Humanized mouse liver reveals endothelial control of essential hepatic metabolic functions.

Hepatocytes, the major metabolic hub of the body, execute functions that are human-specific, altered in human disease, and currently thought to be regulated through endocrine and cell-autonomous mechanisms. Here, we show that key metabolic functions of human hepatocytes are controlled by non-parenchymal cells (NPCs) in their microenvironment. We developed mice bearing human hepatic tissue composed of human hepatocytes and NPCs, including human immune, endothelial, and stellate cells. Humanized livers reproduce human liver architecture, perform vital human-specific metabolic/homeostatic processes, and model human pathologies, including fibrosis and non-alcoholic fatty liver disease (NAFLD). Leveraging species mismatch and lipidomics, we demonstrate that human NPCs control metabolic functions of human hepatocytes in a paracrine manner. Mechanistically, we uncover a species-specific interaction whereby WNT2 secreted by sinusoidal endothelial cells controls cholesterol uptake and bile acid conjugation in hepatocytes through receptor FZD5. These results reveal the essential microenvironmental regulation of hepatic metabolism and its human-specific aspects.

Glutathione Primes T Cell Metabolism for Inflammation.

Activated T cells produce reactive oxygen species (ROS), which trigger the antioxidative glutathione (GSH) response necessary to buffer rising ROS and prevent cellular damage. We report that GSH is essential for T cell effector functions through its regulation of metabolic activity. Conditional gene targeting of the catalytic subunit of glutamate cysteine ligase (Gclc) blocked GSH production specifically in murine T cells. Gclc-deficient T cells initially underwent normal activation but could not meet their increased energy and biosynthetic requirements. GSH deficiency compromised the activation of mammalian target of rapamycin-1 (mTOR) and expression of NFAT and Myc transcription factors, abrogating the energy utilization and Myc-dependent metabolic reprogramming that allows activated T cells to switch to glycolysis and glutaminolysis. In vivo, T-cell-specific ablation of murine Gclc prevented autoimmune disease but blocked antiviral defense. The antioxidative GSH pathway thus plays an unexpected role in metabolic integration and reprogramming during inflammatory T cell responses.

Alzheimer's disease: using gene/protein network machine learning for molecule discovery in olive oil.

Alzheimer's disease (AD) poses a profound human, social, and economic burden. Previous studies suggest that extra virgin olive oil (EVOO) may be helpful in preventing cognitive decline. Here, we present a network machine learning method for identifying bioactive phytochemicals in EVOO with the highest potential to impact the protein network linked to the development and progression of the AD. A balanced classification accuracy of 70.3 ± 2.6% was achieved in fivefold cross-validation settings for predicting late-stage experimental drugs targeting AD from other clinically approved drugs. The calibrated machine learning algorithm was then used to predict the likelihood of existing drugs and known EVOO phytochemicals to be similar in action to the drugs impacting AD protein networks. These analyses identified the following ten EVOO phytochemicals with the highest likelihood of being active against AD: quercetin, genistein, luteolin, palmitoleate, stearic acid, apigenin, epicatechin, kaempferol, squalene, and daidzein (in the order from the highest to the lowest likelihood). This in silico study presents a framework that brings together artificial intelligence, analytical chemistry, and omics studies to identify unique therapeutic agents. It provides new insights into how EVOO constituents may help treat or prevent AD and potentially provide a basis for consideration in future clinical studies.

COVID-19 annual update: a narrative review.

Three and a half years after the pandemic outbreak, now that WHO has formally declared that the emergency is over, COVID-19 is still a significant global issue. Here, we focus on recent developments in genetic and genomic research on COVID-19, and we give an outlook on state-of-the-art therapeutical approaches, as the pandemic is gradually transitioning to an endemic situation. The sequencing and characterization of rare alleles in different populations has made it possible to identify numerous genes that affect either susceptibility to COVID-19 or the severity of the disease. These findings provide a beginning to new avenues and pan-ethnic therapeutic approaches, as well as to potential genetic screening protocols. The causative virus, SARS-CoV-2, is still in the spotlight, but novel threatening virus could appear anywhere at any time. Therefore, continued vigilance and further research is warranted. We also note emphatically that to prevent future pandemics and other world-wide health crises, it is imperative to capitalize on what we have learnt from COVID-19: specifically, regarding its origins, the world's response, and insufficient preparedness. This requires unprecedented international collaboration and timely data sharing for the coordination of effective response and the rapid implementation of containment measures.

