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Background Coproduction is defined as patients and clinicians collaborating equally and reciprocally in healthcare and is a crucial concept for quality improvement (QI) of health services. Learning Health Networks (LHNs) provide insights to integrate coproduction with QI efforts from programmes from various health systems.Objective We describe interventions to develop and maintain patient and family partner (PFP) coproduction, measured by PFP-reported and programme-reported scales. We aim to increase percentage of programmes with PFPs reporting active QI work within their programme, while maintaining satisfaction in PFP-clinician relationships.Methods Conducted in the Cystic Fibrosis Learning Network (CFLN), an LHN comprising over 30 cystic fibrosis (CF) programmes, people with CF, caregivers and clinicians cocreated interventions in readiness awareness, inclusive PFP recruitment, onboarding process, partnership development and leadership opportunities. Interventions were adapted by CFLN programmes and summarised in a change package for existing programmes and the orientation of new ones. We collected monthly assessments for PFP and programme perceptions of coproduction and PFP self-rated competency of QI skills and satisfaction with programme QI efforts. We used control charts to analyse coproduction scales and run charts for PFP self-ratings.Results Between 2018 and 2022, the CFLN expanded to 34 programmes with 52% having ≥1 PFP reporting active QI participation. Clinicians from 76% of programmes reported PFPs were actively participating or leading QI efforts. PFPs reported increased QI skills competency (17%–32%) and consistently high satisfaction and feeling valued in their work.Conclusions Implementing system-level programmatic strategies to engage and sustain partnerships between clinicians and patients and families with CF improved perceptions of coproduction to conduct QI work. Key adaptable strategies for programmes included onboarding and QI training, supporting multiple PFPs simultaneously and developing financial recognition processes. Interventions may be applicable in other health conditions beyond CF seeking to foster the practice of coproduction.

Abstract Introduction Asthma is characterized by preventable morbidity, cost, and inequity. We sought to build an Asthma Learning Health System (ALHS) to coordinate regional pediatric asthma improvement activities. Methods We generated quantitative and qualitative insights pertinent to a better, more equitable care delivery system. We used electronic health record data to calculate asthma hospitalization rates for youth in our region. We completed an “environmental scan” to catalog the breadth of asthma‐related efforts occurring in our children's hospital and across the region. We supplemented the scan with group‐level assessments and focus groups with parents, clinicians, and community partners. We used insights from this descriptive epidemiology to inform the definition of shared aims, drivers, measures, and prototype interventions. Results Greater Cincinnati's youth are hospitalized for asthma at a rate three times greater than the U.S. average. Black youth are hospitalized at a rate five times greater than non‐Black youth. Certain neighborhoods bear the disproportionate burden of asthma morbidity. Across Cincinnati, there are many asthma‐relevant activities that seek to confront this morbidity; however, efforts are largely disconnected. Qualitative insights highlighted the importance of cross‐sector coordination, evidence‐based acute and preventive care, healthy homes and neighborhoods, and accountability. These insights also led to a shared, regional aim: to equitably reduce asthma‐related hospitalizations. Early interventions have included population‐level pattern recognition, multidisciplinary asthma action huddles, and enhanced social needs screening and response. Conclusion Learning health system methods are uniquely suited to asthma's complexity. Our nascent ALHS provides a scaffold atop which we can pursue better, more equitable regional asthma outcomes.

Abstract Introduction Patient engagement has historically referenced engagement in one's healthcare, with more recent definitions expanding patient engagement to encompass patient advocacy work in Learning Health Networks (LHNs). Efforts to conceptualize and define what patient engagement means—and what successful patient engagement means—are, however, lacking and a barrier to meaningful and sustainable patient engagement via patient advisory councils (PACs) across LHNs. Methods Several co‐authors (Madeleine Huwe, Becky Woolf, Jennie David) are former ImproveCareNow (ICN) PAC members, and we integrate a narrative review of the extant literature and a case study of our lived experiences as former ICN PAC members. We present nuanced themes of successful patient engagement from our lived experiences on ICN's PAC, with illustrative quotes from other PAC members, and then propose themes and metrics to consider in patient engagement across LHNs. Results Successful patient engagement in our experiences with ICN's PAC reaches beyond the “levels of engagement” previously described in the literature. We posit that our successful patient/PAC engagement experiences with ICN represent key mechanisms that could be applied across LHNs, including (1) personal growth for PAC members, (2) PAC internal engagement/community, (3) PAC engagement and presence within the LHN, (4) local institutional engagement for those who participate in the LHN, and (5) tangible resources/products from PAC members. Conclusion Patient engagement in LHNs, like ICN, holds significant power to meaningfully shape and co‐produce healthcare systems, and engagement is undervalued and conceptualized dichotomously (eg, engaged or not engaged). Reconceptualizing successful patient/PAC engagement is critical in ongoing efforts to study, support, and understand mechanisms of sustainable and successful patient engagement. Having a modern, multidimensional definition for successful patient engagement in LHNs can support efforts to increase underrepresented voices in PACs, measure and track successful multidimensional patient engagement, and study how successful patient engagement may impact outcomes for patients and LHNs.

