Rapid detection of fertilizer information based on Raman spectroscopy and machine learning.

The rapid detection of fertilizer nutrient information is a crucial element in enabling intelligent and precise variable fertilizer application. However, traditional detection methods possess limitations, such as the difficulty in quantifying multiple components and cross-contamination. In this study, a rapid detection method was proposed, leveraging Raman spectroscopy combined with machine learning, to identify five types of fertilizers: K2SO4, (CO(NH2)2, KH2PO4, KNO3, and N:P:K (15-15-15), along with their concentrations. Qualitative and quantitative models of fertilizers were constructed using three machine learning algorithms combined with five spectral preprocessing methods. Two variable selection methods were used to optimize the quantitative model. The results showed that the classification accuracy of the five fertilizer solutions obtained by random forest (RF) was 100 %. Moreover, in terms of regression, partial least squares regression (PLSR) outperformed extreme learning machine (ELM) and least squares support vector machine (LSSVM), yielding prediction Rp2 within the range of 0.9843-0.9990 and a root mean square error in the range of 0.0486-0.1691. In addition, this study evaluated the impact of different water types (deionized water, well water, and industrial transition water) on the detection of fertilizer information via Raman spectroscopy. The results showed that while different water types did not notably affect the identification of fertilizer nutrients, they did exert a pronounced effect on the quantification of concentrations. This study highlights the efficacy of combining Raman spectroscopy with machine learning in detecting fertilizer nutrients and their concentration information effectively.

Exploring Evolutionary Pathways and Abiotic Stress Responses through Genome-Wide Identification and Analysis of the Alternative Oxidase (AOX) Gene Family in Common Oat (Avena sativa).

The alternative oxidase (AOX), a common terminal oxidase in the electron transfer chain (ETC) of plants, plays a crucial role in stress resilience and plant growth and development. Oat (Avena sativa), an important crop with high nutritional value, has not been comprehensively studied regarding the AsAOX gene family. Therefore, this study explored the responses and potential functions of the AsAOX gene family to various abiotic stresses and their potential evolutionary pathways. Additionally, we conducted a genome-wide analysis to explore the evolutionary conservation and divergence of AOX gene families among three Avena species (Avena sativa, Avena insularis, Avena longiglumis) and four Poaceae species (Avena sativa, Oryza sativa, Triticum aestivum, and Brachypodium distachyon). We identified 12 AsAOX, 9 AiAOX, and 4 AlAOX gene family members. Phylogenetic, motif, domain, gene structure, and selective pressure analyses revealed that most AsAOXs, AiAOXs, and AlAOXs are evolutionarily conserved. We also identified 16 AsAOX segmental duplication pairs, suggesting that segmental duplication may have contributed to the expansion of the AsAOX gene family, potentially preserving these genes through subfunctionalization. Chromosome polyploidization, gene structural variations, and gene fragment recombination likely contributed to the evolution and expansion of the AsAOX gene family as well. Additionally, we hypothesize that AsAOX2 may have potential function in resisting wounding and heat stresses, while AsAOX4 could be specifically involved in mitigating wounding stress. AsAOX11 might contribute to resistance against chromium and waterlogging stresses. AsAOX8 may have potential fuction in mitigating ABA-mediated stress. AsAOX12 and AsAOX5 are most likely to have potential function in mitigating salt and drought stresses, respectively. This study elucidates the potential evolutionary pathways of the AsAOXs gene family, explores their responses and potential functions to various abiotic stresses, identifies potential candidate genes for future functional studies, and facilitates molecular breeding applications in A. sativa.

Fabrication of ionic liquid self-assemblies based on dicamba with improved herbicidal activity and reduced environmental risks.

