Depression Symptoms, Problem Gambling and the Role of Escape and Excitement Gambling Outcome Expectancies.

The relationship between problem gambling and depression is well documented. However, there are few studies that have explored the mechanisms that may help maintain the association between depression symptoms and problem gambling. This study tests the assumption that gambling for escape and excitement may either mediate or moderate the relationship between depression and problem gambling. To test these propositions, 282 adults who gambled at least once a month were recruited to complete an online survey that assessed depression severity, the gambling outcomes expectancies of escape and excitement and problem gambling. The study did not find evidence for a mediation effect for either escape or excitement, although escape moderated the relationship between depression and problem gambling. In particular, there was not a relationship between depression and problem gambling when there was low endorsement of the escape gambling outcomes expectancies. However, the relationship between depression and problem gambling strengthened when endorsement of gambling as an escape increased. This indicates that individuals with elevated levels of depression symptoms, and who view gambling as a way to moderate mood states, may be at higher risk for problem gambling than those who hold less favourable views towards gambling as a mood modifier. This suggests it may be helpful to consider the gambling expectancies of gamblers experiencing problems when formulating educational and treatment initiatives, especially with those experiencing heightened levels of depressive symptoms.

Exploring emotion regulation as a mediator of the relationship between resilience and distress in cancer.

OBJECTIVES: Distress in patients with cancer is a significant problem that affects up to 32% of patients. Yet research indicates that 35% of cancer patients do maintain high levels of well-being. Resilience is one psychological factor implicated as being protective against distress; however, the mechanisms for this relationship are currently unknown. The present study aimed to explore emotion regulation as a potential mediator of the relationship between resilience and distress. METHODS: A cross-sectional survey examining emotional regulation, resilience, and distress was completed by 227 patients from two hospitals with heterogeneous cancer types. Measures included the Difficulties in Emotion Regulation Scale (DERS), the Connor Davidson Resilience Scale, and the Depression, Anxiety, Stress Scale. RESULTS: Difficulties in emotion regulation and resilience explained 33.2% of the variance in distress. Resilience had a significant direct effect on distress, accounting for 15.8% of the variance. However, this effect was no longer significant when difficulties in emotion regulation were controlled for. The indirect effect through difficulties in emotion regulation was significant, b = 0.009, 95% CI [-0.013,-0.007], suggesting that the effect of resilience on distress was fully mediated by emotion regulation. Parallel mediation analyses also examined the differential effects of the six DERS subscales on the relationship between resilience and distress. CONCLUSION: These findings suggest that emotion regulation is an important mediator of resilience in cancer. Hence, in patients with cancer, difficulties in emotion regulation (and the DERS specifically) might be a useful focus for screening for patients at risk of distress.

Baseline cortisol levels and social behavior differ as a function of handedness in marmosets (Callithrix jacchus).

Population hand preferences are rare in nonhuman primates, but individual hand preferences are consistent over a lifetime and considered to reflect an individual's preference to use a particular hemisphere when engaged in a specific task. Previous findings in marmosets have indicated that left-handed individuals tend to be more fearful than their right-handed counterparts. Based on these findings, we tested the hypotheses that left-handed marmosets are (a) more reactive to a social stressor and (b) are slower than right-handed marmosets in acquiring a reversal learning task. We examined the hand preference of 27 male and female marmosets (ages of 4-7 years old) previously tested in a social separation task and a reversal learning task. Hand preference was determined via a simple reaching task. In the social separation task, monkeys were separated from their partner and the colony for a single 7-hr session. Urinary cortisol levels and behavior were assessed at baseline, during the separation and 24 hr postseparation. Hand preferences were equally distributed between left (n = 10), right-handed (n = 10), and ambidextrous (n = 7) individuals. The separation phase was associated with an increase in cortisol levels and behavioral changes that were similar across handedness groups. However, cortisol levels at baseline were positively correlated with right-handedness, and this relationship was stronger in females than in males. In addition, the occurrence of social behaviors (pre- and postseparation) was positively correlated with right-handedness in both sexes. Baseline cortisol levels did not correlate significantly with social behavior. Acquisition of the reversals was poorer in females than males but did not differ as a function of handedness. We conclude that (a) both stress reactivity and cognitive flexibility are similar across handedness groups and (b) left-handers exhibit less social behavior and have lower basal cortisol levels than ambidextrous and right-handed subjects. The underlying causes for these differences remain to be established.