Abstract Introduction A learning health network is a type of learning health system in which stakeholders use network organization to improve health and health care. Building on existing resources in the cystic fibrosis (CF) community, the Cystic Fibrosis Learning Network (CFLN) was designed to improve medical outcomes and quality of life through an intentional focus on achieving reliable evidence‐based chronic care delivery and creating a system for data‐driven collaborative learning. Methods We describe the development and growth of the CFLN considering six domains of a Network Maturity Grid: system leadership; governance and policy management; quality improvement (QI); engagement and community building; data and analytics; and research. We illustrate the impact of the CFLN experience on chronic care processes and indicators of collaborative infrastructure. Results The CFLN represents 36 accredited care centers in the CF Foundation Care Center Network caring for over 6300 patients. Of 6779 patient clinical care visits/quarter, 77% are entered into the CF Foundation Patient Registry within 30 days, providing timely means to track outcomes. Collaborative visit planning is occurring in 93% of clinical care visits to share agenda setting with patients and families. Almost all CFLN teams (94%, n = 34) have a patient/family partner (PFP), and 74% of PFPs indicate they are actively participating, taking ownership of, or leading QI initiatives with the interdisciplinary care team. In 2022, 97% of centers reported completing 1–13 improvement cycles per month, and 82% contributed to monthly QI progress reports to share learning. Conclusion The CFLN is a maturing, collaborative infrastructure. CFLN centers practice at an advanced level of coproduction. The CFLN fosters interdisciplinary and PFP leadership and the performance of consistent data‐driven improvement cycles. CFLN centers are positioned to respond to rapid changes in evidence‐based care and advance the practice of QI and implementation science on a broader scale.

Abstract Introduction The Cystic Fibrosis (CF) Foundation sponsored the design, pilot testing, and implementation of the CF Learning Network (CFLN) to explore how the Foundation's Care Center Network (CCN) could become a learning health system. Six years after the design, the Foundation commissioned a formative mixed methods evaluation of the CFLN to assess: CFLN participants' understanding of program goals, attributes, and perceptions of current and future impact. Methods We performed semi‐structured interviews with CFLN participants to identify perceived goals, attributes, and impact of the network. Following thematic analyses, we developed and distributed a survey to CFLN members and a matched sample of CCN programs to understand whether the themes were unique to the CFLN. Results Interviews with 24 CFLN participants were conducted. Interviewees identified the primary CFLN goal as improving outcomes for people living with CF, with secondary goals of providing training in quality improvement (QI), creating a learning community, engaging all stakeholders in improvement, and spreading best practices to the CCN. Project management, use of data, common QI methods, and the learning community were seen as critical to success. Survey responses were collected from 103 CFLN members and 25 CCN members. The data revealed that CFLN respondents were more likely than CCN respondents to connect with other CF programs, routinely use data for QI, and engage patient and family partners in QI. Conclusions Our study suggests that the CFLN provides value beyond that achieved by the CCN. Key questions remain about whether spread of the CFLN could improve outcomes for more people living with CF.

