Atrial Fibrillation and Heart Failure With Reduced Ejection Fraction: New Assessment of an Old Problem.

Atrial fibrillation (AF) and heart failure (HF)-specifically, heart failure with reduced ejection fraction (HFrEF)-often coexist, and each contributes to the propagation of the other. This relationship extends from the mechanistic and physiological to clinical syndromes, quality of life, and long-term cardiovascular outcomes. The risk factors for AF and HF overlap and create a critical opportunity to prevent adverse outcomes among patients at greatest risk for either condition. Increasing recognition of the linkages between AF and HF have led to widespread interest in designing diagnostic, predictive, and interventional strategies targeting all aspects of disease, from identifying genetic predisposition to addressing social determinants of health. Advances across this spectrum culminated in updated multisociety guidelines for management of AF, which includes specific consideration of comorbid AF and HF. This review expands on these guidelines by further highlighting relevant clinical trial findings and providing additional context for the evolving recommendations for management in this important and growing population.

High-Temperature Resistance of Anchorage System for Carbon Fiber-Reinforced Polymer Composite Cable-A Review.

Unidirectional carbon fiber-reinforced polymer (CFRP) may exhibit significant mechanical softening in the transverse direction at an elevated temperature. While significant transverse compressive stress exists on CFRP due to the clamping force from anchorage, a CFRP cable may exhibit anchorage failure when suffering an accidental fire disaster. The high-temperature resistance of a CFRP cable anchorage is critical, and clarifying the performance deterioration and failure mechanism of a CFRP cable anchorage system at elevated temperature is fundamental for clarifying its fire resistance. This paper reviews the current research status of the high-temperature resistance of CFRP cable anchorage systems from two aspects, including the high-temperature resistance of the comprising materials and the anchorage system. The reviews on the high-temperature properties of the comprising materials are summarized from two aspects. Firstly, the mechanical performance degradation of bonding epoxy resin at elevated temperatures and the effect of a filler on its mechanical-thermal properties are analyzed. Secondly, the mechanical performances of CFRP composites at elevated temperatures are summarized, with consideration of the stress state of the CFRP cable under the constraint of an anchorage device. The reviews on the high-temperature resistance of the anchorage system also include two aspects. Firstly, the temperature field solution method for the anchorage system is summarized and discussed. Secondly, the current research status of the anchorage performance at elevated temperatures is also summarized and discussed. Based on these reviews, the research shortage of the high-temperature resistance of CFRP cable anchorage systems is summarized, and further research is recommended.

A Review of Data Mining Strategies by Data Type, with a Focus on Construction Processes and Health and Safety Management.

Increasingly, information technology facilitates the storage and management of data useful for risk analysis and event prediction. Studies on data extraction related to occupational health and safety are increasingly available; however, due to its variability, the construction sector warrants special attention. This review is conducted under the research programs of the National Institute for Occupational Accident Insurance (Inail). OBJECTIVES: The research question focuses on identifying which data mining (DM) methods, among supervised, unsupervised, and others, are most appropriate for certain investigation objectives, types, and sources of data, as defined by the authors. METHODS: Scopus and ProQuest were the main sources from which we extracted studies in the field of construction, published between 2014 and 2023. The eligibility criteria applied in the selection of studies were based on the Preferred Reporting Items for Systematic Review and Meta-Analyses (PRISMA). For exploratory purposes, we applied hierarchical clustering, while for in-depth analysis, we used principal component analysis (PCA) and meta-analysis. RESULTS: The search strategy based on the PRISMA eligibility criteria provided us with 63 out of 2234 potential articles, 206 observations, 89 methodologies, 4 survey purposes, 3 data sources, 7 data types, and 3 resource types. Cluster analysis and PCA organized the information included in the paper dataset into two dimensions and labels: "supervised methods, institutional dataset, and predictive and classificatory purposes" (correlation 0.97-8.18 × 10-1; p-value 7.67 × 10-55-1.28 × 10-22) and the second, Dim2 "not-supervised methods; project, simulation, literature, text data; monitoring, decision-making processes; machinery and environment" (corr. 0.84-0.47; p-value 5.79 × 10-25--3.59 × 10-6). We answered the research question regarding which method, among supervised, unsupervised, or other, is most suitable for application to data in the construction industry. CONCLUSIONS: The meta-analysis provided an overall estimate of the better effectiveness of supervised methods (Odds Ratio = 0.71, Confidence Interval 0.53-0.96) compared to not-supervised methods.

