Actinium‐227 (227Ac) has been used as a powerful tracer of diapycnal mixing in the ocean, assuming that it is conservative and originates mainly from deep‐sea sediments. However, here we show an ...unexpectedly large source (continental margin) and sink (scavenging) of 227Ac in the ocean, based on high‐resolution 227Ac distributions obtained for the first time by mooring Mn‐fibers in the East Sea (Japan Sea). Although we expected a decrease in radium‐228 (228Ra) to 227Ac ratios with depth owing to their different half‐lives, the ratios increased with depth in the upper layer, indicating efficient removal of 227Ac by particle scavenging. In addition, unusually high 227Ac activities (∼15 dpm m−3) were observed in the surface layer, likely due to the horizontal transport of 227Ac‐enriched shelf water. Thus, our results suggest refining our understanding of the geochemical cycle and application of 227Ac in the ocean.
Plain Language Summary
Distributions of 227Ac provide crucial information for the vertical mixing of the deep ocean on timescales of up to 100 years. However, behaviors of 227Ac in the ocean have not been well understood to date because of its extremely low concentration. In this study, we for the first time determined high‐resolution 227Ac profiles by mooring Mn‐fibers in a marginal sea of the northwestern Pacific Ocean. Our results display that the shelf source inputs as well as efficient removal by particle scavenging have been overlooked so far. In particular, we emphasize that the removal of 227Ac by particle scavenging revealed in this study should be considered when using 227Ac as a tracer of mixing rates in the ocean.
Key Points
The high‐resolution measurement of 227Ac with our Mn‐fiber mooring method agrees very well with the onboard Mn‐fiber filtration method
Significantly high 227Ac activities, which might originate from the 227Ac‐enriched shelf water, are observed in the surface layer (0–100 m)
High 227Ac scavenging rates are calculated based on the increasing trend of 228Ra to 227Ac ratio with depth in the upper layer (0–1,000 m)
Drug-phospholipid complexing is a promising formulation technology for improving the low bioavailability of active pharmaceutical ingredients (APIs). However, identifying whether phospholipid and ...candidate drug can form a complex through in vitro tests can be costly and time-consuming due to the physicochemical properties and experimental environment. In a previous study, the authors developed seven machine learning models to predict drug-phospholipid complex formation, and the lightGBM model demonstrated the best performance. However, the previous study was unable to sufficiently address the degradation of test performance caused by the small size of the training data with class imbalance, and it had the limitation of considering only machine learning techniques. To overcome these limitations, we propose a new deep learning-based prediction model that employs variational autoencoder (VAE) and principal component analysis (PCA) techniques to improve prediction performance. The model uses a multi-layer one-dimensional convolutional neural network (CNN) with a skip connection to effectively capture the complex relationship between drugs and lipid molecules. The computer simulation results demonstrate that our proposed model performs better than the previous model in all performance metrics.
Sequential recommender models should capture evolving user preferences over time, but there is a risk of obtaining biased results such as false positives and false negatives due to noisy ...interactions. Generative models effectively learn the underlying distribution and uncertainty of the given data to generate new data, and they exhibit robustness against noise. In particular, utilizing the Diffusion model, which generates data through a multi-step process of adding and removing noise, enables stable and effective recommendations. The Diffusion model typically leverages a Gaussian distribution with a mean fixed at zero, but there is potential for performance improvement in generative models by employing distributions with higher degrees of freedom. Therefore, we propose a Diffusion model-based sequential recommender model that uses a new noise distribution. The proposed model improves performance through a Weibull distribution with two parameters determining shape and scale, a modified Transformer architecture based on Macaron Net, normalized loss, and a learning rate warmup strategy. Experimental results on four types of real-world e-commerce data show that the proposed model achieved performance gains ranging from a minimum of 2.53% to a maximum of 13.52% across HR@K and NDCG@K metrics compared to the existing Diffusion model-based sequential recommender model.
