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Objective: To assess the current trends in the field of artificial intelligence in medicine by analysing 100 most cited original articles relevant to the field., Methods: The bibliometric analysis was conducted in September 2022, and comprised literature search on Scopus database for original articles only. Google and Medical Subject Headings databases were used as resources to extract key words. In order to cover a broad range of articles, original studies comprising human as well as non-human subjects, studies without abstract and studies in languages other than English were part of the inclusion criteria. There was no specific time period applied to the search and no specific selection was done regarding the journals in the database. The screening was done using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines to extract the top 100 most cited articles in the field of artificial intelligence usage in medicine. Data was analysed using SPSS 23., Results: Of the 11,571 studies identified, 100(0.86%) were analysed in detail. The studies were published between 1986 and 2021, with a median of 43 citations (IQR 53) per article. The journal 'Artificial Intelligence in Medicine' accounted for the highest number 9(9%)) of articles, and the United States was the country of origin for most of the articles 36(36%)., Conclusion: The trends, development and shortcomings in field of artificial intelligence usage in medicine need to be understood to conduct an effective research in areas that still need attention, and to guide the authorities to direct their funding accordingly.

The sterile paper-plastic barrier system for packaging sterilized medical equipment is studied, the main factors affecting its breakdown are revealed, and the inhalation rate during the pressure sterilization is experimentally analyzed. The results offer a new window of opportunity for a stricter risk-analysis and a robust strategy for the pressure sterilization, and this paper can be served as an example of strict clinical applications. [ABSTRACT FROM AUTHOR]

Introduction: Over the last decade, the emergence and spread of personalized medicine (PM) have defined a substantial revolution in healthcare. In principle, healthcare system sustainability is challenged by the investments required for research and development, as well as the adoption of PM techniques in routine clinical care. The "Integrating China in the International Consortium for Personalized Medicine" (IC2PerMed) EU-funded project aims to integrate China into the "International Consortium for Personalized Medicine" (ICPerMed). IC2PerMed aims to align the EU and China's research agendas in this field to enable a swift development of approaches in the EU and China with strong leverage upon EU-Chinese collaborations. Methods: Within this project, we first mapped relevant policies on PM in both the EU and China, and then we involved European and Chinese experts in PM in workshops and Delphi surveys in order to identify relevant priorities for the implementation of PM in sustainable healthcare. Results: As a result of this process, we identified nine overarching priorities, each addressing specific aspects of the sustainability of healthcare systems and PM implementation, with the main goal of supporting policymakers in integrating PM approaches in the EU and China. Discussion/conclusion: The implementation of PM in health systems is appealing in terms of improved accuracy in diagnostics, treatment, and prevention of disease, as well as reduction of the side effects resulting from inefficient use of drugs. Research, development, and implementation of needed techniques require time and resources that can slow the adoption of PM in healthcare systems. The nine priorities we identified address some of the most critical points, trying to lay the foundations for a comprehensive approach. [ABSTRACT FROM AUTHOR]

Background: Papillary thyroid carcinoma (PTC) is the most common thyroid malignancy, and its distant metastasis (PTCDM), although uncommon, seriously affects the survival rate and quality of life of patients. With the rapid development of science and technology, research in the field of PTCDM has accumulated rapidly, presenting a complex knowledge structure and development trend. Methods: In this study, bibliometric analysis was used to collect 479 PTCDMrelated papers published between 2004 and 2023 through the Web of Science (WoS) Core Collection (WoSCC) database. Keyword clustering analysis was performed using VOSviewer and citespace, as well as dual-map overlay analysis, to explore knowledge flows and interconnections between different disciplines. Results: The analysis indicated that China, the United States, and South Korea were the most active countries in conducting research activities. Italy's research was notable due to its higher average citation count. Keyword analysis revealed that "cancer," "papillary thyroid carcinoma," and "metastasis" were the most frequently used terms in these studies. The journal co-citation analysis underscored the dominant roles of molecular biology, immunology, and clinical medicine, as well as the growing importance of computer science in research. Conclusion: This study identified the main trends and scientific structure of PTCDM research, highlighting the importance of interdisciplinary approaches and the crucial role of top academic journals in promoting high-quality research. The findings not only provide valuable information for basic and clinical research on thyroid cancer but also offer guidance for future research directions. [ABSTRACT FROM AUTHOR]

Background: Aesthetics medicine, a controversial branch of clinical medicine known for its high degree of commercialization, faces numerous conflicts, particularly in some developing countries. The global aesthetics medicine industry requires enhancements of its legal and supervision framework and risk management systems. Aims: This paper aimed to provide a comprehensive visual analysis of academic achievements related to regulatory and legal issues in the field of aesthetic medicine and to identify its development trends and research hotspots. Methods: The Web of Science Core Collection was employed to retrieve relevant studies, resulting in a total of 602 research articles after selection. Utilizing bibliometric methods and CiteSpace, this study analyzed the primary countries, institutions, authors, journals, hotspots, frontiers, and trends in this domain. Results: The findings indicated rapid increases in the number of published papers. The United States emerged as the leading contributor with 131 research papers and the highest intermediate centrality. Eleven keyword clusters were identified, with "adolescence" and "office‐based surgery" being the most recent topics. We also analyzed the trends and frontiers of legal research in medical aesthetics. Conclusion: The importance of informed consent has been increasingly emphasized, and research in the field of medical aesthetics has been gradually expanding beyond individual cosmetic procedures. The management system has become more comprehensive, moreover, guidelines and medical laws have been continually published, with research shifting toward a holistic perspective that encompasses patients, medical aesthetic providers, and regulatory authorities in the study of medical aesthetics regulation and legislation. This paper also proposes some innovative directions for future research and applications. [ABSTRACT FROM AUTHOR]

Digital health technologies (DHTs) at the intersection of health, medical informatics, and business aim to enhance patient care through personalised digital approaches. Ensuring the efficacy and reliability of these innovations demands rigorous clinical validation. A PubMed literature review (January 2006 to July 2023) identified 1250 papers, highlighting growing academic interest. A focused narrative review (January 2018 to July 2023) delved into challenges, highlighting issues such as diverse regulatory landscapes, adoption issues in complex healthcare systems, and a plethora of evaluation frameworks lacking pragmatic guidance. Existing frameworks often omit crucial criteria, neglect empirical evidence, and clinical effectiveness is rarely included as a criterion for DHT quality. The paper underscores the urgency of addressing challenges in accreditation, adoption, business models, and integration to safeguard the quality, efficacy, and safety of DHTs. A pivotal illustration of collaborative efforts to address these challenges is exemplified by the Digital Health Validation Center, dedicated to generating clinical evidence of innovative healthcare technologies and facilitating seamless technology transfer. In conclusion, it is necessary to harmonise evaluation approaches and frameworks, improve regulatory clarity, and commit to collaboration to integrate rigorous clinical validation and empirical evidence throughout the DHT life cycle. [ABSTRACT FROM AUTHOR]

