Gut Microbiome variation in patients with early-stage mild-to-moderate intracerebral hemorrhage: A pilot study exploring therapeutic targets.

BACKGROUND: The significant morbidity and mortality rates of acute intracerebral hemorrhage (ICH) are well-known around the world. The link between gut microbiota and different types of strokes is becoming more studied. The goal of this study was to look at the relationships between intestinal flora and early-stage mild-to-moderate ICH (emICH), and to provide a new perspective for adjunctive treatment of emICH. METHODS: Fecal samples from 100 participants with emICH (n=50) and healthy individuals (n=50) in this study were collected as well as analyzed utilizing 16S rRNA gene amplicon sequencing in order to characterize the gut microbial community. RESULTS: Distinct microbial communities are present within each group, with emICH patients exhibiting a diminished diversity and uniformity in their microbial profiles. A notable shift in the gut microbiota composition of emICH patients has been observed, characterized by an upsurge in pro-inflammatory microbes belonging to the Euryarchaeota phylum and a concurrent decline in beneficial Bacteroidetes species. Concurrently, significant associations and patterns among operational taxonomic units (OTUs) were identified in emICH patients. A panel of biomarkers (WAL_1855D, Methanobrevibacter, Streptococcus, Bacteroides, Coprococcus, Lachnospira) has been effectively utilized to distinguish emICH patients from healthy individuals, with an area under the curve (AUC) of 0.845. Additionally, an analysis using the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway annotation uncovered several perturbed pathways in emICH patients, predominantly those related to metabolic processes and the inflammatory response. Moreover, predictive profiling of the microbiome's phenotypic traits suggests that emICH patients are likely to harbor a higher prevalence of Gram-negative bacteria and potential opportunistic pathogens compared to healthy controls. CONCLUSIONS: The gut microbiota ecosystem of emICH patients is disrupted, characterized primarily by an increase in pro-inflammatory microbiota, elevated inflammatory signaling pathways, and metabolic dysregulation. Furthermore, microbiota modulation may be seen as a novel approach for the adjunctive treatment of emICH.

Myeloid differentiation protein 2 regulates the innate immunity and the disease resistant against Vibrio alginolyticus in Scylla paramamosain.

Myeloid differentiation protein 2 (MD2), generally functions as a coreceptor of Toll-like receptor 4 (TLR4), facilitating the activation of TLR4 and the recognition of lipopolysaccharides (LPS) in host organisms. While the role of MD2 in immune activation is well-documented across various species, the specific role of the MD2 homolog in Scylla paramamosain (SpMD2) remains unidentified. In this study, we applied RNA interference to reduce SpMD2 expression, aiming to elucidate its role in immune system of mud crabs. Notably, SpMD2 interference leded to decrease in the hemocyte counts and phagocytic activity, along with increase in apoptosis rates and level of reactive oxygen species (ROS). Furthermore, the activities of key enzymes related to immune, such as superoxide dismutase (SOD), catalase (CAT), phenoloxidase (PO), peroxidase (POD), lysozyme (LZM), and acid phosphatase (ACP), were reduced by SpMD2 knockdown. Following infection with Vibrio alginolyticus, increase of SpMD2 expression level was observed. This was accompanied by alterations in the expression levels of genes related to immune in mud crabs. Challenge experiment with Vibrio alginolyticus showed a higher mortality rate after SpMD2 interference. Our study underscore the critical role of SpMD2 in enhancing the innate immunity and disease resistant in S. paramamosain, advancing our understanding of the innate immune regulatory mechanisms in crustaceans.

Therapeutic vaccine targeting dual immune checkpoints induces potent multifunctional CD8+ T cell anti-tumor immunity.

