Search Results (462)

The modified Rankin Scale (mRS) is a widely used outcome measure for assessing disability in stroke care; however, its administration is often affected by subjectivity and variability, leading to poor inter-rater reliability and inconsistent scoring. Originally designed for hospital discharge evaluations, the mRS has evolved into an outcome tool for disability assessment and clinical decision-making. Inconsistencies persist due to a lack of standardization and cognitive biases during its use. This paper presents design principles for creating a standardized clinical assessment tool (CAT) for the mRS, grounded in human–computer interaction (HCI) and cognitive engineering principles. Design principles were informed in part by an anonymous online survey conducted with clinicians across Canada to gain insights into current administration practices, opinions, and challenges of the mRS. The proposed design principles aim to reduce cognitive load, improve inter-rater reliability, and streamline the administration process of the mRS. By focusing on usability and standardization, the design principles seek to enhance scoring consistency and improve the overall reliability of clinical outcomes in stroke care and research. Developing a standardized CAT for the mRS represents a significant step toward improving the accuracy and consistency of stroke disability assessments. Future work will focus on real-world validation with healthcare stakeholders and exploring self-completed mRS assessments to further refine the tool. Full article

Objectives: This study investigates whether scan time in the high-resolution magnetic resonance imaging (MRI) of human embryos can be reduced without compromising spatial resolution by applying zero-shot self-supervised learning (ZS-SSL), a deep-learning-based reconstruction method. Methods: Simulations using a numerical phantom were conducted to evaluate spatial resolution across various acceleration factors (AF = 2, 4, 6, and 8) and signal-to-noise ratio (SNR) levels. Resolution was quantified using a blur-based estimation method based on the Sparrow criterion. ZS-SSL was compared to conventional compressed sensing (CS). Experimental imaging of a human embryo at Carnegie stage 21 was performed at a spatial resolution of (30 μm)³ using both retrospective and prospective undersampling at AF = 4 and 8. Results: ZS-SSL preserved spatial resolution more effectively than CS at low SNRs. At AF = 4, image quality was comparable to that of fully sampled data, while noticeable degradation occurred at AF = 8. Experimental validation confirmed these findings, with clear visualization of anatomical structures—such as the accessory nerve—at AF = 4; there was reduced structural clarity at AF = 8. Conclusions: ZS-SSL enables significant scan time reduction in high-resolution MRI of human embryos while maintaining spatial resolution at AF = 4, assuming an SNR above approximately 15. This trade-off between acceleration and image quality is particularly beneficial in studies with limited imaging time or specimen availability. The method facilitates the efficient acquisition of ultra-high-resolution data and supports future efforts to construct detailed developmental atlases. Full article

Disassembly is a crucial process in industrial operations, especially in tasks requiring high precision and strict safety standards when handling components with collaborative robots. However, traditional methods often rely on rigid and sequential task planning, which makes it difficult to adapt to unforeseen changes or dynamic environments. This rigidity not only limits flexibility but also leads to prolonged execution times, as operators must follow predefined steps that do not allow for real-time adjustments. Although techniques like teleoperation have attempted to address these limitations, they often hinder direct human–robot collaboration within the same workspace, reducing effectiveness in dynamic environments. In response to these challenges, this research introduces an advanced human–robot interaction (HRI) system leveraging a mixed-reality (MR) interface embedded in a head-mounted device (HMD). The system enables operators to issue real-time control commands using multimodal inputs, including voice, gestures, and gaze tracking. These inputs are synchronized and processed via the Robot Operating System (ROS2), enabling dynamic and flexible task execution. Additionally, the integration of deep learning algorithms ensures precise detection and validation of disassembly components, enhancing accuracy. Experimental evaluations demonstrate significant improvements, including reduced task completion times, enhanced operator experience, and compliance with strict adherence to safety standards. This scalable solution offers broad applicability for general-purpose disassembly tasks, making it well-suited for complex industrial scenarios. Full article

