Careful Balance Research Articles

An analysis of the virtual cardio-oncology research initiative (VICORI) resource: bleeding risk among cancer patients beyond 1-year post-myocardial infarction

Abstract Introduction Cardiovascular disease (CVD) and cancer are common causes of morbidity and mortality. Advancements in treatment strategies for both diseases have resulted in a growing population who live with both conditions. Myocardial infarction (MI) represents approximately 20% of all CVD admissions in cancer patients and 10% of patients who present with an acute MI have cancer. Managing MI patients with cancer require careful balancing of their ischaemic and bleeding risks. While dual antiplatelet therapy (DAPT) increases a patient’s bleeding risk, cancer patients are at further increased risk due to a range of direct and indirect cancer effects. While our recent studies demonstrated an increased bleeding risk in cancer patients in the 1st year after MI (the period of intensive APT), it is currently not known if this risk is sustained beyond this period. VICORI is the world’s first whole-country cardio-oncology research platform, linking data from the National Cancer Registration and Analysis Service, National Institute for Cardiovascular Outcomes Research and Hospital Episode Statistics [1]. We investigated the risk of bleeding among MI patients in the 2nd year post-MI, where a large majority of patients would have completed a course of DAPT, stratified by the presence or absence of cancer. Methods In this retrospective observational study, we investigated the risk of bleeding following an MI between 2006-2019, in patients with and without cancer. Cancer was defined as a diagnosis of cancer in the 1-year preceding MI. Patients who lived past the 1st year after MI were followed-up from 12 to 24 months after their MI. We used inverse probability weighting based on propensity scores to produce a balanced cohort of patients with and without cancer. Cox proportional hazard and flexible parametric modelling were used to investigate cancer as a predictor of bleeding. Subgroup analyses were performed on stent status, MI and cancer type. Results Of 506280 patients presenting with MI, 5666 (1.1%) had cancer while 500614 (98.9%) did not. Prostate (n=1377), colorectal (n=1024), lung (n=490), breast (n=448) and bladder (n=334) cancers were among the most common types of cancers. The rate (hazard) of bleeding in MI was higher in patients with cancer in the 2nd year post-MI (HR:1.42, 95%CI 1.29-1.56) compared to those without. From the flexible parametric survival analysis, the risk of bleeding in cancer patients in the 2nd year post-MI was lower compared to the 1st year but remained statistically significant compared to non-cancer patients. Conclusion In this large real-world study, cancer patients have a persistent, increased bleeding risk beyond the 1-year post-MI period, compared to those without cancer, and this risk differed by type of cancer. Further work is needed to identify specific patient characteristics in each patient sub-group which alters one’s ischaemic or bleeding risk so they can be balanced favourably with personalised strategies.

Alteration of the Intestinal Bacterial Community in Rainbow Trout (Oncorhynchus mykiss): The Role of Animal, Plant, and Microbial Diets

Intestinal bacterial community in rainbow trout (Oncorhynchus mykiss) is increasingly recognized as important for aquaculture and fish health. This review summarizes the current knowledge on how various feed components, including animal- and plant-derived ingredients, as well as other feed additives, influence the gut microbiota of rainbow trout. Studies using 16S rRNA gene profiling and metagenomics demonstrate how dietary changes affect the composition, diversity, and functionality of bacterial communities. The findings suggest that there is no single optimal alternative ingredient for fish feeds, but emphasize that the ratio of natural components plays a more significant role in shaping the intestinal bacterial community of trout. This balance is crucial for maintaining diversity, functionality, and overall fish health, thereby promoting growth and disease resistance, while enhancing aquaculture efficiency. The use of popular animal protein derived from the larva of Hermetia illucens increases the amount of Pseudomonadota, but the chitin they contain can prevent the absorption of nutrients. Thus, the development of optimal feed formulas requires careful selection and balancing of various natural ingredients to sustain a healthy microbiota and overall fish well-being.

Balanced-risk analysis in the engineering design of complex systems with extreme conditions

The engineering design of components and systems in a fusion power plant, an example of a complex system with extreme conditions, requires careful consideration and balance of the numerous associated risks. Key risks are observed from several perspectives and categorised as failure modes, situational and quality risks. Several methods exist for the separate consideration of these risks at the various design phases. However, an optimum approach is to consider all risks and balance the effects during the early design phase. The paper introduces a novel methodology to consider all associated risks at the conceptual design phase by combining a generalised Π-theorem and dimensional analysis for qualitative physics reasoning. The method is applied to a Balance of Plant components as a case study. Initial results show positive concurrent consideration and analysis of all risks in the conceptual stage.

