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This study is one component of a multi-year research project directed at increasing oral health providers' adoption of an evidence-based clinical practice guideline. Research-to-practice gaps present a significant barrier to patients' receiving quality oral healthcare. Moreover, increasingly in the US, oral healthcare is provided by private corporations employing contracted providers. The relative autonomy of the actors working in these healthcare contexts presents challenges to efforts that support adoption of evidence-based practices. Participatory engagement can usefully support efforts to implement evidence-based practice. How providers orient towards participatory engagement is one challenge not yet considered by researchers. Our analysis sought to discover whether oral health providers exhibited evidence of citizenship behavior (i.e., oriented as citizens) in their deliberations over how to implement an evidence-based clinical practice guideline. We devised and employed a coding scheme based in an Occupational Citizenship Behavior framework to conduct a directed content analysis of transcripts from online deliberative forums among oral healthcare workers who practice within a network of clinics managed by a private healthcare system. In their deliberations, participants exhibited three citizenship behavior types; these behaviors were directed at reinforcing the status quo of relationships, practices, and norms operating in their specific clinics. Further, participants expressed suspicion and fear of outside forces influencing their practice; outside forces included the organization that employs them and professional organizations for oral health providers. An analysis focused on citizenship behavior revealed the reasoning providers advance in relation to their choices about whether and how to implement evidence-based practice guidelines. Moreover, it captured information about barriers and facilitators operating in these providers' localized contexts (i.e., specific clinics) that had not been captured by other methods. More needs to be learned about the citizenship orientation exhibited by participants. The sense of allegiance expressed by participants to their clinic-as-community and their expressions of suspicion and fear about outside forces seem to pose significant barriers to efforts to implement evidence-based guidelines and to close research-to-practice gaps. The Dissemination and Implementation of Sealant Guidelines in Organizations (DISGO) project is registered at ClinicalTrials.gov with ID NCT04682730. The trial was first registered on 12/18/2020. https://clinicaltrials.gov/ct2/show/NCT04682730.

To gain insight into the considerations that play a role for medical students in the final two years of their education when (possibly) choosing the specialty of Public and Occupational Health. Qualitative study using semi-structured interviews. Eleven medical students in their 5th or 6th year who were planning or considering a career in public health care were interviewed. Students tend to explore social medicine specialties late in their studies, due to a lack of internships, networks, and role models. Experiences during clinical hospital rotations prompt students to explore other career paths. Through informal sources, they discover alternatives and choose work that aligns with their ideals and identity. The decision to pursue a career in Public and Occupational Health often emerges late in medical training. Structural reinforcement of undergraduate medical education with content related to social medicine and exposure to role models, combined with career orientation support, can contribute to well-informed career choices.

To assess and compare rural versus urban Minnesotans experiences, perspectives, and awareness of hearing health care. Cross-sectional study. Community-based screening at Driven to Discover Research Facility in Bemidji and St. Paul, MN. Adults &#x2265;18 years. In-person survey, otoscopy, and audiometric screening at 25&#xa0;dB across four frequencies. Descriptive analysis of sociodemographics, awareness of hearing loss and health care, and Brief Health Literacy Screening (BHLS). Hearing loss (HL) was defined as failing at least 1 frequency in 1 ear. There were 77 rural and 212 urban participants, mean age 57.9 years rural versus 47.4 years urban (P<0.05). Overall, 58.8% female, 88.5% white, 93.7% insured. Health literacy was adequate in both groups (mean rural BHLS 13.5 [95% CI: 13.2-13.8], urban 14.2 [95% CI: 14.0-14.4], P<0.05). Rural residents were more likely to have subjective HL (57.1% vs. 32.1%, P<0.05) and audiometric HL (69.9% vs. 42.0%, P<0.05). Rural and urban participants reported similar rates in challenges with access to hearing health care (27.3% vs. 24.1%, P=0.58). Both groups had low rates of hearing testing within 5 years (33.8% vs. 30.2%, P=0.53). Few participants from either group were aware of normal hearing levels (15.6%), discussed hearing testing with their primary care provider (PCP) (9.5%), or had awareness of Minnesota Medicaid coverage of hearing services (35.6%). Urban and rural residents in the Upper Midwest with good health literacy have poor awareness of hearing health and available hearing health care. Both would benefit from public health initiatives to educate PCPs and increase awareness of state benefits.