Nonalcoholic fatty liver disease (NAFLD) is one of the most common health problems worldwide. Sleep apnea (SA) causes cardiovascular and metabolic problems, as well as a significant socioeconomic ...burden. Although several studies have found that SA causes NAFLD, there is no evidence that NAFLD causes SA. The goal of this study was to look at the relationship between NAFLD and SA in realworld data. We evaluated 334,334 healthy individuals without comorbidities who underwent National Health checkups in the Republic of Korea from 2009 to 2014. NAFLD was defined by a surrogate marker, the fatty liver index (FLI). The association between FLI and SA was analyzed using multivariate Cox proportional hazards regression models. During a median followup of 5.3 years, 1,351 patients (0.4%) were newly diagnosed with SA. Subjects were categorized into quartile groups according to FLI (range: Q1, 0-4.9; Q2, 5.0-12.5; Q3, 12.6-31.0; Q4, >31.0). Subjects with higher FLIs had a significantly higher cumulative incidence of SA than those with lower FLIs (Q1, 119 0.1%; Q2, 210 0.3%; Q3, 339 0.4%; Q4, 683 0.8%; P < 0.001). Adjusted hazard ratios (HRs) revealed that a higher FLI was independently associated with an increased risk of SA (HR between Q4 and Q1, 4.03; 95% confidence interval, 3.22-5.05; P < 0.001). This association remained statistically significant after further adjustment for Body mass index (BMI) (HR between Q4 and Q1, 2.19; 95% confidence interval, 1.69-2.83; P < 0.001). FLI was significantly associated with an increased risk of new-onset SA regardless of baseline characteristics. This study demonstrated that NAFLD, assessed by FLI, was independently associated with increased risk for SA in the healthy Korean population.
Over 10 years after the Hebei Spirit oil spill (HSOS), the concentrations of pollutants, such as TPH and PAHs, in spilled crude oil have recovered to background levels, but in some areas, the ...environment has not fully recovered. In particular, PAHs were more resistant to degradation, and their persistence could have deleterious impacts on the sediment ecosystem. This study aimed to evaluate the microbial recovery of coastal sediments from the HSOS by analyzing the structure and diversity of the microbial community and its functional contribution to PAHs degradation. High-throughput sequencing on the MiSeq platform was conducted using tidal flat sediments collected in 2014 and 2016 from the area contaminated by the HSOS. The microbial recovery was evaluated by various diversity factors, including microbial composition and structure and functional diversity based on PICRUSt analysis. The abundance of microbial taxa associated with TPH degradation was higher in 2014 than that in 2016, but the taxa associated with PAHs degradation were similar between years. These results are consistent with the dynamics of microbes associated with the fate of pollutants, and they also showed similar tendency in functional profiles. That is, even if the pollutants are completely degraded, the microbial community has not yet completely recovered from the HSOS. The evaluation of microbial ecosystems in contaminated environments should consider both the fate of pollutants and the dynamics of microbial species that make functional contributions to the degradation of pollutants.
Display omitted
•Microbial PAHs-degradation was operating even in fully recovered coastal beach.•Microbial contribution to PAHs-degradation was gradually shifted toward the late stage of the pathway.•Functional diversity of microbial community should be considered to assess ecosystem health.
Performance of models highly depend not only on the used algorithm but also the data set it was applied to. This makes the comparison of newly developed tools to previously published approaches ...difficult. Either researchers need to implement others' algorithms first, to establish an adequate benchmark on their data, or a direct comparison of new and old techniques is infeasible. The Ischemic Stroke Lesion Segmentation (ISLES) challenge, which has ran now consecutively for 3 years, aims to address this problem of comparability. ISLES 2016 and 2017 focused on lesion outcome prediction after ischemic stroke: By providing a uniformly pre-processed data set, researchers from all over the world could apply their algorithm directly. A total of nine teams participated in ISLES 2015, and 15 teams participated in ISLES 2016. Their performance was evaluated in a fair and transparent way to identify the state-of-the-art among all submissions. Top ranked teams almost always employed deep learning tools, which were predominately convolutional neural networks (CNNs). Despite the great efforts, lesion outcome prediction persists challenging. The annotated data set remains publicly available and new approaches can be compared directly via the online evaluation system, serving as a continuing benchmark (www.isles-challenge.org).
Asthma and nonalcoholic fatty liver disease (NAFLD) are chronic diseases known to be associated with metabolic abnormalities. We aimed to clarify the association between NAFLD and asthma incidence in ...a large population-based cohort.
