Diagnostic performance of metagenomic sequencing in patients with suspected infection: a large-scale retrospective study.

Background: Metagenomic next-generation sequencing (mNGS) has been widely reported to identify pathogens in infectious diseases (IDs). In this work, we intended to investigate the diagnostic value and clinical acceptance of paired-samples mNGS as compared to the culture method. Methods: A total of 361 patients with suspected infection were retrospectively included. With reference to the clinical diagnosis, we compared the diagnostic performance and clinical acceptance in pathogen detection between mNGS and culture tests. Moreover, the pathogen concordance of paired blood and respiratory tract (RT) samples in mNGS assay was investigated. Results: Among 511 samples, 62.04% were shown to be pathogen positive by mNGS, and that for clinical diagnosis was 51.86% (265/511). When compared to culture assay (n = 428), mNGS had a significantly higher positivity rate (51.87% vs. 33.18%). With reference to the clinical diagnosis, the sensitivity of mNGS outperformed that of culture (89.08% vs. 56.72%). Importantly, mNGS exhibited a clinically accepted rate significantly superior to that of culture. In addition, the mNGS result from 53 paired blood and RT samples showed that most pairs were pathogen positive by both blood and RT, with pathogens largely being partially matched. Conclusion: Through this large-scale study, we further illustrated that mNGS had a clinically accepted rate and sensitivity superior to those of the traditional culture method in diagnosing infections. Moreover, blood and paired RT samples mostly shared partial-matched positive pathogens, especially for pathogens with abundant read numbers in RT, indicating that both blood and RT mNGS can aid the identification of pathogens for respiratory system infection.

Cxcl10 and Cxcr3 regulate self-renewal and differentiation of hematopoietic stem cells.

BACKGROUND: The function of hematopoietic stem cells (HSC) is regulated by HSC internal signaling pathways and their microenvironment. Chemokines and chemokine ligands play important roles in the regulation of HSC function. Yet, their functions in HSC are not fully understood. METHODS: We established Cxcr3 and Cxcl10 knockout mouse models (Cxcr3-/- and Cxcl10-/-) to analyze the roles of Cxcr3 or Cxcl10 in regulating HSC function. The cell cycle distribution of LT-HSC was assessed via flow cytometry. Cxcr3-/- and Cxcl10-/- stem/progenitor cells showed reduced self-renewal capacity as measured in serial transplantation assays. To study the effects of Cxcr3 or Cxcl10 deficient bone marrow microenvironment, we transplanted CD45.1 donor cells into Cxcr3-/-or Cxcl10-/- recipient mice (CD45.2) and examined donor-contributed hematopoiesis. RESULTS: Deficiency of Cxcl10 and its receptor Cxcr3 led to decreased BM cellularity in mice, with a significantly increased proportion of LT-HSC. Cxcl10-/- stem/progenitor cells showed reduced self-renewal capacity in the secondary transplantation assay. Notably, Cxcl10-/- donor-derived cells preferentially differentiated into B lymphocytes, with skewed myeloid differentiation ability. Meanwhile, Cxcr3-deficient HSCs demonstrated a reconstitution disadvantage in secondary transplantation, but the lineage bias was not significant. Interestingly, the absence of Cxcl10 or Cxcr3 in bone marrow microenvironment did not affect HSC function. CONCLUSIONS: The Cxcl10 and Cxcr3 regulate the function of HSC, including self-renewal and differentiation, adding to the understanding of the roles of chemokines in the regulation of HSC function.

The Diagnostic Value of Systemic Immune-Inflammatory Index (SII) and Lymphocyte-Albumin-Neutrophil Ratio (LANR) in Chronic Obstructive Pulmonary Disease with Lung Cancer.

