Detection of active SARS-CoV-2 in cough aerosols from COVID-19 patients.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is an airborne pathogen, but detection of infectious SARS-CoV-2 in air and in particular the introduction of the virus into the environment by different human expiratory manoeuvres is not well studied. OBJECTIVES: The aim of this study was to investigate the presence of SARS-CoV-2 in cough from coronavirus disease of 2019 (COVID-19) in-patients and to study contamination of the virus in the patient's environment. METHODS: Detection of SARS-CoV-2 in cough was analyzed by PCR, culture and imaging. Detection in cough was compared to presence of the virus in air and on surfaces from patient rooms. RESULTS: Twenty-five patients in 21 rooms were included in the study. SARS-CoV-2 RNA was found in cough aerosols from 16 out of 22 patients that produced voluntary cough. As demonstrated by plaque-forming unit assays, active virus was isolated from 11 of these 16 patients. Using mainly molecular detection, the virus was also found in air, on high-contact surfaces, and no-touch surfaces from the room of the COVID-19 patients. CONCLUSIONS: These results show that infectious SARS-CoV-2 circulating in air can originate from patient cough and should be considered against the risk of acquiring COVID-19 through inhalation.

Self-Sampling by Adolescents at Home: Assessment of the Feasibility to Successfully Collect Blood Microsamples by Inexperienced Individuals.

Blood microsampling has increasingly attracted interest in the past decades as a more patient-centric sampling approach, offering the possibility to collect a minimal volume of blood following a finger or arm prick at home. In addition to conventional dried blood spots (DBS), many different devices allowing self-sampling of blood have become available. Obviously, the success of home-sampling can only be assured when (inexperienced) users collect samples of good quality. Therefore, the feasibility of six different microsampling devices to collect capillary blood by inexperienced adolescents at home was evaluated. Participants (n = 95) were randomly assigned to collect blood (dried or liquid) at different time points using four of six different self-sampling devices (i.e., DBS, Mitra volumetric absorptive microsampling (VAMS), Capitainer B, Tasso M20, Minicollect tube and Tasso+ serum separator tube (SST)). The quality of the samples was visually inspected and analytically determined. Moreover, the participants' satisfaction was assessed via questionnaires. Although a majority succeeded based on the visual inspection, the success rate differed largely between the different devices. In general, the lowest success rate was obtained for the Minicollect tubes, although there is an opportunity and need for improvement for the other self-sampling devices as well. Hence, this also emphasizes the importance to assess the quality of samples collected by the target population prior to study initiation. In addition, visual classification by a trained individual was confirmed based on assessment of the analytical variability between replicates. Finally, self-sampling at home was overall (very) positively received by the participants.

Experiences of Self-Sampling and Future Screening Preferences in Non-Attenders Who Returned an HPV Vaginal Self-Sample in the YouScreen Study: Findings From a Cross-Sectional Questionnaire.

BACKGROUND: We assessed experiences of human papillomavirus (HPV) vaginal self-sampling and future screening preferences in an ethnically and socio-economically diverse group of women overdue for cervical screening. SETTING AND PARTICIPANTS: A postal questionnaire was embedded in the YouScreen self-sampling trial in England: 32.5% (2712/8338) of kit completers returned the survey. Kit non-completers were encouraged to return a questionnaire, but no responses were received. Participants were ethnically diverse (40.3% came from ethnic minority backgrounds), and 59.1% came from the two most deprived quintiles. Differences in confidence in kit completion, trust in the test results and intention to attend a follow-up test if HPV-positive were evaluated using Pearson's χ2 analyses. Binary logistic regression models explored predictors of a future screening choice and preferences for urine versus vaginal self-sampling. RESULTS: Most kit-completers reported high confidence in self-sampling (82.6%) and high trust in the results (79.9%), but experiences varied by ethnicity and screening status. Most free-text comments were positive but some reported difficulties using the device, pain or discomfort. Most women would opt for self-sampling in the future (71.3% vs. 10.4% for a clinician-taken test) and it was more often preferred by ethnic minority groups, overdue screeners and never attenders. Urine self-tests were preferred to vaginal tests (41.9% vs. 15.4%), especially among women from Asian, Black or Other Ethnic backgrounds. CONCLUSIONS: Kit-completers were confident, found the test easy to complete, and trusted the self-sample results. However, experiences varied by ethnic group and some women highlighted difficulties with the kit. Most women would prefer self-sampling in the future, but it was not a universal preference, so offering a choice will be important. PATIENT OR PUBLIC CONTRIBUTION: We did not have direct patient and public involvement and engagement (PPIE) in the questionnaire design. However, patients and public representatives did input into the design of the YouScreen trial and reviewed the wider study materials (e.g. participant information sheet). TRIAL REGISTRATION: This questionnaire study was embedded in the YouScreen trial. The protocol for the YouScreen trial is available at https://www.isrctn.com/ISRCTN12759467. The National Institute for Health Research 43 Clinical Research Network (NIHR CRN) Central Portfolio Management System (CPMS) ID is 4441934.

