Agarose Film-Based Liquid-Solid Conversion for Heavy Metal Detection of Water Samples by Laser-Induced Breakdown Spectroscopy.

Laser-induced breakdown spectroscopy (LIBS) shows promising applications in the analysis of environmental heavy metals. However, direct analysis in water by LIBS faces the problems of droplet splashing and laser energy decay. In this study, a novel liquid-solid conversion method based on agarose films is proposed to provide an easy-to-operate and sensitive detection of heavy metals. First, the water samples were converted into semi-solid hydrogels with the aid of agarose and then dried into agarose films to make the signal intensities stronger. The calibration curves of Cd, Pb and Cr were constructed. The proposed method was validated by standard heavy metal solutions and real water samples. The results showed that the values of R2 were 0.990, 0.989 and 0.975, and the values of the LOD were 0.011, 0.122 and 0.118 mg L-1 for Cd (I) 228.80, Pb (I) 405.78 and Cr (I) 427.48 nm, respectively. The RMSEs of validation were 0.068 (Cd), 0.107 (Pb) and 0.112 mg·L-1 (Cr), and the recovery values were in the range of 91.2-107.9%. The agarose film-based liquid-solid conversion method achieved the desired ease of operation and sensitivity of LIBS in heavy-metal detection, thereby, showing good application prospects in heavy metal monitoring of water.

Crater-Spectrum Feature Fusion Method for Panax notoginseng Cadmium Detection Using Laser-Induced Breakdown Spectroscopy.

Panax notoginseng (P. notoginseng) is a valuable herbal medicine, as well as a dietary food supplement known for its satisfactory clinical efficacy in alleviating blood stasis, reducing swelling, and relieving pain. However, the ability of P. notoginseng to absorb and accumulate cadmium (Cd) poses a significant environmental pollution risk and potential health hazards to humans. In this study, we employed laser-induced breakdown spectroscopy (LIBS) for the rapid detection of Cd. It is important to note that signal uncertainty can impact the quantification performance of LIBS. Hence, we proposed the crater-spectrum feature fusion method, which comprises ablation crater morphology compensation and characteristic peak ratio correction (CPRC), to explore the feasibility of signal uncertainty reduction. The crater morphology compensation method, namely, adding variables using multiple linear regression (MLR) analysis, decreased the root-mean-square error of the prediction set (RMSEP) from 7.0233 µg/g to 5.4043 µg/g. The prediction results were achieved after CPRC pretreatment using the calibration curve model with an RMSEP of 3.4980 µg/g, a limit of detection of 1.92 µg/g, and a limit of quantification of 6.41 µg/g. The crater-spectrum feature fusion method reached the lowest RMSEP of 2.8556 µg/g, based on a least-squares support vector machine (LSSVM) model. The preliminary results suggest the effectiveness of the crater-spectrum feature fusion method for detecting Cd. Furthermore, this method has the potential to be extended to detect other toxic metals in addition to Cd, which significantly contributes to ensuring the quality and safety of agricultural production.

Chromium in soil detection using adaptive weighted normalization and linear weighted network framework for LIBS matrix effect reduction.

Rapid and accurate detection of agricultural soil chromium (Cr) is of great significance for soil pollution assessment. Laser-induced breakdown spectroscopy (LIBS) could serve as a rapid and chemical-free method for hazardous metal analysis compared with conventional chemical methods. However, the detection of LIBS is interfered by uncertainty and matrix effect. In this study, an average strategy combined with linear weighted network (LWNet) was proposed to reduce the uncertainty. Adaptive weighted normalization-LWNet (AWN-LWNet) framework was proposed to reduce the matrix effect in two soil types. The results indicated that LWNet outperformed traditional machine learning and achieved the average relative error (ARE) of 2.08 % and 3.03 % for yellow brown soil and lateritic red soil, respectively. Moreover, LWNet could effectively mine Cr feature peaks even under the low spectral resolution. AWN-LWNet was the optimal model compared with commonly used models to reduce matrix effect (ARE=4.12 %). Besides, AWN-LWNet greatly reduced the number (from 22016 to 72) of spectral variables for model input. By extracting Cr peaks from models, the difference of Cr peaks intensity could be intuitively observed, which served as spectral interpretation for matrix effect reduction. The two methods have the potential to realize the detection of hazardous metals in soil by LIBS.

