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Microcystins (MCs) are secondary metabolites generated by cyanobacterial blooms, among which microcystin-LR (MC-LR) stands out as the most widely distributed variant in aquatic environments. However, the effects of MC-LR on the colorectum and its role in promoting colorectal tumor progression remain unclear. Therefore, this study aims to scrutinize the impact of MC-LR on a mice model of colitis-associated colorectal cancer and elucidate the potential underlying molecular mechanisms. In this study, we used AOM/DSS mice and orally administered MC-LR at doses of 40 µg/kg or 200 µg/kg. Exposure to MC-LR increased tumor burden, promoted tumor growth, shortened colon size, and decreased goblet cell numbers and tight junction protein levels in intestinal tissues. Additionally, exposure to MC-LR induced alterations in the structure of gut microbiota in the mouse colon, characterized by an increase in the relative abundance of Escherichia_coli and Shigella_sonnei, and a decline in the relative abundance of Akkermansia_muciniphila. Transcriptomic analysis revealed that MC-LR exposure activated the IL-17 signaling pathway in mouse colorectal tissues and participated in inflammation regulation and immune response. Immunofluorescence results demonstrated an increase in T-helper 17 (Th17) cell levels in mouse colorectal tumors following MC-LR exposure. The results from RT-qPCR revealed that MC-LR induced the upregulation of IL-6, IL-1β, IL-10, IL-17A, TNF-α, CXCL1, CXCL2, CXCL5 and CCL20. The novelty of this study lies in its comprehensive approach to understanding the mechanisms by which MC-LR may contribute to CRC progression, offering new perspectives and valuable reference points for establishing guidance standards regarding MC-LR in drinking water. Our findings suggest that even at guideline value, MC-LR can have profound effects on susceptible mice, emphasizing the need for a reevaluation of guideline value and a deeper understanding of the role of environmental toxins in cancer progression.

ObjectiveIn clinical practice, imaging manifestations of diffuse lung parenchymal lesions are common and indicative of various diseases, making differential diagnosis difficult. Some of these lesions are eventually diagnosed as lung cancer.MethodsBecause respiratory microorganisms play an important role in lung cancer development, we searched for microbial markers that could predict the risk of lung cancer by retrospectively analyzing the lower respiratory tract (LRT) microbiome of 158 patients who were hospitalized in the First Affiliated Hospital of Guangzhou Medical University (March 2021–March 2023) with diffuse lung parenchymal lesions. The final diagnosis was lung cancer in 21 cases, lung infection in 93 cases, and other conditions (other than malignancy and infections) in 44 cases. The patient’s clinical characteristics and the results of metagenomic next-generation sequencing of bronchoalveolar lavage fluid (BALF) were analyzed.ResultsBody mass index (BMI) and LRT microbial diversity (Shannon, Simpson, species richness, and Choa1 index) were significantly lower (P< 0.001, respectively) and Lactobacillus acidophilus relative abundance in the LRT was significantly higher (P< 0.001) in patients with lung cancer. The relative abundance of L. acidophilus in BALF combined with BMI was a good predictor of lung cancer risk (area under the curve = 0.985, accuracy = 98.46%, sensitivity = 95.24%, and specificity = 100.00%; P< 0.001).ConclusionOur study showed that an imbalance in the component ratio of the microbial community, diminished microbial diversity, and the presence of specific microbial markers in the LRT predicted lung cancer risk in patients with imaging manifestations of diffuse lung parenchymal lesions.

Microcystin-LR (MC-LR), a cyanobacterial toxin, is a potent carcinogen implicated in colorectal cancer (CRC) progression. However, its impact on the tumor microenvironment (TME) during CRC development remains poorly understood. This study investigates the interaction between tumor cells and macrophages mediated by MC-LR within the TME and its influence on CRC progression. CRC mice exposed to MC-LR demonstrated a significant transformation from adenoma to adenocarcinoma. The infiltration of macrophages increased, and the IRE1α/XBP1 pathway was activated in CRC cells after MC-LR exposure, influencing macrophage M2 polarization under co-culture conditions. Additionally, hexokinase 2 (HK2), a downstream target of the IRE1α/XBP1 pathway, was identified, regulating glycolysis and lactate production. The MC-LR-induced IRE1α/XBP1/HK2 axis enhanced lactate production in CRC cells, promoting M2 macrophage polarization. Furthermore, co-culturing MC-LR-exposed CRC cells with macrophages, along with the IRE1α/XBP1 pathway inhibitor 4μ8C and the hexokinase inhibitor 2-DG, suppressed M2 macrophage-induced CRC cell migration, clonogenicity, and M2 macrophage polarization. This study elucidates the mechanism by which MC-LR-mediated interactions through the IRE1α/XBP1 pathway promote CRC progression, highlighting potential therapeutic targets.

