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Discover research articles across all indexed journals
Integrating machine learning and geomorphic indices to assess tectonic geomorphology in the Karoun River Basin, Zagros, SW Iran
Visual motion perception and driving hazard visibility at night-time
Enabling whole genome sequencing analysis from FFPE specimens in clinical oncology
Enhanced interhemispheric functional connectivity in patients with functional anorectal pain
Abstract Functional anorectal pain (FAP) is a chronic condition with unclear pathophysiological mechanisms that is often linked to psychological distress. This resting-state functional magnetic resonance imaging (rs-fMRI) study investigated aberrant interhemispheric connections in 30 FAP patients versus 21 matched healthy controls (HC) via seed-based functional connectivity (FC) and voxel-mirrored homotopic connectivity (VMHC). Compared with HC, FAP patients presented enhanced FC between the left middle frontal gyrus (MFG.L) and regions such as the right MFG (MFG.R) and left superior temporal gyrus (STG.L). VMHC analysis revealed increased patterns in the MFG.L and left superior medial frontal gyrus (SFGmed.L) in FAP patients. Moreover, the strength of FC between the MFG.L and MFG.R was negatively correlated with age, indicating that this heightened connection may diminish with age. These findings indicate that FAP involves aberrant interhemispheric hyperconnectivity, which may play crucial roles in pain perception and emotional processing. The age-dependent decline in FC highlights the eroding of neuroplasticity in aging patients. These neural alterations could serve as diagnostic biomarkers and provide targets for therapeutic interventions. Our work positions FAP within a brain-gut axis dysregulation framework and suggests circuit-specific therapeutics to restore neural homeostasis.
Deep spatio-temporal graph convolutional network for police combat action recognition and training assessment
Abstract Traditional police combat training relies heavily on subjective evaluation by human instructors, which lacks consistency and comprehensive coverage of complex movement patterns in real-world scenarios. This paper presents an enhanced deep spatio-temporal graph convolutional network (ST-GCN) framework specifically designed for automated police combat action recognition and quality assessment. The proposed method incorporates adaptive graph topology learning mechanisms that dynamically adjust spatial connectivity patterns based on action-specific joint relationships, multi-modal fusion strategies combining skeletal and RGB video data for robust recognition under diverse environmental conditions, and comprehensive quality assessment algorithms providing objective evaluation of technique execution. The enhanced ST-GCN architecture features attention-guided feature extraction, curriculum learning-based training strategies, and real-time processing capabilities suitable for practical deployment in training facilities. Experimental validation on a comprehensive police combat dataset demonstrates superior performance with 96.7% recognition accuracy across twelve action categories and real-time processing at 42.8 frames per second. The multi-dimensional evaluation framework successfully assesses action completion, standardization compliance, and movement fluency, providing immediate feedback for skill development. The proposed system offers significant improvements over conventional approaches, enabling standardized evaluation criteria, data-driven curriculum development, and enhanced training effectiveness for law enforcement personnel.
A non-monotonic code for event probability in the human brain
Abstract Assessing probabilities and predicting future events are fundamental for perception and adaptive behavior, yet the neural representations of probability remain elusive. While previous studies have shown that neural activity in several brain regions correlates with probability-related factors such as surprise and uncertainty, similar correlations have not been found for probability. Here, using 7 Tesla functional magnetic resonance imaging, we uncover a representation of the probability of the next event in a sequence within the human dorsolateral prefrontal and intraparietal cortices. Crucially, univariate and multivariate analyses revealed that this representation employs a highly non-monotonic code. Tuning curves for probability exhibit selectivity to various probability ranges, while the code for confidence accompanying these estimates is predominantly monotonic. Given such diversity in tuning curves, future studies should move from assuming monotonic or simple canonical forms of tuning curves to considering richer representations, and clarify why different types of code exist.
Tetrapeptide from microbial coculture exhibiting a unique algicidal mechanism against Alexandrium fundyense
Artificial intelligence-generated sustainable gift box design evaluation via reinforcement learning-driven hybrid molecular fuzzy modelling
An essential adaptor for apicoplast fission and inheritance in malaria parasites
Identifying priority zones for carbon management in the Central Yunnan agglomeration
Feature centric based deep learning approach for music mood recognition with HuBERT transformer model
Human plasma proteomic profile of clonal hematopoiesis
Residual modality alleviation and shape guided consistency learning for cross modality identification under complete modality missing
Fulfilment of the promises of 5G according to business and industry stakeholders in Europe and the United Kingdom
Abstract For businesses there is now the opportunity to incorporate fifth generation cellular technology (5G) into working practices to, for example, deliver contextual information in real time by ultra short latency and connect large numbers of devices, alongside artificial intelligence applications. The aim of this study was to gain insights into the development, implementation and the use of 5G in Europe, and to obtain an overview of developments associated specifically for occupational settings. We interviewed 14 experts from business, industry and (inter)national stakeholder organisations from the UK, Belgium, Spain, Poland and Switzerland between March and September 2023 using a semi-structured topic guide. Interviews were then transcribed, coded and analysed. Participants had mixed opinions about 5G as “ it will not be the solution to the problems that we thought ”, but “ 5G is still developing ”. The introduction of 5G in workplaces was viewed as “pretty small” and in several countries “hasn’t been very well taken up” . Occupational settings where 5G had been initially incorporated included farming, manufacturing, airports, and university campuses. Introduction was also influenced by government-funded schemes to pilot 5G within businesses. Participants felt 5G could lead to a “natural evolution in factories” . However, this would require continuing investment in user equipment and resources, as “all equipment would need to be able to connect to the 5G network” . Experiences varied, but participants acknowledged that COVID-19 had had an impact on public perception, with misinformation being a prominent factor. Employment of 5G in industrial settings in Europe has been behind expectations, and to date mostly limited to test sites. Although work began in 2015, 5G deployment is continuing across Europe. Further research is needed to understand how businesses can effectively implement 5G.