The role of the emergency medical service (EMS) is changing globally as ambulance crews respond to a shifting burden of disease, as well as societal stressors such as violence and inequality. New ways of thinking about how to provide emergency care are required to shift EMS from a role primarily focused on clinical care and transporting patients to hospital. In this paper, we present the experience of the Philippi Project (PP), an innovative community-based model of care developed by front line ambulance crews in a low-income neighbourhood in Cape Town, South Africa. Our insights were developed through observational, interview and document review work, within an overall embedded research approach. Our analysis draws on the everyday health systems resilience (EHSR) framework, which sees resilience as an emergent process that may be stimulated through response to stress and shock. Responses take the form of absorptive, adaptive or transformative strategies and are underpinned by system capacities (cognitive, behavioural and contextual). We consider the PP as a potentially transformative resilience strategy, defined as a new way of working that offered the promise of long-term health system gains. We found that the PP's initial development was supported by a range of system capacity attributes (such as the intentional development of relationships, a sense of collective purpose and creating spaces for constructive sense-making). However, the PP was hard to sustain over time because emergent ways of working were undermined both by other capacity attributes rooted in pre-existing organizational routines and two contextual shocks (Coronavirus and a violent incident). The paper adds a new empirical contribution to the still-small EHSR literature. In addition, the PP experience offers globally relevant lessons for developing community-based models of EMS care. It demonstrates that front line staff can develop creative solutions to their stressful daily realities, but only if space is created and protected. [ABSTRACT FROM AUTHOR]

Biobanking plays a pivotal role in biomedical research by providing standardized processing, precise storing, and management of biological sample collections along with the associated data. Effective data management is a prerequisite to ensure the integrity, quality, and accessibility of these resources. This review provides a current landscape of data management in biobanking, discussing key challenges, existing strategies, and potential future directions. We explore multiple aspects of data management, including data collection, storage, curation, sharing, and ethical considerations. By examining the evolving technologies and methodologies in biobanking, we aim to provide insights into addressing the complexities and maximizing the utility of biobank data for research and clinical applications. [ABSTRACT FROM AUTHOR]

Introduction: A hiatal hernia (HH) can be defined as a condition in which elements from the abdominal cavity herniate through the oesophageal hiatus in the mediastinum and, in the majority of cases, parts of the proximal stomach. Today, the role of HHs within the complex entity of gastroesophageal reflux disease (GERD) is very important with regard to its pathophysiology, severity, and therapeutic and prognostic options. Despite this, the application and stringent use of the worldwide accepted classification (Skinner and Belsey: Types I–IV) are lacking. The aim of this study was to carry out a systematic review of the clinical applications of HH classifications and scientific documentation over time, considering their value in diagnosis and treatment. Methods: Following the PRISMA concept, all abstracts published on pubmed.gov until 12/2023 (hiatal hernia) were reviewed, and those with a focus and clear description of the application of the current HH classification in the full-text version were analysed to determine the level of classification and its use within the therapeutic context. Results: In total, 9342 abstracts were screened. In 9199 of the abstracts, the reports had a different focus than HH, or the HH classification was not used or was incompletely applied. After further investigation, 60 papers were used for a detailed analysis, which included more than 12,000 patient datapoints. Among the 8904 patients, 83% had a Type I HH; 4% had Type II; 11% had Type III; and 1% had Type IV. Further subgroup analyses were performed. Overall, the precise application of the HH classification has been insufficient, considering that only 1% of all papers and only 54% of those with a special focus on HH have documented its use. Conclusions: The application and documentation of a precise HH classification in clinical practice and scientific reports are decreasing, which should be rectified for the purpose of scientific comparability. [ABSTRACT FROM AUTHOR]

Objective: This scoping review aims to map the available literature and provide an overview of the published articles discussing the impact of electronic prescribing on medication errors and pharmacy workflow. Methods: The literature search was conducted using PubMed®, Web of Science®, and the Cochrane Database of Systematic Reviews®, as well as grey literature reports, using the search terms and related components of "pharmacists", "electronic prescribing", "medication errors", and "efficiency". The search included all articles that were published from January 2011 to September 2023. Twenty-two relevant articles were identified and fully reviewed, ten of which were included in this review. Results: Electronic prescribing (e-prescribing) provides a solution for some of the challenges that are associated with handwritten and paper prescriptions. However, the implementation of e-prescribing systems has been recognized as a source of new unforeseen medication errors in all the reviewed articles. Productivity in community pharmacies has been affected with receiving electronic prescriptions (e-prescriptions) and having to deal with the issues that arise from them. The pharmacists' interventions were not eliminated with e-prescriptions compared to other prescription formats. The most frequently reported reason for intervention was related to incomplete instructions in the field of directions of use. Other common challenges with e-prescriptions were related to missing information, quantity, inappropriate dose, dosage form, and drug. Discussion: This review demonstrates the scarcity of research about the impact of electronic prescribing on medication error and efficiency in community pharmacies. In the literature, most of the studies had mainly focused on hospital pharmacies. The literature search demonstrated that there are still some barriers to overcome with e-prescribing systems and that medication errors were not fully eliminated with e-prescriptions. New errors have been identified with e-prescriptions, all of which caused delays in processing, which affected the productivity of the pharmacy staff, and could have negatively impacted patients' safety if not properly resolved. Conclusion: e-Prescribing solved some of the challenges associated with illegibility of handwritten prescriptions. However, more time is required to allow e-prescribing systems to mature. Further training for prescribers and pharmacists is also recommended before and after the implementation. [ABSTRACT FROM AUTHOR]

(1) Background: In digital-technology-assisted nasal defect reconstruction methods, a crucial step involves utilizing computer-aided design to virtually reconstruct the nasal defect's complete morphology. However, current digital methods for virtual nasal defect reconstruction have yet to achieve efficient, precise, and personalized outcomes. In this research paper, we propose a novel approach for reconstructing external nasal defects based on the Facial Mesh Generation Network (FMGen-Net), aiming to enhance the levels of automation and personalization in virtual reconstruction. (2) Methods: We collected data from 400 3D scans of faces with normal morphology and combined the structured 3D face template and the Meshmonk non-rigid registration algorithm to construct a structured 3D facial dataset for training FMGen-Net. Guided by defective facial data, the trained FMGen-Net automatically generated an intact 3D face that was similar to the defective face, and maintained a consistent spatial position. This intact 3D face served as the 3D target reference face (3D-TRF) for nasal defect reconstruction. The reconstructed nasal data were extracted from the 3D-TRF based on the defective area using reverse engineering software. The '3D surface deviation' between the reconstructed nose and the original nose was calculated to evaluate the effect of 3D morphological restoration of the nasal defects. (3) Results: In the simulation experiment of 20 cases involving full nasal defect reconstruction, the '3D surface deviation' between the reconstructed nasal data and the original nasal data was 1.45 ± 0.24 mm. The reconstructed nasal data, constructed from the personalized 3D-TRF, accurately reconstructed the anatomical morphology of nasal defects. (4) Conclusions: This paper proposes a novel method for the virtual reconstruction of external nasal defects based on the FMGen-Net model, achieving the automated and personalized construction of the 3D-TRF and preliminarily demonstrating promising clinical application potential. [ABSTRACT FROM AUTHOR]

