Allergic disease prevalence has increased globally with the subset of type 2 inflammatory diseases playing a substantial role. Type 2 inflammatory diseases may differ in clinical presentation, but they exhibit shared pathophysiology that is targeted by the unique pharmacology of dupilumab. Dupilumab binds to the interleukin (IL)-4 receptor alpha subunit (IL-4Rα) that blocks IL-4 and IL-13 signaling, two key drivers of type 2 inflammation. Herein, we review the mechanism of action and pharmacology of dupilumab, and the clinical evidence that led to the regulatory approvals of dupilumab for the treatment of numerous type 2 inflammatory diseases: atopic dermatitis, asthma, chronic rhinosinusitis with nasal polyposis, eosinophilic esophagitis, and prurigo nodularis.

Food insecurity is a pervasive problem that impacts health and well-being across the lifespan. The human research linking food insecurity to poor metabolic and behavioral health outcomes is inherently correlational and suffers from a high degree of variability both between households and even within the same household over time. Further, food insecurity is impacted by societal and political factors that are largely out of the control of individuals, which narrows the range of intervention strategies. Animal models of food insecurity are being developed to address some of the barriers to mechanistic research. However, animal models are limited in their ability to consider some of the more complex societal elements of the human condition. We believe that understanding the role that food insecurity plays in ingestive behavior and chronic disease requires a truly translational approach, and that understanding the health impacts of this complex social phenomenon requires understanding both its psychological and physiological dimensions. This brief review will outline some key features of food insecurity, highlighting those that are amenable to investigation with controlled animal models and identifying areas where integrating animal and human studies can improve our understanding of the psychological burden and health impacts of food insecurity. In the interest of brevity, this review will largely focus on food insecurity in the United States, as the factors that contribute to food insecurity vary considerably across the globe.

In this article, the authors summarize the current state of translational science for esophageal and gastric cancers. The available targeted therapies, immunotherapies, and recently discovered molecular targets are reviewed. The authors introduce circulating tumor deoxyribonucleic acid and its promise as a biomarker to detect disease recurrence. The authors present patient-derived organoids as a new model for studying carcinogenesis and treatment responses. Finally, we discuss the implications of organoid models for precision oncology and describe exciting new work applying gene editing technology to organoids and studying tumor-microenvironment interactions using 3-dimensional co-culture systems.

BACKGROUND: We aimed to develop the first machine learning models to predict citation counts and the translational impact, defined as inclusion in guidelines or policy documents, of headache research, and assess which factors are most predictive.
METHODS: Bibliometric data and the titles, abstracts, and keywords from 8600 publications in three headache-oriented journals from their inception to 31 December 2017 were used. A series of machine learning models were implemented to predict three classes of 5-year citation count intervals (0-5, 6-14 and, >14 citations); and the translational impact of a publication. Models were evaluated out-of-sample with area under the receiver operating characteristics curve (AUC).
RESULTS: The top performing gradient boosting model predicted correct citation count class with an out-of-sample AUC of 0.81. Bibliometric data such as page count, number of references, first and last author citation counts and h-index were among the most important predictors. Prediction of translational impact worked optimally when including both bibliometric data and information from the title, abstract and keywords, reaching an out-of-sample AUC of 0.71 for the top performing random forest model.
CONCLUSIONS: Citation counts are best predicted by bibliometric data, while models incorporating both bibliometric data and publication content identifies the translational impact of headache research.

OBJECTIVE: Without strategic actions in its support, the translation of scientific research evidence into health policy is often absent or delayed. This review systematically maps and assesses national-level strategic documents in the field of knowledge translation (KT) for health policy, and develops a practical template that can support Evidence-informed Policy Network (EVIPNet) Europe countries in producing national strategies for evidence-informed policy-making.
METHODS: Websites of organizations with strategic responsibilities in KT were electronically searched, on the basis of pre-defined criteria, in July-August 2017, and an updated search was carried out in April-June 2021. We included national strategies or elements of national strategies that dealt with KT activities, as well as similar strategies of individual institutions with a national policy focus. Two reviewers screened the strategies for inclusion. Data were analysed using qualitative content analysis.
RESULTS: A total of 65 unique documents were identified, of which 17 were eligible and analysed for their structure and content. Of the 17, 1 document was a national health KT action plan and 6 documents were institution-level KT strategies. The remaining 10 strategies, which were also included were 2 national health strategies, 5 national health research strategies and 3 national KT strategies (not specific to the field of health alone). In all, 13 structural elements and 7 major themes of health policy KT strategies were identified from the included documents.
CONCLUSIONS: KT in health policy, as emerged from the national strategies that our mapping identified, is based on the production and accessibility of policy-relevant research, its packaging for policy-making and the activities related to knowledge exchange. KT strategies may play different roles in the complex and context-specific process of policy-making. Our findings show that the main ideas of health-specific evidence-informed policy literature appear in these strategies, but their effectiveness depends on the way stakeholders use them. Specific knowledge-brokering institutions and organizational capacity, advocacy about the use of evidence, and close collaboration and co-decision-making with key stakeholders are essential in furthering the policy uptake of research results.