From capture to detection: A critical review of passive sampling techniques for pathogen surveillance in water and wastewater.

Water quality, critical for human survival and well-being, necessitates rigorous control to mitigate contamination risks, particularly from pathogens amid expanding urbanization. Consequently, the necessity to maintain the microbiological safety of water supplies demands effective surveillance strategies, reliant on the collection of representative samples and precise measurement of contaminants. This review critically examines the advancements of passive sampling techniques for monitoring pathogens in various water systems, including wastewater, freshwater, and seawater. We explore the evolution from conventional materials to innovative adsorbents for pathogen capture and the shift from culture-based to molecular detection methods, underscoring the adaptation of this field to global health challenges. The comparison highlights passive sampling's efficacy over conventional techniques like grab sampling and its potential to overcome existing sampling challenges through the use of innovative materials such as granular activated carbon, thermoplastics, and polymer membranes. By critically evaluating the literature, this work identifies standardization gaps and proposes future research directions to augment passive sampling's efficiency, specificity, and utility in environmental and public health surveillance.

Spatiotemporal distribution of oxidative potential in PM2.5 and its key components across six Chinese cities.

Increasing evidence has supported that oxidative potential (OP) serves as a crucial indicator of health risk of exposure to PM2.5 over mass concentration. However, there is a lack of comparative studies across multiple cities, particularly on a fine temporal scale. In this study, we aim to investigate daily variation of ambient PM2.5 OP through simultaneous samplings in six Chinese cities for one year. Results showed that more than 60 % of the sampling days exhibited non-zero ranking difference between volume-normalized oxidative potential (OPv) and mass concentration among the six cities. Key components contributing to OPv inculde Mn, NO3-, and K+, followed by Ca2+, Al, SO42-, Cl-, Fe, and NH4+. Based on these chemical components, we developed a stepwise multivariable linear regression model (R2: 0.71) for OPv prediction. The performance of the model is comparable to both species- and sources-based ones in the literature. These findings suggest that a relatively lower daily-averaged mass concentration of PM2.5 does not necessarily indicate a lower oxidative risk. Future studies and policy developments on health benefits should also consider OPv rather than mass concentration alone. Priority could be given to sources/species that contribute significantly to oxidative potential of ambient PM2.5. SYNOPSIS: This study highlights inclusion of oxidative potential as a complementary metric for air pollution assessment and control.

Experiences and perspectives regarding human papillomavirus self-sampling in sub-Saharan Africa: A systematic review of qualitative evidence.

