BACKGROUND: Addressing Indigenous food security and food sovereignty calls for community-driven strategies to improve access to and availability of traditional and local food. Participatory approaches that integrate Indigenous leadership have supported successful program implementation. Learning Circles: Local Healthy Food to School is a participatory program that convenes a range of stakeholders including food producers, educators and Knowledge Keepers to plan, implement and monitor local food system action. Pilot work (2014-2015) in Haida Gwaii, British Columbia (BC), showed promising results of the Learning Circles (LC) approach in enhancing local and traditional food access, knowledge and skills among youth and adolescents. The objective of the current evaluation was therefore to examine the process of scaling-up the LC vertically within the Haida Nation; and horizontally across three diverse First Nations contexts: Gitxsan Nation, Hazelton /Upper Skeena, BC; Ministikwan Lake Cree Nation, Saskatchewan; and Black River First Nation, Manitoba between 2016 and 2019.
METHODS: An implementation science framework, Foster-Fishman and Watson\'s (2012) ABLe Change Framework, was used to understand the LC as a participatory approach to facilitate community capacity building to strengthen local food systems. Interviews (n = 52), meeting summaries (n = 44) and tracking sheets (n = 39) were thematically analyzed.
RESULTS: The LC facilitated a collaborative process to: (1) build on strengths and explore ways to increase readiness and capacity to reclaim traditional and local food systems; (2) strengthen connections to land, traditional knowledge and ways of life; (3) foster community-level action and multi-sector partnerships; (4) drive actions towards decolonization through revitalization of traditional foods; (5) improve availability of and appreciation for local healthy and traditional foods in school communities; and (6) promote holistic wellness through steps towards food sovereignty and food security. Scale-up within Haida Gwaii supported a growing, robust local and traditional food system and enhanced Haida leadership. The approach worked well in other First Nations contexts, though baseline capacity and the presence of champions were enabling factors.
CONCLUSIONS: Findings highlight LC as a participatory approach to build capacity and support iterative planning-to-action in community food systems. Identified strengths and challenges support opportunities to expand, adopt and modify the LC approach in other Indigenous communities with diverse food systems.

This study aimed to develop a value-added bio-based polymer product for food packaging. Poly(3-hydroxybutyrate-co-3-hydroxyvalerate) (PHBV) is a promising bioplastic with limitations in processability and brittleness, which our group previously addressed by incorporating high-molecular-weight natural rubber (NR) compatibilized with peroxide and coagent. Yet, processability in an industrial setting proved difficult. Coffee oil epoxide (COE), a waste-derived plasticizer, was incorporated into the PHBV/NR/peroxide/coagent matrix via extrusion, and properties of resulting sheets were evaluated. COE incorporation significantly decreased the oxygen and water permeability of the PHBV/NR sheets. Maximum degradation temperature Tpeak (°C) increased by ~4.6 °C, and degree of crystallinity decreased by ~15.5% relative to pristine PHBV, indicating good thermal stability. Melting (Tm) and glass transition temperatures (Tg) of the PHBV/NR blend remained unchanged with COE incorporation. X-ray diffraction (XRD) revealed ~10.36% decrease in crystal size for the plasticized blend. Energy-dispersive X-ray analysis (EDAX) and scanning electron microscopy (SEM) confirmed good dispersion with no phase separation. The water uptake capacity of the plasticized blend was reduced by 61.02%, while surface contact angle measurements showed improved water resistance. The plasticized PHBV sheet shows promise for environmentally friendly packaging films due to its high thermal stability, effective barrier properties, and industrial scalability.

Advanced microbiome therapeutics have emerged as a powerful approach for the treatment of numerous diseases. While the genetic instability of genetically engineered microorganisms is a well-known challenge in the scale-up of biomanufacturing processes, it has not yet been investigated for advanced microbiome therapeutics. Here, the evolution of engineered Escherichia coli Nissle 1917 strains producing Interleukin 2 and Aldafermin were investigated in two strain backgrounds with and without the three error-prone DNA polymerases polB, dinB, and umuDC, which contribute to the mutation rate of the host strain. Whole genome short-read sequencing revealed the genetic instability of the pMUT-based production plasmid after serial passaging for approximately 150 generations using an automated platform for high-throughput microbial evolution in five independent lineages for six distinct strains. While a reduction of the number of mutations of 12%-43% could be observed after the deletion of the error-prone DNA polymerases, the interruption of production-relevant genes could not be prevented, highlighting the need for additional strategies to improve the stability of advanced microbiome therapeutics.