This article aims to summarize performance indicators used in telephone triage services research, and make recommendations for the selection of valid indicators to measure the performance of telephone triage. We describe what kind of frameworks, performance indicators, or variables have been used for evaluating telephone triage performance by systematically mapping the telephone triage performance measurement. The objective was to find measures for each Triple Aim dimension. A scoping review method was used following Joanna Briggs Institute guidelines. Using this method, we defined indicators to measure the performance of telephone triage. We used the Triple Aim framework to identify indicators to measure the overall performance of telephone triage. The Triple Aim framework consists of improving the patient experience of care, improving the health of populations, and reducing cost per capita. The scoping review was performed using CINAHL, Medline, EBSCOhost, and PubMed electronic databases. The eligibility criterion was research published in English between 2015 and 2023. The inclusion focused on the use and performance of telephone triage services and system-focused studies. A total of 1098 papers were screened for inclusion, with 57 papers included in our review. We identified 13 performance indicators covering all Triple Aim dimensions: waiting times, access, patient satisfaction, the accuracy of triage decision, severity and urgency of the symptoms, triage response, patient compliance with the advice given, follow-up healthcare service use, and running costs of service. We didn't find any earlier framework covering all Triple Aim dimensions properly. Measuring the performance of telephone triage requires an extensive and comprehensive approach. We presented performance indicators that may be included in the framework for measuring the performance of telephone triage to support overall performance measurements of telephone triage. [ABSTRACT FROM AUTHOR]

In recent years, with the aggravation of aging, the incidence of neurodegenerative diseases is increasing year by year, and the prognosis of patients is poor. Functional Near-Infrared Spectroscopy (fNIRS) is a new and non-invasive neuroimaging technology, which has been gradually deepened in the application research of neurodegenerative diseases by virtue of its unique neurooxygen signal brain functional imaging characteristics in monitoring the disease condition, making treatment plans and evaluating the treatment effect. In this paper, the mechanism of action and technical characteristics of fNIRS are briefly introduced, and the application research of fNIRS in different neurodegenerative diseases is summarized in order to provide new ideas for future related research and clinical application. [ABSTRACT FROM AUTHOR]

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In recent years, Raman spectroscopy has garnered growing interest in the field of biomedical research. It offers a non-invasive and label-free approach to defining the molecular fingerprint of immune cells. We utilized Raman spectroscopy on optically trapped immune cells to investigate their molecular compositions. While numerous immune cell types have been studied in the past, the characterization of living human CD3/CD28-stimulated T cell subsets remains incomplete. In this study, we demonstrate the capability of Raman spectroscopy to readily distinguish between naïve and stimulated CD4 and CD8 cells. Additionally, we compared these cells with monocytes and discovered remarkable similarities between stimulated T cells and monocytes. This paper contributes to expanding our knowledge of Raman spectroscopy of immune cells and serves as a launching point for future clinical applications. [ABSTRACT FROM AUTHOR]

The integration of advanced diagnostic technologies in healthcare is crucial for enhancing the accuracy and efficiency of disease detection and management. This paper presents an innovative approach combining machine learning-assisted 3D flexible fiber-based organic transistor (FOT) sensors for high-accuracy metabolite analysis and potential diagnostic applications. Machine learning algorithms further enhance the analytical capabilities of FOT sensors by effectively processing complex data, identifying patterns, and predicting diagnostic outcomes with 100% high accuracy. We explore the fabrication and operational mechanisms of these transistors, the role of machine learning in metabolite analysis, and their potential clinical applications by analyzing practical human blood samples for hypernatremia syndrome. This synergy not only improves diagnostic precision but also holds potential for the development of personalized diagnostics, tailoring treatments for individual metabolic profiles. [ABSTRACT FROM AUTHOR]

The tumor microenvironment (TME) constitutes a complex microenvironment comprising a diverse array of immune cells and stromal components. Within this intricate context, tumor-associated macrophages (TAMs) exhibit notable spatial heterogeneity. This heterogeneity contributes to various facets of tumor behavior, including immune response modulation, angiogenesis, tissue remodeling, and metastatic potential. This review summarizes the spatial distribution of macrophages in both the physiological environment and the TME. Moreover, this paper explores the intricate interactions between TAMs and diverse immune cell populations (T cells, dendritic cells, neutrophils, natural killer cells, and other immune cells) within the TME. These bidirectional exchanges form a complex network of immune interactions that influence tumor immune surveillance and evasion strategies. Investigating TAM heterogeneity and its intricate interactions with different immune cell populations offers potential avenues for therapeutic interventions. Additionally, this paper discusses therapeutic strategies targeting macrophages, aiming to uncover novel approaches for immunotherapy. EjPgUqH7NocL1u9xj7Aojm Video Abstract [ABSTRACT FROM AUTHOR]

Dissolving microneedles (DMNs) represent an innovative advancement in drug delivery and skincare technologies, offering significant advantages compared to traditional needles. This paper presents an overview of the historical evolution of microneedles and the rise of dissolving types, exploring their definition, concept, and diverse clinical applications such as vaccinations, drug delivery, and skincare treatments. Design and manufacturing considerations cover the materials employed, fabrication techniques, and methods for characterizing DMNs, focusing on aspects like mechanical strength, dissolution rate, and delivery efficiency. The mechanism of action section examines skin penetration mechanics, the process of microneedle dissolution, controlled release of active compounds, and considerations of biocompatibility and safety. Recent developments in DMNs encompass technological advancements, improved delivery systems, and updates on clinical trials and studies. Challenges and opportunities in scaling up production, overcoming market adoption barriers, and future research directions are discussed, aiming to address unmet medical needs and expand applications. In summary, DMNs have the potential to transform drug delivery and skincare treatments, with ongoing advancements aimed at tackling current challenges and unlocking new opportunities for enhanced healthcare outcomes. [ABSTRACT FROM AUTHOR]

A knowledge of the complex phenomena that regulate T1 signal on Magnetic Resonance Imaging is essential in clinical practice for a more effective characterization of pathological processes. The authors review the physical basis of T1 Relaxation Time and the fundamental aspects of physics and chemistry that can influence this parameter. The main substances (water, fat, macromolecules, methemoglobin, melanin, Gadolinium, calcium) that influence T1 and the different MRI acquisition techniques that can be applied to enhance their presence in diagnostic images are then evaluated. An extensive case illustration of the different phenomena and techniques in the areas of CNS, abdomino-pelvic, and osteoarticular pathology is also proposed. Critical relevance statement: T1 relaxation time is strongly influenced by numerous factors related to tissue characteristics and the presence in the context of the lesions of some specific substances. An examination of these phenomena with extensive MRI exemplification is reported. Key Points: The purpose of the paper is to illustrate the chemical-physical basis of T1 Relaxation Time. MRI methods in accordance with the various clinical indications are listed. Several examples of clinical application in abdominopelvic and CNS pathology are reported. [ABSTRACT FROM AUTHOR]

Since three-dimensional (3D) bioprinting has emerged, it has continuously to evolved as a revolutionary technology in surgery, offering new paradigms for reconstructive and regenerative medical applications. This review highlights the integration of 3D printing, specifically bioprinting, across several surgical disciplines over the last five years. The methods employed encompass a review of recent literature focusing on innovations and applications of 3D-bioprinted tissues and/or organs. The findings reveal significant advances in the creation of complex, customized, multi-tissue constructs that mimic natural tissue characteristics, which are crucial for surgical interventions and patient-specific treatments. Despite the technological advances, the paper introduces and discusses several challenges that remain, such as the vascularization of bioprinted tissues, integration with the host tissue, and the long-term viability of bioprinted organs. The review concludes that while 3D bioprinting holds substantial promise for transforming surgical practices and enhancing patient outcomes, ongoing research, development, and a clear regulatory framework are essential to fully realize potential future clinical applications. [ABSTRACT FROM AUTHOR]