BACKGROUND: Vaccines targeting immune checkpoints represent a promising immunotherapeutic approach for solid tumors. However, the therapeutic efficacy of dual targeting immune checkpoints is still unclear in renal carcinoma. METHODS: An adenovirus (Ad) vaccine targeting B7H1 and B7H3 was developed and evaluated for its therapeutic efficacy in subcutaneous, lung metastasis or orthotopic renal carcinoma mouse and humanized models using flow cytometry, Enzyme-linked immunosorbent spot (ELISPOT), cytotoxic T lymphocyte (CTL) killing, cell deletion, hematoxylin and eosin (HE) staining, and immunohistochemistry (IHC) assays. RESULTS: The Ad-B7H1/B7H3 immunization effectively inhibited tumor growth and increased the induction and percentages of CD8+ T cells in subcutaneous tumor models. The vaccine enhanced the induction and maturation of CD11c+ or CD8+CD11c+ cells, promoting tumor-specific CD8+ T cell immune responses. This was evidenced by increased proliferation of CD8+ T cells and enhanced CTL killing activity. Deletion of CD8+ T cells in vivo abolished the anti-tumor effect of the Ad-B7H1/B7H3 vaccine, highlighting the pivotal role of functional CD8+ T cell immune responses. Moreover, significant therapeutic efficacy of the Ad-B7H1/B7H3 vaccine was observed in lung metastasis, orthotopic, and humanized tumor models through multifunctional CD8+ T cell immune responses. CONCLUSIONS: The Ad vaccine targeting dual immune checkpoints B7H1 and B7H3 exerts a potent therapeutic effect for renal carcinoma and holds promise for solid tumor treatment.

Adenovirus vaccine targeting kinases induces potent antitumor immunity in solid tumors.

BACKGROUND: Targeting kinases presents a potential strategy for treating solid tumors; however, the therapeutic potential of vaccines targeting kinases remains uncertain. METHODS: Adenovirus (Ad) vaccines encoding Aurora kinase A (AURKA) or cyclin-dependent kinase 7 (CDK7) were developed, and their therapeutic potentials were investigated by various methods including western blot, flow cytometry, cytotoxic T lymphocyte assay, and enzyme-linked immunospot (ELISpot), in mouse and humanized solid tumor models. RESULTS: Co-immunization with Ad-AURKA/CDK7 effectively prevented subcutaneous tumor growth in the Renca, RM-1, MC38, and Hepa1-6 tumor models. In therapeutic tumor models, Ad-AURKA/CDK7 treatment impeded tumor growth and increased immune cell infiltration. Administration of Ad-AURKA/CDK7 promoted the induction and maturation of dendritic cell subsets and augmented multifunctional CD8+ T-cell antitumor immunity. Furthermore, the vaccine induced a long-lasting antitumor effect by promoting the generation of memory CD8+ T cells. Tumor recovery on CD8+ T-cell depletion underscored the indispensable role of these cells in the observed therapeutic effects. The potent efficacy of the Ad-AURKA/CDK7 vaccine was consistently demonstrated in lung metastasis, orthotopic, and humanized tumor models by inducing multifunctional CD8+ T-cell antitumor immune responses. CONCLUSIONS: Our findings illustrate that the Ad-AURKA/CDK7 vaccine targeting dual kinases AURKA and CDK7 emerges as a promising and effective therapeutic approach for the treatment of solid tumors.

Multi-objective molecular generation via clustered Pareto-based reinforcement learning.

De novo molecular design is the process of learning knowledge from existing data to propose new chemical structures that satisfy the desired properties. By using de novo design to generate compounds in a directed manner, better solutions can be obtained in large chemical libraries with less comparison cost. But drug design needs to take multiple factors into consideration. For example, in polypharmacology, molecules that activate or inhibit multiple target proteins produce multiple pharmacological activities and are less susceptible to drug resistance. However, most existing molecular generation methods either focus only on affinity for a single target or fail to effectively balance the relationship between multiple targets, resulting in insufficient validity and desirability of the generated molecules. To address the problems, an approach called clustered Pareto-based reinforcement learning (CPRL) is proposed. In CPRL, a pre-trained model is constructed to grasp existing molecular knowledge in a supervised learning manner. In addition, the clustered Pareto optimization algorithm is presented to find the best solution between different objectives. The algorithm first extracts an update set from the sampled molecules through the designed aggregation-based molecular clustering. Then, the final reward is computed by constructing the Pareto frontier ranking of the molecules from the updated set. To explore the vast chemical space, a reinforcement learning agent is designed in CPRL that can be updated under the guidance of the final reward to balance multiple properties. Furthermore, to increase the internal diversity of the molecules, a fixed-parameter exploration model is used for sampling in conjunction with the agent. The experimental results demonstrate that CPRL is capable of balancing multiple properties of the molecule and has higher desirability and validity, reaching 0.9551 and 0.9923, respectively.

