An extra honey polyphenols-rich diet ameliorates the high-fat diet induced chronic kidney disease via modulating gut microbiota in C57BL/6 mice.

Honey is not equivalent to sugar and possess a worldwide health promoting effects such as antioxidant, antibacterial, anti-inflammatory, and hepatoprotective activities. Nevertheless, the potential impacts of honey on high-fat diet induced chronic kidney disease (CKD) and gut microbiota remain to be explored. Herein a high-fat diet was used to induce a mouse CKD model, and analysis was conducted on liver, kidney, spleen indices, tissue morphology, biochemical parameters, CKD related genes, and gut microbial diversity. The results indicated that significant inhibitory effects on renal damage caused by a high-fat diet in mice and improvement in disease symptoms were observed upon honey treatment. Significant changes were also found in serum TC, TG, UA, and BUN as well as the inflammation-related protein TNF-α and IL-6 levels in renal tissues. Gene expression analysis revealed that honey intake closely relates to gut microbiota diversity, which can regulate the composition of gut microbiota, increase microbial diversity, especially Bifidobacteriales and S24_7 and promote the synthesis of short chain fatty acids (SCFAs). In summary, this study suggests that honey has both preventive and therapeutic effects on CKD, which may be associated with its ability to improve microbial composition, increase microbial diversity, and regulate SCFAs levels.

m6A methyltransferase METTL14­mediated RP1­228H13.5 promotes the occurrence of liver cancer by targeting hsa­miR­205/ZIK1.

The aim of the present study was to explore the association between N6­methyladenosine (m6A) modification regulatory gene­related long noncoding (lnc)RNA RP1­228H13.5 and cancer prognosis through bioinformatics analysis, as well as the impact of RP1­228H13.5 on cell biology­related behaviors and specific molecular mechanisms. Bioinformatics analysis was used to construct a risk model consisting of nine genes. This model can reflect the survival time and differentiation degree of cancer. Subsequently, a competing endogenous RNA network consisting of 3 m6A­related lncRNAs, six microRNAs (miRs) and 201 mRNAs was constructed. A cell assay confirmed that RP1­228H13.5 is significantly upregulated in liver cancer cells, which can promote liver cancer cell proliferation, migration and invasion, and inhibit liver cancer cell apoptosis. The specific molecular mechanism may be the regulation of the expression of zinc finger protein interacting with K protein 1 (ZIK1) by targeting the downstream hsa­miR­205. Further experiments found that the m6A methyltransferase 14, N6­adenosine­methyltransferase subunit mediates the regulation of miR­205­5p expression by RP1­228H13.5. m6A methylation regulatory factor­related lncRNA has an important role in cancer. The targeting of hsa­miR­205 by RP1­228H13.5 to regulate ZIK1 may serve as a potential mechanism in the occurrence and development of liver cancer.

Lignite-steel slag constructed wetland with multi-functionality and effluent reuse.

Constructed wetlands (CWs) are widely used to treat wastewater, while innovative studies are needed to support resource conservation, enhance multi-functionality, and improve the effectiveness of effluent usage. This study assessed the potential of CW's multiple functions by combining low-rank coal (lignite) and industrial waste (steel slag) in different configurations as CW substrates. The results of scanning electron microscope (SEM), energy dispersive spectroscopy (EDS), X-ray photoelectron spectroscopy (XPS), and metagenomic sequencing showed that the experimental treatment with lignite and steel slag mixtures had the highest multi-functionality, including efficient nutrient removal and carbon sequestration, as well as hydroponic crop production. Lignite and steel slag were mixed to form lignite-steel slag particle clusters, where Ca2+ dissolved on the surface of steel slag was combined with PO43- in wastewater to form Ca3(PO4)2 precipitation for phosphorus removal. A biofilm grew on the surface of lignite in this cluster, and OH- released from steel slag promoted lignite to release fulvic acid, which provided a carbon source for heterotrophic microorganisms and promoted denitrification. Moreover, fulvic acid enhanced carbon sequestration in CWs by increasing the biomass of Phragmites australis. The effluent from lignite-steel slag CW increased cherry tomato yield and quality while saving N and P applications. These results provide new ideas for the "green" and economic development of CW technology.

Different cervical vertebral bone quality scores for bone mineral density assessment for the patients with cervical degenerative disease undergoing ACCF/ACDF: computed tomography and magnetic resonance imaging-based study.

