Mechanisms insights into bisphenol S-induced oxidative stress, lipid metabolism disruption, and autophagy dysfunction in freshwater crayfish.

Bisphenol S (BPS) is widely used in plastic products, food packaging, electronic products, and other applications. In recent years, BPS emissions have increasingly impacted aquatic ecosystems. The effects of BPS exposure on aquatic animal health have been documented; however, our understanding of its toxicology remains limited. This study aimed to explore the mechanisms of lipid metabolism disorders, oxidative stress, and autophagy dysfunction induced in freshwater crayfish (Procambarus clarkii) by exposure to different concentrations of BPS (0 µg/L, 1 µg/L, 10 µg/L, and 100 µg/L) over 14 d. The results indicated that BPS exposure led to oxidative stress by inducing elevated levels of reactive oxygen species (ROS) and inhibiting the activity of antioxidant-related enzymes. Additionally, BPS exposure led to increased lipid content in the serum and hepatopancreas, which was associated with elevated lipid-related enzyme activity and increased expression of related genes. Furthermore, BPS exposure decreased levels of phosphatidylcholine (PC) and phosphatidylinositol (PI), disrupted glycerophospholipid (GPI) metabolism, and caused lipid deposition in the hepatopancreatic. These phenomena may have occurred because BPS exposure reduced the transport of fatty acids and led to hepatopancreatic lipid deposition by inhibiting the transport and synthesis of PC and PI in the hepatopancreas, thereby inhibiting the PI3K-AMPK pathway. In conclusion, BPS exposure induced oxidative stress, promoted lipid accumulation, and led to autophagy dysfunction in the hepatopancreas of freshwater crayfish. Collectively, our findings provide the first evidence that environmentally relevant levels of BPS exposure can induce hepatopancreatic lipid deposition through multiple pathways, raising concerns about the potential population-level harm of BPS and other bisphenol analogues.

Exploring the mechanism of intestinal injury induced by Bisphenol S in freshwater crayfish (Procambarus clarkii): Molecular and biochemical approaches.

Bisphenol S (BPS) is extensively utilized in various industries such as plastic manufacturing, food packaging, and electronics. The release of BPS into aquatic environments has been observed to have negative impacts on aquatic ecosystems. Research has shown that exposure to BPS can have adverse effects on the health of aquatic animals. This study aimed to explore the mechanism of oxidative stress and endoplasmic reticulum stress induced in freshwater crayfish (Procambarus clarkii) by exposure to BPS (0 µg/L, 1 µg/L, 10 µg/L, and 100 µg/L) for 14 days. The results showed that BPS exposure resulted in elevated levels of reactive oxygen species (ROS) and malondialdehyde (MDA) and severe intestinal histological damage. In addition, oxidative stress can occur in the body by inhibiting the activity of antioxidant enzymes and the expression of related genes. BPS exposure induced a significant increase in the relative mRNA expression levels of inflammatory cytokines (NF-κB and TNF-α) and key unfolded protein response (UPR) related genes (Bip, Ire1, and Xbp1). At the same time, BPS exposure also induced up-regulation of apoptosis genes (Cytc and Casp3), suggesting that UPR and Nrf2-Keap1 signaling pathways may play a protective role in the process of apoptosis and oxidative stress. In conclusion, Our findings present the initial evidence that exposure to environmentally relevant levels of BPS can lead to intestinal injury through various pathways, highlighting concerns about the potential harm at a population level from BPS and other bisphenol analogs.

Influence of Different Feed Particle Sizes on the Growth Performance and Nutrition Composition in Crayfish, Procambarus clarkii Larvae.

