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Glioma is a lethal malignant brain tumor, it comprises about 80% of all malignant brain tumours. Mounting evidence has reported that YTHDF2 plays a significant role in the cancer progression. However, the effects of YTHDF2 on the prognosis of low-grade gliomas (LGGs) and its correlation with tumor immune infiltration are unclear. The present study was designed to determine the biological functions of YTHDF2 in glioma and to evaluate the association of YTHDF2 expression with glioma progression.Clinical data on patients with glioma were obtained from The Cancer Genome Atlas (TCGA), the Chinese Glioma Genome Atlas (CGGA), the Gene Expression Omnibus (GEO), as well as the Rembrandt and Gravendeel databases. The correlations among YTHDF2 expression, pathological characteristics, glioma progression and clinical outcome were evaluated. In addition, the correlation of YTHDF2 expression with immune cell infiltration was analyzed too.We found that YTHDF2 was significantly up-regulated in LGGs which correlated with tumor grade and poor prognosis. Interestingly, we showed that YTHDF2 expression in LGG was associated with copy number variation, DNA hypomethylation, and induced transcription factor YY1. Besides, KEGG pathway analysis shows that YTHDF2 mainly participates in the immune response and oncogenic signaling pathway. Additionally, YTHDF2 is positively associated with diverse immune cells infiltration, immune cells, and multiple immune checkpoint molecules. Finally, we confirmed that YTHDF2 was highly expressed in LGGs tissues and correlated with the tumor grade with immunohistochemistry assay. More importantly, our results demonstrated that YTHDF2 was elevated in GBM cells. Knockdown of YTHDF2 significantly inhibits the proliferation and migration of GBM cells.YTHDF2 correlates with glioma progression and immune cell infiltration, suggesting that YTHDF2 may be a useful prognostic biomarker for glioma.

The study of yield traits can reveal the genetic architecture of grain yield for improving maize production. In this study, an association panel comprising 362 inbred lines and a recombinant inbred line population derived from X178 × 9782 were used to identify candidate genes for nine yield traits. High-priority overlap (HPO) genes, which are genes prioritized in a genome-wide association study (GWAS), were investigated using coexpression networks. The GWAS identified 51 environmentally stable SNPs in two environments and 36 pleiotropic SNPs, including three SNPs with both attributes. Seven hotspots containing 41 trait-associated SNPs were identified on six chromosomes by permutation. Pyramiding of superior alleles showed a highly positive effect on all traits, and the phenotypic values of ear diameter and ear weight consistently corresponded with the number of superior alleles in tropical and temperate germplasm. A total of 61 HPO genes were detected after trait-associated SNPs were combined with the coexpression networks. Linkage mapping identified 16 environmentally stable and 16 pleiotropic QTL. Seven SNPs that were located in QTL intervals were assigned as consensus SNPs for the yield traits. Among the candidate genes predicted by our study, some genes were confirmed to function in seed development. The gene Zm00001d016656 encoding a serine/threonine protein kinase was associated with five different traits across multiple environments. Some genes were uniquely expressed in specific tissues and at certain stages of seed development. These findings will provide genetic information and resources for molecular breeding of maize grain yield.

Gliomas are the most aggressive primary brain tumors. However, no significant improvement in survival has been achieved with the addition of temozolomide (TMZ) or radiation as initial therapy, although many clinical efforts have been carried out to target various signaling pathways or putative driver mutations. Here, we report that glycosyltransferase 8 domain containing 1 (GLT8D1), induced by HIF-1α under a hypoxic niche, significantly correlates with a higher grade of glioma, and a worse clinical outcome. Depletion of GLT8D1 inhibits self-renewal of glioma stem cell (GSC) in vitro and represses tumor growth in glioma mouse models. GLT8D1 knockdown promotes cell cycle arrest at G2/M phase and cellular apoptosis with or without TMZ treatment. We reveal that GLT8D1 impedes CD133 degradation through the endosomal-lysosomal pathway by N-linked glycosylation and protein-protein interaction. Directly blocking the GLT8D1/CD133 complex formation by CD133