The off-target loss of pesticide formulations caused by volatilization and leaching has reduced effective utilization and increased risks to the ecological environment and human health. Self-assembly of pesticides has been widely concerned due to the improved bioactivity and environmental compatibility. Herbicidal ionic liquids (HILs) could effectively decrease off-target loss and increase efficacy and environmental safety by improving the physicochemical properties of herbicides. Herein, HILs were prepared by pairing dicamba with quaternary ammonium salts containing different alkyl chain lengths and aromatic groups and subsequently self-assembled into spherical nanoparticles (HIL NPs) via electrostatic interaction and hydrophobic effect. Compared with dicamba, the obtained HIL NPs with an average particle size of 6-55 nm exhibited improved physicochemical properties, including high zeta potential values (+20.3 to +27.8 mV), low volatilization rate (2.4-3.9 %) and surface tension (22.83-33.07 mN m-1), decreased contact angle (32.25-41.55°) and leaching potential (76.2-86.5 %), and high soil adsorption (12.1-23.8 %), suggesting low risks to the environment. The control efficacy against Amaranthus retroflexus of HIL3 NPs pairing dicamba with octadecyl-trimethyl ammonium chloride was better than that of dicamba sodium salt at different concentrations. Therefore, the ionic liquid self-assembly developed by a facile and green preparation approach to reduce the volatility and leaching of pesticides would have enormous potential in sustainable agriculture.

Comprehensive analysis of neonicotinoids in Chinese commercial honey and pollen: A corresponding health risk assessment for non-targeted organisms.

Neonicotinoids are broad-spectrum and highly effective insecticides that work by affecting neural activity in insects. Neonicotinoids are systemic pesticides that are absorbed by plants, transported, and accumulated in plant tissues, including nectar and pollen. Currently, there is a lack of a comprehensive assessment of the level of neonicotinoid contamination and the associated health risks to non-targeted organisms in commercial honey and pollen produced in China. This study collected 160 batches of honey and 26 batches of pollen from different regions and plant sources in China, analyzed the residue patterns of neonicotinoid pesticides, and comprehensively evaluated the exposure risks to non-targeted organisms including bees (adults and larvae) and humans. Furthermore, this study addresses this imperative by establishing a high-throughput, rapid, and ultra-sensitive indirect competitive enzyme-linked immunosorbent assay (ic-ELISA) based on broad-spectrum monoclonal antibodies to detect and quantify neonicotinoids, with validation conducted using the LC-MS/MS method. The findings indicated that 59.4 % of honey samples contained at least one of eight neonicotinoids, and the ic-ELISA rapid detection and calculation method could detect all the samples containing neonicotinoids. Additionally, the dietary risk assessment for humans and honeybees indicates that the consumption of a specific quantity of honey may not pose a health risk to human due to neonicotinoid intake. However, the Risk Quotient values for imidacloprid to adult bees and bee larvae, as well as clothianidin to bee larvae, were determined to be 2.22, 5.03, and 1.01, respectively-each exceeding 1. This highlights the elevated risk of acute toxicity posed by imidacloprid and clothianidin residues to honey bees. The study bears significant implications for the safety evaluation of non-targeted organisms in the natural food chain. Moreover, it provides scientific guidance for protecting the diversity and health of the ecosystem.

Interaction of human dendritic cell receptor DEC205/CD205 with keratins.

DEC205 (CD205) is one of the major endocytic receptors on dendritic cells and has been widely used as a receptor target in immune therapies. It has been shown that DEC205 can recognize dead cells through keratins in a pH-dependent manner. However, the mechanism underlying the interaction between DEC205 and keratins remains unclear. Here we determine the crystal structures of an N-terminal fragment of human DEC205 (CysR∼CTLD3). The structural data show that DEC205 shares similar overall features with the other mannose receptor family members such as the mannose receptor and Endo180, but the individual domains of DEC205 in the crystal structure exhibit distinct structural features that may lead to specific ligand binding properties of the molecule. Among them, CTLD3 of DEC205 adopts a unique fold of CTLD, which may correlate with the binding of keratins. Furthermore, we examine the interaction of DEC205 with keratins by mutagenesis and biochemical assays based on the structural information and identify an XGGGX motif on keratins that can be recognized by DEC205, thereby providing insights into the interaction between DEC205 and keratins. Overall, these findings not only improve the understanding of the diverse ligand specificities of the mannose receptor family members at the molecular level but may also give clues for the interactions of keratins with their binding partners in the corresponding pathways.

Determination of mycobiota and aflatoxin contamination in commercial bee pollen from eight provinces and one autonomous region of China.

