UNASSIGNED: Photoacoustic imaging (PAI) is an emerging technology that holds high promise in a wide range of clinical applications, but standardized methods for system testing are lacking, impeding objective device performance evaluation, calibration, and inter-device comparisons. To address this shortfall, this tutorial offers readers structured guidance in developing tissue-mimicking phantoms for photoacoustic applications with potential extensions to certain acoustic and optical imaging applications.
UNASSIGNED: The tutorial review aims to summarize recommendations on phantom development for PAI applications to harmonize efforts in standardization and system calibration in the field.
UNASSIGNED: The International Photoacoustic Standardization Consortium has conducted a consensus exercise to define recommendations for the development of tissue-mimicking phantoms in PAI.
UNASSIGNED: Recommendations on phantom development are summarized in seven defined steps, expanding from (1) general understanding of the imaging modality, definition of (2) relevant terminology and parameters and (3) phantom purposes, recommendation of (4) basic material properties, (5) material characterization methods, and (6) phantom design to (7) reproducibility efforts.
UNASSIGNED: The tutorial offers a comprehensive framework for the development of tissue-mimicking phantoms in PAI to streamline efforts in system testing and push forward the advancement and translation of the technology.

BACKGROUND: The use of technologies has had a significant impact on patient safety and the quality of care and has increased globally. In the literature, it has been reported that people die annually due to adverse events (AEs), and various methods exist for investigating and measuring AEs. However, some methods have a limited scope, data extraction, and the need for data standardization. In Brazil, there are few studies on the application of trigger tools, and this study is the first to create automated triggers in ambulatory care.
OBJECTIVE: This study aims to develop a machine learning (ML)-based automated trigger for outpatient health care settings in Brazil.
METHODS: A mixed methods research will be conducted within a design thinking framework and the principles will be applied in creating the automated triggers, following the stages of (1) empathize and define the problem, involving observations and inquiries to comprehend both the user and the challenge at hand; (2) ideation, where various solutions to the problem are generated; (3) prototyping, involving the construction of a minimal representation of the best solutions; (4) testing, where user feedback is obtained to refine the solution; and (5) implementation, where the refined solution is tested, changes are assessed, and scaling is considered. Furthermore, ML methods will be adopted to develop automated triggers, tailored to the local context in collaboration with an expert in the field.
RESULTS: This protocol describes a research study in its preliminary stages, prior to any data gathering and analysis. The study was approved by the members of the organizations within the institution in January 2024 and by the ethics board of the University of São Paulo and the institution where the study will take place. in May 2024. As of June 2024, stage 1 commenced with data gathering for qualitative research. A separate paper focused on explaining the method of ML will be considered after the outcomes of stages 1 and 2 in this study.
CONCLUSIONS: After the development of automated triggers in the outpatient setting, it will be possible to prevent and identify potential risks of AEs more promptly, providing valuable information. This technological innovation not only promotes advances in clinical practice but also contributes to the dissemination of techniques and knowledge related to patient safety. Additionally, health care professionals can adopt evidence-based preventive measures, reducing costs associated with AEs and hospital readmissions, enhancing productivity in outpatient care, and contributing to the safety, quality, and effectiveness of care provided. Additionally, in the future, if the outcome is successful, there is the potential to apply it in all units, as planned by the institutional organization.
UNASSIGNED: PRR1-10.2196/55466.

暂无摘要。

Body composition (BC) measured by DXA differs between devices. We aimed to compare regional and total BC measurements assessed by the Hologic Horizon A and the GE Lunar iDXA devices; to determine device-specific calibration equations for each BC parameter; and to assess the impact of this standardization procedure on the assessment of sarcopenia, lipedema, obesity, and cardiovascular risk with DXA. A total of 926 postmenopausal women (aged 72.9 ± 6.9 yr, height 160.3 ± 6.6 cm, weight 66.1 ± 12.7 kg) underwent BC assessment on each device within 1 h, following the ISCD guidelines. The included sample was split into 80% train and 20% test datasets stratified by age, height, and weight. Inter-device differences in BC parameters were assessed with Bland-Altman analysis, Pearson or Spearman correlation coefficients, and t-tests or Wilcoxon tests. The equations were developed in the train dataset using backward stepwise multiple linear regressions and were evaluated in the test dataset with the R-squared and mean absolute error. We compared the abovementioned BC-derived health conditions before and after standardization in the test set with respect to relative risk, accuracy, Kappa score, and McNemar tests. Total and regional body masses were similar (p>.05) between devices. BMC was greater for all regions in the Lunar device (p<.05), while fat and lean masses differed among regions. Regression equations showed high performance metrics in both datasets. The BC assessment from Hologic classified 2.13 times more sarcopenic cases (McNemar: p<.001), 1.39 times more lipedema (p<.001), 0.40 times less high cardiovascular risk (p<.001), and similarly classified obesity (p>.05), compared to Lunar. After standardization, the differences disappeared (p>.05), and the classification metrics improved. This study discusses how hardware and software differences impact BC assessments. The provided standardization equations address these issues and improve the agreement between devices. Future studies and disease definitions should consider these differences.