Neural stem cells play pivotal roles during prenatal development and throughout life. Here, we report that Paired immunoglobulin-like receptor B (PirB) functions as a suppressor during brain neurogenesis in the adult mouse. PirB expression increased with age during development, and its deficiency promoted neural stem cell proliferation and differentiation in vivo and in vitro. Furthermore, we detected an increase in Type 1 neural stem cells in PirB-deficient mice compared to their wild-type littermates. PirB deficiency promoted stemness marker gene expression of Sox2 and KLF4 by activating Akt1 phosphorylation. These findings suggest that PirB inhibits the self-renewal and differentiation capacities of neural stem cells. Thus, PirB may have the potential to serve as a therapeutic target for treatment of reduced neurogenesis in adults due to aging or other pathological conditions.

We revealed that SNX20 was up-regulated in LGG, and its higher expression was associated with adverse clinical outcomes and poor clinical characteristics, including WHO grade, IDH mutation, 1p/19q codeletion, and primary therapy outcome. The results of the Cox regression analysis revealed that SNX20 was an independent factor for the prognosis of low-grade glioma. Meanwhile, we also established a nomogram based on SNX20 to predict the 1-, 3-, or 5-year survival in LGG patients. Furthermore, we found that DNA hypomethylation results in its overexpression in LGG. In addition, functional annotation confirmed that SNX20 was mainly involved in the immune response and inflammatory response related signaling pathways, including the T cell receptor signaling pathway, natural killer cell-mediated cytotoxicity, and the NF-kappa B signaling pathway. Finally, we determined that increased expression of SNX20 was correlated with infiltration levels of various immune cells and immune checkpoint in LGG. Importantly, we found that SNX20 was highly expressed in glioma cell lines. Depletion of SNX20 significantly inhibits glioma cell proliferation and migration abilities. This is the first study to identify SNX20 as a new potential prognostic biomarker and characterize the functional roles of SNX20 in the progression of LGG, and provides a novel potential diagnostic and therapeutic biomarker for LGG in the future.

The spindle assembly checkpoint (SAC) is a highly conserved monitoring system that ensures a fidelity of chromosome segregation during mitosis. Bub3, a mitotic Checkpoint Protein, is a member of the Bub protein family, and an important factor in the SAC. Abnormal expression of Bub3 results in mitotic defects, defective spindle gate function, chromosomal instability and the development of aneuploidy cells. Aneuploidy is a state of abnormal karyotype that has long been considered as a marker of tumorigenesis. Karyotypic heterogeneity in tumor cells, known as "chromosomal instability" (CIN), can be used to distinguish cancerous cells from their normal tissue counterpart. In this review, we summarize the expression and clinical significance of Bub3 in a variety of tumors and suggest that it has potential in the treatment of cancer.