The co-occurrence of fungi and mycotoxins in various foods has been frequently reported in many countries, posing a serious threat to the health and safety of consumers. In this study, the mycobiota in five types of commercial bee pollen samples from China were first revealed by DNA metabarcoding. Meanwhile, the content of total aflatoxins in each sample was investigated by high-performance liquid chromatography with fluorescence detection. The results demonstrated that Cladosporium (0.16 %-89.29 %) was the most prevalent genus in bee pollen, followed by Metschnikowia (0-81.12 %), unclassified genus in the phylum Ascomycota (0-81.13 %), Kodamaea (0-73.57 %), and Penicillium (0-36.13 %). Meanwhile, none of the assayed aflatoxins were determined in the 18 batches of bee pollen samples. In addition, the fungal diversity, community composition, and trophic mode varied significantly among five groups. This study provides comprehensive information for better understanding the fungal communities and aflatoxin residues in bee pollen from different floral origins in China.

A novel ratiometric fluorescent probe for sensitive detection of jasmonic acid in crops.

Herein, a novel ratiometric fluorescent probe was proposed for sensitive detection of jasmonic acid (JA) based on NCQDs@Co-MOFs@MIPs. The prepared NCQDs, with uniquely dual-emissive performance, are insensitive to JA due to electrostatic repulsion. Interestingly, the introduction of Co-MOFs not only avoided the self-aggregation of NCQDs, but changed the surface charge of NCQDs and triggered the response of NCQDs to JA. More importantly, the imprinted recognition sites from MIPs provided "key-lock" structures to specifically capture JA molecules, greatly improving the selectivity of the probe to JA. Under the synergistic actions of Co-MOFs and MIPs, JA can interact with NCQDs through photo-induced electron transfer (PET), resulting in the changes on emission intensity of the probe at Em = 367 nm and 442 nm. Based on the observations, the quantification of JA was realized in the range of 1-800 ng/mL with the limit of detection (LOD) of 0.35 ng/mL. In addition, the probe was used for detecting JA in rice with satisfactory analysis results, indicating the probe holds great potential for monitoring JA levels in crops. Overall, this strategy provides new insights into the construction of practical probes for sensitive detection of plant hormones in crops.

Distribution Characteristics of Nutritional Elements and Combined Health Risk of Heavy Metals in Medicinal Tea from Genuine Producing Area of China.

The development of the medicinal tea (MT) system has promoted the health awareness in the whole world, and the nutritional elements are also an important resource of health care delivery except for the medicinal components. Among various medicinal teas, Astragalus membranaceus (AM), Zingiberaceae rhizome (ZR), and Lonicera japonica (LJ) were the most popular ingredients in China. However, except for the nutrition value, MT was inevitably contaminated with heavy metals due to the special planting environment and processing system. This study was aimed to investigate the distribution characteristics of nutrition elements and combined health risk of heavy metals in MT sample, referring to the maximum residue limit (MRL), estimated daily intake (EDI), total target hazard quotients (TTHQs), and lifetime cancer risk (LCR). Furthermore, the bioaccessibility of gastrointestinal phase and bioavailability of human colon adeno carcinoma cell line were selected for elaborating the exact damage degree to human digestive system. The results showed that, the nutritional elements of Na, Se, K, Ca, and Mn were very rich in MT, but a total of 50% of MT were contaminated by Cr, Hg, and Cd in raw material. Although the cumulative lifetime cancer risk can be accepted under the bioaccessibility (26.62-99.27%), the heavy metals of Cr, As, Hg, and Fe in AM and LJ posed a slight threaten of non-carcinogenic risk to consumers. This study will give an exactly assessment of multiple elements in digestive system, thus further to predict the potential health risk under the consumption of MT products.

Development and comparison of classification models on VIS-NIR hyperspectral imaging spectra for qualitative detection of the Staphylococcus aureus in fresh chicken breast.

