Cell-type and dynamic state govern genetic regulation of gene expression in heterogeneous differentiating cultures.

Identifying the molecular effects of human genetic variation across cellular contexts is crucial for understanding the mechanisms underlying disease-associated loci, yet many cell-types and developmental stages remain underexplored. Here we harnessed the potential of heterogeneous differentiating cultures ( HDCs ), an in vitro system in which pluripotent cells asynchronously differentiate into a broad spectrum of cell-types. We generated HDCs for 53 human donors and collected single-cell RNA-sequencing data from over 900,000 cells. We identified expression quantitative trait loci in 29 cell-types and characterized regulatory dynamics across diverse differentiation trajectories. This revealed novel regulatory variants for genes involved in key developmental and disease-related processes while replicating known effects from primary tissues, and dynamic regulatory effects associated with a range of complex traits.

Evaluation of aroma characteristics of Penaeus vannamei with different drying methods using HS-SPME-GC-MS, MMSE-GC-MS, and sensory evaluation.

The effects of microwave drying (MD), hot air drying (HAD), vacuum hot air drying (VD), and vacuum freeze drying (VFD) on the volatile profiles of Penaeus vannamei were investigated. A total of 89 and 94 volatile compounds were identified by headspace solid-phase microextraction-gas chromatography-mass spectrometry (HS-SPME-GC-MS) and monolithic material sorptive extraction gas chromatography-mass spectrometry (MMSE-GC-MS), respectively. Orthogonal partial least squares-discriminant analysis (OPLS-DA) and variable influence on projection (VIP) models were utilized to select characteristic volatiles and key marker compounds (e.g., octanal, 1-octen-3-ol, 2-methyl-butanal, 2-ethyl-furan, and trimethyl-pyrazine) to discriminate among four drying methods. Based on synthesis of odor descriptions and sensory evaluation, it was found that P. vannamei via MD, HAD, and VD greatly reduced the fishy and generated roasted, fatty, and smoked odors. This study systematically analyzed the aroma characteristics of four traditional dried P. vannamei products, which may provide theoretical guidance for industrial production.

Nanocatalytic Anti-Tumor Immune Regulation.

Immunotherapy has brought a new dawn for human being to defeat cancer. Although existing immunotherapy regimens (CAR-T, etc.) have made breakthroughs in the treatments of hematological cancer and few solid tumors such as melanoma, the therapeutic efficacy on most solid tumors is still far from being satisfactory. In recent years, the researches on tumor immunotherapy based on nanocatalytic materials are under rapid development, and significant progresses have been made. Nanocatalytic medicine has been demonstrated to be capable of overcoming the limitations of current clinicnal treatments by using toxic chemodrugs, and exhibits highly attractive advantages over traditional therapies, such as the enhanced and sustained therapeutic efficacy based on the durable catalytic activity, remarkably reduced harmful side-effects without using traditional toxic chemodrugs, and so on. Most recently, nanocatalytic medicine has been introduced in the immune-regulation for disease treatments, especially, in the immunoactivation for tumor therapies. This article presents the most recent progresses in immune-response activations by nanocatalytic medicine-initiated chemical reactions for tumor immunotherapy, and elucidates the mechanism of nanocatalytic medicines in regulating anti-tumor immunity. By reviewing the current research progress in the emerging field, this review will further highlight the great potential and broad prospects of nanocatalysis-based anti-tumor immune-therapeutics.

Multitask Image Clustering via Deep Information Bottleneck.