A suitable feed size has a positive effect on animal feeding. For aquatic larvae, the correct feed size is very important for their growth. This experiment analyzed and compared the effect of different particle sizes of feed for larval stages on the growth performance, whole body composition, and muscle amino acid and fatty acid composition of crayfish. Five larval crayfish diets of different particle sizes, namely < 0.40 mm (Group A, control group), 0.40-0.50 mm (Group B), 0.71-0.85 mm (Group C), 0.90-1.00 mm (Group D) and 1.5 mm (Group E), were fed to 2000 crayfish (initial weight 0.0786 ± 0.0031 g) for 100 d. The results showed that as the particle size increased, final weight, weight gain (WG, p = 0.001) and specific growth rate (SGR, p = 0.000) of the crayfish tended to increase and then leveled off, with the control group being the lowest. The feed conversion ratio (FCR, p = 0.000) showed a decreasing and then equalizing trend with increasing particle size, but there was no significant difference between the groups except the control group. Broken-line regression analysis showed that the critical values for the appropriate particle feed size for crayfish larvae were 0.55 mm and 0.537 mm using SGR and FCR as indicators. Groups B, C and D had the highest crude protein content and were significantly higher than the control group (p = 0.001). Group E had the highest umami amino acid (UAA) and was significantly higher than the control group (p = 0.026). The content of isoleucine (Ile, p = 0.038) and phenylalanine (Phe, p = 0.038) was highest in group C and significantly higher than in the control group. Through principal component analysis, groups C and D were shown to contain leucine (Leu), glutamic (Glu), methionine (Met), valine (Val), histidine (His), Phe, and Ile levels significantly induced. The content of linoleic acid (C18:2n6, p = 0.000), linolenic acid (C18:3n3, p = 0.000), saturated fatty acid (SFA, p = 0.000), monounsaturated fatty acid (MUFA, p = 0.001), polyunsaturated fatty acid (PUFA, p = 0.000) and n-6 PUFA (p = 0.000) in group C was the highest and significantly higher than the control group. Principal component analysis showed that group C significantly induced the levels of C18:2n6, C18:3n3, DHA, EPA, n-3 PUFA and n-6 PUFA in muscle. Therefore, our results suggest that appropriate feed particle size can improve the growth performance and nutrient composition of crayfish. Based on the broken-line regression analysis of SGR and FCR, the critical values of optimal particle size for crayfish are 0.55 mm and 0.537 mm, and when the particle size exceeds these critical values (not more than 1.5 mm commercial feed), growth performance and FCR of the crayfish are no longer changed. Nevertheless, group C has high protein and low lipid content, as well as better nutrition with amino acids and fatty acids. Overall, combined with growth performance and nutrient composition, it is recommended that the particle size of the diet at the larval stage for crayfish is between 0.71 and 0.85 mm.

Improving contaminant removal and inhibiting CH4 and H2S emissions from septic tanks: Nitrified human urine as a source of electron acceptor.

Septic tanks are widely adopted in decentralized household wastewater treatment systems serving billions of people globally. Due to the lack of effective electron acceptors, insufficient nutrient removal and the emission of harmful gases, e. g. H2S, CH4, etc., are the common drawbacks. In the present work, we attempted to supplement nitrite into septic tanks as an electron acceptor, via nitrifying human urine source-separated from blackwater, to overcome these drawbacks. Partial or complete nitritation of source-separated urine was achieved in a sequencing batch reactor. The addition of nitrified urine into septic tanks improved organic and nitrogen removals in blackwater up to 90 % and 70 %, respectively. The emission of harmful gases from the septic tanks was stably diminished, with more than 75 % of CH4, CO2 and H2S reductions. Nitrite addition significantly reduced the abundance of hydrogenotrophic methanogens in septic tanks. Though the activity of sulfate-reducing bacteria recovered after the initial inhibition upon nitrite addition, the bio-generated H2S was retained in water since the increased wastewater pH after nitrite addition promoted the disassociation of H2S in aqueous solution.

Regulation of ginseng adventitious root growth in Panax ginseng by the miR156-targeted PgSPL24-09 transcription factors.

