Organoids—three-dimensional structures derived from stem cells—are transforming biomedical research by modeling key aspects of human physiology and disease. By replicating native tissue architecture, cellular heterogeneity, and functional behavior, they provide human-relevant systems that address limitations inherent to conventional in-vitro and animal models.

Diabetes and cardiovascular disease are deeply interconnected conditions, characterized by shared, multi-organ pathophysiology. Organoid technologies offer unique opportunities to dissect disease mechanisms, evaluate therapeutic strategies, and develop personalized, physiologically relevant models. These systems enable the investigation of cardiometabolic processes in platforms that better reflect the complexity and progression of human disease.

Cardiovascular Diabetology welcomes original research articles, reviews, and meta-analyses for this Collection, which aims to highlight the use of organoid technologies in advancing our understanding of cardiovascular complications associated with diabetes.

Areas of interest include, but are not limited to:

- Organoid models of diabetic cardiomyopathy and heart failure

- Matrigel alternatives for organoid development

- Cell-cell and extracellular matrix interactions in organoids

- Organoid-based drug testing for cardiovascular diseases

- Organoid-on-chip systems for tissue crosstalk and perfusion3D bioprinting and tissue engineering for cardiovascular organoids

- Artificial intelligence–driven analysis of organoid function and phenotypes

- Organoid models of gestational diabetes–induced congenital heart disease

- Functional genomics using CRISPR in cardiovascular organoids

- Single-cell and spatial omics to map disease states in organoids

- Co-culture systems of vascular and pancreatic organoids to study metabolic-vascular crosstalk

- Organoid-based screening platforms for anti-diabetic and cardioprotective drugs

Submissions that contribute to conceptual clarity (e.g., distinctions between organoids and spheroids), incorporate multi-organ or metabolic system perspectives, or connect technological development with clinical or translational insights are especially welcome.

This Collection supports and amplifies research related to SDG 3, Good Health and Well-Being.

All submissions in this collection undergo the journal’s standard peer review process. Similarly, all manuscripts authored by a Guest Editor(s) will be handled by the Editor-in-Chief. As an open access publication, this journal levies an article processing fee (details here). We recognize that many key stakeholders may not have access to such resources and are committed to supporting participation in this issue wherever resources are a barrier. For more information about what support may be available, please visit OA funding and support, or email OAfundingpolicy@springernature.com or the Editor-in-Chief.

The persistent 17-year span between discovery and application of evidence in practice has been a rallying cry for implementation science. That frequently quoted time period often implies that implementation needs to occur faster. But what do we really know about the time required to implement new evidence-based practices into routine settings of care. Does implementation take 17 years? Is implementation too slow? Can it be accelerated? Or, does a slower pace of implementing new evidence-based innovations serve a critical function? In many cases—pandemics, health inequities, urgent social crises—pressing needs demand timely implementation of rapidly accruing evidence to reduce morbidity and mortality. Yet many central tenets of implementation, such as trust, constituent inclusion, and adaptation, take time and may require a slow pace to ensure acceptability and sustained uptake.

To date, little attention and scant data address the pace of implementation. Speed is a rarely studied or reported metric in implementation science. Few in the field can answer the question, “how long does implementation take?” Answering that question requires data on how long various implementation phases take, or how long it takes to achieve implementation outcomes such as fidelity, adoption, and sustainment. Importantly, we lack good data on how different implementation strategies may influence the amount of time to achieve given outcomes.

To advance knowledge about how long implementation takes and how long it “should optimally” take, this collection seeks to stimulate the publication of papers that can advance the measurement of implementation speed, along with the systematic study of influences on and impacts of speed across diverse contexts, to more adequately respond to emerging health crises and benefit from emerging health innovations for practice and policy. In particular, we welcome submissions on 1) methodological papers that facilitate development, specification, and reporting on metrics of speed, and 2) data-based research (descriptive or inferential) that reports on implementation speed metrics, contextual factors and/or active strategies that affect speed, or the effects of implementation speed on important outcomes in various contexts.

Areas of interest include but are not limited to:

• Data based papers documenting pace of moving through various implementation phases, and identifying factors (e.g., implementation context, process, strategies) that affect pace of implementation (e.g., accelerators and inhibitors)

• Data based papers from multi-site, including multi-national, studies comparing pace of innovation adoption, implementation, and sustainment across various contexts

• Data based papers reporting time to implementation in the face of urgent social conditions (e.g., climate change, disaster relief) Papers on how to accelerate time to delivery of treatment discoveries for specific health conditions (e.g., cancer, infectious disease, suicidality, opioid epidemic)

• Data based papers on the timeliness of policy implementation, including factors influencing the time from data synthesis to policy recommendation, and from policy recommendation to implementation

• Span of time needed to: achieve partner collaboration, including global health partnerships adapt interventions to make them more feasible, usable, or acceptable achieve specific implementation outcomes (e.g., adoption, fidelity, scale-up, sustainment) de-implement harmful or low-value innovations, or to identify failed implementation efforts

• Effect of implementation pace on attainment of key outcomes such as constituent engagement, intervention acceptability or sustainability, health equity, or other evidence of clinical, community, economic, and/or policy benefits.

• Papers addressing the interplay between pace and health equity, speed and sustainability, and other considerations that impact decision-making on implementation

• Methodological pieces that advance designs for testing speed or metrics for capturing the pace of implementation

• This Collection welcomes submission of a range of article types. Should you wish to submit to this Collection, please read the submission guidelines of the journal you are submitting to Implementation Science or Implementation Science Communications to confirm that type is accepted by the journal you are submitting to.

• Articles for this Collection should be submitted via our submission systems in Implementation Science or Implementation Science Communications. During the submission process you will be asked whether you are submitting to a Collection, please select "Advancing the Science and Metrics on the Pace of Implementation" from the dropdown menu.

• Articles will undergo the standard peer-review process of the journal they are considered in Implementation Science or Implementation Science Communications and are subject to all of the journal’s standard policies. Articles will be added to the Collection as they are published.

• The Editors have no competing interests with the submissions which they handle through the peer-review process. The peer-review of any submissions for which the Editors have competing interests is handled by another Editorial Board Member who has no competing interests.