Designing digital health solutions for critical environments like intensive care units (ICUs) is challenging, especially in resource-constrained settings. The integration of user experience (UX) design methods into digital health development may improve alignment with clinical workflows, reduce barriers to adoption, and enhance perceived usefulness. To apply user experience design methodologies to develop the interface of a telemedicine platform intended to support multidisciplinary tele-rounds in public ICUs in Northern and Northeastern Brazil. We conducted a methodological study from February to May 2022, using the four-stage Double Diamond design model: Discover, Define, Develop, and Deliver. The design process was embedded within a Tele-ICU program implemented through the Brazilian Unified Health System (SUS), supporting public ICUs across the North and Northeast regions of the country. Design activities included desk research, rapid ethnography, benchmarking, development of personas and empathy maps, situational diagnosis of participating ICUs, user journey mapping, wireframing, and heuristic-based usability evaluation. The primary outcome was the successful development and implementation of the "Mangar&#xe1; Digital" tele-round platform. The user-centered process directly informed key features designed to address identified user "pains", such as time pressure and lack of process standardization. These features included at-a-glance patient summary cards, a visual ICU bed map, and integrated checklists. This study demonstrates that UX design methodologies can effectively guide the development of telemedicine platforms tailored to the realities of public ICUs in underserved regions. Explicit consideration of geographic, organizational, and infrastructural constraints is essential to ensure usability, adoption, and sustainability of digital health solutions in resource-constrained intensive care settings.

The purpose of this study is to discover how occupational burnout influences the health status of emergency nurses and to investigate the mediation effect of work-family behavior role conflict. A multi-center cross-sectional study. A questionnaire survey of 1,540 emergency nurses from 30 tertiary hospitals in China was conducted between December 26, 2023, and January 18, 2024. Using an online questionnaire, we performed a cross-sectional survey to collect demographic data and information about occupational burnout, work environment, work-family behavior, role conflict, and emergency nurses' health status. The PROCESS macro for SPSS 26.0 was used to analyze the moderated mediation model, and the bootstrap approach was used to investigate the mediating effects. The findings revealed that 57.3% of the nurses had experienced occupational burnout. A substantial positive association was identified between professional burnout, work-family behavior role conflict, and somatic symptoms (r&#x202f;=&#x202f;0.493, 0.534; p&#x202f;<&#x202f;0.001). Occupational burnout was found to be a significant predictor of somatic symptoms, with work-family conflict serving as a mediator (&#x3b2;&#x202f;=&#x202f;0.616, t&#x202f;=&#x202f;13.295, R 2&#x202f;=&#x202f;0.488, p&#x202f;<&#x202f;0.01). Our research found that nurses' work environment mediated the association between burnout and work-family behavior role conflict (&#x3b2;&#x202f;=&#x202f;0.007, t&#x202f;=&#x202f;3.647, p&#x202f;<&#x202f;0.01), indicating that a positive work environment may reduce the impact of burnout on family role conflict. Work-family behavioral role conflict and the nursing work environment were found to partially mediate the association between occupational burnout and the health outcomes of emergency nurses. These findings suggest that, while interventions aimed at mitigating work-family role conflict and improving the work environment are essential, they may not be sufficient on their own to safeguard nurses' health. Additional strategies are needed to comprehensively address the health risks associated with occupational burnout. Moreover, the interplay among burnout, work-family conflict, and environmental factors underscores the necessity of integrated and multifaceted intervention approaches to alleviate the health burden experienced by emergency nurses effectively.

Sexual minoritized men (SMM) experience disproportionate rates of eating and body image disturbances relative to their heterosexual counterparts due, in part, to exposure to sociocultural pressures (e.g., community-specific body ideals, minority stress). Research often represents SMM as a monolith, precluding an understanding of within-group heterogeneity. There is a lack of research examining differences between SMM based on intimate partner preferences or sexual self-labels, including "top," "bottom," and "versatile." The present study examined how thinness- and muscularity-oriented eating and body image disturbances and sociocultural variables (i.e., sexual minority and intracommunity stressors, tripartite influence model variables) differ across sexual self-label subgroups, including those not identifying with any label. Participants were SMM between the ages of 18 and 30 (N=375; tops, n=104, bottoms, n=60, versatiles, n=175, no self-label, n=36) recruited via Prolific. Results indicated significant group differences in muscularity-oriented eating and body image disturbances, thin internalization, internalized heterosexism, and body stigma intracommunity stress. Versatiles reported greater muscularity-oriented disordered eating than non-self-labels. Bottoms reported greater muscularity-oriented body dissatisfaction than tops, versatiles, and non-self-labels. Bottoms also reported greater thin internalization than tops. Individuals not identifying with any sexual self-label reported greater internalized heterosexism than versatiles and greater body stigma intracommunity stress than all other groups. Findings highlight the role of sexual self-labels in explaining meaningful heterogeneity in eating and body image disturbances and sociocultural stressors among SMM. Future research should replicate and extend our analyses to elucidate the temporal pathways underlying these associations.

