shifts in a system. For direct evidence hereof in depression, designs are needed in which early warning signals and symptom transitions are prospectively assessed within an individual. Therefore, this study aimed to detect personalized early warning signals preceding the occurrence of a major symptom transition. Methods: Six single-subject time-series studies were conducted, collecting frequent observations of momentary affective states during a time-period when participants were at increased risk of a symptom transition. Momentary affect states were reported three times a day over three to six months (95-183 days). Depressive symptoms were measured weekly using the Symptom CheckList-90. Presence of sudden symptom transitions was assessed using change point analysis. Early warning signals were analysed using moving window techniques. Results: As change point analysis revealed a significant and sudden symptom transition in one participant in the studied period, early warning signals were examined in this person. Autocorrelation (r=0·51; p<2.2e-16), and variance (r=0·53; p<2.2e-16) in 'feeling down', and network connectivity (r=0·42; p<2.2e-16) significantly increased a month before this transition occurred. These early warnings also preceded the rise in absolute levels of 'feeling down' and the participant's personal indication of risk for transition. Conclusions: This study replicated the findings of a previous study and confirmed the presence of rising early warning signals a month before the symptom transition occurred. Results show the potential of early warning signals to improve personalized risk assessment in the field of psychiatry

Early warning signals and critical transitions in psychopathology:challenges and recommendations

Empirical evidence is mounting that monitoring momentary experiences for the presence of early warning signals (EWS) may allow for personalized predictions of meaningful symptom shifts in psychopathology. Studies aiming to detect EWS require intensive longitudinal measurement designs that center on individuals undergoing change. We recommend that researchers: (a) define criteria for relevant symptom shifts a priori to allow specific hypothesis testing; (b) balance the observation period length and high-frequency measurements with participant burden by testing ambitious designs with pilot studies; (c) choose variables that are meaningful to their patient group and facilitate replication by others. Thoroughly considered designs are necessary to assess the promise of EWS as a clinical tool to detect, prevent or encourage impending symptom changes in psychopathology

Prelimbic Input to Basolateral Amygdala Facilitates the Acquisition of Trace Cued Fear Memory Under Weak Training Conditions

The ability to predict the occurrence of an aversive outcome based on available cues requires associative learning and plastic changes in the amygdala. When the predictive cue and aversive shock outcome are separated in time as in trace fear conditioning, additional circuitry is needed, including the prelimbic (PL) area of the prefrontal cortex. We have previously shown that neuronal firing in the PL during the trace interval separating the cue and shock is required for trace cued fear memory formation, but whether this mnemonic signal is conveyed to the amygdala is unknown. Here we show in males that silencing PL activity during the trace interval reduces Arc protein in the basolateral amygdala (BLA) of trace-conditioned rats. Then, using pathway-specific optogenetic and chemogenetic silencing, we show a role for direct PL-BLA communication in trace cued fear learning under weak training conditions, but not standard training. These results suggest that PL input to the BLA may serve to promote cued learning when the cue-shock relationship is most ambiguous and that other trace fear circuitry can compensate for the loss of this connection with additional training. This also highlights the challenge to studying how emotional memories are formed and stored within a distributed network and suggests that the function of individual connections within such a network may best be determined using weak training conditions

Anticipating Transitions in Mental Health in At-Risk Youths:A 6-Month Daily Diary Study Into Early-Warning Signals

If psychopathology behaves like a complex dynamic system, sudden onset or worsening of symptoms may be preceded by early-warning signals (EWSs). EWSs could thus reflect personalized warning signals for impending psychopathology. We empirically investigated this hypothesis in at-risk youths (N = 122, mean age = 23.6 ± 0.7 years, 57% males) from the clinical cohort of Tracking Adolescents’ Individual Lives Survey (TRAILS-CC), who provided daily emotion assessments for 6 months. We analyzed whether EWSs (rising autocorrelations and standard deviations in emotions) preceded transitions toward psychopathology. Across indicators and a range of analytical options, EWSs had low sensitivity (M = 26%, SD = 11%) and moderate specificity (M = 75%, SD = 14%). Thus, in the present sample, the proposed generic nature and clinical utility of EWSs could not be substantiated. Given this finding, we call for a more nuanced view on the application of complex-dynamic-systems principles to psychopathology and lay out key questions to be addressed in the future

Patients’ views on the implementation of artificial intelligence in radiology:Development and validation of a standardized questionnaire

