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Introduction: Osteoporosis is a major disease state associated with significant morbidity, mortality, and health care costs. Less than half of the individuals sustaining a low energy hip fracture are diagnosed and treated for the underlying osteoporosis. Objective: A multidisciplinary Canadian hip fracture working group has developed practical recommendations to meet Canadian quality indicators in post hip fracture care. Methods: A comprehensive narrative review was conducted to identify and synthesize key articles on post hip fracture orthogeriatric care for each of the individual sections and develop recommendations. These recommendations are based on the best evidence available today. Conclusion: Recommendations are anticipated to reduce recurrent fractures, improve mobility and healthcare outcomes post hip fracture, and reduce healthcare costs. Key messages to enhance postoperative care are also provided. [ABSTRACT FROM AUTHOR]

To achieve clinical impact in daily oncological practice, emerging AI-based cancer imaging research needs to have clearly defined medical focus, AI methods, and outcomes to be estimated. AI-supported cancer imaging should predict major relevant clinical endpoints, aiming to extract associations and draw inferences in a fair, robust, and trustworthy way. AI-assisted solutions as medical devices, developed using multicenter heterogeneous datasets, should be targeted to have an impact on the clinical care pathway. When designing an AI-based research study in oncologic imaging, ensuring clinical impact in AI solutions requires careful consideration of key aspects, including target population selection, sample size definition, standards, and common data elements utilization, balanced dataset splitting, appropriate validation methodology, adequate ground truth, and careful selection of clinical endpoints. Endpoints may be pathology hallmarks, disease behavior, treatment response, or patient prognosis. Ensuring ethical, safety, and privacy considerations are also mandatory before clinical validation is performed. The Artificial Intelligence for Health Imaging (AI4HI) Clinical Working Group has discussed and present in this paper some indicative Machine Learning (ML) enabled decision-support solutions currently under research in the AI4HI projects, as well as the main considerations and requirements that AI solutions should have from a clinical perspective, which can be adopted into clinical practice. If effectively designed, implemented, and validated, cancer imaging AI-supported tools will have the potential to revolutionize the field of precision medicine in oncology. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) has made tremendous advances in recent years and will presumably have a major impact in health care. These advancements are expected to affect different aspects of clinical medicine and lead to improvement of delivered care but also optimization of available resources. As a modern specialty that extensively relies on imaging, interventional radiology (IR) is primed to be on the forefront of this development. This is especially relevant since IR is a highly advanced specialty that heavily relies on technology and thus is naturally susceptible to disruption by new technological developments. Disruption always means opportunity and interventionalists must therefore understand AI and be a central part of decision-making when such systems are developed, trained, and implemented. Furthermore, interventional radiologist must not only embrace but lead the change that AI technology will allow. The CIRSE position paper discusses the status quo as well as current developments and challenges. [ABSTRACT FROM AUTHOR]

Cardiac magnetic resonance (CMR) has become an essential tool for the evaluation of patients affected or at risk of developing cardiomyopathies (CMPs). In fact, CMR not only provides precise data on cardiac volumes, wall thickness, mass and systolic function but it also a non-invasive characterization of myocardial tissue, thus helping the early diagnosis and the precise phenotyping of the different CMPs, which is essential for early and individualized treatment of patients. Furthermore, several CMR characteristics, such as the presence of extensive LGE or abnormal mapping values, are emerging as prognostic markers, therefore helping to define patients' risk. Lastly new experimental CMR techniques are under investigation and might contribute to widen our knowledge in the field of CMPs. In this perspective, CMR appears an essential tool to be systematically applied in the diagnostic and prognostic work-up of CMPs in clinical practice. This review provides a deep overview of clinical applicability of standard and emerging CMR techniques in the management of CMPs. [ABSTRACT FROM AUTHOR]

In recent years, medical image segmentation methods based on deep learning have been of great importance for disease diagnosis and treatment planning in clinical medicine. U-Net and a series of networks derived from it have led the research trend in medical image segmentation. In this paper, an end-to-end lightweight MLP-based medical image segmentation network G-UNeXt is proposed to address the problems of high computational complexity, large number of model parameters and slow inference in medical image segmentation networks. Firstly, this paper proposes a new skip connection method Ghost path. It reduces the semantic gap between features while combining different levels of features, and exploits the redundancy of features, which helps to improve the segmentation ability of the model for details. Secondly, this paper designs a cheap and effective G-S block, which uses low-cost linear operations to mine potential ghost features outside of intrinsic features. The G-S block reduce the number of parameters and computational complexity compared to traditional convolution. In addition, it can also adaptively calibrate the channel feature response, enhancing the characterization capability of the network and bringing some performance improvement at a lower computational cost. Finally, we build the lightweight MLP-based network G-UNeXt used Ghost path and G-S block for real-time segmentation of medical images. The results tested on the benchmark medical image segmentation datasets BUSI and ISIC2018 show that G-UNeXt reduces the parameters by 33% and the computational complexity by 23.7% compared with UNeXt. In addition, G-UNeXt also obtains faster inference speed and higher segmentation accuracy. [ABSTRACT FROM AUTHOR]

Diabetic retinopathy, a microvascular condition associated with an increased risk of cardiovascular disease, poses a substantial global healthcare challenge. The demand for timely diagnosis has prompted the development of automated solutions due to the scarcity of specialists. In this paper, we introduce a ground-breaking approach to diabetic retinopathy detection – the Diabetic Retinopathy Residual Network (DR-ResNet +). The proposed model leverages the power of deep learning to automatically extract features, achieving optimal results in just seven training epochs. The DR-ResNet + architecture is meticulously designed by incorporating a series of convolutional, pooling, and fully connected layers. Hyperparameter optimization is done using both grid and random search techniques to ensure peak performance. To validate the proposed model's robustness, simulated results are compared with well-established deep learning models, such as GoogleNet, VGG16, and AlexNet, using a comprehensive Kaggle dataset comprising over 35,000 retinal images. Moreover, the proposed model is also tested on external datasets like MESSIDOR and IDRiD for its validation. Simulation results reveal that the proposed DR-ResNet + model not only reduces training time by an impressive 95% but also exhibits outstanding performance metrics, including an accuracy of 0.9898, specificity of 0.9916, precision of 0.9670, sensitivity of 0.9829, and an F1-score of 0.9748. These findings position the proposed model as exceptionally well-suited for real-time clinical applications, offering a potential game-changer in diabetic retinopathy diagnosis. This paper presents DR-ResNet + as a pioneering advancement in diabetic retinopathy diagnosis. With its rapid training, superior accuracy, and significant real-world implications, the model holds promise for transforming the landscape of healthcare by providing timely and precise diagnoses for this critical condition. [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]