BackgroundMindfulness can improve overall well-being by training individuals to focus on the present moment without judging their thoughts. However, it is unknown how much mindfulness practice and training are necessary to improve well-being. ObjectiveThe primary aim of this study was to determine whether a standard 8-session web-based mindfulness-based cognitive therapy (MBCT) program, compared with a brief 3-session mindfulness intervention, improved overall participant well-being. In addition, we sought to explore whether the treatment effects differed based on the baseline characteristics of the participants (ie, moderators). MethodsParticipants were recruited from 17 patient-powered research networks, web-based communities of stakeholders interested in a common research area. Participants were randomized to either a standard 8-session MBCT or a brief 3-session mindfulness training intervention accessed on the web. The participants were followed for 12 weeks. The primary outcome of the study was well-being, as measured by the World Health Organization—Five Well-Being Index. We hypothesized that MBCT would be superior to a brief mindfulness training. ResultsWe randomized 4411 participants, 3873 (87.80%) of whom were White and 3547 (80.41%) of female sex assigned at birth. The mean baseline World Health Organization—Five Well-Being Index score was 50.3 (SD 20.7). The average self-reported well-being in each group increased over the intervention period (baseline to 8 weeks; model-based slope for the MBCT group: 0.78, 95% CI 0.63-0.93, and brief mindfulness group: 0.76, 95% CI 0.60-0.91) as well as the full study period (ie, intervention plus follow-up; baseline to 20 weeks; model-based slope for MBCT group: 0.41, 95% CI 0.34-0.48; and brief mindfulness group: 0.33, 95% CI 0.26-0.40). Changes in self-reported well-being were not significantly different between MBCT and brief mindfulness during the intervention period (model-based difference in slopes: −0.02, 95% CI −0.24 to 0.19; P=.80) or during the intervention period plus 12-week follow-up (−0.08, 95% CI −0.18 to 0.02; P=.10). During the intervention period, younger participants (P=.05) and participants who completed a higher percentage of intervention sessions (P=.005) experienced greater improvements in well-being across both interventions, with effects that were stronger for participants in the MBCT condition. Attrition was high (ie, 2142/4411, 48.56%), which is an important limitation of this study. ConclusionsStandard MBCT improved well-being but was not superior to a brief mindfulness intervention. This finding suggests that shorter mindfulness programs could yield important benefits across the general population of individuals with various medical conditions. Younger people and participants who completed more intervention sessions reported greater improvements in well-being, an effect that was more pronounced for participants in the MBCT condition. This finding suggests that standard MBCT may be a better choice for younger people as well as treatment-adherent individuals. Trial RegistrationClinicalTrials.gov NCT03844321; https://clinicaltrials.gov/ct2/show/NCT03844321

Abstract Objective To establish a basis for a domain ontology ‐ a formal, explicit specification of a shared conceptualization ‐ of collaborative learning healthcare systems (CLHSs) in order to facilitate measurement, explanation, and improvement. Methods We adapted the “Methontology” approach to begin building an ontology of CLHSs. We specified the purpose of an ontology, acquired domain knowledge via literature review, conceptualized a common framework of CLHSs using a grounded approach, refined these concepts based on expert panel input, and illustrated concept application via four cases. Results The set of concepts identified as important to include in an ontology includes goals, values, structure, actors, environment, and products. To establish this set of concepts, we gathered input from content experts in two ways. First, expert panel methods were used to elicit feedback on these concepts and to test the elicitation of terms for the vocabulary of the Values concept. Second, from these discussions we developed a mapping exercise to test the intuitiveness of the concepts, requesting that network leaders from four CLHSs complete a mapping exercise to associate characteristics of their networks with the high‐level concepts, building the vocabulary for each concept in a grounded fashion. We also solicited feedback from these participants on the experience of completing the mapping exercise, finding that the exercise is acceptable and could aid in CLHS development and collaboration. Respondents identified opportunities to improve the operational definitions of each concept to ensure that corresponding vocabularies are distinct and non‐overlapping. Discussion Our results provide a foundation for developing a formal, explicit shared conceptualization of CLHSs. Once developed, such a tool can be useful for measurement, explanation, and improvement. Further work, including alignment to a top‐level ontology, expanding the vocabulary, and defining relations between vocabulary is required to formally build out an ontology for these uses.

Abstract Introduction Improving the U.S. healthcare system and health outcomes is one of the most pressing public health challenges of our time. Previously described Collaborative Learning Health Systems (CLHSs) are a promising approach to outcomes improvement. In order to fully realize this promise, a deeper understanding of this phenomenon is necessary. Methods We drew on our experience over the past decade with CLHSs as well as qualitative literature review to answer three questions: What kind of phenomena are CLHSs? and what is an appropriate scientific approach? How might we frame CLHSs conceptually? What are potential mechanisms of action? Results CLHSs are complex adaptive systems in which all stakeholders are able to collaborate, at scale, to create and share resources to satisfy a variety of needs. This is accomplished by providing infrastructure and services that enable stakeholders to act on their inherent motivations. This framing has implications for both research and practice. Conclusion Articulating this framework and potential mechanisms of action should facilitate research to test and refine hypotheses as well as guide practice to develop and optimize this promising approach to improving healthcare systems.

Abstract Background Collaborative Learning Health Systems (CLHS) improve outcomes in part by facilitating collaboration among all stakeholders. One way to facilitate collaboration is by creating conditions for the production and sharing of medical and non‐medical resources (information, knowledge, and knowhow [IKK]) so anybody can get “what is needed, when it's needed” (WINWIN) to act in ways that improve health and healthcare. Matching resources to needs can facilitate accurate diagnosis, appropriate prescribing, answered questions, provision of emotional and social support, and uptake of innovations. Objectives We describe efforts in ImproveCareNow, a CLHS improving outcomes in pediatric inflammatory bowel disease (IBD), to increase the number of patients and families creating and accessing IKK, and the challenges faced in that process. Methods We applied tactics such as outreach through trusted messengers, community organizing, and digital outreach such as sharing resources on our website, via social media, and email to increase the number of people producing, able to access, and accessing IKK. We applied an existing measurement system to track our progress and supplemented this with community feedback. Results In August of 2017 we identified and began measuring specific actions to track community growth. The number of patients and families producing IKK has increased by a factor of 2.7, using resources has increased by a factor of 4.1 and aware of resources as increased by a factor of 4.0. We identified challenges to measurement and scaling. Conclusions It is possible to intentionally increase the number of patients and caregivers engaged with a CHLS to produce and share resources to improve their health.

