Mechanism insights into the histopathological changes of polypropylene microplastics induced gut and liver in zebrafish.

Microplastics (MPs), emerging as significant pollutants, have been consistently detected in aquatic environments, with the Yangtze River experiencing a particularly severe level of microplastic pollution, exceeding all other watersheds in China. Polypropylene (PP), the plastic most abundantly found in the middle and lower reaches of the Yangtze River Basin, has less comprehensive research results into its toxic effects. Consequently, the present investigation employed zebrafish as a model organism to delve into the toxicological impacts of polypropylene microplastics (PP-MPs) with a diameter of 5 µm across varying concentrations (300 mg/L and 600 mg/L). Using histopathological, microbiota profiling, and transcriptomic approaches, we systematically evaluated the impact of PP-MPs exposure on the intestine and liver of zebrafish. Histopathological analysis revealed that exposure to PP-MPs resulted in thinner intestinal walls, damaged intestinal mucosa, and hepatic cellular damage. Intestinal microbiota profiling demonstrated that, the richness, uniformity, diversity, and homogeneity of gut microbes significantly increased after the PP-MPs exposure at high concentration. These alterations were accompanied by shifts in the relative abundance of microbiota associated with intestinal pathologies, suggesting a profound impact on the intestinal microbial community structure. Concurrently, hepatic transcriptome analysis and RT-qPCR indicated that the downregulation of pathways and genes associated with cell proliferation regulation and DNA damage repair mechanisms contributed to hepatic cellular damage, ultimately exerting adverse effects on the liver. Correlation analysis between the intestinal microbiota and liver transcriptome profiles further highlighted significant associations between intestinal microbiota and the downregulated hepatic pathways. Collectively, these results provide novel insights into the subacute toxicological mechanisms of PP-MPs in aquatic organisms and highlight the need for further research on the ecological and health risks associated with PP-MPs pollution.

Optical and MRI Multimodal Tracing of Stem Cells In Vivo.

Stem cell therapy has shown great clinical potential in oncology, injury, inflammation, and cardiovascular disease. However, due to the technical limitations of the in vivo visualization of transplanted stem cells, the therapeutic mechanisms and biosafety of stem cells in vivo are poorly defined, which limits the speed of clinical translation. The commonly used methods for the in vivo tracing of stem cells currently include optical imaging, magnetic resonance imaging (MRI), and nuclear medicine imaging. However, nuclear medicine imaging involves radioactive materials, MRI has low resolution at the cellular level, and optical imaging has poor tissue penetration in vivo. It is difficult for a single imaging method to simultaneously achieve the high penetration, high resolution, and noninvasiveness needed for in vivo imaging. However, multimodal imaging combines the advantages of different imaging modalities to determine the fate of stem cells in vivo in a multidimensional way. This review provides an overview of various multimodal imaging technologies and labeling methods commonly used for tracing stem cells, including optical imaging, MRI, and the combination of the two, while explaining the principles involved, comparing the advantages and disadvantages of different combination schemes, and discussing the challenges and prospects of human stem cell tracking techniques.

Mechanistic insights into super-enhancer-driven genes as prognostic signatures in patients with glioblastoma.

