Protein is important to the human body, and different sources of protein may have different effects on the risk of breast cancer. Thus, we conducted a meta-analysis to investigate the association between different dietary protein sources and breast cancer risk. PubMed and several databases were searched until December 2015. Relevant articles were retrieved according to specific searching criteria. Forty-six prospective studies were included. The summary relative risk (RR) for highest versus lowest intake was 1.07 (95% confidence interval (CI) 1.01–1.14, I2 = 34.6%) for processed meat, 0.92 (95% CI 0.84–1.00, I2 = 0%) for soy food, 0.93 (95% CI 0.85–1.00, I2 = 40.1%) for skim milk, and 0.90 (95% CI 0.82–1.00, I2 = 0%) for yogurt. Similar conclusions were obtained in dose-response association for each serving increase: total red meat (RR: 1.07; 95% CI 1.01–1.14, I2 = 7.1%), fresh red meat (RR: 1.13; 95% CI 1.01–1.26, I2 = 56.4%), processed meat (RR: 1.09; 95% CI 1.02–1.17, I2 = 11.8%), soy food (RR: 0.91; 95% CI 0.84–1.00, I2 = 0%), and skim milk (RR: 0.96; 95% CI 0.92–1.00, I2 = 11.9%). There was a null association between poultry, fish, egg, nuts, total milk, and whole milk intake and breast cancer risk. Higher total red meat, fresh red meat, and processed meat intake may be risk factors for breast cancer, whereas higher soy food and skim milk intake may reduce the risk of breast cancer.

Binding of 30S ribosomal subunits to mRNA during the initiation of prokaryotic translation is known to be influenced by the initiation codon and the Shine-Dalgarno sequence. Site-directed mutagenesis ofrnd, the Escherichia cofi gene encoding RNase D, has now shown that a Us sequence upstream of the Shine-Dalgarno region is also essential for expression of this mRNA. Alteration of two to five uridine residues within this sequence has no effect on mRNA levels but decreases RNase D protein and activity by as much as 95%, indicating that the U-rich sequence acts as an enhancer of translation. Moreover, mutant transcripts bind to 30S ribosomes in vitro with lower affinity than their wild-type counterparts, suggesting that the role of the Us sequence is in the initial binding of ribosomes to the translation initiation region of the message. These data demonstrate that sequences other than those previously recognized can be essential for translation initiation.Selection of the correct initiation codon by 30S ribosomal subunits is a primary determinant of accurate translation of mRNA in prokaryotic cells. However, despite extensive study, it is still not understood how this sequence of three nucleotides is distinguished from other residues in a message (1, 2). Factors known to influence the efficiency of binding of ribosomes to the translation initiation region of a mRNA include the initiation codon itself, a run of three to seven nucleotides upstream ofthe initiation codon termed the ShineDalgarno sequence, the spacing between these two segments, and the secondary structure of the initiation region (3,4). However, statistical analyses (5) and isolation of functional translation initiation regions (6) have shown that other sequences in these regions are nonrandom and may also play a role in the initiation process. Several possibilities for sequences upstream of the Shine-Dalgarno region that might function as translational enhancers have been proposed (7,8), although their significance is unclear. In addition to the RNA-RNA interactions between mRNA and ribosomes, it is likely that ribosomal proteins also participate in the selection of translation start sites, and protein S1 of the 30S subunit, in particular, has been implicated in this process (9). Based on UV crosslinking of protein S1 to phage and bacterial messages in vitro, it was suggested recently that pyrimidine-rich regions upstream of the Shine-Dalgarno sequence might interact with protein S1 and serve as ribosome recognition sites (10).During the course of studying the Escherichia coli rnd gene, which encodes the tRNA-processing enzyme RNase D, we identified (11, 12) a potential stem-loop structure followed by eight uridine residues located upstream of the initiator UUG codon and the Shine-Dalgarno sequence in the mRNA (Fig. 1). Although such a structure has features of a transcription terminator, when the stem-loop and uridine residues were deleted neither the rnd mRNA level nor the transcription start site was altered, but RNase D expression was el...

DNA methylation is a critical epigenetic mechanism involved in key cellular processes. Its deregulation has been linked to many human cancers including esophageal squamous cell carcinoma (ESCC). This study was designed to explore the whole methylation status of ESCC and to identify potential plasma biomarkers for early diagnosis. We used Infinium Methylation 450k array to analyze ESCC tissues (n = 4), paired normal surrounding tissues (n = 4) and normal mucosa from healthy individuals (n = 4), and combined these with gene expression data from the GEO database. One hundred and sixty eight genes had differentially methylated CpG sites in their promoter region and a gene expression pattern inverse to the direction of change in DNA methylation. These genes were involved in several cancer-related pathways. Three genes were validated in additional 42 ESCC tissues and paired normal surrounding tissues. The methylation frequency of EPB41L3, GPX3, and COL14A1 were higher in tumor tissues than in normal surrounding tissues (P<0.017). The higher methylation frequency of EPB41l3 was correlated with large tumor size (P = 0.044) and advanced pT tumor stage (P = 0.001). The higher methylation frequency of GPX3 and COL14A1 were correlated with advanced pN tumor stage (P = 0.001 and P<0.001). The methylation of EPB41L3, GPX3, and COL14A1 genes were only found in ESCC patients' plasma, but not in normal individuals upon testing 42 ESCC patients and 50 healthy individuals. Diagnostic sensitivity was increased when methylation of any of the 3 genes were counted (64.3% sensitivity and 100% specificity). These differentially methylated genes in plasma may be used as biomarkers for early diagnosis of ESCC.