Purpose: This study aims to explore the association of inflammatory markers such as the Systemic Immune-Inflammatory Index (SII) and LANR with the comorbidity of Chronic Obstructive Pulmonary Disease (COPD) and lung cancer. Patients and Methods: A cross-sectional analysis was conducted on the clinical data of 309 patients with COPD only and 193 patients with COPD and lung cancer who attended the First Affiliated Hospital of Anhui Medical University. Additionally, we examined autonomous risk factors that contribute to the simultaneous development of COPD and lung cancer through univariate and multivariate logistic regression analyses. This analysis resulted in the development of a nomogram model for visual representation. The effectiveness of the model was assessed using a receiver operating characteristic (ROC) curve, calibration curve, and clinical decision analysis (DCA) curve, with internal validation conducted via repeated sampling methods. Results: Multivariate analysis of clinical characteristics and inflammatory markers showed that smoking history of >60 pack-years, hemoptysis, emphysema, WBC count > 5.53 (×10^9/L), SII > 629.285, and LANR < 11.39 were significantly associated with the comorbidity of COPD and lung cancer. These factors were subsequently integrated into the nomogram model. The AUC of the model stood at 0.849 (95% CI: 0.815-0.882), demonstrating a notable improvement over the COPD-LUCSS scoring system (AUC: 0.716, 95% CI: 0.671-0.761). The DCA curve indicated a notable clinical advantage provided by the model. Additionally, patients with stage IV tumors exhibited elevated SII levels and reduced LANR levels compared to earlier stages, indicating potential prognostic significance for both markers. Conclusion: Increased levels of the inflammatory markers SII and LANR are associated with the risk of comorbidity of COPD and lung cancer.

Evolutionary Ensemble Learning for EEG-Based Cross-Subject Emotion Recognition.

Electroencephalogram (EEG) has been widely utilized in emotion recognition due to its high temporal resolution and reliability. However, the individual differences and non-stationary characteristics of EEG, along with the complexity and variability of emotions, pose challenges in generalizing emotion recognition models across subjects. In this paper, an end-to-end framework is proposed to improve the performance of cross-subject emotion recognition. A novel evolutionary programming (EP)-based optimization strategy with neural network (NN) as the base classifier termed NN ensemble with EP (EPNNE) is designed for cross-subject emotion recognition. The effectiveness of the proposed method is evaluated on the publicly available DEAP, FACED, SEED, and SEED-IV datasets. Numerical results demonstrate that the proposed method is superior to state-of-the-art cross-subject emotion recognition methods. The proposed end-to-end framework for cross-subject emotion recognition aids biomedical researchers in effectively assessing individual emotional states, thereby enabling efficient treatment and interventions.

Preparation of Pinoresinol and Dehydrodiconiferyl Alcohol from Eucommiae Cortex Extract by Fermentation with Traditional Mucor.

Eucommiae Cortex (EC) is frequently used alone or in combination with other active ingredients to treat a range of illnesses. An efficient technical instrument for changing cheap or plentiful organic chemicals into rare or costly counterparts is biotransformation. It combines EC with biotransformation techniques with the aim of producing some novel active ingredients, using different strains of bacteria that were introduced to biotransform EC in an aseptic environment. The high-quality strains were screened for identification after the fermentation broth was found using HPLC, and the primary unidentified chemicals were separated and purified in order to be structurally identified. Strain 1 was identified as Aspergillus niger and strain 2 as Actinomucor elegans; the main transformation product A was identified as pinoresinol (Pin) and B as dehydrodiconiferyl alcohol (DA). The biotransformation of EC utilizing Aspergillus niger and Actinomucor elegans is reported for the first time in this study's conclusion, resulting in the production of Pin and DA.

Efficient Masked Autoencoders With Self-Consistency.