From vision to text: A comprehensive review of natural image captioning in medical diagnosis and radiology report generation.

Natural Image Captioning (NIC) is an interdisciplinary research area that lies within the intersection of Computer Vision (CV) and Natural Language Processing (NLP). Several works have been presented on the subject, ranging from the early template-based approaches to the more recent deep learning-based methods. This paper conducts a survey in the area of NIC, especially focusing on its applications for Medical Image Captioning (MIC) and Diagnostic Captioning (DC) in the field of radiology. A review of the state-of-the-art is conducted summarizing key research works in NIC and DC to provide a wide overview on the subject. These works include existing NIC and MIC models, datasets, evaluation metrics, and previous reviews in the specialized literature. The revised work is thoroughly analyzed and discussed, highlighting the limitations of existing approaches and their potential implications in real clinical practice. Similarly, future potential research lines are outlined on the basis of the detected limitations.

Random kernel k-nearest neighbors regression.

The k-nearest neighbors (KNN) regression method, known for its nonparametric nature, is highly valued for its simplicity and its effectiveness in handling complex structured data, particularly in big data contexts. However, this method is susceptible to overfitting and fit discontinuity, which present significant challenges. This paper introduces the random kernel k-nearest neighbors (RK-KNN) regression as a novel approach that is well-suited for big data applications. It integrates kernel smoothing with bootstrap sampling to enhance prediction accuracy and the robustness of the model. This method aggregates multiple predictions using random sampling from the training dataset and selects subsets of input variables for kernel KNN (K-KNN). A comprehensive evaluation of RK-KNN on 15 diverse datasets, employing various kernel functions including Gaussian and Epanechnikov, demonstrates its superior performance. When compared to standard KNN and the random KNN (R-KNN) models, it significantly reduces the root mean square error (RMSE) and mean absolute error, as well as improving R-squared values. The RK-KNN variant that employs a specific kernel function yielding the lowest RMSE will be benchmarked against state-of-the-art methods, including support vector regression, artificial neural networks, and random forests.

Applying the Milan models to setting analytical performance specifications - considering all the information.

Analytical performance specifications (APS) are used for decisions about the required analytical quality of pathology tests to meet clinical needs. The Milan models, based on clinical outcome, biological variation, or state of the art, were developed to provide a framework for setting APS. An approach has been proposed to assign each measurand to one of the models based on a defined clinical use, physiological control, or an absence of quality information about these factors. In this paper we propose that in addition to such assignment, available information from all models should be considered using a risk-based approach that considers the purpose and role of the actual test in a clinical pathway and its impact on medical decisions and clinical outcomes in addition to biological variation and the state-of-the-art. Consideration of APS already in use and the use of results in calculations may also need to be considered to determine the most appropriate APS for use in a specific setting.

Emerging pharmacotherapy for the treatment of cannabis use disorder.

INTRODUCTION: About one-fifth of cannabis users, the most commonly used illicit substance, have cannabis use disorder (CUD). Psychiatric disorders and suicide are more common in these patients, and the disability-adjusted life years were reported to be 0.69 million. Pharmacotherapy for CUD is an unmet public health need, as current evidence-based therapies have limited efficacy. AREAS COVERED: After explaining the pathophysiology of CUD, the effects of emerging pharmacological interventions in its treatment obtained from randomized controlled trials were reviewed in light of mechanisms of action. Superiority over control of cannabidiol, gabapentin, galantamine, nabilone plus zolpidem, nabiximols, naltrexone, PF-04457845, quetiapine, varenicline, and topiramate were observed through the cannabinoid, glutamatergic, γ-aminobutyric acidergic, serotonergic, noradrenergic, dopaminergic, opioidergic, and cholinergic systems. All medications were reported to be safe and tolerable. EXPERT OPINION: Adding pharmacotherapy to psychotherapy is the optimal treatment for CUD on a case-by-case basis. Drug development to add to psychotherapy is the main path, but time and cost suggest repurposing and repositioning existing drugs. Considering sample size, follow-up, and effect size, further studies using objective tools are necessary. The future of CUD treatment is promising.