An AI-powered patient triage platform for future viral outbreaks using COVID-19 as a disease model.

Over the last century, outbreaks and pandemics have occurred with disturbing regularity, necessitating advance preparation and large-scale, coordinated response. Here, we developed a machine learning predictive model of disease severity and length of hospitalization for COVID-19, which can be utilized as a platform for future unknown viral outbreaks. We combined untargeted metabolomics on plasma data obtained from COVID-19 patients (n = 111) during hospitalization and healthy controls (n = 342), clinical and comorbidity data (n = 508) to build this patient triage platform, which consists of three parts: (i) the clinical decision tree, which amongst other biomarkers showed that patients with increased eosinophils have worse disease prognosis and can serve as a new potential biomarker with high accuracy (AUC = 0.974), (ii) the estimation of patient hospitalization length with ± 5 days error (R2 = 0.9765) and (iii) the prediction of the disease severity and the need of patient transfer to the intensive care unit. We report a significant decrease in serotonin levels in patients who needed positive airway pressure oxygen and/or were intubated. Furthermore, 5-hydroxy tryptophan, allantoin, and glucuronic acid metabolites were increased in COVID-19 patients and collectively they can serve as biomarkers to predict disease progression. The ability to quickly identify which patients will develop life-threatening illness would allow the efficient allocation of medical resources and implementation of the most effective medical interventions. We would advocate that the same approach could be utilized in future viral outbreaks to help hospitals triage patients more effectively and improve patient outcomes while optimizing healthcare resources.

LeadinCare: A Qualitative Informed Digital Training Platform Development to Increase Physicians' Soft Communication Skills After COVID-19.

The post-COVID-19 pandemic era has placed new demands on physicians. One of these demands is the need to use targeted knowledge and soft communication skills, to address the psychosocial problems (e.g. vaccine hesitancy, fears) of individuals with Chronic Physical Illnesses (CPIs). Focusing on training physicians in targeted soft communication skills can help health care systems to address psychosocial-type problems. Yet, such training programs are rarely implemented, effectively.This study aimed to (a) understand physicians' implementation challenges when using soft communication skills during the COVID-19 pandemic; (b) identify beliefs, barriers, and facilitators that can influence physicians' behaviours to use soft communication skills; and (c) inform the content of the LeadinCare; a new digital training platform, designed to improve physicians' soft communication skills, by leveraging the TDF Theoretical Domain Framework (TDF).We conducted 14 in-depth semi-structured interviews with physicians in Greece, supporting non-COVID-19 cases with CPIs. We analyzed their data using inductive and deductive approaches.Physicians highlighted time, inability to see patients in person, absence of space for non-COVID-19 cases, and poor organizational procedures as barriers to using soft communication skills. Five TDF domains (beliefs) were identified as the most salient to inform the LeadinCare platform: (1) practical and well-organized knowledge; (2) skills that support patients and their relatives; (3) physicians' beliefs about capabilities to use the skills; (4) beliefs about consequences of using the skills (job satisfaction); and (5) the use of digital, interactive, and on-demand platforms (environmental context & resources). We mapped the domains in six narrative-based practices that informed the content of the LeadinCare.Physicians need skills that go beyond talking and towards cultivating resilience and flexibility.

Scientific evidence supporting the newly developed one-health labeling tool "Med-Index": an umbrella systematic review on health benefits of mediterranean diet principles and adherence in a planeterranean perspective.

