Designing a Se-intercalated MOF/MXene-derived nanoarchitecture for advancing the performance and durability of lithium-selenium batteries.

Lithium-selenium batteries have emerged as a promising alternative to lithium-sulfur batteries due to their high electrical conductivity and comparable volume capacity. However, challenges such as the shuttle effect of polyselenides and high-volume fluctuations hinder their practical implementation. To address these issues, we propose synthesizing Fe-CNT/TiO2 catalyst through high-temperature sintering of an amalgamated nanoarchitecture of carbon nanotubes decorated metal-organic framework (MOF) and MXene, optimized for efficient selenium hosting, leveraging the distinctive physicochemical properties. The catalytic features inherent in the porous Se@Fe-CNT/TiO2 nanoarchitecture were instrumental in promoting efficient ion and electron transport, and lithium-polyselenide kinetics, while its inherent porosity could play a crucial role in inhibiting electrode stress during cycling. This nanoarchitecture exhibits remarkable battery performance, retaining 99.7% of theoretical capacity after 425 cycles at 0.5 C rate and demonstrating 95.8% capacity retention after 2000 cycles at 1 C rate, with ∼100% Coulombic efficiency. Additionally, the Se@Fe-CNT/TiO2 electrode exhibited an impressive recovery of 297.5 mAh/g (97.9%) capacity after undergoing 450 cycles at a charging rate of 10 C and a discharging rate of 1 C. This synergistic integration of MOF- and MXene-derived materials unveils new possibilities for high-performance and durable LSeBs, thus advancing electrochemical energy storage systems.

Physiological features of parvalbumin-expressing GABAergic interneurons contributing to high-frequency oscillations in the cerebral cortex.

Parvalbumin-expressing (PV+) inhibitory interneurons drive gamma oscillations (30-80 Hz), which underlie higher cognitive functions. In this review, we discuss two groups/aspects of fundamental properties of PV+ interneurons. In the first group (dubbed Before Axon), we list properties representing optimal synaptic integration in PV+ interneurons designed to support fast oscillations. For example: [i] Information can neither enter nor leave the neocortex without the engagement of fast PV+ -mediated inhibition; [ii] Voltage responses in PV+ interneuron dendrites integrate linearly to reduce impact of the fluctuations in the afferent drive; and [iii] Reversed somatodendritic Rm gradient accelerates the time courses of synaptic potentials arriving at the soma. In the second group (dubbed After Axon), we list morphological and biophysical properties responsible for (a) short synaptic delays, and (b) efficient postsynaptic outcomes. For example: [i] Fast-spiking ability that allows PV+ interneurons to outpace other cortical neurons (pyramidal neurons). [ii] Myelinated axon (which is only found in the PV+ subclass of interneurons) to secure fast-spiking at the initial axon segment; and [iii] Inhibitory autapses - autoinhibition, which assures brief biphasic voltage transients and supports postinhibitory rebounds. Recent advent of scientific tools, such as viral strategies to target PV cells and the ability to monitor PV cells via in vivo imaging during behavior, will aid in defining the role of PV cells in the CNS. Given the link between PV+ interneurons and cognition, in the future, it would be useful to carry out physiological recordings in the PV+ cell type selectively and characterize if and how psychiatric and neurological diseases affect initiation and propagation of electrical signals in this cortical sub-circuit. Voltage imaging may allow fast recordings of electrical signals from many PV+ interneurons simultaneously.

Identifying Differences in Frames of Reference That Are Hard to Reconcile During the Process of Normative Integration to Deliver Care for People with Multiple Problems: A Mixed-Method Delphi Study in the Netherlands.