Chicken is at risk of contaminated foodborne pathogens in the production process. Timely and nondestructive detection of foodborne pathogens in chicken is essential for food security. The study aims to explore the feasibility of developing efficient classification models for qualitative detection of Staphylococcus aureus in chicken breast using the hyperspectral imaging technique. Principal component analysis was used to process the full spectral information and three wavelength selection methods (competitive adaptive reweighted sampling, genetic algorithm, and successive projections algorithm) were applied to extract effective wavelengths. These methods were combined with the support vector machine algorithm to develop conventional classification models, respectively. In addition, a convolutional neural network model based on deep learning was designed and trained for comparison. The performance of the convolutional neural network model was significantly better than that of conventional classification models. The overall accuracy for chicken sample classifications was improved from 83.88% to 91.38%. The results demonstrated that deep learning can effectively extract spectral features and promote the application of hyperspectral imaging in foodborne pathogens detection of chicken products.

Potential health risk of areca nut consumption: Hazardous effect of toxic alkaloids and aflatoxins on human digestive system.

Contemporarily, there has been a growing consumption rate of areca nut (AN) products worldwide, despite the fact that both fresh and processed AN contain various hazardous ingredients, including toxic alkaloids and carcinogenetic aflatoxins. However, there is a dearth of toxicity and potential cancer risk information regarding toxic alkaloids and aflatoxins via consuming AN products. The present study conducted a comprehensive assessment of the combined hazardous effects of AN alkaloids and aflatoxins towards human digestive system, by methods of HPLC analysis, cell study and in vitro digestive system study. The results revealed a synergetic effect of arecoline and aflatoxins was on human gingival normal fibroblast cell of HGF-1 and a proliferation effect on human tongue squamous carcinoma cell of CAL-27. Specifically, the residual arecoline was as high as 91.08 µg·ml-1 in oral phase and 72.41 µg·ml-1 in gastric phase, which could be an evidence of oral cancer. More importantly, 25.93 % of AN products were contaminated with aflatoxins and the maximum value was three times the MRLs. Under these circumstances, the cytotoxic and MOE values raised a considerable health concern in terms of malignancy risk for children that consume processed AN product, especially compared to scenarios that involve adults and/or fresh AN samples. This study would give rise to a better understanding of the hazards associated with AN alkaloids and aflatoxins towards digestive system, and thus to predict the potential carcinogenic risk of AN products.

Rapid Identification of Soybean Varieties by Terahertz Frequency-Domain Spectroscopy and Grey Wolf Optimizer-Support Vector Machine.

Different soybean varieties vary greatly in their nutritional value and composition. Screening for superior varieties is also essential for the development of the soybean seed industry. The objective of the paper was to analyze the feasibility of terahertz (THz) frequency-domain spectroscopy and chemometrics for soybean variety identification. Meanwhile, a grey wolf optimizer-support vector machine (GWO-SVM) soybean variety identification model was proposed. Firstly, the THz frequency-domain spectra of experimental samples (6 varieties, 270 in total) were collected. Principal component analysis (PCA) was used to analyze the THz spectra. After that, 203 samples from the calibration set were used to establish a soybean variety identification model. Finally, 67 samples from the test set were used for prediction validation. The experimental results demonstrated that THz frequency-domain spectroscopy combined with GWO-SVM could quickly and accurately identify soybean varieties. Compared with discriminant partial least squares (DPLS) and particles swarm optimization support vector machine, GWO-SVM combined with the second derivative could establish a better soybean variety identification model. The overall correct identification rate of its prediction set was 97.01%.

A highly parallel DTT/MB-DNA/Au electrochemical biosensor for trace Hg monitoring by using configuration occupation approach and SECM.