Inspired by the masked language modeling (MLM) in natural language processing tasks, the masked image modeling (MIM) has been recognized as a strong self-supervised pre-training method in computer vision. However, the high random mask ratio of MIM results in two serious problems: 1) the inadequate data utilization of images within each iteration brings prolonged pre-training, and 2) the high inconsistency of predictions results in unreliable generations, i.e., the prediction of the identical patch may be inconsistent in different mask rounds, leading to divergent semantics in the ultimately generated outcomes. To tackle these problems, we propose the efficient masked autoencoders with self-consistency (EMAE) to improve the pre-training efficiency and increase the consistency of MIM. In particular, we present a parallel mask strategy that divides the image into K non-overlapping parts, each of which is generated by a random mask with the same mask ratio. Then the MIM task is conducted parallelly on all parts in an iteration and the model minimizes the loss between the predictions and the masked patches. Besides, we design the self-consistency learning to further maintain the consistency of predictions of overlapping masked patches among parts. Overall, our method is able to exploit the data more efficiently and obtains reliable representations. Experiments on ImageNet show that EMAE achieves the best performance on ViT-Large with only 13% of MAE pre-training time using NVIDIA A100 GPUs. After pre-training on diverse datasets, EMAE consistently obtains state-of-the-art transfer ability on a variety of downstream tasks, such as image classification, object detection, and semantic segmentation.

APTT critical value establishment in four different reagent/instrument systems based on single factor deficiencies.

INTRODUCTION: There are significant differences in the activated partial thromboplastin time (APTT) critical values reported in different studies, most of which does not make recommendations for any specific clear detection systems. The International Council for Standardization in Hematology (ICSH) recommends that APTT critical values be established based on the reagent type, coagulation factor sensitivity and heparin response. The objective of this study was to establish APTT critical values by using different reagents and based on single coagulation factor deficiencies. METHODS: The APTT values were determined in commercial endogenous coagulation factor-deficient plasma at concentrations of 1 IU/dL, 2 IU/dL, 5 IU/dL, 10 IU/dL, 20 IU/dL, and 30 IU/dL by using four assay systems. The retrospective collection of data from patients who lacked factor VIII (FVIII), FIX, or FXI alone was performed. Receiver operating characteristic (ROC) curves were constructed to assess the diagnostic accuracy of APTT for identifying patients with an endogenous coagulation factor activity < 5 IU/dL. RESULTS: The APTT values in the plasma samples with the same concentrations of endogenous coagulation factors were significantly different among the four assay systems (P < 0.001). The suggested critical values of APTT were 40.0 s for Sysmex CS5100 (Actin FSL), 58.0 s for Sysmex CS5100 (Actin), 51.8 s for STA-R Evolution (STA-PTTA), and 64.8 s for ACL TOP 700 (HemosIL SynthasIL). On the basis of the ROC curve, the optimal threshold values for APTT (STA-PTTA) were 55.8 s in patients with a simple deficiency of FVIII (sensitivity = 100%, specificity = 85.7%, area under the ROC curve (AUC) = 0.982), 54.3 s in patients with a simple deficiency of FIX (sensitivity = 100%, specificity = 92.9%, AUC = 0.986), and 71.7 s in patients with a simple deficiency of FXI (sensitivity = 100%, specificity = 94.1%, AUC = 0.992), which were closer (difference of 0.6-2.5 s) to the cutoff points for commercial plasma at equal factor levels. CONCLUSIONS: APTT critical values need to be established for different reagents based on the presence of a single coagulation factor deficiency.

[The Effect of SIRT5 Deletion on Recovery of Hematopoietic Stem Cells after Injury in Mouse].

OBJECTIVE: To investigate the effect of deacylase Sirtuin 5 in the recovery of hematopoietic stem cells (HSCs) after treated by 5-FU in mouse. METHODS: Flow cytometry was used to analyze the effect of SIRT5 deletion on the proportion of hematopoietic stem/progenitor cells (HSPCs) in bone marrow (BM), the proportion of T cells, B cells and myeloid cells (TBM) in peripheral blood (PB) and spleen, and the development of T cells in thymus. Mouse were treated with 5-FU to study the effect of SIRT5 deletion on the cell cycle, apoptosis and the proportion of HSPCs in BM. The effect of SIRT5 deletion on the proliferation of HSCs was analyzed by flow sorting in vitro. RESULTS: SIRT5 deletion did not affect the development of T cells in thymus and the proportion of TBM cells in PB and spleen compared with wild type mice. SIRT5 deletion increased proportion of HSPCs in BM. After 5-FU treatment, the proportion of HSCs in SIRT5 deletion mice was significant decreased (P < 0.05), the HSPC in SIRT5 deletion mice was activated from G0 to G1 phase (P < 0.05), and the proportion of early apoptosis increased (P < 0.05). By monoclonal culture in vitro, the ability of HSCs to form clones in SIRT5 deletion mice was decreased significantly (P < 0.05). CONCLUSION: SIRT5 deletion lead to a decreased the ability of HSCs to clone in vitro. SIRT5 deletion is not conducive to the recovery of HSPCs injury in mice under hematopoietic stress.