Multitask image clustering approaches intend to improve the model accuracy on each task by exploring the relationships of multiple related image clustering tasks. However, most existing multitask clustering (MTC) approaches isolate the representation abstraction from the downstream clustering procedure, which makes the MTC models unable to perform unified optimization. In addition, the existing MTC relies on exploring the relevant information of multiple related tasks to discover their latent correlations while ignoring the irrelevant information between partially related tasks, which may also degrade the clustering performance. To tackle these issues, a multitask image clustering method named deep multitask information bottleneck (DMTIB) is devised, which aims at conducting multiple related image clustering by maximizing the relevant information of multiple tasks while minimizing the irrelevant information among them. Specifically, DMTIB consists of a main-net and multiple subnets to characterize the relationships across tasks and the correlations hidden in a single clustering task. Then, an information maximin discriminator is devised to maximize the mutual information (MI) measurement of positive samples and minimize the MI of negative ones, in which the positive and negative sample pairs are constructed by a high-confidence pseudo-graph. Finally, a unified loss function is devised for the optimization of task relatedness discovery and MTC simultaneously. Empirical comparisons on several benchmark datasets, NUS-WIDE, Pascal VOC, Caltech-256, CIFAR-100, and COCO, show that our DMTIB approach outperforms more than 20 single-task clustering and MTC approaches.

Transparent Self-Healing Anti-Freezing Ionogel for Monolayered Triboelectric Nanogenerator and Electromagnetic Energy-Based Touch Panel.

The advent of Internet of Things and artificial intelligence era necessitates the advancement of self-powered electronics. However, prevalent multifunctional electronics still face great challenges in rigid electrodes, stacked layers, and external power sources to restrict the development in flexible electronics. Here, a transparent, self-healing, anti-freezing (TSA) ionogel composed of fluorine-rich ionic liquid and fluorocarbon elastomer, which is engineered for monolayered triboelectric nanogenerators (M-TENG) and electromagnetic energy-based touch panels is developed. Notably, the TSA-ionogel exhibits remarkable features including outstanding transparency (90%), anti-freezing robustness (253 K), impressive stretchability (600%), and repetitive self-healing capacity. The resultant M-TENG achieves a significant output power density (200 mW m-2 ) and sustains operational stability beyond 1 year. Leveraging this remarkable performance, the M-TENG is adeptly harnessed for biomechanical energy harvesting, self-powered control interface, electroluminescent devices, and enabling wireless control over electrical appliances. Furthermore, harnessing Faraday's induction law and exploiting human body's intrinsic antenna properties, the TSA-ionogel seamlessly transforms into an autonomous multifunctional epidermal touch panel. This touch panel offers impeccable input capabilities through word inscription and participation in the Chinese game of Go. Consequently, the TSA-ionogel's innovation holds the potential to reshape the trajectory of next-generation electronics and profoundly revolutionize the paradigm of human-machine interaction.

Identification of a 2-phenylthiazole derivative acetylcholinesterase modulator with in vitro antitumor activity in breast cancer cells.

Acetylcholinesterase (AchE) is a serine hydrolase with classical function to degrade acetylcholine and terminate neurotransmission. While "nonclassical" functions of AchE were involved in cell growth, death, invasion, etc. The expression and activity of AchE is changed in tumors, suggesting AChE inhibitors (AchEIs) may serve as potential antitumor drugs. In this study, the antitumor activity of a series of 2-phenylthiazole derivatives originally designed and synthesized as AchEIs were investigated. One compound named A6, was screened out with superior antitumor efficacy, especially against breast cancer MCF-7 cells. A6 significantly disrupted the amino acid metabolism and inhibited migration of MCF-7. In addition, A6 induced apoptosis of MCF-7 cells. To clarify how A6 affected on MCF-7 cells, RNA-seq analysis was conducted to evaluate the whole genome effect of A6 on gene expression. A total of 153 genes were increased, and the expression of 81 genes was decreased. GO and KEGG enrichment analysis showed A6 treatment mainly disrupted sterol/cholesterol pathway, Ras signaling pathway, VEGF signaling pathway, etc. Moreover, bioinformatic analysis and cell viability test showed A6 plays anticancer role by regulating Best1 and HIST1H2BJ. These results indicate that AchEI A6 could be a potential antitumor agent for breast cancer patients and could help the development of novel therapies.

The role of body mass index on the association between the energy-adjusted dietary inflammatory index and hyperuricemia: a mediation analysis based on NHANES (2007-2016).