Motivated by a recent trend that advocates a reassessment of the aim of medical science and clinical practice, this paper investigates the epistemic aims of biomedical research. Drawing on contemporary discussions in epistemology and the philosophy of science, along with a recent study on scurvy, this paper (1) explores the concept of understanding as the aim of scientific inquiry and (2) establishes a framework that will guide the examination of its forms in biomedical research. Using the case of Tuberculosis (TB), (3) it is argued that grasping a mechanistic explanation is crucial for reaching a threshold of understanding at which we may speak of an objectual, biomedical understanding of TB. [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]

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]

The external and middle ear conditions are diagnosed using a digital otoscope. The clinical diagnosis of ear conditions is suffered from restricted accuracy due to the increased dependency on otolaryngologist expertise, patient complaint, blurring of the otoscopic images, and complexity of lesions definition. There is a high requirement for improved diagnosis algorithms based on otoscopic image processing. This paper presented an ear diagnosis approach based on a convolutional neural network (CNN) as feature extraction and long short-term memory (LSTM) as a classifier algorithm. However, the suggested LSTM model accuracy may be decreased by the omission of a hyperparameter tuning process. Therefore, Bayesian optimization is used for selecting the hyperparameters to improve the results of the LSTM network to obtain a good classification. This study is based on an ear imagery database that consists of four categories: normal, myringosclerosis, earwax plug, and chronic otitis media (COM). This study used 880 otoscopic images divided into 792 training images and 88 testing images to evaluate the approach performance. In this paper, the evaluation metrics of ear condition classification are based on a percentage of accuracy, sensitivity, specificity, and positive predictive value (PPV). The findings yielded a classification accuracy of 100%, a sensitivity of 100%, a specificity of 100%, and a PPV of 100% for the testing database. Finally, the proposed approach shows how to find the best hyperparameters concerning the Bayesian optimization for reliable diagnosis of ear conditions under the consideration of LSTM architecture. This approach demonstrates that CNN-LSTM has higher performance and lower training time than CNN, which has not been used in previous studies for classifying ear diseases. Consequently, the usefulness and reliability of the proposed approach will create an automatic tool for improving the classification and prediction of various ear pathologies. [ABSTRACT FROM AUTHOR]

Lung cancer, being the most widespread and lethal form of cancer globally, has a high incidence and mortality rate primarily attributed to challenges associated with early detection, extensive metastasis, and frequent recurrence. In the context of lung cancer development, noncoding RNA molecules have a crucial role in governing gene expression and protein synthesis. Specifically, tRNA-derived fragments (tRFs), a subset of noncoding RNAs, exert significant biological influences on cancer progression, encompassing transcription and translation processes as well as epigenetic regulation. This article primarily examines the mechanisms by which tRFs modulate gene expression and contribute to tumorigenesis in lung cancer. Furthermore, we provide a comprehensive overview of the current bioinformatics analysis of tRFs in lung cancer, with the objective of offering a systematic and efficient approach for studying the expression profiling, functional enrichment, and molecular mechanisms of tRFs in this disease. Finally, we discuss the clinical significance and potential avenues for future research on tRFs in lung cancer. This paper presents a comprehensive systematic review of the existing research findings on tRFs in lung cancer, aiming to offer improved biomarkers and drug targets for clinical management of lung cancer. [ABSTRACT FROM AUTHOR]

The clinical decision-making is a group decision-making process given by the imbalanced decision-making groups, which has hybrid quantitative and qualitative attributes. Data-driven decision-making paradigm is a novel idea for constructing a clinical quantitative decision-making model. The conflict analysis provides an effective method for managing the imbalanced group decision-making problems with hybrid attributes. In this paper, we consider a kind of imbalanced group confilct problems with hybrid quantitative and qualitative attributes information given by large and small groups and use three-way conflict analysis to solve these problems. First, a hybrid information system is repersented the qualitative and quantitative hybrid attribute information given by large and small groups. Further, the real-value information system consisting of hybrid quantitative and qualitative attributes information given by this imbalanced group is transformed into a 19-scale conflict information system. Then, the optimal alternatives are derived by measuring group conflict degree, conflict function, and group conflict measurement in a three-way conflict framework. Finally, the clinical decision-making problem of rheumatoid arthritis treated with integrated TCM and Western medicine clinic as the research object, the conflict analysis process and steps of the theoretical model constructed in this paper are validated and explicitly applied based on the actual clinical data of Guangdong Provincial Hospital of Chinese Medicine, furthermore the quantitative conflict analysis simulated by actual clinical data is given, which obtains application results that are almost consistent with real clinical scenarios. On the one hand, the paper's research extends a novel conflict analysis model and idea for the group conflict analysis with imbalanced, quantitative, and qualitative hybrid information attributes. On the other hand, it also provides a new attempt and exploration for applyling of three-way conflict analysis in clinical decisions. [ABSTRACT FROM AUTHOR]

Most victims of physical violence sooner or later will access a hospital or medical cabinet because of that violence, and in particular emergency departments (EDs). This paper aims to analyze the performance of emergency ward clinicians in the forensic management of such victims by examining the activities carried out and the data reported. A total of 991 medical records were extrapolated from the database of the ED of the Policlinico of Milan in an average pre-pandemic 1-year activity. For each medical record, 16 parameters were analyzed in-depth including epidemiological data, information on the type of violent actions, injuries, and time between the infliction of the lesion and access to the ED. In the vast majority of cases, all the actions with medicolegal implications had been neglected by health professionals causing loss of data not only for the justice system but especially for correctly interpreting what happened and taking appropriate measures to protect the patient/victim. Hence, given that clinicians in EDs are busy with non-forensic clinical tasks (and rightly so), it should be ensured that there be specific forensic clinical personnel. However, it is crucial that when unfortunately there can be no forensic staff, at least the clinicians who work in the ED are properly trained to correctly apply essential medicolegal measures. Overall, timely and informed medical and forensic intervention is possible and necessary for the improvement and maintenance of the mental and physical health of victims of violence. [ABSTRACT FROM AUTHOR]