Background: Rheumatoid arthritis (RA) is an autoimmune disease that remains incurable. An increasing number of proteomic genome-wide association studies (GWASs) are emerging, offering immense potential for identifying novel therapeutic targets for diseases. This study aims to identify potential therapeutic targets for RA based on human plasma proteome. Methods: Protein quantitative trait loci were extracted and integrated from eight large-scale proteomic GWASs. Proteome-wide Mendelian randomization (Pro-MR) was performed to prioritize proteins causally associated with RA. Further validation of the reliability and stratification of prioritized proteins was performed using MR meta-analysis, colocalization, and transcriptome-wide summary-data-based MR. Subsequently, prioritized proteins were characterized through protein–protein interaction and enrichment analyses, pleiotropy assessment, genetically engineered mouse models, cell-type-specific expression analysis, and druggability evaluation. Phenotypic expansion analyses were also conducted to explore the effects of the prioritized proteins on phenotypes such as endocrine disorders, cardiovascular diseases, and other immune-related diseases. Results: Pro-MR prioritized 32 unique proteins associated with RA risk. After validation, prioritized proteins were stratified into four reliability tiers. Prioritized proteins showed interactions with established RA drug targets and were enriched in an immune-related functional profile. Four trans-associated proteins exhibited vertical or horizontal pleiotropy with specific genes or proteins. Genetically engineered mouse models for 18 prioritized protein-coding genes displayed abnormal immune phenotypes. Single-cell RNA sequencing data were used to validate the enriched expression of several prioritized proteins in specific synovial cell types. Nine prioritized proteins were identified as targets of existing drugs in clinical trials or were already approved. Further phenome-wide MR and mediation analyses revealed the effects and potential mediating roles of some prioritized proteins on other phenotypes. Conclusions: This study identified 32 plasma proteins as potential therapeutic targets for RA, expanding the prospects for drug discovery and deepening insights into RA pathogenesis. Full article

The mineralocorticoid receptor (MR), traditionally associated with renal function, has also been identified in various extrarenal tissues, including the heart, brain, and dorsal root ganglion (DRG) neurons in rodents. Previous studies suggest a role for the MR in modulating peripheral nociception, with MR activation in rat DRG neurons by its endogenous ligand, aldosterone. This study aimed to determine whether MR, its protective enzyme 11β-hydroxysteroid dehydrogenase type 2 (11β-HSD2), its endogenous ligand aldosterone, and the aldosterone-synthesizing enzyme CYP11B2 are expressed in human DRG neurons and whether they colocalize with key pain-associated signaling molecules as potential targets for genomic regulation. To this end, we performed mRNA transcript profiling and immunofluorescence confocal microscopy on human and rat DRG tissues. We detected mRNA transcripts for MR, 11β-HSD2, and CYP11B2 in human DRG, alongside transcripts for key thermosensitive and nociceptive markers such as TRPV1, the TTX-resistant sodium channel Nav1.8, and the neuropeptides CGRP and substance P (Tac1). Immunofluorescence analysis revealed substantial colocalization of MR with 11β-HSD2 and CGRP, a marker of unmyelinated C-fibers and thinly myelinated Aδ-fibers, in human DRG. MR immunoreactivity was primarily restricted to small- and medium-diameter neurons, with lower expression in large neurons (>70 µm). Similarly, aldosterone colocalized with CYP11B2 and MR with nociceptive markers including TRPV1, Nav1.8, and TrkA in human DRG. Importantly, functional studies demonstrated that prolonged intrathecal inhibition of aldosterone synthesis within rat DRG neurons, using an aldosterone synthase inhibitor significantly downregulated pain-associated molecules and led to sustained attenuation of inflammation-induced hyperalgesia. Together, these findings identify a conserved peripheral MR signaling axis in humans and highlight its potential as a novel target for pain modulation therapies. Full article

Metabolic Dysfunction-Associated Steatotic Liver Disease (MASLD) is one of the fastest-growing hepatic disorders worldwide. During its natural course, MASLD tends to progress from isolated steatosis of the liver to Metabolic Dysfunction-Associated Alcoholic Steatohepatitis (MASH), advanced fibrosis, and finally cirrhosis, with the risk of developing hepatocellular carcinoma (HCC). Although frequently related to overweight or obesity and other components of the metabolic syndrome (MS), MASLD can also be present in individuals without such risk factors. The mechanisms leading to MASLD are incompletely elucidated and may involve many proinflammatory and pro-fibrotic pathways, disrupted biliary acid homeostasis, and gut microbiota dysbiosis. Aldosterone and its interaction with the mineralocorticoid receptor (MR) are thought to participate in the pathogenesis of MASLD through the modulation of inflammation and fibrosis. Remarkably, blockade of the MR in experimental models was shown to improve MASH and fibrosis through mechanisms that need further characterization. So far, however, few clinical studies have explored the effect of MR blockade in the management of MASH and associated fibrosis. This review is intended to summarize the recent animal and human data concerning the interaction between MR pathways and MASLD. Full article

