Interpreters

Deep learning (DL) is poised to redefine the way medical images are processed and analyzed. Convolutional neural networks (CNNs), a specific type of DL architecture, are exceptional for high-throughput processing, allowing for the effective extraction of relevant diagnostic patterns from large volumes of complex visual data. This technology has garnered substantial interest in the field of neuro-oncology as a promising tool to enhance medical imaging throughput and analysis. A multitude of methods harnessing MRI-based CNNs have been proposed for brain tumor segmentation, classification, and prognosis prediction...

AIM: To understand clinicians' motivations to engage in mentoring to support newly graduated nurses and midwives working in hospital settings. BACKGROUND: Nursing and midwifery literature has established the benefits of mentoring and challenges that affect the effectiveness of formal mentoring programmes. No studies have explored hospital nurses' and midwives' motivations to mentor in the absence of the obligatory status and associated rewards of institutionalised mentoring...

Precise and personalized drug application is crucial in the clinical treatment of complex diseases. Although neural networks offer a new approach to improving drug strategies, their internal structure is difficult to interpret. Here, we propose PBAC (Pathway-Based Attention Convolution neural network), which integrates a deep learning framework and attention mechanism to address the complex biological pathway information, thereby provide a biology function-based robust drug responsiveness prediction model. PBAC has four layers: gene-pathway layer, attention layer, convolution layer and fully connected layer...

BACKGROUND: There are no unequivocal histopathological findings for the diagnosis of fatal asphyxia due to neck compression. From the observation of a series of asphyxiation cases, we noted, during microscopic analysis, a high frequency of "detachment" of soft tissues from the hyoid bone. This specifically refers to the presence of an optical space between the surface of the hyoid bone and soft tissues. OBJECTIVES: We aimed to evaluate the detachment of soft tissues from the hyoid bone as specific histological evidence of death due to strangulation asphyxia...

PURPOSE: The National Institute of Health's All of Us Research Program represents a national effort to develop a database to advance health research, especially among individuals historically underrepresented in research, including rural populations. The purpose of this study was to describe the rural populations identified in the All of Us Research Program using the only proxy measure currently available in the dataset. METHODS: Currently, the All of Us Research Program provides a proxy measure of rurality that identifies participants who self-reported delaying care due to far travel distances associated with living in rural areas...

Genome-wide association studies (GWAS) significantly advanced our understanding of the genetic underpinnings of diseases. However, challenges persist, particularly in interpreting non-coding variants in linkage disequilibrium that affect genes in disease-relevant cells. Addressing key obstacles-identifying causal variants, uncovering target genes, and understanding their network impact-is crucial. This graphical review navigates advanced techniques to fully leverage GWAS for future therapeutic breakthroughs...

Quantum sensors leverage matter's quantum properties to enable measurements with unprecedented spatial and spectral resolution. Among these sensors, those utilizing nitrogen-vacancy (NV) centers in diamond offer the distinct advantage of operating at room temperature. Nevertheless, signals received from NV centers are often complex, making interpretation challenging. This is especially relevant in low magnetic field scenarios, where standard approximations for modeling the system fail. Additionally, NV signals feature a prominent noise component...

Identifying what quantum-mechanical properties are useful to untap a superior performance in quantum technologies is a pivotal question. Quantum resource theories provide a unified framework to analyze and understand such properties, as successfully demonstrated for entanglement and coherence. While these are examples of convex resources, for which quantum advantages can always be identified, many physical resources are described by a nonconvex set of free states and their interpretation has so far remained elusive...

The first complete measurement of the β-decay strength distribution of _{17}^{45}Cl_{28} was performed at the Facility for Rare Isotope Beams (FRIB) with the FRIB Decay Station Initiator during the second FRIB experiment. The measurement involved the detection of neutrons and γ rays in two focal planes of the FRIB Decay Station Initiator in a single experiment for the first time. This enabled an analytical consistency in extracting the β-decay strength distribution over the large range of excitation energies, including neutron unbound states...

Unlike bosons and fermions, quasiparticles in two-dimensional quantum systems, known as anyons, exhibit statistical exchange phases that range between 0 and π. In fractional quantum Hall states, these anyons, possessing a fraction of the electron charge, traverse along chiral edge channels. This movement facilitates the creation of anyon colliders, where coupling different edge channels through a quantum point contact enables the observation of two-particle interference effects. Such configurations are instrumental in deducing the anyonic exchange phase via current cross-correlations...

