Sorption of representative organic contaminants on microplastics: Effects of chemical physicochemical properties, particle size, and biofilm presence

Microplastic pollution has attracted mounting concerns worldwide. Microplastics may concentrate organic and metallic contaminants; thus, affecting their transport, fate and organismal exposure. To better understand organic contaminant-microplastic interactions, our study explored the sorption of selected polychlorinated biphenyls (PCBs), polybrominated diphenyl ethers (PBDEs), α-hexabromocyclododecane (α-HBCDD), and organophosphate flame retardants (OPFRs) on high-density polyethylene (HDPE) and polyvinylchloride (PVC) microplastics under saline conditions. Sorption isotherms determined varied between chemicals and between HDPE and PVC microplastics. Log Freundlich sorption coefficients (Log KF) for the targeted chemicals ranged from 2.01 to 5.27 L kg-1 for HDPE, but were significantly lower for PVC, i.e., ranging from Log KF data (2.84 – 8.58 L kg-1). Significant correlations between chemicals’ Log KF and Log Kow (octanol-water partition coefficient) indicate that chemical-dependent sorption was largely influenced by their hydrophobicity. Sorption was evaluated using three size classes (\u3c 53, 53 – 300, and 300 – 1000 µm) of lab-fragmented microplastics. Particle size did not significantly affect sorption isotherms, but influenced the time to reach equilibrium and the predicted maximum sorption, likely related to microplastic surface areas. The presence of biofilms on HDPE particles significantly enhanced contaminant sorption capacity, indicating more complex sorption dynamics in the chemical-biofilm-microplastic system. Our findings offer new insights into the chemical-microplastic interactions in marine environment

SAMScore: A Semantic Structural Similarity Metric for Image Translation Evaluation

Image translation has wide applications, such as style transfer and modality conversion, usually aiming to generate images having both high degrees of realism and faithfulness. These problems remain difficult, especially when it is important to preserve semantic structures. Traditional image-level similarity metrics are of limited use, since the semantics of an image are high-level, and not strongly governed by pixel-wise faithfulness to an original image. Towards filling this gap, we introduce SAMScore, a generic semantic structural similarity metric for evaluating the faithfulness of image translation models. SAMScore is based on the recent high-performance Segment Anything Model (SAM), which can perform semantic similarity comparisons with standout accuracy. We applied SAMScore on 19 image translation tasks, and found that it is able to outperform all other competitive metrics on all of the tasks. We envision that SAMScore will prove to be a valuable tool that will help to drive the vibrant field of image translation, by allowing for more precise evaluations of new and evolving translation models. The code is available at https://github.com/Kent0n-Li/SAMScore

Does religion matter to informal finance? Evidence from trade credit in China

<p>Informal finance plays an important role in transitional economies with weak legal institutions, such as China. As a major informal finance instrument, trade credit relies on informal institutions and enforcement. The paper argues that religion enhances the ethical climate in which firms do business, and it predicts that religiosity increases trade credit, in that religion enhances enforcement by increasing non-pecuniary cost and reducing risk-taking. The results based on Chinese non-state listed firms between 2003 and 2013 confirm the prediction that firms located in high-religiosity regions are associated with more trade credit, especially in regions where formal institutions are weak or formal financing channels are limited. Furthermore, the paper shows that religiosity reduces overdue trade credit. Finally, the results are driven by Buddhism, Taoism and Christianity, but not Islam.</p

Point Absorber Limits to Future Gravitational-Wave Detectors

High-quality optical resonant cavities require low optical loss, typically on the scale of parts per million. However, unintended micron-scale contaminants on the resonator mirrors that absorb the light circulating in the cavity can deform the surface thermoelastically, and thus increase losses by scattering light out of the resonant mode. The point absorber effect is a limiting factor in some highpower cavity experiments, for example, the Advanced LIGO gravitational wave detector. In this Letter, we present a general approach to the point absorber effect from first principles and simulate its contribution to the increased scattering. The achievable circulating power in current and future gravitational-wave detectors is calculated statistically given different point absorber configurations. Our formulation is further confirmed experimentally in comparison with the scattered power in the arm cavity of Advanced LIGO measured by in-situ photodiodes. The understanding presented here provides an important tool in the global effort to design future gravitational wave detectors that support high optical power, and thus reduce quantum noise