Environmental pollution and medicine safety have aroused increasing public concerns due to human health. Amongst various contaminants, mercury is of special attention owing to their environmental persistence and biogeochemical recycling and ecological risks. Herein, a simple and highly parallel electrochemical biosensor for Hg determination was designed and investigated. The proposed biosensor was prepared and compared between (1) DTT/MB-DNA/Au with configuration occupation approach and (2) MCH/MB-DNA/Au with passivation approach. According to the combined results of scanning electrochemical microscope (SECM) and Randles-Sevcik equation, the DTT modified electrode exhibited high uniformity on DNA distribution and superb stability on electron transfer in Hg2+ detection. Evidentially, the response value of proposed DTT/MB-DNA/Au was increased from 57.518% to 97.607%, while RSD% between duplicate runs had dropped from 22.658% to 0.223% (n = 3). Moreover, the increased proportion of effective working area was 467.380% compared with general sensors. Besides, DTT concentration, DNA concentration as well as assembly time were optimized, utilizing electrochemical impedance spectroscopy (EIS), Cyclic Voltammetry (CV) and Square Wave Anode Stripping Voltammetry (SWASV). This optimized biosensor exhibited an excellent selectivity toward Hg2+ over Cu2+, As2+, Cd2+, Pb2+, Cr3+, Ni2+ and Zn2+ etc., and the stability of DTT/MB-DNA/Au were at least two times better even after 3 days under room temperature. Also, a linear relation was observed between the peak current and Hg2+concentrations in a range from 0.25 nM to 2.00 µM with a detection limit of 53.00 pM under optimal conditions. Finally, DTT/MB-DNA/Au was applied for plants and medical products analysis. In all, this optimized DTT/MB-DNA/Au with advantages of high repeatability and sensitivity would provide a new insight into the design and application of biosensor for reliable sensing in safeguarding plant protection and medicinal safety.

Rapid and nondestructive detection of marine fishmeal adulteration by hyperspectral imaging and machine learning.

Pure fishmeal (PFM) from whole marine-origin fish is an expensive and indispensable protein ingredient in most aquaculture feeds. In China, the supply shortage of domestically produced PFM has caused frequent PFM adulteration with low-cost protein sources such as feather meal (FTM) and fishmeal from by-products (FBP). The aim of this study was to develop a rapid and nondestructive detection method using near-infrared hyperspectral imaging (NIR-HSI) combined with machine learning algorithms for the identification of PFM adulterated with FTM, FBP, and the binary adulterant (composed of FTM and FBP). A hierarchical modelling strategy was adopted to acquire a better classification accuracy. Partial least squares discriminant analysis (PLS-DA) and support vector machine (SVM) coupled with four spectral preprocessing methods were employed to construct classification models. The SVM with baseline offset (BO-SVM) model using 20 effective wavelengths selected by successive projections algorithm (SPA) and competitive adaptive reweighted sampling (CARS) achieved classification accuracy of 100% and 99.43% for discriminating PFM from the adulterants (FTM, FBP) and adulterated fishmeal (AFM), respectively. This study confirmed that NIR-HSI offered a promising technique for feed mills to identify AFM containing FTM, FBP, or binary adulterants.

Assembly and recognition of keratins: A structural perspective.

Keratins are one of the major components of cytoskeletal network and assemble into fibrous structures named intermediate filaments (IFs), which are important for maintaining the mechanical properties of cells and tissues. Over the past decades, evidence has shown that the functions of keratins go beyond providing mechanical support for cells, they interact with multiple cellular components and are widely involved in the pathways of cell proliferation, differentiation, motility and death. However, the structural details of keratins and IFs are largely missing and many questions remain regarding the mechanisms of keratin assembly and recognition. Here we briefly review the current structural models and assembly of keratins as well as the interactions of keratins with the binding partners, which may provide a structural view for understanding the mechanisms of keratins in the biological activities and the related diseases.

[Health risk assessment of exogenous harmful pollutants in Chinese medicine: a review].

In recent years, the quality and safety problems have been limiting the internationalization of Chinese medicine. The pollutants in Chinese medicine, particularly the exogenous harmful pollutants mainly including mycotoxins, pesticide residues, heavy metals, harmful elements, and sulfur dioxide, are of high risks for people. Therefore, the World Health Organization(WHO) and relevant national organizations have clearly defined the maximum residue limits(MRLs) of such pollutants. Chinese Pharmacopoeia(2020 edition, volume Ⅳ) also demonstrates the detection methods, MRLs and preliminary risk assessment methods for four typical exogenous harmful pollutants in Chinese medicine. Therefore, continuous optimization of the health risk assessment system can further help further raise the quality and safety of Chinese medicine. This paper reviews the research on the health risk assessment of four typical exogenous harmful pollutants in Chinese medicine and discusses the problems of and challenges for the assessment system, which is expected to lay a scientific basis for the establishment of the risk warning mode and response measures suitable for specific types of Chinese medicine.