BACKGROUND: Glioblastoma (GBM) is one of the most common malignant brain tumors in adults and is characterized by high aggressiveness and rapid progression, poor treatment, high recurrence rate, and poor prognosis. Although super-enhancer (SE)-driven genes haven been recognized as prognostic markers for several cancers, whether it can be served as effective prognostic markers for patients with GBM has not been evaluated. METHODS: We first combined histone modification data with transcriptome data to identify SE-driven genes associated with prognosis in patients with GBM. Second, we developed a SE-driven differentially expressed genes (SEDEGs) risk score prognostic model by univariate Cox analysis, KM survival analysis, multivariate Cox analysis and least absolute shrinkage and selection operator (LASSO) regression. Its reliability in predicting was verified by two external data sets. Third, through mutation analysis, immune infiltration, we explored the molecular mechanisms of prognostic genes. Next, Genomics of Drug Sensitivity in Cancer (GDSC) and the Connectivity Map (cMap) database were employed to assess different sensitivities to chemotherapeutic agents and small-molecule drug candidates between high- and low-risk patients. Finally, SEanalysis database was chosen to identify SE-driven transcription factors (TFs) regulating prognostic markers which will reveal a potential SE-driven transcriptional regulatory network. RESULTS: First, we developed a 11-gene risk score prognostic model (NCF2, MTHFS, DUSP6, G6PC3, HOXB2, EN2, DLEU1, LBH, ZEB1-AS1, LINC01265, and AGAP2-AS1) selected from 1,154 SEDEGs, which is not only an independent prognostic factor for patients, but also can effectively predict the survival rate of patients. The model can effectively predict 1-, 2- and 3-year survival of patients and was validated in external Chinese Glioma Genome Atlas (CGGA) and Gene Expression Omnibus (GEO) datasets. Second, the risk score was positively correlated with the infiltration of regulatory T cell, CD4 memory activated T cell, activated NK cell, neutrophil, resting mast cell, M0 macrophage, and memory B cell. Third, we found that high-risk patients showed higher sensitivity than low-risk patients to both 27 chemotherapeutic agents and 4 small-molecule drug candidates which might benefit further precision therapy for GBM patients. Finally, 13 potential SE-driven TFs imply how SE regulates GBM patient's prognosis. CONCLUSION: The SEDEG risk model not only helps to elucidate the impact of SEs on the course of GBM, but also provides a bright future for prognosis determination and choice of treatment for GBM patients.

The Tumor Stemness Indice mRNAsi can Act as Molecular Typing Tool for Lung Adenocarcinoma.

Due to the high heterogeneity, lung adenocarcinoma (LUAD) cannot be distinguished into precise molecular subtypes, thereby resulting in poor therapeutic effect and low 5-year survival rate clinically. Although the tumor stemness score (mRNAsi) has been shown to accurately characterize the similarity index of cancer stem cells (CSCs), whether mRNAsi can serve as an effective molecular typing tool for LUAD isn't reported to date. In this study, we first demonstrate that mRNAsi is significantly correlated with the prognosis and disease degree of LUAD patients, i.e., the higher the mRNAsi, the worse the prognosis and the higher the disease degree. Second, we identify 449 mRNAsi-related genes based on both weighted gene co-expression network analysis (WGCNA) and univariate regression analysis. Third, our results display that 449 mRNAsi-related genes can accurately distinguish the LUAD patients into two molecular subtypes: ms-H subtype (with high mRNAsi) and ms-L subtype (with low mRNAsi), particularly the ms-H subtype has a worse prognosis. Remarkably, significant differences in clinical characteristics, immune microenvironment, and somatic mutation exist between the two molecular subtypes, which might lead to the poorer prognosis of the ms-H subtype patients than that of the ms-L subtype ones. Finally, we establish a prognostic model containing 8 mRNAsi-related genes, which can effectively predict the survival rate of LUAD patients. Taken together, our work provides the first molecular subtype related to mRNAsi in LUAD, and reveals that these two molecular subtypes, the prognostic model and marker genes may have important clinical value for effectively monitoring and treating LUAD patients.

Delving into the molecular initiating event of cadmium toxification via the dose-dependent functional genomics approach in Saccharomyces cerevisiae.

Determining dose-response relationship is essential for comprehensively revealing chemical-caused effects on organisms. However, uncertainty and complexity of gene/protein interactions cause the inability of traditional toxicogenomic methods (e.g., transcriptomics, proteomics and metabolomics) to effectively establish the direct relationship between chemical exposure and genes. In this work, we built an effective dose-dependent yeast functional genomics approach, which can clearly identify the direct gene-chemical link in the process of cadmium (Cd) toxification from a genome-wide scale with wide range concentrations (0.83, 2.49, 7.48, 22.45, 67.34, 202.03 and 606.1 µM). Firstly, we identified 220 responsive strains, and found that 142, 110, 91, 34, 8, 0 and 0 responsive strains can be respectively modulated by seven different Cd exposure concentrations ranging from high to low. Secondly, our results demonstrated that these genes induced by the high Cd exposure were mainly enriched in the process of cell autophagy, but ones caused by the low Cd exposure were primarily involved in oxidative stress. Thirdly, we found that the top-ranked GO biological processes with the lowest point of departure (POD) were transmembrane transporter complex and mitochondrial respiratory chain complex III, suggesting that mitochondrion might be the toxicity target of Cd. Similarly, nucleotide excision repair was ranked first in KEGG pathway with the least POD, indicating that this dose-dependent functional genomics approach can effectively detect the molecular initiating event (MIE) of cadmium toxification. Fourthly, we identified four key mutant strains (RIP1, QCR8, CYT1 and QCR2) as biomarkers for Cd exposure. Finally, the dose-dependent functional genomics approach also performed well in identifying MIE for additional genotoxicity chemical 4-nitroquinoline-1-oxide (4-NQO) data. Overall, our study developed a dose-dependent functional genomics approach, which is powerful to delve into the MIE of chemical toxification and is beneficial for guiding further chemical risk assessment.