Low grade glioma is one of the most common lethal cancers in the human nervous system. Emerging evidence has demonstrated that homeobox A cluster (HOXA) gene family plays a critical role in the transcriptional regulation as well as cancer initiation and progression. However, the expression, biological functions and upstream regulatory mechanism of 11 HOXAs in low grade glioma are not yet clear.In this study, we utilized various public databases and bioinformatics analyzed, including TCGA, CGGA, Rembrandt, HPA, LinkedOmics, cBioPortal, TISDIB, single-sample GSEA (ssGSEA), TIMER, LnCeVar, LASSO regression, Cox regression, Kaplan-Meier plot, and receiver operating, characteristic (ROC) analyses, GDSC and CTRP databases to analyzed the mRNA and protein expression profiles, gene mutation, clinical features, diagnosis, prognosis, signaling pathway, TMB, immune subtype, immune cell infiltration, immune modulator, ceRNA network and drug sensitivity of 11 HOXAs. Growth curve and transwell assays were utilized to study the biological characteristics of HOXA6 in LGG progression.In the present study, we found that 11 HOXAs (HOXA1, HOXA2, HOXA3, HOXA4, HOXA5, HOXA6, HOXA7, HOXA9, HOXA10, HOXA11 and HOXA3) were consistently up-regulated in LGG tissues and GBM tissues. Up-regulated of the HOXAs expression were significantly correlated with higher tumor stage, IDH mutation status, 1p/19q co-deletion, histological type and primary therapy outcome. Survival analyses showed that higher expression of HOXA1, HOXA2, HOXA3, HOXA4, HOXA5, HOXA7, HOXA9, HOXA10, HOXA11 and HOXA13 were correlated with shorter overall survival (OS), disease-specific survival (DSS) and progression-free survival (PFS) in LGG patients. Univariate and multivariate analyses revealed that HOXA1, HOXA6 expression and tumor grade, age, primary therapy outcome and age were independent factors affecting the prognosis of LGG patients. ROC curve analysis of HOXAs showed that HOXAs had a high accuracy (AUC0.80) in predicting LGG. Furthermore, gene functional enrichment analysis indicated that HOXAs mainly involved in the inflammatory response and immune regulation signaling pathway. CNV and DNA methylation significantly affect the expression of HOXAs. Finally, we uncover that HOXAs expression are highly correlated with immune cells infiltrate, immune modulator and drug sensitivity. We also uncover that the HOXAs related ceRNA network in LGG. More importantly, we found that HOXA6 was highly expressed in LGG cells lines and significantly affected their proliferation and migration abilities.In conclusion, our data demonstrated that HOXA was correlated with progression and immune infiltration, and could serve as a prognostic biomarker for LGG.

BackgroundIncreasing demand for minimally invasive myxoma resection. This study aimed to investigate the safety and feasibility of minimally invasive myxoma resection. MethodsThis is a retrospective study, we collected information on 95 patients who underwent myxoma resection from January 2016 to December 2020. According to the operative approach, they were divided into a minimally invasive myxoma resection(Mini-MR) group (n=30) and a sternotomy myxoma resection(SMR) group (n=65), we compared the intraoperative and postoperative data between the two groups. ResultsPostoperative ventilator assisted time, CSICU time and postoperative hospital stay of Mini-AVR were shorter than SAVR [(13.05 ± 4.98) VS (17.07 ± 9.52)h ;(1.73 ± 0.29) VS (2.27 ± 1.53)d; (6.20 ± 1.50) VS (9.48 ± 3.37)d], the difference was statistically significant (P

SUMMARY Inorganic phosphorus (Pi) is an essential element in numerous metabolic reactions and signaling pathways, but the molecular details of these pathways remain largely unknown. In this study, metabolite profiles of maize (Zea mays L.) leaves and roots were compared between six low‐Pi‐sensitive lines and six low‐Pi‐tolerant lines under Pi‐sufficient and Pi‐deficient conditions to identify pathways and genes associated with the low‐Pi stress response. Results showed that under Pi deprivation the concentrations of nucleic acids, organic acids and sugars were increased, but that the concentrations of phosphorylated metabolites, certain amino acids, lipid metabolites and nitrogenous compounds were decreased. The levels of secondary metabolites involved in plant immune reactions, including benzoxazinoids and flavonoids, were significantly different in plants grown under Pi‐deficient conditions. Among them, the 11 most stable metabolites showed significant differences under low‐ and normal‐Pi conditions based on the coefficient of variation (CV). Isoleucine and alanine were the most stable metabolites for the identification of Pi‐sensitive and Pi‐resistant maize inbred lines. With the significant correlation between morphological traits and metabolites, five low‐Pi‐responding consensus genes associated with morphological traits and simultaneously involved in metabolic pathways were mined by combining metabolites profiles and genome‐wide association study (GWAS). The consensus genes induced by Pi deficiency in maize seedlings were also validated by reverse‐transcription quantitative polymerase chain reaction (RT‐qPCR). Moreover, these genes were further validated in a recombinant inbred line (RIL) population, in which the glucose‐6‐phosphate‐1‐epimerase encoding gene mediated yield and correlated traits to phosphorus availability. Together, our results provide a framework for understanding the metabolic processes underlying Pi‐deficient responses and give multiple insights into improving the efficiency of Pi use in maize., Significance statement Metabolite profiling and GWAS were applied to reveal maize low‐Pi response mechanisms.