Effect of black soldier fly larvae frass addition on humus content during low temperature co-composting.

Initiating aerobic fermentation under low temperature is the main challenge for winter livestock manure composting. This study aims to address this issue by applying black soldier fly larvae (BSFL) frass as a co-composting additive to enhance the low-temperature composting process. Specifically, this work explored the effects of chicken manure and BSFL frass co-composting on the temperature, humus content, and microorganisms with fresh weight ratio of 2:1, 1:1, 1:2 (w/w) at 6 °C. The result showed frass could rapidly rise the temperature to 50 °C and significantly increased the humus content by 15.6 % ∼ 26.3 %. Moreover, microbial analysis revealed that Sphingobacteriaceae accelerated temperature rise via low-temperature reproduction, creating proper temperature for thermophilic bacteria (Truepera and Georgia). Additionally, Cellulomonas and other bacteria promoted organic matter degradation and participated in humus formation. This study presents a novel solution for low-temperature composting, providing practical insights for improving manure management in winter.

A novel mRNA multi-epitope vaccine of Acinetobacter baumannii based on multi-target protein design in immunoinformatic approach.

Acinetobacter baumannii is a gram-negative bacillus prevalent in nature, capable of thriving under various environmental conditions. As an opportunistic pathogen, it frequently causes nosocomial infections such as urinary tract infections, bacteremia, and pneumonia, contributing to increased morbidity and mortality in clinical settings. Consequently, developing novel vaccines against Acinetobacter baumannii is of utmost importance. In our study, we identified 10 highly conserved antigenic proteins from the NCBI and UniProt databases for epitope mapping. We subsequently screened and selected 8 CTL, HTL, and LBL epitopes, integrating them into three distinct vaccines constructed with adjuvants. Following comprehensive evaluations of immunological and physicochemical parameters, we conducted molecular docking and molecular dynamics simulations to assess the efficacy and stability of these vaccines. Our findings indicate that all three multi-epitope mRNA vaccines designed against Acinetobacter baumannii are promising; however, further animal studies are required to confirm their reliability and effectiveness.

Design of Cryptococcus neoformans multi-epitope vaccine based on immunoinformatics method.

Cryptococcus neoformans is a widely distributed opportunistic pathogenic fungus. While C. neoformans commonly infects immunocompromised individuals, it can also affect those who are immunocompetent. Transmission of C. neoformans primarily occurs through the respiratory tract, leading to the development of meningitis. The mortality rate of Cryptococcal meningitis is high, and treatment options are limited. Cryptococcus neoformans infections pose a significant public health threat and currently lack targeted and effective response strategies. This study aimed to screen T lymphocyte (cytotoxic T lymphocyte and helper T lymphocyte) and B lymphocyte epitopes derived from four C. neoformans antigens and develop two multi-epitope vaccines by combining them with various adjuvants. Molecular docking results demonstrated that the vaccines bind stably to Toll-like receptor 4 ( and induce innate immunity. The credibility of the molecular docking results was validated through subsequent molecular dynamics simulations. Furthermore, the results of immune simulation analyses underscored the multi-epitope vaccine's capability to effectively induce robust humoral and cellular immune responses within the host organism. These two vaccines have demonstrated theoretical efficacy against C. neoformans infection as indicated by computer analysis. Nevertheless, additional experimental validation is essential to substantiate the protective efficacy of the vaccines.

A multi-epitope Cryptococcus neoformans vaccine covering the most common A and D phenotypes was designed using bioinformatics methods.

Multivariate associations between neuroanatomy and cognition in unmedicated and medicated individuals with schizophrenia.