MicroRNA (miRNA) is a class of non-coding endogenous small-molecule, single-stranded RNAs, and it is involved in post-transcriptional gene expression regulation in plants and plays an important role in plant growth and development. Among them, miRNA156 regulates members of target SPL gene family and thus participates in plant growth and development, hormonal response and adversity stress. However, it has not been reported in ginseng. In this study, based on the previous analysis of the SPL gene family, the age-related and stably expressed SPL gene PgSPL24-09 was obtained in roots. The binding site of miRNA156 to this gene was analyzed using target gene prediction tools, and the interactions between miRNA156 and PgSPL24-09 gene were verified by dual luciferase reporter gene assay and RT-qPCR. At the same time, miRNA156 silencing vector and overexpression vector were constructed and transformed into ginseng adventitious roots and Arabidopsis thaliana to analyze the molecular mechanism of miRNA156-SPL module in regulating the growth of ginseng adventitious roots. This study provides a theoretical basis for the in-depth study of the molecular role of miRNAs in ginseng growth, and also lays the foundation for the study of the role of miRNA156-SPL module in regulating the growth and development of ginseng.

Effects of Substituting Tenebrio molitor and Elodea nuttallii as Feed on Growth, Flesh Quality and Intestinal Microbiota of Red Swamp Crayfish (Procambarus clarkii).

This study aimed to evaluate the impact of substituting a portion of feed with Tenebrio molitor (TM) and Elodea nuttallii (EN) on crayfish culture. A total of 270 crayfish (5.1 ± 0.4 g) were fed three different diet combinations (A: 100% feed; B: 80% feed + 10% TM + 10% EN; C: 75% feed + 15% TM + 10% EN) for 12 weeks. The findings demonstrated that group C had an important beneficial impact on the growth performance of crayfish. This was evidenced by a rise in digestive enzyme activity (trypsin, lipase, and cellulase) in the intestinal and hepatopancreas, as well as an upregulation in the expression of growth-related genes (ghsr, igfbp7, mhc, mlc1, mef2, and pax7) in the muscle. Furthermore, the assessment of the flesh quality of crayfish muscle in group C was conducted. The findings indicated a significant increase (p < 0.05) in the energy value (moisture, crude protein, and crude lipid) within the muscle. The levels of delicious amino acids (Glu, Ala, Ser, Gly, and Tyr) and polyunsaturated fatty acids (ARA, DHA) were enhanced, resulting in an improved nutritional profile and flavor of the muscle while maintaining the Σn-3/Σn-6 ratio. The remodeling of the intestinal microbiota (abundance of Proteobacteria and ratio of Firmicutes/Bacteroidota bacteria) also revealed improved growth performance. Additional research is necessary to ascertain whether excessive use of TM or EN feed substitution can have negative effects on crayfish culture.

The molecular phylogeny of Caenogastropoda (Mollusca, Gastropoda) based on mitochondrial genomes and nuclear genes.

Comprising about 60 % of gastropod diversity, caenogastropods display almost all kinds of shell forms and include many commercially important marine groups. Although the monophyly of Caenogastropoda has been widely accepted, thier internal phylogenetic relationships remain unclear. In the present study, a total of 27 caenogastropods belonging to eight superfamilies were sequenced and used for phylogenetic reconstruction. All newly sequenced mitogenomes adhered to the consensus gene order of caenogastropods, except for those of Vanikoroidea, Vermetoidea and Cerithioidea, which involved protein-coding genes. The reconstructed mitogenomic phylogeny suggested the monophylies of Architaenioglossa, Sorbeoconcha, Hypsogastropoda and the siphonate clade. The present study also identified a close affinity among Cypraeoidea, Ficoidea, Tonnoidea, and Neogastropoda, supported by the presence of a pleurembolic proboscis. The monophyly of Neogastropoda was not supported, as Cancellariidae was found to be sister to the limpet-shaped group Calyptraeoidea, and (Tonooidea + Ficoidea) were sister to the remaining neogastropods. This study provides important information for better understanding the evolution of caenogastropods, as well as for the protection and utilization of these diverse and economically significant marine resources.