As a kind of well-known moxibustion material across the world, Artemisia argyi Folium (AAF) has a definite curative effect. From 1996 to now, various studies on AAF have been increasing year by year. That is why this paper is conducted because of no comprehensive summary except for an essential oil review recently published in 2023. Using "AAF" and "mugwort" as keywords, the related literature was summarized in four internationally recognized databases: PubMed, Web of Science, ACS, and ScienceDirect, mainly include four aspects such as botany, phytochemistry, pharmacology, and clinical application. Four traditional identification methods and two new ones were reported. A total of 136 compounds were identified, among which 23 new terpenoids and two new flavonoids were discovered. The pharmacological effects of AAF mainly focus on anti-inflammatory, anti-tumor, antioxidant, antibacterial, and other aspects. Clinically, it is mainly used in respiratory, immune, digestive, and nervous systems in addition to gynecology. The current research mainly focuses on the composition and pharmacology of AAF. Future studies should thoroughly establish the quality criteria and pharmacokinetics of AAF. According to the different application fields, the corresponding quality standards should be formulated to ensure the efficacy of drugs in the actual treatment. [ABSTRACT FROM AUTHOR]

Background: Standardized clinical care processes for patients with Crohn's disease (CD) and a permanent ileostomy (PI) are lacking. The EndOTrial consortium aims to address this gap by developing pathways for care. Methods: In this umbrella review, we searched major databases for relevant systematic reviews (SRs) or scoping reviews (ScR) published until January 5, 2024. Screening, data extraction, and quality appraisal (AMSTAR 2) were performed by two independent reviewers. Results: Of 1349 screened papers, 22 reviews met our inclusion criteria, including 20 SRs (eight with meta-analysis) and 2 ScRs. None exclusively focused on PI. Furthermore, nine reviews did not mention patients with inflammatory bowel disease (IBD), and only two reviews included patients with high-output ileostomy, highlighting a large evidence gap. The identified reviews covered six categories with nine types of interventions, including ostomy care pathways, peristomal skin care, patient education, clinical management of high-output stoma, management and prevention of postoperative ileus, dietary and nutritional support, nursing and supporting care, telemedicine, and self-management interventions. Most SRs including nursing interventions for stoma care highlighted nurses' role in a variety of standard and specialized treatments. Notably, none of the reviews exclusively examined disease recurrence, stoma pouching systems or adhesives, behavioral interventions, or mental health in patients living with ileostomy. Conclusions: Evidence for best practice interventions to treat complications and improve quality of life in patients living with an ileostomy for CD is limited and heterogeneous. These results outline the need for standardized clinical care processes and pathways tailored to the unique needs of this patient population. [ABSTRACT FROM AUTHOR]

Purpose: Cricopharyngeus muscle dysfunction (CPMD) is a common clinical occurrence with very few clear diagnostic criteria and multiple pathways for treatment. Incidence of CPMD is not known, but some data suggest around 25% of people with dysphagia experience some degree of CPMD, which negatively impacts swallowing safety and efficiency. Workup and treatment of CPMD can require multidisciplinary collaboration across laryngologists, speech-language pathologists with training in dysphagia management, and gastroenterologists. The purpose of this paper is to review what is known about CPMD and identify areas of future research in CPMD diagnosis and treatment. Methods: An overview of CPMD, relative treatments and disorders, and a discussion of future areas of research needed to improve clinical care of CPMD. Results: Details regarding historical background, pathophysiology and treatment practiced for CPMD are included. Conclusion: In summary, CPMD is a poorly defined disease due to a lack of understanding of its pathophysiology and the lack of consensus diagnostic criteria. Well-designed, prospective clinical trials are necessary to develop a better understanding of clinical incidence of CPMD, impact of the disorder on oropharyngeal swallowing, and how to approach treatment of the disorder surgically or in conjunction with therapy directed by a specialized speech-language pathologist. [ABSTRACT FROM AUTHOR]

Articular cartilage damage and degeneration are among hallmark manifestations of joint injuries and arthritis, classically osteoarthritis. Cartilage compositional MRI (Cart-C MRI), a quantitative technique, which aims to detect early-stage cartilage matrix changes that precede macroscopic alterations, began development in the 1990s. However, despite the significant advancements over the past three decades, Cart-C MRI remains predominantly a research tool, hindered by various technical and clinical hurdles. This paper will review the technical evolution of Cart-C MRI, delve into its clinical applications, and conclude by identifying the existing gaps and challenges that need to be addressed to enable even broader clinical application of Cart-C MRI. [ABSTRACT FROM AUTHOR]

Histological terminology of the female genital organs is currently a part of the internationally accepted nomenclature Terminologia Histologica (TH), the latest edition of which dates back to 2008. Many new discoveries have been documented within 16 years since then, and many discrepancies have been found. This paper aims to revise the terminology from clinical and educational perspectives comprehensively. The authors thoroughly searched the current edition of "Terminologia Histologica: International Terms for Human Cytology and Histology," focusing on missing and controversial terms in the chapter Female genital system. The authors identified six controversial and ambiguous terms and four missing important histological terms. The authors also discussed the addition of less used eponymic terms in the histological description of female genital organs like Hamperl cells, Popescu cells, Kroemer lacunae, Balbiani bodies, Call–Exner bodies, membrane of Slavianski, nabothian cysts, or anogenital sweat glands of van der Putte. We expect the second and revised edition of the TH to be published soon and hope that the Federative International Program on Anatomical Terminology will approve and incorporate all these propositions and suggestions. We also strongly recommend using the official internationally accepted Latin and English histological nomenclature—the TH, either in oral or written form, both in theoretical and clinical medicine. [ABSTRACT FROM AUTHOR]

Traditionally, common testing problems are formalized in terms of a precise null hypothesis representing an idealized situation such as absence of a certain "treatment effect". However, in most applications the real purpose of the analysis is to assess evidence in favor of a practically relevant effect, rather than simply determining its presence/absence. This discrepancy leads to erroneous inferential conclusions, especially in case of moderate or large sample size. In particular, statistical significance, as commonly evaluated on the basis of a precise hypothesis low p value, bears little or no information on practical significance. This paper presents an innovative approach to the problem of testing the practical relevance of effects. This relies upon the proposal of a general method for modifying standard tests by making them suitable to deal with appropriate interval null hypotheses containing all practically irrelevant effect sizes. In addition, when it is difficult to specify exactly which effect sizes are irrelevant we provide the researcher with a benchmark value. Acceptance/rejection can be established purely by deciding on the (ir)relevance of this value. We illustrate our proposal in the context of many important testing setups, and we apply the proposed methods to two case studies in clinical medicine. First, we consider data on the evaluation of systolic blood pressure in a sample of adult participants at risk for nutritional deficit. Second, we focus on a study of the effects of remdesivir on patients hospitalized with COVID-19. [ABSTRACT FROM AUTHOR]