Interstellar ices as carriers of supernova material to the early solar system
Abstract Planetary materials show systematic variations in their nucleosynthetic isotope compositions that resonate with orbital distance. The origin of this pattern remains debated, limiting how these isotopic signatures can be used to trace the precursors of terrestrial planets. Here we test the hypothesis that interstellar ices carried supernova-produced nuclides by searching for a supernova nucleosynthetic fingerprint in aqueous alteration minerals from carbonaceous and non-carbonaceous chondrite meteorites. We focus on zirconium, a refractory element that includes the neutron-rich isotope 96 Zr formed in core-collapse supernovae. Leaching experiments reveal extreme 96 Zr enrichments in alteration minerals, showing that they incorporated supernova material hosted in interstellar ices. We show that the Solar System’s zirconium isotope variability reflects mixing between these ices and an ice-free rocky component. Finally, the presence of supernova nuclides in a volatile carrier supports models where the Solar System’s nucleosynthetic variability was imparted by thermal processing of material in the protoplanetary disk and during planetary accretion.
Chemically tuned radiolabeling and membrane affinity in Drug-Functionalized carbon nanotube nanocarriers
New insights on Ötzi’s injuries from a clinical perspective
Efficient and accurate search in petabase-scale sequence repositories
Abstract The amount of biological sequencing data available in public repositories is growing rapidly, forming a critical resource for biomedicine. However, making these data efficiently and accurately full-text searchable remains challenging. Here we build on efficient data structures and algorithms for representing large sequence sets 1–6 . We present MetaGraph, a methodological framework that enables us to scalably index large sets of DNA, RNA or protein sequences using annotated de Bruijn graphs. Integrating data from seven public sources 7–13 , we make 18.8 million unique DNA and RNA sequence sets and 210 billion amino acid residues across all clades of life—including viruses, bacteria, fungi, plants, animals and humans—full-text searchable. We demonstrate the feasibility of a cost-effective full-text search in large sequence repositories (67 petabase pairs (Pbp) of raw sequence) at an on-demand cost of around US$100 for small queries up to 1 megabase pairs (Mbp) and down to US$0.74 per queried Mbp for large queries. We show that the highly compressed representation of all public biological sequences could fit on a few consumer hard drives (total cost of around US$2,500), making it cost-effective to use and readily transportable for further analysis. We explore several practical use cases to mine existing archives for interesting associations, demonstrating the use of our indexes for integrative analyses, and illustrating that such capabilities are poised to catalyse advancements in biomedical research.
Localized Wnt-signaling promotes asymmetric NuMA-dependent oriented divisions and unequal apportioning of mitochondria
Abstract In multicellular organisms, the execution of developmental and homeostatic programs often relies on asymmetric cell divisions. These divisions require the alignment of the mitotic spindle axis to cortical polarity cues, and the unequal partitioning of cellular components between progeny cells. Asymmetric divisions are orchestrated by signals from the niche frequently presented in a directional manner, such as Wnt signals. Here we employ bioengineered Wnt-niches to demonstrate that in metaphase NuMA/dynein microtubule motors form a complex with activated LRP6 and β-catenin at the cortical sites of Wnt activation to orient cell division perpendicularly. We show that engagement of LRP6 co-receptors by Wnt ligands locally stabilizes actomyosin contractility through the accumulation of myosin1C. Additionally, we describe a proteomic-based approach to identify mitotic protein complexes enriched at the Wnt-contact site, revealing that mitochondria polarize toward localized Wnt3a sources and are asymmetrically apportioned to the Wnt-proximal daughter cell during Wnt-mediated asymmetric cell division of embryonic stem cells. Mechanistically, we show that CENP-F is required for mitochondria polarization towards localized sites of Wnt3a activation, and that deletion of the Wnt-co-receptor LRP6 impairs the asymmetric apportioning of mitochondria. Our findings enhance the understanding of mitotic Wnt-signaling and elucidate fundamental principles underlying Wnt-dependent mitochondrial polarization.