Malignant tumor, one of the most threatening diseases to human health, has been comprehensively treated with surgery, radiotherapy, chemotherapy and targeted therapy, but the prognosis has not always been ideal. In the past decade, immunotherapy has shown increased efficacy in tumor treatment; however, for immunotherapy to achieve its fullest potential, obstacles are to be conquered, among which tumor microenvironment (TME) has been widely investigated. In remodeling the tumor immune microenvironment to inhibit tumor progression, macrophages, as the most abundant innate immune population, play an irreplaceable role in the immune response. Therefore, how to remodel TME and alter the recruitment and polarization status of tumor-associated macrophages (TAM) has been of wide interest. In this context, nanoparticles, photodynamic therapy and other therapeutic approaches capable of affecting macrophage polarization have emerged. In this paper, we categorize and organize the existing means and methods for reprogramming TAM to provide ideas for clinical application of novel tumor-related therapies. [ABSTRACT FROM AUTHOR]

Platelets play a significant role in hemostasis, forming plugs at sites of vascular injury to limit blood loss. However, if platelet activation is not controlled, it can lead to thrombotic events, such as myocardial infarction and stroke. To prevent this, antiplatelet agents are used in clinical settings to limit platelet activation in patients at risk of arterial thrombotic events. However, their use can be associated with a significant risk of bleeding. An enhanced comprehension of platelet signaling mechanisms should facilitate the identification of safer targets for antiplatelet therapy. Over the past decade, our comprehension of the breadth and intricacy of signaling pathways that orchestrate platelet activation has expanded exponentially. Several recent studies have provided further insight into the regulation of platelet signaling events and identified novel targets against which to develop novel antiplatelet agents. Antiplatelet drugs are essential in managing atherothrombotic vascular disease. The current antiplatelet therapy in clinical practice is limited in terms of safety and efficacy. Novel compounds have been developed in response to patient variability and resistance to aspirin and/or clopidogrel. Recent studies based on randomized controlled trials and systematic reviews have definitively demonstrated the role of antiplatelet therapy in reducing the risk of cardiovascular events. Antiplatelet therapy is the recommended course of action for patients with established atherosclerosis. These studies compared monotherapy with a P2Y12 inhibitor versus aspirin for secondary prevention. However, in patients undergoing percutaneous coronary intervention, it is still unclear whether the efficacy of P2Y12 inhibitor monotherapy after a short course of dual antiplatelet therapy depends on the type of P2Y12 inhibitor. This paper focuses on the advanced-stage evaluation of several promising antiplatelet drugs. [ABSTRACT FROM AUTHOR]

This paper reviews the latest trends and applications of silicone in ophthalmology, especially related to intraocular lenses (IOLs). Silicone, or siloxane elastomer, as a synthetic polymer, has excellent biocompatibility, high chemical inertness, and hydrophobicity, enabling wide biomedical applications. The physicochemical properties of silicone are reviewed. A review of methods for mechanical and in vivo characterization of IOLs is presented as a prospective research area, since there are only a few available technologies, even though these properties are vital to ensure medical safety and suitability for clinical use, especially if long-term function is considered. IOLs represent permanent implants to replace the natural lens or for correcting vision, with the first commercial foldable lens made of silicone. Biological aspects of posterior capsular opacification have been reviewed, including the effects of the implanted silicone IOL. However, certain issues with silicone IOLs are still challenging and some conditions can prevent its application in all patients. The latest trends in nanotechnology solutions have been reviewed. Surface modifications of silicone IOLs are an efficient approach to further improve biocompatibility or to enable drug-eluting function. Different surface modifications, including coatings, can provide long-term treatments for various medical conditions or medical diagnoses through the incorporation of sensory functions. It is essential that IOL optical characteristics remain unchanged in case of drug incorporation and the application of nanoparticles can enable it. However, clinical trials related to these advanced technologies are still missing, thus preventing their clinical applications at this moment. [ABSTRACT FROM AUTHOR]

Universal health coverage has been proposed as a strategy to improve health in low- and middle-income countries, but this depends on a good provision of health services. Under-5 mortality (U5M) reflects the quality of health services, and its reduction has been a milestone in modern society, reducing global mortality rates by more than two-thirds between 1990 and 2020. However, despite these impressive achievements, they are still insufficient, and most deaths in children under 5 can be prevented with the provision of timely and high-quality health services. The aim of this paper is to conduct a literature review on amenable (treatable) mortality in children under 5. This indicator is based on the concept that deaths from certain causes should not occur in the presence of timely and effective medical care. A systematic and exhaustive review of available literature on amenable mortality in children under 5 was conducted using MEDLINE/PubMed, Cochrane CENTRAL, OVID medline, Scielo, Epistemonikos, ScienceDirect, and Google Scholar in both English and Spanish. Both primary sources, such as scientific articles, and secondary sources, such as bibliographic indices, websites, and databases, were used. Results: The main cause of amenable mortality in children under 5 was respiratory disease, and the highest proportion of deaths occurred in the perinatal period. Approximately 65% of avoidable deaths in children under 5 were due to amenable mortality, that is, due to insufficient quality in the provision of health services. Most deaths in all countries and around the world are preventable, primarily through effective and timely access to healthcare (amenable mortality) and the management of public health programs focused on mothers and children (preventable mortality). [ABSTRACT FROM AUTHOR]

Neurodegenerative diseases are a significant challenge to global healthcare, and oxidative stress plays a crucial role in their development. This paper presents a comprehensive analysis of the neuroprotective potential of olive oil, with a primary focus on its antioxidant properties. The chemical composition of olive oil, including key antioxidants, such as oleuropein, hydroxytyrosol, and oleocanthal, is systematically examined. The mechanisms by which these compounds provide neuroprotection, including counteracting oxidative damage and modulating neuroprotective pathways, are explored. The neuroprotective efficacy of olive oil is evaluated by synthesizing findings from various sources, including in vitro studies, animal models, and clinical trials. The integration of olive oil into dietary patterns, particularly its role in the Mediterranean diet, and its broader implications in neurodegenerative disease prevention are also discussed. The challenges in translating preclinical findings to clinical applications are acknowledged and future research directions are proposed to better understand the potential of olive oil in mitigating the risk of neurodegenerative conditions. This review highlights olive oil not only as a dietary component, but also as a promising candidate in preventive neurology, advocating for further investigation in the context of neurodegenerative diseases. [ABSTRACT FROM AUTHOR]

Low-Dose computer tomography (LDCT) is an ideal alternative to reduce radiation risk in clinical applications. Although supervised-deep-learning-based reconstruction methods have demonstrated superior performance compared to conventional model-driven reconstruction algorithms, they require collecting massive pairs of low-dose and norm-dose CT images for neural network training, which limits their practical application in LDCT imaging. In this paper, we propose an unsupervised and training data-free learning reconstruction method for LDCT imaging that avoids the requirement for training data. The proposed method is a post-processing technique that aims to enhance the initial low-quality reconstruction results, and it reconstructs the high-quality images by neural work training that minimizes the ℓ1-norm distance between the CT measurements and their corresponding simulated sinogram data, as well as the total variation (TV) value of the reconstructed image. Moreover, the proposed method does not require to set the weights for both the data fidelity term and the plenty term. Experimental results on the AAPM challenge data and LoDoPab-CT data demonstrate that the proposed method is able to effectively suppress the noise and preserve the tiny structures. Also, these results demonstrate the rapid convergence and low computational cost of the proposed method. The source code is available at https://github.com/linfengyu77/IRLDCT. [ABSTRACT FROM AUTHOR]