Simulation of Starch Gel Printing and Deformation Process Using COMSOL.

The food industry holds immense promise for 3D printing technology. Current research focuses mainly on optimizing food material composition, molding characteristics, and printing parameters. However, there is a notable lack of comprehensive studies on the shape changes of food products, especially in modeling and simulating deformations. This study addresses this gap by conducting a detailed simulation of the starch gel printing and deformation process using COMSOL Multiphysics 6.2 software. Additive manufacturing (AM) technology is widely acclaimed for its user-friendly operation and cost-effectiveness. The 3D printing process may lead to changes in part dimensions and mechanical properties, attributable to the accumulation of residual stresses. Studies require a significant amount of time and effort to discover the optimal composition of the printed material and the most effective deformed 3D structure. There is a risk of failure, which can lead to wasted resources and research delays. To tackle this issue, this study thoroughly analyzes the physical properties of the gel material through COMSOL Multiphysics 6.2 software, It simulates the heat distribution during the 3D printing process, providing important insights into how materials melt and solidify. Three-part models with varying aspect ratios were meticulously designed to explore shape changes during both the printing process and exposure to an 80 °C environment, employing NMR and rheological characterization. Using the generalized Maxwell model for material simulation in COMSOL Multiphysics, the study predicted stress and deformation of the parts by analyzing solid heat transfer and solid mechanics physical fields. Simulation results showed that among three models utilizing a gel-PET plastic membrane bilayer structure, Model No. 1, with the largest aspect ratio, exhibited the most favorable deformation under an 80 °C baking environment. It displayed uniform bending in the transverse direction without significant excess warpage in the edge direction. In contrast, Models No. 2 and No. 3 showed varying degrees of excess warpage at the edges, with Model No. 3 exhibiting a more pronounced warpage. These findings closely aligned with the actual printing outcomes.

Bimetallic AuNR@AgNCs for ultrasensitive surface-enhanced Raman scattering sensing of dithianon in apple juice.

In this study, a bimetallic surfaced-enhanced Raman spectroscopy (SERS)-active substrate consisting of AuNR@AgNCs was proposed for the rapid detection of dithianon. Due to the significant synergistic enhancement of the core-shell nanocuboids, the obtained AuNR@AgNC substrate exhibited excellent SERS performance. The simulation findings supported the practical SERS results and demonstrated that interactions were mainly maintained by the nitrile functional group. The AuNR@AgNCs could be used to detect dithianon with an LOD value of 20 nM. Moreover, dithianon in river water and apple juice could be detected with recovery in the satisfactory ranges of 97.41%-98.35% and 97.77%-98.70%, respectively, by using this substrate under optimal conditions, indicating that the AuNR@AgNC substrate could serve as an excellent SERS detection platform for pesticide residues in fruit.

Gut microbiota and metabolic biomarkers in metabolic dysfunction-associated steatotic liver disease.

