Totally laparoscopic gastrectomy with natural orifice (vagina) specimen extraction in gastric cancer: Introduction of a new technique.

Radical excision by surgery is the main treatment method for gastric cancer and as the surgery develops, the laparoscopic treatment effect on gastric cancer is gradually being verified. The totally laparoscopic gastrectomy (TLG) with natural orifice specimen extraction surgery (NOSES) for gastric cancer has attracted people's attention by avoiding abdominal incision and further reducing surgical injury and provides ideas for the further development of minimally invasive surgical treatment on the basis of laparoscopy. Surgical technique of TLG with natural orifice (vagina) specimen extraction is detailed in the text. We have employed NOSES in 4 cases of TLG in the past year. The visual analogue scale score was low, and all patients had no complications during and after the operation. No recurrence or metastasis was found in the short-term follow-up. TLG with NOSES is feasible and has many advantages such as aesthetics, light post-operative pain.

Designing a general method for predicting the regulatory relationships between long noncoding RNAs and protein-coding genes based on multi-omics characteristics.

MOTIVATION: Long noncoding RNA (lncRNA) has been verified to interact with other biomolecules especially protein-coding genes (PCGs), thus playing essential regulatory roles in life activities and disease development. However, the inner mechanisms of most lncRNA-PCG relationships are still unclear. Our study investigated the characteristics of true lncRNA-PCG relationships and constructed a novel predictor with machine learning algorithms. RESULTS: We obtained the 307 true lncRNA-PCG pairs from database and found that there are significant differences in multiple characteristics between true and random lncRNA-PCG sets. Besides, 3-fold cross-validation and prediction results on independent test sets show the great AUC values of LR, SVM and RF, among which RF has the best performance with average AUC 0.818 for cross-validation, 0.823 and 0.853 for two independent test sets, respectively. In case study, some candidate lncRNA-PCG relationships in colorectal cancer were found and HOTAIR-COMP interaction was specially exemplified. The proportion of the reported pairs in the predicted positive results was significantly higher than that in negative results (P < 0.05). SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Genome-wide identification of the essential protein-coding genes and long non-coding RNAs for human pan-cancer.

MOTIVATION: Genome-scale CRISPR/Cas9 system has been a democratized gene editing technique and widely used to investigate gene functions in some biological processes and diseases especially cancers. Aiming to characterize gene aberrations and assess their effects on cancer, we designed a pipeline to identify the essential genes for pan-cancer. METHODS: CRISPR screening data were used to identify the essential genes that were collected from published data and integrated by Robust Rank Aggregation algorithm. Then, hypergeometrics test and random walks with restart (RWR) were used to predict additional essential genes on broader scale. Finally, the expression status and potential roles of these genes were explored based on TCGA portal and regulatory network analysis. RESULTS: We collected 926 samples from 10 CRISPR-based screening studies involving 33 different types of cancer to identify cancer-essential genes, which consists of 799 protein-coding genes (PCGs) and 97 long non-coding RNAs (lncRNAs). Then, we constructed a 'bi-colored' network with both PCGs and lncRNAs and applied it to predict additional essential genes including 495 PCGs and 280 lncRNAs on a broader scale using hypergeometrics test and RWR. After obtaining all essential genes, we further investigated their potential roles in cancer and found that essential genes have higher and more stable expression levels, and are associated with multiple cancer-associated biological processes and survival time. The regulatory network analysis detected two intriguing modules of essential genes participating in the regulation of cell cycle and ribosome biogenesis in cancer. AVAILABILITY AND IMPLEMENTATION: . SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.

Network analysis of KLF5 targets showing the potential oncogenic role of SNHG12 in colorectal cancer.