A Siah3 of relief: A role for mitophagy as a fail-safe during developmental axon pruning.

Developmental axon pruning is controlled by a careful balance of pro- and anti-apoptotic signals, which are activated in response to external cues to sculpt mature neuronal circuitry. In this issue of Science Signaling, Abraham et al. define a safeguard against apoptotic axon pruning and illustrate that Siah3 represses Parkin-mediated mitophagy to control the availability of axonal mitochondria that activate the pruning process.

Blending Tradition and Technology: An Ethnographic Study of Gamelan Production at Bogor Gong Factory

This study aimed to uncover insights into how tradition and technology coexist in gamelan production, preserving cultural authenticity while embracing innovation. The research revealed a harmonious interplay between tradition and technology in the production of gamelan instruments at the Bogor Factory in Indonesia. With a historical legacy spanning 370 years, skilled artisans demonstrated an unwavering commitment to preserving Sundanese cultural heritage through traditional craftsmanship. This commitment coexists seamlessly with modern technology, exemplified by smartphone use for tonal fine-tuning. The five-stage manufacturing process highlights precision and artistry, striking a careful balance between tradition and innovation. Key figures like Mr. Krisna and Mr. Hidayat navigated technological challenges, solidifying the Gong Factory in Bogor as a living embodiment of Indonesia cultural richness, bridging the past and future with grace.

Harnessing Intellectual Property Rights for Endangered Species Conservation: Balancing Innovation with Biodiversity Protection

Protection of endangered species has now become an essential priority worldwide due to alarming rates of biodiversity destruction, largely because of habitat destruction, climate variation, pollution, and over-exploitation. Conventional conservation methods include protective legislation, habitat preservation, and international agreements. However, Intellectual Property Rights, hereinafter referred to as IPR, has emerged over the past few decades as an increasingly powerful yet complex tool for nature conservation. IPR can take the form of legal protections through the use of patents, trademarks, copyrights, and geographical indications that provide an incentive for the innovation and development of technologies that directly or indirectly assist in species conservation. Examples include Patents on the utilization of biotechnological innovations, such as genetically modified organisms engineered to increase the survival of threatened species, cloning, and cryopreservation techniques to preserve genetic material; and Trademarks to promote wildlife-friendly products. While IPR has great potential to boost the course of conservation, it is by no means devoid of challenges. Some of the major issues include ethical issues regarding the commodification of varieties of life, rights to genetic resources, and benefits sharing with Indigenous communities and countries rich in biodiversity. It, therefore, requires a careful balance between the drive for innovation and the imperative to protect biodiversity, and international frameworks navigate the complexities arising-in particular, the Convention on Biological Diversity and the Nagoya Protocol. This paper discusses the intersection of IPR and conservation through an analysis of legal regimes governing the area, benefits, and challenges associated with IPR in conservation, and ethical debates shaping its application. The paper points out, through case studies and legal precedents, how IPR can be made to align with the bigger conservation goals so that protection accorded to endangered species is sustainable and yet encourages innovation. Findings highlight that although IPR may act as a catalyst for technological advances supportive of conservation, it needs to be implemented with clear guidelines, ethical oversight, and strong international collaboration in order not to produce unintended consequences. The needed directions include the strengthening of regulatory frameworks, raising awareness, and equitable benefit-sharing to balance IPR with conservation goals. If managed judiciously, the ultimate synergy between IPR and conservation strategies promises to unleash innovations that could go a long way toward protecting and preserving the most threatened species of the world.