Supported self-management in long-term conditions in an African context.

Self-management is an important strategy to improve quality of life, appropriately manage long-term health conditions, and reduce the economic burden of long-term health conditions. However, equitable healthcare access remains an issue, and the focus on 'self' in self-management is problematic. Our review aims to explore the conceptualisation and evolution of supported self-management in an African context and its relevance to physiotherapy. A state-of-the-art review of the literature was undertaken by the authors. The authors knowledge of the subject area and a database search retrieved recent articles exploring patients' and healthcare providers' understanding of supported self-management in Africa. Relevant articles were read, and data summaries of included studies were extracted and tabulated. Findings were organised deductively. Sixteen studies, 11 primary research, and 5 reviews (2016-2023) undertaken in a variety of sub-Saharan countries with healthcare workers (~n = 177) and people (~n = 16 115) living with a mix of non-communicable and communicable conditions were considered in this state-of-the-art review. Self-management perceptions were drawn from Western authors spanning development research and understanding of the concepts in Western thinking. We conclude that imported concepts, such as supported self-management for long-term conditions, should be considered within local health delivery solutions. These should be embedded in an understanding of traditional African health systems. Clinical implications: There is a need to develop locally derived African solutions. Self-management strategies for long-term health conditions should be developed, considering traditional holistic African health systems.

Bibliometric analysis of Advanced Oxidation Processes studies with a focus on Life Cycle Assessment and Costs.

Advanced oxidation processes (AOPs) are wastewater treatment technologies that stand out for their ability to degrade Contaminants of Emerging Concern (CECs). The literature has extensively investigated these removal processes for different aqueous matrices. Once technically mature, some of these systems have become accredited to be applied on a large scale, and therefore, their systemic performances in the environmental and cost spheres have also become essential requirements. This study proposed corroborating this trend, analyzing the available literature on the subject to verify how experts in the AOP area investigated this integration during 2015-2023. For this purpose, a sample of publications was treated by applying the Systematic Review (SR) methodology. This resulted in an extract of 83 studies that adopted life-cycle logic to estimate environmental impacts and process costs or evaluated them as complementary to the technical dimension of each treatment technology. This analysis found that both dimensions can be used for selecting or sizing AOPs at the design scale. However, the appropriate choice of the impact categories for the environmental assessment and establishing a methodology for cost analysis can make the approach still more effective. In addition, a staggering number of processes would broaden the reality and applicability of the estimates, and adopting multicriteria analysis methodologies could address essential aspects of decision-making processes during the design of the arrangements. By meeting the original purposes, the study broadened the requirements for designing AOPs and disseminating their use in mitigating the discharge of CECs.

Immunotherapy and Cancer: The Multi-Omics Perspective.

Immunotherapies have revolutionized cancer treatment approaches. Because not all patients respond positively to immune therapeutic agents, it represents a challenge for scientists who strive to understand the mechanisms behind such resistance. In-depth exploration of tumor biology, using novel technologies such as omics science, can help decode the role of the tumor immune microenvironment (TIME) in producing a response to the immune blockade strategies. It can also help to identify biomarkers for patient stratification and personalized treatment. This review aims to explore these new models and highlight their possible pivotal role in changing clinical practice.

Ultrasound Elastography as a Diagnostic Tool for Peyronie's Disease: A State-of-the-Art Review.

Elastography is a noninvasive method that utilizes ultrasound imaging to assess the elasticity and stiffness of soft tissue. Peyronie's disease (PD) is a chronic inflammatory condition that affects the male penis, causing the formation of fibrous plaques. This alters the penis's elasticity and can lead to changes in its shape. Ultrasound elastography (UE) is an important advancement in the diagnosis of PD. It not only identifies plaques, but it also measures their rigidity, providing crucial information to monitor changes during and after treatment. We conducted a narrative review of the scientific literature to identify articles that discuss the use of elastography in the diagnostic study of PD. The purpose of this study was to describe the "state of the art" in the diagnostic use of ultrasound in combination with elastography to highlight any benefits in the diagnosis of PD. We found 12 relevant articles after searching PubMed, Embase, and Google Scholar using the keywords "ultrasound elastography" and "Peyronie's disease", including eight clinical studies, two case reports, and two review articles. The results of our review indicate that UE is a useful technique for identifying Peyronie-related plaques, particularly when they are not detectable using a standard ultrasound or physical examination. It is also helpful in monitoring improvements during and after conservative treatments. More research is required to confirm the effectiveness of ultrasound elastography in diagnosing Peyronie's disease and to determine whether it is better than traditional ultrasound.