BACKGROUND: Bone mineral density (BMD) is important for the outcome of cervical spine surgery. As the gold standard of assessing BMD, dual-energy X-ray absorptiometry scans are often not ordered or go unreviewed in patients' charts. As the supplement, MRI-based vertebral bone quality (VBQ) was found to accurately predict osteopenia/osteoporosis and postoperative complications in lumbar spine. However, discussion of the efficiency of VBQ in cervical spine is lacking. And measurement methods of VBQ in cervical spine are diverse and not universally acknowledged like lumbar spine. We aimed to compare the predictive performance of three kinds of different Cervical-VBQ (C-VBQ) scores for bone mineral density assessment in patients undergoing cervical spine surgery. HU value of cervical spine was set as a reference. METHODS: Adult patients receiving cervical spine surgery for degenerative diseases were retrospectively included between Jan 2015 and Dec 2022 in our hospital. The VBQ scores and HU value were measured from preoperative MRI and CT. The correlation between HU value/C-VBQs (named C-VBQ1/2/3 according to different calculating methods) and DEXA T-score was analyzed using univariate linear correlation and Pearson's correlation. We evaluated the predictive performance of those two parameters and achieved the most appropriate cutoff value by comparing the receiver operating characteristic (ROC) curves. RESULTS: 106 patients (34 patients with T ≥ - 1.0 vs 72 patients with T < - 1.0) were included (mean age: 51.95 ± 10.94, 48 men). According to Pearson correlation analysis, C-VBQ1/2/3 and HU value were all significantly correlated to DEXA T-score (Correlation Coefficient (r): C-VBQ1: - 0.393, C-VBQ2: - 0.368, C-VBQ3: - 0.395, HU value: 0.417, p < 0.001). The area under the ROC curve (AUC) was calculated (C-VBQ1: 0.717, C-VBQ2: 0.717, C-VBQ3: 0.727, HU value: 0.746). The AUC of the combination of C-VBQ3 and HU value was 0.786. At last, the most appropriate cutoff value was determined (C-VBQ1: 3.175, C-VBQ2: 3.005, C-VBQ3: 2.99, HU value: 299.85 HU). CONCLUSIONS: Different MRI-based C-VBQ scores could all be potential and alternative tools for opportunistically screening patients with osteopenia and osteoporosis before cervical spine surgery. Among them, C-VBQ calculated in ASIC2-C7/SIT1-CSF performed better. We advised patients with C-VBQ higher than cutoff value to accept further BMD examination.

Negative regulation of tobacco cold stress tolerance by NtPhyA.

Cold stress is a non-biological stressor that adversely affects tobacco yield and leaf quality. Plant photoreceptor proteins, which function as dual light-temperature sensors, play a vital role in temperature changes, making them crucial for responses to non-biological stressors. However, the regulatory mechanisms of PhyA in tobacco remain poorly understood. Therefore, in this study, we aimed to clone the NtPhyA gene from tobacco and generate overexpression (OE-NtPhyA) and mutant (KO-NtPhyA) constructs of NtPhyA. By assessing the physiological and biochemical responses of the mutants under cold stress and performing transcriptome sequencing, we determined the signalling mechanism of NtPhyA under cold stress. Comparative analysis with wild-type (WT) NtPhyA revealed that KO-NtPhyA exhibited increased seed germination rates and reduced wilting under cold stress. In additional, the degree of damage to leaf cells, cell membranes, and stomatal structures was mitigated, and the levels of reactive oxygen species (ROS) were significantly decreased. Antioxidant enzyme activity, net photosynthetic rate, and Fv/Fm were significantly enhanced in KO-NtPhyA, whereas the opposite effects were observed in OE-NtPhyA. These findings indicate that KO-NtPhyA augments tobacco tolerance to cold stress, implying a negative regulatory role of NtPhyA in tobacco during cold stress. Transcriptome analysis revealed that NtPhyA governs the expression of a cascade of genes involved in the response to oxygen-containing compounds, hydrogen peroxide (H2O2), ROS, temperature stimuli, photosystem II oxygen-evolving complex assembly, water channel activity, calcium channel activity, and carbohydrate transport. Collectively, our findings indicate that NtPhyA activates downstream gene expression to enhance the resilience of tobacco to cold stress.

HER-2 Expression in Colorectal Cancer and Its Correlation with Immune Cell Infiltration.