Response mechanism and rapid detection of phenotypic information in rice root under heavy metal stress.

The root is an important organ affecting cadmium accumulation in grains, but there is no comprehensive research involving rice root phenotype under cadmium stress yet. To assess the effect of cadmium on root phenotypes, this paper investigated the response mechanism of phenotypic information including cadmium accumulation, adversity physiology, morphological parameters, and microstructure characteristics, and explored rapid detection methods of cadmium accumulation and adversity physiology. We found that cadmium had the effect of "low-promotion and high-inhibition" on root phenotypes. In addition, the rapid detection of cadmium (Cd), soluble protein (SP), and malondialdehyde (MDA) were achieved based on spectroscopic technology and chemometrics, where the optimal prediction model was least squares support vector machine (LS-SVM) based on the full spectrum (Rp=0.9958) for Cd, competitive adaptive reweighted sampling-extreme learning machine (CARS-ELM) (Rp=0.9161) for SP and CARS-ELM (Rp=0.9021) for MDA, all with Rp higher than 0.9. Surprisingly, it took only about 3 min, which was more than 90% reduction in detection time compared with laboratory analysis, demonstrating the excellent ability of spectroscopy for root phenotype detection. These results reveal response mechanism to heavy metal and provide rapid detection method for phenotypic information, which can substantially contribute to crop heavy metal control and food safety supervision.

Differential pattern of indigenous microbiome responses to probiotic Bifidobacterium lactis V9 consumption across subjects.

Various factors, including those associated with the host and environment, should be considered to further explore the health-promoting effects of probiotics. However, it is important to consider persistence as a basic but crucial factor in the function of probiotics in the gut. To date, few studies have investigated the factors that influence probiotic persistence. To address these challenges, we designed a cohort experiment that included 49 subjects and used the probiotic Bifidobacterium lactis V9 to identify intestinal microbiota related to probiotic persistence based on high-throughput amplicon sequencing. All of the subjects were divided into three groups (Persisters, Temporary and Non-Persisters) according to the detected amount of viable Bifidobacterium lactis V9 in their faeces. Accordingly, the intestinal microbiota fluctuations in the Persisters group were significant and persistent, whereas those observed in the Non-Persisters group were limited. At the genus level, up to seven genera changed significantly in Persisters group, whereas only the genus Anaerobacterium changed significantly in Non-Persisters group throughout the experiment. At baseline, we observed highly distinct microbial alpha diversity and taxonomic features between the Persisters and Non-Persisters groups. A total of 12 genera were associated with probiotic persistence, with Bifidobacterium and eight other genera negatively associated with probiotic persistence and Anaerobacterium, Paraprevotella and Erysipelatoclostridium positively associated with probiotic persistence. Based on these potential biomarkers, an "Anti-Engraftment Index" (AEI) was derived to classify and predict probiotic persistence in test and validation cohorts with high accuracy. However, we also observed that the AEI did not work in other probiotic consumption experiments, indicating that the AEI was strain-specific.

The distal intestinal microbiome of hybrids of Hainan black goats and Saanen goats.