To ensure optimal use of images while preserving privacy, it is necessary to partition the shared image into public and private areas, with public areas being openly accessible and private areas being shared in a controlled and privacy-preserving manner. Current works only facilitate image-level sharing and use common cryptographic algorithms. To ensure efficient, controlled, and privacy-preserving image sharing at the area level, this paper proposes an image partition security-sharing mechanism based on blockchain and chaotic encryption, which mainly includes a fine-grained access control method based on Attribute-Based Access Control (ABAC) and an image-specific chaotic encryption scheme. The proposed fine-grained access control method employs smart contracts based on the ABAC model to achieve automatic access control for private areas. It employs a Cuckoo filter-based transaction retrieval technique to enhance the efficiency of smart contracts in retrieving security attributes and policies on the blockchain. The proposed chaotic encryption scheme generates keys based on the private areas' security attributes, largely reducing the number of keys required. It also provides efficient encryption with vector operation acceleration. The security analysis and performance evaluation were conducted comprehensively. The results show that the proposed mechanism has lower time overhead than current works as the number of images increases.

Microcystins (MCs), toxins generated by cyanobacteria, feature microcystin-LR (MC-LR) as one of the most prevalent and toxic variants in aquatic environments. MC-LR not only causes environmental problems but also presents a substantial risk to human health. This study aimed to investigate the impact of MC-LR on APCmin/+ mice, considered as an ideal animal model for intestinal tumors. We administered 40 µg/kg MC-LR to mice by gavage for 8 weeks, followed by histopathological examination, microbial diversity and metabolomics analysis. The mice exposed to MC-LR exhibited a significant promotion in colorectal cancer progression and impaired intestinal barrier function in the APCmin/+ mice compared with the control. Gut microbial dysbiosis was observed in the MC-LR-exposed mice, manifesting a notable alteration in the structure of the gut microbiota. This included the enrichment of Marvinbryantia, Gordonibacter and Family_XIII_AD3011_group and reductions in Faecalibaculum and Lachnoclostridium. Metabolomics analysis revealed increased bile acid (BA) metabolites in the intestinal contents of the mice exposed to MC-LR, particularly taurocholic acid (TCA), alpha-muricholic acid (α-MCA), 3-dehydrocholic acid (3-DHCA), 7-ketodeoxycholic acid (7-KDCA) and 12-ketodeoxycholic acid (12-KDCA). Moreover, we found that Marvinbryantia and Family_XIII_AD3011_group showed the strongest positive correlation with taurocholic acid (TCA) in the mice exposed to MC-LR. These findings provide new insights into the roles and mechanisms of MC-LR in susceptible populations, providing a basis for guiding values of MC-LR in drinking water.

Fracture porosity is one of the key parameters for characterizing fractured reservoirs. However, fracture porosity calculation is difficult with conventional logging data due to severe anisotropy of the reservoirs. To deal with the problem, the equivalent macroscopic anisotropic formation model based on dual laterolog (DLL) data is adopted to cyclically assign such parameters as bedrock resistivity (RB), fluid resistivity in fractures (RFL), fracture dip angle (FDA) and fracture thickness as well as fracture spacing, and to produce massive data for formation modeling. A large number of training data obtained through three dimensional finite element forward modeling and the functional relationship between DLL responses and fracture parameters that are trained and summarized by deep neural network, are combined to establish a new fast forward model for calculating DLL responses in fractured formations. A new fracture porosity inversion model for fractured reservoirs based on gradient optimization inversion algorithm combined with multi-initial inversion strategy is then proposed. While running the model, formation is divided into eight intervals according to bedrock resistivity and fracture dip angle from 0° to 90° is divided every 0.5° to improve the operation speed and efficiency. The results of numerical verification show that when bedrock resistivity is greater than 1000 Ω m, the mean absolute error (MAE) of fracture porosity inversion is 0.001658% for horizontal fractures, 0.00413% for intermediate fractures and 0.0027% for quasi-vertical fractures. When bedrock resistivity is between 100 Ω m and 1000 Ω m, MAE of fracture porosity inversion is 0.003% for horizontal fractures, 0.0034% for intermediate fractures and 0.00348% for quasi-vertical fractures. Fracture parameters determined by the fracture porosity inversion model with actual data are in good agreement with the results of micro resistivity imaging logging.