Numerous influential policy and scientific bodies are calling for more rapid advances in the scale-up of child and youth mental health services (CYMHS). A number of CYMHS innovations hold promise for advancing scale-up but little is known about how real-world efforts are progressing. We conducted a scoping review to identify promising approaches to CYMHS scale-up across the globe. Searches were completed in six databases (Academic Search Complete, CINAHL, MEDLINE, PsychInfo, PubMed, and Web of Science). Article selection and synthesis were conducted in accordance to the Preferred Reporting Items for Systematic Reviews and Meta-Analysis extension for Scoping Reviews (PRISMA-ScR) checklist. A second search focused on low-and-middle-income countries (LMIC) was conducted based on the Cochrane Library recommended search filters of the World Bank listed LMIC countries. Authors used a double coding strategy during the title/abstract and full-text review. Twenty-eight articles meeting the eligibility criteria were identified that described 22 initiatives (in 11 different countries). Our review found the majority of published scale-up studies in CYMHS were not informed by scale-up frameworks in design or reporting. The methods and outcomes used in the identified articles were highly variable and limited our ability to draw conclusions about comparative effectiveness although promising approaches emerged. Successes and failures identified in our review largely reflect consensus in the broader literature regarding the need for strategies to better navigate the complexities of system and policy implementation while ensuring CYMHS interventions fit local contexts.

BACKGROUND: Learning Health Systems (LHS) - characterised by cycles of evidence generation and application - are increasingly recognised for their potential to improve public health interventions and optimise health impacts; however there is little evidence of their application in the context of public health practice. Here, we describe how an Australian public health unit applied a LHS approach to successfully improve a model of support for implementation of a school-based physical activity policy.
METHODS: This body of work was undertaken in the context of a strong research-practice partnership. Core LHS capabilities included: i) partnerships and stakeholder engagement; ii) workforce development and learning health communities; iii) multi-disciplinary scientific expertise; iv) practice data collection and management system; v) evidence surveillance and synthesis; and vi) governance and organisational processes of decision making. Three cycles of data generation and application were used. Within each cycle, randomised controlled trials conducted in NSW primary schools were used to generate data on the support model\'s effectiveness for improving schools\' implementation of a government physical activity policy, its delivery costs, and process measures such as adoption and acceptability. Each type of data were analysed independently, synthesised, and then presented to a multi-disciplinary team of researchers and practitioners, in consult with stakeholders, leading to collaborative decisions for incremental improvements to the support model.
RESULTS: Cycle 1 tested the first version of the support model (composed of five implementation strategies targeting identified barriers of policy implementation) and showed the model\'s feasibility and efficacy for improving schools\' policy implementation. Data-informed changes were made to enhance impact, including the addition of three implementation strategies to address outstanding barriers. Cycle 2 (now, testing a package of eight implementation strategies) established the model\'s effectiveness and cost-effectiveness for improving school\'s policy implementation. Data-informed changes were made to reduce delivery costs, specifically adapting the costliest strategies to reduce in-person contact from external support personnel. Cycle 3 showed that the adaptations minimised the relative cost of delivery without adversely impacting on the effect.
CONCLUSIONS: Through this process, we identified an effective, cost-effective, acceptable and scalable policy implementation support model for service delivery. This provides important information to inform or support LHS approaches for other agencies seeking to optimise the health impact of evidence-based interventions.

Cell and gene therapies are an innovative solution to various severe diseases and unfulfilled needs. Adoptive cell therapy (ACT), a form of cellular immunotherapies, has been favored in recent years due to the approval of chimeric antigen receptor CAR-T products. Market research indicates that the industry\'s value is predicted to reach USD 24.4 billion by 2030, with a compound annual growth rate (CAGR) of 21.5%. More importantly, ACT is recognized as the hope and future of effective, personalized cancer treatment for healthcare practitioners and patients worldwide. The significant global momentum of this therapeutic approach underscores the urgent need to establish it as a practical and standardized method. It is essential to understand how cell culture conditions affect the expansion and differentiation of T-cells. However, there are ongoing challenges in ensuring the robustness and reproducibility of the manufacturing process. The current study evaluated various adoptive T-cell culture platforms to achieve large-scale production of several billion cells and high-quality cellular output with minimal cell death. It examined factors such as bioreactor parameters, media, supplements and stimulation. This research addresses the fundamental challenges of scalability and reproducibility in manufacturing, which are essential for making adoptive T-cell therapy an accessible and powerful new class of cancer therapeutics.