Leverage machine learning to identify key measures in hospital operations management: a retrospective study to explore feasibility and performance of four common algorithms

BackgroundMeasures in operations management are pivotal for monitoring and assessing various aspects of hospital performance. Existing literature highlights the importance of regularly updating key management measures to reflect changing trends and organizational goals. Advancements in machine learning (ML) have presented promising opportunities for enhancing the process of updating operations management measures. However, their specific application and performance remain relatively unexplored. We aimed to investigate the feasibility and effectiveness of using common ML techniques to identify and update key measures in hospital operations management.MethodsHistorical data on 43 measures on financial balance and quality of care under 4 categories were retrieved from the BI system of a regional health system in Central China. The dataset included 17 surgical and 15 non-surgical departments over 48 months. Four common ML techniques, linear models (LM), random forest (RF), partial least squares (PLS), and neural networks (NN), were used to identify the most important measures. Ordinary least square was employed to investigate the impact of the top 10 measures. A ground truth validation compared the ML-identified key measures against the humanly decided strategic measures from annual meeting minutes.ResultsFor financial balancing, inpatient treatment revenue was an important measure in 3/4 years, followed by equipment depreciation costs. The measures identified using the same technique differed between years, though RF and PLS yielded relatively consistent results. For quality of care, none of the ML-identified measures repeated over the years. Those consistently important over four years differed almost entirely among four techniques. On ground truth validation, the 2016–2019 ML-identified measures were among the humanly identified measures, with the exception of equipment depreciation from the 2019 dataset. All the ML-identified measures for quality of care failed to coincide with the humanly decided measures.ConclusionsUsing ML to identify key hospital operational measures is viable but performance of ML techniques vary considerably. RF performs best among the four techniques in identifying key measures in financial balance. None of the ML techniques seem effective for identifying quality of care measures. ML is suggested as a decision support tool to remind and inspire decision-makers in certain aspects of hospital operations management.

Integrating Tax Amnesty, CSR, and Emerging Technologies: Exploring Ethical challenges and Strategic Choices

This paper explores the complex relationship between tax amnesty programs and Corporate Social Responsibility (CSR), focusing on the ethical challenges businesses face as they navigate financial decisions and societal obligations. While tax amnesty offers financial relief, it raises significant concerns about ethical behavior and transparency. The evolution of CSR into a strategic priority necessitates a careful balance between financial goals and broader societal contributions. Emerging technologies, such as AI, blockchain, and data analytics, are transforming tax compliance and CSR practices by enhancing transparency and accountability, but they also introduce new ethical dilemmas. This study integrates theoretical frameworks with practical insights, highlighting the need for businesses to align tax amnesty participation with CSR objectives. Key themes include the role of emerging technologies, ethical decision-making, and the alignment of financial incentives with societal values. By examining these dynamics, the research contributes valuable insights into how businesses can effectively manage the intersection of tax amnesty and CSR, promoting ethical practices and societal well-being.

Dynamic Performance and Power Optimization with Heterogeneous Processing-in-Memory for AI Applications on Edge Devices

The rapid advancement of artificial intelligence (AI) technology, combined with the widespread proliferation of Internet of Things (IoT) devices, has significantly expanded the scope of AI applications, from data centers to edge devices. Running AI applications on edge devices requires a careful balance between data processing performance and energy efficiency. This challenge becomes even more critical when the computational load of applications dynamically changes over time, making it difficult to maintain optimal performance and energy efficiency simultaneously. To address these challenges, we propose a novel processing-in-memory (PIM) technology that dynamically optimizes performance and power consumption in response to real-time workload variations in AI applications. Our proposed solution consists of a new PIM architecture and an operational algorithm designed to maximize its effectiveness. The PIM architecture follows a well-established structure known for effectively handling data-centric tasks in AI applications. However, unlike conventional designs, it features a heterogeneous configuration of high-performance PIM (HP-PIM) modules and low-power PIM (LP-PIM) modules. This enables the system to dynamically adjust data processing based on varying computational load, optimizing energy efficiency according to the application’s workload demands. In addition, we present a data placement optimization algorithm to fully leverage the potential of the heterogeneous PIM architecture. This algorithm predicts changes in application workloads and optimally allocates data to the HP-PIM and LP-PIM modules, improving energy efficiency. To validate and evaluate the proposed technology, we implemented the PIM architecture and developed an embedded processor that integrates this architecture. We performed FPGA prototyping of the processor, and functional verification was successfully completed. Experimental results from running applications with varying workload demands on the prototype PIM processor demonstrate that the proposed technology achieves up to 29.54% energy savings.

