Combined lineage tracing and scRNA-seq reveal the activation of Sox9+ cells in renal regeneration with PGE2 treatment.

Uncovering mechanisms of endogenous regeneration and repair through resident stem cell activation will allow us to develop specific therapies for injuries and diseases by targeting resident stem cell lineages. Sox9+ stem cells have been reported to play an essential role in acute kidney injury (AKI). However, a complete view of the Sox9+ lineage was not well investigated to accurately elucidate the functional end state and the choice of cell fate during tissue repair after AKI. To identify the mechanisms of fate determination of Sox9+ stem cells, we set up an AKI model with prostaglandin E2 (PGE2) treatment in a Sox9 lineage tracing mouse model. Single-cell RNA sequencing (scRNA-seq) was performed to analyse the transcriptomic profile of the Sox9+ lineage. Our results revealed that PGE2 could activate renal Sox9+ cells and promote the differentiation of Sox9+ cells into renal proximal tubular epithelial cells and inhibit the development of fibrosis. Furthermore, single-cell transcriptome analysis demonstrated that PGE2 could regulate the restoration of lipid metabolism homeostasis in proximal tubular epithelial cells by participating in communication with different cell types. Our results highlight the prospects for the activation of endogenous renal Sox9+ stem cells with PGE2 for the regenerative therapy of AKI.

Thymol targeting interleukin 4 induced 1 expression reshapes the immune microenvironment to sensitize the immunotherapy in lung adenocarcinoma.

Immune checkpoint blockades are the most promising therapy in lung adenocarcinoma (LUAD). However, the response rate remains limited, underscoring the urgent need for effective sensitizers. Interleukin 4 induced 1 (IL4I1) is reported to have immunoinhibitory and tumor-promoting effects in several cancers. However, the targetable value of IL4I1 in sensitizing the immunotherapy is not clear, and there is a lack of effective small molecules that specifically target IL4I1. Here, we show that silencing IL4I1 significantly remodels the immune microenvironment via inhibiting aryl hydrocarbon receptor (AHR) signaling, thereby enhancing the efficacy of anti-PD-1 antibody in LUAD, which suggests that IL4I1 is a potential drug target for the combination immunotherapy. We then identify thymol as the first small molecule targeting IL4I1 transcription through a drug screening. Thymol inhibits the IL4I1 expression and blocks AHR signaling in LUAD cells. Thymol treatment restores the antitumor immune response and suppresses the progression of LUAD in an orthotopic mouse model. Strikingly, the combination treatment of thymol with anti-PD-1 antibody shows significant tumor regression in LUAD mice. Thus, we demonstrate that thymol is an effective small molecule to sensitize the PD-1 blockade in LUAD via targeting IL4I1, which provides a novel strategy for the immunotherapy of LUAD.

Whole exome sequencing reveals novel variants associated with diminished ovarian reserve in young women.

Background: Diminished ovarian reserve is one of the most important causes of female infertility. In the etiology study of DOR, besides age, it is known that chromosomal abnormality, radiotherapy, chemotherapy and ovarian surgery can result in DOR. For young women without obvious risk factors, gene mutation should be considered as a possible cause. However, the specific molecular mechanism of DOR has not been fully elucidated. Methods: In order to explore the pathogenic variants related to DOR, twenty young women under 35 years old affected by DOR without definite factors damaging ovarian reserve were recruited as the research subjects, and five women with normal ovarian reserve were recruited as the control group. Whole exome sequencing was applied as the genomics research tool. Results: As a result, we obtained a set of mutated genes that may be related to DOR, where the missense variant on GPR84 was selected for further study. It is found that GPR84Y370H variant promotes the expression of proinflammatory cytokines (TNF-α, IL12B, IL-1ß) and chemokines (CCL2, CCL5), as well as the activation of NF-κB signaling pathway. Conclusion: In conclusion, GPR84Y370H variant was identified though analysis for WES results of 20 DOR patients. The deleterious variant of GPR84 could be the potential molecular mechanism of non-age-related pathological DOR through its role in promoting inflammation. The findings of this study can be used as a preliminary research basis for the development of early molecular diagnosis and treatment target selection of DOR.