Introduction: The European Association of Urology (EAU) and the American Society of Clinical Oncology (ASCO) recently issued updated guidelines on penile cancer, emphasising dynamic sentinel node biopsy (DSNB) as the preferred method for surgical staging among patients with invasive penile tumours and no palpable inguinal lymphadenopathy. This paper outlines the rationale behind this new recommendation and describes remaining challenges, as well as strategies for promoting DSNB worldwide. Main text: DSNB offers high diagnostic accuracy with the lowest postoperative complications compared to open or minimally invasive inguinal lymph node dissection (ILND), prompting its preference in the new guidelines. Nevertheless, despite its advantages, there are challenges hampering the widespread adoption of DSNB. This includes the false-negative rate associated with DSNB and the potential negative impact on patient outcome. To address this issue, improvements should be made in several areas, including refining the timing and interpretation of the lymphoscintigraphy and the single photon emission computed tomography/computed tomography images. In addition, the quantity of tracer employed and choice of the injection site for the radiopharmaceutical should be optimised. Finally, limiting the removal of nodes without tracer activity during surgery may help minimise complication rates. Conclusion: Over the years, DSNB has evolved significantly, related to the dedicated efforts and innovations in nuclear medicine and subsequent clinical studies validating its efficacy. It is now strongly recommended for surgical staging among selected penile cancer patients. To optimise DSNB further, multidisciplinary collaborative research is required to improve SN identification for better diagnostic accuracy and fewer complications. [ABSTRACT FROM AUTHOR]

Background: The anatomical basis of pituitary adenomas (PAs) with oculomotor cistern (OC) extension as a growth corridor is overlooked in the literature. In this paper, the authors use the technique of epoxy sheet plastination to study the membranous structure of the OC and validate the results by retrospective analysis of patients with OC extension. Methods: Eighteen specimens were used to study the membranous anatomy surrounding the OC using the epoxy sheet plastination technique. Thirty-four patients with OC extension were retrospectively reviewed. Results: The OC consisted of two thin membranous layers. The inner layer was extended by the arachnoid layer from the posterior fossa, and the lateral layer consisted of the dura mater sinking from the roof of the cavernous sinus. The oculomotor nerve is more likely to displace with a superolateral trajectory due to the weakness of the posterior dura and the relatively large space in the medial and posterior trajectories, which is consistent with the intraoperative observations. Among the anatomical factors that affect the PA by OC extension, we found that the relative position of the internal carotid artery (ICA) and posterior clinoid process may lead to the narrowing of the OC. Of 34 cases, 28 patients achieved total resection. Among 24 preoperative patients with oculomotor nerve palsy, 16 cases were relieved to varying degrees postoperatively. There was no ICA injury or severe intracranial infection found in any of the patients. Conclusions: Extension into the OC is influenced by two anatomical factors: a weak point in the dura in the posterior OC and a potential space beyond this region of the dura. Meticulous knowledge of the membranous anatomy in endoscopic endonasal surgery is required to safely and effectively resect PA with OC extension. [ABSTRACT FROM AUTHOR]

The advent of artificial intelligence (AI) and machine learning (ML) has revolutionized the field of medicine. Although highly effective, the rapid expansion of this technology has created some anticipated and unanticipated bioethical considerations. With these powerful applications, there is a necessity for framework regulations to ensure equitable and safe deployment of technology. Generative Adversarial Networks (GANs) are emerging ML techniques that have immense applications in medical imaging due to their ability to produce synthetic medical images and aid in medical AI training. Producing accurate synthetic images with GANs can address current limitations in AI development for medical imaging and overcome current dataset type and size constraints. Offsetting these constraints can dramatically improve the development and implementation of AI medical imaging and restructure the practice of medicine. As observed with its other AI predecessors, considerations must be taken into place to help regulate its development for clinical use. In this paper, we discuss the legal, ethical, and technical challenges for future safe integration of this technology in the healthcare sector. [ABSTRACT FROM AUTHOR]

A phonocardiogram (PCG) is a plot of high-fidelity recording of the sounds of the heart obtained using an electronic stethoscope that is highly valuable in clinical medicine. It can help cardiologists diagnose cardiovascular diseases quickly and accurately. In this paper, we propose a multi-view deep network for the classification of PCG signals that can extract rich multi-view features from different modalities of PCG for classification. The model is mainly composed of two branches. In the first branch, we divide each PCG signal into three equal-length sub-signals, using Gramian Angular Fields to encode them from audio modality to two-dimensional image modality, and then Res2Net is applied to extract the image view features. In the second branch, we propose MobileNet-LSTM to extract the features of another view from preprocessed PCG signals. Finally, the features from these two views are fused and fed into the classifier for classification. Experiments show that our proposed method achieves 97.99% accuracy on the 2016 PhysioNet/CinC Challenge dataset, which is very competitive compared with the existing baseline models. In addition, the ablation experiment proves the necessity and effectiveness of our proposed method. [ABSTRACT FROM AUTHOR]

Highly precise micromanipulation tools that can manipulate and interrogate cell organelles and components must be developed to support the rapid development of new cell-based medical therapies, thereby facilitating in-depth understanding of cell dynamics, cell component functions, and disease mechanisms. This paper presents a literature review on micro/nanomanipulation tools and their control methods for single-cell surgery. Micromanipulation methods specifically based on laser, microneedle, and untethered micro/nanotools are presented in detail. The limitations of these techniques are also discussed. The biological significance and clinical applications of single-cell surgery are also addressed in this paper. [ABSTRACT FROM AUTHOR]

Big data analytics utilizes different techniques to transform large volumes of big datasets. The analytics techniques utilize various computational methods such as Machine Learning (ML) for converting raw data into valuable insights. The ML assists individuals in performing work activities intelligently, which empowers decision-makers. Since academics and industry practitioners have growing interests in ML, various existing review studies have explored different applications of ML for enhancing knowledge about specific problem domains. However, in most of the cases existing studies suffer from the limitations of employing a holistic, automated approach. While several researchers developed various techniques to automate the systematic literature review process, they also seemed to lack transparency and guidance for future researchers. This research aims to promote the utilization of intelligent literature reviews for researchers by introducing a step-by-step automated framework. We offer an intelligent literature review to obtain in-depth analytical insight of ML applications in the clinical domain to (a) develop the intelligent literature framework using traditional literature and Latent Dirichlet Allocation (LDA) topic modeling, (b) analyze research documents using traditional systematic literature review revealing ML applications, and (c) identify topics from documents using LDA topic modeling. We used a PRISMA framework for the review to harness samples sourced from four major databases (e.g., IEEE, PubMed, Scopus, and Google Scholar) published between 2016 and 2021 (September). The framework comprises two stages—(a) traditional systematic literature review consisting of three stages (planning, conducting, and reporting) and (b) LDA topic modeling that consists of three steps (pre-processing, topic modeling, and post-processing). The intelligent literature review framework transparently and reliably reviewed 305 sample documents. [ABSTRACT FROM AUTHOR]