BACKGROUND: Med-Index is a one-health front-of-pack (FOP) label, based on Mediterranean diet (MedDiet) principles, developed to summarize information about the nutritional properties and related-health benefits of any food as well as its sustainable production processes, and the associated food company's social responsibility parameters in a new "Planeterranean" perspective. Thus, Med-Index can be adopted in and by any European region and authority as well as worldwide; this is achieved by consumption and cooking of locally available and sourced foods that respect MedDiet principles, both in terms of healthy nutrition and sustainable production. The huge body of scientific evidence about the health benefits of the MedDiet model and principles requires a comprehensive framework to encompass the scientific reliability and robustness of this tool. A systematic review was carried out to examine the association between human health and adherence to MedDiet patterns upon which the "Med-Index" tool was subsequently developed. METHODS: MEDLINE and PubMed databases were searched for eligible publications from 1990 to April 2023. Systematic literature reviews, with or without meta-analysis, of clinical trials and observational studies were screened by two independent investigators for eligibility, data extraction, and quality assessment. English language and the time interval 1990-2023 were applied. A registry code CRD42023464807 was generated on PROSPERO and approved for this search protocol. The corrected covered area (CCA), calculated to quantify the degree of overlap between reviews, gave a slight overlap (CCA = 4%). RESULTS: A total of 84 systematic reviews out of 6681 screened records were selected. Eligible reviews included studies with predominantly observational designs (61/84, 72.6%%), of which 26/61 referenced studies of mixed observational and RCT designs, while 23/84 (27.4%) were RCT-only systematic reviews. Seventy-nine different entries were identified for health outcomes, clustered into 10 macro-categories, each reporting a statistically significant association with exposure to the MedDiet. Adherence to MedDiet was found to strongly benefit age-related chronic diseases (21.5%), neurological disorders (19%), and obesity-related metabolic features (12.65), followed by CVDs (11.4%), cancer (10.1%), diabetes (7.5%), liver health (6.3%), inflammation (5%), mortality (5%), and renal health (1.2%). The quality of the studies was moderate to high. CONCLUSION: In the context of a "Planeterranean" framework and perspective that can be adopted in any European region and worldwide, MedDiet represents a healthy and sustainable lifestyle model, able to prevent several diseases and reduce premature mortality. In addition, the availability of a FOP, such as Med-Index, might foster more conscious food choices among consumers, paying attention both to human and planetary health.

Update of the keratin gene family: evolution, tissue-specific expression patterns, and relevance to clinical disorders.

Intermediate filament (IntFil) genes arose during early metazoan evolution, to provide mechanical support for plasma membranes contacting/interacting with other cells and the extracellular matrix. Keratin genes comprise the largest subset of IntFil genes. Whereas the first keratin gene appeared in sponge, and three genes in arthropods, more rapid increases in keratin genes occurred in lungfish and amphibian genomes, concomitant with land animal-sea animal divergence (~ 440 to 410 million years ago). Human, mouse and zebrafish genomes contain 18, 17 and 24 non-keratin IntFil genes, respectively. Human has 27 of 28 type I "acidic" keratin genes clustered at chromosome (Chr) 17q21.2, and all 26 type II "basic" keratin genes clustered at Chr 12q13.13. Mouse has 27 of 28 type I keratin genes clustered on Chr 11, and all 26 type II clustered on Chr 15. Zebrafish has 18 type I keratin genes scattered on five chromosomes, and 3 type II keratin genes on two chromosomes. Types I and II keratin clusters-reflecting evolutionary blooms of keratin genes along one chromosomal segment-are found in all land animal genomes examined, but not fishes; such rapid gene expansions likely reflect sudden requirements for many novel paralogous proteins having divergent functions to enhance species survival following sea-to-land transition. Using data from the Genotype-Tissue Expression (GTEx) project, tissue-specific keratin expression throughout the human body was reconstructed. Clustering of gene expression patterns revealed similarities in tissue-specific expression patterns for previously described "keratin pairs" (i.e., KRT1/KRT10, KRT8/KRT18, KRT5/KRT14, KRT6/KRT16 and KRT6/KRT17 proteins). The ClinVar database currently lists 26 human disease-causing variants within the various domains of keratin proteins.