BACKGROUND: This study aimed to investigate the effect of increased HER-2 expression on tumor-infiltrating lymphocytes (TILs) and determine its impact on the prognosis of colorectal cancer (CRC) patients; Methods: HER-2, CD4, CD8, CD19, LY6G, CD56, CD68, CD11b, and EpCam expression in CRC tissues and adjacent paracancerous tissues were assessed using multiplex fluorescence immunohistochemical staining. The correlation between HER-2 expression and the number of TILs in CRC tissues was analyzed. Kaplan-Meier and Cox proportional hazards models were used to analyze survival outcomes; Results: The expression of HER-2 in tumor tissues was higher than that in paracancerous tissues (1.31 ± 0.45 vs. 0.86 ± 0.20, p < 0.05). Additionally, there was an increase in the numbers of CD4+, CD8+, CD19+, and CD68+ cells in CRC tissues (14.11 ± 1.10 vs. 3.40 ± 0.18, p < 0.005; 0.16 ± 0.12 vs. 0.04 ± 0.04, p < 0.005; 0.71 ± 0.46 vs. 0.25 ± 0.13, p < 0.0005; 0.27 ± 0.24 vs. 0.03 ± 0.11, p < 0.05). An increase in HER-2 expression was positively correlated with an increase in CD4, CD8, and CD19 (p < 0.0001). In HER-2-positive CRC tissues, CD68 expression was increased (0.80 ± 0.55 vs. 0.25 ± 0.22, p < 0.05). In HER-2-upregulated CRC tissues, CD4, CD8, CD19, CD68, CD11b, Ly6G, and CD56 expressions were elevated (0.70 ± 0.37 vs. 0.32 ± 0.17, p = 0.03; 0.22 ± 0.13 vs. 0.09 ± 0.06, p = 0.03; 0.31 ± 0.19 vs. 0.12 ± 0.08, p = 0.02; 1.05 ± 0.62 vs. 0.43 ± 0.21, p < 0.01; 1.34 ± 0.81 vs. 0.53 ± 0.23, p < 0.01; 0.50 ± 0.31 vs. 0.19 ± 0.10, p < 0.01; 1.26 ± 0.74 vs. 0.52 ± 0.24, p < 0.01). Furthermore, increased HER-2 expression was an independent risk factor for recurrence-free survival (RFS) in patients (p < 0.01, HR = 3.421); Conclusions: The increased expression of HER-2 and its relationship with immune cells will provide new insights for immunotherapy in CRC patients.

Identification and validation of a necroptosis-related gene prognostic signature for colon adenocarcinoma.

Background: Necroptosis is a novel programmed cell death pathway proposed in 2005, which is mainly activated by the tumor necrosis factor (TNF) family and mediates cellular disassembly via receptor interacting serine/threonine kinase 1 (RIPK1), receptor interacting serine/threonine kinase 3 (RIPK3) and mixed lineage kinase domain like pseudokinase (MLKL). We tried to analyze the relationship of necroptosis-related genes (NRGs) expression with colon adenocarcinoma (COAD) and propose potential therapeutic targets through immunological analysis. Methods: First, we evaluated the expression of NRGs in COAD patients and constructed a prognostic signature. The prognostic signature was validated using The Cancer Genome Atlas (TCGA)-COAD and GSE39582 datasets, respectively. And the Kaplan-Meier analysis, receiver operating characteristic (ROC) curves, and principal component analysis were used to evaluate the signature. Then we analyzed the enrichment of NRGs in the signature using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Finally, we analyzed the immunological characteristics of the COAD patients by single sample gene set enrichment analysis (ssGSEA) and predicted the possible immune checkpoints. Results: We constructed a prognostic signature with 8 NRGs (RIPK3, MLKL, TRAF2, CXCL1, RBCK1, CDKN2A, JMJD7-PLA2G4B and CAMK2B). The Kaplan-Meier analysis, ROC curves, and principal component analysis demonstrated good predictivity of the signature. In addition, we constructed a nomogram with good individualized predictive ability (C-index =0.772). The immunological analysis revealed that the prognosis of COAD was associated with autoimmune function, and we proposed 10 potential therapeutic targets. Conclusions: Overall, we constructed an NRGs prognostic signature and suggested potential therapeutic targets for the COAD treatment.

JARID2 coordinates with the NuRD complex to facilitate breast tumorigenesis through response to adipocyte-derived leptin.