Background: Integrated care is enhanced by integration on system, organizational, professional, and clinical levels including functional and normative integration. Many studies have been done on functional integration on these different levels, less studies focus on how normative integration takes place. In this study, we focus on the question: what differences in frames of refence must be addressed to establish consensus on appropriate care for People with Multiple Problems? Methods: A mixed-method Delphi study was carried out in which professionals and managers regularly involved in care for people with multiple problems (PWMPs) worked towards consensus on appropriate care delivery through the assessment of 15 vignettes representing real trajectories of PWMPs. Results: No consensus on appropriate care delivery was reached on any of the 15 vignettes. Five differences in perspective explained the dissensus: 1) an individual versus a systemic perspective on the client; 2) a focus on self-expressed needs of clients or professionally assessed (normative) needs; 3) client-directed or caregiver-directed care; 4) client as victim of circumstances or responsible for circumstances; 5) a focus on barriers or opportunities. Conclusions: In general, panelists agreed that care for PWMPs should be integrated. However, the further integrated care was to be operationalized in practice the greater the dissensus between panelists emerged. To understand how these differences in perspectives may be overcome to provide care for PWMPs normative integration needs to be studied during actual processes of care delivery.

Production benefits on encoding are modulated by language experience: Less experience may help.

Several lines of research have shown that performing movements while learning new information aids later retention of that information, compared to learning by perception alone. For instance, articulated words are more accurately remembered than words that are silently read (the production effect). A candidate mechanism for this movement-enhanced encoding, sensorimotor prediction, assumes that acquired sensorimotor associations enable movements to prime associated percepts and hence improve encoding. Yet it is still unknown how the extent of prior sensorimotor experience influences the benefits of movement on encoding. The current study addressed this question by examining whether the production effect is modified by prior language experience. Does the production effect reduce or persist in a second language (L2) compared to a first language (L1)? Two groups of unbalanced bilinguals, German (L1) - English (L2) bilinguals (Experiment 1) and English (L1) - German (L2) bilinguals (Experiment 2), learned lists of German and English words by reading the words silently or reading the words aloud, and they subsequently performed recognition tests. Both groups showed a pronounced production effect (higher recognition accuracy for spoken compared to silently read words) in the first and second languages. Surprisingly, the production effect was greater in the second languages compared to the first languages, across both bilingual groups. We discuss interpretations based on increased phonological encoding, increased effort or attention, or both, when reading aloud in a second language.

Can 2D Semiconductors Be Game-Changers for Nanoelectronics and Photonics?

2D semiconductors have interesting physical and chemical attributes that have led them to become one of the most intensely investigated semiconductor families in recent history. They may play a crucial role in the next technological revolution in electronics as well as optoelectronics or photonics. In this Perspective, we explore the fundamental principles and significant advancements in electronic and photonic devices comprising 2D semiconductors. We focus on strategies aimed at enhancing the performance of conventional devices and exploiting important properties of 2D semiconductors that allow fundamentally interesting device functionalities for future applications. Approaches for the realization of emerging logic transistors and memory devices as well as photovoltaics, photodetectors, electro-optical modulators, and nonlinear optics based on 2D semiconductors are discussed. We also provide a forward-looking perspective on critical remaining challenges and opportunities for basic science and technology level applications of 2D semiconductors.

Exploiting the potential of a novel "in-situ latent heat recovery" in hollow-fiber vacuum membrane distillation process for simultaneously improved water production and energy efficiency.

Thermal driven membrane distillation (MD) technology is a promising method for purifying & recovering various salty (especially high salty) or contaminated wastewaters with low-grade heat sources. However, the drawbacks of "high energy consumption" and "high cooling water consumption" pose special challenges for the future development of this technology. In this article, we report an innovative strategy called "in-situ heat transfer", which is based on the jacketed structure composed of hollow fiber membranes and capillary heat exchange tubes, to simplify the migration steps of condensation latent heat in MD heat recovery process. The results indicate that the novel heat recovery strategy exhibits higher growth rates both in the flux and gained output ratio (47.4 % and 173.1 %, respectively), and further reduces the system's dependence on cooling water. In sum, under the control of the "in-situ heat transfer" mechanism, the functional coupling of "vapor condensation (exothermic)" and "feed evaporation (endothermic)" in limited-domain space is an attractive alternative solution, because it eliminates the disadvantages of the imbalance between heat supply and demand in traditional heat recovery methods. Our research may facilitate the development of MD heat recovery modules for industrial applications, which will help to further achieve the goal of energy saving and emission reduction.