One- vs two-phase extraction:re-evaluation of sample preparation procedures for untargeted lipidomics in plasma samples

Lipidomics is a rapidly developing field in modern biomedical research. While LC-MS systems are able to detect most of the known lipid classes in a biological matrix, there is no single technique able to extract all of them simultaneously. In comparison with two-phase extractions, one-phase extraction systems are of particular interest, since they decrease the complexity of the experimental procedure. By using an untargeted lipidomics approach, we explored the differences/similarities between the most commonly used two-phase extraction systems (Folch, Bligh and Dyer, and MTBE) and one of the more recently introduced one-phase extraction systems for lipid analysis based on the MMC solvent mixture (MeOH/MTBE/CHCl3). The four extraction methods were evaluated and thoroughly compared against a pooled extract that qualitatively and quantitatively represents the average of the combined extractions. Our results show that the lipid profile obtained with the MMC system displayed the highest similarity to the pooled extract, indicating that it was most representative of the lipidome in the original sample. Furthermore, it showed better extraction efficiencies for moderate and highly apolar lipid species in comparison with the Folch, Bligh and Dyer, and MTBE extraction systems. Finally, the technical simplicity of the MMC procedure makes this solvent system highly suitable for automated, untargeted lipidomics analysis

Multiple local symmetries result in a common average polar axis in high strain BiFeO3 based ceramics

For the first time, the origin of large electrostrain in pseudocubic BiFeO3-based ceramics is verified with direct structural evidence backed by appropriate simulations. We employ advanced structural and microstructural characterisations of BiFeO3 based ceramics that exhibit large electrostrain (>0.4%) to reveal the existence of multiple, nanoscale local symmetries, dominantly tetragonal/orthorhombic, which have a common, averaged direction of polarisation over larger, meso/micro-scale regions. Phase-field simulations confirm the existence of local nanoscale symmetries, thereby providing a new vision for designing high-performance lead-free ceramics for high strain actuators

Impact of Protein Stability, Cellular Localization, and Abundance on Proteomic Detection of Tumor-Derived Proteins in Plasma

Tumor-derived, circulating proteins are potentially useful as biomarkers for detection of cancer, for monitoring of disease progression, regression and recurrence, and for assessment of therapeutic response. Here we interrogated how a protein's stability, cellular localization, and abundance affect its observability in blood by mass-spectrometry-based proteomics techniques. We performed proteomic profiling on tumors and plasma from two different xenograft mouse models. A statistical analysis of this data revealed protein properties indicative of the detection level in plasma. Though 20% of the proteins identified in plasma were tumor-derived, only 5% of the proteins observed in the tumor tissue were found in plasma. Both intracellular and extracellular tumor proteins were observed in plasma; however, after normalizing for tumor abundance, extracellular proteins were seven times more likely to be detected. Although proteins that were more abundant in the tumor were also more likely to be observed in plasma, the relationship was nonlinear: Doubling the spectral count increased detection rate by only 50%. Many secreted proteins, even those with relatively low spectral count, were observed in plasma, but few low abundance intracellular proteins were observed. Proteins predicted to be stable by dipeptide composition were significantly more likely to be identified in plasma than less stable proteins. The number of tryptic peptides in a protein was not significantly related to the chance of a protein being observed in plasma. Quantitative comparison of large versus small tumors revealed that the abundance of proteins in plasma as measured by spectral count was associated with the tumor size, but the relationship was not one-to-one; a 3-fold decrease in tumor size resulted in a 16-fold decrease in protein abundance in plasma. This study provides quantitative support for a tumor-derived marker prioritization strategy that favors secreted and stable proteins over all but the most abundant intracellular proteins

Single-cell multi-omics reveals dyssynchrony of the innate and adaptive immune system in progressive COVID-19.

Dysregulated immune responses against the SARS-CoV-2 virus are instrumental in severe COVID-19. However, the immune signatures associated with immunopathology are poorly understood. Here we use multi-omics single-cell analysis to probe the dynamic immune responses in hospitalized patients with stable or progressive course of COVID-19, explore V(D)J repertoires, and assess the cellular effects of tocilizumab. Coordinated profiling of gene expression and cell lineage protein markers shows that S100