Introduction: Cervical cancer screening coverage remains low in sub-Saharan Africa (SSA) due to limited access and low uptake of available services by women. The use of HPV-based self-sampling intervention for cervical cancer screening has the potential to increase screening coverage in the region. This study aimed to analyse qualitative evidence on the experiences and perspectives of women, healthcare workers, and policymakers regarding HPV self-sampling. Methods: We reviewed qualitative studies from January 2011 to March 2023 in PubMed, Scopus, Medline Ovid, Cochrane, and WEB of Science databases for articles with qualitative data on HPV self-sampling from different countries in SSA. The socio-ecological model was used to guide data analysis and the study findings. Results: Thirteen qualitative studies were included for analysis, and they revealed themes under the intrapersonal, interpersonal, community, and health systems constructs of the Socio-ecological model. Intrapersonal themes included the acceptability of self-sampling, self-efficacy, and the perceived value of self-sampling. The interpersonal construct had themes such as women's spousal relationships, peer support, and the health worker's relationship with the women. The community construct had two themes: social stigma and misinformation, and the influence of cultural norms and religion. Finally, the health systems construct had themes such as the setting for self-sampling, follow-up availability of treatment services and education and awareness. Conclusion: This study highlights the factors influencing the acceptability and uptake of an HPV-based self-sampling intervention for cervical cancer screening in SSA. Considering these findings when designing interventions in SSA is crucial to ensure acceptance and demand among end-users. Self-sampling interventions offer the potential to reach many unscreened women and increase cervical cancer screening coverage in SSA, which is an essential strategy towards achieving the World Health Organisation's cervical cancer elimination targets by the close of the century.

Valuations of target items are drawn towards unavailable decoy items due to prior expectations.

When people make choices, the items they consider are often embedded in a context (of other items). How this context affects the valuation of the specific item is an important question. High-value context might make items appear less attractive because of contrast-the tendency to normalize perception of an object relative to its background-or more attractive because of assimilation-the tendency to group objects together. Alternatively, a high-value context might increase prior expectations about the item's value. Here, we investigated these possibilities. We examined how unavailable context items affect choices between two target items, as well as the willingness-to-pay for single targets. Participants viewed sets of three items for several seconds before the target(s) were highlighted. In both tasks, we found a significant assimilation-like effect where participants were more likely to choose or place a higher value on a target when it was surrounded by higher-value context. However, these context effects were only significant for participants' fastest choices. Using variants of a drift-diffusion model, we established that the unavailable context shifted participants' prior expectations towards the average values of the sets but had an inconclusive effect on their evaluations of the targets during the decision (i.e. drift rates). In summary, we find that people use context to inform their initial valuations. This can improve efficiency by allowing people to get a head start on their decision. However, it also means that the valuation of an item can change depending on the context.

Feasibility, reliability and satisfaction of (automated) capillary carcinoembryonic antigen measurements for future home-based blood sampling: the prospective CASA-I study.

AIM: Follow-up for colorectal cancer (CRC) necessitates regular monitoring of carcinoembryonic antigen (CEA) at the hospital. Capillary home-based blood collection, including minimally invasive techniques such as lancet sampling or an automated upper arm device (TAP-II), has the potential to replace a significant portion of hospital-based blood sampling, thereby enhancing self-reliance and quality of life. The objectives of this study were to assess the feasibility, reliability and preference for CEA blood collection. METHODS: Baseline venous and capillary (by lancet and TAP-II) blood samples were collected from 102 participants, including 20 CRC patients with elevated CEA levels, 60 CRC patients undergoing postoperative outpatient monitoring and 20 healthy volunteers. The second group performed capillary blood collections at home on two consecutive follow-up appointments and subsequently sent them to the hospital. Satisfaction was assessed via patient reported outcome measures on pain, burden, ease of use and preference. RESULTS: The Pearson's correlation test of all usable samples resulted in a linear coefficient of 0.998 (95% CI 0.997-0.998) for the TAP-II method and 0.997 (95% CI 0.996-0.998) for the lancet method, both compared to venipuncture. Following the initial blood collection, 86% of the participants (n = 102) favoured the TAP-II, rating it as the least painful and burdensome option. After two home-based blood samples, the preference for the TAP-II method persisted, with 64% of the patients endorsing its use. CONCLUSION: This study demonstrated the feasibility of home-based capillary sampling of CEA. The TAP-II blood collection is the most reliable method and is preferred by patients over venipuncture and lancet sampling.