The 2016 Zika virus (ZIKV) epidemic has largely subsided, but a key question remains. How did ZIKV evolve to become a virulent human pathogen compared to the virus of its original discovery? What specific virologic and pathologic changes contributed to increased pathogenicity in humans? Phylogenetic studies have identified two genetically distinct ZIKV, the African and Asian lineages, which differ in their pathogenicity. Previous studies including ours suggest that the envelope (E) protein plays a key role in viral entry, immune activation, and neuropathogenesis. This study aimed to further elucidate virologic and pathogenic differences between these lineages by assessing their ability to bind and replicate in host cells, induce apoptotic cell death, trigger inflammatory responses, and influence human neural progenitor cell (hNPC)-derived neurosphere formation. We compared a historic African ZIKV strain (MR766) with an epidemic Brazilian strain (BR15) and evaluated the effects of the E protein inhibitor quercetin-3-β-O-D-glucoside (Q3G) and an E protein-neutralizing antibody (AbII). Our results revealed distinct virologic properties and that MR766 exhibited stronger inhibition of neurosphere formation due to enhanced viral binding to neuronal SH-SY5Y cells, while BR15 infection triggered a heightened pro-inflammatory cytokine response with reduced viral binding. Chimeric virus studies suggested that the E protein likely influences viral binding, replication efficiency, immune activation, and neuropathogenesis. Notably, Q3G exhibited antiviral activities against both MR766 and BR15, whereas AbII preferentially inhibited MR766. These findings highlight the virological differences between ancestral and epidemic viral strains, as well as the critical role of E protein in viral permissiveness, immune response, and neuropathogenesis, providing insights for developing targeted antiviral strategies. Full article

Background/Objectives: Knowledge Graphs (KGs) are often incomplete, which can significantly impact the performance of downstream applications. Manual completion of KGs is time-consuming and costly, emphasizing the importance of developing automated methods for KGC. Link prediction serves as a fundamental task in this domain. The semantic correlation among entity features plays a crucial role in determining the effectiveness of link-prediction models. Notably, the human brain can often infer information using a limited set of salient features. Methods: Inspired by this cognitive principle, this paper proposes a lightweight Bi-level routing attention mechanism specifically designed for link-prediction tasks. This proposed module explores a theoretically grounded and lightweight structural design aimed at enhancing the semantic recognition capability of language models without altering their core parameters. The proposed module enhances the model’s ability to attend to feature regions with high semantic relevance. With only a marginal increase of approximately one million parameters, the mechanism effectively captures the most semantically informative features. Result: It replaces the original feature-extraction module within the KGML framework and is evaluated on the publicly available WN18RR and FB15K-237 dataset. Conclusions: Experimental results demonstrate consistent improvements in standard evaluation metrics, including Mean Rank (MR), Mean Reciprocal Rank (MRR), and Hits@10, thereby confirming the effectiveness of the proposed approach. Full article

Blastocystis, a common intestinal protozoan in humans, is associated with gastrointestinal disorders, irritable bowel syndrome, urticaria, and colorectal cancer. Its genetic diversity and potential for treatment resistance make it a focus of ongoing research. This study evaluated the in vitro antiprotozoal activity of a postbiotic derived from Pediococcus acidilactici as a natural alternative treatment. P. acidilactici cultures were grown in MRS broth under anaerobic conditions, and the postbiotic was collected and characterized for pH, yield, organic acid composition, and phenolic compound content. Human isolates of Blastocystis subtypes ST1 and ST3 were cultured in Jones’ medium and exposed to varying postbiotic concentrations for 72 h. Viability was assessed microscopically. The cytotoxic effect of the postbiotic-derived P. acidilactici was evaluated by investigating its impact on the viability of HT-29 cells using the Cell Counting Kit 8. The postbiotic showed a 7% yield and a pH of 4.52 ± 0.11. It contained seven different organic acids, predominantly lactic acid, and eleven phenolic compounds, with naringin as the most abundant. At 4.38 mg/mL, the postbiotic achieved over 94% inhibition and 100% inhibition at 8.75 mg/mL and above. A pH analysis confirmed that the inhibition was independent of the culture medium acidity. Cell viability was not affected at the postbiotic concentration showing 100% antiprotozoal activity (8.75 mg/mL). These findings suggest that the P. acidilactici postbiotic is effective on a mixed culture of ST1 and ST3 subtypes and holds promise as a safe, natural antiprotozoal agent. Further in vivo studies are needed to confirm this. Full article