N6-methyladenosine (m6A) is the most prevalent, abundant and conserved internal cotranscriptional modification in eukaryotic RNAs, especially within higher eukaryotic cells. m6A modification is modified by the m6A methyltransferases, or writers, such as METTL3/14/16, RBM15/15B, ZC3H3, VIRMA, CBLL1, WTAP, and KIAA1429, and, removed by the demethylases, or erasers, including FTO and ALKBH5. It is recognized by m6A-binding proteins YTHDF1/2/3, YTHDC1/2 IGF2BP1/2/3 and HNRNPA2B1, also known as “readers”. Recent studies have shown that m6A RNA modification plays essential role in both physiological and pathological conditions, especially in the initiation and progression of different types of human cancers. In this review, we discuss how m6A RNA methylation influences both the physiological and pathological progressions of hematopoietic, central nervous and reproductive systems. We will mainly focus on recent progress in identifying the biological functions and the underlying molecular mechanisms of m6A RNA methylation, its regulators and downstream target genes, during cancer progression in above systems. We propose that m6A RNA methylation process offer potential targets for cancer therapy in the future.

Phosphorus (P) is required for numerous developmental processes, such as flowering and reproduction, in maize (Zea mays L.). It is also an essential nutrient in fertilizers to sustain high yields in farmlands with insufficient available phosphate, particularly in acid soils in China. Flowering time is a key factor influencing the adaptation of maize to the local environment and is associated with high yields. However, few studies have focused on the genetic characteristics of flowering time under low phosphate conditions. In this study, a recombinant inbred line (RIL) population derived from a cross between X178 and 9782 was evaluated for three flowering time traits under two phosphates (Pi) levels at four locations. We found that low phosphate significantly delayed the flowering stage of maize and proposed the hypothesis of “Phosphorus Accumulation Effect”. Mixed-model-based composite interval mapping was used to dissect the genetic basis of the flowering time traits. A total of 41 quantitative trait loci (QTL) was identified for the three flowering time traits through four procedures. Among these 41 QTL, 38 focused on four hot regions, including bin 2.02, bin 2.03, bin 5.04, and bin 6.01. These regions and linked markers should be the targets for fine mapping, map-based cloning, and marker-assisted selection of flowering time and phosphate utilization efficiency.

Triple-negative breast cancer (TNBC) is currently the most malignant subtype of breast cancers without effective targeted therapies. Mifepristone (MIF), a drug regularly used for abortion, has been reported to have anti-tumor activity in multiple hormone-dependent cancers, including luminal type breast cancers. In this study, we showed that MIF suppressed tumor growth of the TNBC cell lines and patient-derived xenografts in NOD-SCID mice. Furthermore, MIF reduced the TNBC cancer stem cell (CSC) population through down-regulating KLF5 expression, a stem cell transcription factor over-expressed in basal type TNBC and promoting cell proliferation, survival and stemness. Interestingly, MIF suppresses the expression of KLF5 through inducing the expression of miR-153. Consistently, miR-153 decreases CSC and miR-153 inhibitor rescued MIF-induced down-regulation of the KLF5 protein level and CSC ratio. Taken together, our findings suggest that MIF inhibits basal TNBC via the miR-153/KLF5 axis and MIF may be used for the treatment of TNBC.