Medical Visual Question Answering (Med-VQA) faces significant limitations in application development due to sparse and challenging data acquisition. Existing approaches focus on multi-modal learning to equip models with medical image inference and natural language understanding, but this worsens data scarcity in Med-VQA, hindering clinical application and advancement. This paper proposes the ITLTA framework for Med-VQA, designed based on field requirements. ITLTA combines multi-label learning of medical images with the language understanding and reasoning capabilities of large language models (LLMs) to achieve zero-shot learning, meeting natural language module needs without end-to-end training. This approach reduces deployment costs and training data requirements, allowing LLMs to function as flexible, plug-and-play modules. To enhance multi-label classification accuracy, the framework uses external medical image data for pretraining, integrated with a joint feature and label attention mechanism. This configuration ensures robust performance and applicability, even with limited data. Additionally, the framework clarifies the decision-making process for visual labels and question prompts, enhancing the interpretability of Med-VQA. Validated on the VQA-Med 2019 dataset, our method demonstrates superior effectiveness compared to existing methods, confirming its outstanding performance for enhanced clinical applications. [ABSTRACT FROM AUTHOR]

Introduction: Globally, healthcare organizations have transitioned from paper-based documentation to electronic health records (EHR), including in Saudi Arabia. However, the adoption of EHR at the national level in Saudi Arabia needs more attention. Thus, this study aimed to determine the workflow integration of EHR and associated factors. Objectives: The specific aims were to examine the level of EHR use and workflow integration among nurses, to determine the differences in EHR use and workflow integration based on nurses' demographic characteristics, and to determine the association between the predictive factors and EHR workflow integration. Methods: This is a cross-sectional, correlational descriptive study. The data were collected from 293 nurses using the convenience sampling method. The participating nurses completed a questionnaire that included two measures: the Information System Use Survey and the Workflow Integration Survey (WIS). The data were analyzed using descriptive and multivariate statistics with SPSS software. Results: The nurses had a positive perception of EHR use and workflow. The EHR use scores differed based on workplace (P <.01), education level (P <.05), and area of practice (P <.001). Similarly, the EHR workflow integration scores varied according to workplace (P <.05), education level (P <.05), and area of practice (P <.001). Education level and workplace significantly predicted information system use. Furthermore, education level and information system use significantly predicted the EHR integration into nurses' workflow. Conclusion: The nurses expressed a greater perceived use of EHR regarding the integrated health information system, which was a predictor of EHR integration into nurses' workflow. [ABSTRACT FROM AUTHOR]

Automatically segmenting polyps from colonoscopy videos is crucial for developing computer-assisted diagnostic systems for colorectal cancer. Existing automatic polyp segmentation methods often struggle to fulfill the real-time demands of clinical applications due to their substantial parameter count and computational load, especially those based on Transformer architectures. To tackle these challenges, a novel lightweight long-range context fusion network, named LightCF-Net, is proposed in this paper. This network attempts to model long-range spatial dependencies while maintaining real-time performance, to better distinguish polyps from background noise and thus improve segmentation accuracy. A novel Fusion Attention Encoder (FAEncoder) is designed in the proposed network, which integrates Large Kernel Attention (LKA) and channel attention mechanisms to extract deep representational features of polyps and unearth long-range dependencies. Furthermore, a newly designed Visual Attention Mamba module (VAM) is added to the skip connections, modeling long-range context dependencies in the encoder-extracted features and reducing background noise interference through the attention mechanism. Finally, a Pyramid Split Attention module (PSA) is used in the bottleneck layer to extract richer multi-scale contextual features. The proposed method was thoroughly evaluated on four renowned polyp segmentation datasets: Kvasir-SEG, CVC-ClinicDB, BKAI-IGH, and ETIS. Experimental findings demonstrate that the proposed method delivers higher segmentation accuracy in less time, consistently outperforming the most advanced lightweight polyp segmentation networks. [ABSTRACT FROM AUTHOR]

Stepper motors are synchronous electric actuators with incremental displacement that can be controlled in open loop in position or speed. Unfortunately, the rotor oscillations that characterize stepper motors are a major handicap that limits the use of this type of actuator in precision industrial applications and especially in biomedical systems. Improving motor drive performance is challenging due to the presence of uncertainty in system parameters and large load variations. To overcome these problems and the shortcomings of conventional control approaches, a new control concept based on fuzzy logic is developed. To this purpose, this paper proposes a fuzzy logic concept (FLC) for damping rotor oscillations of stepper actuator devoted to an Electrical Syringe Pump application. The FLC membership functions and rules are designed with value normalization that allows the developed controller able to be flexible when applied to a wide range of applications. The proposed FLC is numerically validated. Critical testing scenarios are employed including motor inertia variation, supply voltage variation, fluid friction variation and for different loads. Moreover, thanks to its normalized design, the proposed FLC is not limited to the studied biomedical applications, but can be applied to other application systems. [ABSTRACT FROM AUTHOR]

A brain tumor magnetic resonance image processing algorithm can help doctors to diagnose and treat the patient's condition, which has important application significance in clinical medicine. This paper proposes a network model based on the combination of U-net and DenseNet to solve the problems of class imbalance in multi-modal brain tumor image segmentation and the loss of effective information features caused by the integration of features in the traditional U-net network. The standard convolution blocks of the coding path and decoding path on the original network are improved to dense blocks, which enhances the transmission of features. The mixed loss function composed of the Binary Cross Entropy Loss function and the Tversky coefficient is used to replace the original single cross-entropy loss, which restrains the influence of irrelevant features on segmentation accuracy. Compared with U-Net, U-Net++, and PA-Net the algorithm in this paper has significantly improved the segmentation accuracy, reaching 0.846, 0.861, and 0.782 respectively in the Dice coefficient index of WT, TC, and ET. The PPV coefficient index has reached 0.849, 0.883, and 0.786 respectively. Compared with the traditional U-net network, the Dice coefficient index of the proposed algorithm exceeds 0.8%, 4.0%, and 1.4%, respectively, and the PPV coefficient index in the tumor core area and tumor enhancement area increases by 3% and 1.2% respectively. The proposed algorithm has the best performance in tumor core area segmentation, and its Sensitivity index has reached 0.924, which has good research significance and application value., Competing Interests: The authors have declared that no competing interests exist., (Copyright: © 2024 Wu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.)