Previous studies that focused on univariate correlations between neuroanatomy and cognition in schizophrenia identified some inconsistent findings. Moreover, antipsychotic medication may impact the brain-behavior profiles in affected individuals. It remains unclear whether unmedicated and medicated individuals with schizophrenia would share common neuroanatomy-cognition associations. Therefore, we aimed to investigate multivariate neuroanatomy-cognition relationships in both groups. A sample of 59 drug-naïve individuals with first-episode schizophrenia (FES) and a sample of 115 antipsychotic-treated individuals with schizophrenia were finally included. Multivariate modeling was conducted in the two patient samples between multiple cognitive domains and neuroanatomic features, such as cortical thickness (CT), cortical surface area (CSA), and subcortical volume (SV). We observed distinct multivariate correlational patterns between the two samples of individuals with schizophrenia. In the FES sample, better performance in token motor, symbol coding, and verbal fluency tests was associated with greater thalamic volumes but lower CT in the prefrontal and anterior cingulate cortices. Two significant multivariate correlations were identified in antipsychotic-treated individuals: 1) worse verbal memory performance was related to smaller volumes for the most subcortical structures and smaller CSA mainly in the temporal regions and inferior parietal lobule; 2) a lower symbol coding test score was correlated with smaller CSA in the right parahippocampal gyrus but greater volume in the right caudate. These multivariate patterns were sample-specific and not confounded by imaging quality, illness duration, antipsychotic dose, or psychopathological symptoms. Our findings may help to understand the neurobiological basis of cognitive impairments and the development of cognition-targeted interventions.

Genes associated with cortical thickness alterations in behavioral addiction.

Behavioral addiction (BA) is a conceptually new addictive phenotype characterized by compulsive reward-seeking behaviors despite adverse consequences. Currently, its underlying neurogenetic mechanism remains unclear. Here, this study aimed to investigate the association between cortical thickness (CTh) and genetic phenotypes in BA. We conducted a systematic search in five databases and extracted gene expression data from the Allen Human Brain Atlas. Meta-analysis of 10 studies (343 addicted individuals and 355 controls) revealed that the BA group showed thinner CTh in the precuneus, postcentral gyrus, orbital-frontal cortex, and dorsolateral prefrontal cortex (P < 0.005). Meta-regression showed that the CTh in the precuneus and postcentral gyrus were negatively associated with the addiction severity (P < 0.0005). More importantly, the CTh phenotype of BA was spatially correlated with the expression of 12 genes (false discovery rate [FDR] < 0.05), and the dopamine D2 receptor had the highest correlation (rho = 0.55). Gene enrichment analysis further revealed that the 12 genes were involved in the biological processes of behavior regulation and response to stimulus (FDR < 0.05). In conclusion, our findings demonstrated the thinner CTh in cognitive control-related brain areas in BA, which could be associated with the expression of genes involving dopamine metabolism and behavior regulation.

The Roles of Proactive Personality and Career Satisfaction in the Impact of Employer Brand Attributes Congruence on Creativity.

Although the relationship between employer brand and employee creativity has become a popular theme, this nexus is indirect and ambiguous. Additionally, most studies ignore the consistency of instrumental and symbolic attributes when discussing the consequences of employer brand. This study explored the mechanism of employer brand attributes congruence on employee creativity through career satisfaction, and further revealed the moderating role of proactive personality. Based on the cue consistency theory and the social information processing theory, a polynomial regression model was created and a response surface analysis was conducted using 488 paired questionnaires. The results showed that employer brand attributes congruence impacted employee creativity via career satisfaction. A consistent employer brand strategy is more effective for the creativity of less proactive individuals, while a high-level proactive personality can compensate for the deficiencies of employer brand attributes incongruence. The results complemented employer brand research from the perspective of the instrumental-symbolic attribute configuration and provided supportive empirical evidence of employer brand practices aiming at improving employee creativity. This study has certain practical implications for HR practitioners.

Photocatalytic PAN Nanofibrous Membrane through Anchoring a Nanoflower-Branched CoAl-LDH@PANI Heterojunction for Organic Hazards Degradation and Oil-Containing Emulsified Wastewater Separation.