Fbxw11 impairs the repopulation capacity of hematopoietic stem/progenitor cells.

BACKGROUND: The ubiquitin-proteasome system plays important roles in maintaining the self-renewal and differentiation of stem and progenitor cells through highly ordered degradation of cellular proteins. Fbxw11, an E3 ligase, participates in many important biological processes by targeting a broad range of proteins. However, its roles in hematopoietic stem/progenitor cells (HSPCs) have not been established. METHODS: In this study, the effects of Fbxw11 on HSPCs were studied in vitro and in vivo by an overexpression strategy. Real-time PCR was performed to detect the expression of Fbxw11 in hematopoietic subpopulations. Colony-forming assays were performed to evaluate the in vitro function of Fbxw11 on HSPCs. Hoechst 33342 and Ki67 staining was performed to determine the cell-cycle distribution of HSPCs. Competitive transplantation experiments were used to evaluate the effect of Fbxw11 on the reconstitution potential of HSPCs. Single-cell RNA sequencing (scRNA-seq) was employed to reveal the transcriptomic alterations in HSPCs. RESULTS: The expression of Fbxw11 was higher in Lin-c-Kit+Sca-1+ (LSK) cells and myeloid progenitors than in lymphoid progenitors. Fbxw11 played negative roles in colony-forming and quiescence maintenance of HSPCs in vitro. Furthermore, serial competitive transplantation experiments revealed that Fbxw11 impaired the repopulation capacity of HSPCs. The proportion of granulocytes (Gr-1+CD11b+) in the differentiated mature cells was significantly higher than that in the control group, T cells and B cells were lower. Moreover, scRNA-seq revealed seven cell clusters in HSPCs. In addition, Fbxw11 downregulated the expression of Cebpa, Myc and Arid5b, which are significant regulators of HSPC activity, in most cell clusters. CONCLUSION: Our data demonstrate that Fbxw11 plays a negative role in the maintenance of HSPCs in vitro and repopulation capacity in vivo. Our data also provide valuable transcriptome references for HSPCs in homeostasis.

Identification of Neural Progenitor Cell-associated Chemoradiotherapy Resistance Gene Set (ARL4C, MSN, TNFAIP6) for Prognosis of Glioma.

BACKGROUND: Glioma is the most common malignant intracranial tumor with high lethality. Despite surgery combined with chemoradiotherapy, the prognosis for patients with glioma remains poor. This is primarily due to acquired chemoradiotherapy resistance. Therefore, to improve the prognosis of glioma, further study into the mechanism of chemoradiotherapy resistance is needed. OBJECTIVE: This study aimed to (1) evaluate the prognosis of patients with glioma by using a prognostic risk score model constructed by chemoradiotherapy resistance genes, (2) provide new targets and directions for precise treatment of glioma, and (3) discuss the tumor heterogeneity of tumor cells. METHODS: According to therapy class and overall survival (OS), we identified 53 genes associated with glioma chemoradiotherapy resistance in The Cancer Genome Atlas Glioblastoma (TCGA GBM) database. Considering the important role of chemoradiotherapy resistance-related genes in the prognosis of glioma, we preliminarily screened and identified vital prognostic factors among these genes by using the Cox regression model of absolute contraction and selection operators in the TCGA GBM lower-grade glioma (TCGA GBMLGG) dataset. Next, the heterogeneity of the chemoradiotherapy resistance-associated genes in different glioma cells was revealed by single-cell sequencing in the GSE117891 cohort. RESULTS: A prognostic risk score model consisting of three genes (ARL4C, MSN, TNFAIP6) was constructed. The expression of this model was high in glioma neural progenitor cells (NPCs) and low in glioma oligodendrocytes. The OS rates were significantly lower in the high- vs. low-risk group. CONCLUSION: Our 3 gene risk score complements the current glioma diagnosis and provides a novel insight into chemoradiotherapy resistance mechanisms for the prognosis of patients with glioma.

Perioperative Serum Scoring Systems Predict Early Recurrence and Poor Prognosis of Resectable Pancreatic Cancer.

