Separation of Palladium by an Imine-Linked Cu(I)-Organic Framework.

Selective capture of palladium (Pd) is one of the important works in science due to its high application and low content in the Earth's crust. To this end, we present herein a new Cu(I)-organic framework (ECUT-MOF-1) by introducing pyridine N active sites to chelate Pd(II). ECUT-MOF-1 demonstrated that the maximal adsorption capacity of Pd(II) was 350 mg/g in pH = 3 solution. In addition, kinetic analysis, cycle performance, selectivity, and adsorption mechanisms were also investigated. All of the results suggested its superior application in the recovery of Pd(II).

Confinement of ZIF-67-derived N, Co-doped C@Si on a 2D MXene for enhanced lithium storage.

A heterostructure composed of ZIF-67-derived nitrogen and cobalt-doped carbon enfolded silicon (C@Si) nanoparticles anchored on 2D MXene layers was constructed for boosting the performance of lithium-ion batteries (LIBs). The heterostructure anode demonstrated a high initial discharge capacity of 3021 mA h g-1 at 0.2 A g-1, retaining outstanding cycling stability with a reversible capacity of 520 mA h g-1 at 2000 mA g-1, and the coulombic efficiency remained above 97% after 500 cycles. The introduced Ti3C2 nanosheets and the cobalt-doped carbon can not only contribute to the interfacial transfer of Li+ and electrons but also buffer the volume expansion of Si.

Dual-Color Visual Ratiometric Fluorescence Sensing for H2O and D2O Mixtures Using a Hexanuclear Ln(III) Cluster-Based Metal-Organic Framework.

High-purity heavy water (D2O) is a strategic material owing to its important application in the fields of nuclear energy and scientific research. D2O always tends to get contaminated by H2O owing to its strong hygroscopicity. Herein, a bimetallic hexanuclear Ln(III) cluster-based metal-organic framework (Eu0.5Tb0.5-TZB-MOF) has been synthesized for fluorescence sensing of the D2O-H2O binary mixtures. Eu0.5Tb0.5-TZB-MOF can be used to immediately differentiate D2O or H2O via fluorescent color responses that are obvious to the naked eye and allow for quantitative ratiometric analysis using simple spectrophotometry. Fluorescence titration experiments demonstrate that both trace H2O in D2O and trace D2O in H2O can be quantitatively detected. Mechanistic studies demonstrate that the weaker vibrational quenching of the O-D oscillator compared to the O-H oscillator, in addition to the terbium-to-europium energy transfer, triggered the fluorescence signal response.

pH-Dependent Dual-Mode Detection toward Uranium by a Zinc-Tetraphenylethylene Fluorescent Metal-Organic Framework.

An interpenetrated tetraphenylethylene-based fluorescent metal-organic framework (ECUT-180) with exceptional sensitivity, excellent selectivity, and fast response (less than 30 s) toward uranium was successfully prepared. Especially, in the prescence of uranyl, ECUT-180 displays significant fluorescence turn-on under pH 2-3, while fluorescence turn-off under pH 4-8. The corresponding detection limits were determined to be 2.92 ppb at pH 2 and 0.86 ppb at pH 8, both of which are lower than the average uranium content (3.3 ppb) in seawater. Mechanism investigation reveals that the fluorescence enhancement on the strong acid condition can be assigned to uranium adsorption, while the quenching is caused by the resonance energy transfer.

CDC23 knockdown suppresses the proliferation, migration and invasion of liver cancer via the EMT process.

Liver cancer (LC) is a malignant tumour that is associated with high mortality rates worldwide. Cell division cycle 23 (CDC23) acts as an oncogene in papillary thyroid cancer. In addition, epithelial-mesenchymal transition (EMT) is frequently involved in the malignant metastasis of various cancer types. Therefore, we hypothesized that CDC23 may regulate the malignant biological behaviours of LC cells through EMT. Proliferation, colony formation and Transwell assays, western blotting and xenograft experiments were performed. The results of the present study showed that CDC23 was highly expressed in LC cell lines. In addition, it was found via multiple in vitro assays that CDC23 knockdown reduced the proliferation, migration and invasion of LC cell lines. Finally, an in vivo study confirmed that CDC23 knockdown inhibited the growth of xenograft LC in nude mice. More importantly, the changes in the levels of EMT-related marker proteins were analysed in the sh-CDC23 group compared with the sh-NC group of cells and xenografts. E-cadherin was upregulated, and N-cadherin and vimentin were significantly downregulated after CDC23 silencing. Taken together, these results revealed that the knockdown of CDC23 inhibits the progression of LC by regulating EMT and that CDC23 may be a novel therapeutic target for LC.