Precision enhancement in variance estimation for complex environmental populations using adaptive cluster sampling.

Estimating dispersion in populations that are extremely rare, hidden, geographically clustered, and hard to access is a well-known challenge. Conventional sampling approaches tend to overestimate the variance, even though it should be genuinely reduced. In this environment, adaptive cluster sampling is considered to be the most efficient sampling technique as it provides generally a lower variance than the other conventional probability sampling designs for the assessment of rare and geographically gathered population parameters like mean, total, variance, etc. The use of auxiliary data is very common to obtain the precise estimates of the estimators by taking advantage of the correlation between the survey variable and the auxiliary data. In this article, we introduced a generalized estimator for estimating the variance of populations that are rare, hidden, geographically clustered and hard-to-reached. The proposed estimator leverages both actual and transformed auxiliary data through adaptive cluster sampling. The expressions of approximate bias and mean square error of the proposed estimator are derived up to the first-order approximation using Taylor expansion. Some special cases are also obtained using the known parameters associated with the auxiliary variable. The proposed class of estimators is compared with available estimators using simulation and real data applications.

Recent advances in Rapidly-exploring random tree: A review.

Path planning is an crucial research area in robotics. Compared to other path planning algorithms, the Rapidly-exploring Random Tree (RRT) algorithm possesses both search and random sampling properties, and thus has more potential to generate high-quality paths that can balance the global optimum and local optimum. This paper reviews the research on RRT-based improved algorithms from 2021 to 2023, including theoretical improvements and application implementations. At the theoretical level, branching strategy improvement, sampling strategy improvement, post-processing improvement, and model-driven RRT are highlighted, at the application level, application scenarios of RRT under welding robots, assembly robots, search and rescue robots, surgical robots, free-floating space robots, and inspection robots are detailed, and finally, many challenges faced by RRT at both the theoretical and application levels are summarized. This review suggests that although RRT-based improved algorithms has advantages in large-scale scenarios, real-time performance, and uncertain environments, and some strategies that are difficult to be quantitatively described can be designed based on model-driven RRT, RRT-based improved algorithms still suffer from the problems of difficult to design the hyper-parameters and weak generalization, and in the practical application level, the reliability and accuracy of the hardware such as controllers, actuators, sensors, communication, power supply and data acquisition efficiency all pose challenges to the long-term stability of RRT in large-scale unstructured scenarios. As a part of autonomous robots, the upper limit of RRT path planning performance also depends on the robot localization and scene modeling performance, and there are still architectural and strategic choices in multi-robot collaboration, in addition to the ethics and morality that has to be faced. To address the above issues, I believe that multi-type robot collaboration, human-robot collaboration, real-time path planning, self-tuning of hyper-parameters, task- or application-scene oriented algorithms and hardware design, and path planning in highly dynamic environments are future trends.

Assessment of the effects of dredging on metal levels in port waters using DGT passive samplers and spot sampling.

Aiming at assessing the effect of dredging activities on the levels of metals in Bilbao Port (northern Spain), dissolved and labile metal concentrations in the water were concurrently measured, before, during, and after dredging activities by spot sampling and Diffusive Gradients in Thin-films (DGTs) passive samplers, respectively. Most of the dissolved metal results were below the quantification limits (Cd, <0.06-0.26 µg/L; Co, <5 µg/L; Cu, <5-15 µg/L; Fe, <10-48 µg/L; Mn, <10-22 µg/L; Ni, <2.6-7 µg/L; Pb, <0.39-0.8 µg/L; Zn, <9-24 µg/L). In contrast, DGT results for all sampling times and stations were obtained (Cd, 0.02-0.12 µg/L; Co, 0.08-0.15 µg/L; Cu, 0.5-2.8 µg/L; Fe, 1.0-3.6 µg/L; Mn, 4.7-23.5 µg/L; Ni, 0.5-0.9 µg/L; Pb, 0.15-0.28 µg/L; Zn, 2.6-7.2 µg/L), enabling to determine those metals affected by dredging. Only labile-Pb concentration surpassed momentarily the DGT-Environmental Quality Standard, enabling to rule out biological effects on biota. DGTs are a promising technique for facilitating decision-making during dredging operations.