Metadata describe and provide context for other data, playing a pivotal role in enabling findability, accessibility, interoperability, and reusability (FAIR) data principles. By providing comprehensive and machine-readable descriptions of digital resources, metadata empower both machines and human users to seamlessly discover, access, integrate, and reuse data or content across diverse platforms and applications. However, the limited accessibility and machine-interpretability of existing metadata for population health data hinder effective data discovery and reuse.
To address these challenges, we propose a comprehensive framework using standardized formats, vocabularies, and protocols to render population health data machine-readable, significantly enhancing their FAIRness and enabling seamless discovery, access, and integration across diverse platforms and research applications.
The framework implements a 3-stage approach. The first stage is Data Documentation Initiative (DDI) integration, which involves leveraging the DDI Codebook metadata and documentation of detailed information for data and associated assets, while ensuring transparency and comprehensiveness. The second stage is Observational Medical Outcomes Partnership (OMOP) Common Data Model (CDM) standardization. In this stage, the data are harmonized and standardized into the OMOP CDM, facilitating unified analysis across heterogeneous data sets. The third stage involves the integration of Schema.org and JavaScript Object Notation for Linked Data (JSON-LD), in which machine-readable metadata are generated using Schema.org entities and embedded within the data using JSON-LD, boosting discoverability and comprehension for both machines and human users. We demonstrated the implementation of these 3 stages using the Integrated Disease Surveillance and Response (IDSR) data from Malawi and Kenya.
The implementation of our framework significantly enhanced the FAIRness of population health data, resulting in improved discoverability through seamless integration with platforms such as Google Dataset Search. The adoption of standardized formats and protocols streamlined data accessibility and integration across various research environments, fostering collaboration and knowledge sharing. Additionally, the use of machine-interpretable metadata empowered researchers to efficiently reuse data for targeted analyses and insights, thereby maximizing the overall value of population health resources. The JSON-LD codes are accessible via a GitHub repository and the HTML code integrated with JSON-LD is available on the Implementation Network for Sharing Population Information from Research Entities website.
The adoption of machine-readable metadata standards is essential for ensuring the FAIRness of population health data. By embracing these standards, organizations can enhance diverse resource visibility, accessibility, and utility, leading to a broader impact, particularly in low- and middle-income countries. Machine-readable metadata can accelerate research, improve health care decision-making, and ultimately promote better health outcomes for populations worldwide.

UNASSIGNED: Knee osteoarthritis(KOA), a chronic degenerative disease, significantly impairs quality of life due to pain and mobility limitations. Traditional treatments focus on symptom management without addressing the underlying disease progression, leading to a growing interest in regenerative medicine approaches. Bone marrow aspirate concentrate (BMAC), rich in mesenchymal stem cells and growth factors, has shown potential for cartilage repair and symptom relief in KOA. Despite promising outcomes, the optimal BMAC dosage for knee OA treatment remains undetermined. This study aims to evaluate the radiological outcomes of varying BMAC dosages in knee OA treatment.
UNASSIGNED: This prospective controlled dose-escalation study involved 75 patients with early-stage knee OA, categorized into three groups based on BMAC dosage administered 10x106 cells (low-dose group), 50 × 106 cells (medium-dose group), or 100x106 cells (high-dose group). All the patients underwent a single intra-articular injection of BMAC and were monitored over a year. The primary outcomes include magnetic resonance observation of cartilage repair tissue (MOCART 2.0) score to assess the cartilage.
UNASSIGNED: We noted significant improvement in the overall MOCART score (p = 0.027) and subchondral change sub-score (p = 0.048) and defect filling sub-score (p = 0.025) in the medium- and high-dose cohorts compared to the low-dose cohort at 1 year follow-up. Although we noted positive correlation between the clinical and radiological outcome (r = 0.43), we did not find any significant different in the clinical outcome between the treatment groups.
UNASSIGNED: BMAC for OA knee resulted in significant improvement in the radiological scores compared to the baseline. Medium and high doses of BMAC result in significantly higher radiological scores compared to low-dose BMAC at 1 year. However, the radiological improvement did not translate into functional improvement, irrespective of the dosage administered at 1 year. Further research is necessary on the long-term outcomes to understand and optimize the dosing strategy based on clinico-radiological results.