Repeated infection with high-risk HPV is a major cause for the development and metastasis of human cervical cancer, even though the mechanism of the metastasis is still not completely understood. Here, we reported that miR-218 (microRNA-218) was downregulated in cervical cancer tissues, especially in metastatic cancer tissues. We found that miR-218 expression was associated with clinicopathological characteristics of patients with cervical cancer. MiR-218 overexpression inhibited Epithelial-Mesenchymal Transition (EMT), migration and invasiveness of cervical cancer cells in vitro. Moreover, miR-218 repressed the expression of SFMFBT1 (Scm-like with four MBT domains 1) and DCUN1D1 (defective in cullin neddylation 1, domain containing 1) by direct binding to the 3′UTRs of the mRNAs. The overexpression of SFMBT1 induced EMT and increased the migration and invasiveness of cervical cancer cells, while the overexpression of DCUN1D1 increased the migration and invasiveness of these cells, but did not induce EMT. An inverse correlation was observed between the expression of miR-218 and DCUN1D1 protein in cervical cancer tissues. Importantly, HPV16 E6 downregulated the expression of miR-218 in cervical cancer, while miR-218 rescued the promotion effect of HPV16 E6 on the expression of SFMBT1 and DCUN1D1. Taken together, our results revealed that HPV16 E6 promoted EMT and invasion in cervical cancer via the repression of miR-218, while miR-218 inhibited EMT and invasion in cervical cancer by targeting SFMBT1 and DCUN1D1.

Casein kinase I (CKI) is a family of serine/threonine protein kinases found in all eukaryotes examined to date. Here, the rat CKI isoforms alpha and alpha L were cloned and expressed in both eukaryotic and prokaryotic systems. Characterization of the genomic DNA flanking the exon unique to CKI alpha L demonstrated that CKI alpha and CKI alpha L arise by the alternative splicing of a common pre-mRNA molecule. To the best of our knowledge, the alpha L isoform is the only known active serine/threonine kinase to contain an insert within its catalytic domain. Tissue distribution of each splicing isoform was examined by RT-PCR, immunoprecipitation, and Western blotting. Both isoforms were expressed in all tissues tested but at different levels. Bacterially expressed CKI alpha isoforms were active and therefore biochemically characterized. CKI alpha and CKI alpha L proteins were demonstrated to have casein kinase I catalytic properties. More importantly, the recombinant isoform proteins exhibited differences in binding and activity toward common CKI substrates. These observations demonstrate that the alpha L insert within the kinase domain modulates substrate kinetics. These kinetic differences suggest that CKI alpha and CKI alpha L may perform different biological roles.

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Although there have been reports about the role of erythrocyte membrane protein band 4.1 like 3 (EPB41L3) in several types of cancer, primarily in non-small-cell lung carcinoma, the molecular function and modulatory mechanisms of EPB41L3 remain unclear. In specific, the functional and clinical significance of EPB41L3 in esophageal squamous cell carcinoma (ESCC) has not been explored to date. In the present study, reduced EPB41L3 expression was demonstrated in ESCC cell lines and tissues, which was due to its high methylation rate. Ectopic expression of EPB41L3 in ESCC cells inhibited cell proliferation in vivo and in vitro. In addition, EPB41L3 overexpression induced apoptosis and G2/M cell cycle arrest by activating Caspase-3/8/9 and Cyclin-dependent kinase 1/Cyclin B1 signaling, respectively. Notably, patients with higher EPB41L3 expression had markedly higher overall survival rates compared with patients with lower EPB41L3 expression. In summary, the present results suggest that EPB41L3 may be a tumor suppressor gene in ESCC development, representing a potential therapeutic target and a prognostic indicator for ESCC.

In automatic parking motion planning, multi-objective optimization including safety, comfort, parking efficiency, and final parking performance should be considered. Most of the current research relies on the parking data from expert drivers or prior knowledge of humans. However, it is challenging to obtain a large amount of high-quality expert drivers' data. Furthermore, expert drivers' data or prior knowledge of humans does not guarantee an optimal multi-objective parking performance. In this paper, we propose a model-based reinforcement learning method that learns parking policy of the data, by executing the data generation, data evaluation, and training network, iteratively. The trained network is used to guide the data generation cycle in the subsequent iteration. Based on this proposed method, we can get rid of human experience largely and learn parking strategies autonomously and quickly. The learned strategies ensure the multi-objective optimality of above requirements in the parking process. First, an environment model that approximates the actual environment is established, and the learning efficiency is accelerated through the simulated interaction between the agent and the environment model. To make the system independent of expert data or prior knowledge, a data generation algorithm combining Monte Carlo Tree Search (MCTS) and longitudinal and lateral policies is proposed. Then, to meet the multi-objective optimal demands mentioned above, a reward function is constructed to evaluate and filter the parking data. Finally, a neural network is used to learn the parking strategy from the filtered data. From the real vehicle test benchmarked with a mass-produced parking system, the proposed method is found to achieve better parking efficiency and lower requirements for start parking posture, thereby verifying the algorithm's superiority.