Pathology in the Age of Artificial Intelligence (AI): Redefining Roles and Responsibilities for Tomorrow's Practitioners.

The evolution of pathology from its rudimentary beginnings around 1700 BC to the present day has been marked by profound advancement in understanding and diagnosing diseases. This journey, from the earliest dissections to the modern era of histochemical analysis, sets the stage for the next transformative leap to the integration of artificial intelligence (AI) in pathology. Recent research highlights AI's significant potential to revolutionize healthcare within the next decade, with a particular impact on diagnostic processes. A majority of pathologists foresee AI becoming a cornerstone in diagnostic workflow, driven by the advent of image-based algorithms and computational pathology. These innovations promise to enhance the precision of disease diagnosis, particularly in complex cases, such as cancers, by offering detailed insights into the molecular and cellular mechanisms. Moreover, AI-assisted tools are improving the efficiency and accuracy of histological analysis by automating the evaluation of immunohistochemical biomarkers and tissue architecture. This shift not only accelerates diagnostic processes but also facilitates early disease management, crucial for improving patient outcomes. Furthermore, AI is reshaping educational paradigms in pathology, offering interactive learning environments that promise to enrich the training of future pathologists. Despite these advancements, the integration of AI in pathology raises ethical considerations regarding patient consent and data privacy. As pathology embarks on this AI-augmented era, it is imperative to navigate these challenges thoughtfully, ensuring that AI enhances rather than replaces the pathologist's role. This editorial discussed the historical progression of pathology, the current impact of AI on diagnostic practices, and the ethical implications of its adoption, underscoring the need for a symbiotic relationship between pathologists and AI to unlock the full potential of healthcare.

Prediction of drug-target binding affinity based on deep learning models.

The prediction of drug-target binding affinity (DTA) plays an important role in drug discovery. Computerized virtual screening techniques have been used for DTA prediction, greatly reducing the time and economic costs of drug discovery. However, these techniques have not succeeded in reversing the low success rate of new drug development. In recent years, the continuous development of deep learning (DL) technology has brought new opportunities for drug discovery through the DTA prediction. This shift has moved the prediction of DTA from traditional machine learning methods to DL. The DL frameworks used for DTA prediction include convolutional neural networks (CNN), graph convolutional neural networks (GCN), and recurrent neural networks (RNN), and reinforcement learning (RL), among others. This review article summarizes the available literature on DTA prediction using DL models, including DTA quantification metrics and datasets, and DL algorithms used for DTA prediction (including input representation of models, neural network frameworks, valuation indicators, and model interpretability). In addition, the opportunities, challenges, and prospects of the application of DL frameworks for DTA prediction in the field of drug discovery are discussed.

Postural behaviour in people with multiple sclerosis: A complexity paradox.

BACKGROUND: Balance deficits are a major concern for people with multiple sclerosis (pwMS). Measuring complexity of motor behaviour can offer an insight into MS-related changes in adaptability of the balance control system when dealing with increasingly complex tasks. QUESTION: Does postural behaviour complexity differ between pwMS at early stages of the disease and healthy controls (HC)? Does postural behaviour complexity change across increasingly complex tasks? METHODS: Forty-eight pwMS and 24 HC performed four increasingly complex postural tasks with eyes open (EO), eyes closed (EC), on firm (FS) and compliant surface (CS). Lumbar and sternum sensors recorded 3D acceleration, from which complexity index (CI) was calculated using multiscale sample entropy (MSE) in the frontal and sagittal planes. RESULTS: We found that only the complexity index in both planes during the eyes closed on compliant surface (EC-CS) task was significantly lower in pwMS compared to HC. We also found that complexity in pwMS was significantly lower during EC-CS compared to the other three tasks when using both lumbar and sternum sensors. SIGNIFICANCE: Increasing the complexity of postural tasks reduces the complexity of postural behaviour in pwMS. This paradox may reflect reduced adaptability of the sensorimotor integration processes at early stages of MS. CI can provide a different perspective on balance deficits and could potentially be a more sensitive biomarker of MS progression and an early indicator of balance deficit.

Perception of visual and audiovisual trajectories toward and away from the body in the first postnatal year.

