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Marine Microplastics (MPs) exhibit a wide range of properties due to their variable origins and the weathering processes to which they are exposed. MP’s versatile properties are connected to their dispersal, accumulation, and deposition in the marine environment. MP transport and dispersion are often explained by analogy with sediments. For natural sediments, one of the key features linked to transport and marine morphology is particle size. There is, however, no size classification defined for MP particles and MPs constitute all plastic particles sized smaller than the threshold of 5 mm. In this study, based on existing knowledge in hydrodynamics and natural sediment transport, the impact of MP size on turbulent entrainment, particle settling, and resuspension is described. Moreover, by analyzing several quantitative studies that have provided size distribution, size-selective accumulation of MPs in various regions of the marine environment is reported on. The preferential presence of MPs based on their size in different marine compartments is discussed based on the governing hydrodynamic parameters. Furthermore, the linkage between polymer properties and MP shape and size is explored. Despite the evident connection between hydrodynamic transport and MP size presented, classification of MP size presents challenges. MP size, shape, and density appear simultaneously in the definition of many hydrodynamic parameters described in this study. Unlike mineral sediments that possess a narrow range of density and shape, plastics are manufactured in a wide variety of densities and marine MPs are versatile in shape. Classification for MP size should incorporate particle variability in terms of polymer density and shape.

Comprehending speech with the existence of background noise is of great importance for human life. In the past decades, a large number of psychological, cognitive and neuroscientific research has explored the neurocognitive mechanisms of speech-in-noise comprehension. However, as limited by the low ecological validity of the speech stimuli and the experimental paradigm, as well as the inadequate attention on the high-order linguistic and extralinguistic processes, there remains much unknown about how the brain processes noisy speech in real-life scenarios. A recently emerging approach, i.e., the second-person neuroscience approach, provides a novel conceptual framework. It measures both of the speaker’s and the listener’s neural activities, and estimates the speaker-listener neural coupling with regarding of the speaker’s production-related neural activity as a standardized reference. The second-person approach not only promotes the use of naturalistic speech but also allows for free communication between speaker and listener as in a close-to-life context. In this review, we first briefly review the previous discoveries about how the brain processes speech in noise; then, we introduce the principles and advantages of the second-person neuroscience approach and discuss its implications to unravel the linguistic and extralinguistic processes during speech-in-noise comprehension; finally, we conclude by proposing some critical issues and calls for more research interests in the second-person approach, which would further extend the present knowledge about how people comprehend speech in noise.

Sepsis is a severe systemic infection that can result in organ dysfunction and mortality. Dyslipidemia emerges as a key player in the intricate web of sepsis pathogenesis. Yet, the causal relationship between blood lipid profiles and sepsis risk remains uncertain. This study aims to investigate the association between genetically predicted lipid traits, drug targets, and sepsis. The UK Biobank's Genome-wide association studies (GWAS) produced data on lipid and apolipoprotein characteristics. Four independent GWAS datasets were used to generate the sepsis statistics. The study utilized the two-sample Mendelian randomization (MR) approach, which incorporates multivariable (MVMR) models, to assess the correlations between sepsis risk and lipid-related parameters. To gain further insight, expression quantitative trait loci (eQTL) data were used to investigate the significant drug targets for lipid-lowering. Increasing ApoA-1 levels was associated with a diminished risk of sepsis (under 75) (OR 0.927, 95% CI 0.861-0.999; p = 0.047). This inverse correlation persevered even after performing multivariable MR. Elevated levels of HDL-C were associated with a decreased risk of sepsis (under 75) (OR 0.897, 95% CI 0.838-0.960; P = 0.002) and incidence of sepsis (OR 0.883, 95% CI 0.820-0.951; P = 0.001), which was consistent across sensitivity analyses. Furthermore, a decrease in total cholesterol exhibited a causal effect on sepsis in multivariable MR (OR 0.779, 95% CI 0.642-0.944; P = 0.01). The genetic variants related to lowering LDL-C, located near the HMGCR and LDLR genes, were predicted to elevate the risk of sepsis. Moreover, genetic mimicry near the ANGPTL3 and LPL gene suggested that reducing the activity of ANGPTL3 and LPL (mimicking antisense anti-ANGPTL3 and LPL agents) was forecasted to decrease sepsis risk. Genetically inferred elevated ApoA-1, total cholesterol, and HDL-C manifest a protective effect against sepsis. Within the 9 lipid-lowering drug targets investigated ANGPTL3 and LPL exhibit potential as candidate drug targets for sepsis.