Characteristic Extraction and Assessment Methods for Transformers DC Bias Caused by Metro Stray Currents.

Metro stray currents flowing into transformer-neutral points cause the high neutral DC and a transformer to operate in the DC bias state.Because neutral DC caused by stray current varies with time, the neutral DC value cannot be used as the only characteristic indicator to evaluate the DC bias risk level. Thus, unified characteristic extraction and assessment methods are proposed to evaluate the DC bias risk of a transformer caused by stray current, considering the signals of transformer-neutral DC and vibration. In the characteristic extraction method, the primary characteristics are obtained by comparing the magnitude and frequency distributions of transformer-neutral DC and vibration with and without metro stray current invasion. By analyzing the correlation coefficients, the final characteristics are obtained by clustering the primary characteristics with high correlation. Then, the magnitude and frequency characteristics are extracted and used as indicators to evaluate the DC bias risk. Moreover, to avoid the influence of manual experience on indicator weights, the entropy weight method (EWM) is used to establish the assessment model. Finally, the proposed methods are applied based on the neutral DC and vibration test data of a certain transformer. The results show that the characteristic indicators can be extracted, and the transformer DC bias risk can be evaluated by using the proposed methods.

Chromomycins from soil-derived Streptomyces sp. inhibit the growth of human non-small cell lung cancer cells by targeting c-FLIP.

Three chromomycin derivatives, chromomycins A3 (1, CA3), A5 (2, CA5), and monodeacetylchromomycin A3 (3, MDA-CA3), were identified from the soil-derived Streptomyces sp. CGMCC 26516. A reinvestigation of the structure of CA5 is reported, of which the absolute configuration was unambiguously determined for the first time to be identical with that of CA3 based on nuclear magnetic resonance (NMR) data analysis as well as NMR and electronic circular dichroism calculations. Compounds 1-3 showed potent cytotoxicity against the non-small-cell lung cancer (NSCLC) cells (A549, H460, H157-c-FLIP, and H157-LacZ) and down-regulated the protein expression of c-FLIP in A549 cells. The IC50 values of chromomycins in H157-c-FLIP were higher than that in H157-LacZ. Furthermore, si-c-FLIP promoted anti-proliferation effect of chromomycins in NSCLC cells. In nude mice xenograft model, 1 and 2 both showed more potent inhibition on the growth of H157-lacZ xenografts than that of H157-c-FLIP xenografts. These results verify that c-FLIP mediates the anticancer effects of chromomycins in NSCLC.

Genome-wide identification and integrated analysis of the FAR1/FHY3 gene family and genes expression analysis under methyl jasmonate treatment in Panax ginseng C. A. Mey.

Ginseng (Panax ginseng C. A. Mey.) is an important and valuable medicinal plant species used in traditional Chinese medicine, and its metabolite ginsenoside is the primary active ingredient. The FAR1/FHY3 gene family members play critical roles in plant growth and development as well as participate in a variety of physiological processes, including plant development and signaling of hormones. Studies have indicated that methyl jasmonate treatment of ginseng adventitious roots resulted in a significant increase in the content of protopanaxadiol ginsenosides. Therefore, it is highly significant to screen the FAR1/FHY3 gene family members in ginseng and preliminarily investigate their expression patterns in response to methyl jasmonic acid signaling. In this study, we screened and identified the FAR1/FHY3 family genes in the ginseng transcriptome databases. And then, we analyzed their gene structure and phylogeny, chromosomal localization and expression patterns, and promoter cis-acting elements, and made GO functional annotations on the members of this family. After that, we treated the ginseng adventitious roots with 200 mM methyl jasmonate and investigated the trend of the expression of four genes containing the largest number of methyl jasmonate cis-acting elements at different treatment times. All four genes were able to respond to methyl jasmonate, the most significant change was in the PgFAR40 gene. This study provides data support for subsequent studies of this family member in ginseng and provides experimental reference for subsequent validation of the function of this family member under methyl jasmonic acid signaling.