Extended reality (XR) has emerged as a transformative technology, offering innovative ways to visualize and interact with digital content. For educators, XR constitutes a valuable tool that advances pedagogical experience and improves teaching quality and clarity. While the literature highlights case studies and general guidelines for XR content development, there is limited focus on interaction techniques based on a comparative methodology within educational XR games. This study evaluates different interaction techniques from developers and users perspectives to identify strengths and limitations, providing useful insights to guide future developments in the field. Performed analysis determines the context in which each technique is most effective, how different techniques can be combined, and how integration can be improved for optimal impact. Additionally, methods for transitioning from traditional interaction techniques to modern XR approaches utilizing 3D space and interaction requirements are proposed. A theoretical framework for integrating, configuring, and blending interaction techniques in XR environments tailored for educational purposes is introduced to assist developers and educators in selecting and combining techniques to maximize their effectiveness in different educational contexts and challenges. By addressing these critical aspects, this paper contributes to advancing the understanding and design of XR interaction strategies, ultimately fostering better learning experiences and leading to improved educational outcomes. Full article

The advent of mixed reality (MR) systems has revolutionized human–computer interactions by seamlessly integrating virtual elements with the real world. Devices like the HoloLens 2 (HL2) enable intuitive, hands-free interactions through advanced hand-tracking technology, making them valuable in fields such as education, healthcare, engineering, and training simulations. However, despite the growing adoption of MR, there is a noticeable lack of comprehensive comparisons between the hand-tracking accuracy of the HL2 and high-precision benchmarks like motion capture systems. Such evaluations are essential to assess the reliability of MR interactions, identify potential tracking limitations, and improve the overall precision of hand-based input in immersive applications. This study aims to assess the accuracy of HL2 in tracking hand position and measuring kinematic hand parameters, including joint angles and lateral pinch span (distance between thumb and index fingertips), using its tracking data. To achieve this, the Vicon motion capture system (VM) was used as a gold-standard reference. Three tasks were designed: (1) finger tracing of a 2D pattern in 3D space, (2) grasping various common objects, and (3) lateral pinching of objects with varying sizes. Task 1 tests fingertip tracking, Task 2 evaluates joint angle accuracy, and Task 3 examines the accuracy of pinch span measurement. In all tasks, HL2 and VM simultaneously recorded hand positions and movements. The data captured in Task 1 were analyzed to evaluate HL2’s hand-tracking capabilities against VM. Finger rotation angles from Task 2 and lateral pinch span from Task 3 were then used to assess HL2’s accuracy compared to VM. The results indicate that the HL2 exhibits millimeter-level errors compared to Vicon’s tracking system in Task 1, spanning in a range from 2 mm to 4 mm, suggesting that HL2’s hand-tracking system demonstrates good accuracy. Additionally, the reconstructed grasping positions in Task 2 from both systems show a strong correlation and an average error of 5°, while in Task 3, the accuracy of the HL2 is comparable to that of VM, improving performance as the object thickness increases. Full article

Background/Objectives: There is a growing need for efficient prostate MRI protocols due to their increasing use in managing prostate cancer (PCa) and potential inclusion in screening. Deep learning reconstruction (DLR) may enhance MR acquisitions and improve image quality compared to conventional acceleration techniques. This systematic review examines DLR approaches to prostate MRI. Methods: A search of PubMed, Web of Science, and Google Scholar identified eligible studies comparing DLR to conventional reconstruction for prostate imaging. A narrative synthesis was performed to summarize the impact of DLR on acquisition time, image quality, and diagnostic performance. Results: Thirty-three studies showed that DLR can reduce acquisition times for T₂w and DWI imaging while maintaining or improving image quality. It did not significantly affect clinical tasks, such as biopsy decisions, and performed comparably to human readers in PI-RADS scoring and the detection of extraprostatic extension. However, AI models trained on conventional data might be less accurate with DLR images. The heterogeneity in image quality metrics among the studies prevented quantitative synthesis. Discussion: DLR has the potential to achieve substantial time savings in prostate MRI while maintaining image quality, which is especially relevant because of increased MRI demands. Future research should address the effect of DLR on clinically relevant downstream tasks, including AI algorithms’ performances and biopsy decisions, and explore task-specific accelerated protocols for screening, image-guided biopsy, and treatment. Full article