Metabolic dysfunction-associated steatotic liver disease (MASLD), a replacement of the nomenclature employed for NAFLD, is the most prevalent chronic liver disease worldwide. Despite its high global prevalence, NAFLD is often under-recognized due to the absence of reliable noninvasive biomarkers for diagnosis and staging. Growing evidence suggests that the gut microbiome plays a significant role in the occurrence and progression of NAFLD by causing immune dysregulation and metabolic alterations due to gut dysbiosis. The rapid advancement of sequencing tools and metabolomics has enabled the identification of alterations in microbiome signatures and gut microbiota-derived metabolite profiles in numerous clinical studies related to NAFLD. Overall, these studies have shown a decrease in α-diversity and changes in gut microbiota abundance, characterized by increased levels of Escherichia and Prevotella, and decreased levels of Akkermansia muciniphila and Faecalibacterium in patients with NAFLD. Furthermore, bile acids, short-chain fatty acids, trimethylamine N-oxide, and tryptophan metabolites are believed to be closely associated with the onset and progression of NAFLD. In this review, we provide novel insights into the vital role of gut microbiome in the pathogenesis of NAFLD. Specifically, we summarize the major classes of gut microbiota and metabolic biomarkers in NAFLD, thereby highlighting the links between specific bacterial species and certain gut microbiota-derived metabolites in patients with NAFLD.

Ferritin-mediated mitochondrial iron homeostasis is essential for the survival of hematopoietic stem cells and leukemic stem cells.

Iron metabolism plays a crucial role in cell viability, but its relationship with adult stem cells and cancer stem cells is not fully understood. The ferritin complex, responsible for intracellular iron storage, is important in this process. We report that conditional deletion of ferritin heavy chain 1 (Fth1) in the hematopoietic system reduced the number and repopulation capacity of hematopoietic stem cells (HSCs). These effects were associated with a decrease in cellular iron level, leading to impaired mitochondrial function and the initiation of apoptosis. Iron supplementation, antioxidant, and apoptosis inhibitors reversed the reduced cell viability of Fth1-deleted hematopoietic stem and progenitor cells (HSPCs). Importantly, leukemic stem cells (LSCs) derived from MLL-AF9-induced acute myeloid leukemia (AML) mice exhibited reduced Fth1 expression, rendering them more susceptible to apoptosis induced by the iron chelation compared to normal HSPCs. Modulating FTH1 expression using mono-methyl fumarate increased LSCs resistance to iron chelator-induced apoptosis. Additionally, iron supplementation, antioxidant, and apoptosis inhibitors protected LSCs from iron chelator-induced cell death. Fth1 deletion also extended the survival of AML mice. These findings unveil a novel mechanism by which ferritin-mediated iron homeostasis regulates the survival of both HSCs and LSCs, suggesting potential therapeutic strategies for blood cancer with iron dysregulation.

Improving the survival of Lactobacillus plantarum FZU3013 by phase separated caseinate/alginate gel beads.

The phase separation behavior of mixed solution of caseinate (Cas) and alginate (Alg) was investigated. Lactobacillus plantarum FZU3013 was encapsulated using 4 % Cas/1 % Alg gel beads with a phase-separated structure. The bacteria were predominantly distributed in the Alg-rich continuous phase. The use of 4 % Cas/1 % Alg beads resulted in higher encapsulation efficiency for L. plantarum FZU3013 compared to 1 % Alg beads. After 5 weeks of storage at 4 °C, the viable count in 4 % Cas/1 % Alg beads was 8.3 log CFU/g, which was 1.1 log CFU/g higher than that of the 1 % Alg beads. When 1 % Alg beads of the smallest size were subjected to in vitro digestion, no viable bacteria could be detected at the end of the digestion, whereas the 4 % Cas/1 % Alg beads of the smallest size had a viable count of 3.9 log CFU/g. When the size of the 4 % Cas/1 % Alg beads was increased to 1000 µm, the viable count was 7.0 log CFU/g after digestion. The results of infrared spectroscopy and zeta potential indicated that hydrogen bonding and electrostatic interactions between caseinate and alginate reinforced the structure of the gel beads and improved the protection for L. plantarum FZU 3013.

Green and sustainable self-cleaning flexible SERS base: Utilized for cyclic-detection of residues on apple surface.

