Personality Risk Factors for Vape Use amongst Young Adults and Its Consequences for Sleep and Mental Health.

(1) Background: The surge in vape (e-cigarette) use among young adults is concerning, as there is limited knowledge about risk factors and health consequences. This study explores the personality traits linked to vape use, and associations between vaping and chronotype, sleep quality, and mental health, among young adults. (2) Methods: 316 participants, aged 18-25, completed measurements of mindfulness, rumination, self-compassion, anxiety/depression, chronotype, and sleep quality. (3) Results: the vape user group scored significantly lower on mindfulness, higher on rumination, and lower on self-compassion. Vape users were more likely to be evening types and had significantly lower sleep quality and higher anxiety symptoms, as well as higher alcohol use and loneliness (at trend) (4) Conclusions: These novel findings enhance our understanding of what might predispose young adults to vaping and the potential impact on their mental health and sleep quality. Findings point to specific cognitive/personality traits as vaping risk factors, which could inform intervention strategies.

Pragmatic patchwork ethnography, a call to action for health, nutrition and dietetic researchers.

Qualitative research methods are increasingly used in nutrition and dietetics research. Ethnography is an underexploited approach which seeks to explore the diversity of people and cultures in a given setting, providing a better understanding of the influences that determine their choices and behaviours. It is argued that traditional ethnography, that is, the methodology of living within participant communities, is a dated practice, with roots in colonialism, accessible to only researchers with the means, connections and status to conduct such research, typically white, privileged males. This paper proposes a formal interpretation of 'patchwork ethnography', whereby research is carried out in situ around existing modern-day commitments of the researcher, thus enabling more researchers within health, nutrition and dietetic practice to benefit from the rich data that can be discovered from communities. This review proposes the concept that pragmatic patchwork ethnography is required, proposing a framework for implementation, providing researchers, particularly within the fields of human nutrition, dietetics and health, the accessibility and means to deploy a meaningful client-centric methodology. We present pragmatic patchwork ethnography as a modern method for use within multiple healthcare settings, thus adding a progressive brick in the wall of qualitative research.

The transition from genomics to phenomics in personalized population health.

Modern health care faces several serious challenges, including an ageing population and its inherent burden of chronic diseases, rising costs and marginal quality metrics. By assessing and optimizing the health trajectory of each individual using a data-driven personalized approach that reflects their genetics, behaviour and environment, we can start to address these challenges. This assessment includes longitudinal phenome measures, such as the blood proteome and metabolome, gut microbiome composition and function, and lifestyle and behaviour through wearables and questionnaires. Here, we review ongoing large-scale genomics and longitudinal phenomics efforts and the powerful insights they provide into wellness. We describe our vision for the transformation of the current health care from disease-oriented to data-driven, wellness-oriented and personalized population health.

Training in new forms of human-AI interaction improves complex working memory and switching skills of language professionals.

AI-related technologies used in the language industry, including automatic speech recognition (ASR) and machine translation (MT), are designed to improve human efficiency. However, humans are still in the loop for accuracy and quality, creating a working environment based on Human-AI Interaction (HAII). Very little is known about these newly-created working environments and their effects on cognition. The present study focused on a novel practice, interlingual respeaking (IRSP), where real-time subtitles in another language are created through the interaction between a human and ASR software. To this end, we set up an experiment that included a purpose-made training course on IRSP over 5 weeks, investigating its effects on cognition, and focusing on executive functioning (EF) and working memory (WM). We compared the cognitive performance of 51 language professionals before and after the course. Our variables were reading span (a complex WM measure), switching skills, and sustained attention. IRSP training course improved complex WM and switching skills but not sustained attention. However, the participants were slower after the training, indicating increased vigilance with the sustained attention tasks. Finally, complex WM was confirmed as the primary competence in IRSP. The reasons and implications of these findings will be discussed.

Framework for Implementing Individualised Dosing of Anti-Cancer Drugs in Routine Care: Overcoming the Logistical Challenges.