Integrated spatial metabolomics and network pharmacology to explore the pharmacodynamic substances and mechanism of Radix ginseng-Schisandra chinensis Herb Couple on Alzheimer's disease.

Radix ginseng and Schisandra chinensis have been extensively documented in traditional Chinese medicine (TCM) for their potential efficacy in treating dementia. However, the precise mechanism of their therapeutic effects remains to be fully elucidated. In this study, air flow-assisted desorption electrospray ionization mass spectrometry imaging (AFADESI-MSI) and network pharmacology are used to investigate the pharmacodynamics and mechanism underlying the herbal combination consisting of Radix ginseng-Schisandra chinensis (RS) in a rodent model for Alzheimer's disease (AD). Brain histopathological findings suggested that RS attenuates hippocampal damage in AD mice, making this combination a potential AD treatment. Twenty-eight biomarkers were identified by spatial metabolomics analysis, which are intricately linked to neuroinflammation, neurotransmitter imbalance, energy deficiency, oxidative stress, and aberrant fatty acid metabolism in AD. The total extract of RS (TE) affected 22 of these biomarkers, with the small molecule components of RS (SN) significantly influencing 19 and the large molecule components of RS (PR) impacting 14. Nine small molecule components are likely to dominate the pharmacodynamics of RS. We constructed a target interaction network based on the corresponding bioactivities that revealed relationships amongst 11 key biomarkers, 8 active ingredients and 12 critical targets. This research illustrates the immense potential of spatial metabolomics and network pharmacology in the study of TCM, revealing the targets and mechanisms underlying herbal formulas.

Screening of key immune-related gene in Parkinson's disease based on WGCNA and machine learning. / 基于WGCNAå’Œæœºå™¨å­¦ä¹ ç­›é€‰å¸•é‡‘æ£®ç— å ç–«ç›¸å ³å ³é”®åŸºå› .

OBJECTIVES: Abnormal immune system activation and inflammation are crucial in causing Parkinson's disease. However, we still don't fully understand how certain immune-related genes contribute to the disease's development and progression. This study aims to screen key immune-related gene in Parkinson's disease based on weighted gene co-expression network analysis (WGCNA) and machine learning. METHODS: This study downloaded the gene chip data from the Gene Expression Omnibus (GEO) database, and used WGCNA to screen out important gene modules related to Parkinson's disease. Genes from important modules were exported and a Venn diagram of important Parkinson's disease-related genes and immune-related genes was drawn to screen out immune related genes of Parkinson's disease. Gene ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to analyze the the functions of immune-related genes and signaling pathways involved. Immune cell infiltration analysis was performed using the CIBERSORT package of R language. Using bioinformatics method and 3 machine learning methods [least absolute shrinkage and selection operator (LASSO) regression, random forest (RF), and support vector machine (SVM)], the immune-related genes of Parkinson's disease were further screened. A Venn diagram of differentially expressed genes screened using the 4 methods was drawn with the intersection gene being hub nodes (hub) gene. The downstream proteins of the Parkinson's disease hub gene was identified through the STRING database and a protein-protein interaction network diagram was drawn. RESULTS: A total of 218 immune genes related to Parkinson's disease were identified, including 45 upregulated genes and 50 downregulated genes. Enrichment analysis showed that the 218 genes were mainly enriched in immune system response to foreign substances and viral infection pathways. The results of immune infiltration analysis showed that the infiltration percentages of CD4+ T cells, NK cells, CD8+ T cells, and B cells were higher in the samples of Parkinson's disease patients, while resting NK cells and resting CD4+ T cells were significantly infiltrated in the samples of Parkinson's disease patients. ANK1 was screened out as the hub gene. The analysis of the protein-protein interaction network showed that the ANK1 translated and expressed 11 proteins which mainly participated in functions such as signal transduction, iron homeostasis regulation, and immune system activation. CONCLUSIONS: This study identifies the Parkinson's disease immune-related key gene ANK1 via WGCNA and machine learning methods, suggesting its potential as a candidate therapeutic target for Parkinson's disease.