Changing times: trends in risk classification, tumor upstaging, and positive surgical margins after radical prostatectomy - results from a contemporary National Cancer Database study

PurposeRecent advancements in screening, prostate MRI, robotic surgery, and active surveillance have influenced the profile of patients undergoing radical prostatectomy (RP). We sought to examine their impact on trends in clinicodemographic, risk classification, and adverse pathology in men undergoing surgery.MethodsWe queried the National Cancer Database for clinicodemographic, risk group, and pathology data in men undergoing upfront RP between 2006 and 2020. Patients were categorized by NCCN risk groups, and trends were assessed among 2006–2010, 2011–2015, and 2016–2020 periods. Endpoints included rates of pT3, positive surgical margins (PSM), pathologic upstaging, and Gleason grade group (GG) upgrading.Results610,762 patients were included. There were significant increases in African Americans (9.8–14.1%), comorbidities (2.1–5.2% with Charlson scores > 1), and robot-assisted RP (78–84%). Over the three time periods, high-risk cases increased from 15 to 20 to 27%, and intermediate-risk from 54 to 51 to 60%. Overall rates of pT3 rose from 20 to 38%, and PSM from 20 to 27% (p < 0.001). Pathologic upstaging increased in low (6–15%), intermediate (20–33%), and high-risk groups (42–58%) –p < 0.001. Gleason upgrading rose in low-risk (45–59%, p < 0.001), with slight reductions in the intermediate and high-risk groups.ConclusionsRecent trends in RP indicate a shift towards more advanced disease, evidenced by increasing rates of pT3, PSM, and pathologic upstaging across all NCCN risk groups. These findings emphasize the need for a careful balance in applying fascia and nerve-sparing techniques to avoid compromising oncological safety.

Impact of side chain length on the properties and alkaline fuel cell performance of OEG-grafted poly(terphenyl piperidinium) anion exchange membranes

In designing comb-shaped anion exchange membranes (AEMs), replacing alkyl side chains with ethylene glycol (EG)-based ones significantly enhances membrane properties and boosts AEM fuel cell performance. Although much research has focused on optimizing the placement of EG segments within the polymer matrix, the effect of EG chain length remains less explored. In this work, a series of poly(terphenyl piperidinium) AEMs with N-oligo(ethylene glycol) (OEG) terminal pendants having two to five EG repeating units were prepared by simple post-polymerization quaternization. The membrane properties showed a strong correlation with the length of the OEG side chains, influenced by both chemical composition and phase behavior. Among the OEG-grafted AEMs, PTP-OEG3 with moderate three EG repeating units, exhibited the best properties due to a careful balance between EG and cationic groups, leading to a favorable microphased separation. It achieved high hydroxide conductivity (114 mS cm−1 at 80 °C in water), robust mechanical strength (tensile strength >52 MPa), and good ex situ alkaline stability. As a result, the AEM fuel cells with the property-balanced PTP-OEG3 membrane achieved the highest peak power density of 976 mW cm−2. The in situ stability of these AEMs was also investigated. Evidently, understanding the optimal EG side chain length is an important criterion for designing AEM materials for alkaline fuel cells.

Highly Stretchable Composite Conductive Fibers (SCCFs) and Their Applications.

Stretchable composite conductive fibers (SCCFs) exhibit remarkable conductivity, stretchability, breathability, and biocompatibility, making them ideal candidates for wearable electronics and bioelectronics. The exploitation of SCCFs in electronic devices requires a careful balance of many aspects, including material selection and process methodologies, to address the complex challenges associated with their electrical and mechanical properties. In this review, we elucidate the conductive mechanism of SCCFs and summarize strategies for integrating various conductors with stretchable fibers, emphasizing the primary challenges in fabricating highly conductive fibers. Furthermore, we explore the multifaceted applications of SCCFs-based frameworks in wearable electronic devices. This review aims to emphasize the significance of SCCFs and offers insights into their conductive mechanisms, material selection, manufacturing technologies, and performance improvement. Hopefully, it can guide the innovative development of SCCFs and broaden their application potential.