BACKGROUND: Proteins containing the Jumonji C (JmjC) domain participated in tumorigenesis and cancer progression. However, the mechanisms underlying this effect are still poorly understood. Our objective was to investigate the role of Jumonji and the AT-rich interaction domain-containing 2 (JARID2) - a JmjC family protein - in breast cancer, as well as its latent association with obesity. METHODS: Immunohistochemistry, The Cancer Genome Atlas, Gene Expression Omnibus, and other databases were used to analyze the expression of JARID2 in breast cancer cells. Growth curve, 5-ethynyl-2-deoxyuridine (EdU), colony formation, and cell invasion experiments were used to detect whether JARID2 affected breast cancer cell proliferation and invasion. Spheroidization-based experiments and xenotumor transplantation in NOD/SCID mice were used to examine the association between JARID2 and breast cancer stemness. RNA-sequencing, Kyoto Encyclopedia of Genes and Genomes, and Gene Set Enrichment Analysis were used to identify the cell processes in which JARID2 participates. Immunoaffinity purification and silver staining mass spectrometry were conducted to search for proteins that might interact with JARID2. The results were further verified using co-immunoprecipitation and glutathione S-transferase (GST) pull-down experiments. Using chromatin immunoprecipitation (ChIP) sequencing, we sought the target genes that JARID2 and metastasis-associated protein 1 (MTA1) jointly regulated; the results were validated by ChIP-PCR, quantitative ChIP (qChIP) and ChIP-reChIP assays. A coculture experiment was used to explore the interactions between breast cancer cells and adipocytes. RESULTS: In this study, we found that JARID2 was highly expressed in multiple types of cancer including breast cancer. JARID2 promoted glycolysis, lipid metabolism, proliferation, invasion, and stemness of breast cancer cells. Furthermore, JARID2 physically interacted with the nucleosome remodeling and deacetylase (NuRD) complex, transcriptionally repressing a series of tumor suppressor genes such as BRCA2 DNA repair associated (BRCA2), RB transcriptional corepressor 1 (RB1), and inositol polyphosphate-4-phosphatase type II B (INPP4B). Additionally, JARID2 expression was regulated by the obesity-associated adipokine leptin via Janus kinase 2/signal transducer and activator of transcription 3 (JAK2/STAT3) pathway in the breast cancer microenvironment. Analysis of various online databases also indicated that JARID2/MTA1 was associated with a poor prognosis of breast cancer. CONCLUSION: Our data indicated that JARID2 promoted breast tumorigenesis and development, confirming JARID2 as a target for cancer treatment.

Development of prediction model to estimate future risk of ovarian lesions: A multi-center retrospective study.

Background: To develop the preoperative prediction of ovarian lesions using regression-based statistics analyses and machine learning methods based on multiple serological biomarkers in China. Methods: 1137 patients with ovarian lesions in Zhujiang Hospital and 518 patients in others hospital in China were randomly assigned to training, test and external validation cohorts. Five machine learning classifiers, including Random Forest (RF), Extreme Gradient Boosting (XGB), Support Vector Classifier (SVC), K-nearest Neighbor (KN), Multi-Layer Perceptron (MLP) and the Lasso-Logistics prediction model (LLRM) were used to derive diagnostic information from 23 predictors. Results: The RF model had a high diagnostic value (AUC = 0.968) in predicting benign and malignant ovarian disease. Age and MLR were also potential diagnostic indicators for predicting ovarian disease except tumor indicators. The RF model well distinguished borderline ovarian tumors (AUC = 0.742). The RFM had a high predictive power to identify ovarian serous adenocarcinoma (AUC = 0.943) and ovarian endometriosis cysts (AUC = 0.914). Conclusions: The RF models can effectively predict adnexal lesions, promising to be adjuncts to the preoperative prediction of ovarian cancer.

Identifying key transcription factors and immune infiltration in non-small-cell lung cancer using weighted correlation network and Cox regression analyses.

Introduction: Lung cancer is one of the most common cancers and a significant cause of cancer-related deaths. Non-small cell lung cancer (NSCLC) accounts for about 85% of all lung cancer cases. Therefore, it is crucial to identify effective diagnostic and therapeutic methods. In addition, transcription factors are essential for eukaryotic cells to regulate their gene expression, and aberrant expression transcription factors are an important step in the process of oncogenesis in NSCLC. Methods: Differentially expressed transcription factors between NSCLC and normal tissues by analyzing mRNA profiling from The Cancer Genome Atlas (TCGA) database program were identified. Weighted correlation network analysis (WGCNA) and line plot of least absolute shrinkage and selection operator (LASSO) were performed to find prognosis-related transcription factors. The cellular functions of transcription factors were performed by 5-ethynyl-2'-deoxyuridine (EdU) assay, wound healing assay, cell invasion assay in lung cancer cells. Results: We identified 725 differentially expressed transcription factors between NSCLC and normal tissues. Three highly related modules for survival were discovered, and transcription factors highly associated with survival were obtained by using WGCNA. Then line plot of LASSO was applied to screen transcription factors related to prognosis and build a prognostic model. Consequently, SETDB2, SNAI3, SCML4, and ZNF540 were identified as prognosis-related transcription factors and validated in multiple databases. The low expression of these hub genes in NSCLC was associated with poor prognosis. The deletions of both SETDB2 and SNAI3 were found to promote proliferation, invasion, and stemness in lung cancer cells. Furthermore, there were significant differences in the proportions of 22 immune cells between the high- and low-score groups. Discussion: Therefore, our study identified the transcription factors involved in regulating NSCLC, and we constructed a panel for the prediction of prognosis and immune infiltration to inform the clinical application of transcription factor analysis in the prevention and treatment of NSCLC.