Ultrasound is a highly adaptable medical imaging modality that offers several applications and a wide range of uses, both for diagnostic and therapeutic purposes. The principles of sound wave propagation and reflection enable ultrasound imaging to function as a highly secure modality. This technique facilitates the production of real-time visual representations, thereby assisting in the evaluation of various medical conditions such as cardiac, gynecologic, and abdominal diseases, among others. The ultrasound modality encompasses a diverse range of modes and mechanisms that serve to enhance the methodology of pathology and physiology assessment. Doppler imaging and US elastography, in particular, are two such techniques that contribute to this expansion. Elastography-based imaging methods have attracted significant interest in recent years for the non-invasive evaluation of tissue mechanical characteristics. These techniques utilize the changes in soft tissue elasticity in various diseases to generate both qualitative and quantitative data for diagnostic purposes. Specialized imaging techniques collect data by identifying tissue stiffness under mechanical forces such as compression or shear waves. However, in this review paper, we provide a comprehensive examination of the fundamental concepts, underlying physics, and limitations associated with ultrasound elastography. Additionally, we present a concise overview of its present-day clinical utilization and ongoing advancements across many clinical domains. [ABSTRACT FROM AUTHOR]

Context: The COVID-19 pandemic has reignited a commitment from the health policy and health services research communities to rebuilding trust in healthcare and created a renewed appetite for measures of trust for system monitoring and evaluation. The aim of the present paper was to develop a multidimensional measure of trust in healthcare that: (1) Is responsive to the conceptual and methodological limitations of existing measures; (2) Can be used to identify systemic explanations for lower levels of trust in equity-deserving populations; (3) Can be used to design and evaluate interventions aiming to (re)build trust. Methods: We conducted a 2021 review of existing measures of trust in healthcare, 72 qualitative interviews (Aug-Dec 2021; oversampling for equity-deserving populations), an expert review consensus process (Oct 2021), and factor analyses and validation testing based on two waves of survey data (Nov 2021, n = 694; Jan-Feb 2022, n = 740 respectively). Findings: We present the Trust in Multidimensional Healthcare Systems Scale (TIMHSS); a 38-item correlated three-factor measure of trust in doctors, policies, and the system. Measurement of invariance tests suggest that the TIMHSS can also be reliably administered to diverse populations. Conclusions: This global measure of trust in healthcare can be used to measure trust over time at a population level, or used within specific subpopulations, to inform interventions to (re)build trust. It can also be used within a clinical setting to provide a stronger evidence base for associations between trust and therapeutic outcomes. [ABSTRACT FROM AUTHOR]

Purpose: The significance of atraumatic electrode array (EA) insertion in cochlear implant (CI) surgery is widely acknowledged, with consensus that forces due to EA insertion are directly correlated with insertion trauma. Unfortunately, the manual perception of these forces through haptic feedback is inherently limited, and techniques for in vivo force measurements to monitor the insertion are not yet available. Addressing this gap, we developed of a force-sensitive insertion tool capable of capturing real-time insertion forces during standard CI surgery. Methods: This paper describes the tool and its pioneering application in a clinical setting and reports initial findings from an ongoing clinical study. Data and experiences from five patients have been evaluated so far, including force profiles of four patients. Results: The initial intraoperative experiences are promising, with successful integration into the conventional workflow. Feasibility of in vivo insertion force measurement and practicability of the tool's intraoperative use could be demonstrated. The recorded in vivo insertion forces show the expected rise with increasing insertion depth. Forces at the end of insertion range from 17.2 mN to 43.6 mN, while maximal peak forces were observed in the range from 44.8 mN to 102.4 mN. Conclusion: We hypothesize that this novel method holds the potential to assist surgeons in monitoring the insertion forces and, thus, minimizing insertion trauma and ensuring better preservation of residual hearing. Future data recording with this tool can form the basis of ongoing research into the causes of insertion trauma, paving the way for new and improved prevention strategies. [ABSTRACT FROM AUTHOR]

Precise medical image segmentation of regions of interest (ROIs) is crucial for accurate disease diagnosis and progression assessment. However, acquiring high-quality annotated data at the pixel level poses a significant challenge due to the resource-intensive nature of this process. This scarcity of high-quality annotated data results in few-shot scenarios, which are highly prevalent in clinical applications. To address this obstacle, this paper introduces Agent-Guided SAM (AGSAM), an innovative approach that transforms the Segment Anything Model (SAM) into a fully automated segmentation method by automating prompt generation. Capitalizing on the pre-trained feature extraction and decoding capabilities of SAM-Med2D, AGSAM circumvents the need for manual prompt engineering, ensuring adaptability across diverse segmentation methods. Furthermore, the proposed feature augmentation convolution module (FACM) enhances model accuracy by promoting stable feature representations. Experimental evaluations demonstrate AGSAM's consistent superiority over other methods across various metrics. These findings highlight AGSAM's efficacy in tackling the challenges associated with limited annotated data while achieving high-quality medical image segmentation. [ABSTRACT FROM AUTHOR]

Medical image segmentation is crucial for clinical applications, but challenges persist due to noise and variability. In particular, accurate glottis segmentation from high-speed videos is vital for voice research and diagnostics. Manual searching for failed segmentations is labor-intensive, prompting interest in automated methods. This paper proposes the first deep learning approach for detecting faulty glottis segmentations. For this purpose, faulty segmentations are generated by applying both a poorly performing neural network and perturbation procedures to three public datasets. Heavy data augmentations are added to the input until the neural network's performance decreases to the desired mean intersection over union (IoU). Likewise, the perturbation procedure involves a series of image transformations to the original ground truth segmentations in a randomized manner. These data are then used to train a ResNet18 neural network with custom loss functions to predict the IoU scores of faulty segmentations. This value is then thresholded with a fixed IoU of 0.6 for classification, thereby achieving 88.27% classification accuracy with 91.54% specificity. Experimental results demonstrate the effectiveness of the presented approach. Contributions include: (i) a knowledge-driven perturbation procedure, (ii) a deep learning framework for scoring and detecting faulty glottis segmentations, and (iii) an evaluation of custom loss functions. [ABSTRACT FROM AUTHOR]

Background: Numerous studies have cast light on the relationship between the gastric microbiota and gastric carcinogenesis. In this study, we conducted a bibliometric analysis of the relevant literature in the field of gastric cancer and the gastric microbiota and clarified its research status, hotspots, and development trends. Materials and methods: Publications were retrieved from the Web of Science Core Collection on 18 July 2023. CiteSpace 6.2.R4, VOSviewer 1.6.19.0, and Biblioshiny were used for the co-occurrence and cooperation analyses of countries, institutions, authors, references, and keywords. A keyword cluster analysis and an emergence analysis were performed, and relevant knowledge maps were drawn. Results: The number of published papers in this field totaled 215 and showed an increasing trend. The analysis of funding suggested that the input in this field is increasing steadily. China had the highest number of publications, while the United States had the highest betweenness centrality. Baylor College of Medicine published the most articles cumulatively. Both Ferreira RM and Cooker OO had the highest citation frequency. The journal Helicobacter showed the most interest in this field, while Gut provided a substantial research foundation. A total of 280 keywords were obtained using CiteSpace, which were primarily focused on the eradication and pathogenic mechanisms of Helicobacter pylori, as well as the application of the gastric microbiota in the evaluation and treatment of gastric cancer. The burst analysis suggested that in the future, research may focus on the application of gastric microorganisms, particularly Fusobacterium nucleatum, in the diagnosis and treatment of gastric cancer, along with their pathogenic mechanisms. Conclusion: Current studies have been tracking the eradication of Helicobacter pylori and its pathogenic mechanisms, as well as changes in the gastric microbiota during gastric carcinogenesis. Future research may focus on the clinical application and pathogenesis of stomach microorganisms through bacteria such as Fusobacterium nucleatum. [ABSTRACT FROM AUTHOR]