Advances in flexible SERS substrates has made it possible to approach the ultimate goal of rapid in-situ monitoring of fruit and vegetable safety, but its vulnerability under laser ablation results in low utilization. In order to solve this problem, a 3D framework of TiO2-doped PVDF\PVP polymer was utilized to self-assemble gold-silver core-shell nanorods (Au@Ag NRs) to prepare a flexible SERS substrate with good physical stability and self-cleaning properties. This substrate showed excellent detection limit and recyclability after the detection of three pesticide residues in apple peel. The LOD of methyl-parathion (MP) was as low as 0.037 ng/cm2, with an RSD of 5.61 % for 5 cycle-detection. The recoveries of two additional pesticides thiram (TMTD) and chlorpyrifos (CPF) were 86.32 %-112.47 %. We hoped that this research will contribute to providing a recyclable and facile method for in-situ analysis of fruit and vegetable surface residues and functional manufacture of flexible SERS substrates.

Synthesis and biological evaluation of novel quaternary ammonium antibody drug conjugates based on camptothecin derivatives.

Antibody drug conjugates (ADCs) have emerged as a highly promising class of cancer therapeutics, comprising antibodies, effector molecules, and linkers. Among them, DS-8201a with DXd as the effector molecule, has shown remarkable anti-tumor efficacy against solid tumors, sparking a surge of interest in ADCs with camptothecin derivatives as ADC effector molecules. In this study, we introduced and successfully constructed quaternary ammonium ADCs utilizing camptothecin derivatives WL-14 and CPTS-1 for the first time. All four ADCs displayed excellent stability under physiological conditions and in plasma, facilitating their prolonged circulation in vivo. Moreover, the four ADCs, employing Val-Cit or Val-Ala dipeptide linkers effectively achieved complete release of the effector molecules via cathepsin B. Although, the in vitro antitumor activity of these ADCs was comparatively limited, the development of quaternary ammonium ADCs based on novel camptothecin derivatives as effector molecules is still a viable and promising strategy. Significantly, our study provides valuable insights into the crucial role of linker optimization in ADCs design.

Causal Link between Gut Microbiota, Neurophysiological States, and Bone Diseases: A Comprehensive Mendelian Randomization Study.

Increasing evidence highlights a robust correlation between the gut microbiota and bone diseases; however, the existence of a causal relationship between them remains unclear. In this study, we thoroughly examined the correlation between gut microbiota and skeletal diseases using genome-wide association studies. Linkage disequilibrium score regression and Mendelian randomization were used to probe genetic causality. Furthermore, the potential mediating role of neuropsychological states (i.e., cognition, depression, and insomnia) between the gut microbiota and bone diseases was evaluated using mediation analysis, with genetic colocalization analysis revealing potential targets. These findings suggest a direct causal relationship between Ruminococcaceae and knee osteoarthritis (OA), which appears to be mediated by cognitive performance and insomnia. Similarly, a causal association was observed between Burkholderiales and lumbar pelvic fractures, mediated by cognitive performance. Colocalization analysis identified a shared causal variant (rs2352974) at the TRAF-interacting protein locus for cognitive ability and knee OA. This study provides compelling evidence that alterations in the gut microbiota can enhance cognitive ability, ameliorate insomnia, and potentially reduce the risk of site-specific fractures and OA. Therefore, strategies targeting gut microbiota optimization could serve as novel and effective preventive measures against fractures and OA.

Assessment of Ferroptosis in Hematopoietic Stem and Progenitor Cells.

Hematopoietic stem cells (HSCs) are critical for maintaining hematopoiesis throughout life by utilizing their self-renewing and multipotent capabilities. Ferroptosis is a type of cell death characterized by the iron-dependent accumulation of lipid peroxides, and it is involved in multiple physiological and pathological conditions. Recent studies have highlighted the important role of ferroptosis in the functional maintenance of HSCs. Here, we describe our current protocols for accessing ferroptosis in hematopoietic stem and progenitor cells (HSPCs) both in vivo and in vitro. We introduce procedures for measuring total reactive oxygen species (ROS) and lipid ROS in HSPCs, as well as analyzing cell number, cell viability, and cell cycle profiles. This protocol provides a useful approach for characterizing the status of ferroptosis and its related parameters in HSPCs and more broadly, for studying the outcomes of ferroptosis on hematopoiesis.