Lipoproteins and metabolites in diagnosing and predicting Alzheimer's disease using machine learning.

BACKGROUND: Alzheimer's disease (AD) is a chronic neurodegenerative disorder that poses a substantial economic burden. The Random forest algorithm is effective in predicting AD; however, the key factors influencing AD onset remain unclear. This study aimed to analyze the key lipoprotein and metabolite factors influencing AD onset using machine-learning methods. It provides new insights for researchers and medical personnel to understand AD and provides a reference for the early diagnosis, treatment, and early prevention of AD. METHODS: A total of 603 participants, including controls and patients with AD with complete lipoprotein and metabolite data from the Alzheimer's disease Neuroimaging Initiative (ADNI) database between 2005 and 2016, were enrolled. Random forest, Lasso regression, and CatBoost algorithms were employed to rank and filter 213 lipoprotein and metabolite variables. Variables with consistently high importance rankings from any two methods were incorporated into the models. Finally, the variables selected from the three methods, with the participants' age, sex, and marital status, were used to construct a random forest predictive model. RESULTS: Fourteen lipoprotein and metabolite variables were screened using the three methods, and 17 variables were included in the AD prediction model based on age, sex, and marital status of the participants. The optimal random forest modeling was constructed with "mtry" set to 3 and "ntree" set to 300. The model exhibited an accuracy of 71.01%, a sensitivity of 79.59%, a specificity of 65.28%, and an AUC (95%CI) of 0.724 (0.645-0.804). When Mean Decrease Accuracy and Gini were used to rank the proteins, age, phospholipids to total lipids ratio in intermediate-density lipoproteins (IDL_PL_PCT), and creatinine were among the top five variables. CONCLUSIONS: Age, IDL_PL_PCT, and creatinine levels play crucial roles in AD onset. Regular monitoring of lipoproteins and their metabolites in older individuals is significant for early AD diagnosis and prevention.

Deciphering the environmental adaptation and functional trait of core and noncore bacterial communities in impacted coral reef seawater.

Microorganisms play pivotal roles in different biogeochemical cycles within coral reef waters. Nevertheless, our comprehension of the microbially mediated processes following environmental perturbation is still limited. To gain a deeper insight into the environmental adaptation and nutrient cycling, particularly within core and noncore bacterial communities, it is crucial to understand reef ecosystem functioning. In this study, we delved into the microbial community structure and function of seawater in a coral reef under different degrees of anthropogenic disturbance. To achieve this, we harnessed the power of 16S rRNA gene high-throughput sequencing and metagenomics techniques. The results showed that a continuous temporal succession but little spatial heterogeneity in the bacterial communities of core and noncore taxa and functional profiles involved in nitrogen (N) and phosphorus (P) cycling. Eutrophication state (i.e., nutrient concentration and turbidity) and temperature played pivotal roles in shaping both the microbial community composition and functional traits of coral reef seawater. Within this context, the core subcommunity exhibited a remarkably broader habitat niche breadth, stronger phylogenetic signal and lower environmental sensitivity when compared to the noncore taxa. Null model analysis further revealed that the core subcommunity was governed primarily by stochastic processes, while deterministic processes played a more significant role in shaping the noncore subcommunity. Furthermore, our observations indicated that changes in function related to N cycling were correlated to the variations in noncore taxa, while core taxa played a more substantial role in critical processes such as P cycling. Collectively, these findings facilitated our knowledge about environmental adaptability of core and noncore bacterial taxa and shed light on their respective roles in maintaining diverse nutrient cycling within coral reef ecosystems.

Antibiotic resistance and virulence genes in Helicobacter pylori strains isolated from children in Shanghai, China (2019-2022).