Delving into the Heterogeneity of Different Breast Cancer Subtypes and the Prognostic Models Utilizing scRNA-Seq and Bulk RNA-Seq.

BACKGROUND: Breast cancer (BC) is the most common malignancy in women with high heterogeneity. The heterogeneity of cancer cells from different BC subtypes has not been thoroughly characterized and there is still no valid biomarker for predicting the prognosis of BC patients in clinical practice. METHODS: Cancer cells were identified by calculating single cell copy number variation using the inferCNV algorithm. SCENIC was utilized to infer gene regulatory networks. CellPhoneDB software was used to analyze the intercellular communications in different cell types. Survival analysis, univariate Cox, least absolute shrinkage and selection operator (LASSO) regression and multivariate Cox analysis were used to construct subtype specific prognostic models. RESULTS: Triple-negative breast cancer (TNBC) has a higher proportion of cancer cells than subtypes of HER2+ BC and luminal BC, and the specifically upregulated genes of the TNBC subtype are associated with antioxidant and chemical stress resistance. Key transcription factors (TFs) of tumor cells for three subtypes varied, and most of the TF-target genes are specifically upregulated in corresponding BC subtypes. The intercellular communications mediated by different receptor-ligand pairs lead to an inflammatory response with different degrees in the three BC subtypes. We establish a prognostic model containing 10 genes (risk genes: ATP6AP1, RNF139, BASP1, ESR1 and TSKU; protective genes: RPL31, PAK1, STARD10, TFPI2 and SIAH2) for luminal BC, seven genes (risk genes: ACTR6 and C2orf76; protective genes: DIO2, DCXR, NDUFA8, SULT1A2 and AQP3) for HER2+ BC, and seven genes (risk genes: HPGD, CDC42 and PGK1; protective genes: SMYD3, LMO4, FABP7 and PRKRA) for TNBC. Three prognostic models can distinguish high-risk patients from low-risk patients and accurately predict patient prognosis. CONCLUSIONS: Comparative analysis of the three BC subtypes based on cancer cell heterogeneity in this study will be of great clinical significance for the diagnosis, prognosis and targeted therapy for BC patients.

The accuracy and learning curve of active and passive dynamic navigation-guided dental implant surgery: An in vitro study.

OBJECTIVES: Infrared dynamic navigation systems can be categorized into active and passive based on whether the surgical instruments can emit or only reflect light. This in vitro study aimed to compare the accuracy of implant placement and the learning curve of both active and passive dynamic navigation systems, using different registration methods. METHODS: Implants (n = 704) were placed in 64 sets of models and divided into active (Yizhime, DCARER, Suzhou, China) and passive (Iris-Clinic, EPED, Kaohsiung, China) dynamic navigation groups. Both marker point-based registration (M-PBR) and feature point-based registration (F-PBR) were employed for the two groups. Based on preoperative and postoperative cone-beam computed tomography imaging, the coronal, midpoint, apical, and angular deviations were analyzed from 2D and 3D views. The operation time was recorded for each group. RESULTS: The active dynamic navigation group exhibited significantly higher accuracy than the passive dynamic navigation group (angular deviation, 4.13 ± 2.39° versus 4.62 ± 3.32°; coronal global deviation, 1.48 ± 0.60 versus 1.86 ± 1.12 mm; apical global deviation, 1.75 ± 0.81 versus 2.20 ± 1.68 mm, respectively). Significant interaction effects were observed for both registration methods and four quadrants with different dynamic navigation systems. Learning curves for the two dynamic navigation groups approached each other after 12 procedures, and finally converged after 27 procedures. CONCLUSIONS: The accuracy of active dynamic navigation system was superior to that of passive dynamic navigation system. Different combinations of dynamic navigation systems, registration methods, and implanted quadrants displayed various interactions. CLINICAL SIGNIFICANCE: Our findings could provide guidance for surgeons in choosing an appropriate navigation system in various implant surgeries. Furthermore, the time required by surgeons to master the technique was calculated. Nevertheless, there are certain limitations in this in vitro study, and therefore further research is required.