Pharmacological inhibition of LSD1 suppresses growth of hepatocellular carcinoma by inducing GADD45B.

Lysine-specific histone demethylase 1 (LSD1) is an attractive target for malignancies therapy. Nevertheless, its role in hepatocellular carcinoma (HCC) progression and the potential of its inhibitor in HCC therapy remains unclear. Here, we show that LSD1 overexpression in human HCC tissues is associated with HCC progression and poor patient survival. ZY0511, a highly selective and potent inhibitor of LSD1, suppressed human HCC cell proliferation in vitro and tumor growth in cell-derived and patient-derived HCC xenograft models in vivo. Mechanistically, ZY0511 induced mRNA expression of growth arrest and DNA damage-inducible gene 45beta (GADD45B) by inducing histone H3 at lysine 4 (H3K4) methylation at the promoter of GADD45B, a novel target gene of LSD1. In human HCC tissues, LSD1 level was correlated with a decreased level of GADD45B, which was associated with HCC progression and predicted poor patient survival. Moreover, co-administration of ZY0511 and DTP3, which specifically enhanced the pro-apoptotic effect of GADD45B, effectively inhibited HCC cell proliferation both in vitro and in vivo. Collectively, our study revealed the potential value of LSD1 as a promising target of HCC therapy. ZY0511 is a promising candidate for HCC therapy through upregulating GADD45B, thereby providing a novel combinatorial strategy for treating HCC.

The PRMT6/PARP1/CRL4B Complex Regulates the Circadian Clock and Promotes Breast Tumorigenesis.

Circadian rhythms, as physiological systems with self-regulatory functions in living organisms, are controlled by core clock genes and are involved in tumor development. The protein arginine methyltransferase 6 (PRMT6) serves as an oncogene in a myriad of solid tumors, including breast cancer. Hence, the primary aim of the current study is to investigate the molecular mechanisms by which the PRMT6 complex promotes breast cancer progression. The results show that PRMT6, poly(ADP-ribose) polymerase 1 (PARP1), and the cullin 4 B (CUL4B)-Ring E3 ligase (CRL4B) complex interact to form a transcription-repressive complex that co-occupies the core clock gene PER3 promoter. Moreover, genome-wide analysis of PRMT6/PARP1/CUL4B targets identifies a cohort of genes that is principally involved in circadian rhythms. This transcriptional-repression complex promotes the proliferation and metastasis of breast cancer by interfering with circadian rhythm oscillation. Meanwhile, the PARP1 inhibitor Olaparib enhances clock gene expression, thus, reducing breast carcinogenesis, indicating that PARP1 inhibitors have potential antitumor effects in high-PRMT6 expression breast cancer.

Loss of TTC17 promotes breast cancer metastasis through RAP1/CDC42 signaling and sensitizes it to rapamycin and paclitaxel.