Despite a growing body of literature on school engagement and burnout, little is known about how these constructs jointly vary in response to socioemotional skills and phone dependency. This study examined how socioemotional skills and phone dependency predict engagement-burnout profiles among primary school students (N = 615; 47% female; M age  = 9.69, SD age  = 0.79). The dimensions of school engagement and burnout were examined as indicators of the latent profiles. The OECD socioemotional skills framework (curiosity, grit, social engagement, belongingness, and academic buoyancy) and phone dependency were examined as predictors of profile membership. Latent profile analysis identified three distinct profiles: (1) a moderately burned-out group (36.1%); (2) a highly burned-out and moderately engaged group (10.9%); and (3) a highly engaged group (53%). Follow-up logistic regression analysis revealed that students who reported a higher level of social engagement, buoyancy, and grit were more likely to be engaged than those who were burned out. In contrast, students who felt lonely and curious were more likely to experience burnout. Moreover, those who reported higher levels of phone dependency and left-behind status were more likely to have burnout symptoms. These findings highlight the role of socioemotional skills and phone dependency in understanding student engagement and burnout, with implications for school interventions.

Advances in opto-electronics are often led by discovery and development of materials featuring unique properties. Recently, the material class of transparent conductive oxides (TCO) has attracted attention for active photonic devices on-chip. In particular, indium tin oxide (ITO) is found to have refractive index changes on the order of unity. This property makes it possible to achieve electrooptic modulation of sub-wavelength device scales, when thin ITO films are interfaced with optical light confinement techniques such as found in plasmonics; optical modes are compressed to nanometer scale to create strong light-matter interactions. Here we review efforts towards utilizing this novel material for high performance and ultra-compact modulation. While high performance metrics are achieved experimentally, there are open questions pertaining to the permittivity modulation mechanism of ITO. Finally, we review a variety of optical and electrical properties of ITO for different processing conditions, and show that ITO-based plasmonic electro-optic modulators have the potential to significantly outperform diffractionlimited devices.

Background Osteoporosis represents a salient metabolic bone disorder. Histone demethylase plays a vital role in bone development and homeostasis. This study explored the mechanism of histone demethylase KDM5A affecting osteoporotic fracture healing via the miR-495/SKP2/Runx2 axis. Methods The murine model of osteoporotic fracture was established. The bone mineral density, maximum elastic stress, and maximum load were tested. The relative trabecular bone volume, bone trabecular thickness, and trabecular number at the proximal end of tibia were detected. The histopathological changes of femur tissues and bone microstructure were observed. Expressions of KDM5A and osteogenic factors were detected. The cell proliferation, alkaline phosphatase activity, and calcified nodules were measured. The binding relationships between KDM5A and miR-495 promoter, and miR-495 and SKP2 were verified. The interaction between SKP2 and Runx2 was detected. The ubiquitination level of Runx2 and the stability of Runx2 protein were detected. Results KDM5A was highly expressed in the murine model of osteoporotic fracture. Interference of KDM5A expression facilitated fracture healing in osteoporotic mice. KDM5A downregulated miR-495 expression by promoting the H3K4me3 methylation of the miR-495 promoter. Inhibition of miR-495 reversed the effect of KDM5A silencing on osteoblast proliferation, differentiation, and mineralization. miR-495 facilitated osteoblast proliferation, differentiation, and mineralization by targeting SKP2. SKP2 suppressed Runx2 expression through ubiquitination degradation. Inhibition of Runx2 reversed the promoting effect of SKP2 silencing on osteogenic differentiation. Conclusion KDM5A attenuated the inhibition of miR-495 on SKP2 and promoted the ubiquitination degradation of Runx2 protein by SKP2, thereby repressing osteoblast differentiation and retarding osteoporotic fracture healing.

In order to investigate the causes of swine diarrhea in Yunnan Province, this study was conducted to detect and monitor diarrhea viruses through regular sampling and reverse transcription polymerase chain reaction (RT-PCR). In October 2023, porcine sapelovirus (PSV) was detected in fecal specimens collected from diarrheal pigs in Honghe City, and three strains of PSV were successfully isolated by inoculating them into PK-15 cells; electron microscopy revealed virus particles with diameters of ~32 nm. Next-generation sequencing (NGS) revealed that the PSV isolate genomes ranged from 7480 to 7515 nucleotides in length. Homology analyses indicated that ML-15 and ML-16 showed the highest nucleotide and amino acid identities with the Asian PSV strains, ML-19 showed the highest sequence identities with the Zambia PSV strains, and the VP1 to VP4 genes of the three PSV isolates were in the hypervariable region. Phylogenetic analyses showed that the three PSVs isolated in this study all clustered together with Chinese PSV strains; furthermore, recombination analyses indicated that PSV-ML-19 might be a recombined strain and may have emerged through genetic recombination between the major putative parent strain PSV-21-V and the minor putative parent GER L00798-K11 14-02. This was the first reported instance of the isolation and phylogenetic analyses of the PSV strains in Yunnan Province, which enriched the understanding of Chinese PSV strains and indicated the need to prevent and control PSV; the mutation of the VP1 and 3D genes may also provide an important reference for the development of PSV vaccines.