Stain-Free Approach to Determine and Monitor Cell Heath Using Supervised and Unsupervised Image-Based Deep Learning.

Cell-based medicinal products (CBMPs) are a growing class of therapeutics that promise new treatments for complex and rare diseases. Given the inherent complexity of the whole human cells comprising CBMPs, there is a need for robust and fast analytical methods for characterization, process monitoring, and quality control (QC) testing during their manufacture. Existing techniques to evaluate and monitor cell quality typically constitute labor-intensive, expensive, and highly specific staining assays. In this work, we combine image-based deep learning with flow imaging microscopy (FIM) to predict cell health metrics using cellular morphology "fingerprints" extracted from images of unstained Jurkat cells (immortalized human T-lymphocyte cells). A supervised (i.e., algorithm trained with human-generated labels for images) fingerprinting algorithm, trained on images of unstained healthy and dead cells, provides a robust stain-free, non-invasive, and non-destructive method for determining cell viability. Results from the stain-free method are in good agreement with traditional stain-based cytometric viability measurements. Additionally, when trained with images of healthy cells, dead cells and cells undergoing chemically induced apoptosis, the supervised fingerprinting algorithm is able to distinguish between the three cell states, and the results are independent of specific treatments or signaling pathways. We then show that an unsupervised variational autoencoder (VAE) algorithm trained on the same images, but without human-generated labels, is able to distinguish between samples of healthy, dead and apoptotic cells along with cellular debris based on learned morphological features and without human input. With this, we demonstrate that VAEs are a powerful exploratory technique that can be used as a process monitoring analytical tool.

AYA 'Can-Sleep' programme: protocol for a stepped-care, cognitive behavioural therapy-based approach to the management of sleep difficulties in adolescents and young adults with cancer.

BACKGROUND: Sleep problems are reported in up to 50% of adolescents and young adults (AYA) with cancer. Cognitive behavioural therapy for insomnia (CBTi) is considered the gold-standard treatment. In the AYA population, CBTi is associated with improvements in insomnia, daytime sleepiness, fatigue and quality of life. In adults, stepped-care interventions can improve accessibility to CBTi. This study aims to evaluate the acceptability and feasibility of a stepped-care CBTi programme in AYA with cancer. METHODS AND ANALYSIS: AYA (target N = 80) aged 16-25 with a diagnosis of cancer will be screened using the Insomnia Severity Index (ISI) and Epworth Sleepiness Scale (ESS). When sleep difficulties are identified by the ISI and/or ESS, they will be screened for obstructive sleep apnoea and restless leg syndrome and referred to a sleep service if indicated. The remainder with sleep difficulties will be offered a stepped-care sleep programme including CBT self-management and coaching (first step). Participants will then be rescreened at 5 weeks, and those with ongoing sleep difficulties will be offered individualised CBT (second step). Recruitment and retention rates, adherence to intervention and time taken to deliver screening and intervention will be collected to assess the feasibility of the programme. AYA and clinicians will complete evaluation surveys to assess the acceptability of the AYA Can-Sleep programme. DISCUSSION: We seek to contribute to the evidence base regarding screening and treatment of sleep difficulties in the AYA population by implementing the AYA Can-Sleep programme and determining its feasibility and acceptability as an approach to care in an Adolescent & Young Adult Cancer Service.

A computational pipeline for functional gene discovery.

Many computational pipelines exist for the detection of differentially expressed genes. However, computational pipelines for functional gene detection rarely exist. We developed a new computational pipeline for functional gene identification from transcriptome profiling data. Key features of the pipeline include batch effect correction, clustering optimization by gap statistics, gene ontology analysis of clustered genes, and literature analysis for functional gene discovery. By leveraging this pipeline on RNA-seq datasets from two mouse retinal development studies, we identified 7 candidate genes involved in the formation of the photoreceptor outer segment. The expression of top three candidate genes (Pde8b, Laptm4b, and Nr1h4) in the outer segment of the developing mouse retina were experimentally validated by immunohistochemical analysis. This computational pipeline can accurately predict novel functional gene for a specific biological process, e.g., development of the outer segment and synapses of the photoreceptor cells in the mouse retina. This pipeline can also be useful to discover functional genes for other biological processes and in other organs and tissues.