Abstract Introduction Improving the healthcare system is a major public health challenge. Collaborative learning health systems (CLHS) ‐ network organizations that allow all healthcare stakeholders to collaborate at scale ‐ are a promising response. However, we know little about CLHS mechanisms of actions, nor how to optimize CLHS performance. Agent‐based models (ABM) have been used to study a variety of complex systems. We translate the conceptual underpinnings of a CLHS to a computational model and demonstrate initial computational and face validity. Methods CLHSs are organized to allow stakeholders (patients and families, clinicians, researchers) to collaborate, at scale, in the production and distribution of information, knowledge, and know‐how for improvement. We build up a CLHS ABM from a population of patient‐ and doctor‐agents, assign them characteristics, and set them into interaction, resulting in engagement, information, and knowledge to facilitate optimal treatment selection. To assess computational and face validity, we vary a single parameter ‐ the degree to which patients influence other patients ‐ and trace its effects on patient engagement, shared knowledge, and outcomes. Results The CLHS ABM, developed in Python and using the open‐source modeling framework Mesa, is delivered as a web application. The model is simulated on a cloud server and the user interface is a web browser using Python and Plotly Dash. Holding all other parameters steady, when patient influence increases, the overall patient population activation increases, leading to an increase in shared knowledge, and higher median patient outcomes. Conclusions We present the first theoretically‐derived computational model of CLHSs, demonstrating initial computational and face validity. These preliminary results suggest that modeling CLHSs using an ABM is feasible and potentially valid. A well‐developed and validated computational model of the health system may have profound effects on understanding mechanisms of action, potential intervention targets, and ultimately translation to improved outcomes.

Abstract Background Patient and Family Advisory Councils (PFACs) are an emerging mechanism to integrate patient and family voices into healthcare. One such PFAC is the Patient Advisory Council (PAC) of the ImproveCareNow (ICN) network, a learning health system dedicated to advancing the care of individuals with pediatric inflammatory bowel disease (IBD). Using quality improvement techniques and co‐production, the PAC has made great strides in developing novel patient‐led resources. Methods This paper, written by patients and providers from ICN, reviews current ICN data on PAC‐generated resources, including creation processes and download statistics. Results Looking at different iterations of PAC infrastructure, this paper highlights specific leadership approaches used to increase patient involvement and improve resource creation. Emerging data suggests that the larger ICN learning health system has had limited interactions with these resources. Conclusion ICN provides a novel approach for meaningful integration of patient partners into learning health systems. This paper points to the incredible value of PFAC expertise in the resource creation process. Future work should seek to support PFAC development across other diseases and address the challenges of integrating patient‐led resources into clinical care.

Abstract Background Collaborative learning health systems have demonstrated improved outcomes for a range of different chronic conditions. Patient and healthcare provider engagement in these systems is thought to be associated with improved outcomes. We have adapted an observational framework to measure, and track over time, engagement in ImproveCareNow, a collaborative learning health system for children with inflammatory bowel disease. Introduction We developed a categorical classification scheme for engagement in ImproveCareNow. Each tier is defined in terms of observable individual behaviors. When an individual completes one or more qualifying behavior, s/he is classified as engaged at that tier. Individuals are entered into a database, which is accessible to care centers throughout the ImproveCareNow network. Database records include fields for individual name, behavior type, time, place, and level of engagement. Results The resulting system is employed at 79 ImproveCareNow care centers in the United States. The system recognizes four levels of engagement. Behaviors are recorded in a managed vocabulary and recorded in an online database. The database is queried weekly for individual engagement behaviors, which are tracked longitudinally. Center‐ and network‐level statistics are generated and disseminated to stakeholders. Conclusion It is possible to monitor longitudinal engagement in a collaborative learning health system, thereby charting progress toward engagement goals and enabling quantitative evaluation of interventions aimed at increasing engagement.