Intestinal microbiota performed numerous important functions during digestion. The first filial generation (F1) hybrids of Hainan black goats and Saanen goats had different traits, black goats (BG) and white goats (WG), which also brought different production performance. We explored the difference of gut microbiota between black goats and white goats that both belonged to the first filial generation (F1) hybrids. In general, the alpha diversity of the black goat group was significantly higher than the white goat group. The species richness had no significant difference, while the species evenness of BG was higher than WG. Bacteroides, Oscillospira, Alistipes, Ruminococcus, Clostridium and Oscillibacter, as the core gut microbial genera, all had high abundance in BG and WG group. Only the Bacteroides and Bacteroidaceae 5-7N15 were the different genera between the BG and WG group, of which Bacteroides overlapped with the core genera and enriched in the WG group. Besides, PICRUSt analysis showed that there was a high abundance in the secondary metabolic pathways including membrane transport, replication and repair, carbohydrate metabolism and amino acid metabolism. We found the intestinal microbial species of black goats and white goats were very similar for living in the identical growing environment and feeding conditions, but there was still a slight difference in the content. On the one hand, it was proved that the small effect of genotype and the great effect of diet affected the intestinal microbiota together. On the other hand, it was also proved that these different traits of first filial generation (F1) hybrids may not related to gut microbiota and only because of different genotype. Moreover, characterization of the gut microbiota in BG and WG will be useful in goats gut microbiota research.

The gut microbiome stability is altered by probiotic ingestion and improved by the continuous supplementation of galactooligosaccharide.

The stable gut microbiome plays a key role in sustaining host health, while the instability of gut microbiome also has been found to be a risk factor of various metabolic diseases. At the ecological and evolutionary scales, the inevitable competition between the ingested probiotic and indigenous gut microbiome can lead to an increase in the instability. It remains largely unclear if and how exogenous prebiotic can improve the overall gut microbiome stability in probiotic consumption. In this study, we used Lactobacillus plantarum HNU082 (Lp082) as a model probiotic to examine the impact of the continuous or pulsed supplementation of galactooligosaccharide (GOS) on the gut microbiome stability in mice using shotgun metagenomic sequencing. Only continuous GOS supplement promoted the growth of probiotic and decreased its single-nucleotide polymorphisms (SNPs) mutation under competitive conditions. Besides, persistent GOS supplementation increased the overall stability, reshaped the probiotic competitive interactions with Bacteroides species in the indigenous microbiome, which was also evident by over-abundance of carbohydrate-active enzymes (CAZymes) accordingly. Also, we identified a total of 793 SNPs arisen in probiotic administration in the indigenous microbiome. Over 90% of them derived from Bacteroides species, which involved genes encoding transposase, CAZymes, and membrane proteins. However, neither GOS supplementation here de-escalated the overall adaptive mutations within the indigenous microbes during probiotic intake. Collectively, our study demonstrated the beneficial effect of continuous prebiotic supplementation on the ecological and genetic stability of gut microbiomes.

Potassium sorbate suppresses intestinal microbial activity and triggers immune regulation in zebrafish (Danio rerio).

Potassium sorbate (PS) is a class of bacteriostatic antiseptic agent widely used in the food industry; the effects of its intake on host health are currently unclear. In the present study, zebrafish (Danio rerio) were exposed to 0.1 g L-1 and 1 g L-1 aqueous solutions of PS for 2 weeks to investigate the impact of PS on the microecological balance of the intestinal microbiota and immune system. PS exposure triggered immune regulation of zebrafish, significantly reducing the content of diverse biomarkers in the gut, including Immunoglobulin G (IgG), interleukin-1ß (IL-1ß) and tumor necrosis factor-α (TNF-α). Based on high-throughput sequencing data, it was observed that PS exposure resulted in some destabilization of the microbiome composition of the zebrafish, which mainly manifested as a reduction in the abundance of specific genera and the relative levels of transcription and carbohydrate metabolism related to microbial reproductive ability and activity. These changes were consistent with the activity index of microbiota (AIM), a novel measure that we constructed. Collectively, these results illustrate that PS can affect the immune system of zebrafish by changing the composition and function of the gut microbiota, and inhibiting the metabolism of the intestinal microbiota. Our study offers a new understanding of the toxicity of PS.