We selected 160,603 individuals without comorbidities from the National Health Insurance Service-National Sample cohort between 2009 and 2014. NAFLD was defined using a surrogate marker, fatty liver index (FLI). During a median of 5.08 years' follow-up, 16,377 subjects (10.2%) were newly diagnosed with asthma and categorized into three groups according to FLI. The cumulative incidence of asthma was higher in subjects with higher vs. lower FLIs (FLI < 30, 10.1%; 30 ≤ FLI < 60, 10.8%; FLI ≥ 60, 10.5%). Higher FLI was associated with an increased incidence of asthma (Hazard ratios (HR)highest vs. lowest FLI, 1.25; 95% CI, 1.15-1.36). The results using another definition of NAFLD, as measured by the hepatic steatosis index (HSI), were similar to the primary results. This association was more pronounced in women than in men (HR 1.46; 95% CI, 1.13-1.64 vs. HR 1.07; 95% CI, 0.94-1.20).
This study demonstrated that NAFLD, as measured by FLI and HSI, may influence the incidence rates of asthma in adults, especially in women.
Glaciers, formed from the gradual accumulation of snow, can be continuous records representing past environments and recognized as a time capsule of our planetary evolution. Due to extremely harsh ...conditions, glacial ice has long been considered an uninhabitable ecosystem for microorganisms to sustain their life. However, recent developments in microbiological analysis techniques revealed the presence of unexpectedly diverse microbial strains. Glacial microorganisms could also provide valuable information, including not only biological diversity and structure but also molecular systematics, metabolic profiles, and evolutionary changes from the past climate and ecosystem. However, there are several obstacles in investigating the glacier environment, such as low regional accessibility, technical difficulties of ice coring, potential contamination during the sampling process, and low microbial biomass. This review aims to summarize recent knowledge on decontamination methods, biomass, diversity based on culture-dependent and -independent methods, application of biological proxies, greenhouse gas production and adaptive strategies in glaciers from various regions and to imply further directions for a comprehensive understanding of habitatility in an icy world including outer of our planet.
Dispersion and biodegradation of petroleum hydrocarbons are significantly enhanced by formation of oil-suspended particulate matter aggregates (OSAs), but little is known about their adverse effects ...on benthic invertebrates or microbes. In this study, we investigated: (1) bioaccumulation of polycyclic aromatic hydrocarbons (PAHs) by the marine bivalve, Mactra veneriformis and (2) changes in composition and relative abundances of microbes, during 50-d of an OSAs feeding experiment. Total concentrations of PAHs increased more rapidly during the first week of exposure, peaked at Day 30, then gradually declined to the end of experiment. While bioaccumulation of PAHs by clams varied among the 20 target compounds, two major groups of PAHs were identified by cluster analysis. One group including 3-methylphenanthrene, 1,6-dimethylphenanthrene, 1,2,6,9-tetramethylphenanthrene, and benzoaanthracene showed a fairly constant rate of accumulation, while the second group including 2-methyldibenzothiophene, 2,4-dimethyldibenzothiophene, 2,4,7-trimethyldibenzothiophene, 3-methylchrysene, 6-ethylchrysene, and 1,3,6-trimethylchrysene exhibited a bell-shaped pattern. Bioaccumulation of PAHs by clams was dependent on changes in abundance of Gammaproteobacteria, indicating active degradations of hydrocarbons by selected species. Six key species included: Porticoccus litoralis, Porticoccus hydrocarbonoclasticus, Cycloclasticus spirillensus, Alcanivorax borkumensis, Alcanivorax dieselolei, and Alkalimarinus sediminis. These results are the first to demonstrate interactions of OSAs and macrofauna/microbe in oil cleanup operations.
Marine fungi are potential producers of bioactive compounds that may have pharmacological and medicinal applications. Fungi were cultured from marine brown algae and identified using multiple target ...genes to confirm phylogenetic placement. These target genes included the internal transcribed spacer (ITS), the nuclear large subunit (LSU), and the β-tubulin region. Various biological activities of marine-derived fungi were evaluated, including their antifungal, antioxidant and cellulolytic enzyme activities. As a result, a total of 50 fungi was isolated from the brown algae Sargassum sp. Among the 50 isolated fungi, Corollospora angusta was the dominant species in this study. The genus Arthrinium showed a relatively strong antifungal activity to all of the target plant pathogenic fungi. In particular, Arthrinium saccharicola KUC21221 showed high radical scavenging activity and the highest activities in terms of filter paper units (0.39 U/mL), endoglucanase activity (0.38 U/mL), and β-glucosidase activity (1.04 U/mL).
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