Ready-to-eat breakfast cereals are a major source of dietary fiber, and their intake is associated with better diet quality and reduced incidence of chronic disease. However, dietary fiber intake remains significantly lower than recommended levels, particularly in North America. This fiber gap is one of the most important issues facing public health nutrition and deserves continued attention. This extensive analysis summarizes the body of research from the last decade on whole grain/high-fiber breakfast cereals, cereal fibers, and/or selected fiber sources commonly found in, or added to, breakfast cereals (e.g., wheat bran, psyllium). The primary health outcomes of interest for this review are digestive function, gut microbial effects, satiety signaling, body weight management, cardiovascular disease and blood glucose control. The evidence indicates that the fiber amount, fiber type, processing techniques, and numerous associated nutrients and phytochemicals in ready-to-eat breakfast cereals are all critical factors impacting health outcomes. Therefore, in addition to dietary guidance on total daily intake levels, guidance targeting specific health outcomes should also emphasize the unique mechanisms of action (e.g., gel-forming, digestion slowing, fecal-bulking, laxative, toxin binding, prebiotic) for the predominant types of fibers in ready-to-eat cereals and other fiber-rich foods. In particular, a growing body of research indicates that wheat bran, the predominant source of fiber in the U.S. and Canada, contains a novel array of fibers and phytonutrients that support bowel function and influence gut microbiota composition, and may help lower the risk for cardiometabolic disease. Notably, the research shows that individuals with low-cereal fiber consumption are most likely to benefit from an increase in their daily intake. While there is still much to discover regarding the mechanistic effects of different types of cereal fibers, continued encouragement to increase daily consumption of wheat fiber-rich foods, including ready-to-eat cereals, could help to close the fiber gap and reduce the incidence of multiple diet-related chronic diseases.

kidney disease (CKD) is a rising global public health emergency. Singapore faces one of the world&#x2019;s highest CKD prevalence rates at 15.6%, projected to reach 25% by 2035. This is driven by an ageing population and increasing rates of diabetes, hypertension, and obesity. The UK faces similar pressures, with CKD affecting over 10% of its population and costing the National Health Service an estimated GBP7 billion annually. To address this, the Discover-NOW programme in North West London developed a transformative project, bringing together partners across both primary and secondary care. This project aims to identify barriers that prevent optimal management for those at risk of or already living with CKD, and to co-develop solutions to overcome them. Priorities identified were to improve the identification and screening of patients with CKD, support accurate coding and documentation of CKD in primary care, enhance patient understanding and self-management of kidney disease, and promote treatment optimisation of CKD patients within primary care. Key innovations included electronic searches to identify undiagnosed, uncoded, and unoptimised CKD; integration of automated diagnostic guidance into laboratory results; creation of educational materials; and embedding decision-support templates aligned with the latest evidence-based guidelines into electronic medical records. This initiative provides transferable insights into how healthcare systems across the world can integrate early CKD detection, system-wide data integration, and population-level prevention strategies to strengthen the capacity of primary care in the management of early CKD, eventually shifting from a reactive dialysis-centric model towards proactive kidney preservation.

The pathogenesis of pulmonary hypertension associated with heart failure (PH-HF) is partially understood. To advance knowledge in this regard, the investigator-initiated, public-funded, prospective, translational stuDy to dISseCt remOdeling of capillaries and Veins in pulmonary hypErtension associated with heaRt failure (DISCOVER PH-HF) will assess biomarkers of PH-HF in pulmonary capillary and venous (PCV) and peripheral venous blood taken during right heart catheterization (RHC). This report presents the design of DISCOVER PH-HF and the baseline characteristics of the included patients. DISCOVER PH-HF enrolled heart failure&#xa0;patients scheduled for transcatheter edge-to-edge repair (TEER) of severe mitral regurgitation. PCV and peripheral venous whole blood was collected during RHC within 48&#x200a;h before mitral regurgitation (MR)-TEER, and processed into plasma/serum aliquots and peripheral blood mononuclear cell (PBMC) pellets. Then, the samples were centralized to a core biobank. Follow-up entails visits at 90&#x200a;&#xb1;&#x200a;10 and 180&#x200a;&#xb1;&#x200a;10&#x200a;days and - optionally - a second RHC with collection of PCV and peripheral venous blood within 30&#x200a;days from the second follow-up evaluation. A proteomic analysis of part of the PCV and peripheral plasma is already planned. Seven patients without pulmonary hypertension&#xa0;at RHC, 12 patients with isolated postcapillary pulmonary hypertension, and 18 patients with combined postcapillary and precapillary pulmonary hypertension&#xa0;were recruited, leading to a total of 148 PCV and 148 peripheral plasma aliquots, 111 PCV and 111 peripheral serum aliquots, and 37 PBMC pellets. DISCOVER PH-HF has generated a limited-size, but unique biobank of RHC-derived PCV and peripheral venous blood samples and PBMCs, linked to clinical and hemodynamic phenotyping, which will allow the exploration of biomarkers of PH-HF and its subtypes.