BACKGROUND: The Energy-Adjusted Dietary Inflammatory Index (E-DII) is related to both body mass index (BMI) and hyperuricemia. However, the association among BMI, hyperuricemia and DII is yet to be fully elucidated. The purpose of this study is to explore the role of BMI in the relationship between E-DII and hyperuricemia in the American population. METHODS: A cross-sectional study was conducted using data from the National Health and Nutrition Examination Survey (NHANES) spanning from 2007 to 2016, with a sample size of 10,571 participants. The study used a weighted logistic regression model and a generalized additive model (GAM) to explore the associations among BMI, hyperuricemia and E-DII. Furthermore, mediation analysis was utilized to illustrate the mediating relationships among these variables. RESULTS: The results of the study indicated that a higher E-DII was related to an increased risk of hyperuricemia. The association between E-DII and hyperuricemia was partially mediated by BMI. CONCLUSIONS: E-DII is associated with hyperuricemia. BMI mediates the relationship between E-DII and hyperuricemia among Americans, which provides crucial information for the prevention of hyperuricemia.

Norbornene Copolymerization with Polar Monomers Catalyzed by Palladium Catalysts Containing Imidazolidin-2-imine/Guanidine Ligands.

The development of a palladium catalyst that has enhanced catalytic performance, such as low aluminum cocatalyst loading, good copolymerization ability, high molecular weight, and excellent solubility of the (co)polymers, is still a challenge in norbornene copolymerizations. Here, a series of PdCl2 and PdMeCl complexes containing differently substituted anilines and imidazolidin-2-imine/guanidine ligands was successfully synthesized and characterized. X-ray diffraction analysis results revealed that these Pd complexes adopted an almost square-planar geometry, and the six-membered chelate ring showed structural distinctions as compared to traditional N^N-based α-diimine and ß-diimine Pd complexes. These Pd complexes were activated by EtAlCl2 and then exhibited moderate activity (104-105 g mol-1 h-1) and good thermal stability (up to 90 °C) for norbornene polymerization to produce high-molecular-weight PNBs (Mn up to 96.4 kg mol-1) with narrow polydispersities (PDI as low as 1.39). These Pd complexes also exhibited good polar group tolerance in the copolymerization of norbornene with methyl 5-norbornene-2-carboxylate and methyl 10-undecenoate, in which the activity was achieved up to 7.04 × 104 g mol-1 h-1. It furnished polar functionalized norbornene-based copolymers with high molecular weight (Mn up to 63.1 kg mol-1), narrow PDI, reasonable polar monomer incorporation, and good solubility. These Pd catalysts exhibited an enhanced copolymerization ability to produce PNB or NB-based copolymers, representing significant progress in this field.

LGNN: a novel linear graph neural network algorithm.

The emergence of deep learning has not only brought great changes in the field of image recognition, but also achieved excellent node classification performance in graph neural networks. However, the existing graph neural network framework often uses methods based on spatial domain or spectral domain to capture network structure features. This process captures the local structural characteristics of graph data, and the convolution process has a large amount of calculation. It is necessary to use multi-channel or deep neural network structure to achieve the goal of modeling the high-order structural characteristics of the network. Therefore, this paper proposes a linear graph neural network framework [Linear Graph Neural Network (LGNN)] with superior performance. The model first preprocesses the input graph, and uses symmetric normalization and feature normalization to remove deviations in the structure and features. Then, by designing a high-order adjacency matrix propagation mechanism, LGNN enables nodes to iteratively aggregate and learn the feature information of high-order neighbors. After obtaining the node representation of the network structure, LGNN uses a simple linear mapping to maintain computational efficiency and obtain the final node representation. The experimental results show that the performance of the LGNN algorithm in some tasks is slightly worse than that of the existing mainstream graph neural network algorithms, but it shows or exceeds the machine learning performance of the existing algorithms in most graph neural network performance evaluation tasks, especially on sparse networks.

MdNup62 involved in salt and osmotic stress tolerance in apple.