BACKGROUND: The increasing prevalence of antibiotic-resistant Helicobacter pylori strains poses a significant threat to children's health. This study investigated antibiotic resistance rates in Helicobacter pylori strains isolated from children in Shanghai and analyzed the presence of virulence genes in these strains. METHODS: We obtained 201 Helicobacter pylori strains from pediatric patients with upper gastrointestinal symptoms who underwent gastrointestinal endoscopy between 2019 and 2022. Subsequently, we performed antibiotic susceptibility tests and virulence gene PCR assays on these strains. RESULTS: Helicobacter pylori resistance rates of 45.8%, 15.4%, 1.0%, and 2.5% were detected for metronidazole, clarithromycin, amoxicillin, and levofloxacin, respectively. Among all isolates, 64.7% exhibited resistance to at least one antibiotic. Resistance to metronidazole and clarithromycin increased from 2019 to 2022. The predominant vacA gene subtype was vacA s1a/m2. The prevalence of vacA m2 and dupA exhibited an upward trend, while oipA presented a decreasing trend from 2019 to 2022. The prevalence of dupA was significantly higher in gastritis than peptic ulcer disease, and in non-treatment compared to treatment groups. CONCLUSIONS: Helicobacter pylori antibiotic resistance remains high in children and has risen in recent years. Therefore, the increasing use of metronidazole and clarithromycin requires increased monitoring in children. No association was observed between antibiotic resistance and virulence gene phenotypes.

Bisphenol S exposed changes in intestinal microflora and metabolomics of freshwater crayfish, Procambarus clarkii.

Bisphenol S (BPS), a typical endocrine-disrupting chemical (EDC), can cause hepatopancreas damage and intestinal flora disturbance. Comprehensive studies on the mechanisms of acute toxicity in crustaceans are lacking. In this study, 16S rRNA and liquid chromatography were used to investigate intestinal microbiota and metabolites of freshwater crayfish (Procambarus clarkii). In this study, freshwater crayfish were exposed to BPS (10 µg/L and 100 µg/L). The results showed a significant decrease in catalase (CAT) and superoxide dismutase (SOD) activities after exposure to BPS, which inhibited the Nrf2-Keap1 signaling pathway and induced oxidative stress toxicity in freshwater crayfish. In addition, BPS exposure induced the structural changes of intestinal microbial in the freshwater crayfish, showing different patterns of effects. The number of potentially pathogenic bacteria increased, such as Citrobacter, Hafnia-Obesumbacterium, and RsaHf231. A total of 128 different metabolites were analyzed by LC-MS/MS. The inositol and leukotriene (LT) contents in the hepatopancreas of freshwater crayfish were significantly decreased after 10 µg/L BPS exposure, which in turn led to the accumulation of lipids causing hepatopancreas damage. In conclusion, when the concentration of BPS in the water environment exceeded 10 µg/L, the freshwater crayfish intestinal microbiota was dysbiosis and the hepatopancreas metabolism was disturbed.

Effects of replacing fishmeal with soybean meal on the immune and antioxidant capacity, and intestinal metabolic functions of red swamp crayfish Procambarus clarkii.