Chemicals can perturb gene functions to affect chronic human diseases, and a significant amount of biological knowledge involved in environmental health is available in public databases. Combining information across resources can assist in the discovery of novel testable hypotheses related to how chemical exposures influence human diseases, such as autism. The Comparative Toxicogenomics Database (CTD) is a public resource that provides curated content for chemicals, genes, phenotypes, diseases, and exposures. The AOP-Wiki is a repository of adverse outcome pathways (AOPs) that provide defined biological frameworks describing disease processes. Here, we intersect CTD toxicogenomic content with the AOP-Wiki to identify environmental chemicals that could potentially modulate key steps in autism. We identify numerous chemical stressors that intersect with the individual events of the autism AOP, including bisphenol compounds, per/polyfluoroalkyl substances, pesticides, metals, and air pollutants, suggesting a wide range of environmental factors that could synergize to potentially affect autism. By integrating additional CTD curated content for three autism-associated chemicals (bisphenol A, particulate matter, and valproic acid), we discover other mechanisms, including specific genes (e.g., SLC1A1, GSTP1, CNTNAP2) and phenotypes (e.g., lipid metabolism, inflammatory response, social behavior) that can be used to help refine or expand this AOP or create an entirely new pathway for autism. Furthermore, related diseases are identified to build interconnected networks, mechanistically linking autism to fatty liver disease, intellectual disability, and cancer. We demonstrate the value of integrating content from different resources to address environmental health questions related to autism etiology and co-morbidities. Importantly, our methodology is easily adapted for any AOP in the AOP-Wiki to identify potential environmental influences on the disease process and help support or refine AOPs. This analysis underscores the importance of standardizing public databases to make them efficiently interoperable for enhanced shared utility across the numerous bioknowledge digital landscapes.

Given the impact of kinetoplastid diseases, the limited therapeutic options and risk of treatment failure, continued research efforts to discover novel drug entities are required. The ambition to deliver drug development candidates has mainly been taken on board by academia and public private partnerships, but remains highly challenging because of the lack of adequate funding and standardized laboratory procedures. Establishing a systematic roadmap of experiments and decision criteria to attain high-quality leads and drug candidates with lower risk profiles remains the logical path to deliver more compelling proof-of-concepts for impactful diseases, such as African trypanosomiasis, Chagas disease and visceral and cutaneous leishmaniasis. In a three-part series, a structured roadmap from 'hit finding' to 'drug development candidate' is presented with a focus on the minimal essential data package, laboratory experimental models and endpoints. Part 1 introduces the concept of a pragmatic framework with reference to specific preclinical R&D stages: (i) hit finding, (ii) hit profiling, (iii) lead definition and (iv) drug development candidate to support a more focused early development path that remains accessible to engaged stakeholders. The experiment-oriented roadmap is presented in the next parts addressing the discovery and characterization of confirmed hits (Part 2) and the lead discovery phase towards identification of a drug development candidate (Part 3). Although specifically focusing on kinetoplastid diseases, the principles also apply to small-molecule preclinical R&D against other microbial diseases, evidently with specific adaptation of the primary pharmacology models.

