Chibuike Mbanefo

Introduction: Primary healthcare (PHC) systems in Sub-Saharan Africa (SSA) continue to prioritise reactive, curative models of care, despite the region’s pressing need for health-promotive and preventative strategies. Instead of disrupting the existing curative model, the expansion of digital health often automates old, treatment-oriented systems with a limited focus on creating new tools for preventive and health-promoting functions. While there is no shortage of reviews on digital health and telemedicine in SSA, these predominantly focus on curative care and service delivery within the walls of healthcare facilities. An understanding of how remotely provided preventive and health-promoting services can be implemented by PHC facilities to strengthen the PHC overall is currently lacking. Addressing this gap is critical for guiding research, policy and practice towards designing more preventive and proactive PHC service models. Methods and analysis: This protocol details a scoping review that will identify and establish what is currently known about the implementation and feasibility of remote preventive and digital health-promoting services as potential levers to strengthen PHC in SSA. The review will consolidate evidence on digital health initiatives for prevention and identify key opportunities, barriers and gaps in the current knowledge. Results will be analysed using quantitative summaries and qualitative thematic analysis. Ethics and dissemination: Ethical approval is not required as this study uses publicly available literature. The findings could guide policymakers, programme implementers and researchers in reorienting PHCs towards more preventive approaches. The findings of the proposed scoping review will be disseminated through publication in a peer-reviewed journal. Registration: The protocol is registered with the Open Science Framework (OSF: https://osf.io/8whkc/ ) to comply with methodological transparency and accountability.

Periodontal regeneration remains one of the most demanding challenges in oral bioengineering due to the structural complexity of the periodontium and the inflammatory microenvironment accompanying disease. Conventional surgical and pharmacological therapies often fail to achieve full restoration of bone, ligament and cementum, prompting the development of cell-based and biomaterial-assisted approaches. This review summarizes current advances in cellular technologies for periodontal regeneration, emphasizing the biological rationale, material design and delivery methods shaping next-generation treatments. We discuss stem-cell-based strategies employing periodontal ligament, dental pulp and mesenchymal stem cells, their paracrine and immunomodulatory roles, and how their therapeutic potential is enhanced through integration into engineered scaffolds. Recent progress in hydrogel systems, microspheres, decellularized matrices and 3D bioprinting is analyzed, highlighting how structural cues, bioactive nanoparticles and gene-modified cells enable multi-tissue regeneration. Emerging delivery and biofabrication techniques, from manual seeding to automated and in situ printing, are reviewed as key determinants of clinical translation. The convergence of bioprinting precision, immune-responsive biomaterials and personalized cellular constructs positions periodontal bioengineering as a rapidly maturing field with strong prospects for functional restoration of diseased oral tissues.

Delivering quality healthcare rests on multiple interactions between several actors. From providers and patients to insurers and policymakers, each contributes to a network of services that promote, maintain, and restore health. Digital platforms are emerging as an innovative approach to facilitate this collaboration. These platforms function as collaborative networks where independent actors integrate resources around a central platform to co-create value. However, despite the promise of digital platforms in healthcare, a critical knowledge gap persists on how actor roles evolve within platform ecosystems. This paper investigates the evolutionary dynamics of digital platform ecosystems in healthcare. The study presents a case study approach to systematically collect and analyse data on the five chronological stages of the Discovery ecosystem development. Through an event history analysis, we focus on (i) actors and roles enacted during ecosystem emergence, (ii) the timing of activities during the evolutionary stages, and (iii) discovery and the evolution of its platform ecosystem. The paper’s findings contribute to understanding actor roles, interactions, role diversity, and ecosystem activities during digital platform development. For managers and practitioners, our study underlines a model for building partnerships with technology providers, financial institutions and other stakeholders to co-create value and improve patient outcomes.

The usability and versatility of autoinjectors in managing chronic and autoimmune diseases have made them increasingly attractive in medicine. However, investigations into autoinjector designs require an understanding of the kinematic properties and fluid behaviour during injection. To optimise injection efficiency, this study develops a mathematical and computational fluid dynamics (CFD) model of an IM autoinjector by investigating the effects of viscosity, needle length, needle diameter, and medication volume on the injection process. The model was verified and validated using a comparator experiment and optimised using a parameter sensitivity analysis. The mathematical model results show plunger displacement increases linearly in low viscous fluids (v < 20 cP), allowing faster injections. CFD simulations show that high-viscosity fluids (v > 20 cP) reduce injectability and increase syringeability. Needle gauges below 20 exhibited constant dynamic pressure and negligible shear stress, while gauges between 20 and 25 showed higher shear stress and pressure variability. Longer needles and larger medication volumes increase dynamic pressure and shear stress, prolonging injection time. The mathematical and CFD models matched experimental measurements within a 1.1 % and 4.8 % margin of error, respectively. These findings inform the design of efficient autoinjectors, enhancing drug delivery, patient comfort, and compliance.