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Benign conditions of the lower urinary tract, including benign prostatic hyperplasia, overactive bladder syndrome, and stress urinary incontinence, are frequent in the general population. Despite their benign nature, they have major adverse effects on the quality of life of the afflicted patients and their partners. Despite major progress in the diagnosis and treatment of these conditions, improved understanding and management of these patients remain substantial medical needs. This editorial discusses some recent high-quality articles published in the Journal of Clinical Medicine on the understanding of the epidemiology, pathophysiology, diagnostic, and treatment of benign diseases of the lower urinary tract tissues such as the bladder and prostate. [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]

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]

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]

Simple Summary: Platelet concentrates have become increasingly popular in both animal and human medicine. These concentrates mainly consist of higher-than-normal levels of platelets and therefore contain a high concentration of growth factors which are stored within platelet α-granules. One specific type of platelet concentrate, known as Platelet-Rich Plasma (PRP), is notable for its low-density fibrin. Recent research has focused on how PCs can benefit cattle, and PRP has shown promise in treating various reproductive issues, assisting in the production of bovine embryos, and addressing problems like sole ulcers and udder diseases. In this report, we aim to review the existing literature on the use of PRP in bovine veterinary practice. We followed strict guidelines to identify relevant studies. After searching extensively through databases, we found a total of 1196 papers, but only six met our criteria for inclusion. Out of these six papers, two discussed the use of PRP for mastitis, two for uterine dysfunction, and two for ovarian dysfunction in cattle. PRP emerged as a cost-effective and readily available treatment option, showing positive results in these cases. However, due to the diversity of conditions and definitions involved, more research is needed to fully understand its potential in clinical practice for cattle. Platelet concentrates (PCs) have become widely used in veterinary and human medicine. The PCs consist mainly of supraphysiological concentrations of platelets and, therefore, growth factors (GFs) which are stored within platelet α-granules. Among PCs, Platelet-Rich Plasma (PRP) is characterised by low-density fibrin. Research on the effect of PCs in cattle has surged in recent years; in particular, evidence has shown the positive use of PRP for treating reproductive problems, in vitro production of bovine embryos, sole ulcers and udder diseases. The aim of this report is to critically review, in accordance with the PRISMA guidelines, the available literature reporting clinical application in the bovine practice of PRP. Three bibliographic databases PubMed, Web of Science and Scopus were used for a broad search of "platelet concentrates" OR "PRP" OR "platelet-rich plasma" OR "PRF" OR "platelet-rich fibrin" AND "cows" OR "cattle". From 1196 papers, only six met the inclusion criteria. Two papers described the use of PRP in mastitis, two papers in uterine dysfunction and two papers in ovarian dysfunction. PRP offered a low-cost, easily obtained therapeutic option and showed positive results for these patients. However, given the different pathologies and definitions involved, further studies are necessary to assess its full clinical potential. [ABSTRACT FROM AUTHOR]

BCI devices are increasingly being used to create interactive interfaces between users and their own psychophysiological signals. Over the years, these systems have seen strong development as they can enable people with limited mobility to make certain decisions to alter their environment. Additionally, their portability and ease of use have allowed a field of research to flourish for the study of cognitive and emotional processes in natural settings. The study of creativity, especially little creativity (little-c), is one example, although the results of this cutting-edge research are often poorly systematized. The purpose of the present paper, therefore, was to conduct a scoping review to describe and systematize the various studies that have been conducted on the application potential of BCI to the field of creativity. Twenty-two papers were selected that collect information on different aspects of creativity, including clinical applications; art experience in settings with high ecological validity; BCI for creative content creation, and participants' engagement. Critical issues and potentialities of this promising area of study are also presented. Implications for future developments towards multi-brain creativity settings and C2 are discussed. [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]

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]

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]

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]