Precision medicine in oncology involves identifying the 'right drug', at the 'right dose', for the right person. Currently, many orally administered anti-cancer drugs, particularly kinase inhibitors (KIs), are prescribed at a standard fixed dose. Identifying the right dose remains one of the biggest challenges to optimal patient care. Recently the Precision Dosing Group established the Accurate Dosing of Anti-cancer Patient-centred Therapies (ADAPT) Program to address individualised dosing; thus, use existing anti-cancer drugs more safely and efficiently. In this paper, we outline our framework, based on the Medical Research Council (MRC) framework, with a simple 6-step process and strategies which have led to the successful implementation of the ADAPT program in South Australia. Implementation strategies in our 6-step process involve: (1) Evaluate the evidence and identify the cancer drugs: Literature review, shadowing other experts, establishing academic partnerships, adaptability/flexibility; (2) Establishment of analytical equipment for drug assays for clinical purposes: assessment for readiness, accreditation, feasibility, obtaining formal commitments, quality assurance to all stakeholders; (3) Clinical preparation and education: educational material, conducted educational meetings, involve opinion leaders, use of mass media, promote network weaving, conduct ongoing training; (4) Blood collection, sample preparation and analyses: goods received procedures, critical control points (transport time); (5) Interpret and release results with recommendations: facilitate the relay of clinical data to providers; (6) Clinical application: providing ongoing consultation, identify early adopters, identify, and prepare champions. These strategies were selected from the 73 implementation strategies outlined in the Expert Recommendations for Implementing Change (ERIC) study. The ADAPT program currently provides routine plasma concentrations for patients on several orally administered drugs in South Australia and is currently in its evaluation phase soon to be published. Our newly established framework could provide great potential and opportunities to advance individualised dosing of oral anti-cancer drugs in routine clinical care.

Beyond fear and anger: A global analysis of emotional response to Covid-19 news on Twitter using deep learning.

The media has been used to disseminate public information amid the Covid-19 pandemic. However, the Covid-19 news has triggered emotional responses in people that have impacted their mental well-being and led to news avoidance. To understand the emotional response to the Covid-19 news, we study user comments on the news published on Twitter by 37 media outlets in 11 countries from January 2020 to December 2022. We employ a deep-learning-based model to identify one of the 6 Ekman's basic emotions, or the absence of emotional expression, in comments to the Covid-19 news, and an implementation of Latent Dirichlet Allocation (LDA) to identify 12 different topics in the news messages. Our analysis finds that while nearly half of the user comments show no significant emotions, negative emotions are more common. Anger is the most common emotion, particularly in the media and comments about political responses and governmental actions in the United States. Joy, on the other hand, is mainly linked to media outlets from the Philippines and news on vaccination. Over time, anger is consistently the most prevalent emotion, with fear being most prevalent at the start of the pandemic but decreasing and occasionally spiking with news of Covid-19 variants, cases, and deaths. Emotions also vary across media outlets, with Fox News having the highest level of disgust, the second-highest level of anger, and the lowest level of fear. Sadness is highest at Citizen TV, SABC, and Nation Africa, all three African media outlets. Also, fear is most evident in the comments to the news from The Times of India.

GP assessment of unmet need in a complex multimorbid population using a data-driven and clinical triage system: a prospective cohort study.

BACKGROUND: Patients with unmet healthcare needs are more likely to access unscheduled care. Identifying these patients through data-driven and clinical risk stratification for active case management in primary care can help address patient need and reduce demand on acute services. AIM: To determine how a proactive digital healthcare system can be used to undertake comprehensive needs analysis of patients at risk of unplanned admission and mortality. DESIGN & SETTING: Prospective cohort study of six general practices in a deprived UK city. METHOD: To identify those with unmet needs, the study's population underwent digitally-driven risk stratification into Escalated and Non-escalated groups using seven risk factors. The Escalated group underwent further stratification using GP clinical assessment into Concern and No concern groups. The Concern group underwent Unmet Needs Analysis (UNA). RESULTS: From 24 746 patients, 516 (2.1%) were triaged into the Concern group and 164 (0.7%) underwent UNA. These patients were more likely to be older (t = 4.69, P<0.001), female (X2 = 4.46, P<0.05), have a Patients At Risk of Re-hospitalisation (PARR) score ≥80 (X2 = 4.31, P<0.05), be a nursing home resident (X2 = 6.75, P<0.01), or on an end-of-life (EOL) register (X2 = 14.55, P<0.001). Following UNA, 143 (87.2%) patients had further review planned or were referred for further input. The majority of patients had four domains of need. In those who GPs would not be surprised if they died within the next few months, n = 69 (42.1%) were not on an EOL register. CONCLUSION: This study showed how an integrated, patient-centred, digital care system working with GPs can highlight and implement resources to address the escalating care needs of complex individuals.