Pragmatism in clinical trials is focused on increasing the generalizability of research findings for routine clinical care settings. Hybridism in clinical trials (i.e., assessing both clinical effectiveness and implementation success) is focused on speeding up the process by which evidence-based practices are developed and adopted into routine clinical care. Even though pragmatic trial methodologies and implementation science evolved from very different disciplines, Pragmatic Trials and Hybrid Effectiveness-Implementation Trials share many similar design features. In fact, these types of trials can easily be conflated, creating the potential for investigators to mislabel their trial type or mistakenly use the wrong trial type to answer their research question. Blurred boundaries between trial types can hamper the evaluation of grant applications, the scientific interpretation of findings, and policy-making. Acknowledging that most trials are not pure Pragmatic Trials nor pure Hybrid Effectiveness-Implementation Trials, there are key differences in these trial types and they answer very different research questions. The purpose of this paper is to clarify the similarities and differences of these trial types for funders, researchers, and policy-makers. In addition, recommendations are offered to help investigators choose, label, and operationalize the most appropriate trial type to answer their research question. These recommendations complement existing reporting guidelines for clinical effectiveness trials (TIDieR) and implementation trials (StaRI). [ABSTRACT FROM AUTHOR]

On July 19th, 2023, the National Institute of Allergy and Infectious Diseases co-organized a workshop with the Society of Mathematical Biology, with the authors of this paper as the organizing committee. The workshop, "Bridging multiscale modeling and practical clinical applications in infectious diseases" sought to create an environment for mathematical modelers, statisticians, and infectious disease researchers and clinicians to exchange ideas and perspectives. [ABSTRACT FROM AUTHOR]

Nucleic acid testing technology has made considerable progress in the last few years. However, there are still many challenges in the clinical application of multiple nucleic acid assays, such as how to ensure accurate results, increase speed and decrease cost. Herein, a three-way junction structure has been introduced to specifically translate analytes of loop-mediated isothermal amplification to a catalytic hairpin assembly. For different analyses, a well-optimized nucleic acid circuit can be directly applied to detection, through only one-component replacement, which only not avoids duplicate sequence design but also saves detection cost. Thanks to this design, multiple and logical analysis can be easily realized in a single reaction with ultra-high sensitivity and selectivity. In this paper, Mycoplasma pneumoniae and Streptococcus pneumoniae can be clearly distinguished from the clinical mixed sample with negative control or one analyte in one tube single fluorescence channel. The fair experimental results of actual clinical samples provide a strong support for the possibility of clinical application of this methodology. [ABSTRACT FROM AUTHOR]

Background: [18F]fluoromisonidazole ([18F]FMISO, 1H-1-(3-[18F]fluoro-2-hydroxypropyl)-2-nitroimidazole) is a commonly used radiotracer for imaging hypoxic conditions in cells. Since hypoxia is prevalent in solid tumors, [18F]FMISO is in clinical application for decades to explore oxygen demand in cancer cells and the resulting impact on radiotherapy and chemotherapy. Results: Since the introduction of [18F]FMISO as positron emission tomography imaging agent in 1986, a variety of radiosynthesis procedures for the production of this hypoxia tracer has been developed. This paper gives a brief overview on [18F]FMISO radiosyntheses published so far from its introduction until now. From a radiopharmaceutical chemist's perspective, different precursors, radiolabeling approaches and purification methods are discussed as well as used automated radiosynthesizers, including cassette-based and microfluidic systems. Conclusion: In a GMP compliant radiosynthesis using original cassettes for FASTlab we produced [18F]FMISO in 49% radiochemical yield within 48 min with radiochemical purities > 99% and molar activities > 500 GBq/µmol. In addition, we report an easy and efficient radiosynthesis of [18F]FMISO, based on in-house prepared FASTlab cassettes, providing the radiotracer for research and preclinical purposes in good radiochemical yields (39%), high radiochemical purities (> 99%) and high molar activity (> 500 GBq/µmol) in a well-priced option. [ABSTRACT FROM AUTHOR]

The practice of clinical medicine is imbued with uncertainty. The ways in which clinicians and patients think about, communicate about, and act within situations of heightened uncertainty can have significant implications for the therapeutic alliance and for the trajectory and outcomes of clinical care. Despite this, there is limited guidance about the best methods for physicians to recognize, acknowledge, communicate about, and manage uncertainty in clinical settings. In this paper, we propose a structured approach for discussing and managing uncertainty within the context of a clinician-patient relationship. The approach involves four steps: Recognize, Acknowledge, Partner, and Seek Support (i.e., the RAPS framework). The approach is guided by existing literature on uncertainty as well as our own experience as clinicians working at different stages of career. We define each component of the approach and present sample language and actions for how to implement it in practice. Our aim is to empower clinicians to regard situations of high uncertainty as an opportunity to deepen the therapeutic alliance with the patient, and simultaneously to grow and learn as practitioners. [ABSTRACT FROM AUTHOR]

Background: Care for patients undergoing elective colectomy has become increasingly standardized using Enhanced Recovery Programs (ERP). ERP, encorporating minimally invasive surgery (MIS), decreased postoperative morbidity and length of stay (LOS). However, disruptive changes are needed to safely introduce colectomy in an ambulatory or same-day discharge (SDD) setting. Few research groups showed the feasibility of ambulatory colectomy. So far, no minimum standards for the quality of care of this procedure have been defined. This study aims to identify quality indicators (QIs) that assess the quality of care for ambulatory colectomy. Methods: A literature search was performed to identify recommendations for ambulatory colectomy. Based on that search, a set of QIs was identified and categorized into seven domains: preparation of the patient (pre-admission), anesthesia, surgery, in-hospital monitoring, home monitoring, feasibility, and clinical outcomes. This list was presented to a panel of international experts (surgeons and anesthesiologists) in a 1 round Delphi to assess the relevance of the proposed indicators. Results: Based on the literature search (2010–2021), 3841 results were screened on title and abstract for relevant information. Nine papers were withheld to identify the first set of QIs (n = 155). After excluding duplicates and outdated QIs, this longlist was narrowed down to 88 indicators. Afterward, consensus was reached in a 1 round Delphi on a final list of 32 QIs, aiming to be a comprehensive set to evaluate the quality of ambulatory colectomy care. Conclusion: We propose a list of 32 QI to guide and evaluate the implementation of ambulatory colectomy. [ABSTRACT FROM AUTHOR]