This paper introduces a complex novel concept and methodology for the creation of personalized biomedical appliances 3D-printed from certified biocompatible photopolymer resin Dental LT Clear (V2). The explained workflow includes intraoral and CT scanning, patient virtualization, digital appliance design, additive manufacturing, and clinical application with evaluation of the appliance intended for patients with cranio-facial syndromes. The presented concept defines virtual 3D fusion of intraoral optical scan and segmented CT as sufficient and accurate data defining the 3D surface of the face, intraoral and airway morphology necessary for the 3D design of complex personalized intraoral and extraoral parts of the orthopedic appliance. A central aspect of the concept is a feasible utilization of composite resin for biomedical prototyping of the sequence of marginally different appliances necessary to keep the pace with the patient rapid growth. Affordability, noninvasiveness, and practicality of the appliance update process shall be highlighted. The methodology is demonstrated on a particular case of two-year-old infant with Pierre Robin sequence. Materialization by additive manufacturing of this photopolymer provides a highly durable and resistant-to-fracture two-part appliance similar to a Tübingen palatal plate, for example. The paper concludes with the viability of the described method and material upon interdisciplinary clinical evaluation of experts from departments of orthodontics and cleft anomalies, pediatric pneumology and phthisiology, and pediatric otorhinolaryngology. [ABSTRACT FROM AUTHOR]

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]

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]

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]

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]

This paper provides a comprehensive overview of the potential applications of dual-energy CT (DECT) in improving image quality and the diagnostic capabilities of CT arthrography (CTA) in clinical practice. The paper covers the use of virtual non-contrast (VNC) images, in which the injected contrast medium is subtracted from the articular cavity in order to better analyze 2D and 3D images of the bone. Moreover, virtual monoenergetic imaging (VMI) applications and their potential use for the reduction of metal artifacts and improving image contrast are reviewed. The role of virtual non-calcium (VNCa) in detecting bone marrow edema surrounding the imaged joint will be discussed. Furthermore, the role of iodine maps in enhancing the contrast between soft tissues, optimizing the visualization of contrast material, and distinguishing contrast material from calcifications is described. Finally, a case series including different joints is provided to underline the additional advantages of high-spatial-resolution dual-energy CT reconstructed images. [ABSTRACT FROM AUTHOR]

Our aim was to provide a comprehensive overview of the existing literature concerning the clinical applications of positron emission computed tomography (PET) with radiopharmaceuticals targeting the translocator protein (TSPO) in gliomas. A literature search for studies about TSPO PET in the last 10 years (from 2013 to February 2023) was carried out on PubMed, Scopus, and Web of Science using the following keywords: "PET" AND "Gliomas" AND "TSPO". The Critical Appraisal Skills Program checklist for diagnostic test studies was used for testing the quality of selected papers. Ten articles were selected, encompassing 314 glioma patients submitted to PET/CT (9/10) or PET/MRI (1/10) with TSPO ligands. Among the various available TSPO tracers, the most frequently used was the third-generation ligand, [18F]-GE-180. TSPO PET results were useful to identify anaplastic transformation in gliomas and for the prognostic stratification of patients bearing homogeneous genetic alterations. When compared to amino-acid PET, TSPO PET with [18F]-GE-180 presented superior image quality and provided larger and only partially overlapping PET-based volumes. Although biased by some issues (i.e., small sample size, most of the studies coming from the same country), preliminary applications of TSPO PET were encouraging. Further studies are needed to define implications in clinical practice and shape the role of TSPO PET for patients' selection for potential TSPO-targeted molecular therapies. [ABSTRACT FROM AUTHOR]

The goal of clinical practice education is to develop the ability to apply theoretical knowledge in a clinical setting and to foster growth as a professional healthcare provider. One effective method of achieving this is through the utilization of Standardized Patients (SP) in education, which familiarizes students with real patient interviews and allows educators to assess their clinical performance skills. However, SP education faces challenges such as the cost of hiring actors and the shortage of professional educators to train them. In this paper, we aim to alleviate these issues by utilizing deep learning models to replace the actors. We employ the Conformer model for the implementation of the AI patient, and we develop a Korean SP scenario data generator to collect data for training responses to diagnostic questions. Our Korean SP scenario data generator is devised to generate SP scenarios based on the provided patient information, using pre-prepared questions and answers. In the AI patient training process, two types of data are employed: common data and personalized data. The common data are employed to develop natural general conversation skills, while personalized data, from the SP scenario, are utilized to learn specific clinical information relevant to a patient's role. Based on these data, to evaluate the learning efficiency of the Conformer structure, a comparison was conducted with the Transformer using the BLEU score and WER as evaluation metrics. Experimental results showed that the Conformer-based model demonstrated a 3.92% and 6.74% improvement in BLEU and WER performance compared to the Transformer-based model, respectively. The dental AI patient for SP simulation presented in this paper has the potential to be applied to other medical and nursing fields, provided that additional data collection processes are conducted. [ABSTRACT FROM AUTHOR]