Deep learning model for diagnosing early gastric cancer using preoperative computed tomography images.

Background: Early gastric cancer (EGC) is defined as a lesion restricted to the mucosa or submucosa, independent of size or evidence of regional lymph node metastases. Although computed tomography (CT) is the main technique for determining the stage of gastric cancer (GC), the accuracy of CT for determining tumor invasion of EGC was still unsatisfactory by radiologists. In this research, we attempted to construct an AI model to discriminate EGC in portal venous phase CT images. Methods: We retrospectively collected 658 GC patients from the first affiliated hospital of Nanchang university, and divided them into training and internal validation cohorts with a ratio of 8:2. As the external validation cohort, 93 GC patients were recruited from the second affiliated hospital of Soochow university. We developed several prediction models based on various convolutional neural networks, and compared their predictive performance. Results: The deep learning model based on the ResNet101 neural network represented sufficient discrimination of EGC. In two validation cohorts, the areas under the curves (AUCs) for the receiver operating characteristic (ROC) curves were 0.993 (95% CI: 0.984-1.000) and 0.968 (95% CI: 0.935-1.000), respectively, and the accuracy was 0.946 and 0.914. Additionally, the deep learning model can also differentiate between mucosa and submucosa tumors of EGC. Conclusions: These results suggested that deep learning classifiers have the potential to be used as a screening tool for EGC, which is crucial in the individualized treatment of EGC patients.

Transfer Parameter Analysis of Chloride Ingress into Concrete Based on Long-Term Exposure Tests in China's Coastal Region.

Chloride penetration resistance is one of the most important performance measures for the evaluation of the durability of concrete under a chloride environment. Due to differences in theory and experimental conditions, the durability index (chloride diffusion coefficient) obtained from laboratory accelerated migration tests cannot reflect the real process of chloride ingress into concrete in the natural environment. The difference in test methods must be considered and the transfer parameter kt should be introduced into the service life prediction model when the test results of accelerated methods are used. According to the test data of coastal exposure in South China, the attenuation rule of the chloride diffusion coefficient of different cement-based materials changed with time and was analyzed in this paper. Based on the diffusion coefficient-time curve, the theoretical natural diffusion coefficients of 28 d and 56 d were deduced, which were compared with the chloride diffusion coefficients obtained from the non-steady-state rapid migration method (RCM) at the same age. Therefore, the transfer parameter kt that expounds the relationship between concrete resistance to chloride permeability under a non-stationary electrical accelerated state and natural diffusion in the marine environment can be calculated; thus, the RCM testing index can be used to evaluate the long-term performance of the concrete structure in the marine environment. The results show that the value of kt was related to environmental conditions, test methods, and binder systems.

Hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta gene as a tumour suppressor in stomach adenocarcinoma.

Background: Stomach adenocarcinoma (STAD) is the most common type of gastric cancer. In this study, the functions and potential mechanisms of hydroxyacyl-CoA dehydrogenase trifunctional multienzyme complex subunit beta (HADHB) in STAD were explored. Methods: Different bioinformatics analyses were performed to confirm HADHB expression in STAD. HADHB expression in STAD tissues and cells was also evaluated using western blot, qRT-PCR, and immunohistochemistry. Further, the viability, proliferation, colony formation, cell cycle determination, migration, and wound healing capacity were assessed, and the effects of HADHB on tumour growth, cell apoptosis, and proliferation in nude mice were determined. The upstream effector of HADHB was examined using bioinformatics analysis and dual luciferase reporter assay. GSEA was also employed for pathway enrichment analysis and the expression of Hippo-YAP pathway-related proteins was detected. Results: The expression of HADHB was found to be low in STAD tissues and cells. The upregulation of HADHB distinctly repressed the viability, proliferation, colony formation, cell cycle progression, migration, invasion, and wound healing of HGC27 cells, while knockdown of HADHB led to opposite effects. HADHB upregulation impeded tumour growth and cell proliferation, and enhanced apoptosis in nude mice. KLF4, whose expression was low in STAD, was identified as an upstream regulator of HADHB. KLF4 upregulation abolished the HADHB knockdown-induced tumour promoting effects in AGS cells. Further, HADHB regulates the Hippo-YAP pathway, which was validated using a pathway rescue assay. Low expression of KLF4 led to HADHB downregulation in STAD. Conclusion: HADHB might function as a tumour suppressor gene in STAD by regulation the Hippo-YAP pathway.