Objective: Some patients with pancreatic ductal adenocarcinoma (PDAC) are prone to rapid recurrence or metastasis after radical resection. However, evaluation methods for effectively identifying these patients are lacking. In this study, we established perioperative serum scoring systems to screen patients with early recurrence and poor prognosis. Methods: We systematically analysed 44 perioperative serum parameters, including systemic inflammatory parameters, coagulation system parameters, tumor markers, and 18 clinicopathological characteristics of 218 patients with radical resection in our centre. Univariate Cox regression and LASSO regression models were used to screen variables. Kaplan-Meier survival analysis was used to compare relapse-free survival and overall survival. Multivariate Cox regression was used to evaluate the independent risk variables. AUC and C-index were used to reveal the effectiveness of the models. In addition, the effectiveness was also verified in an independent cohort of 109 patients. Results: Preoperative systemic immune coagulation cascade (SICC) (including increased neutrophil to lymphocyte ratio, decreased lymphocyte to monocyte ratio, increased platelet and fibrinogen) and increased postoperative tumor markers (TMs) (CA199, CEA and CA242) were independent risk factors for early recurrence of resectable pancreatic cancer. On this basis, we established the preoperative SICC score and postoperative TMs score models. The patients with higher preoperative SICC or postoperative TMs score were more likely to have early relapse and worse prognosis. The nomogram based on preoperative SICC, postoperative TMs, CACI, smoking index, vascular cancer embolus and adjuvant chemotherapy can effectively evaluate the recurrence rate (AUC1 year: 0.763, AUC2 year: 0.679, AUC3 year: 0.657) and overall survival rate (AUC1 year: 0.770, AUC3 year: 0.804, AUC5 year: 0.763). Conclusion: Preoperative SICC and postoperative TMs can help identify resectable PDAC patients with early recurrence and poor prognosis.

Genome-wide CRISPR/Cas9 knockout screening uncovers ZNF319 as a novel tumor suppressor critical for breast cancer metastasis.

Breast cancer is prone to relapse and metastasize to many vital organs, contributing to most of the breast cancer-related death and accentuating the importance of systematic identification of key factors regulating the metastasis of breast cancer. In this study, we performed a genome-wide CRISPR/Cas9 knock out screen in an orthotopic murine model of breast cancer for essential genes monitoring the progression and metastasis of breast cancer. We found one member of the zinc finger protein (ZNF) family, i.e., ZNF319, was among the top candidate genes. We further confirmed the lower expression of ZNF319 in the tumor tissue of breast cancer patients by analyzing tissue sections with IHC staining and TCGA database. Consistently, higher expression of ZNF319 correlates with better clinical outcome in almost all subtypes of breast cancer. Moreover, knocking down or overexpressing ZNF319 in breast cancer cells dramatically affects the breast cancer growth and metastasis capacity both in vitro and in vivo, suggesting ZNF319 functions as a strong suppressor of breast cancer progression. Lastly, the transcriptome analysis on ZNF319-silenced breast cancer cells shows that ZNF319 is involved in multiple crucial signaling pathways and biological processes, especially in cell cycle and proliferation. GO and KEGG analyses of our RNA-seq results reveal the up-regulation of E2F and G2/M related genes in ZNF319-silenced cells, suggesting that ZNF319 monitors the cell cycle during the breast cancer progression through the regulation of the E2F target genes and G2/M checkpoint. In summary, our study identifies ZNF319 as a novel metastasis suppressor gene arresting tumor cell cycle in breast cancer and thus presents a novel potential therapeutic target for breast cancer treatment.