Copyright as an Access Right: Concretizing Positive Obligations for Rightholders to Ensure the Exercise of User Rights

Abstract The legal frameworks that govern access to information are essential for safeguarding a sustainable, creative ecosystem. Institutions, such as libraries, research organizations, educational and other cultural heritage institutions, are gateways to diverse collections of scientific production, media and other cultural artefacts. Enabling access to creative works requires careful balancing of the interest of creators, producers of information, publishers and users of that information. While copyright law has traditionally recognized that rightholders enjoy exclusive rights, courts have only recently emphasized that users of works must also enjoy rights, which better reflects that copyright is based on a social contract with reciprocal obligations. This study explores what positive obligations must be imposed on rightholders as a consequence of the rights users enjoy under copyright law. Although specific access-enabling mechanisms already exist in EU copyright law, they are often not properly implemented or lack efficient enforcement tools. For that purpose, certain exceptions and limitations must be made mandatory, prohibitions on contractual override must apply horizontally, privileged institutions should enjoy enforceable rights to obtain copies on reasonable terms, and the existing ‘lending’ right must become a ‘right to lend’. Supporting these substantive changes is the proposal for a new governance structure for the EU copyright framework through the establishment of an independent EU regulatory body. It is only through a blend of changes that copyright can serve society and that a sound ecosystem for creators and creativity is set up making the EU fit for the knowledge economy.

CFD-based redesign of large industrial-scale cyclones

Cyclones represent a cost-effective solution employed for the separation of particles in gas-solid streams, wherein the enhancement of performance relies on the careful balance between pressure drop and collection efficiency. This study employs Computational Fluid Dynamics (CFD) techniques to numerically assess a large-scale first stage cyclone within a cement kiln cyclone tower. Investigating its reported low collection efficiency, we analyze the impact of geometric modifications aimed at enhancing cyclone performance. The introduction of a dipleg proves to be particularly effective, leading to a substantial increase in collection efficiency and a reduction in pressure drop. The most favorable cyclone configuration demonstrates a remarkable 6 % improvement in collection efficiency and a decrease in pressure drop of approximately 1 mbar. Consequently, particle emissions from the first-stage cyclone are reduced by approximately 30 %, while an increase in clinker production by approximately 100 tons per day is achieved. These findings showcase the potential for significant operational and environmental benefits through optimized cyclone design in cement manufacturing processes.

Personal finance tips for the early career radiologist and beyond.

This paper aims to provide a summary of the basics of personal finance, specifically as it pertains to medical trainees and early career physicians. While not sufficient by itself, it may serve as a jumping off point for further reading and investigation into different aspects of personal finance. It includes discussion of spending and saving, emergency funds, insurance, student loans, and investments and tax-advantaged retirement accounts. Graduating financially well-rounded radiologists and physicians allows for a more effective balance of patient care, education, family, and interests outside of work.

Artificial intelligence and health-related data: The patient's best interest and data ownership dilemma.

The rapid advancement of artificial intelligence (AI) in healthcare has the potential to revolutionize the global healthcare sector and medicine in general. However, integrating AI technologies in healthcare requires access to large amounts of personal health-related data (HRD), which raises concerns regarding confidential personal information considering unregulated and not transparent data ownership. Setting up the patient's welfare as an unquestionable principle, this commentary explores the various ethical aspects of using HRD in AI applications, focusing on informed consent, data ownership, data sharing, financial considerations, accountability, and ethical standards. Three models of potential collaboration between AI-specializing firms and healthcare providers are evaluated: the commercial model, the equitable profit-sharing model, and the public-funded non-profit model. Each model has its advantages and challenges, necessitating a careful balance between ethical considerations, financial implications, and technological advancements. Policymakers and healthcare regulators are urged to establish transparent legislation to safeguard patient privacy, ensure informed consent, and promote the responsible use of HRD in AI applications. This commentary emphasizes the importance of addressing ethical issues to protect basic patient rights, foster responsible collaborations, and ensure the ethical use of health-related data in AI-based healthcare applications. While the coexistence of regulated AI and healthcare professionals is inevitable for validating the cost-effectiveness of AI use in healthcare economics, the transparency of HRD sources is deemed of utmost importance in the best interest of the patient.

Sensor-Based Balance Training with Exergaming Feedback in Subjects with Chronic Stroke: A Pilot Randomized Controlled Trial.