The photo-induced dissociative ionization of lanthanide complexes Ln(hfac)3 (Ln = Pr, Er, Yb) is studied using ultrafast shaped laser pulses in a time-of-flight (TOF) mass spectrometry setup. Various fluorine and Ln-containing mass fragments were observed, which can be interpreted by the photo-fragmentation mechanistic pathway involving C-C bond rotation processes proposed previously. A set of experiments used pulse shaping guided by closed-loop feedback control to identify pulses that optimize the ratio of LnF+ /LnO+ ...

PURPOSE: To investigate perspectives of multiple stakeholders involved in development and delivery of Vietnam's first speech-language pathology degrees and derive recommendations for future degrees in Vietnam and other Majority World countries. METHODS: An exploratory-descriptive qualitative research design using focus groups and individual semi-structured interviews in the preferred language (English or Vietnamese) was used, with 70 participants from five stakeholder groups: project managers, students, academic educators, placement supervisors and interpreters...

Normal epileptiform-like variants or benign epileptiform variants are a diagnostic challenge in the interpretation of electroencephalograms, which require the knowledge and extensive experience of those responsible for the electroencephalographic report. They include a heterogeneous group of findings, some quite uncommon, initially related to epilepsy and various neurological conditions. Most of them are currently considered variants with no pathological significance, and their over-interpretation usually leads to misdiagnosis and the establishment of unnecessary treatments...

BACKGROUND: Autologous platelet-rich plasma (PRP) consists of plasma and a concentrate of platelets extracted from fresh whole blood of the person being treated. Research has suggested that intrauterine or intraovarian infusion/injection of PRP before embryo transfer may improve endometrial receptivity and response to ovarian stimulation in women undergoing assisted reproduction. We compared these interventions to standard treatment, placebo, or other interventions (mechanical or pharmacological)...

The rapid evolution of artificial intelligence (AI), particularly in deep learning, has significantly impacted radiology, introducing an array of AI solutions for interpretative tasks. This paper provides radiology departments with a practical guide for selecting and integrating AI solutions, focusing on interpretative tasks that require the active involvement of radiologists. Our approach is not to list available applications or review scientific evidence, as this information is readily available in previous studies; instead, we concentrate on the essential factors radiology departments must consider when choosing AI solutions...

Metabolomics, leveraging techniques like NMR and MS, is crucial for understanding biochemical processes in pathophysiological states. This field, however, faces challenges in metabolite sensitivity, data complexity, and omics data integration. Recent machine learning advancements have enhanced data analysis and disease classification in metabolomics. This study explores machine learning integration with metabolomics to improve metabolite identification, data efficiency, and diagnostic methods. Using deep learning and traditional machine learning, it presents advancements in metabolic data analysis, including novel algorithms for accurate peak identification, robust disease classification from metabolic profiles, and improved metabolite annotation...

Nearly 80% of the world's population trusts traditional medicine and plant-based drug compounds to improve health, and more than 50% of women who participated in a study have used herbal remedies during pregnancy. Bocconia frutescens L. is a plant native to tropical America, where infusion of its leaves has been widely used for the treatment of several gastrointestinal disorders. We have already shown that orogastric consumption of B. frutescens L. during the organogenesis period at concentrations equivalent to human consumption produces teratogenic effects in rats, but effects on progeny development have not yet been studied...

Inferring the cancer-type specificities of ultra-rare, genome-wide somatic mutations is an open problem. Traditional statistical methods cannot handle such data due to their ultra-high dimensionality and extreme data sparsity. To harness information in rare mutations, we have recently proposed a formal multilevel multilogistic "hidden genome" model. Through its hierarchical layers, the model condenses information in ultra-rare mutations through meta-features embodying mutation contexts to characterize cancer types...

BACKGROUND: The United Nations has declared 2021-2030 the 'Decade of Healthy Ageing' and identified the need to strengthen the evidence base on interpretations and determinants of healthy ageing to inform policy. OBJECTIVES: This study sought to interrogate a 'policy blind spot' and examine interpretations and experiences of sexuality and sexual health within the context of ageing well among women aged 50+. DESIGN: The qualitative study design was underpinned by an interpretivist epistemology...

BACKGROUND: Bronchoalveolar lavage (BAL) is a method for collecting the cellular and fluid components of the airway surface in the lungs. The assessment of differential cell profiles is potentially valuable in the diagnosis of pulmonary diseases, but there is no information about the normal BAL profiles in the Gezel breed. AIM: This study aimed to characterize the normal cryptologic findings of BAL with Gezel sheep. METHODS: Twenty healthy sheep (15 females: 5 males, bodyweight: 55-65 kg) were sedated with xylazine (0...