Efficient risk-based collection of biospecimens in cohort studies: Designing a prospective study of diagnostic performance for multicancer detection tests.

In cohort studies, it can be infeasible to collect specimens on an entire cohort. For example, to estimate sensitivity of multiple Multi-Cancer Detection (MCD) assays, we desire an extra 80mL of cell-free DNA (cfDNA) blood, but this much extra blood is too expensive for us to collect on everyone. We propose a novel epidemiologic study design that efficiently oversamples those at highest baseline disease risk from whom to collect specimens, to increase the number of future cases with cfDNA blood collection. The variance reduction ratio from our risk-based subsample versus a simple random (sub)sample (SRS) depends primarily on the ratio of risk model sensitivity to the fraction of the cohort selected for specimen collection subject to constraining the risk model specificity. In a simulation where we chose 34% of Prostate, Lung, Colorectal, and Ovarian Screening Trial cohort at highest risk of lung cancer for cfDNA blood collection, we could enrich the number of lung cancers 2.42-fold and the standard deviation of lung-cancer MCD sensitivity was 31-33% reduced versus SRS. Risk-based collection of specimens on a subsample of the cohort could be a feasible and efficient approach to collecting extra specimens for molecular epidemiology.

Sampling and Scoring in Protein-Protein Docking.

Protein-protein docking is considered one of the most important techniques supporting experimental proteomics. Recent developments in the field of computer science helped to improve this computational technique so that it better handles the complexity of protein nature. Sampling algorithms are responsible for the generation of numerous protein-protein ensembles. Unfortunately, a primary docking output comprises a set of both near-native poses and decoys. Application of the efficient scoring function helps to differentiate poses with the most favorable properties from those that are very unlikely to represent a natural state of the complex. This chapter explains the importance of sampling and scoring in the process of protein-protein docking. Moreover, it summarizes advances in the field.

Molecular Dynamics Simulations in Protein-Protein Docking.

Concerted interactions between all the cell components form the basis of biological processes. Protein-protein interactions (PPIs) constitute a tremendous part of this interaction network. Deeper insight into PPIs can help us better understand numerous diseases and lead to the development of new diagnostic and therapeutic strategies. PPI interfaces, until recently, were considered undruggable. However, it is now believed that the interfaces contain "hot spots," which could be targeted by small molecules. Such a strategy would require high-quality structural data of PPIs, which are difficult to obtain experimentally. Therefore, in silico modeling can complement or be an alternative to in vitro approaches. There are several computational methods for analyzing the structural data of the binding partners and modeling of the protein-protein dimer/oligomer structure. The major problem with in silico structure prediction of protein assemblies is obtaining sufficient sampling of protein dynamics. One of the methods that can take protein flexibility and the effects of the environment into account is Molecular Dynamics (MD). While sampling of the whole protein-protein association process with plain MD would be computationally expensive, there are several strategies to harness the method to PPI studies while maintaining reasonable use of resources. This chapter reviews known applications of MD in the PPI investigation workflows.

Linguistic style as a digital marker for depression severity: An ambulatory assessment pilot study in patients with depressive disorder undergoing sleep deprivation therapy.