Placing human gene families into their evolutionary context.

Following the draft sequence of the first human genome over 20 years ago, we have achieved unprecedented insights into the rules governing its evolution, often with direct translational relevance to specific diseases. However, staggering sequence complexity has also challenged the development of a more comprehensive understanding of human genome biology. In this context, interspecific genomic studies between humans and other animals have played a critical role in our efforts to decode human gene families. In this review, we focus on how the rapid surge of genome sequencing of both model and non-model organisms now provides a broader comparative framework poised to empower novel discoveries. We begin with a general overview of how comparative approaches are essential for understanding gene family evolution in the human genome, followed by a discussion of analyses of gene expression. We show how homology can provide insights into the genes and gene families associated with immune response, cancer biology, vision, chemosensation, and metabolism, by revealing similarity in processes among distant species. We then explain methodological tools that provide critical advances and show the limitations of common approaches. We conclude with a discussion of how these investigations position us to gain fundamental insights into the evolution of gene families among living organisms in general. We hope that our review catalyzes additional excitement and research on the emerging field of comparative genomics, while aiding the placement of the human genome into its existentially evolutionary context.

Associations between per- and polyfluoroalkyl substances, liver function, and daily alcohol consumption in a sample of U.S. adults.

BACKGROUND AND AIM: Per- and polyfluoroalkyl substances (PFAS) are ubiquitous in the environment and in the serum of the U.S. POPULATION: We sought to evaluate the association of PFAS independently and jointly with alcohol intake on liver function biomarkers in a sample of the U.S. general population. METHODS: Using data from the National Health and Nutrition Examination Survey (2003-2016; N = 11,794), we examined the five most historically prevalent PFAS with >75% detection rates. We estimated odds ratios (OR) and 95% confidence intervals (CI) for the association between PFAS (quartiles and log-transformed continuous, ng/mL) and high levels (>95th percentile) of liver injury biomarkers using logistic regression models adjusted for key confounders. We evaluated interactions between PFAS and alcohol consumption and sex via stratified analyses and conducted sub-analyses adjusting for daily alcohol intake among those with available drinking history (N = 10,316). RESULT: Serum perfluorooctanoic acid (PFOA) was positively associated with high levels of alanine transferase (ALT) without monotonic trend (ORQ4vsQ1 = 1.45, CI: 0.99-2.12; p-trend = 0.18), and with increased aspartate transaminase when modeled continuously (OR = 1.15, CI: 1.02-1.30; p-trend = 0.03). Perfluorooctane sulfonate (PFOS) and perfluorohexane sulfonate (PFHxS) were both inversely associated with alkaline phosphatase while a trend was evident only for PFHxS (p = 0.02). A non-monotonic inverse association was observed with PFOA (p-trend = 0.10). The highest quartile of PFOS was associated with high total bilirubin (TB; ORQ4vsQ1 = 1.57, CI: 1.01-2.43, p-trend = 0.02). No significant associations were found between any PFAS and γ-glutamyl transpeptidase. We found no associations for perfluorodecanoic acid and perfluorononanoic acid. We observed some suggestive interactions with alcohol intake, particularly among heavy drinkers. CONCLUSION: Consistent with other studies, serum levels of PFOA, PFHxS and PFNA were positively associated with high levels of ALT, and we also observed weak positive associations between some PFAS and TB. Associations observed among heavy drinkers warrant additional evaluation.

Predictors of changing patterns of adherence to containment measures during the early stage of COVID-19 pandemic: an international longitudinal study.