The synergistic treatment of oily wastewater containing organic hazards and emulsified oils remains a big challenge for membrane separation technology. Herein, the photocatalytic membrane, which combined the physical barrier and catalytic oxidation-driven degradation functionality, was fabricated via anchoring a nanoflower-branched CoAl-LDH@PANI Z-scheme heterojunction onto a porous polyacrylonitrile mat and using tannic acid as an adhesive. The assembly of such a Z-scheme heterojunction offered the superior photocatalytic degradation performance of soluble dyes and tetracycline (up to 94.3%) to the membrane with the improved photocatalytic activity of 2.33 times compared with the CoAl-LDH@pPAN membrane. Quenching experiments suggested that the •O2- was the most reactive oxygen species in the catalytic reaction system of the composite membrane. The greatly enhanced photocatalytic activity was attributed to the effective inhibition of photogenerated hole-electron combination using PANI as a carrier, with charge transferring from LDH to PANI. The possible photocatalytic degradation mechanism was proposed based on VB-XPS, electron spin resonance spectroscopy, and DRS technologies, which was confirmed by density functional theory calculation. Meanwhile, benefiting from the superhydrophilic/oleophobic feature and low oil adhesion, the membrane exhibited high permeability for isooctane emulsion (3990.39 L·m-2·h-1), high structure stability, and satisfactory cycling performance. This work provided a strategy to develop superwetting and photocatalytic composite membranes for treating complex multicomponent pollutants in the chemical industry.

Explorer: efficient DNA coding by De Bruijn graph toward arbitrary local and global biochemical constraints.

With the exponential growth of digital data, there is a pressing need for innovative storage media and techniques. DNA molecules, due to their stability, storage capacity, and density, offer a promising solution for information storage. However, DNA storage also faces numerous challenges, such as complex biochemical constraints and encoding efficiency. This paper presents Explorer, a high-efficiency DNA coding algorithm based on the De Bruijn graph, which leverages its capability to characterize local sequences. Explorer enables coding under various biochemical constraints, such as homopolymers, GC content, and undesired motifs. This paper also introduces Codeformer, a fast decoding algorithm based on the transformer architecture, to further enhance decoding efficiency. Numerical experiments indicate that, compared with other advanced algorithms, Explorer not only achieves stable encoding and decoding under various biochemical constraints but also increases the encoding efficiency and bit rate by ¿10%. Additionally, Codeformer demonstrates the ability to efficiently decode large quantities of DNA sequences. Under different parameter settings, its decoding efficiency exceeds that of traditional algorithms by more than two-fold. When Codeformer is combined with Reed-Solomon code, its decoding accuracy exceeds 99%, making it a good choice for high-speed decoding applications. These advancements are expected to contribute to the development of DNA-based data storage systems and the broader exploration of DNA as a novel information storage medium.

Early detection of uterine corpus endometrial carcinoma utilizing plasma cfDNA fragmentomics.

BACKGROUND: Uterine corpus endometrial carcinoma (UCEC) is a prevalent gynecologic malignancy with a favorable prognosis if detected early. However, there is a lack of accurate and reliable early detection tests for UCEC. This study aims to develop a precise and non-invasive diagnostic method for UCEC using circulating cell-free DNA (cfDNA) fragmentomics. METHODS: Peripheral blood samples were collected from all participants, and cfDNA was extracted for analysis. Low-coverage whole-genome sequencing was performed to obtain cfDNA fragmentomics data. A robust machine learning model was developed using these features to differentiate between UCEC and healthy conditions. RESULTS: The cfDNA fragmentomics-based model showed high predictive power for UCEC detection in training (n = 133; AUC 0.991) and validation cohorts (n = 89; AUC 0.994). The model manifested a specificity of 95.5% and a sensitivity of 98.5% in the training cohort, and a specificity of 95.5% and a sensitivity of 97.8% in the validation cohort. Physiological variables and preanalytical procedures had no significant impact on the classifier's outcomes. In terms of clinical benefit, our model would identify 99% of Chinese UCEC patients at stage I, compared to 21% under standard care, potentially raising the 5-year survival rate from 84 to 95%. CONCLUSION: This study presents a novel approach for the early detection of UCEC using cfDNA fragmentomics and machine learning showing promising sensitivity and specificity. Using this model in clinical practice could significantly improve UCEC management and control, enabling early intervention and better patient outcomes. Further optimization and validation of this approach are warranted to establish its clinical utility.