Genome-wide identification of m6A-associated functional SNPs as potential functional variants for thyroid cancer.

m6A methylation has been demonstrated to be one of the most important epigenetic regulation mechanisms in cell differentiation and cancer development especially m6A derived diagnostic and prognostic biomarkers have been identified in the past several years. However, systemic investigation to the interaction between germline single-nucleotide polymorphisms (SNPs) and m6A has not been conducted yet. In this study, we collected previous identified significant thyroid cancer associated SNPs from UKB cohort (358 cases and 407,399 controls) and ICR cohort (3,001 patients and 287,550 controls) and thyroid eQTL (sample size = 574 from GTEx project) and m6A-SNP (N = 1,678,126) were applied to prioritize the candidate SNPs. Finally, five candidate genes (PLEKHA8, SMUG1, CDC123, RMI2, ACSM5) were identified to be thyroid cancer associated m6A-related genetic susceptibility. Loss and gain function studies of m6A writer proteins confirm that ACSM5 is regulated by m6A methylation of mRNA. Moreover, ACSM5 is downregulated in thyroid cancer and inversely correlated with PTC malignancy and patient survival. Together, our study highlight mRNA-seq and m6A-seq double analysis provided a novel approach to identify cancer biomarkers and understanding the heterogeneity of human cancers.

Cytotoxic lymphocytes-related gene ITK from a systematic CRISPR screen could predict prognosis of ovarian cancer patients with distant metastasis.

BACKGROUND: Ovarian cancer, a highly metastatic malignancy, has benefited tremendously from advances in modern human genomics. However, the genomic variations related to the metastasis remains unclear. METHODS: We filtered various significant genes (n = 6722) associated with metastasis within a large-scale functional genomic CRISPR/Cas9 knock-out library including 122,756 single guide RNAs, and identified ITK (IL2 Inducible T Cell Kinase) as a potential cancer suppressor gene for ovarian cancer metastasis. Downstream bioinformatic analysis was performed for ITK using public databases. RESULTS: We found that patients in low-ITK group had poor prognosis and more distant metastasis than those in high-ITK group in TCGA and GEO databases. We also demonstrated that ITK combined with the clinical factors could accurately predict prognosis through multiple Cox regression analysis and ROC analysis. Moreover, alterations correlated with distant metastasis emereged with significantly increased expression in SAMRCD1 in low-ITK group, but CD244 and SOCS1 in high-ITK group. Integrated analysis revealed dysregulated molecular processes including predominantly oncogenic signaling pathways in low-ITK group but immune related pathways in high-ITK group, which suggested ITK might inhibit distant metastasis in ovarian cancer. Furtherly, deconvolution of the cellular composition of all samples validated the close correlation between ITK and immune related function especially for cytotoxic lymphocytes. CONCLUSIONS: Together, these data provide insights into the potential role of ITK, with implications for the future development of tansformative ovarian cancer therapeutics.

Comprehensive Evaluation of Differential Methylation Analysis Methods for Bisulfite Sequencing Data.

Background: With advances in next-generation sequencing technologies, the bisulfite conversion of genomic DNA followed by sequencing has become the predominant technique for quantifying genome-wide DNA methylation at single-base resolution. A large number of computational approaches are available in literature for identifying differentially methylated regions in bisulfite sequencing data, and more are being developed continuously. Results: Here, we focused on a comprehensive evaluation of commonly used differential methylation analysis methods and describe the potential strengths and limitations of each method. We found that there are large differences among methods, and no single method consistently ranked first in all benchmarking. Moreover, smoothing seemed not to improve the performance greatly, and a small number of replicates created more difficulties in the computational analysis of BS-seq data than low sequencing depth. Conclusions: Data analysis and interpretation should be performed with great care, especially when the number of replicates or sequencing depth is limited.

Serotonin/HTR1E signaling blocks chronic stress-promoted progression of ovarian cancer.