Does gene therapies clinical research in rare diseases reflects the competitivity of the country: Example of France.

Rare diseases are chronic, serious and generally genetic conditions affecting a small number of people, and their therapeutic management is a real challenge. They represent a considerable burden for patients, caregivers and society alike. Compared with existing symptomatic treatments, gene therapies represent a promising new approach aimed at treating these diseases by replacing a defective gene, or by abolishing or reviving a gene-derived function. France is considered one of the leading countries in the research and development of drugs for rare diseases, yet the position of French public and private stakeholders in the research and development of gene therapies for rare diseases at global and European level remains unclear. To answer this question, we used the GENOTRIAL FR database developed by OrphanDev to clarify France's involvement and competitiveness in this field. The results show that France is actively involved in gene therapy clinical trials, with a dense international collaboration network and solid expertise. However, the French medical infrastructure is mainly involved in clinical research on gene therapy candidates sponsored by several foreign countries. To a lesser extent, French public and private entities are also developing their own gene therapy candidates for various rare diseases, some of which have already reached advanced clinical phases. In conclusion, a number of technical and financial challenges need to be overcome if France is to maintain its position as a European and world leader and increase its contribution to reducing the economic and social burden of rare diseases by developing revolutionary and effective new therapies.

LSTM-SAGDTA: Predicting Drug-target Binding Affinity with an Attention Graph Neural Network and LSTM Approach.

INTRODUCTION: Drug development is a challenging and costly process, yet it plays a crucial role in improving healthcare outcomes. Drug development requires extensive research and testing to meet the demands for economic efficiency, cures, and pain relief. METHODS: Drug development is a vital research area that necessitates innovation and collaboration to achieve significant breakthroughs. Computer-aided drug design provides a promising avenue for drug discovery and development by reducing costs and improving the efficiency of drug design and testing. RESULTS: In this study, a novel model, namely LSTM-SAGDTA, capable of accurately predicting drug-target binding affinity, was developed. We employed SeqVec for characterizing the protein and utilized the graph neural networks to capture information on drug molecules. By introducing self-attentive graph pooling, the model achieved greater accuracy and efficiency in predicting drug-target binding affinity. CONCLUSION: Moreover, LSTM-SAGDTA obtained superior accuracy over current state-of-the-art methods only by using less training time. The results of experiments suggest that this method represents a highprecision solution for the DTA predictor.

What the Milan conference has taught us about analytical performance specification model definition and measurand allocation.

Analytical performance specifications (APS) represent the criteria that specify the quality required for laboratory test information to satisfy clinical needs. In 2014 the European Federation of Clinical Chemistry and Laboratory Medicine (EFLM) considered timely to update the topic of APS by organizing a conference in Milan in which some strategic concepts were proposed. Here I summarize the essential points representing the EFLM Strategic Conference heritage and discuss the approaches that will permit us to become more concrete, including roles and main actions expected from each of involved stakeholders for contributing a quantum leap forward in the way of practicality of Milan consensus about APS.

Downscaling of environmental indicators: A review.

Environmental indicators at different scales are important for environmental management, daily life, and scientific research. Because of the lack of statistics below a national scale for many environmental indicators, scholars have developed various downscaling methods to obtain finer-scale and diverse forms of data for different environmental indicators. However, the existing downscaling methods for environmental indicators are diverse and fragmented. Here, we reviewed the downscaling methods by reclassifying the environmental indicators from a life cycle perspective into five categories: natural resources use and related attributes; material and energy consumption; environmental discharge; climate change; and environmental footprints. We first provide a general introduction to downscaling theory in the environmental field, including definitions, techniques, and evolution. We then elaborate on downscaling methods and make an inventory of the five categories of environmental indicators. We summarize the downscaling methods commonly applied to specific indicators, scale transformation, the strengths and limitations of corresponding methods, and provide specific examples. Next, we discuss ways to select or construct downscaling methods based on four principles: objective orientation, data accessibility, model feasibility, and model adjustment. Finally, we explore the future direction of downscaling and provide insights for improving downscaling for environmental indicators. In this review, we generalize and clarify the downscaling techniques for environmental indicators, which will help facilitate the appropriate selection of downscaling methods by researchers.