Identification of novel disulfidptosis-related lncRNA signatures to predict the prognosis and immune microenvironment of skin cutaneous melanoma patients.

BACKGROUND: Skin cutaneous melanoma (SKCM) is an aggressive form of malignant melanoma with poor prognosis and high mortality rates. Disulfidptosis is a newly discovered cell death regulatory mechanism caused by the abnormal accumulation of disulfides. This unique pathway is guiding significant new research to understand cancer progression for targeted treatment. However, the correlation between disulfidptosis with long non-coding RNAs (lncRNAs) in SKCM remains unknown at present. METHODS: The Cancer Genome Atlas database furnished lncRNA expression data and clinical information for SKCM patients. Pearson correlation and Cox regression analyses identified disulfidptosis-related lncRNAs associated with SKCM prognosis. ROC curves and a nomogram validated the model. TME, immune infiltration, GSEA analysis, immune checkpoint gene expression profiling, and drug sensitivity were assessed in high and low-risk groups. Consistent clustering categorized SKCM patients for personalized clinical treatment guidance. RESULTS: A total of twelve disulfidptosis-related lncRNAs were identified for the development of prognosis prediction models. The area under the curve (AUC) values of the ROC curve and the nomogram provided reliable discrimination to evaluate the prognostic potential for SKCM patients. The TME played a crucial role in tumorigenesis, progression and prognosis, and the risk scores were closely related to immune cell infiltration. Meanwhile, the combination of chemotherapy, targeted therapy, and immunotherapy was recommended for low-risk patients based on drug sensitivity and immune efficacy analyses. CONCLUSION: We identified a risk model of twelve disulfidptosis-related lncRNAs that could be used to predict the prognosis of SKCM patients and help guide immunotherapy and chemotherapy for personalized treatment plans.

Structural characteristics, immune-activating mechanisms in vitro, and immunomodulatory effects in vivo of the exopolysaccharide EPS53 from Streptococcus thermophilus XJ53.

Our previous investigations have successfully identified the repeating structural units of EPS53, an exopolysaccharide derived from Streptococcus thermophilus XJ53 fermented milk, and substantiated its potential immunomodulatory properties. The present study further elucidated the structural characteristics of EPS53 and investigated the underlying mechanisms governing its in vitro immunoreactivity as well as its in vivo immunoreactivity. The results obtained from multi-detector high performance gel filtration chromatography revealed that EPS53 adopted a rigid rod conformation in aqueous solution, with the weight-average molecular weight of 1464 kDa, the number-average molecular weight of 694 kDa, and the polydispersity index of 2.11. Congo red experiment confirmed the absence of a triple helix conformation. Scanning electron microscopy showed that EPS53 displayed a three-dimensional fibrous structure covered with flakes. The in vitro findings indicated that EPS53 enhanced phagocytosis ability, reactive oxygen species (ROS) production, and cytokine levels of macrophages via the TLR4-mediated NF-κB/MAPK signaling pathways as confirmed by immunofluorescence staining experiments, inhibition blocking experiments, and Western blot assay. Additionally, the in vivo experiments demonstrated that EPS53 significantly increased macrophage and neutrophil number while enhancing NO and ROS levels in zebrafish larvae; thus, providing further evidence for the immunomodulatory efficacy of EPS53.

Design of a cryptococcus neoformans vaccine by subtractive proteomics combined with immunoinformatics.

The emergence of Cryptococcus neoformans has posed an undeniable burden to many regions worldwide, with its strains mainly entering the lungs through the respiratory tract and spreading throughout the body. Limitations of drug regimens, such as high costs and limited options, have directed our attention toward the promising field of vaccine development. In this study, the subtractive proteomics approach was employed to select target proteins from databases that can accurately cover serotypes A and D of the Cryptococcus neoformans. Further, two multi-epitope vaccines consisting of T and B cell epitopes were demonstrated that they have good structural stability and could bind with immune receptor to induce desired immune responses in silico. After further evaluation, these vaccines show the potential for large-scale production and applicability to the majority of the population of the world. In summary, these two vaccines have been theoretically proven to combat Cryptococcus neoformans infections, awaiting further experimental validation of their actual protective effects.