Abstract Background The vision of learning healthcare systems (LHSs) is attractive as a more effective model for health care services, but achieving the vision is complex. There is limited literature describing the processes needed to construct such multicomponent systems or to assess development. Methods We used the concept of a capability maturity matrix to describe the maturation of necessary infrastructure and processes to create learning networks (LNs), multisite collaborative LHSs that use an actor‐oriented network organizational architecture. We developed a network maturity grid (NMG) assessment tool by incorporating information from literature review, content theory from existing networks, and expert opinion to establish domains and components. We refined the maturity grid in response to feedback from network leadership teams. We followed NMG scores over time for nine LNs and plotted scores for each domain component with respect to SD for one participating network. We sought subjective feedback on the experience of applying the NMG to individual networks. Results LN leaders evaluated the scope, depth, and applicability of the NMG to their networks. Qualitative feedback from network leaders indicated that changes in NMG scores over time aligned with leaders' reports about growth in specific domains; changes in scores were consistent with network efforts to improve in various areas. Scores over time showed differences in maturation in the individual domains of each network. Scoring patterns, and SD for domain component scores, indicated consistency among LN leaders in some but not all aspects of network maturity. A case example from a participating network highlighted the value of the NMG in prompting strategic discussions about network development and demonstrated that the process of using the tool was itself valuable. Conclusions The capability maturity grid proposed here provides a framework to help those interested in creating Learning Health Networks plan and develop them over time.

Abstract Creating better value in health care service today is very challenging. The social pressure to do so is real for every health care system and its leadership. Real benefit has been achieved in manufacturing sector work by the use of “value‐chain” thinking, which assumes that the work is a series of linked processes necessary to make a product. For those activities in health care systems that are similar, this model may be very helpful. Attempts to “install” the value chain widely in health care systems have, however, been frustrating. As a result, well‐meaning leaders seeking better value have resorted to programs of cost reduction, rather than service redesign. Professionals have not been very happy or willing participants. The work of health care service invites an expanded model of value creation, one that better matches the work. This paper proposes a networked architecture that can mobilize and integrate the resources of health care professionals, interested patients, family, and other community members in the delivery and improvement of health care systems. It also suggests how this value‐creation architecture might contribute to research and the development of new knowledge. Two cases illustrate the proposed architecture and its implications for system design and practice, technology development, and roles and responsibilities of all actors involved in health care systems. We believe that this model better fits the need of making and improving health care services. This expanded understanding of how value is created invites attention by senior leaders, by those attempting to facilitate the improvement of current systems, by patients and clinicians involved in the daily work of health care service coproduction, by those charged with the preparation and formation of future professionals, by those who measure and conduct research in health care services, and by those leading policy, payment, and reimbursement systems.

Objectives To compare real-world effectiveness of two adaptive treatment strategies of disease-modifying antirheumatic drugs (DMARDs) in treating children with newly diagnosed polyarticular course juvenile idiopathic arthritis (pcJIA): early aggressive use of biologic DMARDs (bDMARDs) in combination with conventional synthetic DMARDs (csDMARDs) versus conservative delayed use of bDMARDs following the initial csDMARD prescription.Methods A single-centre newly diagnosed DMARD-naive pcJIA patient database (n=465) was derived from the electronic medical records between 1 January 2009 and 31 December 2018. The primary study endpoints were clinical Juvenile Arthritis Disease Activity Score (cJADAS) at 6 and 12 months following the first DMARD prescription. The secondary study endpoint was Pediatric Quality of Life Inventory (PedsQL) generic total score at 12 months. Averaged causal treatment effects were assessed using a Bayesian non-parametric casual inference method.Results Both cJADAS and PedsQL improve over time, regardless of the treatment strategies. Compared with the conservative approach, early aggressive approach is more effective in reducing cJADAS (mean −2.17, 95% CI −3.77 to −0.56) by 6 months. Adding bDMARD after 6 months to the initial treatment provides very little added benefit. The averaged treatment effect was 6.35 (95% CI −5.89 to 18.58) improvement in PedsQL at 12 months.Conclusions Timing matters—early aggressive use with bDMARDs is more effective than conservative delayed treatment in lowering disease activity after 6 and 12 months of treatment.

Abstract Background Collaborative learning health systems (CLHSs) enable patients, clinicians, researchers, and others to collaborate at scale to improve outcomes and generate new knowledge. An organizational framework to facilitate this collaboration is the actor‐oriented architecture, composed of (a) actors (people, organizations, and databases) with the values and abilities to self‐organize; (b) a commons where they create and share resources; and (c) structures, protocols, and processes that facilitate multiactor collaboration. CLHSs may implement a variety of changes to strengthen the actor‐oriented architecture and enable more actors to create and share resources. Objective To describe and measure implementation of elements of the actor‐oriented architecture in an existing Collaborative Learning Health System. Methods We used the case of ImproveCareNow, a CLHS improving outcomes in pediatric inflammatory bowel disease, founded in 2006. We traced several network‐level indicators of actor‐oriented architecture between 2010 and 2016. Results We identified measures of actors, the commons, and ways that have made it easier for network member sites to participate. These indicators show ImproveCareNow has made changes in the three elements of the actor‐oriented architecture over time. Conclusion It is possible to measure the implementation of an actor‐oriented architecture in a CLHS. The elements of the actor‐oriented architecture may provide a conceptual framework for their development and optimization. Metrics such as those described here may be actionable indicators of the “health of the system.”