Perceiving motion in depth is important in everyday life, especially motion in relation to the body. Visual and auditory cues inform us about motion in space when presented in isolation from each other, but the most comprehensive information is obtained through the combination of both of these cues. We traced the development of infants' ability to discriminate between visual motion trajectories across peripersonal space and to match these with auditory cues specifying the same peripersonal motion. We measured 5-month-old (n = 20) and 9-month-old (n = 20) infants' visual preferences for visual motion toward or away from their body (presented simultaneously and side by side) across three conditions: (a) visual displays presented alone, (b) paired with a sound increasing in intensity, and (c) paired with a sound decreasing in intensity. Both groups preferred approaching motion in the visual-only condition. When the visual displays were paired with a sound increasing in intensity, neither group showed a visual preference. When a sound decreasing in intensity was played instead, the 5-month-olds preferred the receding (spatiotemporally congruent) visual stimulus, whereas the 9-month-olds preferred the approaching (spatiotemporally incongruent) visual stimulus. We speculate that in the approaching sound condition, the behavioral salience of the sound could have led infants to focus on the auditory information alone, in order to prepare a motor response, and to neglect the visual stimuli. In the receding sound condition, instead, the difference in response patterns in the two groups may have been driven by infants' emerging motor abilities and their developing predictive processing mechanisms supporting and influencing each other.

Examination of sensory reception and integration abilities in children with and without Prader-Willi syndrome.

BACKGROUND: Good postural stability control is dependent upon the complex integration of incoming sensory information (visual, somatosensory, vestibular) with neuromotor responses that are constructed in advance of a voluntary action or in response to an unexpected perturbation. AIMS: To examine whether differences exist in how sensory inputs are used to control standing balance in children with and without Prader-Willi syndrome (PWS). METHODS AND PROCEDURES: In this cross-sectional study, 18 children with PWS and 51 children categorized as obese but without PWS (without PWS) ages 8-11 completed the Sensory Organization Test®. This test measures the relative contributions of vision, somatosensory, and vestibular inputs to the control of standing balance. The composite equilibrium score (CES) derived from performance in all sensory conditions, in addition to equilibrium scores (EQs) and falls per condition were compared between groups. OUTCOMES AND RESULTS: The CES was lower for children with PWS compared to children without PWS (M=53.93, SD=14.56 vs. M=66.17, SD=9.89, p = .001) while EQs declined in both groups between conditions 1 and 4 (F (1.305, 66.577) = 71.381, p < .001). No group differences in the percent of falls were evident in condition 5 but more children with PWS fell in condition 6 (χ2 (1) = 7.468, p = .006). Group differences in frequency of repeated falls also approached significance in conditions 5 (χ2 (3) = 4.630, p = .099) and 6 (χ2 (3) = 5.167, p = .076). CONCLUSIONS AND IMPLICATIONS: Children with PWS demonstrated a lower overall level of postural control and increased sway when compared to children with obesity. Both the higher incidence and repeated nature of falls in children with PWS in conditions 5 and 6 suggest an inability to adapt to sensory conditions in which vestibular input must be prioritized. Postural control training programs in this population should include activities that improve their ability to appropriately weight sensory information in changing sensory environments, with a particular focus on the vestibular system. WHAT DOES THIS STUDY ADD?: This study shows that children with PWS demonstrate a lower level of postural stability. The results suggest that children with PWS show inability to adapt to sensory conditions that require prioritizing vestibular information to maintain postural control. This information can be used to help guide training programs in this population.

Factors Influencing the Integration of Traditional Medicine and Mainstream Medicine in Mental Health Services in West Africa: A Systematic Review Using Narrative Synthesis.