BACKGROUND: Identifying common factors that affect public adherence to COVID-19 containment measures can directly inform the development of official public health communication strategies. The present international longitudinal study aimed to examine whether prosociality, together with other theoretically derived motivating factors (self-efficacy, perceived susceptibility and severity of COVID-19, perceived social support) predict the change in adherence to COVID-19 containment strategies. METHOD: In wave 1 of data collection, adults from eight geographical regions completed online surveys beginning in April 2020, and wave 2 began in June and ended in September 2020. Hypothesized predictors included prosociality, self-efficacy in following COVID-19 containment measures, perceived susceptibility to COVID-19, perceived severity of COVID-19 and perceived social support. Baseline covariates included age, sex, history of COVID-19 infection and geographical regions. Participants who reported adhering to specific containment measures, including physical distancing, avoidance of non-essential travel and hand hygiene, were classified as adherence. The dependent variable was the category of adherence, which was constructed based on changes in adherence across the survey period and included four categories: non-adherence, less adherence, greater adherence and sustained adherence (which was designated as the reference category). RESULTS: In total, 2189 adult participants (82% female, 57.2% aged 31-59 years) from East Asia (217 [9.7%]), West Asia (246 [11.2%]), North and South America (131 [6.0%]), Northern Europe (600 [27.4%]), Western Europe (322 [14.7%]), Southern Europe (433 [19.8%]), Eastern Europe (148 [6.8%]) and other regions (96 [4.4%]) were analyzed. Adjusted multinomial logistic regression analyses showed that prosociality, self-efficacy, perceived susceptibility and severity of COVID-19 were significant factors affecting adherence. Participants with greater self-efficacy at wave 1 were less likely to become non-adherence at wave 2 by 26% (adjusted odds ratio [aOR], 0.74; 95% CI, 0.71 to 0.77; P < .001), while those with greater prosociality at wave 1 were less likely to become less adherence at wave 2 by 23% (aOR, 0.77; 95% CI, 0.75 to 0.79; P = .04). CONCLUSIONS: This study provides evidence that in addition to emphasizing the potential severity of COVID-19 and the potential susceptibility to contact with the virus, fostering self-efficacy in following containment strategies and prosociality appears to be a viable public health education or communication strategy to combat COVID-19.

Use of clinical chemistry health outcomes and PFAS chain length to predict 28-day rodent oral toxicity.

Current literature suggests PFAS carbon chain length may be a predictive variable of toxicity. If so, statistical modeling may be used to help predict toxicity, thus improving the efficiency of PFAS regulation development. Data were analyzed using one-way ANOVAs, Tukey's HSD post hoc tests, and simple linear regressions. A dataset was predicted using modeling from this data. Analysis indicated that 11 of 15 health outcomes showed significant differences in mean values. Two of 15 health outcomes were analyzed using simple linear regressions, with statistically significant results. After predictive modeling generated a theoretical dataset, unpaired t-tests comparing the results of an actual dataset indicated no significant differences among the mean values of the two health outcomes. Therefore, predictive statistical modeling may be used to predict health outcomes for PFAS exposure.

Integrated Analysis of Tracheobronchial Fluid from Before and After Cardiopulmonary Bypass Reveals Activation of the Integrated Stress Response and Altered Pulmonary Microvascular Permeability.

Objective: We aim to comprehensively describe the transcriptional activity and signaling of pulmonary parenchymal and immune cells before and after cardiopulmonary bypass (CPB) by using a multi-omic approach coupled with functional cellular assays. We hypothesize that key signaling pathways from specific cells within the lung alter pulmonary endothelial cell function resulting in worsening or improving disease. Methods: We collected serial tracheobronchial lavage samples from intubated patients less than 2-years-old undergoing surgery with CPB. Samples were immediately processed for single cell RNA sequencing (10x Genomics). Cell clustering, cell-type annotation, and visualization were performed, and differentially expressed genes (DEG) between serial samples were identified. Metabolomic and proteomic analyses were performed on the supernatant using mass spectrometry and a multiplex assay (SomaScan) respectively. Functional assays were done using electric cell-substrate impedance sensing to measure resistance across human pulmonary microvascular endothelial cells (HPMECs). Results: Analysis of eight patients showed a heterogeneous mixture of pulmonary parenchymal and immune cells. Cell clustering demonstrated time-dependent changes in the transcriptomic signature indicating altered cellular phenotypes after CPB. DEG analysis was represented by genes involved in host defense, innate immunity, and the mitochondrial respiratory transport chain. Ingenuity pathway analysis showed upregulation of the integrated stress response across all cell types after CPB. Metabolomic analysis demonstrated upregulation of ascorbate and aldarate metabolism. Unbiased proteomic analysis revealed upregulation of proteins involved in cytokine and chemokine pathways. Post-CPB patient supernatant improved HMPEC barrier function, suggesting a protective cellular response to CPB. Conclusion: Children who undergo CPB for cardiac surgery have distinct cell populations, transcriptional activity, and metabolism that change over time. The response to ischemia-reperfusion injury in the lower airway of children appears to be protective, with the need to identify potential targets through future investigations.