Role of STX6 as a prognostic factor associated with immune infiltration in hepatocellular carcinoma.

Syntaxin 6 (STX6), a soluble N-ethylmaleimide-sensitive factor-activating receptor protein, has formed an increasing part of cancer research. However, to the best of our knowledge, the role of STX6 in hepatocellular carcinoma (HCC) is still unclear. In the present study, data from multiple bioinformatics databases, including The Cancer Genome Atlas, Gene Expression Omnibus, Kaplan-Meier plotter, Tumor Immune Estimation Resource (TIMER) and Gene Expression Profiling Integrative Analysis (GEPIA2), and immunohistochemistry (IHC) were utilized to assess the role of STX6 in HCC. The results demonstrated that STX6 expression was upregulated in HCC tissues compared with normal tissues. STX6 expression was significantly associated with tumor size, Edmondson grade and α-fetoprotein (AFP) level. Furthermore, survival analysis demonstrated that high STX6 expression was significantly associated with poor prognosis in patients with HCC. Furthermore, assessment of the immune infiltrates demonstrated that CD163 expression was positively correlated with the STX6 level when analyzed using the TIMER and GEPIA2 databases. IHC results further demonstrated this association. Furthermore, compared with the typically used AFP, STX6 could have an improved diagnostic value in the diagnosis of HCC. In conclusion, STX6 expression was not only positively associated with poor prognosis but may also be involved in the immune inflammatory reaction in HCC. STX6 may become a potential therapeutic and diagnosis maker for patients with HCC.

Phosphogypsum-Based Ultra-Low Basicity Cementing Material.

Traditional Portland cement is widely used in the preparation of various hydraulic concrete. However, the high alkalinity produced by cement hydration threatens the survival of aquatic animals and plants. In this paper, a new eco-friendly, ultra-low alkalinity, cementitious material was prepared with industrial waste phosphogypsum, granulated ground blast slag (GGBS) and sulphoaluminate cement. When appropriate proportions are used, the pH value of the test blocks' pore solutions at different ages were all less than 9, showing the remarkable characteristic of ultra-low alkalinity. The XRD and SEM analyses showed that the 56 d hydration products were mainly ettringite and hydrated calcium silicate, and the content of Ca(OH)2 was not detected. The new cementitious material also has the advantages of short setting time, low heat of hydration, high strength of cement mortar and the ability to fix harmful substances in phosphogypsum, such as phosphate, fluoride and Cr and Ba elements. It has a broad application prospect in the construction of island and reef construction, river restoration and so on.

CT-based radiomic nomogram for preoperative prediction of DNA mismatch repair deficiency in gastric cancer.

Background: DNA mismatch repair (MMR) deficiency has attracted considerable attention as a predictor of the immunotherapy efficacy of solid tumors, including gastric cancer. We aimed to develop and validate a computed tomography (CT)-based radiomic nomogram for the preoperative prediction of MMR deficiency in gastric cancer (GC). Methods: In this retrospective analysis, 225 and 91 GC patients from two distinct hospital cohorts were included. Cohort 1 was randomly divided into a training cohort (n = 176) and an internal validation cohort (n = 76), whereas cohort 2 was considered an external validation cohort. Based on repeatable radiomic features, a radiomic signature was constructed using the least absolute shrinkage and selection operator (LASSO) regression analysis. We employed multivariable logistic regression analysis to build a radiomics-based model based on radiomic features and preoperative clinical characteristics. Furthermore, this prediction model was presented as a radiomic nomogram, which was evaluated in the training, internal validation, and external validation cohorts. Results: The radiomic signature composed of 15 robust features showed a significant association with MMR protein status in the training, internal validation, and external validation cohorts (both P-values <0.001). A radiomic nomogram incorporating a radiomic signature and two clinical characteristics (age and CT-reported N stage) represented good discrimination in the training cohort with an AUC of 0.902 (95% CI: 0.853-0.951), in the internal validation cohort with an AUC of 0.972 (95% CI: 0.945-1.000) and in the external validation cohort with an AUC of 0.891 (95% CI: 0.825-0.958). Conclusion: The CT-based radiomic nomogram showed good performance for preoperative prediction of MMR protein status in GC. Furthermore, this model was a noninvasive tool to predict MMR protein status and guide neoadjuvant therapy.

