ABSTRACT
BACKGROUND AND OBJECTIVE: Accurate identification of individuals with subjective cognitive decline (SCD) is crucial for early intervention and prevention of neurodegenerative diseases. Fractal dimensionality (FD) has emerged as a robust and replicable measure, surpassing traditional geometric metrics, in characterizing the intricate fractal geometrical properties of brain structure. Nevertheless, the effectiveness of FD in identifying individuals with SCD remains largely unclear. A 3D regional FD method can be suggested to characterize and quantify the spatial complexity of the precise gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD. METHODS: This study introduces a novel integer ratio based 3D box-counting fractal analysis (IRBCFA) to quantify regional fractal dimensions (FDs) in structural magnetic resonance imaging (MRI) data. The innovative method overcomes limitations of conventional box-counting techniques by accommodating arbitrary box sizes, thereby enhancing the precision of FD estimation in small, yet neurologically significant, brain regions. RESULTS: The application of IRBCFA to two publicly available datasets, OASIS-3 and ADNI, consisting of 520 and 180 subjects, respectively. The method identified discriminative regions of interest (ROIs) predominantly within the limbic system, fronto-parietal region, occipito-temporal region, and basal ganglia-thalamus region. These ROIs exhibited significant correlations with cognitive functions, including executive functioning, memory, social cognition, and sensory perception, suggesting their potential as neuroimaging markers for SCD. The identification model trained on these ROIs demonstrated exceptional performance achieving over 93 % accuracy on the discovery dataset and exceeding 87 % on the independent testing dataset. Furthermore, an exchange experiment between datasets revealed a substantial overlap in discriminative ROIs, highlighting the robustness of our method across diverse populations. CONCLUSION: Our findings indicate that IRBCFA can serve as a valuable tool for quantifying the spatial complexity of gray matter, providing insights into cognitive aging and aiding in the automated identification of individuals with SCD. The demonstrated generalizability and robustness of this method position it as a promising tool for neurodegenerative disease research and offer potential for clinical applications.
Subject(s)
Cognitive Dysfunction , Fractals , Imaging, Three-Dimensional , Magnetic Resonance Imaging , Humans , Cognitive Dysfunction/diagnostic imaging , Magnetic Resonance Imaging/methods , Female , Male , Aged , Imaging, Three-Dimensional/methods , Brain/diagnostic imaging , Middle Aged , Aged, 80 and over , Gray Matter/diagnostic imaging , AlgorithmsABSTRACT
Small nucleolar RNAs (snoRNAs) are short non-coding RNAs that are abundant in the nucleoli of eukaryotic cells and play a crucial role in various aspects of ribosomal RNA (rRNA) maturation, including modifications such as 2'-O-methylation or pseudouridylation. On the other hand, Giardia duodenalis is a microaerophilic, flagellated, binucleate protozoan responsible for causing giardiasis. Although numerous snoRNAs have been detected in Giardia, their investigation remains limited. Nevertheless, they have been found to play a crucial role in the rRNA precursor processing pathway and influence other cellular functions. In addition, it has been proposed that some microRNAs are generated from these snoRNAs through excision by the Giardia endoribonuclease Dicer. These microRNAs are believed to contribute to the regulation of antigenic variation, which allows the parasite to evade the host immune response. Specifically, they play a role in modulating variant-specific surface proteins (VSPs) and other cysteine-rich surface antigens (CSAs). The main objective of this study was to bring together the available data on snoRNAs in Giardia, uncovering their functions in various processes and their importance on a global scale. In addition, the research delved into potential microRNAs speculated to originate from snoRNAs, exploring their impact on cellular processes.
ABSTRACT
To explore the formation mechanism of the ozone ï¼O3ï¼ and emission reduction strategy in a northwestern cityï¼ an extensive field campaign was conducted in summertime in 2021 in Yining Cityï¼ in which the 0-D box model incorporating the latest explicit chemical mechanism ï¼MCMv3.3.1ï¼ was applied for the first time to quantify the O3-NOx-VOCs sensitivity and formulate a precise O3 control strategy in this city. The results showed thatï¼ â the three indicators ï¼»i.e.ï¼ O3 formation potential ï¼OFPï¼ï¼ ·OH reaction rate ï¼k·OHï¼ï¼ and relative incremental reactivity ï¼RIRï¼ï¼½ jointly indicated that alkenesï¼ oxygenated volatile organic compounds ï¼OVOCsï¼ï¼ and aromatics were the highest contributors among anthropogenic volatile organic compounds ï¼AVOCï¼ to O3 formationï¼ and the contribution of biogenic volatile organic compounds ï¼BVOCï¼ also could not be ignored. Additionallyï¼ the results based on RIR calculation implied that that the acetaldehydeï¼ ethyleneï¼ and propylene were the most sensitive individual VOCs species in Yining City. â¡ The in-situ photochemical O3 variations were primarily influenced by the local photochemical production and export process horizontally to downwind areas or vertically to the upper layerï¼ and the reaction pathways of HO2·+ NO and ·OH + NO2 contributed the most to the gross Ox photochemical production ï¼60%ï¼ and photochemical destruction production ï¼53%ï¼ï¼ respectively. Henceï¼ the reduction in local emissions for O3 precursors was more essential to alleviate O3 pollution in this city. ⢠The outcome based on RIRï¼NOxï¼ / RIRï¼AVOCï¼ and EKMA jointly suggested that the photochemical regime in this city can be considered a transitional regime that was also nearly a VOCs-limited regime. Detailed mechanism modeling based on multiple scenarios further suggested that the NOx and VOCs synergic emission reduction strategies was helpful to alleviate O3 pollution. These results are useful to provide policy-related guidance for other cities facing similar O3 pollution in northwest China.
ABSTRACT
As cardiovascular diseases continue to be the leading cause of death worldwide, groundbreaking research is being conducted to mitigate their effects. This review looks into the potential of small nucleolar RNAs (snoRNAs) and the opportunity to use these molecular agents as therapeutic biomarkers for cardiovascular issues specific to the heart. Through an investigation of snoRNA biogenesis, functionality, and roles in cardiovascular diseases, this review relates our past and present knowledge of snoRNAs to the current scientific literature. Considering the initial discovery of snoRNAs and the studies thereafter analyzing the roles of snoRNAs in disease, we look forward to uncovering many other noncanonical functions that could lead researchers closer to finding preventive and curative solutions for cardiovascular diseases.