Abiotic stress of plants has serious consequences on the development of the apple industry. Nuclear pore complexes (NPCs) control nucleoplasmic transport and play an important role in the regulation of plant abiotic stress response. However, the effects of NPCs on apple salt and osmotic stress responses have not been reported yet. In this study, we analyzed the expression and function of NUCLEOPORIN 62 (MdNup62), a component of apple NPC. MdNup62 expression was significantly increased by salt and mannitol (simulated osmotic stress) treatment. The MdNup62-overexpressing (OE) Arabidopsis and tomato lines exhibited significantly reduced salt stress tolerance, and MdNup62-OE Arabidopsis lines exhibited reduced osmotic stress tolerance. We further studied the function of HEAT SHOCK FACTOR A1d (MdHSFA1d), the interacting protein of MdNup62, in salt and osmotic stress tolerance. In contrast to MdNup62, MdHSFA1d-OE Arabidopsis lines showed significantly enhanced tolerance to salt and osmotic stress. Our findings suggest a possible interaction of MdNup62 with MdHSFA1d in the mediation of nuclear and cytoplasmic transport and the regulation of apple salt and osmotic stress tolerance. These results contribute to the understanding of the salt and osmotic stress response mechanism in apple.

LensAge index as a deep learning-based biological age for self-monitoring the risks of age-related diseases and mortality.

Age is closely related to human health and disease risks. However, chronologically defined age often disagrees with biological age, primarily due to genetic and environmental variables. Identifying effective indicators for biological age in clinical practice and self-monitoring is important but currently lacking. The human lens accumulates age-related changes that are amenable to rapid and objective assessment. Here, using lens photographs from 20 to 96-year-olds, we develop LensAge to reflect lens aging via deep learning. LensAge is closely correlated with chronological age of relatively healthy individuals (R2 > 0.80, mean absolute errors of 4.25 to 4.82 years). Among the general population, we calculate the LensAge index by contrasting LensAge and chronological age to reflect the aging rate relative to peers. The LensAge index effectively reveals the risks of age-related eye and systemic disease occurrence, as well as all-cause mortality. It outperforms chronological age in reflecting age-related disease risks (p < 0.001). More importantly, our models can conveniently work based on smartphone photographs, suggesting suitability for routine self-examination of aging status. Overall, our study demonstrates that the LensAge index may serve as an ideal quantitative indicator for clinically assessing and self-monitoring biological age in humans.

DeepQuality improves infant retinopathy screening.

Image quality variation is a prominent cause of performance degradation for intelligent disease diagnostic models in clinical applications. Image quality issues are particularly prominent in infantile fundus photography due to poor patient cooperation, which poses a high risk of misdiagnosis. Here, we developed a deep learning-based image quality assessment and enhancement system (DeepQuality) for infantile fundus images to improve infant retinopathy screening. DeepQuality can accurately detect various quality defects concerning integrity, illumination, and clarity with area under the curve (AUC) values ranging from 0.933 to 0.995. It can also comprehensively score the overall quality of each fundus photograph. By analyzing 2,015,758 infantile fundus photographs from real-world settings using DeepQuality, we found that 58.3% of them had varying degrees of quality defects, and large variations were observed among different regions and categories of hospitals. Additionally, DeepQuality provides quality enhancement based on the results of quality assessment. After quality enhancement, the performance of retinopathy of prematurity (ROP) diagnosis of clinicians was significantly improved. Moreover, the integration of DeepQuality and AI diagnostic models can effectively improve the model performance for detecting ROP. This study may be an important reference for the future development of other image-based intelligent disease screening systems.

NEDD4 Regulated Pyroptosis Occurred from Co-infection between Influenza A Virus and Streptococcus pneumoniae.