I was fortunate enough to start my career at what was the dawn of modern-day molecular biology and to apply it to an important health problem. While my early work focused on fundamental science, the desire to understand human disease better and to find practical applications for research discoveries resulted, over the following decades, in creating a stream of translational research directed specifically toward epithelial cancers. This could only have been possible through multiple collaborations. This type of team science would eventually become a hallmark of my career. With the development of higher throughput molecular techniques, the pace of research and discovery has quickened, and the concept of personalized medicine based on genomics is now coming to fruition. I hope my legacy will not just reflect my published works, but will also include the impact I have had on the development of the next generation of scientists and clinician scientists who inspired me with their dedication, knowledge, and enthusiasm.

BACKGROUND: The conventional methods and strategies used for knowledge translation (KT) in academic research often fall short in effectively reaching stakeholders, such as citizens, practitioners, and decision makers, especially concerning complex healthcare issues. In response, a growing number of scholars have been embracing arts-based knowledge translation (ABKT) to target a more diverse audience with varying backgrounds and expectations. Despite the increased interest, utilization, and literature on arts-based knowledge translation over the past three decades, no studies have directly compared traditional knowledge translation with arts-based knowledge translation methods. Thus, our study aimed to evaluate and compare the impact of an arts-based knowledge translation intervention-a circus show-with two traditional knowledge translation interventions (webinar and research report) in terms of awareness, accessibility, engagement, advocacy/policy influence, and enjoyment.
METHODS: To conduct this exploratory convergent mixed method study, we randomly assigned 162 participants to one of the three interventions. All three knowledge translation methods were used to translate the same research project: \"Rural Emergency 360: Mobilization of decision-makers, healthcare professionals, patients, and citizens to improve healthcare and services in Quebec\'s rural emergency departments (UR360).\"
RESULTS: The findings revealed that the circus show outperformed the webinar and research report in terms of accessibility and enjoyment, while being equally effective in raising awareness, increasing engagement, and influencing advocacy/policy. Each intervention strategy demonstrates its unique array of strengths and weaknesses, with the circus show catering to a diverse audience, while the webinar and research report target more informed participants. These outcomes underscore the innovative and inclusive attributes of Arts-Based Knowledge translation, showcasing its capacity to facilitate researchers\' engagement with a wider array of stakeholders across diverse contexts.
CONCLUSIONS: As a relevant first step and a complementary asset, arts-based knowledge translation holds immense potential in increasing awareness and mobilization around crucial health issues.

In August of 2023, the National Academies of Science, Engineering, and Medicine published a timely report titled \"Toward Equitable Innovation in Health and Medicine: A Framework.\" Here, we review some of the key contributions of the report, focusing on two dimensions of equity: input equity and deployment equity. We then use the example of new gene therapies to treat sickle cell disease (SCD) as a case study of input and deployment equity in translational research. The SCD case study illustrates the need for a kind of translational bioethics with deep understanding of lived experiences and clinical realities as well as a high degree of economic and policy sophistication.

The spinocerebellar ataxias (SCA) comprise a group of inherited neurodegenerative diseases. Machado-Joseph Disease (MJD) or spinocerebellar ataxia 3 (SCA3) is the most common autosomal dominant form, caused by the expansion of CAG repeats within the ataxin-3 (ATXN3) gene. This mutation results in the expression of an abnormal protein containing long polyglutamine (polyQ) stretches that confers a toxic gain of function and leads to misfolding and aggregation of ATXN3 in neurons. As a result of the neurodegenerative process, SCA3 patients are severely disabled and die prematurely. Several screening approaches, e.g., druggable genome-wide and drug library screenings have been performed, focussing on the reduction in stably overexpressed ATXN3(polyQ) protein and improvement in the resultant toxicity. Transgenic overexpression models of toxic ATXN3, however, missed potential modulators of endogenous ATXN3 regulation. In another approach to identify modifiers of endogenous ATXN3 expression using a CRISPR/Cas9-modified SK-N-SH wild-type cell line with a GFP-T2A-luciferase (LUC) cassette under the control of the endogenous ATXN3 promotor, four statins were identified as potential activators of expression. We here provide an overview of the high throughput screening approaches yet performed to find compounds or genomic modifiers of ATXN3(polyQ) toxicity in different SCA3 model organisms and cell lines to ameliorate and halt SCA3 progression in patients. Furthermore, the putative role of cholesterol in neurodegenerative diseases (NDDs) in general and SCA3 in particular is discussed.

Flow cytometry is a mainstay technique in cell biology research, where it is used for phenotypic analysis of mixed cell populations. Quantitative approaches have unlocked a deeper value of flow cytometry in drug discovery research. As the number of drug modalities and druggable mechanisms increases, there is an increasing drive to identify meaningful biomarkers, evaluate the relationship between pharmacokinetics and pharmacodynamics (PK/PD), and translate these insights into the evaluation of patients enrolled in early clinical trials. In this review, we discuss emerging roles for flow cytometry in the translational setting that supports the transition and evaluation of novel compounds in the clinic.