Microcystin-LR (MC-LR) is a toxic secondary metabolite produced by cyanobacteria that has been demonstrated to promote colorectal cancer (CRC). However, the mechanism by which MC-LR enhances CRC in the tumor microenvironment (TME) is poorly understood. To elucidate its role in TME, a co-culture system was established using CRC cells and M2 macrophages in a Transwell chamber. The study found that MC-LR promotes CRC cell migration by upregulating TGF-β1 expression and secretion in M2 macrophages and downregulating CST3 in CRC cells. Neutralizing TGF-β1 increased CST3 expression in CRC cells, while overexpressing CST3 in CRC cells suppressed TGF-β1 expression in M2 macrophages, both of which weakened MC-LR-induced cellular motility in the co-culture system. In vivo, the mice in the MC-LR/AOM/DSS group had more tumor nodules, deeper tumor invasion, and higher M2 macrophage infiltration compared to the AOM/DSS group, and the expression of TGF-β1 and CST3 in tumors was consistent with the cellular level. Overall, this study provides insights into the regulatory mechanism of MC-LR on TME, revealing that MC-LR upregulates the expression and secretion of TGF-β1 in M2 macrophages, which in turn inhibits the expression of CST3 in CRC cells to promote migration.

Crop rotation is a typical agronomic practice to mitigate soil deterioration caused by continuous cropping. However, the mechanisms of soil biotic and abiotic factors in response to different cropping patterns in acidic and polyphenol-rich tea nurseries remain unclear. In this study, the composition and function of microbial communities were comparatively investigated in soils of tea seedlings continuously planted for 2 years (AC: autumn-cutting; SC: summer-cutting) and in soils rotation with strawberries alternately for 3 years (AR: autumn-cutting). The results showed that AR significantly improved the survival of tea seedlings but greatly reduced the contents of soil polyphenols. The lower soil polyphenol levels in AR were associated with the decline of nutrients (SOC, TN, Olsen-P) availability, which stimulates the proliferation of nutrient cycling-related bacteria and mixed-trophic fungi, endophytic fungi and ectomycorrhizal fungi, thus further satisfying the nutrient requirements of tea seedlings. Moreover, lower levels of polyphenols facilitated the growth of plant beneficial microorganisms (Bacillus, Mortierella, etc.) and suppressed pathogenic fungi (Pseudopestalotiopsis, etc.), creating a more balanced microbial community that is beneficial to plant health. Our study broadens the understanding of the ecological role of plant secondary metabolites and provides new insights into the sustainability of tea breeding.

The evaluation of joint toxicity of mixtures is an important topic in toxicology. Previous studies have found that the parameter k∙ECx of concentration response curves (CRCs) can be used to assess the applicability of concentration addition model (CA). This study further assesses the predictability of k∙ECx on the joint toxicity evaluation. The toxicities of the twelve environmental pollutants, as well as those of binary mixtures with an equivalent-effect concentration ratio, to Vibrio fischeri were determined by using the microplate toxicity analysis. The toxicity evaluation of mixtures was conducted by CA and independent action model (IA). The relationship between the joint toxicity (measured by the relative model deviation ratio (rMDR)) and the k∙ECx was studied. The results shows that the k∙ECx could reflect the shape of CRCs in the whole concentration range. According to the IA and CA, 65% of the mixtures produce strong antagonistic or synergistic effect due to the significant difference of k∙ECx. The percentage of the relative difference of k∙ECx of components and the rMDRx can be fitted by an exponential function. Different types of interactions could be described using this function. It is suggested that the joint toxicity of binary mixtures can be assessed with the parameter k∙ECx, which can quickly get very important data when planning experiments, but also reduce the number of experiments.

Due to its high content of organics and nutrients, swine wastewater has become one of the main environment pollution sources. Exploring high-efficient technologies for swine wastewater treatment is urgent and becoming a hot topic in the recent years. The present study introduces anaerobic membrane bioreactor (AnMBR) for efficient treatment of swine wastewater, compared with up-flow anaerobic sludge blanket (UASB) as a traditional system. Pollutant removal performance, methanogenic properties, and microbial community structures were investigated in both reactors. Results showed that by intercepting particulate organics, AnMBR achieved stable and much higher chemical oxygen demand (COD) removal rate (approximately 90%) than UASB (around 60%). Due to higher methanogenic activity of anaerobic sludge, methane yield of AnMBR (0.23 L/g-COD) was higher than that of UASB. Microbial community structure analysis showed enrichment of functional bacteria that can remove refractory organic matter in the AnMBR, which promoted the organics conversion processes. In addition, obvious accumulation of acetotrophic and hydrotrophic methanogens in AnMBR system was recorded, which could broaden the organic matter degradation pathways and the methanogenesis processes, ensuring a higher methane yield. Through energy balance analysis, results concluded that the net energy recovery efficiency of AnMBR was higher than that of UASB system, indicating that applying AnMBR for livestock wastewater treatment could not only efficiently remove pollutants, but also significantly enhance the energy recovery.