Identification of potential core genes in gastric cancer using bioinformatics analysis.

BACKGROUND: Gastric cancer is the third leading cause of cancer-related mortality in China. Most patients with gastric cancer have no obvious early symptoms; thus, many of them are in the middle and late stages of gastric cancer at first diagnosis and miss the best treatment opportunity. Molecular targeted therapy is particularly important in changing this status quo. METHODS: Three microarray datasets (GSE29272, GSE33651, and GSE54129) were selected from the Gene Expression Omnibus (GEO) database. Differentially expressed genes (DEGs) were screened using GEO2R. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was used to analyze the functional features of these DEGs and the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment. The protein-protein interaction (PPI) of these DEGs was visualized by Cytoscape software. The expressions of hub genes were evaluated based on Gene Expression Profiling Interactive Analysis (GEPIA). Moreover, we used the online Kaplan-Meier plotter survival analysis tool to evaluate the prognostic values of hub genes. The Target Scan database was used to predict microRNAs that could regulate the target gene, collagen type IV alpha 1 chain (COL4A1). The OncomiR database was used to analyze the expression levels of three microRNAs, as well as the relationships with tumor stage, grade, and prognosis. RESULTS: We identified 78 DEGs, including 53 upregulated genes and 25 downregulated genes. The DEGs were mainly enriched in extracellular matrix organization, extracellular structure organization, and response to wounding. Moreover, three KEGG pathways were markedly enriched, including focal adhesion, complement and coagulation cascades, and extracellular matrix (ECM)-receptor interaction. Among these 78 genes, we selected 10 hub genes. The overexpression levels of these hub genes were closely related to poor prognosis and the development of gastric cancer (except for COL3A1, LOX, and CXCL8). Moreover, we found that microRNA-29a-3p, miR-29b-3p, and miR-29c-3p were the potential microRNAs that could regulate the target gene, COL4A1. CONCLUSIONS: Our results showed that FN1, COL1A1, TIMP1, COL1A2, SPARC, COL4A1, and SERPINE1 could contribute to the development of novel molecular targets and biomarker-driven treatments for gastric cancer.

miR-942-5p Inhibits Proliferation, Metastasis, and Epithelial-Mesenchymal Transition in Colorectal Cancer by Targeting CCBE1.

Although colorectal cancer (CRC) is common, there is a paucity of information regarding its molecular pathogenesis. Studies have shown that miRNAs play pivotal roles in the development and progression of CRC. There is a need to further investigate the biological functions of miRNAs in CRC. In particular, it has been reported that miR-942-5p exhibits tumor-suppressive properties. Thus, we analyzed the functional significance of miR-942-5p in CRC and the underlying molecular mechanisms. We found that miR-942-5p was downregulated in CRC tissues and cells. Cell Counting Kit-8, EdU, and colony formation assays revealed that the overexpression of miR-942-5p by mimics inhibited the proliferation of CRC cells. Use of the miR-942-5p inhibitor effectively enhanced the proliferative potential of CRC cells. Further, in vivo xenograft experiments confirmed these results. Increased expression of miR-942-5p suppressed the invasion, migration, and epithelial-mesenchymal transition of CRC cell lines, while decreased miR-942-5p expression had the opposite effect. CCBE1, a secretory molecule for lymphangiogenesis, was established as a downstream target of miR-942-5p, and its expression was inversely correlated with the expression of miR-942-5p in CRC cells. Additionally, cotransfection of the miR-942-5p inhibitor with si-CCBE1 into CRC cells reversed the effects induced by miR-942-5p overexpression. In conclusion, we confirmed that miR-942-5p exerts oncogenic actions in CRC by targeting CCBE1 and identified miR-942-5p as a potential clinical biomarker for CRC diagnosis and therapy.

[Domestic and international research progress of edible and medicinal Arecae Semen].