Amide proton transfer-weighted imaging of the abdomen: Current progress and future directions.

The chemical exchange saturation transfer technique serves as a valuable tool for generating in vivo image contrast based on the content of various proton groups, including amide protons, amine protons, and aliphatic protons. Among these, amide proton transfer-weighted (APTw) imaging has seen extensive development as a means to assess the biochemical status of lesions. The exchange from saturated amide protons to bulk water protons during and following the saturation ratio frequency pulse contributes to detectable APT signals. While APTw imaging has garnered significant attention in the central nervous system, demonstrating noteworthy findings in cerebral neoplasia, stroke, and Alzheimer's disease over the past decade, its application in the abdomen has been a relatively recent progression. Notably, studies have explored its utility in hepatocellular carcinoma, prostate cancer, and cervical carcinoma within the abdominal context. Despite these advancements, there is a paucity of reviews on APTw imaging in abdominal applications. This paper aims to fill this gap by providing a concise overview of the fundamental theories underpinning APTw imaging. Additionally, we systematically summarize its diverse clinical applications in the abdomen, with a particular focus on the digestive and urogenital systems. Finally, the manuscript concludes by discussing technical limitations and factors influencing APTw imaging in abdominal applications, along with prospects for future research.

Emerging drugs for the treatment of irritability associated with autism spectrum disorder.

INTRODUCTION: Autism spectrum disorder (ASD) is an early-onset disorder with a prevalence of 1% among children and reported disability-adjusted life years of 4.31 million. Irritability is a challenging behavior associated with ASD, for which medication development has lagged. More specifically, pharmacotherapy effectiveness may be limited against high adverse effects (considering side effect profiles and patient medication sensitivity); thus, the possible benefits of pharmacological interventions must be balanced against potential adverse events in each patient. AREAS COVERED: After reviewing the neuropathophysiology of ASD-associated irritability, the benefits and tolerability of emerging medications in its treatment based on randomized controlled trials were detailed in light of mechanisms and targets of action. EXPERT OPINION: Succeeding risperidone and aripiprazole, monotherapy with memantine may be beneficial. In addition, N-acetylcysteine, galantamine, sulforaphane, celecoxib, palmitoylethanolamide, pentoxifylline, simvastatin, minocycline, amantadine, pregnenolone, prednisolone, riluzole, propentofylline, pioglitazone, and topiramate, all adjunct to risperidone, and clonidine and methylphenidate outperformed placebo. These effects were through glutamatergic, γ-aminobutyric acidergic, inflammatory, oxidative, cholinergic, dopaminergic, and serotonergic systems. All medications were reported to be safe and tolerable. Considering sample size, follow-up, and effect size, further studies are necessary. Along with drug development, repositioning and combining existing drugs supported by the mechanism of action is recommended.

Targeting diffuse midline gliomas: The promise of focused ultrasound-mediated blood-brain barrier opening.

Diffuse midline gliomas (DMGs), including diffuse intrinsic pontine glioma, have among the highest mortality rates of all childhood cancers, despite recent advancements in cancer therapeutics. This is partly because, unlike some CNS tumors, the blood-brain barrier (BBB) of DMG tumor vessels remains intact. The BBB prevents the permeation of many molecular therapies into the brain parenchyma, where the cancer cells reside. Focused ultrasound (FUS) with microbubbles has recently emerged as an innovative and exciting technology that non-invasively permeabilizes the BBB in a small focal region with millimeter precision. In this review, current treatment methods and biological barriers to treating DMGs are discussed. State-of-the-art FUS-mediated BBB opening is then examined, with a focus on the effects of various ultrasound parameters and the treatment of DMGs.