Identifying physiological sweet spots (optimal ranges for homeostasis) is essential for precision medicine. However, traditional statistical methods often rely on globally linear or locally jagged models that struggle to capture the smooth, non-linear nature of biological regulation in high-dimensional data. We present the Quantile Feature Selection Network (Q&#x2011;FSNet), a neural network-based framework that integrates quantile regression, feature selection, and uncertainty estimation to identify biomarkers with sweet spots. Unlike traditional methods, Q-FSNet learns continuous response curves without requiring a pre-specified number of change points. We further introduce Quantile Dirichlet Network (Q-DirichNet), a fully Bayesian extension that utilizes Dirichlet priors to automate feature shrinkage. Using data from the Canadian Longitudinal Study on Aging, we identified 25 metabolites with distinct homeostatic ranges for which biological age acceleration is minimized. The metabolites with sweet spots for biological aging include some derived from diet or produced by the gut microbiome; this highlights their potential for knowledge translation and public health impact. Our results, corroborated by existing literature, demonstrate that these sparse neural network-based methods offer a scalable and interpretable tool for discovering metabolic signatures of healthy aging vs. dysregulation in large-scale omics research.

While linear mixed-effects (LME) models are common for analyzing longitudinal data, most users rely on random intercepts or simple stationary covariance, due to unavailability of computationally tractable solutions. Here, we extend the Fast and Efficient Mixed-Effects Algorithm (FEMA) and present FEMA-Long, a computationally tractable approach to flexibly modeling longitudinal covariance suitable for high-dimensional data. FEMA-Long can: i) model unstructured covariance, ii) model covariates as smooth functions using splines, iii) discover time-dependent effects of covariates with spline interactions, and iv) use these flexible longitudinal modeling strategies to perform longitudinal genome-wide association studies and discover time-dependent genetic effects, in a computationally scalable manner, suitable for high-dimensional data. Through extensive simulations, we show that estimates from FEMA-Long are accurate, while being up to several thousand times faster and with minimal carbon footprint. To show the utility of FEMA-Long for discovering novel biological signal, using data from the Norwegian Mother, Father and Child Cohort Study (MoBa), we performed a longitudinal genome-wide association study with non-linear SNP-by-time interaction on length, weight, and BMI of 68,273 infants with up to six measurements in the first year of life. We found dynamic patterns of random effects including time-varying heritability and genetic correlations, as well as several genetic variants showing time-dependent effects, highlighting the applicability of FEMA-Long to enable novel discoveries.

Tetramethylenedisulfotetramine (TETS) is a highly neurotoxic rodenticide and a potential terror agent to national security that can cause death within hours. Therefore, antibody-based guidance for timely determination and treatment is urgently demanded. Discovery of antibody against TETS as a hapten molecule remains a highly challenging, since immunized libraries are often recognized chemical linker or carrier epitopes of hapten-protein conjugates, resulting in an exceedingly low frequency of hapten-specific B cells. Here, we proposed a novel integrated strategy combining next-generation sequencing (NGS) and in vitro random mutagenesis, first successfully discovered the TETS-specific nanobodies (Nbs) within 16 days. The workflow began with the antisera evaluation by identification of IgG subclasses, followed by the enrichment of TETS-specific B cells using a fluorescence-activated cell sorter (FACS). Subsequently, these enriched cells were subjected to NGS to discover TETS-specific Nbs. To improve the affinity of Nbs, an error-prone PCR-based random mutagenesis step with an optimized moderate mutation rate was introduced. Through this strategy, we successfully identified the TETS-specific Nb A104, exhibiting a dissociation constant (KD) of 14.9 nM. Sequence analysis revealed distinct amino acid preferences across both the FR and the CDR of Nbs. Notably, inappropriate amino acid substitutions would compromise the affinity of Nbs. Finally, a chemiluminescent ELISA was developed based on the A104, achieving limits of detection (LODs) of 43 &#x3bc;g/L, 64 &#x3bc;g/L, and 101 &#x3bc;g/L for TETS in grain, human plasma, and human urine, respectively. The results demonstrated that this strategy was a feasible, efficient, and robust platform for the discovery of Nbs against haptens.

Dysfunctional autophagy, a key cellular cleaning process, is a key driver of brain ageing and neurodegenerative diseases such as Alzheimer's disease (AD). However, developing effective treatments by enhancing autophagy has been challenging, as most known compounds act through the broad mTOR pathway, risking side effects, and few can effectively penetrate the brain. To address this, we developed DeepDrugDiscovery-a mechanism-aware, AI-powered screening platform incorporating ADMET and blood-brain barrier penetrability predictions. Here we show that this platform successfully identified novel, mTOR-independent autophagy enhancers, with two lead compounds demonstrating an ability to cross the blood-brain barrier, clear AD-related protein aggregates and restore memory function in worm and mouse AD models. By releasing DeepDrugDiscovery as an open-source, modular tool, we offer a user-friendly AI platform that enables customized therapeutic screening. Our work establishes a scalable, AI-driven pipeline that integrates cross-species validation to rapidly discover mechanism-based therapeutics for diseases with high unmet medical need.