Excess utilization of plant protein sources in animal feed has been found to adversely affect the antioxidant properties and immunity of animals. While the role of gut microbes in plant protein-induced inflammation has been identified in various models, the specific mechanisms regulating gut microbes in crustaceans remain unclear. Accordingly, this study was designed to investigate the effects of replacing fishmeal with soybean meal (SM) on the hepatopancreas antioxidant and immune capacities, and gut microbial functions of crayfish, as well as the potential microbial regulatory mechanisms. 750 crayfish (4.00 g) were randomly divided into five groups: SS0, SS25, SS50, SS75, and SS100, and fed diets with different levels of soybean meal substituted for fishmeal for six weeks. High SM supplementation proved detrimental to maintaining hepatopancreas health, as indicated by an increase in hemolymph MDA content, GPT, and GOT activities, the observed rupture of hepatopancreas cell basement membranes, along with the decreased number of hepatopancreatic F cells. Moreover, crayfish subjected to high SM diets experienced obvious inflammation in hepatopancreas, together with up-regulated mRNA expression levels of nfkb, alf, and tlr (p<0.05), whereas the lzm mRNA expression level exhibited the highest value in the SS25 group. Furthermore, hepatopancreas antioxidant properties highly attenuated by the level of dietary SM substitution levels, as evidenced by the observed increase in MDA content (p<0.05), decrease in GSH content (p<0.05), and inhabitation of SOD, CAT, GPx, and GST activities (p<0.05), along with down-regulated hepatopancreas cat, gpx, gst, and mmnsod mRNA expression levels via inhibiting nrf2/keap1 pathway. Functional genes contributing to metabolism identified that high SM diets feeding significantly activated lipopolysaccharide biosynthesis, revealing gut dysfunction acted as the cause of inflammation. The global microbial co-occurrence network further indicated that the microbes contributing more to serum indicators and immunity were in module eigengene 17 (ME17). A structural equation model revealed that the genes related to alf directly drove the serum enzyme activities through microbes in ME17, with OTU399 and OTU533 identified as major biomarkers and classified into Proteobacteria that secrete endotoxins. To conclude, SM could replace 25 % of fishmeal in crayfish diets without negatively affecting immunity, and antioxidant capacity. Excessive SM levels contributed to gut dysfunction and weakened the innate immune system of crayfish.

Health literacy in patients with gout: A latent profile analysis.

OBJECTIVES: Understanding the health literacy status of patients with gout diagnosis is essential for improving the health of this population. Our study aimed to investigate the latent profiles of health literacy in patients with gout and to analyze differences in characteristics across potential profiles. METHODS: This was a cross-sectional study. Eligible participants attended the Shandong Gout Medical Center, from March 2023 to May 2023 and self-reported gout diagnosis. We used the Health Literacy Scale for Patients with Gout designed and validated by our team. The scale had good reliability and validity among patients with gout. 243 patients completed the Demographic Information Questionnaire and the Health Literacy Scale for Patients with Gout. We used latent profile analysis to identify the latent profiles of gout patients' health literacy. We used Chi-square tests with Bonferroni correction to analyze differences in demographics and illness characteristics across identified profiles. RESULTS: Three profiles of patients with gout emerged (prevalence): the low literacy-low critical group (21.81%), the moderate literacy group (42.79%), and the high literacy-stable group (35.39%). The three groups differed in age, education level, monthly income, disease duration, and place of residence (P<0.01). CONCLUSIONS: The health literacy of patients with gout was heterogeneous. Healthcare professionals should adopt targeted interventions based on the characteristics of each latent health literacy profile to improve the health literacy level of patients with gout.

Machine Tool Wear Prediction Technology Based on Multi-Sensor Information Fusion.

The intelligent monitoring of cutting tools used in the manufacturing industry is steadily becoming more convenient. To accurately predict the state of tools and tool breakages, this study proposes a tool wear prediction technique based on multi-sensor information fusion. First, the vibrational, current, and cutting force signals transmitted during the machining process were collected, and the features were extracted. Next, the Kalman filtering algorithm was used for feature fusion, and a predictive model for tool wear was constructed by combining the ResNet and long short-term memory (LSTM) models (called ResNet-LSTM). Experimental data for thin-walled parts obtained under various machining conditions were utilized to monitor the changes in tool conditions. A comparison between the ResNet and LSTM tool wear prediction models indicated that the proposed ResNet-LSTM model significantly improved the prediction accuracy compared to the individual LSTM and ResNet models. Moreover, ResNet-LSTM exhibited adaptive noise reduction capabilities at the front end of the network for signal feature extraction, thereby enhancing the signal feature extraction capability. The ResNet-LSTM model yielded an average prediction error of 0.0085 mm and a tool wear prediction accuracy of 98.25%. These results validate the feasibility of the tool wear prediction method proposed in this study.