Co-infection of respiratory tract viruses and bacteria often result in excess mortality, especially pneumonia caused by influenza viruses and Streptococcus pneumoniae. However, the synergistic mechanisms remain poorly understood. Therefore, it is necessary to develop a clearer understanding of the molecular basis of the interaction between influenza virus and Streptococcus pneumonia. Here, we developed the BALB/c mouse model and the A549 cell model to investigate inflammation and pyroptotic cell death during co-infection. Co-infection significantly activated the NLRP3 inflammasome and induced pyroptotic cell death, correlated with excess mortality. The E3 ubiquitin ligase NEDD4 interacted with both NLRP3 and GSDMD, the executor of pyroptosis. NEDD4 negatively regulated NLRP3 while positively regulating GSDMD, thereby modulating inflammation and pyroptotic cell death. Our findings suggest that NEDD4 may play a crucial role in regulating the GSDMD-mediated pyroptosis signaling pathway. Targeting NEDD4 represents a promising approach to mitigate excess mortality during influenza pandemics by suppressing synergistic inflammation during co-infection of influenza A virus and Streptococcus pneumoniae.

Construction of predictive ceRNA network and identification of the patterns of immune cells infiltrated in Graves' ophthalmopathy. / Gravesçœ¼ç— ä¸­é¢„æµ‹æ€§ceRNAç½‘ç»œçš„æž„å»ºåŠå ç–«ç»†èƒžæµ¸æ¶¦æ¨¡å¼çš„é‰´å®š.

OBJECTIVES: Graves' ophthalmopathy (GO) is a multifactorial disease, and the mechanism of non coding RNA interactions and inflammatory cell infiltration patterns are not fully understood. This study aims to construct a competing endogenous RNA (ceRNA) network for this disease and clarify the infiltration patterns of inflammatory cells in orbital tissue to further explore the pathogenesis of GO. METHODS: The differentially expressed genes were identified using the GEO2R analysis tool. The Kyoto encyclopedia of genes and genomes (KEGG) and gene ontology analysis were used to analyze differential genes. RNA interaction relationships were extracted from the RNA interactome database. Protein-protein interactions were identified using the STRING database and were visualized using Cytoscape. StarBase, miRcode, and DIANA-LncBase Experimental v.2 were used to construct ceRNA networks together with their interacted non-coding RNA. The CIBERSORT algorithm was used to detect the patterns of infiltrating immune cells in GO using R software. RESULTS: A total of 114 differentially expressed genes for GO and 121 pathways were detected using both the KEGG and gene ontology enrichment analysis. Four hub genes (SRSF6, DDX5, HNRNPC,and HNRNPM) were extracted from protein-protein interaction using cytoHubba in Cytoscape, 104 nodes and 142 edges were extracted, and a ceRNA network was identified (MALAT1-MIR21-DDX5). The results of immune cell analysis showed that in GO, the proportions of CD8+ T cells and CD4+ memory resting T cells were upregulated and downregulated, respectively. The proportion of CD4 memory resting T cells was positively correlated with the expression of MALAT1, MIR21, and DDX5. CONCLUSIONS: This study has constructed a ceRNA regulatory network (MALAT1-MIR21-DDX5) in GO orbital tissue, clarifying the downregulation of the proportion of CD4+ stationary memory T cells and their positive regulatory relationship with ceRNA components, further revealing the pathogenesis of GO.

Lyophilization process optimization and molecular dynamics simulation of mRNA-LNPs for SARS-CoV-2 vaccine.

Some studies have shown that lyophilization significantly improves the stability of mRNA-LNPs and enables long-term storage at 2-8 °C. However, there is little research on the lyophilization process of mRNA-lipid nanoparticles (LNPs). Most previous studies have used empirical lyophilization with only a single lyoprotectant, resulting in low lyophilization efficiency, often requiring 40-100 h. In the present study, an efficient lyophilization method suitable for mRNA-LNPs was designed and optimized, shortening the total length of the lyophilization process to 8-18 h, which significantly reduced energy consumption and production costs. When the mixed lyoprotectant composed of sucrose, trehalose, and mannitol was added to mRNA-LNPs, the eutectic point and collapse temperature of the system were increased. The lyophilized product had a ginger root-shaped rigid structure with large porosity, which tolerated rapid temperature increases and efficiently removed water. In addition, the lyophilized mRNA-LNPs rapidly rehydrated and had good particle size distribution, encapsulation rate, and mRNA integrity. The lyophilized mRNA-LNPs were stable at 2-8 °C, and they did not reduce immunogenicity in vivo or in vitro. Molecular dynamics simulation was used to compare the phospholipid molecular layer with the lyoprotectant in aqueous and anhydrous environments to elucidate the mechanism of lyophilization to improve the stability of mRNA-LNPs. This efficient lyophilization platform significantly improves the accessibility of mRNA-LNPs.