UNASSIGNED: Knee osteoarthritis (KOA), a chronic degenerative disease, significantly impairs quality of life due to pain and mobility limitations. Traditional treatments focus on symptom management without addressing the underlying disease progression, leading to a growing interest in regenerative medicine approaches. Bone marrow aspirate concentrate (BMAC), rich in mesenchymal stem cells and growth factors, has shown potential for cartilage repair and symptom relief in KOA. Despite promising outcomes, the optimal BMAC dosage for knee OA treatment remains undetermined. This study aims to evaluate the clinical efficacy and safety of varying BMAC dosages in knee OA treatment.
UNASSIGNED: This prospective controlled dose-escalation study involved 75 patients with early-stage knee OA, categorized into three groups based on BMAC dosage administered 10 × 106 cells (low-dose group), 50 × 106 cells (medium-dose group), or 100 × 106 cells (high-dose group). All the patients underwent a single intra-articular injection of BMAC and were monitored over a year. The primary outcomes include Visual Analog Scale (VAS) for pain and the Knee Injury and Osteoarthritis Outcome Score (KOOS) for joint function recorded at baseline, 1, 3, 6, and 12 months post-intervention. Adverse events were also documented.
UNASSIGNED: Significant clinical improvements in VAS and KOOS scores were noted across all groups at all time points compared to the baseline. However, these improvements did not significantly differ between dosage groups throughout the follow-up period. Adverse effects were minimal and primarily consisted of transient post-injection pain and effusion, with no dose-dependent increase in complications.
UNASSIGNED: BMAC treatment for knee OA is safe and demonstrates potential for significant pain relief and functional improvement, irrespective of the dosage administered within the tested range. The lack of significant differences among varying dosages suggests a plateau in therapeutic efficacy beyond a certain threshold. Further research is necessary on the long-term outcomes to optimize the dosing strategy.

In vivo studies offer a detailed understanding of organism functioning, surpassing the insights provided by in vitro studies. These experiments are crucial for comprehending disease emergence, progression, and associated mechanisms in humans, as well as for developing treatments. When choosing experimental models, factors such as genomic similarity, physiological relevance, ethical appropriateness, and economic feasibility must be considered. Standardized protocols enhance the reliability, and reproducibility of scientific methods, promoting the assessment of research in the scientific literature. Researchers conducting embryo studies should establish and document standardized protocols for increased data comparability. Standardization is vital for scientific validity, reproducibility, and comparability in both in vivo and in vitro studies, ensuring the accuracy and reliability of experimental results and advancing scientific knowledge.

In order to ensure valid diagnostics for occupational test allergen solutions despite the ongoing reduction in the availability of commercial test extracts, a plan B was initiated for the possible production of skin prick test (SPT) solutions in public pharmacies. For important occupational allergen sources (wheat and rye, storage mites, animal epithelia, mold material) laboratory extraction methods were analyzed in comparison to pharmacy compatible extraction methods regarding protein quantity and quality in SDS-PAGE combined with silver staining. Subsequently, using the example of bovine epithelia, adapted extraction procedures as well as in-process and final product controls were transferred to a public pharmacy. Allergen sources with a high protein content, such as wheat and rye grains as well as storage mites, showed good comparability of the extractable protein quantity and protein pattern, regardless of the applied extraction method. In contrast, allergen source materials with a low total protein content, such as animal epithelia and molds, can benefit from laboratory extraction conditions such as mechanical disruption and specific buffer additives. In the qualitative protein silver staining, characteristic protein patterns were identified for each allergen source. Depending on the extraction method, only minor differences in total protein patterns were observed in animal epithelia and molds. Using source materials from two suppliers, the resulting allergen extracts displayed clear differences in protein content in storage mites and quantitative and qualitative differences in molds. A practical preparation attempt of SPT solutions in a public pharmacy was successful. SPT solutions prepared with adapted pharmacy extraction methods showed a comparable protein and Bos d 2 allergen content and equivalent qualities in the protein pattern compared to a previously available commercial SPT solution. Accordingly, it can be assumed that standardized SPT solutions with sufficient allergen quality for occupational allergen sources can be prepared in public pharmacies if certified allergen sources with appropriate protein content are available.

Ports play an important role in connecting the domestic and global economies. Zero emissions port models are actively developed and frequently utilized to fulfill economic objectives while reducing environmental effect. The cold ironing system is one of technological methods assisting ports in transitioning to zero emissions port models. Although a number of ports have successfully implemented it, many other seaports, particularly those in developing countries, continue to face numerous challenges in implementing cold ironing. The aim of this research is to investigate the factors influencing the adoption of cold ironing. The study used a quantitative method, conducting a survey of 215 port managers from the North, Central, and South of Vietnam. The findings indicate that economic incentives and regulation have a positive impact on the adoption of cold ironing at ports. While lack of initial capital and lack of standardization are barriers to the implementation of cold ironing. The last section will look over the study\'s results and implications in greater detail.