This study explored the enablers and obstacles to the integration of traditional medicine and mainstream medicine in mental health services in West Africa. This study is a systematic review conducted in accordance with the relevant parts of the Preferred Reporting Items for Systematic reviews and Meta-analyses. Keywords searches were done in databases, and other reference lists were also searched. The Rainbow model of integrated care and a thematic analysis framework were used to account for the factors influencing the integration of traditional medicine and mainstream medicine in mental health services in West Africa. A total of 12 studies met the eligibility criteria after the evaluation of 6413 articles from databases and reference lists. The themes of: policy and implementation; different conceptualisation of mental health/referrals; trust issues, and education and training, were enablers or obstacles of integration depending on how they worked to facilitate or hinder integration. There was an indication of little integration of TM and MM at the macro, meso and micro levels in mental health services in West Africa. Though the study does cover all the West African states evenly, it is recommended that policy-makers and stakeholders interested in integration should ensure integration activities, especially policies, cut across all the levels of the rainbow model of integrated care and are planned and aligned at the macro, meso and micro levels instead of using ad hoc measures, informal initiatives or placing TM services in MM mental health services, which do not amount to integration.

University teachers' perceptions of ICT-based teaching to construct knowledge for effective classroom interaction in the context of TPACK model.

The purpose of the research was to investigate university teachers' perceptions of information and communication technology (ICT) to enhance teaching and construct new knowledge. The objective was to determine how teachers at the University of the Gambia perceived the effectiveness of the TPACK (Technology, Pedagogy, and Content Knowledge) model in teaching through ICT and how different attributes of teachers affect their level of TPACK knowledge. This study used a questionnaire, adapted from the TPACK model, which was administered to 88 faculty selected purposively from the University of the Gambia to collect data on their level of awareness of ICT-based teaching. Descriptive analysis was first run to check the scores of all components of TPACK, then a correlational analysis was carried out to measure the relationship between the TPACK constructs. The data collected from these analyses were used to construct a structural equation model that showed the relationship between TPACK constructs as perceived by the faculty of the University of the Gambia. The results of this study showed that the individual construct (i.e., technology, pedagogy, and content) and the paired constructs (i.e. Technology and Pedagogy, Technology and Content, Pedagogy and Content knowledge) of TPACK are positively correlated with teachers' perceived TPACK, as well as the findings are consistent with the earlier claim that ICT-based instruction may not progress as quickly in education even when it is available and teachers are not knowledgeable about it. The results contribute to earlier research that aims to develop strategies for implementing ICT-based instruction in HEIs and offer advice to educators on how to create policies including TPACK components in their teaching and learning.

Analysis of the influencing factors of the scientific fitness literacy of nurses in the context of exercise and medicine integration.

OBJECTIVE: The present study aims to explore the influencing factors of the scientific fitness literacy of nurses and provide a strategic basis for literacy improvement. METHODS: A questionnaire on the influencing factors of scientific fitness literacy of nurses was designed by the group conducting the present study; the questionnaire was based on the socioecology model and the questionnaire preparation method. The general data questionnaire and the questionnaire on the influencing factors of scientific fitness literacy of nurses were adopted to investigate nurses in tertiary hospitals in order to analyze and discuss the influencing factors of their scientific fitness literacy. RESULTS: (1) The questionnaire on the influencing factors of the scientific fitness literacy of nurses comprised five dimensions and 36 items. The overall item-content validity index was 0.833-1.000, the scale-content validity index was 0.974, and the overall Cronbach's α coefficient was 0.955; (2) the results of the pairwise Pearson correlation analysis showed that all five dimensions were positively correlated with the scientific fitness literacy of nurses; and (3) the results of the multiple linear regression analysis revealed that five dimensions, as well as the existence of exercise habits in daily life, had a significant impact on the scientific fitness literacy of nurses (P < 0.001). CONCLUSION: The factors influencing the scientific fitness literacy of nurses involved all levels of the socioecological system. The methods of improving the awareness of the scientific fitness of nurses and providing opportunities for scientific fitness activities via the hospital played a critical role in literacy improvement. However, the lack of professional guidance and an atmosphere promoting scientific fitness might hinder literacy improvement.

Trends and predictors of unmet need for family planning among women living with HIV in Zambia: implications for elimination of vertical transmission of HIV.