Arecae Semen, as the first place among "Four South Medicines" in China, has great dual-use value of medicine and food. The research of Arecae Semen was mainly focused on the active ingredients and efficacy value, and its potential safety hazards were also concerned. Until now, there is still a lack of clear boundaries between medicine and food, resulting in its safety cannot be guaranteed. Therefore, it is of great significance to establish clear boundaries of medicine and food use and health risk assessment. In this paper, the differences of pretreatment and application methods of Arecae Semen were analyzed, and the research progress of Arecae Semen in chemical composition identification and toxicology research and safety evaluation were reviewed emphatically. Finally, the differences of quality control and safety evaluation of Arecae Semen in pharmacopoeias or standards were analyzed at home and abroad. It was expected to provide reference value for quality control, safety evaluation and international standardization research of Arecae Semen.

Interactions of ferritin with scavenger receptor class A members.

Scavenger receptors are a superfamily of membrane-bound receptors that recognize both self and nonself targets. Scavenger receptor class A (SR-A) has five known members (SCARA1 to -5 or SR-A1 to -A5), which are type II transmembrane proteins that form homotrimers on the cell surface. SR-A members recognize various ligands and are involved in multiple biological pathways. Among them, SCARA5 can function as a ferritin receptor; however, the interaction between SCARA5 and ferritin has not been fully characterized. Here, we determine the crystal structures of the C-terminal scavenger receptor cysteine-rich (SRCR) domain of both human and mouse SCARA5 at 1.7 and 2.5 Å resolution, respectively, revealing three Ca2+-binding sites on the surface. Using biochemical assays, we show that the SRCR domain of SCARA5 recognizes ferritin in a Ca2+-dependent manner, and both L- and H-ferritin can be recognized by SCARA5 through the SRCR domain. Furthermore, the potential binding region of SCARA5 on the surface of ferritin is explored by mutagenesis studies. We also examine the interactions of ferritin with other SR-A members and find that SCARA1 (SR-A1, CD204) and MARCO (SR-A2, SCARA2), which are highly expressed on macrophages, also interact with ferritin. By contrast, SCARA3 and SCARA4, the two SR-A members without the SRCR domain, have no detectable binding with ferritin. Overall, these results provide a mechanistic view regarding the interactions between the SR-A members and ferritin that may help to understand the regulation of ferritin homeostasis by scavenger receptors.

A reusable AuNPS with increased stability applied for fast screening of trace heavy metals in edible and medicinal marine products.

Heavy metal pollution in marine environment poses a severe threat to the safety of marine products and is thus causing increasingly concerns in terms of their toxicity and potential health risks pose to human. Due to the complex matrix of marine products, a fast screening method for heavy metals at trace level with low price, reusability, high accuracy and long lifetime is of urgency and necessity for consumers and processing factories. This work described a simplified screening system through the preparation, characterization and particular application of Au nano particle sensor (AuNPS) in the complex marine matrix, the main aim is to significantly increase the stability, sensitivity and lifetime of detection system dedicated to Cu and Hg trace analysis in marine products. It is worth mentioning that, the proposed screening system was characterized through electrochemical experiments and theoretical calculations, which could be a new evidence for selecting the detection system in commercially complex samples. Importantly, the discipline of deposition and oxidative stripping process on AuNPS was explained based on the mechanism of Metal Ion Deficient Layer (MIDL), and illustrated with SEM changes during stripping process, as well as the dissolving-out rate of metals on AuNPS material. Moreover, to further improve the reusability and stability of AuNPS sensor, the complex marine matrix was purified by pre-plating interferences on indium tin oxide glass electrode. The screening system exhibited a liner response in the range of 0.02-0.10 µg mL-1 for Hg, 0.01-0.10 µg mL-1 and 0.001-0.01 µg mL-1 for Cu with the detection limits of 0.138 mg kg-1 and 1.51 mg kg-1 in marine matrix, respectively. The sensitivity and lifetime was at least two times better as compared to similar works even after 20-times use. Finally, this proposed analysis system combined with purification procedure was successfully applied for the edible and medicinal marine products analysis, meanwhile, the accuracy and stability were confirmed with standard analytical methods.