Identification of risk factors of treatment resistance may be useful to guide treatment selection, avoid inefficient trial-and-error, and improve major depressive disorder (MDD) care. We extended the work in predictive modeling of treatment resistant depression (TRD) via partition of the data from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) cohort into a training and a testing dataset. We also included data from a small yet completely independent cohort RIS-INT-93 as an external test dataset. We used features from enrollment and level 1 treatment (up to week 2 response only) of STAR*D to explore the feature space comprehensively and applied machine learning methods to model TRD outcome at level 2. For TRD defined using QIDS-C16 remission criteria, multiple machine learning models were internally cross-validated in the STAR*D training dataset and externally validated in both the STAR*D testing dataset and RIS-INT-93 independent dataset with an area under the receiver operating characteristic curve (AUC) of 0.70-0.78 and 0.72-0.77, respectively. The upper bound for the AUC achievable with the full set of features could be as high as 0.78 in the STAR*D testing dataset. Model developed using top 30 features identified using feature selection technique (k-means clustering followed by χ2 test) achieved an AUC of 0.77 in the STAR*D testing dataset. In addition, the model developed using overlapping features between STAR*D and RIS-INT-93, achieved an AUC of > 0.70 in both the STAR*D testing and RIS-INT-93 datasets. Among all the features explored in STAR*D and RIS-INT-93 datasets, the most important feature was early or initial treatment response or symptom severity at week 2. These results indicate that prediction of TRD prior to undergoing a second round of antidepressant treatment could be feasible even in the absence of biomarker data.

Background: To determine the amount of co-expression of IDO and EGFR in breast cancer patients. Materials and Methods:In order to obtain the distribution of co-expression of IDO and EGFR in breast cancer, we tested 110 breast cancer paraffin tissue blocks with immunohistochemical methods. Then we investigated the relationship between the diagnostic and pathologic characteristics (tumor size, lymph node status, histologic grade, the gene expression of ER, PR, HER2, p53, Ki67 and PCNA) with the situation of co-expression of IDO and EGFR by reviewing the medical records of 32 breast cancer patients. Results: Among 110 breast cancers, 32 cases demonstrated IDO and EGFR co-expression (29.1%), IDO and EGFR synchronous co-expression being found in 19.1% and asynchronous in 10.0%. Conclusions: IDO and EGFR were co-expressed in breast cancer, including synchronous and asynchronous co-expression. The results suggest that considering IDO and EGFR as two indicators for breast cancer treatment or prognosis analysis provides a potential option of individual treatment for the portion of breast cancer patients with co-expression of IDO and EGFR.

Phosphorus (P) is one of the three primary macronutrients that are required in large amounts for plant growth and development. To better understand molecular mechanism of maize and identify relevant genes in response to phosphorus deficiency, we used Solexa/Illumina's digital gene expression (DGE) technology to investigate six genome-wide expression profiles of seedling roots of the low-P tolerant maize inbred line 178. DGE studies were conducted at 6, 24 and 72 h under both phosphorus deficient and sufficient conditions. Approximately 3.93 million raw reads for each sample were sequenced and 6 816 genes exhibited significant levels of differential expressions in at least one of three time points in response to P starvation. The number of genes with increased expression increased over time from 6 to 24 h, whereas genes with decreased expression were more abundant at 72 h, suggesting a gradual response process for P deficiency at different stages. Gene annotations illustrated that most of differentially expressed genes (DEGs) are involved in different cellular and molecular processes such as environmental adaptation and carbohydrate metabolism. The expression of some known genes identified in other plants, such as those involved in root architecture, P metabolism and transport were found to be altered at least two folds, indicating that the mechanisms of molecular and morphological adaptation to P starvation are conserved in plants. This study provides insight into the general molecular mechanisms underlying plant adaptation to low-P stress and thus may facilitate molecular breeding for improving P utilization in maize.

Few prospective studies have reported the cumulative incidence of venous thromboembolism (VTE) in the intensive care unit (ICU), especially for patients receiving guideline-recommended VTE prophylaxis. We aimed to design a prospective observational study to investigate the cumulative incidence and risk factors of ICU-acquired VTE for those populations. We prospectively studied 281 consecutively included patients in the ICU at a single center. All patients provided informed consent. Patients received ultrasound evaluation and were followed for VTE before ICU discharge or within 28 days of ICU stay. The type of VTE thromboprophylaxis was also recorded for all patients. Variables from univariate analyses that were associated with VTE were included in the binary logistic regression analysis to determine VTE predictors. The cumulative VTE incidence with 95% confidence interval (CI) was estimated using Kaplan–Meier methods. Patients had a median age of 60 years (range, 18–89) and an acute physiology and chronic health evaluation II score of 17 (range, 4–36). Despite all patients receiving guideline-recommended thromboprophylaxis, the cumulative incidence of VTE at 7, 14, 21, and 28 days was 4.45% (95% CI 2.55–7.71), 7.14% (95% CI 4.61–10.97), 7.53% (95% CI 4.92–11.43), and 9.55% (95% CI 6.55–13.81), respectively. Central venous catheter use (P = .002, odds ratio [OR] = 4.50), Caprini score (P = .012, OR = 1.20), and ICU length of stay (P = .006, OR = 1.08) were independent risk factors related to the incidence of VTE for patients admitted to the ICU. Our prospective observational study found that the 28-day cumulative incidence of VTE was relatively high for patients admitted to the ICU, despite the use of guideline-recommended thromboprophylaxis. Patients with femoral central venous catheter, prolonged ICU length of stay, or a high Caprini score may have an increased risk of developing VTE.