BACKGROUND: Breast cancer (BC) metastasis is the leading cause of poor prognosis and therapeutic failure. However, the mechanisms underlying cancer metastasis are far from clear. METHODS: We screened candidate genes related to metastasis through genome-wide CRISPR screening and high-throughput sequencing of patients with metastatic BC, followed by a panel of metastatic model assays. The effects of tetratricopeptide repeat domain 17 (TTC17) on migration, invasion, and colony formation ability together with the responses to anticancer drugs were investigated in vitro and in vivo. The mechanism mediated by TTC17 was determined by RNA sequencing, Western blotting, immunohistochemistry, and immunofluorescence. The clinical significance of TTC17 was evaluated using BC tissue samples combined with clinicopathological data. RESULTS: We identified the loss of TTC17 as a metastasis driver in BC, and its expression was negatively correlated with malignancy and positively correlated with patient prognosis. TTC17 loss in BC cells promoted their migration, invasion, and colony formation capacity in vitro and lung metastasis in vivo. Conversely, overexpressing TTC17 suppressed these aggressive phenotypes. Mechanistically, TTC17 knockdown in BC cells resulted in the activation of the RAP1/CDC42 pathway along with a disordered cytoskeleton in BC cells, and pharmacological blockade of CDC42 abolished the potentiation of motility and invasiveness caused by TTC17 silencing. Research on BC specimens demonstrated reduced TTC17 and increased CDC42 in metastatic tumors and lymph nodes, and low TTC17 expression was linked to more aggressive clinicopathologic characteristics. Through screening the anticancer drug library, the CDC42 inhibitor rapamycin and the microtubule-stabilizing drug paclitaxel showed stronger inhibition of TTC17-silenced BC cells, which was confirmed by more favorable efficacy in BC patients and tumor-bearing mice receiving rapamycin or paclitaxel in the TTC17Low arm. CONCLUSIONS: TTC17 loss is a novel factor promoting BC metastasis, that enhances migration and invasion by activating RAP1/CDC42 signaling and sensitizes BC to rapamycin and paclitaxel, which may improve stratified treatment strategies under the concept of molecular phenotyping-based precision therapy of BC.

Dissecting the molecular features of bovine-arrested eight-cell embryos using single-cell multi-omics sequencing†.

The regulation of mammalian early-embryonic development is a complex, coordinated process that involves widespread transcriptomic and epigenetic remodeling. The main cause of developmental failure in preimplantation embryos after in vitro fertilization is the irreversible arrested-at-cleavage stage. To deepen our understanding of this embryonic block, we profiled a single-cell multi-omics map of copy number variations (CNVs), the transcriptome, the DNA methylome, and the chromatin state of bovine eight-cell embryos with a two-cell fate that either arrested or developed into blastocysts. To do this, we sequenced a biopsied blastomere and tracked the developmental potential of the remaining cells. Aneuploid embryos inferred by CNVs from DNA- and RNA-library data tended to lose their developmental potency. Analysis of distinct genomic regions of DNA methylation and chromatin accessibility revealed that enrichment of gene function and signaling pathways, such as the MAPK signaling pathway, was altered in arrested euploid eight-cell embryos compared with blastocyst-developed euploid eight-cell embryos. Moreover, the RNA expression and chromatin accessibility of embryonic genome activation-associated genes were lower in arrested euploid embryos than in blastocyst-developed embryos. Taken together, our results indicate that the developmental block of eight-cell embryos can be caused by multiple molecular layers, including CNVs, abnormality of DNA methylation and chromatin accessibility, and insufficient expression of embryonic genome activation-associated genes. Our integrated and comprehensive data set provides a valuable resource to further dissect the exact mechanisms underlying the arrest of bovine eight-cell embryos in vitro.

Dose-specific efficacy of adipose-derived mesenchymal stem cells in septic mice.

BACKGROUND: Mesenchymal stem cells (MSCs) therapy for sepsis has been extensively studied in the past decade; however, the treatment regimen and mechanism of action of MSCs remain elusive. Here, we attempted to understand the efficacy and mechanism of action of MSCs on rescuing mice with sepsis. METHODS: A mouse model of sepsis was produced by cecal ligation and puncture (CLP). Allogeneic adipose-derived MSCs (ADSCs) were administered by intravenous infusion at 6 h after CLP, and dose-related effects of ADSCs on these mice were determined by survival rate, histopathological changes, biochemical and coagulation parameters, bacterial load, and plasma levels of endotoxin and inflammatory cytokines. The tissue distribution of intravenously infused ADSCs in septic mice was investigated by pre-labeling ADSCs with the lipophilic membrane dye PKH26. RNA sequencing analysis was performed to assess the transcriptional changes in peripheral blood mononuclear cells (PBMCs) and the liver. RESULTS: A significant therapeutic effect of ADSCs at a dose of 2 × 107 cells/kg in septic mice was evidenced by a remarkable reduction in mortality (35.89% vs. 8.89% survival rate), blood bacterial burden, systemic inflammation, and multiple organ damage. In contrast, ADSCs at a lower dose (1 × 107 cells/kg) failed to achieve any beneficial outcomes, while ADSCs at a higher dose (4 × 107 cells/kg) caused more early death within 24 h after CLP, retaining a steady survival rate of 21.42% thereafter. PKH26-labeled ADSCs were predominantly localized in the lungs of septic mice after intravenous infusion, with only a smaller proportion of PKH26-positive signals appearing in the liver and spleen. RNA sequencing analysis identified that insufficient phagocytic activity of PBMCs in addition to a hyperactivation of the hepatic immune response was responsible for the ineffectiveness of low-dose ADSCs therapy, and acute death caused by high-dose ADSCs infusion was associated with impaired coagulation signaling in PBMCs and exacerbated hepatic hypoxic injury. CONCLUSIONS: Our findings demonstrate a dose-specific effect of ADSCs on the treatment of sepsis due to dose-related interactions between exogenous stem cells and the host's microenvironment. Therefore, a precise dosing regimen is a prerequisite for ADSCs therapy for sepsis.