Introduction: The Flexible Lifestyle Empowering Change Study (FLEX) is a multi-site randomized controlled trial to test the efficacy of an adaptive behavioral intervention to promote self-management and improve glycemic control for adolescents with type 1 diabetes mellitus. A two-step recruitment process was used to optimize study retention by facilitating informed decision-making regarding participation. Methods: Those who expressed interest at first contact were given more detailed study information followed by telephone calls to the adolescents and their parents to answer questions and explore potential barriers to participation before making a decision regarding study enrollment. Results: Of 694 eligible adolescents who were invited to participate, 397 (57.2%) expressed interest when initially contacted (Step 1). Upon completion of the follow-up telephone calls (Step 2), 276 (39.8%) still agreed to participate; and 258 (37.2%) enrolled and completed a baseline visit with a parent/guardian. Completion rates for measurement visits remained high throughout the study, with an end-of-study retention rate of 93.4%; and only 12 (4.7%) families withdrew from the study. Conclusion: The two-step recruitment process encourages potential participants to thoughtfully evaluate their willingness to participate, as well as their ability to make a commitment to the full completion of study requirements. When demonstrating the efficacy of a randomized controlled trial, it may be preferable to accept lower recruitment rates in order to optimize retention rates. The additional time and effort required to implement this two-step process is worthwhile. With a high retention rate, we can be more confident that the outcomes of the randomized controlled trial actually reflect the impact of the intervention. Keywords: Recruitment, Retention, Adolescent, Type 1 diabetes, Randomized controlled trial

Abstract Bone infections are still a major problem in surgery. To avoid severe side effects of systemically administered antibiotics, local antibiotic therapy is increasingly being considered. Using a pressure-based method developed in our group, microporous β-TCP ceramics, which had previously been characterized, were loaded with 2% w/v alginate containing 50 mg/mL clindamycin and 10 µg/mL rhBMP-2. Release experiments were then carried out over 28 days with changes of liquid at defined times (1, 2, 3, 6, 9, 14, 21 and 28d). The released concentrations of clindamycin were determined by HPLC and those of rhBMP-2 by ELISA. Continuous release (anomalous transport) of clindamycin and uniform release (Fick’s diffusion) of BMP-2 were determined. The composites were biocompatible (live/dead, WST-I and LDH) and the released concentrations were all antimicrobially active against Staph. aureus. The results were very promising and clindamycin was detected in concentrations above the MIC as well as a constant rhBMP-2 release over the entire study period. Biocompatibility was also not impaired by either the antibiotic or the BMP-2. This promising approach can therefore be seen as an alternative to the common treatment with PMMA chains containing gentamycin, as the new composite is completely biodegradable and no second operation is necessary for removal or replacement. Graphical Abstract

Abstract Intense convective mixing in the central North Atlantic is a major gateway for dissolved organic matter (DOM) into the deep ocean, sustaining elevated dissolved organic carbon (DOC) concentrations. Rapid down‐slope transport on adjacent Irish and Hebrides Margins represents another, less‐explored mechanism contributing to the deep‐sea DOM reservoir. Our analyses of solid‐phase extractable DOM (SPE‐DOM) in bottom waters in this region showed 7–11 μM higher DOC concentration and 190–330 years youngerSPE‐DOM radiocarbon ages compared to similar depths in the open eastern North Atlantic. We estimated a down‐slope DOC flux of 43 Tg C yr−1 from the Irish and Hebrides shelves. During transport, conservative mixing, dominated by physical rather than biological/chemical processes, determined the molecular DOM composition, while minor particulate organic matter degradation introduced less‐refractory DOM with terrigenous characteristics. Thus, rapid down‐slope transport emerges as an efficient conduit for delivering fresh DOM into the deep ocean.