The E3 ubiquitin ligase RING finger protein 115 (RNF115), also known as breast cancer-associated gene 2 (BCA2), has previously been reported to be overexpressed in estrogen receptor α (ERα)-positive breast tumors and to promote breast cell proliferation; however, its mechanism is unknown. In this study, we demonstrated that silencing of BCA2 by small interfering RNAs (siRNAs) in two ERα-positive breast cancer cell lines, MCF-7 and T47D, decreases cell proliferation and increases the protein levels of the cyclin-dependent kinase inhibitor p21Waf/Cip1. The protein stability of p21 was negatively regulated by BCA2. BCA2 directly interacts with p21 and promotes p21 ubiquitination and proteasomal degradation. Knockdown of p21 partially rescues the cell growth arrest induced by the BCA2 siRNA. These results suggest that BCA2 promotes ERα-positive breast cancer cell proliferation at least partially through downregulating the expression of p21.

The prostate transmembrane protein, androgen-induced 1 (PMEPA1) has been previously shown to promote solid malignancies in a variety of cancers, but the role and mechanisms of PMEPA1 in breast cancer has not been fully addressed. Here, we found that PMEPA1 was upregulated in breast cancer cell lines as well as in a set of clinical invasive breast ductal carcinomas. Interestingly, depletion of PMEPA1 decreased breast cancer stem cell (CSC)-enriched populations, while ectopic overexpression of PMEPA1 increased breast CSC-enriched populations. Furthermore, transforming growth factor-β (TGF-β) treatment was also found to upregulate PMEPA1 expression and the CSC-enriched populations in triple-negative breast cancer cell lines. TGF-β-induced PMEPA1 expression partially contributed to TGF-β-induced breast CSC maintenance. These findings suggest that TGF-β-PMEPA1 axis might provide new diagnosis and therapeutic targets for breast cancer treatment.

// Chunyan Wang 1, 2, 3, * , Zhi Nie 3, * , Zhongmei Zhou 1 , Hailin Zhang 1 , Rong Liu 1 , Jing Wu 1, 2, 4 , Junying Qin 1, 2 , Yun Ma 3 , Liang Chen 3 , Shumo Li 3 , Wenlin Chen 5 , Fubing Li 1, 2 , Peiguo Shi 1, 2 , Yingying Wu 3 , Jian Shen 3 , Ceshi Chen 1 1 Key Laboratory of Animal Models and Human Disease Mechanisms of The Chinese Academy of Sciences and Yunnan Province, Kunming Institute of Zoology, Chinese Academy of Sciences, Kunming, Yunnan, China 2 University of The Chinese Academy of Sciences, Beijing, China 3 First Affiliated Hospital of Kunming Medical University, Kunming, Yunnan, China 4 Department of Biochemistry, Kunming Medical University, Kunming, Yunnan, China 5 Cancer Hospital, Kunming Medical University, Kunming, Yunnan, China * These authors have contributed equally to this work Correspondence to: Ceshi Chen, e-mail: chenc@mail.kiz.ac.cn Keywords: TEAD4, KLF5, p27, hippo pathway, TNBC Received: January 10, 2015 Accepted: April 10, 2015 Published: April 22, 2015 ABSTRACT Growing evidence suggests that YAP/TAZ are mediators of the Hippo pathway and promote breast cancer. However, the roles of YAP/TAZ transcription factor partners TEADs in breast cancer remain unclear. Here we found that TEAD4 was expressed in breast cancer cell lines, especially in triple negative breast cancers (TNBC) cell lines. TEAD4 binds to KLF5. Knockdown of either TEAD4 or KLF5 in HCC1937 and HCC1806 cells induced the expression of CDK inhibitor p27 . Depletion of either TEAD4 or KLF5 activated the p27 gene promoter and increased the p27 mRNA levels. Depletion of p27 partially prevents growth inhibition caused by TEAD4 and KLF5 knockdown. TEAD4 overexpression stimulated proliferation in vitro and tumor growth in mice, while stable knockdown of TEAD4 inhibited proliferation in vitro and tumor growth in mice. Thus TEAD4 and KLF5, in collaboration, promoted TNBC cell proliferation and tumor growth in part by inhibiting p27 gene transcription. TEAD4 is a potential target and biomarker for the development of novel therapeutics for breast cancer.