BACKGROUND: Prevention of vertical (mother to child) transmission of HIV is one of the key strategies towards HIV epidemic control. Despite considerable progress over the past decade in Zambia, the country is yet to reach global and national target for elimination of vertical transmission of HIV. Avoidance of unintended pregnancy among women living with HIV is one of the cost-effective interventions in a comprehensive approach to prevent vertical transmission of HIV. Therefore, this study aimed at ascertaining trends in and predictors of unmet need for family planning among women living with HIV in Zambia. METHODS: The study employed a repeated cross sectional (RCS) study design, using data from the three (3) most recent consecutive rounds of the Zambia Demographic and Health Survey (ZDHS) conducted in 2007, 2013/2014 and 2018. The study used data from a total of 27,153 women aged 15-49 years over the three survey periods among whom 4,113 had an HIV positive result following a rigorous HIV testing algorithm of the demographic and health surveys, and these constituted our sample size of women living with HIV. We used descriptive statistics and logistic regression analyses to respectively ascertain trends in and predictors of unmet need for family planning among women living with HIV. RESULTS: Over the three survey points, unmet need for family planning among women living with HIV has largely remained unchanged from 20.8% in 2007 to 20.5% in 2013/14 and 21.1% in 2018 DHS. Residence, age of women, household wealth, woman's parity, employment, and age of spouse emerged as significant predictors of unmet need for family planning among women living with HIV in Zambia. CONCLUSION: Preventing HIV infection in a child preserves life, contributes to improving quality of life from its early stages and averts lifetime costs of HIV treatment and associated healthcare costs. There is need to consider optimization of interventions to prevent vertical transmission of HIV including shaping programming regarding preventing unintended pregnancies among women living with HIV. Among other aspects, policy and practice need to strengthen SRH/HIV integration and better target rural residents, younger women, those with high parity and consider positive male engagement to reduce unmet need for family planning among women living with HIV.

An Urban Intelligence Architecture for Heterogeneous Data and Application Integration, Deployment and Orchestration.

This paper describes a novel architecture that aims to create a template for the implementation of an IT platform, supporting the deployment and integration of the different digital twin subsystems that compose a complex urban intelligence system. In more detail, the proposed Smart City IT architecture has the following main purposes: (i) facilitating the deployment of the subsystems in a cloud environment; (ii) effectively storing, integrating, managing, and sharing the huge amount of heterogeneous data acquired and produced by each subsystem, using a data lake; (iii) supporting data exchange and sharing; (iv) managing and executing workflows, to automatically coordinate and run processes; and (v) to provide and visualize the required information. A prototype of the proposed IT solution was implemented leveraging open-source frameworks and technologies, to test its functionalities and performance. The results of the tests performed in real-world settings confirmed that the proposed architecture could efficiently and easily support the deployment and integration of heterogeneous subsystems, allowing them to share and integrate their data and to select, extract, and visualize the information required by a user, as well as promoting the integration with other external systems, and defining and executing workflows to orchestrate the various subsystems involved in complex analyses and processes.

Integration and the risk of liver cancer-Is there a real risk?

Adeno-associated virus (AAV)-based gene therapies are in clinical development for haemophilia and other genetic diseases. Since the recombinant AAV genome primarily remains episomal, it provides the opportunity for long-term expression in tissues that are not proliferating and reduces the safety concerns compared with integrating viral vectors. However, AAV integration events are detected at a low frequency. Preclinical studies in mouse models have reported hepatocellular carcinoma (HCC) after systemic AAV administration in some settings, though this has not been reported in large animal models. The risk of HCC or other cancers after AAV gene therapy in clinical studies thus remains theoretical. Potential risk factors for HCC after gene therapy are beginning to be elucidated through animal studies, but their relevance to human studies remains unknown. Studies to investigate the factors that may influence the risk of oncogenesis as well as detailed investigation of cases of cancer in AAV gene therapy patients will be important to define the potential risk of AAV genotoxicity.

Tagging the tjp1a Gene in Zebrafish with Monomeric Red Fluorescent Protein Using Biotin Homology Arms.