Method development to characterise elephant tail hairs by LA-ICP-MS to reflect changes in elemental chemistry.

This paper evaluated analytical methods used to generate time-series data from elephant tail hairs, which can be used to reflect changing exposure to environmental geochemistry. Elephant tail hairs were analysed by three methods sequentially, each providing data to inform subsequent analysis. Scanning Electron Microscopy (SEM) and X-ray Microanalysis visually showed the structure of the hair, specific structures such as tubules, and the mineral crusting around the edge of the hair, informing targeting of subsequent analysis by Laser Ablation-Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS). LA-ICP-MS generated time-series data which informed sectioning of the tail hairs for subsequent quantitative analysis for potentially toxic elements and micronutrients using Inductively Coupled Plasma Mass Spectrometry (ICP-MS) of dissolved tail hairs. This novel approach to characterise the tail hair enabled time-series analysis to reflect changes in environmental exposure which may result from seasonal or geochemical spatial variation and could inform elephant movement patterns. The seasonal change between wet and dry seasons was reflected down the length of the hair. Correlations were seen between LA-ICP-MS data and ICP-MS data in several elements including Mg, P, Ca, Fe, Na, Mn and U. This study provided time-series data for the analysis of elephant tail hairs by evaluating analytical challenges to obtaining quantitative data, such as improving protocols to ensure removal of extraneous material, determining where to section the tail hairs to best reflect environmental changes/exposure and ensuring representative analyses. A protocol was established to determine mineral status across a 12-18 month time period utilizing single elephant tail hairs.

The Response of the Human Umbilical Vein Endothelial Cell Transcriptome to Variation in Magnesium Concentration.

Vascular endothelial cells have a critical role in the maintenance of cardiovascular function. Evidence suggests that endothelial function may be compromised under conditions of magnesium deficiency, which increases vulnerability to inflammation. Whole genome transcription analysis was used to explore the acute (24 h) effects of magnesium on human umbilical vascular endothelial cells (HUVEC) cultured in low (0.1 mM) or high (5 mM) concentrations. With low magnesium 2728 transcripts were differentially expressed compared to the 1 mM control cultures and 3030 were differentially expressed with high magnesium. 615 transcripts were differentially expressed under both conditions, of which only 34 showed a concentration-dependent response. Analysis indicated that cellular organisation and biogenesis and key cellular processes such as apoptosis were impacted by both low and high conditions. High magnesium also influenced protein binding functions, intracellular signal transduction, metabolic and catalytic processes. Both conditions impacted on stress-related processes, in particular the inflammatory response. Key mediators of calcium-dependent regulation of gene expression were responsive to both high and low magnesium conditions. The HUVEC transcriptome is highly sensitive to acute changes in the concentration of magnesium in culture medium. The findings of this study support the view that whilst inflammation is an important process that is responsive to magnesium, the function of the endothelium may be impacted by other magnesium-induced changes including maintenance of cellular integrity, receptor expression and metabolic functions. The high proportion of transcripts that did not show a concentration-dependent response suggests variation in magnesium may elicit indirect changes, possibly mediated by other ions.

Variation in movement strategies: Capital versus income migration.

Animal migrations represent the regular movements of trillions of individuals. The scale of these movements has inspired human intrigue for millennia and has been intensively studied by biologists. This research has highlighted the diversity of migratory strategies seen across and within migratory taxa: while some migrants temporarily express phenotypes dedicated to travel, others show little or no phenotypic flexibility in association with migration. However, a vocabulary for describing these contrasting solutions to the performance trade-offs inherent to the highly dynamic lifestyle of migrants (and strategies intermediate between these two extremes) is currently missing. We propose a taxon-independent organising framework based on energetics, distinguishing between migrants that forage as they travel (income migrants) and those that fuel migration using energy acquired before departure (capital migrants). Not only does our capital:income continuum of migratory energetics account for the variable extent of phenotypic flexibility within and across migrant populations, but it also aligns with theoreticians' treatment of migration and clarifies how migration impacts other phases of the life cycle. As such, it provides a unifying scale and common vacabulary for comparing the migratory strategies of divergent taxa.