As one of the leading causes of disability in the world, stroke can determine a reduction of balance performance with a negative impact on daily activity and social life. In this study, we aimed to evaluate the effects of sensor-based balance training with exergaming feedback on balance skills in chronic stroke patients. 21 individuals (11F, 57.14 ± 13.82 years) with a single event of ischemic stroke were randomly assigned to the sensor-based balance training group (SB-group) or the usual care balance training group (UC-group). Both groups received 10 add-on sessions with exergaming feedback (SB-group) or conventional training (UC-group). Clinical and instrumental evaluation was performed before (t0), after (t1), and after one month (t2) from intervention. Participation level was assessed using the Pittsburgh Rehabilitation Participation Scale at the end of each session. The SB-group showed an improvement in postural stability (p = 0.02) when compared to the UC-group. In the evaluation of motivational level, the score was statistically higher in the SB-group with respect to the UC-group (p < 0.01). Except for the improvement in postural stability, no difference was recorded in clinical score, suggesting a comparable gain in both groups. However, patients undergoing sensor-based training exhibited a higher participation score, ultimately indicating the use of this training to improve the adherence to rehabilitation settings, especially in patients with lower compliance.

Catheter-related deep vein thrombosis: Where are we at and where are we going? Updates and ongoing unmet clinical needs.

Catheter-related thrombosis (CRT) is one of the major complications affecting patients with indwelling venous catheters, usually involving the upper extremity deep venous system. This condition can lead to potentially life-threatening complications such as pulmonary embolism and sepsis. The risk of developing CRT varies depending on type of catheters and patient characteristics. Despite advances in materials and technologies, the actual incidence of CRT is still considerable. Available evidence on CRT management remains controversial, and clinical guidelines base their recommendations on data from non-catheter related upper extremity or lower extremity deep venous thromboses. This narrative review aims to describe the epidemiology of CRT, to review the available evidence on its management and to highlight the current unmet needs. No formal search strategy was applied for the revision of the literature. The main sources of information used were Medline and guidelines from international societies. The management of CRT requires a careful balance between the risk of thrombus progression, recurrent events, and systemic embolization and the increased bleeding risk in often fragile patients. Open issues include the optimal management of the catheter and the type and duration of anticoagulant therapy. Direct oral anticoagulants are increasingly prescribed, representing an important alternative to the standard of care low molecular weight heparins in selected cases. The development of new anticoagulant drugs such as factors XI and XII inhibitors may offer further advantages in this context. The management of CRT is still challenging with constant need for updated evidence to support tailored approaches.

DeCa360: Deadline-aware edge caching for two-tier 360° video streaming

Two-tier 360° video streaming provides a robust solution for handling inaccurate viewport prediction and varying network conditions. Within this paradigm, the client employs a dual-buffer mechanism consisting of a long buffer for panoramic basic-quality segments and a short buffer for high-quality tiles. However, designing an efficient edge caching strategy for two-tier 360° videos is non-trivial. First, as basic-quality segments and high-quality tiles possess different delivery deadlines as well as content popularity, ignoring these discrepancies may result in inefficient edge caching. Second, accurately predicting the popularity of 360° videos at a fine granularity of video segments and tiles remains a challenge. To address these issues, we present DeCa360, a deadline-aware edge caching framework for 360° videos. Specifically, we introduce a lightweight runtime cache partitioning approach to achieve a careful balance between improving the cache hit ratio and guaranteeing more on-time delivery of objects. Moreover, we design a content popularity prediction method for two-tier 360° videos that combines a learning-based prediction model with domain knowledge of video streaming, leading to improved prediction accuracy and efficient cache replacement. Extensive experimental evaluations demonstrate that DeCa360 outperforms all baseline algorithms in terms of byte-hit ratio and on-time delivery ratio, making it a promising approach for efficient edge caching of 360° videos.

Utilizing the determinants of healthy aging to guide the choice of social prescriptions for older adults.

Executive summary: The age of Canada's population is increasing, necessitating innovative methods and tools for assessing the needs of older adults and identifying effective health and social prescriptions. In Alberta, a community-based, senior-serving organization undertook the development and piloting of the Healthy Aging Asset Index, an assessment tool and social prescribing guide for use by a variety of professionals within the community. Tool development was rooted in medical complexity assessment and social work practice, and adhered to the determinants of healthy aging established by Alberta's Healthy Aging Framework, which is based on the determinants of healthy aging published by the World Health Organization. Results from the pilot showed improvement in the functionality of older adults within the determinants over time, as they were supported in addressing areas of personal vulnerability. Adopting tools such as the Healthy Aging Asset Index can bring cohesiveness to the support that older adults receive across the care continuum and has the potential to shift the balance of care away from the health system and towards the community, thus improving the capacity of health systems and government to meet the needs of Canada's older adults.