BACKGROUND: Digital phenotyping and monitoring tools are the most promising approaches to automatically detect upcoming depressive episodes. Especially, linguistic style has been seen as a potential behavioral marker of depression, as cross-sectional studies showed, for example, less frequent use of positive emotion words, intensified use of negative emotion words, and more self-references in patients with depression compared to healthy controls. However, longitudinal studies are sparse and therefore it remains unclear whether within-person fluctuations in depression severity are associated with individuals' linguistic style. METHODS: To capture affective states and concomitant speech samples longitudinally, we used an ambulatory assessment approach sampling multiple times a day via smartphones in patients diagnosed with depressive disorder undergoing sleep deprivation therapy. This intervention promises a rapid change of affective symptoms within a short period of time, assuring sufficient variability in depressive symptoms. We extracted word categories from the transcribed speech samples using the Linguistic Inquiry and Word Count. RESULTS: Our analyses revealed that more pleasant affective momentary states (lower reported depression severity, lower negative affective state, higher positive affective state, (positive) valence, energetic arousal and calmness) are mirrored in the use of less negative emotion words and more positive emotion words. CONCLUSION: We conclude that a patient's linguistic style, especially the use of positive and negative emotion words, is associated with self-reported affective states and thus is a promising feature for speech-based automated monitoring and prediction of upcoming episodes, ultimately leading to better patient care.

Hidden Structural States of Proteins Revealed by Conformer Selection with AlphaFold-NMR.

Recent advances in molecular modeling using deep learning can revolutionize our understanding of dynamic protein structures. NMR is particularly well-suited for determining dynamic features of biomolecular structures. The conventional process for determining biomolecular structures from experimental NMR data involves its representation as conformation-dependent restraints, followed by generation of structural models guided by these spatial restraints. Here we describe an alternative approach: generating a distribution of realistic protein conformational models using artificial intelligence-(AI-) based methods and then selecting the sets of conformers that best explain the experimental data. We applied this conformational selection approach to redetermine the solution NMR structure of the enzyme Gaussia luciferase. First, we generated a diverse set of conformer models using AlphaFold2 (AF2) with an enhanced sampling protocol. The models that best-fit NOESY and chemical shift data were then selected with a Bayesian scoring metric. The resulting models include features of both the published NMR structure and the standard AF2 model generated without enhanced sampling. This "AlphaFold-NMR" protocol also generated an alternative "open" conformational state that fits nearly as well to the overall NMR data but accounts for some NOESY data that is not consistent with first "closed" conformational state; while other NOESY data consistent with this second state are not consistent with the first conformational state. The structure of this "open" structural state differs from that of the "closed" state primarily by the position of a thumb-shaped loop between α-helices H5 and H6, revealing a cryptic surface pocket. These alternative conformational states of Gluc are supported by "double recall" analysis of NOESY data and AF2 models. Additional structural states are also indicated by backbone chemical shift data indicating partially-disordered conformations for the C-terminal segment. Considered as a multistate ensemble, these multiple states of Gluc together fit the NOESY and chemical shift data better than the "restraint-based" NMR structure and provide novel insights into its structure-dynamic-function relationships. This study demonstrates the potential of AI-based modeling with enhanced sampling to generate conformational ensembles followed by conformer selection with experimental data as an alternative to conventional restraint satisfaction protocols for protein NMR structure determination.

A constrained optimum adaptive design for dose finding in early phase clinical trials.

Recently, interest has grown in the development of dose-finding methods that consider both toxicity and efficacy as endpoints. Along with responses on these, the incorporation of pharmacokinetic (PK) data can be beneficial in terms of patients' safety and can also increase the efficiency of the design for finding the best dose for the next phase. In this paper, the maximum concentration (Cmax) is used as the PK measure guiding the dose selection. The ethically attractive approach, which is based on the probability of efficacy, is used as a dose optimisation criterion. At each stage of an adaptive trial, that dose is selected for which the criterion is maximised, subject to the constraints imposed on the Cmax and the probability of toxicity. The inter-patient variability of the PK model parameters is considered, and population D-optimal sampling time points for measuring the concentration of a drug in the blood are calculated. The method is illustrated with a one-compartment PK model with first-order absorption, with the parameters being assumed to be random. The Cox model for bivariate binary responses is employed to model the dose-response outcomes. The results of a simulation study for several plausible dose-response scenarios show a significant gain in the efficiency of the design, as well as a reduction in the proportion of toxic responses.