Network machine learning maps phytochemically rich "Hyperfoods" to fight COVID-19.

In this paper, we introduce a network machine learning method to identify potential bioactive anti-COVID-19 molecules in foods based on their capacity to target the SARS-CoV-2-host gene-gene (protein-protein) interactome. Our analyses were performed using a supercomputing DreamLab App platform, harnessing the idle computational power of thousands of smartphones. Machine learning models were initially calibrated by demonstrating that the proposed method can predict anti-COVID-19 candidates among experimental and clinically approved drugs (5658 in total) targeting COVID-19 interactomics with the balanced classification accuracy of 80-85% in 5-fold cross-validated settings. This identified the most promising drug candidates that can be potentially "repurposed" against COVID-19 including common drugs used to combat cardiovascular and metabolic disorders, such as simvastatin, atorvastatin and metformin. A database of 7694 bioactive food-based molecules was run through the calibrated machine learning algorithm, which identified 52 biologically active molecules, from varied chemical classes, including flavonoids, terpenoids, coumarins and indoles predicted to target SARS-CoV-2-host interactome networks. This in turn was used to construct a "food map" with the theoretical anti-COVID-19 potential of each ingredient estimated based on the diversity and relative levels of candidate compounds with antiviral properties. We expect this in silico predicted food map to play an important role in future clinical studies of precision nutrition interventions against COVID-19 and other viral diseases.

COVID-19 one year into the pandemic: from genetics and genomics to therapy, vaccination, and policy.

COVID-19 has engulfed the world and it will accompany us all for some time to come. Here, we review the current state at the milestone of 1 year into the pandemic, as declared by the WHO (World Health Organization). We review several aspects of the on-going pandemic, focusing first on two major topics: viral variants and the human genetic susceptibility to disease severity. We then consider recent and exciting new developments in therapeutics, such as monoclonal antibodies, and in prevention strategies, such as vaccines. We also briefly discuss how advances in basic science and in biotechnology, under the threat of a worldwide emergency, have accelerated to an unprecedented degree of the transition from the laboratory to clinical applications. While every day we acquire more and more tools to deal with the on-going pandemic, we are aware that the path will be arduous and it will require all of us being community-minded. In this respect, we lament past delays in timely full investigations, and we call for bypassing local politics in the interest of humankind on all continents.

Overview of PAX gene family: analysis of human tissue-specific variant expression and involvement in human disease.

Paired-box (PAX) genes encode a family of highly conserved transcription factors found in vertebrates and invertebrates. PAX proteins are defined by the presence of a paired domain that is evolutionarily conserved across phylogenies. Inclusion of a homeodomain and/or an octapeptide linker subdivides PAX proteins into four groups. Often termed "master regulators", PAX proteins orchestrate tissue and organ development throughout cell differentiation and lineage determination, and are essential for tissue structure and function through maintenance of cell identity. Mutations in PAX genes are associated with myriad human diseases (e.g., microphthalmia, anophthalmia, coloboma, hypothyroidism, acute lymphoblastic leukemia). Transcriptional regulation by PAX proteins is, in part, modulated by expression of alternatively spliced transcripts. Herein, we provide a genomics update on the nine human PAX family members and PAX homologs in 16 additional species. We also present a comprehensive summary of human tissue-specific PAX transcript variant expression and describe potential functional significance of PAX isoforms. While the functional roles of PAX proteins in developmental diseases and cancer are well characterized, much remains to be understood regarding the functional roles of PAX isoforms in human health. We anticipate the analysis of tissue-specific PAX transcript variant expression presented herein can serve as a starting point for such research endeavors.