The assessment of human liver stem cells (HLSCs) as cell therapeutics requires scalable, controlled expansion processes. We first focused on defining appropriate process parameters for HLSC expansion such as seeding density, use of antibiotics, optimal cell age and critical metabolite concentrations in conventional 2D culture systems. For scale-up, we transferred HLSC expansion to multi-plate and stirred-tank bioreactor systems to determine their limitations. A seeding density of 4000 cells cm-2 was needed for efficient expansion. Although growth was not significantly affected by antibiotics, the concentrations of lactate and ammonia were important. A maximum expansion capacity of at least 20 cumulative population doublings (cPDs) was observed, confirming HLSC growth, identity and functionality. For the expansion of HLSCs in the multi-plate bioreactor system Xpansion (XPN), the oxygen supply strategy was optimized due to a low kLa of 0.076 h-1. The XPN bioreactor yielded a final mean cell density of 94 ± 8 × 103 cells cm-2, more than double that of the standard process in T-flasks. However, in the larger XPN50 device, HLSC density reached only 28 ± 0.9 × 103 cells cm-2, while the glucose consumption rate increased 8-fold. In a fully-controlled 2 L stirred-tank bioreactor (STR), HLSCs expanded at a comparable rate to the T-flask and XPN50 processes in a homogeneous microenvironment using advanced process analytical technology. Ultimately, the scale-up of HLSCs was successful using two different bioreactor systems, resulting in sufficient numbers of viable, functional and undifferentiated HLSCs for therapeutic applications.

The early detection of sickle cell disease (SCD) is vital to reduce mortality among affected children. Suriname currently lacks a newborn screening programme (NSP) for SCD. We performed a pilot programme to evaluate the scalability of such an initiative. Dried blood spots were collected from five birth centres and subjected to electrophoresis analysis. The programme scalability was evaluated using the non-adoption, abandonment, scale-up, spread, and sustainability framework. Challenges across six domains (illness, technology, value proposition, adopter system, organisation, and societal system), were categorised hierarchically as simple 😊, complicated 😐, or complex 😢. It has been proven that implementing programmes with mainly complicated challenges is difficult and those in mainly complex areas may be unachievable. SCD was detected in 33 of 5185 (0.64%) successfully screened newborns. Most of the domains were classified as simple or complicated. Disease detection and technology suitability for screening in Suriname were confirmed, with favourable parental acceptance. Only minor routine adjustment was required from the medical staff for programme implementation. Complex challenges included a reliance on external suppliers for technical maintenance, ensuring timely access to specialised paediatric care for affected newborns, and securing sustainable financial funding. Scaling up is challenging but feasible, particularly with a targeted focus on identified complex challenges.

The aim of this study was to rapidly develop a sufficiently robust andrographolide nanosuspension (AG-NS) system using hummer acoustic resonance (HAR) technology. The system can effectively improve the dissolution properties of AG, while having high stability and scale-up adaptability. The formulation of AG-NS was optimized in a high-throughput manner using HAR technology and the preparation process was optimized stepwise. Optimal AG-NS with Z-Ave = 223.99 ± 3.16 nm, PDI=0.095 ± 0.007 and zeta potential = -33.20 ± 0.58 mV was successfully prepared with Polyvinylpyrrolidone K30 and Sodium dodecyl sulfate. The optimal prescription was successfully scaled up 100 and 150 times using HAR technology, which was the initial exploration of its commercial scale production. AG-NS was solidified using freeze drying and fluid bed technology, respectively. The optimal AG-NS and its solidified products were exhaustively characterized using various analytical techniques. The high energy input of HAR technology and drying process converted part of the drug into the amorphous state. The in-vitro drug dissolution studies demonstrated relatively higher drug dissolution for AG-NS and its solidified products compared to controls at both the dissolution media (pH 1.2 buffer and pH 6.8 buffer). AG-NS and its solidified products successfully maintained their physical stability in short-term stability and accelerated stability experiments, respectively.

T-shaped partial least squares regression (T-PLSR) is a valuable machine learning technique for the formulation and manufacturing process development of new drug products. An accurate T-PLSR model requires experimental data with multiple formulations and process conditions. However, it is usually challenging to collect comprehensive experimental data using large-scale manufacturing equipment because of the cost, time, and large consumption of raw materials. This study proposes a hybrid modeling of T-PLSR and transfer learning (TL) to enhance the prediction performance of a T-PLSR model for large-scale manufacturing data by exploiting a large amount of small-scale manufacturing data for model building. The proposed method of T-PLSR+TL was applied to a practical case study focusing on scaling up the tableting process from an experienced compaction simulator to a less-experienced rotary tablet press. The T-PLSR+TL models achieved significantly better prediction performance for tablet quality attributes of new drug products than T-PLSR models without using large-scale manufacturing data with new drug products. The results demonstrated that T-PLSR+TL is more capable of addressing new drug products than T-PLSR by using small-scale manufacturing data to cover a scarcity of large-scale manufacturing data. Furthermore, T-PLSR+TL holds the potential to streamline formulation and manufacturing process development activities for new drug products using an extensive database.