Development and validation of a predictive model combining clinical, radiomics, and deep transfer learning features for lymph node metastasis in early gastric cancer.

Background: This study aims to develop and validate a predictive model combining deep transfer learning, radiomics, and clinical features for lymph node metastasis (LNM) in early gastric cancer (EGC). Materials and methods: This study retrospectively collected 555 patients with EGC, and randomly divided them into two cohorts with a ratio of 7:3 (training cohort, n = 388; internal validation cohort, n = 167). A total of 79 patients with EGC collected from the Second Affiliated Hospital of Soochow University were used as external validation cohort. Pre-trained deep learning networks were used to extract deep transfer learning (DTL) features, and radiomics features were extracted based on hand-crafted features. We employed the Spearman rank correlation test and least absolute shrinkage and selection operator regression for feature selection from the combined features of clinical, radiomics, and DTL features, and then, machine learning classification models including support vector machine, K-nearest neighbor, random decision forests (RF), and XGBoost were trained, and their performance by determining the area under the curve (AUC) were compared. Results: We constructed eight pre-trained transfer learning networks and extracted DTL features, respectively. The results showed that 1,048 DTL features extracted based on the pre-trained Resnet152 network combined in the predictive model had the best performance in discriminating the LNM status of EGC, with an AUC of 0.901 (95% CI: 0.847-0.956) and 0.915 (95% CI: 0.850-0.981) in the internal validation and external validation cohorts, respectively. Conclusion: We first utilized comprehensive multidimensional data based on deep transfer learning, radiomics, and clinical features with a good predictive ability for discriminating the LNM status in EGC, which could provide favorable information when choosing therapy options for individuals with EGC.

Clinicopathologic study of mantle cell lymphoma with epstein-barr virus infection: A case series and literature review.

Background: Mantle cell lymphoma (MCL) with Epstein-Barr virus (EBV) infection is rarely reported. The objective of this study was to analyze the prevalence and clinicopathological features of MCL with EBV infection in the largest series thus far. Methods: After screening 138 cases of MCL, we identified eight cases of MCL with EBV infection. Results: Most of them (7/8) had non-neoplastic bystander cells with positivity for EBV and no expression of latent membrane protein 1 (LMP1) and EBV nuclear antigen 2 (EBNA2). The cases of MCL with EBER positivity did not have abnormal immune function or other lymphomas. Moreover, their histopathological morphology was indicative of classical MCL. Cases of MCL with EBER positivity exhibited statistically significant differences in lactate dehydrogenase, anemia status, and MCL international prognostic index grouping (P=0.008, P=0.02, P=0.001, and P=0.011, respectively). The differences between the two groups in age, sex ratio, clinical manifestations, and immunohistochemical phenotypes were not statistically significant. Conclusions: The incidence of MCL with EBV infection was low (5.8%). Clinicopathologically, cases of MCL with EBER positivity were similar to their EBV-negative counterparts. Our findings revealed that most cells infected by EBV in MCL are background cells rather than tumor cells. This is inconsistent with data from previous studies, indicating that tumor cells in MCL may not be prone to EBV infection.

The m7G-Related Long Noncoding RNA Signature Predicts Prognosis and Indicates Tumour Immune Infiltration in Colon Cancer.