Obacunone, a natural triterpenoid, is an active component of the herbs Dictamnus dasycarpus Turcz. and Phellodendron amurense Rupr, and an indicator of the herbs' quality. Owing to its multiple health benefits, several studies have investigated the multi-targeting potential action mechanisms of obacunone. To summarize recent developments on the pharmacological actions of obacunone and focus on the underlying molecular mechanisms and signaling networks, we searched PubMed, Europe PMC, Wiley Online Library, Web of Science, Google Scholar, Wanfang Medical Network, and China National Knowledge Infrastructure for articles published prior to March 2024. Existing research indicates obacunone has great potential to become a promising therapeutic option against tumors, fibrotic diseases, bone and cholesterol metabolism diseases, and infections of pathogenic microorganisms, among others. The paper contributes to providing up-to-date references for further research and clinical applications of obacunone. [ABSTRACT FROM AUTHOR]

Background: Whole-mount histopathology (WMH) has been a powerful tool to investigate the characteristics of prostate cancer. However, the latest advancement of WMH was yet under summarization. In this review, we offer a comprehensive exposition of current research utilizing WMH in diagnosing and treating prostate cancer (PCa), and summarize the clinical advantages of WMH and outlines potential on future prospects. Methods: An extensive PubMed search was conducted until February 26, 2023, with the search term "prostate", "whole-mount", "large format histology", which was limited to the last 4 years. Publications included were restricted to those in English. Other papers were also cited to contribute a better understanding. Results: WMH exhibits an enhanced legibility for pathologists, which improved the efficacy of pathologic examination and provide educational value. It simplifies the histopathological registration with medical images, which serves as a convincing reference standard for imaging indicator investigation and medical image-based artificial intelligence (AI). Additionally, WMH provides comprehensive histopathological information for tumor volume estimation, post-treatment evaluation, and provides direct pathological data for AI readers. It also offers complete spatial context for the location estimation of both intraprostatic and extraprostatic cancerous region. Conclusions: WMH provides unique benefits in several aspects of clinical diagnosis and treatment of PCa. The utilization of WMH technique facilitates the development and refinement of various clinical technologies. We believe that WMH will play an important role in future clinical applications. [ABSTRACT FROM AUTHOR]

Tumors have a huge impact on human life and are now the main cause of disease-related deaths. The main means of treatment are surgery and radiotherapy, but they are more damaging to the organism and have a poor postoperative prognosis. Therefore, we urgently need safe and effective drugs to treat tumors. In recent years, Chinese herbal medicines have been widely used in tumor therapy as complementary and alternative therapies. Medicinal and edible herbs are popular and have become a hot topic of research, which not only have excellent pharmacological effects and activities, but also have almost no side effects. Therefore, as a typical medicine and food homology, some components of Paeoniae Radix Alba (PRA, called Baishao in China) have been shown to have good efficacy and safety against cancer. Numerous studies have also shown that Paeoniae Radix Alba and its active ingredients treat cancer through various pathways and are also one of the important components of many antitumor herbal compound formulas. In this paper, we reviewed the literature on the intervention of Paeoniae Radix Alba in tumors and its mechanism of action in recent years and found that there is a large amount of literature on its effect on total glucosides of paeony (TGP) and paeoniflorin (PF), as well as an in-depth discussion of the mechanism of action of Paeoniae Radix Alba and its main constituents, with a view to promote the clinical development and application of Paeoniae Radix Alba in the field of antitumor management. [ABSTRACT FROM AUTHOR]

The multimodal and multidomain registration of medical images have gained increasing recognition in clinical practice as a powerful tool for fusing and leveraging useful information from different imaging techniques and in different medical fields such as cardiology and orthopedics. Image registration could be a challenging process, and it strongly depends on the correct tuning of registration parameters. In this paper, the robustness and accuracy of a landmarks-based approach have been presented for five cardiac multimodal image datasets. The study is based on 3D Slicer software and it is focused on the registration of a computed tomography (CT) and 3D ultrasound time-series of post-operative mitral valve repair. The accuracy of the method, as a function of the number of landmarks used, was performed by analysing root mean square error (RMSE) and fiducial registration error (FRE) metrics. The validation of the number of landmarks resulted in an optimal number of 10 landmarks. The mean RMSE and FRE values were 5.26 ± 3.17 and 2.98 ± 1.68 mm, respectively, showing comparable performances with respect to the literature. The developed registration process was also tested on a CT orthopaedic dataset to assess the possibility of reconstructing the damaged jaw portion for a pre-operative planning setting. Overall, the proposed work shows how 3D Slicer and registration by landmarks can provide a useful environment for multimodal/unimodal registration. [ABSTRACT FROM AUTHOR]

Background Value-based healthcare (VBHC) is a conceptual framework to improve the value of healthcare by health, care-process and economic outcomes. Benchmarking should provide useful information to identify best practices and therefore a good instrument to improve quality across healthcare organizations. This paper aims to provide a proof-of-concept of the feasibility of an international VBHC benchmarking in breast cancer, with the ultimate aim of being used to share best practices with a data-driven approach among healthcare organizations from different health systems. Methods In the VOICE community—a European healthcare centre cluster intending to address VBHC from theory to practice—information on patient-reported, clinical-related, care-process-related and economic-related outcomes were collected. Patient archetypes were identified using clustering techniques and an indicator set following a modified Delphi was defined. Benchmarking was performed using regression models controlling for patient archetypes and socio-demographic characteristics. Results Six hundred and ninety patients from six healthcare centres were included. A set of 50 health, care-process and economic indicators was distilled for benchmarking. Statistically significant differences across sites have been found in most health outcomes, half of the care-process indicators, and all economic indicators, allowing for identifying the best and worst performers. Conclusions To the best of our knowledge, this is the first international experience providing evidence to be used with VBHC benchmarking intention. Differences in indicators across healthcare centres should be used to identify best practices and improve healthcare quality following further research. Applied methods might help to move forward with VBHC benchmarking in other medical conditions. [ABSTRACT FROM AUTHOR]

Quickly and accurately completing endoscopic submucosal dissection (ESD) operations within narrow lumens is currently challenging because of the environment's high flexibility, invisible collision, and natural tissue motion. This paper proposes a novel stereo visual servoing control for a dual-segment robotic endoscope (DSRE) for ESD surgery. Departing from conventional monocular-based methods, our DSRE leverages stereoscopic imaging to rapidly extract precise depth data, enabling quicker controller convergence and enhanced surgical accuracy. The system's dual-segment configuration enables agile maneuverability around lesions, while its compliant structure ensures adaptability within the surgical environment. The implemented stereo visual servo controller uses image features for real-time feedback and dynamically updates gain coefficients, facilitating rapid convergence to the target. In visual servoing experiments, the controller demonstrated strong performance across various tasks. Even when subjected to unknown external forces, the controller maintained robust performance in target tracking. The feasibility and effectiveness of the DSRE were further verified through ex vivo experiments. We posit that this novel system holds significant potential for clinical application in ESD surgeries. [ABSTRACT FROM AUTHOR]