BACKGROUND: KLF5 is a member of the Kruppel-like factor, subfamily of zinc finger proteins that are involved in cancers. KLF5 functions as a transcription factor and regulates the diverse protein-coding genes (PCGs) in colorectal cancer (CRC). However, the long non-coding RNAs (lncRNAs) regulated by KLF5 in CRC are currently unknown. METHODS: In this study, we first designed a computational pipeline to determine the PCG and lncRNA targets of KLF5 in CRC. Then we analyzed the motif pattern of the binding regions for the lncRNA targets. The regulatory co-factors of KLF5 were then searched for through bioinformatics analysis. We also constructed a regulatory network for KLF5 and annotated its functions. Finally, one of the KLF5 lncRNA targets, SNHG12, was selected to further explore its expression pattern and functions in CRC. RESULTS: We were able to identify 19 lncRNA targets of KLF5 and found that the motifs of the lncRNA binding sites were GC-enriched. Next, we pinpointed the transcription factors AR and HSF1 as the regulatory co-factors of KLF5 through bioinformatics analysis. Then, through the analysis of the regulatory network, we found that KLF5 may be involved in DNA replication, DNA repair, and the cell cycle. Furthermore, in the cell cycle module, the SNHG12 up-regulating expression pattern was verified in the CRC cell lines and tissues, associating it to CRC invasion and distal metastasis. This indicates that SNHG12 may play a critical part in CRC tumorigenesis and progression. Additionally, expression of SNHG12 was found to be down-regulated in CRC cell lines when KLF5 expression was knocked-down by siRNA; and a strong correlation was observed between the expression levels of SNHG12 and KLF5, further alluding to their regulatory relationship. CONCLUSIONS: In conclusion, the network analysis of KLF5 targets indicates that SNHG12 may be a significant lncRNA in CRC.

Knowledge-based analyses reveal new candidate genes associated with risk of hepatitis B virus related hepatocellular carcinoma.

BACKGROUND: Recent genome-wide association studies (GWASs) have suggested several susceptibility loci of hepatitis B virus (HBV)-related hepatocellular carcinoma (HCC) by statistical analysis at individual single-nucleotide polymorphisms (SNPs). However, these loci only explain a small fraction of HBV-related HCC heritability. In the present study, we aimed to identify additional susceptibility loci of HBV-related HCC using advanced knowledge-based analysis. METHODS: We performed knowledge-based analysis (including gene- and gene-set-based association tests) on variant-level association p-values from two existing GWASs of HBV-related HCC. Five different types of gene-sets were collected for the association analysis. A number of SNPs within the gene prioritized by the knowledge-based association tests were selected to replicate genetic associations in an independent sample of 965 cases and 923 controls. RESULTS: The gene-based association analysis detected four genes significantly or suggestively associated with HBV-related HCC risk: SLC39A8, GOLGA8M, SMIM31, and WHAMMP2. The gene-set-based association analysis prioritized two promising gene sets for HCC, cell cycle G1/S transition and NOTCH1 intracellular domain regulates transcription. Within the gene sets, three promising candidate genes (CDC45, NCOR1 and KAT2A) were further prioritized for HCC. Among genes of liver-specific expression, multiple genes previously implicated in HCC were also highlighted. However, probably due to small sample size, none of the genes prioritized by the knowledge-based association analyses were successfully replicated by variant-level association test in the independent sample. CONCLUSIONS: This comprehensive knowledge-based association mining study suggested several promising genes and gene-sets associated with HBV-related HCC risks, which would facilitate follow-up functional studies on the pathogenic mechanism of HCC.

The regulatory network analysis of long noncoding RNAs in human colorectal cancer.