Platinum (Pt) drugs have developed rapidly in clinical applications because of their broad and highly effective antitumor effects. In recent years, with the rapid development of immunotherapy, Pt-based antitumor agents have gained new challenges and opportunities. Since the discovery of their pharmacological effects in immunotherapy and tumor microenvironment regulation, research into Pt drugs has progressed to multi-ligand and multi-functional Pt precursors and their own shortcomings have been further highlighted. With the development of antitumor immunotherapy and the rise of combination therapy, the development of Pt-based drugs has started to move in the direction of multi-targeting, nanocarrier modification, immunotherapy and photodynamic therapy. In this paper, we first overview the recent applications of Pt-based drugs in antitumor inorganic chemistry, with a focus on summarizing the application of Pt-based drugs and their precursors in the anticancer immune response. The paper also provides a reasonable outlook on the future development of Pt-based drugs from the chemical and immunological perspectives, relying on the existing content and problems of Pt-based drug development. On the basis of the gathered information, joint multidisciplinary programs on implementing comprehensive immune analyses for the future development of novel anticancer metal compounds should be initiated. [ABSTRACT FROM AUTHOR]

Acinetobacter baumannii (A. baumannii) is one of the most common clinical pathogens and a typical multi-drug resistant (MDR) bacterium. With the increase of drug-resistant A. baumannii infections, it is urgent to find some new treatment strategies, such as phage therapy. In this paper, we described the different drug resistances of A. baumannii and some basic properties of A. baumannii phages, analyzed the interaction between phages and their hosts, and focused on A. baumannii phage therapies. Finally, we discussed the chance and challenge of phage therapy. This paper aims to provide a more comprehensive understanding of A. baumannii phages and theoretical support for the clinical application of A. baumannii phages. [ABSTRACT FROM AUTHOR]

The paper concentrates on the solitary waves that are retrievable from the generalized Boussinesq equation. The numerical simulations are displayed in the paper that gives a visual perspective to the model studied in neurosciences. The Laplace–Adomian decomposition scheme makes this visualization of the solitons possible. The numerical simulations are being reported for the first time using an elegant approach. The results would be helpful for neuroscientists and clinical studies in Medicine. The novelty lies in the modeling that is successfully conducted with an impressively small error measure. In the past, the model was integrated analytically only to recover soliton solutions and its conserved quantities. [ABSTRACT FROM AUTHOR]

This document is a special issue of the Journal of Clinical Medicine focusing on the latest advances in urinary incontinence (UI). The issue includes contributions from experts in functional and neuro-urology, providing new scientific evidence on the diagnosis and management of UI. Topics covered include strategies to reduce catheter-associated infections, treatment options for neurogenic urinary incontinence, the impact of UI on patients' quality of life, UI after robot-assisted radical prostatectomy, treatment options for female stress and mixed urinary incontinence, and patients' preferences and expectations for overactive bladder treatment. The authors believe that the papers included in this special issue will be a valuable resource for researchers and inspire further research in the field. [Extracted from the article]

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]

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]

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]