Epigallocatechin-3-gallate attenuates the sulfamethoxazole-induced immunotoxicity and reduces SMZ residues in Procambarus clarkii.

Sulfamethoxazole (SMZ) is a commonly used antibiotic in aquaculture, and its residues in water bodies pose a significant threat to aquatic organisms in the water environment. In the present study, epigallocatechin-3-gallate (EGCG), a catecholamine, was used to mitigate the immunotoxicity caused by SMZ exposure in Procambarus clarkii. EGCG reduced the apoptosis rate, which was elevated by SMZ exposure, and increased the total hemocyte count. Simultaneously, EGCG enhanced the activities of enzymes related to antibacterial and antioxidant activities, such as superoxide dismutase (SOD), catalase (CAT), lysozyme (LZM), acid phosphatase (ACP), and GSH, which were decreased following SMZ exposure. Hepatopancreatic histology confirmed that EGCG ameliorated SMZ-induced tissue damage caused by SMZ exposure. In addition to EGCG attenuating SMZ-induced immunotoxicity in crayfish, we determined that EGCG can effectively reduce SMZ residues in crayfish exposed to SMZ. In addition, at the genetic level, the expression levels of genes related to the immune response in hemocytes were disrupted after SMZ exposure, and EGCG promoted their recovery and stimulated an increase in the expression levels of metabolism-related transcripts in hemocytes. The transcriptome analysis was conducted, and "phagosome" and "apoptosis" pathways were shown to be highlighted using Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. To the best of our knowledge, this is the first study to confirm that EGCG attenuates SMZ-induced immunotoxicity in aquatic animals and reduces SMZ residues in aquatic animals exposed to SMZ. Our study contributes to the understanding of the mechanisms by which EGCG reduces the immunotoxicity of antibiotic residues in aquatic animals.

Dispersion-assisted high-dimensional photodetector.

Intensity, polarization and wavelength are intrinsic characteristics of light. Characterizing light with arbitrarily mixed information on polarization and spectrum is in high demand1-4. Despite the extensive efforts in the design of polarimeters5-18 and spectrometers19-27, concurrently yielding high-dimensional signatures of intensity, polarization and spectrum of the light fields is challenging and typically requires complicated integration of polarization- and/or wavelength-sensitive elements in the space or time domains. Here we demonstrate that simple thin-film interfaces with spatial and frequency dispersion can project and tailor polarization and spectrum responses in the wavevector domain. By this means, high-dimensional light information can be encoded into single-shot imaging and deciphered with the assistance of a deep residual network. To the best of our knowledge, our work not only enables full characterization of light with arbitrarily mixed full-Stokes polarization states across a broadband spectrum with a single device and a single measurement but also presents comparable, if not better, performance than state-of-the-art single-purpose miniaturized polarimeters or spectrometers. Our approach can be readily used as an alignment-free retrofit for the existing imaging platforms, opening up new paths to ultra-compact and high-dimensional photodetection and imaging.

Selective Removal of Hemicellulose by Diluted Sulfuric Acid Assisted by Aluminum Sulfate.

Hemicellulose can be selectively removed by acid pretreatment. In this study, selective removal of hemicellulose was achieved using dilute sulfuric acid assisted by aluminum sulfate pretreatment. The optimal pretreatment conditions were 160 °C, 1.5 wt% aluminum sulfate, 0.7 wt% dilute sulfuric acid, and 40 min. A component analysis showed that the removal rate of hemicellulose and lignin reached 98.05% and 9.01%, respectively, which indicated that hemicellulose was removed with high selectivity by dilute sulfuric acid assisted by aluminum sulfate pretreatment. Structural characterizations (SEM, FTIR, BET, TGA, and XRD) showed that pretreatment changed the roughness, crystallinity, pore size, and functional groups of corn straw, which was beneficial to improve the efficiency of enzymatic hydrolysis. This study provides a new approach for the high-selectivity separation of hemicellulose, thereby offering novel insights for its subsequent high-value utilization.