What are the limits of the use of artificial intelligence (AI) in the relational aspects of medical and nursing care? There has been a lot of recent work and applications showing the promise and efficiency of AI in clinical medicine, both at the research and treatment levels. Many of the obstacles discussed in the literature are technical in character, regarding how to improve and optimize current practices in clinical medicine and also how to develop better data bases for optimal parameter adjustments and predictive algorithms. This paper argues that there are also in principle obstacles to the application of AI in clinical medicine and care where empathy is important, and that these problems cannot be solved with any of the technical and theoretical approaches that shape the current application of AI in specific areas of clinical medicine in which care for patients is fundamental. This is important, because it generates specific risks that may be overlooked otherwise, and it justifies the necessity of human monitoring and emotional intervention in clinical medicine. Consequently, difficult issues concerning moral and legal responsibility may ensue if these in principle problems are ignored. [ABSTRACT FROM AUTHOR]

Background and Objective: More than half of all drugs are still prescribed off-label to children. Pharmacokinetic (PK) data are needed to support off-label dosing, however for many drugs such data are either sparse or not representative. Physiologically-based pharmacokinetic (PBPK) models are increasingly used to study PK and guide dosing decisions. Building compound models to study PK requires expertise and is time-consuming. Therefore, in this paper, we studied the feasibility of predicting pediatric exposure by pragmatically combining existing compound models, developed e.g. for studies in adults, with a pediatric and preterm physiology model. Methods: Seven drugs, with various PK characteristics, were selected (meropenem, ceftazidime, azithromycin, propofol, midazolam, lorazepam, and caffeine) as a proof of concept. Simcyp® v20 was used to predict exposure in adults, children, and (pre)term neonates, by combining an existing compound model with relevant virtual physiology models. Predictive performance was evaluated by calculating the ratios of predicted-to-observed PK parameter values (0.5- to 2-fold acceptance range) and by visual predictive checks with prediction error values. Results: Overall, model predicted PK in infants, children and adolescents capture clinical data. Confidence in PBPK model performance was therefore considered high. Predictive performance tends to decrease when predicting PK in the (pre)term neonatal population. Conclusion: Pragmatic PBPK modeling in pediatrics, based on compound models verified with adult data, is feasible. A thorough understanding of the model assumptions and limitations is required, before model-informed doses can be recommended for clinical use. [ABSTRACT FROM AUTHOR]

To explore the clinical advantages of 3D-Slicer + 3D printing guide combined with transcranial neuroendoscopic in minimally invasive neurosurgery. By collecting the datum of patients who underwent craniotomy under 3D-Slicer + 3D printing guide plate positioning combined with transcranial neuroendoscopic in our hospital from October 2021 to February 2022, this paper introduces the accurate planning and positioning lesions of patients before operation and the minimally invasive operation of intraoperative neuroendoscopic and analyses clinical data such as lesion size and surgical bone window size. We collected the case datum of 16 patients who underwent craniocerebral surgery with 3D-Slicer + 3D printing guide combined with transcranial neuroendoscopic, including 5 males and 11 females, aged 46–76 years, including 6 brain tumors (3 meningiomas, 1 glioblastoma, 2 lung cancer brain metastases), 2 cavernous hemangioma, 7 hydrocephalus and 1 chronic subdural hematoma. The lesions of the 16 patients were located accurately before operation and the target areas were reached quickly during operation. Postoperative imaging datum confirmed that the lesions was removed fully, and the ventricular end of shunt tube was in good position. The technology of 3D-Slicer + 3D printing guide plate combined with transcranial neuroendoscopic is not difficult, which has many advantages such as inexpensive equipment, simple operation, easy learning, accurate positioning, and minimally invasive surgery. It is considered to be a practical technology that is feasible, reliable, convenient for diagnosis, preoperative planning and minimally invasive surgery. It is suitable for promotion in neurosurgery and other surgical departments of all medical institutions. [ABSTRACT FROM AUTHOR]

Objective: A new endoscopic thyroidectomy approach—transoral and submental endoscopic thyroidectomy (TOaST)—was applied in clinical practice and considered an improved approach for endoscopic thyroid surgery via the oral approach. This paper discusses the feasibility and effectiveness of this surgical method. Methods: A retrospective analysis was performed on the clinical data of 54 patients who had undergone TOaST in the thyroid disease center of the First Affiliated Hospital of Nanchang University between December 2020 and December 2021. The surgical data and techniques, complications, and cosmetic outcomes of these patients were studied. Results: Among the total 54 patients, 23 underwent unilateral subtotal thyroidectomy, 3 patients underwent bilateral subtotal thyroidectomy, 27 with unilateral thyroid cancer underwent affected thyroid + isthmus + central lymph node resection, and only 1 patient underwent total thyroidectomy. The mean operative time was 88.06 ± 12.03 min (range: 65–135 min), the mean intraoperative blood loss was 8.61 ± 4.60 ml (range: 5–20 ml), the mean postoperative drainage volume was 49.96 ± 9.88 ml (range: 30–60 ml), the mean drainage time was 36.61 ± 2.65 h (range: 32–50 h), and the mean length of hospital stay was 46.63 ± 3.28 h (range 45–70 h). One patient experienced transient recurrent laryngeal nerve injury, and another patient experienced transient parathyroid dysfunction; there was no superior laryngeal nerve injury and other complications, such as postoperative subcutaneous hematoma, hypercapnia, mental nerve injury, tracheoesophageal injury, infection, or lymphatic leakage. Conclusion: TOaST cannot only achieve a good therapeutic effect but also avoid mental nerve injury, reduce the discomfort of the patient's jaw, obtain a good cosmetic effect, and facilitate the operation of the operator. It is an endoscopic thyroidectomy technique with a certain clinical value. [ABSTRACT FROM AUTHOR]