Nanosecond pulsed electric fields impair viability and mucin expression in mucinous colorectal carcinoma cell.

Nanosecond pulsed electric fields (nsPEFs) are a non-thermal technology that can induce a myriad of biological responses and changes in cellular physiology. nsPEFs have gained significant attention as a novel cancer therapy. However, studies investigating the application of nsPEF in mucinous carcinomas are scarce. In this study, we explored several biological responses in two mucinous colorectal adenocarcinoma cell lines, LS 174T and HT-29, to nsPEF treatment. We determined the overall cell survival and viability rates following nsPEF treatment using CCK-8 and colony formation assays. We measured the intracellular effects of nsPEF treatment by analyzing cell cycle distribution, cell apoptosis and mitochondrial potential. We also analyzed mucin production at both mRNA and protein levels. Our results showed that nsPEF treatment significantly reduced mucinous cell viability in a dose-dependent manner. nsPEF treatment increased cell cycles arrest at G0/G1 while the proportion of G2/M cells gradually decreased. Cell apoptosis increased following nsPEF treatment with a clear loss in mitochondrial membrane potential. Furthermore, the protein expression of functional mucin family members decreased after nsPEF treatment. In conclusion, nsPEF treatment reduced MCRC cell viability, cell proliferation, and mucin protein production while promoted apoptosis. Our work is a pilot study that projects some insights into the potential clinical applications of nsPEFs in treating mucinous colorectal carcinoma.

Molecular fingerprints of conazoles via functional genomic profiling of Saccharomyces cerevisiae.

Conazoles were designed to inhibit ergosterol biosynthesis. Conazoles have been widely used as agricultural fungicides and are frequently detected in the environment. Although conazoles have been reported to have adverse effects, such as potential carcinogenic effects, the underlying molecular mechanisms of toxicity remain unclear. Here, the molecular fingerprints of five conazoles (propiconazole (Pro), penconazole (Pen), tebuconazole (Teb), flusilazole (Flu) and epoxiconazole (Epo)) were assessed in Saccharomyces cerevisiae (yeast) via functional genome-wide knockout mutant profiling. A total of 169 (4.49%), 176 (4.67%), 198 (5.26%), 218 (5.79%) and 173 (4.59%) responsive genes were identified at three concentrations (IC50, IC20 and IC10) of Pro, Pen, Teb, Flu and Epo, respectively. The five conazoles tended to have similar gene mutant fingerprints and toxicity mechanisms. "Ribosome" (sce03010) and "cytoplasmic translation" (GO: 0002181) were the common KEGG pathway and GO biological process term by gene set enrichment analysis of the responsive genes, which suggested that conazoles influenced protein synthesis. Conazoles also affected fatty acids synthesis because "biosynthesis of unsaturated fatty acids" pathway was among the top-ranked KEGG pathways. Moreover, two genes, YGR037C (acyl-CoA-binding protein) and YCR034W (fatty acid elongase), were key fingerprints of conazoles because they played vital roles in conazole-induced toxicity. Overall, the fingerprints derived from the yeast functional genomic screening provide an alternative approach to elucidate the molecular mechanisms of environmental pollutant conazoles.

Elucidating mechanisms of toxic action of dissolved organic chemicals in oil sands process-affected water (OSPW).