Passive sampler housing and sorbent type determine aquatic micropollutant adsorption and subsequent bioassay responses.

The combination of integrative passive sampling and bioassays is a promising approach for monitoring the toxicity of polar organic contaminants in aquatic environments. However, the design of integrative passive samplers can affect the accumulation of compounds and therewith the bioassay responses. The present study aimed to determine the effects of sampler housing and sorbent type on the number of chemical features accumulated in polar passive samplers and the subsequent bioassay responses to extracts of these samplers. To this end, four integrative passive sampler configurations, resulting from the combination of polar organic chemical integrative sampler (POCIS) and Speedisk housings with hydrophilic-lipophilic balance and hydrophilic divinylbenzene sorbents, were simultaneously exposed at reference and contaminated surface water locations. The passive sampler extracts were subjected to chemical non-target screening and a battery of five bioassays. Extracts from POCIS contained a higher number of chemical features and caused higher bioassay responses in 91% of cases, while the two sorbents accumulated similar numbers of features and caused equally frequent but different bioassay responses. Hence, the passive sampler design critically affected the number of accumulated polar organic contaminants as well as their toxicity, highlighting the importance of passive sampler design for effect-based water quality assessment.

Association of Positive, Negative, and Disorganized Schizotypy With the Temporal Dynamics of Schizotypic Experiences in Daily Life.

BACKGROUND AND HYPOTHESIS: Schizotypy is a useful and unifying construct for examining the etiology, development, and expression of schizophrenia-spectrum psychopathology. The positive, negative, and disorganized schizotypy dimensions are associated with distinct patterns of schizophrenia-spectrum symptoms and impairment. Furthermore, they are differentiated by mean levels of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, and by temporal dynamics of affect. The schizotypy dimensions were thus hypothesized to be differentiated by the temporal dynamics of schizotypic experiences in daily life. STUDY DESIGN: The present study employed experience sampling methodology in a large nonclinically ascertained sample (n = 693) to examine the associations of multidimensional schizotypy with psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, as well as with their temporal dynamics (variability, reactivity, inertia, and instability). STUDY RESULTS: We replicated the mean-level associations between multidimensional schizotypy and schizotypic experiences in daily life. Furthermore, positive, negative, and disorganized schizotypy demonstrated hypothesized, differential patterns of temporal dynamics of schizotypic experiences. Disorganized schizotypy demonstrated the most robust associations, including intensity, variability, and inertia of disorganized schizotypic experiences. Disorganized schizotypy also moderated reactivity of psychotic-like and disorganized schizotypic experiences following previously reported stress. Positive schizotypy was associated with intensity and variability of psychotic-like experiences. Negative schizotypy was associated with intensity and variability of negative schizotypic experiences. CONCLUSIONS: The findings indicate that schizotypy dimensions can be differentiated by both mean levels and temporal patterns of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, with disorganized schizotypy uniquely characterized by stress reactivity.

From anticipation to action: A RCT on mental imagery exercises in daily life as a motivational amplifier for individuals with depressive symptoms.

Encouraging engagement in rewarding or pleasant activities is one of the most important treatment goals for depression. Mental imagery exercises have been shown to increase the motivation for planned behaviour in the lab but it is unclear whether this is also the case in daily life. Therefore, we aimed to investigate the effect of mental imagery exercises on motivation and behaviour in daily life. Participants with depressive symptoms (N = 59) were randomly assigned to a group receiving mental imagery (MI) exercises or a control group receiving relaxation (RE) exercises via study phones. We employed an experience sampling design with 10 assessments per day for 10 days (three days baseline, four days with two exercises per day and three days post-intervention). Data was analysed using t-tests and multilevel linear regression analyses. As predicted, MI exercises enhanced motivation and reward anticipation during the intervention phase compared to RE. However, MI did not enhance active behaviour or strengthen the temporal association from reward anticipation (t-1) to active behaviour (t). Mental imagery exercises can act as a motivational amplifier but its effects on behaviour and real-life reward processes remain to be elucidated.