To better understand the psychological and physiological basis of human emotion, increasing interest has been drawn towards ambulatory recordings of emotion-related data beyond the laboratories. By employing smartphones-based ambulatory assessment and wrist-worn physiological recording devices, the Daily Ambulatory Psychological and Physiological recording for Emotion Research (DAPPER) dataset provides momentary self-reports and physiological data of people’s emotional experiences in their daily life. The dataset consists of ambulatory psychological recordings from 142 participants and physiological recordings from 88 of them over five days. Both the experience sampling method (ESM) and the day reconstruction method (DRM) were employed to have a comprehensive description of the participants’ daily emotional experiences. Heart rate, galvanic skin response, and three-axis acceleration were recorded during the day time. By including multiple types of physiological and self-report data at a scale of five days with 100+ participants, the present dataset is expected to promote emotion researches in real-life, daily settings. Measurement(s) Heart Rate • Galvanic Skin Response • Emotion Technology Type(s) photoplethysmography • Surface Electrode • Day Reconstruction Method • Experience Sampling Method Sample Characteristic - Organism Homo sapiens Machine-accessible metadata file describing the reported data: https://doi.org/10.6084/m9.figshare.13803185

Ocean vertical velocity (w) plays a key role in regulating the exchanges of mass, heat and nutrients between the surface and deep ocean. However, direct observation remains difficult due to its small magnitude and large spatiotemporal variability. Therefore, w fields are generally diagnosed using dynamic‐based methods. In this study, we developed a deep neural network (DNN) to reconstruct three‐dimensional fields of ocean vertical velocity based on sea surface height (SSH) fields. Compared to dynamic‐based methods, the DNN shows improved performance in the w reconstruction within upper 500 m in terms of higher correlation and less error. Remarkably, the DNN requires only a ∼45 × 45 km size SSH image as input to estimate w at the center. This suggests that the DNN has great potential for w reconstruction in the future combined with high‐resolution observations such as the Surface Water and Ocean Topography mission. Plain Language Summary Direct measurement of ocean vertical motion is challenging because it is too weak and unstable. However, understanding this vertical motion is important to study the heat/material transports in the oceans and even climate variability. Here, we propose a deep learning‐based method that uses only the sea surface height (SSH) fields to reconstruct ocean vertical velocity. Our results indicate that this new reconstruction method outperforms the conventional method, particularly in the upper ocean. Moreover, the less data input makes it possible to be an effective tool for reconstructing oceanic vertical velocity with high‐resolution SSH observations in the future. This demonstrates the promise of using deep learning to estimate hard‐to‐measure ocean features, improving our knowledge of ocean processes related to climate. Key Points A deep learning (DL) based approach is developed to reconstruct the ocean vertical velocity Using the modeled sea surface height (SSH) as input, the DL approach outperforms the dynamic‐based method The DL approach has the potential to improve the retrieval of real‐time vertical velocity field along the SWOT swaths

Reports of hospitalization associated with Diamond Shruumz-branded mushroom-containing products in October 2024 led to a manufacturer's recall that restricted the sale, distribution, and accessibility of this new and emerging psychoactive product. This study seeks to assess the continuing online availability of a mushroom-containing edible product in a diverse e-commerce landscape, specifically aiming to identify and characterize its online availability before and after recall initiation. A retrospective online market surveillance of Diamond Shruumz products using structured and automated search queries was employed to identify online product marketing and availability. Online surveillance included the monitoring of multiple social media platforms, cannabis e-commerce websites, and search engine queries between June 22 and June 27, 2024, immediately preceding the manufacturer-initiated recall. Post-recall simulated purchases were then conducted on July 12, 2024, on platforms, websites and domains identified as continuing to actively market and sell the products through online product listings. Prior to product recall, a total of 4117 product listings across 1600 (38.86%) social media posts and user-generated comments, 11 (0.27%) cannabis e-commerce websites, and 2509 (60.94%) hyperlinks from internet search queries were generated for further content analysis. Review of online sources revealed 49 social media posts, 8 e-commerce shops, and 67 domains that were identified as actively marketing and selling products prior to recall. Post-recall, we identified 45 (67.16%) remaining domains that continued to market the product from these different online sources. Simulated purchases revealed that 15 (33.33%) domains successfully transacted test purchases and 30 (66.66%) transactions failed because of account verification or payment failure. The Diamond Shruumz recall exemplifies the ongoing challenge of unknown consumer harm associated with new and emerging substances marketed and sold on the internet, which is especially concerning as these products appeal to younger audiences with a variety of edible flavored products. While a recall was initiated and products became unavailable, our study found that post-recall online vendors continued to market and sell the products. This indicates that there are ongoing challenges to effectuate recalls and online enforcement in a diverse e-commerce landscape that can rapidly bring new and novel psychoactive substances to the market.