Oil sands process-affected water (OSPW) is generated during extraction of bitumen in the surface-mining oil sands industry in Alberta, Canada, and is acutely and chronically toxic to aquatic organisms. It is known that dissolved organic compounds in OSPW are responsible for most toxic effects, but knowledge of the specific mechanism(s) of toxicity, is limited. Using bioassay-based effects-directed analysis, the dissolved organic fraction of OSPW has previously been fractionated, ultimately producing refined samples of dissolved organic chemicals in OSPW, each with distinct chemical profiles. Using the Escherichia coli K-12 strain MG1655 gene reporter live cell array, the present study investigated relationships between toxic potencies of each fraction, expression of genes and characterization of chemicals in each of five acutely toxic and one non-toxic extract of OSPW derived by use of effects-directed analysis. Effects on expressions of genes related to response to oxidative stress, protein stress and DNA damage were indicative of exposure to acutely toxic extracts of OSPW. Additionally, six genes were uniquely responsive to acutely toxic extracts of OSPW. Evidence presented supports a role for sulphur- and nitrogen-containing chemical classes in the toxicity of extracts of OSPW.

Searching for novel modes of toxic actions of oil spill using E. coli live cell array reporter system - A Hebei Spirit oil spill study.

Oil is a complex mixture of numerous compounds. Therefore, oil spills near shore can cause various adverse effects on coastal ecosystems. However, most toxicological assessments conducted on oil spill sites have focused on limited modes of toxic actions. In the present study, we utilized the Escherichia coli (E. coli) live cell array system (LCA) to identify novel modes of toxicities of the oil spill-affected sediments. For this purpose, sediment samples were collected from an area heavily polluted by Hebei Spirit oil spill (HSOS) incident of 2007. A total of 93 E. coli reporter genes were used to study responses to the chemicals in the mixture. E. coli K12 strains were exposed to extracts of oil or the sediment, and changes in gene expression were measured. Exposure to extracts of crude and weathered oil resulted in decreased expression in ∼30% of tested genes. However, changes in expression observed after exposure to sediment extracts varied. Sediment extracts containing large concentrations of polycyclic aromatic hydrocarbons (PAH) caused down-regulation of >70% of the genes, while extracts containing lesser total concentrations of PAHs exhibited different trends: genes involved in drug resistance were generally up-regulated, while genes responsive to DNA damage were up-regulated in only two extracts. Results suggest that oil pollution can modulate several toxic response pathways related to DNA repair and antibiotic responses. Results from LCA obtained from the sediment and oil samples were different from those observed in the H4IIE-luc assay. Toxicological implications of such observations deserve further examination. Overall, LCA is a promising tool for screening samples and identifying potential modes of toxicities of environmental samples associated with oil spills.

Functional Toxicogenomic Assessment of Triclosan in Human HepG2 Cells Using Genome-Wide CRISPR-Cas9 Screening.

There are thousands of chemicals used by humans and detected in the environment for which limited or no toxicological data are available. Rapid and cost-effective approaches for assessing the toxicological properties of chemicals are needed. We used CRISPR-Cas9 functional genomic screening to identify the potential molecular mechanism of a widely used antimicrobial triclosan (TCS) in HepG2 cells. Resistant genes at IC50 (the concentration causing a 50% reduction in cell viability) were significantly enriched in the adherens junction pathway, MAPK signaling pathway, and PPAR signaling pathway, suggesting a potential role in the molecular mechanism of TCS-induced cytotoxicity. Evaluation of the top-ranked resistant genes, FTO (encoding an mRNA demethylase) and MAP2K3 (a MAP kinase kinase family gene), revealed that their loss conferred resistance to TCS. In contrast, sensitive genes at IC10 and IC20 were specifically enriched in pathways involved with immune responses, which was concordant with transcriptomic profiling of TCS at concentrations of

Synthesis of a new inhibitor of breast cancer resistance protein with significantly improved pharmacokinetic profiles.

The design, synthesis, in vitro inhibitory potency, and pharmacokinetic (PK) profiles of Ko143 analogs are described. Compared to commonly used Ko143, the new breast cancer resistance protein (BCRP) inhibitor (compound A) showed the same potency and a significantly improved PK profile in rats (lower clearance [1.54L/h/kg] and higher bioavailability [123%]). Ko143 on the other hand suffers from poor bioavailability. Compared to Ko143, compound A would be a useful probe for delineating the role of BCRP during in vivo studies in animals.