Portable visible-to-near-infrared (VNIR) and mid-infrared (MIR) spectroscopy coupled with machine learning can provide detailed and inexpensive information on various key soil properties. However, on-site VNIR and MIR proximal sensing applications are hampered by soil moisture and particle size variations, which distort reflectance spectra collected on field-condition soils and impede the integration of established MIR and VNIR soil spectral libraries in predictive models for field measurements.In this study, we explored the capacity of various machine-learning approaches to calibrate VNIR-MIR models for the prediction of soil organic carbon and phospholipid fatty acid (PLFA)-derived microbial soil properties with field-condition spectral data. We further evaluated the potential to integrate soil spectral libraries into VNIR-MIR proximal sensing applications by testing the transfer of VNIR-MIR models calibrated on pre-treated soil samples to field-condition VNIR-MIR scans using the External Parameter Orthogonalization (EPO) approach to minimize soil moisture and particle size effects.We compiled a diverse soil dataset encompassing a wide range of organic matter content, soil texture, and parent material from soils under grassland and arable land use (n = 175). VNIR-MIR models were used to predict soil organic carbon (SOC), bacterial biomass (BAC), fungal biomass (FUN), and different soil quality indicators (C:N, Fungal-to-bacterial ratio, gram-positive-to-gram-negative ratio) for both field-condition and pre-treated soil spectral data. Calibrations were developed with Partial Least Squares Regression (PLSR), Random Forest (RF), Elastic Net (ENET), Cubist, Support Vector Machines (SVM), and an Ensemble-GLM. We further tested the effectiveness of coupling each machine-learning model with the EPO algorithm to transfer models calibrated on pre-treated soils to field-condition scans.Our results show that machine learning methods such as Cubist and SVM readily outperformed the standard PLSR calibration, with average improvements of ΔRMSE ∼15 % for pre-treated soils and ΔRMSE ∼10 % for field-condition samples. Ensemble-GLM models were about as accurate as the best individual model in each case but did not yield further improvements. The direct calibration transfer from laboratory calibrations to field-condition spectra exhibited very low accuracy. The EPO approach improved model transfer results significantly (ΔRMSE ∼40 %) but was still less accurate than predictive models using spectra from pre-treated soils (ΔRMSE ∼18 %).Our findings highlight the benefits of employing a diverse set of machine-learning algorithms and model ensembles for improved VNIR-MIR calibrations of soil properties and demonstrate that the EPO transform is effective in removing moisture and particle size effects from VNIR and MIR soil spectra collected in field-condition. This opens the opportunity to integrate archived local soil data or extensive soil spectral libraries into proximal soil sensing applications with portable VNIR and MIR spectrometers to facilitate the acquisition of high-quality soil information at high spatiotemporal resolution directly in the field.

Abstract Background Antibiotic-containing carrier systems are one option that offers the advantage of releasing active ingredients over a longer period of time. In vitro sustained drug release from a carrier system consisting of microporous β-TCP ceramic and alginate has been reported in previous works. Alginate dialdehyde (ADA) gelatin gel showed both better mechanical properties when loaded into a β-TCP ceramic and higher biodegradability than pure alginate. Methods Dual release of daptomycin and BMP-2 was measured on days 1, 2, 3, 6, 9, 14, 21, and 28 by HPLC and ELISA. After release, the microbial efficacy of the daptomycin was verified and the biocompatibility of the composite was tested in cell culture. Results Daptomycin and the model compound FITC protein A (n = 30) were released from the composite over 28 days. A Daptomycin release above the minimum inhibitory concentration (MIC) by day 9 and a burst release of 71.7 ± 5.9% were observed in the loaded ceramics. Low concentrations of BMP-2 were released from the loaded ceramics over 28 days.

Abstract β-TCP ceramics are versatile bone substitute materials and show many interactions with cells of the monocyte-macrophage-lineage. The possibility of monocytes entering microporous β-TCP ceramics has however not yet been researched. In this study, we used a model approach to investigate whether monocytes might enter β-TCP, providing a possible explanation for the origin of CD68-positive osteoclast-like giant cells found in earlier works. We used flow chambers to unidirectionally load BC, PRP, or PPP into slice models of either 2 mm or 6 mm β-TCP. Immunofluorescence for CD68 and live/dead staining was performed after the loading process. Our results show that monocytes were present in a relevant number of PRP and BC slices representing the inside of our 2 mm slice model and also present on the actual inside of our 6 mm model. For PPP, monocytes were not found beyond the surface in either model. Our results indicate the possibility of a new and so far neglected constituent in β-TCP degradation, perhaps causing the process of ceramic degradation also starting from inside the ceramics as opposed to the current understanding. We also demonstrated flow chambers as a possible new in vitro model for interactions between blood and β-TCP.

Abstract Fluorescence analysis of β-TCP ceramics is often used to describe cells found on said ceramics. However, we found, to our knowledge, so far undescribed artifacts which might sometimes be hard to differentiate from cells due to shape and fluorescence behavior. We tried prolonged ultrasound washing as well as Technovit 9100 fixation to reduce these artifacts. While untreated dowels showed no reduction in artifacts no matter the further treatment, Technovit fixation reduced the artifacts with even further reduction achieved by mechanical cleaning. As a consequence, scientists working with these dowels and likely even other types should try to avoid creating false positive results by considering the existence of these artifacts, checking additional filters for unusual fluorescence and by reducing them by using Technovit fixation when possible.