In resource-limited settings, point-of-care ultrasound (POCUS) has great potential to support the timely diagnosis of extrapulmonary tuberculosis (EPTB). We aim to determine the in-hospital mortality due to EPTB according to clinical and POCUS features and risk factors in newly diagnosed patients hospitalized for EPTB in Chókwè district, Mozambique. We analyzed routinely collected data from paper medical files and electronic POCUS records of EPTB in infected patients aged 15 years or older and admitted to Carmelo Hospital of Chókwè from 2016 to 2020. Kaplan–Meier survival curves and adjusted Cox regression analyses were used to model predictors of mortality and time to death. The 390 included in-patients with EPTB and POCUS data contributed a total of 6240 in-hospital person-days of observation. The overall mortality rate was 2.16 per 100 person-days. Adjusted Cox regression showed a higher risk of death in those with abdominal tenderness (adjusted hazard ratio [aHR] 1.61, 95% confidence interval [CI] 1.00–2.82, p = 0.050), antiretroviral treatment (ART) for more than 90 days (aHR 4.03, 95% CI 1.50–10.78, p = 0.006), and mixed patterns on kidney POCUS (aHR 2.91, 95% CI 1.38–6.10, p = 0.005). An optimal immunovirological response to ART was a protective factor against death [aHR] 0.12, 95% CI 0.04–0.35, p < 0.001). Variables associated with an increased risk of death were male gender, abdominal pain, ART for more than three months (with immunovirological failure or non-response to ART) and having a mixed pattern of kidney POCUS characteristics. Early detection of these risk factors may have a direct impact on reducing TB mortality, and the POCUS approach as a complementary diagnostic method for EPTB provides a simple, feasible and affordable intervention in resource-limited settings like Mozambique. [ABSTRACT FROM AUTHOR]

Myocardial fibrosis (MF) represents the underlying pathologic condition of many cardiac disease, leading to cardiac dysfunction and heart failure (HF). Biopsy studies have shown the presence of MF in patients with decompensating HF despite apparently normal cardiac function. In fact, basic indices of left ventricular (LV) function, such as LV ejection fraction (EF), fail to recognize subtle LV dysfunction caused by MF. Cardiac magnetic resonance (CMR) with late gadolinium enhancement (LGE) is currently recognized as the gold standard imaging investigation for the detection of focal and diffuse cardiac chambers MF; however, its use is limited by its availability and the use of contrast agents, while echocardiography remains the first level cardiac imaging technique due to its low cost, portability and high accessibility. Advanced echocardiographic techniques, above all speckle-tracking echocardiography (STE), have demonstrated reliability for early detection of structural myocardial abnormalities and for the prediction of prognosis in acute and chronic HF. Myocardial strain of both ventricles and also left atrium has been shown to correlate with the degree of MF, providing useful prognostic information in several diseases, such as HF, cardiomyopathies and valvular heart disease. This paper aims to provide an overview of the pathophysiology of MF and the clinical application of STE for the prediction of left and right heart chambers MF in HF patients. [ABSTRACT FROM AUTHOR]

Background: Perforator flaps have become a popular option for soft tissue reconstruction due to their ability to provide pliable and durable coverage without the donor site morbidities of more traditional "workhorse" pedicled and free musculocutaneous flaps. Over the last several years, the medial sural artery perforator flap has been increasingly employed as a reconstructive option in both head and neck surgery and for coverage of extremity defects. The goal of this paper is to review the anatomy of the medial sural artery flap through cadaveric study and highlight the utility of this reconstructive option over other more traditional options including the anterolateral thigh flap and radial forearm free flap through the treatment of several extremity defects at our institution in both pedicled and free tissue transfer. Methods: Four cadaveric lower extremities were dissected and the pedicle of the medial sural artery flap evaluated. Three clinical cases involving lower extremity reconstruction with the medial sural artery perforator flap at our institution were reviewed. Results: Four cadaveric specimens with medial sural artery perforator (MSAP) flap dissected were evaluated for pedicle length (11–16.5 cm) and diameter (2–5 mm). Three clinical cases are described highlighting the utility of this reconstructive method. Conclusions: Through our clinical implementation and cadaveric dissection, the MSAP flap was demonstrated to be a thin and pliable perforator option for reconstruction of the lower extremity in both pedicled and free fashion without significant sacrifice of pedicle length or donor skin paddle diameter. Advantages over more traditional "workhorse" flaps are highlighted. Level of evidence: Level IV, therapeutic. [ABSTRACT FROM AUTHOR]

Deformable image registration can align two images acquired at different times or under different conditions, and thus has important theoretical research and clinical application value. However, existing learning-based registration methods are typically narrowly restricted to small displacement deformations. So to overcome this difficulty, we propose a recursive cascaded parallel network for image registration (RCPN). RCPN optimizes the image registration performance in a coarse-to-fine manner by multiple cascades to incrementally enhance the registration of target image pairs. In addition, the cascaded subnetwork always maintains a high-resolution representation. It connects multi-resolution streams in parallel, thus strengthening the feature representation capability in a finite perceptual field, which allows the registration network focus more on the small displacement deformations beyond the large displacement deformations of the image in space and enhances the registration capability. The experiments based on standard MRI images of the brain indicate that RCPN has significantly improved the registration performance compared with the benchmark method, and the effectiveness of this method can be effectively verified by combining other comparative results. [ABSTRACT FROM AUTHOR]

Where low- and middle-income countries have limited economic resources to provide individualized mental health services to people exposed to conflict, community-based interventions may be more appropriate. We aimed to evaluate community level interventions for improving mental health outcomes in Low- and Middle-income countries (LMIC). A realist review of community-based interventions (CBIs) to improve mental health for people in LMIC following conflict. Five databases (Cochrane, PubMed, PsychINFO, Medline, and CINAHL) and a manual search of individual papers. We found 1318 articles, of which 29 were selected. Out of the 29 primary articles, 19 showed successful results, 4 showed mixed results, 1 showed inconclusive results, and 1 showed unsuccessful results. After analyzing the results, we found 3 mechanisms that may influence the effectiveness of these CBIs: the use of lay community members as intervention deliverers, the application of transdiagnostic approaches, and customized outcome assessment tools. Community-based approaches to improve mental health in LMICs are rare and evidence for their effectiveness is limited. Interventions that have a wide scope, train lay mental health workers, and use contextually adapted outcome assessment tools show promise. [ABSTRACT FROM AUTHOR]