This research aims to review and evaluate the most relevant scientific studies about deep learning (DL) models in the omics field. It also aims to realize the potential of DL techniques in omics data analysis fully by demonstrating this potential and identifying the key challenges that must be addressed. Numerous elements are essential for comprehending numerous studies by surveying the existing literature. For example, the clinical applications and datasets from the literature are essential elements. The published literature highlights the difficulties encountered by other researchers. In addition to looking for other studies, such as guidelines, comparative studies, and review papers, a systematic approach is used to search all relevant publications on omics and DL using different keyword variants. From 2018 to 2022, the search procedure was conducted on four Internet search engines: IEEE Xplore, Web of Science, ScienceDirect, and PubMed. These indexes were chosen because they offer enough coverage and linkages to numerous papers in the biological field. A total of 65 articles were added to the final list. The inclusion and exclusion criteria were specified. Of the 65 publications, 42 are clinical applications of DL in omics data. Furthermore, 16 out of 65 articles comprised the review publications based on single- and multi-omics data from the proposed taxonomy. Finally, only a small number of articles (7/65) were included in papers focusing on comparative analysis and guidelines. The use of DL in studying omics data presented several obstacles related to DL itself, preprocessing procedures, datasets, model validation, and testbed applications. Numerous relevant investigations were performed to address these issues. Unlike other review papers, our study distinctly reflects different observations on omics with DL model areas. We believe that the result of this study can be a useful guideline for practitioners who look for a comprehensive view of the role of DL in omics data analysis. [ABSTRACT FROM AUTHOR]

Paclitaxel, a natural secondary metabolite isolated and purified from the bark of the Taxus tree, is considered one of the most successful natural anticancer drugs due to its low toxicity, high potency and broad-spectrum anticancer activity. Taxus trees are scarce and slow-growing, and with extremely low paclitaxel content, the contradiction between supply and demand in the market is becoming more and more intense. Therefore, researchers have tried to obtain paclitaxel by various methods such as chemical synthesis, artificial culture, microbial fermentation and tissue cell culture to meet the clinical demand for this drug. This paper provides a comprehensive overview of paclitaxel extraction, combination therapy, total synthesis, semi-synthesis and biosynthesis in recent years and provides an outlook, aiming to provide a theoretical basis and reference for further research on the production and application of paclitaxel in the future. [ABSTRACT FROM AUTHOR]

Rhodiola rosea L. (RRL) is a popular plant in traditional medicine, and Rosavin, a characteristic ingredient of RRL, is considered one of the most important active ingredients in it. In recent years, with deepening research on its pharmacological actions, the clinical application value and demand for Rosavin have been steadily increasing. Various routes for the extraction and all-chemical or biological synthesis of Rosavin have been gradually developed for the large-scale production and broad application of Rosavin. Pharmacological studies have demonstrated that Rosavin has a variety of biological activities, including antioxidant, lipid-lowering, analgesic, antiradiation, antitumor and immunomodulation effects. Rosavin showed significant therapeutic effects on a range of chronic diseases, including neurological, digestive, respiratory and bone-related disorders during in vitro and vivo experiments, demonstrating the great potential of Rosavin as a therapeutic drug for diseases. This paper gives a comprehensive and insightful overview of Rosavin, focusing on its extraction and synthesis, pharmacological activities, progress in disease-treatment research and formulation studies, providing a reference for the production and preparation, further clinical research and applications of Rosavin in the future. [ABSTRACT FROM AUTHOR]

In medical research and clinical applications, the utilization of MRI datasets from multiple centers has become increasingly prevalent. However, inherent variability between these centers presents challenges due to domain shift, which can impact the quality and reliability of the analysis. Regrettably, the absence of adequate tools for domain shift analysis hinders the development and validation of domain adaptation and harmonization techniques. To address this issue, this paper presents a novel Domain Shift analyzer for MRI (DSMRI) framework designed explicitly for domain shift analysis in multi-center MRI datasets. The proposed model assesses the degree of domain shift within an MRI dataset by leveraging various MRI-quality-related metrics derived from the spatial domain. DSMRI also incorporates features from the frequency domain to capture low- and high-frequency information about the image. It further includes the wavelet domain features by effectively measuring the sparsity and energy present in the wavelet coefficients. Furthermore, DSMRI introduces several texture features, thereby enhancing the robustness of the domain shift analysis process. The proposed framework includes visualization techniques such as t-SNE and UMAP to demonstrate that similar data are grouped closely while dissimilar data are in separate clusters. Additionally, quantitative analysis is used to measure the domain shift distance, domain classification accuracy, and the ranking of significant features. The effectiveness of the proposed approach is demonstrated using experimental evaluations on seven large-scale multi-site neuroimaging datasets. [ABSTRACT FROM AUTHOR]