COVID-19 update: the first 6 months of the pandemic.

The COVID-19 pandemic is sweeping the world and will feature prominently in all our lives for months and most likely for years to come. We review here the current state 6 months into the declared pandemic. Specifically, we examine the role of the pathogen, the host and the environment along with the possible role of diabetes. We also firmly believe that the pandemic has shown an extraordinary light on national and international politicians whom we should hold to account as performance has been uneven. We also call explicitly on competent leadership of international organizations, specifically the WHO, UN and EU, informed by science. Finally, we also condense successful strategies for dealing with the current COVID-19 pandemic in democratic countries into a developing pandemic playbook and chart a way forward into the future. This is useful in the current COVID-19 pandemic and, we hope, in a very distant future again when another pandemic might arise.

COVID-19 vulnerability: the potential impact of genetic susceptibility and airborne transmission.

The recent coronavirus disease (COVID-19), caused by SARS-CoV-2, is inarguably the most challenging coronavirus outbreak relative to the previous outbreaks involving SARS-CoV and MERS-CoV. With the number of COVID-19 cases now exceeding 2 million worldwide, it is apparent that (i) transmission of SARS-CoV-2 is very high and (ii) there are large variations in disease severity, one component of which may be genetic variability in the response to the virus. Controlling current rates of infection and combating future waves require a better understanding of the routes of exposure to SARS-CoV-2 and the underlying genomic susceptibility to this disease. In this mini-review, we highlight possible genetic determinants of COVID-19 and the contribution of aerosol exposure as a potentially important transmission route of SARS-CoV-2.

Reducing drug-use harms among higher education students: MyUSE contextual-behaviour change digital intervention development using the Behaviour Change Wheel.

BACKGROUND: Digital harm-reduction interventions typically focus on people with severe drug-use problems, yet these interventions have moderate effectiveness on drug-users with lower levels of risk of harm. The difference in effectiveness may be explained by differences in behavioural patterns between the two groupings. Harnessing behavioural theories to understand what is at the core of drug-use behaviours and mapping the content of new interventions, may improve upon the effectiveness of interventions for lower-risk drug-users. To the best of our knowledge, this is the first study to systematically apply the Behaviour Change Wheel (BCW) approach to understand the components, influencing capabilities, opportunities, and motivations (COM-B) of higher education students to change their drug-use behaviors. It is also the first study which identifies specific patterns of behaviours that are more responsive to harm reduction practices through the use of the Theoretical Domain Framework (TDF). METHODS: We employed an explanatory sequential mix-method design. We first conducted an on-line survey and a Delphi exercise to understand the factors influencing COM-B components of higher education students to change their drug-use. Subsequently, we mapped all evidence onto the COM-B components and the TDF domains to identify clusters of behaviours to target for change, using a pattern-based discourse analysis. Finally, a series of multidisciplinary group meetings identified the intervention functions-the means by which the intervention change targeted behaviours and the Behavioural Change Techniques (BCTs) involved using the behaviour change technique taxonomy (v.1). RESULTS: Twenty-nine BCTs relevant to harm-reduction practices were identified and mapped across five intervention functions (education, modelling, persuasion, incentivization, and training) and five policy categories (communication/marketing, guidelines, regulation, service provision, and environmental/social planning). These BCTs were distributed across eight identified saturated clusters of behaviours MyUSE intervention attempts to change. CONCLUSIONS: The BCTs, identified, will inform the development of a digitally delivered behaviour change intervention that focuses on increasing mindful decision-making with respect to drug-use and promotes alternatives to drug-use activities. The findings can also inform implementation scientists in applying context-specific harm-reduction practices in higher education. We present examples of how the eight identified clusters of target behaviours are mapped across the COM-B components and the TDF, along with suggestions of implementation practices for harm reduction at student population level.