Objectives The patients’ view on the implementation of artificial intelligence (AI) in radiology is still mainly unexplored territory. The aim of this article is to develop and validate a standardized patient questionnaire on the implementation of AI in radiology. Methods Six domains derived from a previous qualitative study were used to develop a questionnaire, and cognitive interviews were used as pretest method. One hundred fifty-five patients scheduled for CT, MRI, and/or conventional radiography filled out the questionnaire. To find underlying latent variables, we used exploratory factor analysis with principal axis factoring and oblique promax rotation. Internal consistency of the factors was measured with Cronbach’s alpha and composite reliability. Results The exploratory factor analysis revealed five factors on AI in radiology: (1) distrust and accountability (overall, patients were moderately negative on this subject), (2) procedural knowledge (patients generally indicated the need for their active engagement), (3) personal interaction (overall, patients preferred personal interaction), (4) efficiency (overall, patients were ambiguous on this subject), and (5) being informed (overall, scores on these items were not outspoken within this factor). Internal consistency was good for three factors (1, 2, and 3), and acceptable for two (4 and 5). Conclusions This study yielded a viable questionnaire to measure acceptance among patients of the implementation of AI in radiology. Additional data collection with confirmatory factor analysis may provide further refinement of the scale. Key Points • Although AI systems are increasingly developed, not much is known about patients’ views on AI in radiology. • Since it is important that newly developed questionnaires are adequately tested and validated, we did so for a questionnaire measuring patients’ views on AI in radiology, revealing five factors. • Successful implementation of AI in radiology requires assessment of social factors such as subjective norms towards the technology

The relationship between quality of life and coping strategies of children with EB and their parents

BackgroundEpidermolysis bullosa (EB) is a group of rare genetic skin disorders that primarily manifest as blisters and erosions following mild mechanical trauma. Despite the crucial role of the parents of children with EB in managing the disease, studies focusing on the parent-child relationship remain a gap in the literature. To address this gap, the current quantitative study, involving 55 children with all types of EB and 48 parents, assessed the relationship between their quality of life and coping strategies. Quality of life was measured with the Pediatric Quality of Life Inventory and TNO-AZL Questionnaire for Adult's Health- related Quality of Life, and coping strategies were assessed with the Coping with a Disease Questionnaire. The majority of the analyses were descriptive and the results were interpreted qualitatively because of the small sample size.ResultsOverall, the quality of life of children with EB and that of their parents was somewhat lower compared with the quality of life of healthy children and adults. Children with EB who more frequently used emotional reactions and cognitive-palliative strategies to cope with the disease demonstrated lower levels of emotional and social functioning, while children who showed more acceptance and distancing showed higher levels of functioning on all domains. Parents who frequently demonstrated emotional reactions reported lower levels of social functioning and experienced more depressive emotions and anger. Parents who used more avoidance showed higher levels of positive emotions. Within parent-child dyads, acceptance, cognitive-palliative strategies and distancing were positively related. Children's emotional and social functioning were negatively associated with their parents' depressive emotions. Parents' acceptance was linked to higher physical functioning in children, whereas children's avoidance was linked to a lower level of anger in parents.ConclusionChildren who are able to accept the disease or distance themselves from it appear to be better off in contrast to those who tend to engage in the cognitive-palliative strategies and expressing emotional reactions. Parents seem to be better off when they are able to use avoidance in contrast to those who tend to show emotional reactions. Further research is needed to substantiate these findings

Patients' and parents' experiences during wound care of epidermolysis bullosa from a dyadic perspective:a survey study

Background Epidermolysis bullosa is a rare, often severe, genetic disorder characterized by fragility of the skin and mucous membranes. Despite the important role of parents during wound care, an essential factor in adapting to this disease, studies focusing on the parent-child relationship during wound care are scarce. The current study is aimed at addressing this gap. Methods A quantitative study among 31 children (n = 2

Do People Favor Artificial Intelligence Over Physicians? A Survey Among the General Population and Their View on Artificial Intelligence in Medicine

Objectives: To investigate the general population's view on artificial intelligence (AI) in medicine with specific emphasis on 3 areas that have experienced major progress in AI research in the past few years, namely radiology, robotic surgery, and dermatology. Methods: For this prospective study, the April 2020 Online Longitudinal Internet Studies for the Social Sciences Panel Wave was used. Of the 3117 Longitudinal Internet Studies For The Social Sciences panel members contacted, 2411 completed the full questionnaire (77.4% response rate), after combining data from earlier waves, the final sample size was 1909. A total of 3 scales focusing on trust in the implementation of AI in radiology, robotic surgery, and dermatology were used. Repeated-measures analysis of variance and multivariate analysis of variance was used for comparison. Results: The overall means show that respondents have slightly more trust in AI in dermatology than in radiology and surgery. The means show that higher educated males, employed or student, of Western background, and those not admitted to a hospital in the past 12 months have more trust in AI. The trust in AI in radiology, robotic surgery, and dermatology is positively associated with belief in the efficiency of AI and these specific domains were negatively associated with distrust and accountability in AI in general. Conclusions: The general population is more distrustful of AI in medicine unlike the overall optimistic views posed in the media. The level of trust is dependent on what medical area is subject to scrutiny. Certain demographic characteristics and individuals with a generally positive view on AI and its efficiency are significantly associated with higher levels of trust in AI