With high morbidity and mortality, colon cancer (CC) is considered as one of the most often diagnosed cancers around the world. M7G-related lncRNA may provide a regulatory function in the formation of CC, but the principle of regulation is still unclear. The purpose of this research was to establish a novel signature that may be used to predict survival and tumour immunity in CC patients. Data about CC in TCGA was collected for analysis, coexpression analysis and univariate Cox analysis were used to screen prognostic m7G-related lncRNAs. A consensus clustering analysis based on prognostic m7G-related lncRNAs was applied, and a prognosis model based on least absolute shrinkage and selection operator (LASSO) regression analysis was established. Independent prognostic analysis, nomogram, PCA, clinicopathological correlation analysis, TMB, survival analysis, immune correlation analysis, qRT-PCR and clinical therapeutic compound prediction were also applied. 90 prognostic m7G-related lncRNAs were found, GO and KEGG analysis showed that prognostic m7G-related lncRNAs were mainly related to cell transcription and translation. The results of the consensus clustering analysis revealed substantial disparities in survival prognosis and tumour immune infiltration between two clusters. We built a risk model with 21 signature m7G-related lncRNAs, patients in the high-risk group had a considerably poorer prognosis than those in the low-risk group. Independent prognostic analysis confirmed that patients' prognosis was linked to their tumour stage and risk score. PCA, subgroups with distinct clinicopathological characteristics were studied for survival, multi-index ROC curve, c-index curve, the survival analysis of TMB, and model comparison tested the reliability of risk model. A tumour immunoassay revealed a substantial difference in immune infiltration between high-risk and low-risk individuals. Five chemicals were eliminated, and qRT-PCR indicated that the four lncRNAs were expressed differently. Overall, m7G-related lncRNA is closely related to colon cancer and the 21 signature lncRNAs risk model can efficiently evaluate the prognosis of CC patients, which has a possible positive consequence for the future diagnosis and therapy of CC.

Retraction Notice to: Long Noncoding RNA UCA1 Regulates PRL-3 Expression by Sponging MicroRNA-495 to Promote the Progression of Gastric Cancer.

[This retracts the article DOI: 10.1016/j.omtn.2019.10.020.].

microRNA-15b-5p encapsulated by M2 macrophage-derived extracellular vesicles promotes gastric cancer metastasis by targeting BRMS1 and suppressing DAPK1 transcription.

BACKGROUND: Extracellular vesicles (EVs) derived from tumor-associated macrophages are implicated in the progression and metastasis of gastric cancer (GC) via the transfer of molecular cargo RNAs. We aimed to decipher the impact of microRNA (miR)-15b-5p transferred by M2 macrophage-derived EVs in the metastasis of GC. METHODS: Expression of miR-15b-5p was assessed and the downstream genes of miR-15b-5p were analyzed. GC cells were subjected to gain- and loss-of function experiments for miR-15b-5p, BRMS1, and DAPK1. M2 macrophage-derived EVs were extracted, identified, and subjected to co-culture with GC cells and their biological behaviors were analyzed. A lung metastasis model in nude mice was established to determine the effects of miR-15b-5p on tumor metastasis in vivo. RESULTS: miR-15b-5p was upregulated in GC tissues and cells as well as in M2 macrophage-derived EVs. miR-15b-5p promoted the proliferative and invasive potentials, and epithelial-mesenchymal transition (EMT) of GC cells. M2 macrophage-derived EVs could transfer miR-15b-5p into GC cells where it targeted BRMS1 by binding to its 3'UTR. BRMS1 was enriched in the DAPK1 promoter region and promoted its transcription, thereby arresting the proliferative and invasive potentials, and EMT of GC cells. In vivo experiments demonstrated that orthotopic implantation of miR-15b-5p overexpressing GC cells in nude mice displayed led to enhanced tumor metastasis by inhibiting the BRMS1/DAPK1 axis. CONCLUSIONS: Overall, miR-15b-5p delivered by M2 macrophage-derived EVs constitutes a molecular mechanism implicated in the metastasis of GC, and may thus be considered as a novel therapeutic target for its treatment.

Comprehensive Analysis of Necroptosis-Related Long Noncoding RNA Immune Infiltration and Prediction of Prognosis in Patients With Colon Cancer.