Bernaldo de Quirós et al. [[4]] present a review of the setups for the measurement of movements of stroke patients under free-living conditions using wearable sensors, and for the evaluation of the relation between such sensor-based outcomes and the level of functioning, as assessed using existing clinical evaluation methods. Ferraris et al. [[12]] describe the REHOME project, whose main goal consists of meeting the needs of both clinicians and patients in ensuring continuity of treatment, from healthcare facilities to the patient's home. Ubl et al. [[11]] face the problem of the evaluation of controllers for insulin pumps to be used by patients with diabetes to correctly dose insulin; this is an extremely important task for safety reasons. Among them, we cite micro/nano/cyberphysical systems; AI and machine learning techniques; early pathology detection technologies; e-health, mHealth, telemedicine, and digital solutions; and augmented reality for remote healthcare treatments. [Extracted from the article]

Suppressor of mother against decapentaplegic (SMAD) family proteins are central to one of the most versatile cytokine signalling pathways in metazoan biology, the transforming growth factor-β (TGF-β) pathway. The TGF-β pathway is widely known for its dual role in cancer progression as both an inhibitor of tumour cell growth and an inducer of tumour metastasis. This is mainly mediated through SMAD proteins and their cofactors or regulators. SMAD proteins act as transcription factors, regulating the transcription of a wide range of genes, and their rich post-translational modifications are influenced by a variety of regulators and cofactors. The complex role, mechanisms, and important functions of SMAD proteins in tumours are the hot topics in current oncology research. In this paper, we summarize the recent progress on the effects and mechanisms of SMAD proteins on tumour development, diagnosis, treatment and prognosis, and provide clues for subsequent research on SMAD proteins in tumours. [ABSTRACT FROM AUTHOR]

Accurate identification of lesions and their use across different medical institutions are the foundation and key to the clinical application of automatic diabetic retinopathy (DR) detection. Existing detection or segmentation methods can achieve acceptable results in DR lesion identification, but they strongly rely on a large number of fine-grained annotations that are not easily accessible and suffer severe performance degradation in the cross-domain application. In this paper, we propose a cross-domain weakly supervised DR lesion identification method using only easily accessible coarse-grained lesion attribute labels. We first propose the novel lesion-patch multiple instance learning method (LpMIL), which leverages the lesion attribute label for patch-level supervision to complete weakly supervised lesion identification. Then, we design a semantic constraint adaptation method (LpSCA) that improves the lesion identification performance of our model in different domains with semantic constraint loss. Finally, we perform secondary annotation on the open-source dataset EyePACS, to obtain the largest fine-grained annotated dataset EyePACS-pixel, and validate the performance of our model on it. Extensive experimental results on the public dataset FGADR and our EyePACS-pixel demonstrate that compared with the existing detection and segmentation methods, the proposed method can identify lesions accurately and comprehensively, and obtain competitive results using only coarse-grained annotations. [ABSTRACT FROM AUTHOR]

In recent years, neuro-biomechanical enhancement techniques, such as transcranial direct current stimulation (tDCS), have been widely used to improve human physical performance, including foot biomechanical characteristics. This review aims to summarize research on the effects of tDCS on foot biomechanics and its clinical applications, and further analyze the underlying ergogenic mechanisms of tDCS. This review was performed for relevant papers until July 2023 in the following databases: Web of Science, PubMed, and EBSCO. The findings demonstrated that tDCS can improve foot biomechanical characteristics in healthy adults, including proprioception, muscle strength, reaction time, and joint range of motion. Additionally, tDCS can be effectively applied in the field of foot sports medicine; in particular, it can be combined with functional training to effectively improve foot biomechanical performance in individuals with chronic ankle instability (CAI). The possible mechanism is that tDCS may excite specific task-related neurons and regulate multiple neurons within the system, ultimately affecting foot biomechanical characteristics. However, the efficacy of tDCS applied to rehabilitate common musculoskeletal injuries (e.g., CAI and plantar fasciitis) still needs to be confirmed using a larger sample size. Future research should use multimodal neuroimaging technology to explore the intrinsic ergogenic mechanism of tDCS. [ABSTRACT FROM AUTHOR]