The post-acute sequelae of SARS-CoV-2 infection (PASC), or long COVID, represent a multifaceted challenge in pediatric populations, characterized by symptoms persisting beyond the acute phase. In Taiwan, where early public health measures initially contained the pandemic, the 2022 Omicron surge prompted focused investigation into pediatric PASC, highlighting the critical need for longitudinal data in this specific demographic. To address this challenge, the Diagnosis and Support for COVID Children to Enhance Recovery (DISCOVER) study was established as a prospective, multidisciplinary cohort. By employing a multimodal approach, this study characterizes the clinical landscape of pediatric PASC in Taiwan through validated screening instruments, AI-driven diagnostics, and pulmonary assessments, while concurrently evaluating immune biomarkers, vaccination protection, and vitamin D intervention. This review synthesizes comprehensive findings from the cohort. While the acute phase of infection was predominantly mild, a substantial proportion of children experienced persistent multisystem symptoms, with fatigue, respiratory issues, and somatic complaints being most prevalent. Vaccination was found to significantly modify the disease trajectory, offering protection against subsequent gastrointestinal sequelae and preserving pulmonary function by mitigating small airway resistance. Furthermore, advanced diagnostic modalities, including impulse oscillometry and deep learning-assisted echocardiography, successfully unmasked subclinical organ dysfunction that conventional methods often failed to detect. Mechanistic investigations revealed that symptom severity was closely linked to elevated anti-nucleocapsid antibody titers, while markers of T-cell exhaustion evidenced persistent immune dysregulation, rather than ongoing viral replication. Notably, a preliminary single-center randomized controlled trial within this cohort provided early evidence that vitamin D supplementation may reduce the overall symptom burden and modulate pro-inflammatory cytokine profiles in children with PASC. Collectively, these findings underscore the multisystem nature and immune-driven mechanism of pediatric PASC, while highlighting the role of vaccination, advanced diagnostics, and targeted nutritional interventions in improving recovery. CLINICAL TRIAL REGISTRATION: NCT05426291 (ClinicalTrials.gov).

Spatial biomarkers are critical for precision oncology but remain challenging to systematically discover due to the complexity of whole-slide images. We present PathPrism, an interpretable AI framework for spatial biomarker discovery and virtual experimentation. Unlike black-box models, PathPrism encodes tissue architecture into pathologically informed spatial features, enabling transparent modeling of prognosis, molecular alterations, and therapy response. Applied to 7,000 patients with colorectal cancer across 11 cohorts, PathPrism uncovered hundreds of biomarkers predictive of survival, MSI, BRAF, and TP53 mutations, and stratified chemotherapy benefit in stage II/III disease. Building on these interpretable findings, PathPrism uses large language models as auxiliary tools to generate hypotheses grounded in spatial semantics. We further introduce VirtualWSI, a platform for semantic perturbation within an interpretable spatial biomarker atlas. PathPrism provides a scalable and interpretable framework for spatial biomarker discovery.

Cancer stem cells (CSCs) are metabolically different from differentiated tumour cells, which are known as bulk cells. In this communication, we discuss the metabolic and biological differences between bulk tumour cells and CSCs. We further aim to discuss how plant metabolites can reorchestrate CSC signalling pathways, pushing these metabolically precarious cells towards differentiation and cell death. We delineate how plant metabolites curcumin, resveratrol, epigallocatechin gallate (EGCG) and genistein alter signaling in CSCs. The chemotherapeutic and chemopreventive potential of plant metabolites is also discussed, along with an analysis of how this field is going to progress with reference to drug discovery.

Mutational processes, such as the molecular effects of carcinogenic agents or defective DNA repair mechanisms, produce different mutation types with characteristic frequency profiles, known as mutational signatures. Non-negative matrix factorization (NMF) has been successfully used to discover many mutational signatures, yielding novel insights into cancer etiology and informing targeted therapies. However, the NMF model is only a rough approximation to reality, and even small departures from this assumed model can have large negative effects on the accuracy and reliability of the results. We propose BayesPowerNMF, a Bayesian NMF method that provides nonparametric robustness to model misspecification, principled automated selection of the number of latent processes, and uncertainty quantification of model parameters. In extensive simulation studies, we find that our proposed approach recovers more true signatures with greater accuracy than current leading methods. On whole-genome sequencing data for six cancer types from the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes Consortium, we find that our method is able to accurately recover more signatures than the current state-of-the-art.