Colon cancer (CC) is one of the most frequent malignancies in the world, with a high rate of morbidity and death. In CC, necroptosis and long noncoding RNA (lncRNAs) are crucial, but the mechanism is not completely clear. The goal of this study was to create a new signature that might predict patient survival and tumor immunity in patients with CC. Expression profiles of necroptosis-related lncRNAs in 473 patients with CC were retrieved from the TCGA database. A consensus clustering analysis based on differentially expressed (DE) genes and a prognostic model based on least absolute shrinkage and selection operator (LASSO) regression analysis were conducted. Clinicopathological correlation analysis, expression difference analysis, PCA, TMB, GO analysis, KEGG enrichment analysis, survival analysis, immune correlation analysis, prediction of clinical therapeutic compounds, and qRT-PCR were also conducted. Fifty-six necroptosis-related lncRNAs were found to be linked to the prognosis, and consensus clustering analysis was performed. There were substantial variations in survival, immune checkpoint expression, clinicopathological correlations, and tumor immunity among the different subgroups. Six lncRNAs were discovered, and patients were split into high-risk and low-risk groups based on a risk score generated using these six lncRNAs. The survival time of low-risk patients was considerably longer than that of high-risk patients, indicating that these lncRNAs are directly associated with survival. The risk score was associated with the tumor stage, infiltration depth, lymph node metastasis, and distant metastasis. After univariate and multivariate Cox regression analysis, the risk score and tumor stage remained significant. Cancer- and metabolism-related pathways were enriched by KEGG analyses. Immune infiltration was shown to differ significantly between high- and low-risk patients in a tumor immunoassay. Eight compounds were screened out, and qRT-PCR confirmed the differential expression of the six lncRNAs. Overall, in CC, necroptosis-related lncRNAs have an important function, and the prognosis of patients with CC can be predicted by these six necroptosis-related lncRNAs. They may be useful in the future for customized cancer therapy.

Comprehensive Analysis of Immune Infiltrates of Ferroptosis-Related Long Noncoding RNA and Prediction of Colon Cancer Patient Prognoses.

Ferroptosis is a newly defined mode of programmed oxidative cell death. Knowledge of ferroptosis-related long noncoding (lnc) RNA in the tumor immune microenvironment of colon cancer is lacking. We systematically analyzed the correlations between ferroptosis-related lncRNAs and the tumor microenvironment, immune cell infiltration, and patient prognosis for 379 colon cancer samples in the Cancer Genome Atlas (TCGA). Using consensus clustering, we divided the 379 colon cancer patients into two subgroups (clusters 1 and 2) based on the differentially expressed ferroptosis-related lncRNAs. Cluster 1 was preferentially associated with longer overall survival, upregulated immune checkpoint inhibitor expressions, higher immunoscores, higher stromal scores, higher estimated scores, and distinct immune cell infiltration. Cancer- and metabolism-related pathways were enriched by gene set enrichment analyses. We constructed a prognostic signature of 15 ferroptosis-related lncRNAs (ZEB1-AS1, LINC01011, AC005261.3, LINC01063, LINC02381, ELFN1-AS1, AC009283.1, LINC02361, AC105219.1, AC002310.1, AL590483.1, MIR4435-2HG, NKILA, AC021054.1, and AL450326.1) and divided the patients into the high- and low-risk-score groups. The signature was validated using TCGA training and testing cohorts. The risk signature was an independent prognostic factor for predicting survival and excellently predicted the prognoses of patients with colon cancer. Moreover, the risk signature was related to immune characteristics. Chemosensitivity analyses showed that low-risk-score patients were more sensitive to sorafenib. In summary, our work revealed the important role of ferroptosis-related lncRNAs in the tumor microenvironment and immune cell infiltration and may help determine personalized prognoses and treatment for patients with colon cancer.

RNF114 Silencing Inhibits the Proliferation and Metastasis of Gastric Cancer.

RNF114 (E3 ubiquitin ligase RING finger protein 114) was first identified as a zinc-binding protein that promotes psoriasis development; however, its role in gastric cancer is still unclear. We explored the relationship between RNF114 and gastric cancer using bioinformatics and molecular biology techniques. The results showed that RNF114 was highly expressed in gastric cancer and negatively correlated with the patient's prognosis. Functional assays suggested that RNF114 silencing suppressed the proliferation and metastasis of gastric cancer cells to a certain extent. Further studies showed that RNF114 expression was potentially targeted by miR-218-5p and methylation modification, and mediated downstream EGR1 (early growth response 1) degradation by the ubiquitylation approach. Together, the present results highlight the detrimental effects of RNF114 overexpression in gastric cancer and contribute to a better understanding of the mechanisms underlying RNF114 functionality.