Rationale: Psychological stress has been linked to cancer development and resistance to therapy by many epidemiological and clinical studies. Stress-induced immunosuppressive microenvironment by stress hormones, in particular glucocorticoids, has been extensively studied. However, the impacts of other stress-related neurotransmitters, such as serotonin (5-hydroxytryptamine, 5-HT), on cancer development just start to be revealed. Here, we aimed to identify novel neurotransmitters involved in stress-induced growth and dissemination of ovarian cancer (OC) and reveal the major underlying signaling pathway and the therapeutic significance. Methods: Through a genome-wide CRISPR/Cas9 knockout screen in the murine orthotopic model of ovarian carcinoma (OC), we identified candidate genes regulating the peritoneal dissemination of OC. Among them, we picked out HTR1E, one member of 5-HT receptor family specifically expressed in the ovary and endometrium in addition to brain. The correlation of HTR1E expression with OC progression was analyzed in OC patient specimen by quantitative reverse transcription polymerase chain reaction (qRT-PCR), western blot, and immunohistochemistry (IHC). Gain-of-function and loss-of-function analyses were performed to explore the functions of 5-HT/HTR1E signaling in OC growth and dissemination in vitro and in vivo. In addition, we investigated the therapeutic values of HTR1E specific agonist and small molecular inhibitors against HTR1E downstream factor SRC in a stressed murine OC xenograft model. Results: In OC patients, the HTR1E expression is dramatically decreased in peritoneal disseminated OC cells, which correlates with poor clinical outcome. Silence of HTR1E in OC cells greatly promotes cell proliferation and epithelial mesenchymal transition (EMT) by the activation of SRC-mediated downstream signaling pathways. Furthermore, chronic stress results in significantly decreased serotonin in the ovary and the enhanced OC growth and peritoneal dissemination in mice, which can be strongly inhibited by specific HTR1E agonist or the SRC inhibitor. Conclusions: We discovered the essential role of serotonin/HTR1E signaling in preventing the chronic psychological stress-promoted progression of OC, suggesting the potential therapeutic value of the HTR1E specific agonist and the SRC inhibitor for OC patients who are suffering from psychological stress.

A systematic CRISPR screen reveals an IL-20/IL20RA-mediated immune crosstalk to prevent the ovarian cancer metastasis.

Transcoelomic spread of cancer cells across the peritoneal cavity occurs in most initially diagnosed ovarian cancer (OC) patients and accounts for most cancer-related death. However, how OC cells interact with peritoneal stromal cells to evade the immune surveillance remains largely unexplored. Here, through an in vivo genome-wide CRISPR/Cas9 screen, we identified IL20RA, which decreased dramatically in OC patients during peritoneal metastasis, as a key factor preventing the transcoelomic metastasis of OC. Reconstitution of IL20RA in highly metastatic OC cells greatly suppresses the transcoelomic metastasis. OC cells, when disseminate into the peritoneal cavity, greatly induce peritoneum mesothelial cells to express IL-20 and IL-24, which in turn activate the IL20RA downstream signaling in OC cells to produce mature IL-18, eventually resulting in the polarization of macrophages into the M1-like subtype to clear the cancer cells. Thus, we show an IL-20/IL20RA-mediated crosstalk between OC and mesothelial cells that supports a metastasis-repressing immune microenvironment.

Deep Learning Feature Extraction Approach for Hematopoietic Cancer Subtype Classification.

Hematopoietic cancer is a malignant transformation in immune system cells. Hematopoietic cancer is characterized by the cells that are expressed, so it is usually difficult to distinguish its heterogeneities in the hematopoiesis process. Traditional approaches for cancer subtyping use statistical techniques. Furthermore, due to the overfitting problem of small samples, in case of a minor cancer, it does not have enough sample material for building a classification model. Therefore, we propose not only to build a classification model for five major subtypes using two kinds of losses, namely reconstruction loss and classification loss, but also to extract suitable features using a deep autoencoder. Furthermore, for considering the data imbalance problem, we apply an oversampling algorithm, the synthetic minority oversampling technique (SMOTE). For validation of our proposed autoencoder-based feature extraction approach for hematopoietic cancer subtype classification, we compared other traditional feature selection algorithms (principal component analysis, non-negative matrix factorization) and classification algorithms with the SMOTE oversampling approach. Additionally, we used the Shapley Additive exPlanations (SHAP) interpretation technique in our model to explain the important gene/protein for hematopoietic cancer subtype classification. Furthermore, we compared five widely used classification algorithms, including logistic regression, random forest, k-nearest neighbor, artificial neural network and support vector machine. The results of autoencoder-based feature extraction approaches showed good performance, and the best result was the SMOTE oversampling-applied support vector machine algorithm consider both focal loss and reconstruction loss as the loss function for autoencoder (AE) feature selection approach, which produced 97.01% accuracy, 92.60% recall, 99.52% specificity, 93.54% F1-measure, 97.87% G-mean and 95.46% index of balanced accuracy as subtype classification performance measures.