Synthesis of cell penetrating peptide sterol coupler and its liposome study on S-mRNA.

In order to overcome the current LNP-mRNA delivery system's weakness of poor stability and rapid degradation by nuclease, a novel chol-CGYKK molecule and then the new phospholipid liposome were designed and prepared. A solid phase approach synthesized CGYKK and connected it to cholesterol via a disulfide linker to form the desired chol-CGYKK. Four formulated samples with different proportions of excipients were prepared by freeze-drying cationic liposomes and packaged S-mRNA. The stability test shows that after six months at 4 °C, the encapsulation rate of this novel phospholipid liposome was still approximately 90%, which would significantly improve the storage and transportation requirement. Transmission electron microscopy, atomic force microscopy, and scanning electron microscopy indicated that the liposomes were spherical and uniformly dispersed. On comparing the levels of mRNA protein expression of the four formulated samples, the S protein vaccine expression of formulated sample 1 was the highest. Uptake by vector cells for formulated sample 1 showed that compared to Lipo2000, and the transfection efficiency was 66.7%. Furthermore, the safety evaluation of the CGYKK and mRNA vaccine liposomes revealed no toxic effects. The in vivo study demonstrated that this novel mRNA vaccine had an immune response. However, it was still not as good as the LNP group right now, but its excellent physicochemical properties, stability, in vitro biological activity, and in vivo efficacy against SARS-CoV-2 provided new strategies for developing the next generation of mRNA delivery system.

Protocol to analyze fundus images for multidimensional quality grading and real-time guidance using deep learning techniques.

Data quality issues have been acknowledged as one of the greatest obstacles in medical artificial intelligence research. Here, we present DeepFundus, which employs deep learning techniques to perform multidimensional classification of fundus image quality and provide real-time guidance for on-site image acquisition. We describe steps for data preparation, model training, model inference, model evaluation, and the visualization of results using heatmaps. This protocol can be implemented in Python using either the suggested dataset or a customized dataset. For complete details on the use and execution of this protocol, please refer to Liu et al.1.

A Phase I Study to Evaluate the Safety, Tolerability, and Pharmacokinetics of Novel Intravenous Formulation of Meloxicam (QP001) in Healthy Chinese Subjects.

Background: Meloxicam is a selective cyclooxygenase-2 inhibitor used for pain relief, but its poor solubility limits its clinical applications. QP001 is a novel intravenous formulation of meloxicam developed with PEG and pH regulator to improve its solubility. This study aimed to evaluate the safety, tolerability, and pharmacokinetics of QP001 in Chinese healthy subjects. Methods: The trial consisted of three parts. Part I was a two-period crossover study to evaluate bioavailability, in which 10 healthy were either intravenously infused with 15mg QP001 (test) or orally given 15mg MobicⓇ (reference). Part II was a single-arm design to assess the pharmacokinetic (PK) characteristics after 30 mg single- and multiple-dose QP001 in 10 subjects. In part III, we investigated the PKs and tolerability of QP001 at a high dose (60 mg) in another 10 subjects. The PK parameters and treatment-emergent adverse events (TEAEs) were evaluated. Results: A total of 30 subjects were enrolled in the study. QP001 was well tolerated and safe without significant TEAEs in all three study parts. The PK characteristics of QP001 were linear following a single-dose range of 15-60 mg (Cmax and AUC0-t were 5.82-17.66 µg/mL and 58.08-251.17 µg∙h/mL, respectively). After five consecutive daily 30 mg doses, the accumulation index was around 1.98, which indicated a minimal accumulation of QP001. Compared to the tablet dosage form, the relative bioavailability of QP001 reached 116.85%. Additionally, the PK profile of QP001 showed no gender difference. Conclusion: QP001 was well tolerated in healthy Chinese subjects after single ascending doses up to 60 mg and multiple-dose of 30 mg. Based on the PK and safety results, QP001 is a promising once-daily intravenous COX-2 inhibitor candidate for managing pain. Trial Registration: The trial is registered at chinadrugtrials.org.cn (ChiCTR2100047884).