Summary We report the results of a DREAM challenge designed to predict relative genetic essentialities based on a novel dataset testing 98,000 shRNAs against 149 molecularly characterized cancer cell lines. We analyzed the results of over 3,000 submissions over a period of 4 months. We found that algorithms combining essentiality data across multiple genes demonstrated increased accuracy; gene expression was the most informative molecular data type; the identity of the gene being predicted was far more important than the modeling strategy; well-predicted genes and selected molecular features showed enrichment in functional categories; and frequently selected expression features correlated with survival in primary tumors. This study establishes benchmarks for gene essentiality prediction, presents a community resource for future comparison with this benchmark, and provides insights into factors influencing the ability to predict gene essentiality from functional genetic screens. This study also demonstrates the value of releasing pre-publication data publicly to engage the community in an open research collaboration.

BACKGROUND: Several studies have evaluated the association between plasminogen activator inhibitor-1 (PAI-1) -675 4G/5G polymorphism and sepsis in different populations. However, the available results are conflicting. METHODS: A search of Pubmed and EMBASE databases was performed to identify relevant studies for inclusion in the meta-analysis. Odds ratios (ORs) and corresponding 95% confidence intervals (CIs) were determined using a random-effects model. RESULTS: Twelve case-control studies and three cohort studies were included. Overall, a significant association between 4G/5G polymorphism and sepsis risk was observed for 4G/4G vs. 4G/5G +5G/5G (OR = 1.30, 95% CI 1.08-1.56, P = 0.006). In addition, there was a significant association between PAI-1 4G/5G polymorphism and sepsis-related mortality (OR = 1.72, 95% CI 1.27-2.33, P = 0.0005). In subgroup analyses, increased sepsis risk and mortality risk were found in Caucasians and in patients with sepsis. CONCLUSIONS: This meta-analysis suggested that the PAI-1 -675 4G/5G polymorphism was a risk factor for sepsis and sepsis mortality.

Designed a DNA-based genetic algorithm under the universal architecture of organic computing, combined particle swarm optimization algorithm, introduced a crossover operation for the particle location, can interfere with the particles speed, make inert particles escape the local optimum points, enhanced PSO algorithm's ability to get rid of local extreme point. Utilized improved algorithms to train the RBF neural network models, predict short-time traffic flow of a region intelligent traffic control. Simulation and error analysis of experimental results showed that, the designed algorithms can accurately forecast short-time traffic flow of the regional intelligent transportation control, forecasting effects is better, can be effectively applied to actual traffic engineering.

Membrane computing (P system) is a new computing model; it comes from the research of the basic function and structure of creatures cell membrane. It has complex structure and multi-level. It converges quickly and has high quality of the optimal results. In this article, discussed the basic theory of the membrane computing and the steps of the algorithm. Apply Membrane computing principle to the differential evolution algorithm, constructed a hybrid differential evolution algorithm on the basis of the membrane structure. Finally, utilized the Objective Functions to test the new algorithm performance, compared with related algorithms to analyze the advantages and disadvantages of the new algorithm.