Application of minimally invasive methods to enable the measurement of tissue permittivity in the neuromuscular clinic remain elusive. This paper provides a theoretical and modeling study on the measurement of the permittivity of two-dimensional anisotropic tissues such as skeletal muscle with a multi-electrode cross-shaped needle. For this, we design a novel cross-shaped needle with multiple-electrodes and analyse apparent impedance corresponding to the measured impedance. In addition, we propose three methods of estimate anisotropic muscle permittivity. Compared to existing electrical impedance-based needle methods that we have developed, the new needle design and numerical methods associated enable estimating in vivo muscle permittivity values with only a single needle insertion. Being able to measure muscle permittivity directly with a single needle insertion could open up an entirely new area of research with direct clinical application, including using these values to assist in neuromuscular diagnosis and to assess subtle effects of therapeutic intervention on muscle health. [ABSTRACT FROM AUTHOR]

Polyacrylamide hydrogels have made an immensely important place in various fields having bio-compatibility, high water-holding capacity, tunability and cheap synthesis, which has attracted researchers' attention. Polyacrylamide can be chemically infused with other elements or compounds to find applications in magnetic biosensors, drug delivery, cartilage repair and wound dressing. This paper throws light on the brief introduction of hydrogels and their classification. The polymerization method of polyacrylamide hydrogel followed by its clinical uses (cell biology and drug delivery) is adorned in the report. Keeping at the centre, the recent highlights on the research work done on polyacrylamide hydrogel composites using various reinforcing additives are crucially explored first time in the present report. The improvement practice in the strength, bonding and self-healing of the polyacrylamide hydrogel is demonstrated by the encapsulation of nanoparticles like silicon, carbon nanotubes, gelatine, cellulose, etc. The clinical aspects of the polyacrylamide are corroborated by the cell viability, proliferation and migration. Thus, polyacrylamide hydrogels are emerging candidates, precisely illuminated in the review, which can be an influential highlight designed for upcoming research. [ABSTRACT FROM AUTHOR]

Health systems in many countries are currently undergoing an evolution towards more person-centred care. However, an overview of the literature shows that there is little or no guidance available on how to apply person-centred care to pharmaceutical care and clinical pharmacy practices. In this paper we apply a model for person-centred care created by a national multidisciplinary research centre in Gothenburg, Sweden, to the clinical work tasks of outpatient and inpatient pharmacists and describe how pharmaceutical care can become more person-centred. [ABSTRACT FROM AUTHOR]

Artificial intelligence (AI) represents a broad category of algorithms for which deep learning is currently the most impactful. When electing to begin the process of building an adequate fundamental knowledge base allowing them to decipher machine learning research and algorithms, clinical musculoskeletal radiologists currently have few options to turn to. In this article, we provide an introduction to the vital terminology to understand, how to make sense of data splits and regularization, an introduction to the statistical analyses used in AI research, a primer on what deep learning can or cannot do, and a brief overview of clinical integration methods. Our goal is to improve the readers' understanding of this field. [ABSTRACT FROM AUTHOR]

Current evidence on digital health interventions is disproportionately concerned with high-income countries and hospital settings. This scoping review evaluates the extent of use and effectiveness of digital health interventions for non-communicable disease (NCD) management in primary healthcare settings of low- and middle-income countries (LMICs) and identifies factors influencing digital health interventions' uptake. We use PubMed, Embase, and Web of Science search results from January 2010 to 2021. Of 8866 results, 52 met eligibility criteria (31 reviews, 21 trials). Benchmarked against World Health Organization's digital health classifications, only 14 out of 28 digital health intervention categories are found, suggesting critical under-use and lagging innovation. Digital health interventions' effectiveness vary across outcomes: clinical (mixed), behavioral (positively inclined), and service implementation outcomes (clear effectiveness). We further identify multiple factors influencing digital health intervention uptake, including political commitment, interactivity, user-centered design, and integration with existing systems, which points to future research and practices to invigorate digital health interventions for NCD management in primary health care of LMICs. [ABSTRACT FROM AUTHOR]

When implemented in practice, digital technologies have shown improvements in morbidity and mortality outcomes in patients with cardiovascular disease (CVD). For scholars, research into digital technologies in cardiovascular care has been relatively recent, thus it is important to understand the history of digital health technology in cardiovascular research—its emergence, rate of growth, hot topics, and its temporal evolution. The aim of this study was to analyse more than 16,000 articles in this domain based on their scientometric indicators. Web of Science (WoS) Core Collection was accessed and searched at several levels, including titles, abstracts, keywords, authors, sources and individual articles. Analysis examined the temporal shifts in research and scholarly focus based on keywords, networks of collaboration, topical divisions in relation to digital technologies, and influential publications. Findings showed this research area is growing exponentially. Co-citation analysis revealed twenty prominent research streams and identified variation in the magnitude of activities in each stream. A recent emergence of research activities in digital technology in cardiovascular rehabilitation (CR), out-of-hospital cardiac arrest (OHCA), and arrythmia research was also demonstrated. Conversely, wearable technologies, activity tracking and electronic medical records research are now past their peak of reported research activity. With increasing amounts of novel technologies becoming available and more patients taking part in remote health care monitoring, further evaluation and research into digital technologies, including their long-term effectiveness, is needed. Furthermore, emerging technologies, which are evaluated and/or validated should be considered for implementation into clinical practice as treatment and prevention modalities for CVD. [ABSTRACT FROM AUTHOR]

Fibroblast growth factor 21 (FGF21) is essential for modulating hepatic homeostasis, but the impact of FGF21 on liver graft injury remains uncertain. Here, we show that high FGF21 levels in liver graft and serum are associated with improved graft function and survival in liver transplantation (LT) recipients. FGF21 deficiency aggravates early graft injury and activates arachidonic acid metabolism and regional inflammation in male mouse models of hepatic ischemia/reperfusion (I/R) injury and orthotopic LT. Mechanistically, FGF21 deficiency results in abnormal activation of the arachidonate 15-lipoxygenase (ALOX15)/15-hydroxy eicosatetraenoic acid (15-HETE) pathway, which triggers a cascade of innate immunity-dominated pro-inflammatory responses in grafts. Notably, the modulating role of FGF21/ALOX15/15-HETE pathway is more significant in steatotic livers. In contrast, pharmacological administration of recombinant FGF21 effectively protects against hepatic I/R injury. Overall, our study reveals the regulatory mechanism of FGF21 and offers insights into its potential clinical application in early liver graft injury after LT. Marginal liver grafts are associated with a higher risk of graft failure due to their increased susceptibility to ischemia-reperfusion injury. Here, the authors show the regulatory mechanism of fibroblast growth factor 21 and offer insights into its clinical application in early liver graft injury. [ABSTRACT FROM AUTHOR]