Identification of hepatocellular carcinoma subtypes based on PcG-related genes and biological relevance with cancer cells.

BACKGROUND: Hepatocellular carcinoma (HCC) is an extensive heterogeneous disease where epigenetic factors contribute to its pathogenesis. Polycomb group (PcG) proteins are a group of subunits constituting various macro-molecular machines to regulate the epigenetic landscape, which contributes to cancer phenotype and has the potential to develop a molecular classification of HCC. RESULTS: Here, based on multi-omics data analysis of DNA methylation, mRNA expression, and copy number of PcG-related genes, we established an epigenetic classification system of HCC, which divides the HCC patients into two subgroups with significantly different outcomes. Comparing these two epigenetic subgroups, we identified different metabolic features, which were related to epigenetic regulation of polycomb-repressive complex 1/2 (PRC1/2). Furthermore, we experimentally proved that inhibition of PcG complexes enhanced the lipid metabolism and reduced the capacity of HCC cells against glucose shortage. In addition, we validated the low chemotherapy sensitivity of HCC in Group A and found inhibition of PRC1/2 promoted HCC cells' sensitivity to oxaliplatin in vitro and in vivo. Finally, we found that aberrant upregulation of CBX2 in Group A and upregulation of CBX2 were associated with poor prognosis in HCC patients. Furthermore, we found that manipulation of CBX2 affected the levels of H3K27me3 and H2AK119ub. CONTRIBUTIONS: Our study provided a novel molecular classification system based on PcG-related genes data and experimentally validated the biological features of HCC in two subgroups. Our founding supported the polycomb complex targeting strategy to inhibit HCC progression where CBX2 could be a feasible therapeutic target.

Construction and validation of a nomogram for predicting survival in elderly patients with cardiac surgery.

Background: In recent years, the number of elderly patients undergoing cardiac surgery has rapidly increased and is associated with poor outcomes. However, there is still a lack of adequate models for predicting the risk of death after cardiac surgery in elderly patients. This study sought to identify independent risk factors for 1-year all-cause mortality in elderly patients after cardiac surgery and to develop a predictive model. Methods: A total of 3,752 elderly patients with cardiac surgery were enrolled from the Medical Information Mart for Intensive Care III (MIMIC-III) dataset and randomly divided into training and validation sets. The primary outcome was the all-cause mortality at 1 year. The Least absolute shrinkage and selection operator (LASSO) regression was used to decrease data dimensionality and select features. Multivariate logistic regression was used to establish the prediction model. The concordance index (C-index), receiver operating characteristic curve (ROC), and decision curve analysis (DCA) were used to measure the predictive performance of the nomogram. Results: Our results demonstrated that age, sex, Sequential Organ Failure Assessment (SOFA), respiratory rate (RR), creatinine, glucose, and RBC transfusion (red blood cell) were independent factors for elderly patient mortality after cardiac surgery. The C-index of the training and validation sets was 0.744 (95%CI: 0.707-0.781) and 0.751 (95%CI: 0.709-0.794), respectively. The area under the curve (AUC) and decision curve analysis (DCA) results substantiated that the nomogram yielded an excellent performance predicting the 1-year all-cause mortality after cardiac surgery. Conclusions: We developed a novel nomogram model for predicting the 1-year all-cause mortality for elderly patients after cardiac surgery, which could be an effective and useful clinical tool for clinicians for tailored therapy and prognosis prediction.

A Predictive Model Based on Inflammatory and Coagulation Indicators for Sepsis-Induced Acute Kidney Injury.