Background: There are many similarities in the clinical manifestations of human norovirus and SARS-CoV-2 infections, and nucleic acid detection is the gold standard for diagnosing both diseases. In order to expedite the identification of norovirus and SARS-CoV-2, a quantitative one-step triplex reverse transcription PCR (RT-qPCR) method was designed in this paper. Methods: A one-step triplex RT-qPCR assay was developed for simultaneous detection and differentiation of human norovirus GI (NoV-GI), GII (NoV-GII) and SARS-CoV-2 from fecal specimens. Results: The triplex RT-qPCR assay had high detection reproducibility (CV < 1%) and sensitivity. The lower limits of detection (LLOD95) of the triplex RT-qPCR assay for each target site were 128.5-172.8 copies/mL, and LLOD95 of the singleplex RT-qPCR assay were 110.3-142.0 copies/mL. Meanwhile, among the detection of clinical oropharyngeal swabs and fecal specimens, the results of the singleplex and triplex RT-qPCR assay showed high agreement. Conclusion: The triplex RT-qPCR assay for simultaneous detection of NoV-GI, NoV-GII and SARS-CoV-2 from fecal specimens has high clinical application value. [ABSTRACT FROM AUTHOR]

Introduction: Interest in 3D printing for orthopedic surgery has been increasing since its progressive adoption in most of the hospitals around the world. The aim of the study is to describe all the current applications of 3D printing in patients undergoing hip surgery of any type at the present time. Materials and Methods: We conducted a systematic narrative review of publications indexed in MedLine through the search engine PubMed, with the following parameters: 3D printing AND (orthopedics OR traumatology) NOT tissue engineering NOT scaffold NOT in vitro and deadline 31 July 2023. After reading the abstracts of the articles, papers were selected according to the following criteria: full text in English or Spanish and content related to hip surgery. Those publications involving experimental studies (in vitro or with anatomical specimens) or 3D printing outside of hospital facilities as well as 3D-printed commercial implants were excluded. Results are presented as a reference guide classified by disease, including the used software and the steps required for the development of the idea. Results: We found a total of 27 indications for in-house 3D printing for hip surgery, which are described in the article. Conclusions: There are many surgical applications of 3D printing in hip surgery, most of them based on CT images. Most of the publications lack evidence, and further randomized studies should be encouraged to assess the advantages of these indications. [ABSTRACT FROM AUTHOR]

Centipeda minima is a traditional Chinese medicine with wide applications and diverse pharmacological effects. Scholars have conducted extensive studies on its relevant clinical applications, especially its remarkable efficacy in cancer treatment. This paper thoroughly investigates the chemical composition and identification, pharmacological effects, and toxicity, along with the safety of Centipeda minima, so as to lay the foundation for corresponding clinical applications and product development. Furthermore, as global scholars have conducted extensive research on such clinical applications and made significant progress, the future development and utilization of Centipeda minima's active ingredients to create novel drugs are of great clinical significance. [ABSTRACT FROM AUTHOR]

Deployed surgical teams work together to perform time-critical damage control resuscitation However, the team often includes members who have never worked together or in the field A successful team can rapidly acquire knowledge of their clinical environment and each other In this paper, we explain how Immediate Action Drills (IADs) for the operating theatre department (OTD) can be used to orient individual clinicians to the field and how collective training in these drills can maximise the safety and efficiency of the surgical team [ABSTRACT FROM AUTHOR]

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Despite the increasing number of studies on nanomedicine-based cancer immunotherapy, the overall research trends in this field remain inadequately characterized. This study aims to evaluate the research trends and hotspots in nanomedicine-based cancer immunotherapy through a bibliometric analysis. As of March 31, 2024, relevant publications were retrieved from the Web of Science Core Collection. Analytical tools including VOSviewer, CiteSpace, and an online bibliometric analysis platform were employed. A total of 5,180 publications were analyzed. The study reveals geographical disparities in research output, with China and the United States being the leading contributors. Institutionally, the Chinese Academy of Sciences, University of Chinese Academy of Sciences, and Sichuan University are prominent contributors. Authorship analysis identifies key researchers, with Liu Zhuang being the most prolific author. "ACS Nano" and the "Journal of Controlled Release and Biomaterials" are identified as the leading journals in the field. Frequently occurring keywords include "cancer immunotherapy" and "drug delivery." Emerging frontiers in the field, such as "mRNA vaccine," "sonodynamic therapy," "oral squamous cell carcinoma," "STING pathway,"and "cGAS-STING pathway," are experiencing rapid growth. This study aims to provide new insights to advance scientific research and clinical applications in nanomedicine-based cancer immunotherapy. [ABSTRACT FROM AUTHOR]

[Display omitted] • The immune response and inflammation in pulmonary hypertension (PH) have been systematically summarized based on recent studies. • The relationship between CC chemokines and the pathogenesis of pH is summarized in clinical and animal models. • We found that although the immune response serves as an important potential factor in the pathogenesis of PH, less attention has been paid to CC chemokines and their receptors. • We believe that a greater understanding of the relationship between PH and CC chemokines and their receptors is a pressing issue. • We believe that we need to further clarify the pathogenesis of pH and provide basis for the clinical treatment of PH. Pulmonary hypertension (PH) represents a progressive condition characterized by the remodeling of pulmonary arteries, ultimately culminating in right heart failure and increased mortality rates. Substantial evidence has elucidated the pivotal role of perivascular inflammatory factors and immune dysregulation in the pathogenesis of PH. Chemokines, a class of small secreted proteins, exert precise control over immune cell recruitment and functionality, particularly with respect to their migration to sites of inflammation. Consequently, chemokines emerge as critical drivers facilitating immune cell infiltration into the pulmonary tissue during inflammatory responses. This review comprehensively examines the significant contributions of CC chemokines in the maintenance of immune cell homeostasis and their pivotal role in regulating inflammatory responses. The central focus of this discussion is directed towards elucidating the precise immunoregulatory actions of CC chemokines concerning various immune cell types, including neutrophils, monocytes, macrophages, lymphocytes, dendritic cells, mast cells, eosinophils, and basophils, particularly in the context of pH processes. Furthermore, this paper delves into an exploration of the underlying pathogenic mechanisms that underpin the development of PH. Specifically, it investigates processes such as cellular pyroptosis, examines the intricate crosstalk between bone morphogenetic protein receptor type 2 (BMPR2) mutations and the immune response, and sheds light on key signaling pathways involved in the inflammatory response. These aspects are deemed critical in enhancing our understanding of the complex pathophysiology of PH. Moreover, this review provides a comprehensive synthesis of findings from experimental investigations targeting immune cells and CC chemokines. Aim of review : In summary, the inquiry into the inflammatory responses mediated by CC chemokines and their corresponding receptors, and their potential in modulating immune reactions, holds promise as a prospective avenue for addressing PH. The potential inhibition of CC chemokines and their receptors stands as a viable strategy to attenuate the inflammatory cascade and ameliorate the pathological manifestations of PH. Nonetheless, it is essential to acknowledge the current state of clinical trials and the ensuing progress, which regrettably appears to be less than encouraging. Substantial hurdles exist in the successful translation of research findings into clinical applications. The intention is that such emphasis could potentially foster the advancement of potent therapeutic agents presently in the process of clinical evaluation. This, in turn, may further bolster the potential for effective management of PH. [ABSTRACT FROM AUTHOR]