Clinical Significance of Inflammation Markers in Predicting the Severity of Acute Pancreatitis.

OBJECTIVES: Acute pancreatitis (AP) is an inflammatory disease of the pancreas. We analyzed changes in inflammation markers to explore the clinical significance of using these markers to predict the severity of AP. METHODS: The study included 169 patients (severe AP = 50 and nonsevere AP = 119) admitted to Yanbian University Hospital between January 2015 and July 2017. The neutrophil-to-lymphocyte ratio (NLR), prognostic nutrition index (PNI), lymphocyte-to-monocyte ratio, red blood cell distribution width coefficient of variation, mean platelet volume, platelet-to-lymphocyte ratio, and red blood cell distribution width-to-platelet ratio of the patients were detected after admission. Correlations between AP severity and various inflammatory markers were statistically analyzed. RESULTS: The results indicated that the NLR on the first day after admission (area under the curve, 0.824; 95% confidence interval, 0.753-0.896) and the PNI on the third day after admission (area under the curve, 0.814; 95% confidence interval, 0.753-0.896) had more significance than other inflammation markers in predicting the severity of AP. In AP patients, the NLR showed a gradual decline, and the PNI initially decreased and then increased. CONCLUSIONS: The NLR and PNI can provide new reference values for predicting the severity of AP.

Nucleotide de novo synthesis increases breast cancer stemness and metastasis via cGMP-PKG-MAPK signaling pathway.

Metabolic reprogramming to fulfill the biosynthetic and bioenergetic demands of cancer cells has aroused great interest in recent years. However, metabolic reprogramming for cancer metastasis has not been well elucidated. Here, we screened a subpopulation of breast cancer cells with highly metastatic capacity to the lung in mice and investigated the metabolic alternations by analyzing the metabolome and the transcriptome, which were confirmed in breast cancer cells, mouse models, and patients' tissues. The effects and the mechanisms of nucleotide de novo synthesis in cancer metastasis were further evaluated in vitro and in vivo. In our study, we report an increased nucleotide de novo synthesis as a key metabolic hallmark in metastatic breast cancer cells and revealed that enforced nucleotide de novo synthesis was enough to drive the metastasis of breast cancer cells. An increased key metabolite of de novo synthesis, guanosine-5'-triphosphate (GTP), is able to generate more cyclic guanosine monophosphate (cGMP) to activate cGMP-dependent protein kinases PKG and downstream MAPK pathway, resulting in the increased tumor cell stemness and metastasis. Blocking de novo synthesis by silencing phosphoribosylpyrophosphate synthetase 2 (PRPS2) can effectively decrease the stemness of breast cancer cells and reduce the lung metastasis. More interestingly, in breast cancer patients, the level of plasma uric acid (UA), a downstream metabolite of purine, is tightly correlated with patient's survival. Our study uncovered that increased de novo synthesis is a metabolic hallmark of metastatic breast cancer cells and its metabolites can regulate the signaling pathway to promote the stemness and metastasis of breast cancer.

FZR1 as a novel biomarker for breast cancer neoadjuvant chemotherapy prediction.

The concept of breast-conserving surgery is a remarkable achievement of breast cancer therapy. Neoadjuvant chemotherapy is being used increasingly to shrink the tumor prior to surgery. Neoadjuvant chemotherapy is reducing the tumor size to make the surgery with less damaging to surrounding tissue and downstage locally inoperable disease to operable. However, non-effective neoadjuvant chemotherapy could increase the risks of delaying surgery, develop unresectable disease and metastatic tumor spread. The biomarkers for predicting the neoadjuvant chemotherapy effect are scarce in breast cancer treatment. In this study, we identified that FZR1 can be a novel biomarker for breast cancer neoadjuvant chemotherapy according to clinical patient cohort evaluation and molecular mechanism investigation. Transcriptomic data analysis indicated that the expression of FZR1 is correlated with the effect of neoadjuvant chemotherapy. Mechanistically, we demonstrate that FZR1 is pivotal to the chemotherapy drugs induced apoptosis and cell cycle arrest. FZR1 is involved in the stability of p53 by impairing the phosphorylation at ser15 site. We demonstrate that the expression of FZR1 detected by quantification of IHC can be an effective predictor of neoadjuvant chemotherapy in animal experiment and clinical patient cohort. To obtain more benefit for breast cancer patient, we propose that the FZR1 IHC score using at the clinical to predict the effect of neoadjuvant chemotherapy.