Chitosan (CTS), a biocompatible and multifunctional material derived from chitin, has caught researchers' attention in electrochemical detection due to its unique properties. This review paper provides a comprehensive overview of the recent progress and applications of CTS-based electrochemical sensors in the analysis of pharmaceutical products and other types of samples, with a particular focus on the detection of medicinal substances. The review covers studies and developments from 2003 to 2023, highlighting the remarkable properties of CTS, such as biocompatibility, chemical versatility, and large surface area, that make it an excellent candidate for sensor modification. Combining CTS with various nanomaterials significantly enhances the detection capabilities of electrochemical sensors. Various types of CTS-based sensors are analyzed, including those utilizing carbon nanomaterials, metallic nanoparticles, conducting polymers, and molecularly imprinted CTS. These sensors exhibit excellent sensitivity, selectivity, and stability, enabling the precise and reliable detection of medications. The manufacturing strategies used for the preparation of CTS-based sensors are described, the underlying detection mechanisms are elucidated, and the integration of CTS sensors with transducer systems is highlighted. The prospects of CTS-based electrochemical sensors are promising, with opportunities for miniaturization, simultaneous detection, and real-time monitoring applications. [ABSTRACT FROM AUTHOR]

For decades, the advantages of rapid prototyping for clinical use have been recognized. However, demonstrations of potential solutions to treat spinal problems that cannot be solved otherwise are scarce. In this paper, we describe the development, regulatory process, and clinical application of two types of patient specific 3D-printed devices that were developed at an in-house 3D point-of-care facility. This 3D lab made it possible to elegantly treat patients with spinal problems that could not have been treated in a conventional manner. The first device, applied in three patients, is a printed nylon drill guide, with such accuracy that it can be used for insertion of cervical pedicle screws in very young children, which has been applied even in semi-acute settings. The other is a 3D-printed titanium spinal column prosthesis that was used to treat progressive and severe deformities due to lysis of the anterior column in three patients. The unique opportunity to control size, shape, and material characteristics allowed a relatively easy solution for these patients, who were developing paraplegia. In this paper, we discuss the pathway toward the design and final application, including technical file creation for dossier building and challenges within a point-of-care lab. [ABSTRACT FROM AUTHOR]

A thyroid nodule, a common abnormal growth within the thyroid gland, is often identified through ultrasound imaging of the neck. These growths may be solid- or fluid-filled, and their treatment is influenced by factors such as size and location. The Thyroid Imaging Reporting and Data System (TI-RADS) is a classification method that categorizes thyroid nodules into risk levels based on features such as size, echogenicity, margin, shape, and calcification. It guides clinicians in deciding whether a biopsy or other further evaluation is needed. Machine learning (ML) can complement TI-RADS classification, thereby improving the detection of malignant tumors. When combined with expert rules (TI-RADS) and explanations, ML models may uncover elements that TI-RADS misses, especially when TI-RADS training data are scarce. In this paper, we present an automated system for classifying thyroid nodules according to TI-RADS and assessing malignancy effectively. We use ResNet-101 and DenseNet-201 models to classify thyroid nodules according to TI-RADS and malignancy. By analyzing the models' last layer using the Grad-CAM algorithm, we demonstrate that these models can identify risk areas and detect nodule features relevant to the TI-RADS score. By integrating Grad-CAM results with feature probability calculations, we provide a precise heat map, visualizing specific features within the nodule and potentially assisting doctors in their assessments. Our experiments show that the utilization of ResNet-101 and DenseNet-201 models, in conjunction with Grad-CAM visualization analysis, improves TI-RADS classification accuracy by up to 10%. This enhancement, achieved through iterative analysis and re-training, underscores the potential of machine learning in advancing thyroid nodule diagnosis, offering a promising direction for further exploration and clinical application. [ABSTRACT FROM AUTHOR]