Viral subversion of selective autophagy is critical for biogenesis of virus replication organelles.

Infection by many (+)RNA viruses is accompanied by ER-expansion and membrane remodelling to form viral replication organelles, followed by assembly and secretion of viral progenies. We previously identified that virus-triggered lipophagy was critical for flaviviral assembly, and is driven by the lipid droplet associated protein Ancient ubiquitin protein 1 (Aup1). A ubiquitin conjugating protein Ube2g2 that functions as a co-factor for Aup1 was identified as a host dependency factor in our study. Here we characterized its function: Ube2g2-deficient cells displayed a dramatic reduction in virus production, which could be rescued by reconstituting the wild-type but not the catalytically deficient (C89K) mutant of Ube2g2, suggesting that its enzymatic activity is necessary. Ube2g2 deficiency did not affect entry of virus particles but resulted in a profound loss in formation of replication organelles, and production of infectious progenies. This phenomenon resulted from its dual activity in (i) triggering lipophagy in conjunction with Aup1, and (ii) degradation of ER chaperones such as Herpud1, SEL1L, Hrd1, along with Sec62 to restrict ER-phagy upon Xbp1-IRE1 triggered ER expansion. Our results therefore underscore an exquisite fine-tuning of selective autophagy by flaviviruses that drive host membrane reorganization during infection to enable biogenesis of viral replication organelles.

Effects of fibrous microplastics on the accumulation of tris(2,3-dibromopropyl) isocyanurate and behavior of zebrafish via water- and foodborne exposure routes.

Fibrous microplastics are abundant in water, and the additives on fibers could also be transported jointly, which is a combined pollution scenario prevalent in the environment. Organisms ingest microplastics directly from the environment or indirectly through trophic transfer. However, there is a dearth of available information on the uptake and effects of fibers and their additives. This study investigated the uptake and depuration of polyester microplastic fibers (MFs, 3600 items/L) by adult female zebrafish via waterborne and foodborne exposure routes and the effects on the fish behavior. Moreover, we used brominated flame-retardant tris(2,3-dibromopropyl) isocyanurate (TBC, 5 µg/L) as a representative plastic additive compound and explored MFs' effects on the accumulation of TBC in zebrafish. Results substantiated that the highest MF concentrations in zebrafish from waterborne exposure (12.00 ± 4.59 items/tissue) were approximately three times higher than foodborne exposure, suggesting waterborne exposure as the primary ingestion route. In addition, environmentally relevant MF concentrations did not affect TBC bioaccumulation via aqueous exposure. However, MFs could decrease TBC accumulation via foodborne exposure by ingesting contaminated D. magna, which was probably because MF co-exposure decreased the TBC burden in daphnids. MF exposure also considerably increased behavioral hyperactivity in zebrafish. Moved speed, travelled distance, and active swimming duration all increased when exposed to MFs-containing groups. This phenomenon remained apparent in the foodborne exposure experiment with a low MF concentration (0.67-6.33 items/tissue) in zebrafish. This study offers a deeper understanding of MF uptake and excretion in zebrafish and the accumulation of the co-existing pollutant. We also confirmed that waterborne and foodborne exposure may lead to abnormal fish behavior even at low in vivo MF burdens.