Tjp1a and other tight junction and adherens proteins play important roles in cell-cell adhesion, scaffolding, and forming seals between cells in epithelial and endothelial tissues. In this study, we labeled Tjp1a of zebrafish with the monomeric red fluorescent protein (mRFP) using CRISPR/Cas9-mediated targeted integration of biotin-labeled polymerase chain reaction (PCR) generated templates. Labeling Tjp1a with RFP allowed us to follow membrane and junctional dynamics of epithelial and endothelial cells throughout zebrafish embryo development. For targeted integration, we used short 35 bp homology arms on each side of the Cas9 genomic target site at the C-terminal of the coding sequence in tjp1a. Through PCR using 5' biotinylated primers containing the homology arms, we generated a double-stranded template for homology directed repair containing a flexible linker followed by RFP. Cas9 protein was complexed with the tjp1a gRNA before mixing with the repair template and microinjected into one-cell zebrafish embryos. We confirmed and recovered a precise integration allele at the desired site at the tjp1a C-terminus. Examination of fluorescence reveals RFP cell-cell junctional labeling using confocal imaging. We are currently using this stable tjp1a-mRFPis86 line to examine the behavior and interactions between cells during vascular formation in zebrafish.

Interpretable Deep Learning System for Identifying Critical Patients Through the Prediction of Triage Level, Hospitalization, and Length of Stay: Prospective Study.

BACKGROUND: Triage is the process of accurately assessing patients' symptoms and providing them with proper clinical treatment in the emergency department (ED). While many countries have developed their triage process to stratify patients' clinical severity and thus distribute medical resources, there are still some limitations of the current triage process. Since the triage level is mainly identified by experienced nurses based on a mix of subjective and objective criteria, mis-triage often occurs in the ED. It can not only cause adverse effects on patients, but also impose an undue burden on the health care delivery system. OBJECTIVE: Our study aimed to design a prediction system based on triage information, including demographics, vital signs, and chief complaints. The proposed system can not only handle heterogeneous data, including tabular data and free-text data, but also provide interpretability for better acceptance by the ED staff in the hospital. METHODS: In this study, we proposed a system comprising 3 subsystems, with each of them handling a single task, including triage level prediction, hospitalization prediction, and length of stay prediction. We used a large amount of retrospective data to pretrain the model, and then, we fine-tuned the model on a prospective data set with a golden label. The proposed deep learning framework was built with TabNet and MacBERT (Chinese version of bidirectional encoder representations from transformers [BERT]). RESULTS: The performance of our proposed model was evaluated on data collected from the National Taiwan University Hospital (901 patients were included). The model achieved promising results on the collected data set, with accuracy values of 63%, 82%, and 71% for triage level prediction, hospitalization prediction, and length of stay prediction, respectively. CONCLUSIONS: Our system improved the prediction of 3 different medical outcomes when compared with other machine learning methods. With the pretrained vital sign encoder and repretrained mask language modeling MacBERT encoder, our multimodality model can provide a deeper insight into the characteristics of electronic health records. Additionally, by providing interpretability, we believe that the proposed system can assist nursing staff and physicians in taking appropriate medical decisions.

Clinically significant changes in genes and variants associated with epilepsy over time: implications for re-analysis.

Despite the significant advances in understanding the genetic architecture of epilepsy, many patients do not receive a molecular diagnosis after genomic testing. Re-analysing existing genomic data has emerged as a potent method to increase diagnostic yields-providing the benefits of genomic-enabled medicine to more individuals afflicted with a range of different conditions. The primary drivers for these new diagnoses are the discovery of novel gene-disease and variants-disease relationships; however, most decisions to trigger re-analysis are based on the passage of time rather than the accumulation of new knowledge. To explore how our understanding of a specific condition changes and how this impacts re-analysis of genomic data from epilepsy patients, we developed Vigelint. This approach combines the information from PanelApp and ClinVar to characterise how the clinically relevant genes and causative variants available to laboratories change over time, and this approach to five clinical-grade epilepsy panels. Applying the Vigelint pipeline to these panels revealed highly variable patterns in new, clinically relevant knowledge becoming publicly available. This variability indicates that a more dynamic approach to re-analysis may benefit the diagnosis and treatment of epilepsy patients. Moreover, this work suggests that Vigelint can provide empirical data to guide more nuanced, condition-specific approaches to re-analysis.