Is smoking a risk factor for bleeding in adult men with cerebral arteriovenous malformations? A single-center regression study from China.

OBJECTIVE: To assess whether smoking increases the risk of bleeding in patients with cerebral arteriovenous malformations (CAVM). MATERIAL AND METHODS: According to our research plan, 385 CAVM patients admitted to Beijing Tiantan Hospital from December 2015 to January 2018 were included in this study, including 210 bleeding patients and 175 non-bleeding patients. We divided patients into three subgroups of current smokers, ex-smokers (those who quit smoking for one year or more) and non-smokers. The relationship between smoking and the risk of CAVM rupture was assessed by univariate and multivariate regression analysis. RESULTS: Multivariate regression analysis showed that there was a statistically significant difference between current smoker and non-smoker (OR = 1.87, p = 0.019). Among the covariates of the multivariate regression analysis, the location, combined with blood flow-related intracranial aneurysms and size were related to the risk of CAVM bleeding. CONCLUSION: Current smoking may increase the risk of CAVM bleeding; however, there was no significant correlation between ex-smoking and CAVM bleeding.

Effect of growth modes on electrical and thermal transport of thermoelectric ZnO:Al films.

Electrical and thermal transport controlled by growth mode can be used to optimize thermoelectric properties of ZnO:Al films, which was adjusted by the re-evaporation of Zn and Al via substrate temperatures. The growth modes include equiaxed crystal, columnar crystal and coexistence of both crystals. In the ZnO:Al film, equiaxed crystals improve the carrier mobility and reduce the lattice thermal conductivity. Thus, the carrier mobility and thermal conductivity are tuned by the ratio of equiaxed crystals to columnar crystals. The carrier mobility is dependent on the growth-mode-related defects of oxygen vacancies, zinc interstitials and the substitutional dopant of Al. Improved thermoelectric properties with a power factor of 198.45 µW m-1 K-2 at 510 K were achieved. This study presents a film with the structure of an equiaxed-crystal buffer layer to enhance its thermoelectric properties.

Identification and validation of novel DNA methylation markers for early diagnosis of lung adenocarcinoma.

Lung cancer has the highest mortality of all cancers worldwide. Epigenetic alterations have emerged as potential biomarkers for early diagnosis of various cancer tissue types. To identify methylation markers for early diagnosis of lung adenocarcinoma, we aimed to integrate genome-wide DNA methylation and gene expression data from The Cancer Genome Atlas. To this end, we first examined the global DNA methylation pattern of lung adenocarcinoma and investigated the relationship between DNA methylation subtypes and clinical features. We then extracted differentially methylated and expressed genes, and adopted feature selection techniques to determine the final methylation markers. The performance of the markers in predicting lung adenocarcinoma was evaluated on three independent datasets from Gene Expression Omnibus. Protein levels of marker genes were validated by immunohistochemistry, and their biological function was further verified in vivo. We identified three novel methylation markers in lung adenocarcinoma including cg08032924, cg14823851, and cg19161124, mapping to CMTM2, TBX4, and DPP6, respectively. Validating these results on three independent datasets indicated that the three markers can achieve extremely high sensitivity and specificity in distinguishing lung adenocarcinoma from normal samples. Immunohistochemistry quantification results confirmed that markers are weakly expressed in human lung adenocarcinoma, and CMTM2 decreased tumor growth of mouse Lewis lung carcinoma in vivo. Overall, our study identified three novel methylation markers in lung adenocarcinoma which may contribute toward an improved diagnosis potentially leading to a better outcome for patients with lung adenocarcinoma.