Background: Sepsis-induced acute kidney injury (S-AKI) is associated with systemic inflammatory responses and coagulation system dysfunction, and it is associated with an increased risk of mortality. However, there was no study to explore the predictive value of inflammatory and coagulation indicators for S-AKI. Methods: In this retrospective study, 1051 sepsis patients were identified and divided into a training cohort (75%, n = 787) and a validation cohort (25%, n = 264) in chronological order according to the date they were admitted. Univariate analyses and multivariate logistic regression analyses were performed to identify the independent predictors of S-AKI. The logistic regression analyses (enter methods) were used to conducted the prediction models. The ROC curves were used to determine the predictive value of the constructed models on S-AKI. To test whether the increase in the AUC is significant, we used a two-sided test for ROC curves available online (http://vassarstats.net/roc_comp.html). The secondary outcome was different AKI stages and major adverse kidney events within 30 days (MAKE30). Stage 3B of S-AKI was defined as both meeting the stage 3 criteria [increase of Cr level by > 300% (≥ 4.0 mg/dL with an acute increase of ≥ 0.5 mg/dL) and/or UO < 0.3 mL/kg/h for > 24 h or anuria for > 12 h and/or acute kidney replacement therapy] and having cystatin C positive. MAKE30 were a composite of death, new renal replacement therapy (RRT), or persistent renal dysfunction (PRD). Results: We discovered that cardiovascular disease, white blood cell (WBC), mean arterial pressure (MAP), platelet (PLT), serum procalcitonin (PCT), prothrombin time activity (PTA), and thrombin time (TT) were independent predictors for S-AKI. The predictive value (AUC = 0.855) of the simplest model 3 (constructed with PLT, PCT, and PTA), with a sensitivity of 77.6% and a specificity of 82.4%, had a similar predictive value comparing with the model 1 (AUC = 0.872) and the model 2 (AUC = 0.864) in the training cohort (P > 0.05). Compared with the model 1 (AUC = 0.888) and the model 2 (AUC = 0.887), the model 3 (AUC = 0.887) had a similar predictive value in the validation cohort. Moreover, model 3 had the best predictive power for predicting S-AKI in the stage 3 (AUC = 0.777), especially in stage 3B (AUC = 0.771). Finally, the model 3 (AUC = 0.843) had perfect predictive power for predicting MAKE30 in sepsis patients. Conclusion: Within 24 hours after admission, the simplest model 3 (constructed with PLT, PCT, and PTA) might be a robust predictor of the S-AKI in sepsis patients, providing information for timely and efficient intervention.

RUNX2 recruits the NuRD(MTA1)/CRL4B complex to promote breast cancer progression and bone metastasis.

Runt-related transcription factor 2 (RUNX2) is an osteogenesis-related transcription factor that has emerged as a prominent transcription repressing factor in carcinogenesis. However, the role of RUNX2 in breast cancer metastasis remains poorly understood. Here, we show that RUNX2 recruits the metastasis-associated 1 (MTA1)/NuRD and the Cullin 4B (CUL4B)-Ring E3 ligase (CRL4B) complex to form a transcriptional-repressive complex, which catalyzes the histone deacetylation and ubiquitylation. Genome-wide analysis of the RUNX2/NuRD(MTA1)/CRL4B complex targets identified a cohort of genes including peroxisome proliferator-activated receptor alpha (PPARα) and superoxide dismutase 2 (SOD2), which are critically involved in cell growth, epithelial-to-mesenchymal transition (EMT) and invasion. We demonstrate that the RUNX2/NuRD(MTA1)/CRL4B complex promotes the proliferation, invasion, tumorigenesis, bone metastasis, cancer stemness of breast cancer in vitro and in vivo. Strikingly, RUNX2 expression is upregulated in multiple human carcinomas, including breast cancer. Our study suggests that RUNX2 is a promising potential target for the future treatment strategies of breast cancer.

TXNIP: A Double-Edged Sword in Disease and Therapeutic Outlook.

Thioredoxin-interacting protein (TXNIP) was originally named vitamin D3 upregulated protein-1 (VDUP1) because of its ability to bind to thioredoxin (TRX) and inhibit TRX function and expression. TXNIP is an alpha-arrestin protein that is essential for redox homeostasis in the human body. TXNIP may act as a double-edged sword in the cell. The balance of TXNIP is crucial. A study has shown that TXNIP can travel between diverse intracellular locations and bind to different proteins to play different roles under oxidative stress. The primary function of TXNIP is to induce apoptosis or pyroptosis under oxidative stress. TXNIP also inhibits proliferation and migration in cancer cells, although TXNIP levels decrease, and function diminishes in various cancers. In this review, we summarized the main structure, binding proteins, pathways, and the role of TXNIP in diseases, aiming to explore the double-edged sword role of TXNIP, and expect it to be helpful for future treatment using TXNIP as a therapeutic target.