Peptide-Appended Nanosonosensitizers Targeting Tumor Glycolysis for Synergistic Sonodynamic-Immunometabolic Therapy of Spinal-Metastasized Tumors.

Despite recent advancements in cancer immunotherapy, challenges have yet to be surmounted to achieve two major goals of magnifying antitumor immunity and remodeling the immunosuppressive tumor microenvironment. Here, a nanosystem (ODM-R) that integrates oxygen-deficient molybdenum oxide (ODM) nanosonosensitizers and R7 peptides with tumor metabolism regulation effects is designed and fabricated for synergistic sonodynamic-immunometabolic therapy of spinal-metastasized tumors. The ODM generates reactive oxygen species upon ultrasound irradiation to implement sonodynamic therapy (SDT), inducing cancer cell apoptosis and immunogenic cell death. The R7 attached on ODM markedly inhibits the uptake of glucose and excretion of lactic acid in cancer cells by perturbing the glycolysis process. The combination of SDT and tumor glycolysis obstruction by ODM-R guarantees satisfactory efficacy in synergizing with PD-L1 antibody to eradicate spinal-metastasized tumors, achieving concurrent sonodynamic-triggered immune activation and immunosuppressive tumor microenvironment remodeling. This work provides a proof-of-concept of nanosonosensitizers for boosting cancer immunotherapy by SDT and tumor metabolic regulation.

Construction of Fe3O4/xSiO2/ySiO2 Nanoparticles for Pesticide Removal from Water: Improved Dispersion Stability and Adsorption Capacity.

Highly efficient and reusable adsorbents for pesticide removal from wastewater have received increasing attention. In this study, Fe3O4 was synthesized using the solvothermal method. Fe3O4/xSiO2 and Fe3O4/xSiO2/ySiO2 were obtained through layer-by-layer silica (SiO2) coating on the surface of Fe3O4. SiO2 coating improved the dispersibility of the adsorbent, which can be separated from water rapidly under the action of the external magnetic field. The adsorption capacity of the adsorbent was investigated through removing pyraclostrobin from synthetic wastewater. The adsorbent showed the highest adsorption effect at the adsorbent concentration of 1 mg mL-1, at a pH of 7, and the adsorbent time of 110 min. The fitting model of the adsorption process conformed to the second-order kinetic model and the Langmuir model. The maximum adsorption capacity of Fe3O4/xSiO2/ySiO2 nanoparticles was 94.89 mg g-1, and the removal efficiency was about 96% at adsorption equilibrium. Acetone as the eluent can effectively desorb the adsorbent, and the desorbed adsorbent had high reusability. Particularly, the removal efficiency was still greater than 86% after 9 times of reuse. These results provide a reference for designing reusable nanoparticles to effectively absorb pesticides in wastewater.

Convenient self-assembled PDADMAC/PSS/Au@Ag NRs filter paper for swift SERS evaluate of non-systemic pesticides on fruit and vegetable surfaces.

The goal of food safety supervision is to directly identify the pesticide residues on the surface of fruits and vegetables. This study proposed to develop a facile, non-destructive, and sensitive method based on surface-enhanced Raman scattering (SERS) to detect non-systemic pesticides on the surface of fruits and vegetables. The composite material was prepared by loading CTAB guided Au@Ag NRs with positive charge onto filter paper which was modified with PDADMAC(+) and PSS(-) using electrostatic adsorption. Au@Ag NRs with bimetallic synergies were effectively adsorbed in the fiber grid to generate 3D SERS hotspots within a few microns of depth. The results showed that the 3D composite flexible substrate had a high SERS activity, great repeatability, and sensitivity when the method was utilized to detect 4-MBA, methyl-parathion, thiram and chlorpyrifos. Three kinds of non-systemic pesticides on the peel could be detected directly and quickly owing to the arbitrary bending of the substrate, demonstrating the efficiency of the SERS "paste-reading" method. The acquired findings demonstrated that PDADMAC/PSS/Au@Ag NRs composite filter paper had the potential to provide rapid feedback for in-situ analysis of pesticide residues on the surface of fruit and vegetable.