Photoacoustic imaging is a promising medical imaging modality that enables the visualization of molecular functional and morphological information of biological tissues. Its clinical potential has been widely investigated for assessing and diagnosing various diseases. Currently, several research groups are developing photoacoustic imaging systems for translation from the laboratory to the clinic. In particular, the integration of photoacoustic imaging into existing diagnostic ultrasound applications, such as cancer diagnosis, has shown promising results. Additionally, recent research has explored the application of photoacoustic imaging for novel clinical uses. In this review paper, recent trials of photoacoustic imaging in both conventional and novel clinical applications are summarized and evaluated. Additionally, current limitations and future directions of photoacoustic imaging for successful translation into the clinical world are discussed. The aim of this review is to provide a comprehensive overview of the recent advancements in photoacoustic imaging and highlight its potential for clinical diagnosis and treatment. It is hoped that this review will contribute to the development of improved diagnostic and therapeutic approaches for a wide range of diseases using photoacoustic imaging. [ABSTRACT FROM AUTHOR]

Religiosity and spirituality (R/S) have been described extensively as being an integral part of subjective well-being and mental health, especially in Anglo-American regions. Accordingly, the Multidimensional Inventory for Religious/Spiritual Well-Being (MI-RSWB) was developed in the European context to be able to contribute to the further development of this research field by means of a validated measure. In this paper, after an introduction to basic considerations about the scale, more recent developments (from 2012 to 2022) regarding the use of the MI-RSWB are presented. Thus, it is intended to focus here on (1) the presentation of standard values for the MI-RSWB for the Austrian general population, (2) several scale translations into different languages, (3) more recent data on the relationship between RSWB, personality, and mental health, and (4) the potential clinical applications of the RSWB dimensions. As a conclusion, further potential applications of the RSWB concept are discussed. [ABSTRACT FROM AUTHOR]

Aloe vera is a kind of herb rich in polysaccharides. Acemannan (AC) is considered to be a natural polysaccharide with good biodegradability and biocompatibility extracted from Aloe vera and has a wide range of applications in the biomedical field due to excellent immunomodulatory, antiviral, antitumor, and tissue regeneration effects. In recent years, clinical case reports on the application of AC as a novel biomedical material in tissue regenerative medicine have emerged; it is mainly used in bone tissue engineering, pulp–dentin complex regeneration engineering, and soft tissue repair, among other operations. In addition, multiple studies have proved that the new composite products formed by the combination of AC and other compounds have excellent biological and physical properties and have broader research prospects. This paper introduces the preparation process, surface structure, and application forms of AC; summarizes the influence of acetyl functional group content in AC on its functions; and provides a detailed review of the functional properties, laboratory studies, clinical cutting-edge applications, and combined applications of AC. Finally, the current application status of AC from basic research to clinical treatment is analyzed and its prospects are discussed. [ABSTRACT FROM AUTHOR]

The awareness of the existence of plant bioactive compounds, namely, phytochemicals (PHYs), with health properties is progressively expanding. Therefore, their massive introduction in the normal diet and in food supplements and their use as natural therapeutics to treat several diseases are increasingly emphasized by several sectors. In particular, most PHYs possessing antifungal, antiviral, anti-inflammatory, antibacterial, antiulcer, anti-cholesterol, hypoglycemic, immunomodulatory, and antioxidant properties have been isolated from plants. Additionally, their secondary modification with new functionalities to further improve their intrinsic beneficial effects has been extensively investigated. Unfortunately, although the idea of exploiting PHYs as therapeutics is amazing, its realization is far from simple, and the possibility of employing them as efficient clinically administrable drugs is almost utopic. Most PHYs are insoluble in water, and, especially when introduced orally, they hardly manage to pass through physiological barriers and scarcely reach the site of action in therapeutic concentrations. Their degradation by enzymatic and microbial digestion, as well as their rapid metabolism and excretion, strongly limits their in vivo activity. To overcome these drawbacks, several nanotechnological approaches have been used, and many nanosized PHY-loaded delivery systems have been developed. This paper, by reporting various case studies, reviews the foremost nanosuspension- and nanoemulsion-based techniques developed for formulating the most relevant PHYs into more bioavailable nanoparticles (NPs) that are suitable or promising for clinical application, mainly by oral administration. In addition, the acute and chronic toxic effects due to exposure to NPs reported so far, the possible nanotoxicity that could result from their massive employment, and ongoing actions to improve knowledge in this field are discussed. The state of the art concerning the actual clinical application of both PHYs and the nanotechnologically engineered PHYs is also reviewed. [ABSTRACT FROM AUTHOR]