Human West Nile virus (WNV) infection is usually asymptomatic. Less than 1% of patients develop neuroinvasive disease (WNND) which may result in permanent neurological impairment. The aim of this study was to assess the functional and cognitive status of patients with WNND approximately one year after the onset of symptoms. This prospective observational cohort study involved patients with WNND. Patients’ functional and cognitive abilities one year post-infection were assessed by telephone interviews using the Modified Rankin Scale (mRS), Barthel Index, and Telephone Interview for Cognitive Status. Sixty-two participants were analyzed. All patients had encephalitis, and 7 (11.3%) also had acute flaccid paresis/paralysis (AFP). At discharge, 40 (64.5%) patients had no or minimal neurological deficit (mRS 0–1), and 14 (22.6%) were functionally dependent (mRS 3–5). One year later, 52 (83.9%) patients were functionally independent (mRS 0–2), none was severely dependent (Barthel index 0–60), and 50 (90.9%) had a Barthel index score of 91–100. Among 14 functionally dependent patients at discharge, 3 (21.4%) remained functionally dependent one year later. During the follow-up, 7 (11.3%) patients died. No significant difference was observed in the fatality rate between patients with and without AFP, mRS 3–5 at discharge, or age over 65. The most common persistent symptoms were muscle weakness, walking instability, and issues with focus and memory. Using TICS, it was found that 33/55 patients (60%) had unimpaired and 2 (3.6%) had moderately or severely impaired cognitive status. The long-term prognosis after WNV encephalitis is satisfying. The majority of patients reached functional independence and 60% had unimpaired cognitive status. Full article

Intramedullary nailing (IMN) is the gold standard for fixing mid-shaft fractures of long bones, but distal locking remains a challenging procedure. This study aims to develop and evaluate a novel mixed reality (MR)-based surgical navigation system for distal locking of IMN through phantom experiments. Twelve bone models closely replicating the mechanical properties, anatomy, and density of human tibial bone were utilized. Six orthopedic surgeons participated in the phantom experiments using both MR and traditional electromagnetic (EM) navigation systems. Effectiveness was evaluated using postoperative fluoroscopic imaging and the time taken for distal locking. Compared to the EM navigation system, the MR system significantly reduced distal locking time (81.54 ± 6.06 vs. 132.67 ± 6.45 s per screw) and achieved a higher success rate (23/24 vs. 21/24 screws accurately placed), but the difference in terms of success rate is not statistically significant. The MR-based navigation system for distal locking of IMN is time-efficient, accurate, and shows high potential for enhancing surgical precision in orthopedic procedures. Full article

In this article, I investigate the ontological status of the minor working-class character Mrs. McNab, the cleaner in “Time Passes", the middle section of Virginia Woolf’s tripartite novel To the Lighthouse. Woolf regarded this section as the connecting block between the two outer blocks, “The Window” and “The Lighthouse”, in which she aimed to depict an empty house, devoid of human presence, and to highlight the passage of time. This section has often been analysed by literary-stylistic criticism as if written from a non-anthropocentric worldview. However, the presence of a lower-class cleaner and the absence of the upper middle-class characters who predominate in the other two blocks has also raised much debate in the literary arena. Literary critics agree that this character is given a narrative voice, but how this voice functions, and whether this character is granted narrative agency in terms of the class issues and social relations in the period of transition between Victorian England and the early twentieth-century, is an issue which still remains open. Drawing upon cognitive stylistics, I suggest reading this character both as a category-based and person-based character, and as a narrative device. First, I carry out the analysis of the repetitive she-clusters and their semantic prosodies; then, through samples of the section “Time Passes", I analyse how viewpoint blending between narrator/author and character concur to grant narrative agency to Mrs. McNab and to what extent such agency may be limited by our perception of her through the social schemata of a servant, or whether such a perception may undergo a process of schema refreshment. Last, I suggest that this character may also be viewed as a narrative agent by means of which the reader can activate mental processes of TIME and SPACE blending between the three different blocks of the novel. This blending process allows for the completion of the narrative design of the novel: the journey to the lighthouse. Full article