Introductionβ-TCP ceramics are bone replacement materials that have recently been tested as a drug delivery system that can potentially be applied to endogenous substances like growth factors found in blood platelets to facilitate positive attributes.MethodsIn this work, we used flow chamber loading to load β-TCP dowels with blood suspensions of platelet-rich plasma (PRP), platelet-poor plasma (PPP), or buffy coat (BC) character. PRP and BC platelet counts were adjusted to the same level by dilution. Concentrations of TGF-β1, PDGF-AB, and IGF-1 from dowel-surrounding culture medium were subsequently determined using ELISA over 5 days. The influence of alginate was additionally tested to modify the release.ResultsConcentrations of TGF-β1 and PDGF-AB increased and conclusively showed a release from platelets in PRP and BC compared to PPP. The alginate coating reduced the PDGF-AB release but did not reduce TGF-β1 and instead even increased TGF-β1 in the BC samples. IGF-1 concentrations were highest in PPP, suggesting circulating levels rather than platelet release as the driving factor. Alginate samples tended to have lower IGF-1 concentrations, but the difference was not shown to be significant.DiscussionThe release of growth factors from different blood suspensions was successfully demonstrated for β-TCP as a drug delivery system with release patterns that correspond to PRP activation after Ca2+-triggered activation. The release pattern was partially modified by alginate coating.

IntroductionIntervertebral disk degeneration is a growing problem in our society. The degeneration of the intervertebral disk leads to back pain and in some cases to a herniated disk. Advanced disk degeneration can be treated surgically with either a vertebral body fusion or a disk prosthesis. Vertebral body fusion is currently considered the gold standard of surgical therapy and is clearly superior to disk prosthesis based on the number of cases. The aim of this work was the 3D printing of Gyroid structures and the determination of their mechanical properties in a biomechanical feasibility study for possible use as an intervertebral disc prosthesis.Material and methodsCreo Parametric 6.0.6.0 was used to create models with various Gyroid properties. These were printed with the Original Prusa i3 MK3s+. Different flexible filaments (TPU FlexHard and TPU FlexMed, extrudr, Lauterach, Austria) were used to investigate the effects of the filament on the printing results and mechanical properties of the models. Characterization was carried out by means of microscopy and tension/compression testing on the universal testing machine.ResultsThe 3D prints with the FlexHard and FlexMid filament went without any problems. No printing errors were detected in the microscopy. The mechanical confined compression test resulted in force-deformation curves of the individual printed models. This showed that changing the Gyroid properties (increasing the wall thickness or density of the Gyroid) leads to changes in the force-deformation curves and thus to the mechanical properties.ConlcusionThe flexible filaments used in this work showed good print quality after the printing parameters were adjusted. The mechanical properties of the discs were also promising. The parameters Gyroid volume, wall thickness of the Gyroid and the outer wall played a decisive role for both FlexMed and FlexHard. All in all, the Gyroid structured discs (Ø 50 mm) made of TPU represent a promising approach with regard to intervertebral disc replacement. We would like to continue to pursue this approach in the future.

Legionella pneumophila are pathogenic bacteria that repeatedly occur in high concentrations in the process water of evaporative cooling systems (ECS). When released into the environment, the resulting bioaerosols can cause outbreaks with fatal consequences. The official, internationally accepted detection method for Legionella spp. in water samples is based on cultivation. However, cultivation is time-consuming and may underestimate the total count of viable L. pneumophila in ECS. Therefore, culture-independent methods are receiving attention for rapid monitoring. Cartridge-based immunomagnetic separation (IMS) coupled with flow cytometry (FCM) is an innovative, antibody-based method for the culture-independent quantification of L. pneumophila, using a panel of antibodies against serogroup (Sg) 1–15. We characterized the IMS-FCM method as a quantitative rapid test by general analytical procedures. Viable cryopreserved L. pneumophila standards were used in calibration experiments for the method. We achieved detection limits for Sg 1, Sg 4, and Sg 6 of 100, 105 and 88 viable cells per 100 mL, respectively. Furthermore, we demonstrated the practical applicability of IMS-FCM with real ECS samples and compared the performance against cultivation. Cultivation showed here no positive results, but IMS-FCM evidenced L. pneumophila in a range of 0–80,000 viable cells per 100 mL. This work demonstrates that IMS-FCM is a suitable, culture-independent, quantitative method for rapidly monitoring L. pneumophila.