The effects of calcium cyanamide on the soil fungal communities in successive tea-cuttings nursery soils were investigated based on Illumina high-throughput sequencing. The field experiment was carried out with three treatments, including control (CK), flooding (F) and calcium cyanamide (CC). The treatment with calcium cyanamide increased pH (~1 unit) and reduced the accumulation of phenols (~50%), available phosphorus (~28%) and exchangeable Al (~90%) significantly, and improved soil quality. The predominant phylum in all treatments was Ascomycota. FUNGuild revealed that the dominant trophic mode was saprotrophy in tea-cuttings nursery soil. Plant pathogens had a low abundance in the calcium cyanamide treatment. Alpha diversity analysis showed lower richness in the calcium cyanamide than the other treatments. Network analysis showed a poorly connected but highly modularized network in the calcium cyanamide treatment, with the crucial OTUs functions related to anti-pathogenicity. The results showed that calcium cyanamide should be recommended for improving long-term tea nurseries by increasing the survival rate of tea seedlings due to increasing soil pH value, reducing aluminum toxicity, decreasing the accumulation of polyphenols, diminishing pathogenic fungi and making the taxa related to anti-pathogenicity occupy a more important niche.

Tea is an important beverage in humans’ daily lives. For a long time, tea grade identification relied on sensory evaluation, which requires professional knowledge, so is difficult and troublesome for laypersons. Tea chemical component detection usually involves a series of procedures and multiple steps to obtain the final results. As such, a simple, rapid, and reliable method to judge the quality of tea is needed. Here, we propose a quick method that combines ultraviolet (UV) spectra and color difference to classify tea. The operations are simple and do not involve complex pretreatment. Each method requires only a few seconds for sample detection. In this study, famous Chinese green tea, Huangshan Maofeng, was selected. The traditional detection results of tea chemical components could not be used to directly determine tea grade. Then, digital instrument methods, UV spectrometry and colorimetry, were applied. The principal component analysis (PCA) plots of the single and combined signals of these two instruments showed that samples could be arranged according to grade. The combined signal PCA plot performed better with the sample grade descending in clockwise order. For grade prediction, the random forest (RF) model produced a better effect than the support vector machine (SVM) and the SVM + RF model. In the RF model, the training and testing accuracies of the combined signal were all 1. The grades of all samples were correctly predicted. From the above, the UV spectrum combined with color difference can be used to quickly and accurately classify the grade of Huangshan Maofeng tea. This method considerably increases the convenience of tea grade identification.

Dipeptidyl peptidase IV (DPP-IV) inhibitors occupy a growing place in the drugs used for the management of type 2 diabetes. Recently, food components, including food-derived bioactive peptides, have been suggested as sources of DPP-IV inhibitors without side effects. Chinese black tea is a traditional health beverage, and it was used for finding DPP-IV inhibitory peptides in this study. The ultra-filtrated fractions isolated from the aqueous extracts of black tea revealed DPP-IV inhibitory activity in vitro. Four peptides under 1 kDa were identified by SDS-PAGE and LC-MS/MS (Liquid Chromatography-Mass Spectrometry-Mass Spectrometry) from the ultra-filtrate. The peptide II (sequence: AGFAGDDAPR), with a molecular mass of 976 Da, showed the greatest DPP-IV inhibitory activity (in vitro) among the four peptides. After administration of peptide II (400 mg/day) for 57 days to streptozotocin (STZ)-induced hyperglycemic mice, the concentration of glucagon-like peptide-1 (GLP-1) in the blood increased from 9.85 ± 1.96 pmol/L to 19.22 ± 6.79 pmol/L, and the insulin level was increased 4.3-fold compared to that in STZ control mice. Immunohistochemistry revealed the improved function of pancreatic beta-cells and suppressed proliferation of pancreatic alpha-cells. This study provides new insight into the use of black tea as a potential resource of food-derived DPP-IV inhibitory peptides for the management of type 2 diabetes.