Colorectal cancer (CRC) is among one of the most prevalent and lethiferous diseases worldwide. Long noncoding RNAs (lncRNAs) are commonly accepted to function as a key regulatory factor in human cancer, but the potential regulatory mechanisms of CRC-associated lncRNA are largely obscure. Here, we integrated several expression profiles to obtain 55 differentially expressed (DE) lncRNAs. We first detected lncRNA interactions with transcription factors, microRNAs, mRNAs, and RNA-binding proteins to construct a regulatory network and then create functional enrichment analyses for them using bioinformatics approaches. We found the upregulated genes in the regulatory network are enriched in cell cycle and DNA damage response, while the downregulated genes are enriched in cell differentiation, cellular response, and cell signaling. We then employed module-based methods to mine several intriguing modules from the overall network, which helps to classify the functions of genes more specifically. Next, we confirmed the validity of our network by comparisons with a randomized network using computational method. Finally, we attempted to annotate lncRNA functions based on the regulatory network, which indicated its potential application. Our study of the lncRNA regulatory network provided significant clues to unveil lncRNAs potential regulatory mechanisms in CRC and laid a foundation for further experimental investigation.

Identification of long noncoding RNAs in Schistosoma mansoni and Schistosoma japonicum.

Schistosomiasis is a major parasitic disease caused by 3 principal species of schistosome. Studies of schistosome transcriptomes have focused on protein-coding transcripts and although miRNAs are attracting increased attention, few reports have concerned the long noncoding RNAs (lncRNAs). These have been shown to play key roles in the regulation of gene expression through interactions with mRNAs, proteins and miRNAs. In this study, we first identified lncRNAs from RNA-seq data in Schistosoma mansoni and Schistosoma japonicum: 3247 and 3033 potential lncRNAs were found in these two species respectively. ChIP-seq analysis to determine H3K4me3 profiles along the gene regions corresponding to lncRNAs showed that in 12% of cases this mark was enriched in regions proximal to the transcription start sites, supporting their validity as actively transcribed genes. Besides, the sequence conservation of lncRNAs between schistosome species was much lower than that of mRNAs, but higher than that of the randomly selected genomic sequences, which is consistent with that in mammals. Our results demonstrate that lncRNAs form a significant part of the schistosome transcriptome and suggest that they play an important role in the biology of the parasite.

Effects of Different Doses of Levetiracetam on Aquaporin 4 Expression in Rats with Brain Edema Following Fluid Percussion Injury.

BACKGROUND This study was designed to investigate the effects of different doses of levetiracetam on aquaporin 4 (AQP4) expression in rats after fluid percussion injury. MATERIAL AND METHODS Sprague-Dawley rats were randomly divided into 4 groups: sham operation group, traumatic brain injury group, low-dose levetiracetam group, and high-dose levetiracetam group. Brain edema models were established by fluid percussion injury, and intervened by the administration of levetiracetam. Samples from the 4 groups were collected at 2, 6, 12, and 24 h, and at 3 and 7 days after injury. Histological observation was performed using hematoxylin-eosin staining and immunohistochemical staining. AQP4 and AQP4 mRNA expression was detected using Western blot assay and RT-PCR. Brain water content was measured by the dry-wet method. RESULTS Compared with the traumatic brain injury group, brain water content, AQP4 expression, and AQP4 mRNA expression were lower in the levetiracetam groups at each time point and the differences were statistically significant (P<0.05). The intervention effects of high-dose levetiracetam were more apparent. CONCLUSIONS Levetiracetam can lessen brain edema from fluid percussion injury by down-regulating AQP4 and AQP4 mRNA expression. There is a dose-effect relationship in the preventive effect of levetiracetam within a certain extent.

Molecular epidemiology and evolution of human enterovirus 71 and hand, foot and mouth disease.

Human enterovirus 71(EV71), one of the major pathogens of the hand, foot and mouth disease (HFMD), causes skin rashes in palms, feet and mouth ulcers and complication in the central nervous system such as aseptic meningitis and acute flaccid paralysis that may lead to death. EV71 infection has been reported to be associated with many outbreaks of HFMD worldwide, especially the great outbreaks that occurred in the Asia-Pacific region and caused numerous death since 1997. The studies of molecular epidemiology and evolution of EV71 are important for the prevention and control of HFMD since no vaccines and antiviral drugs have been developed except symptomatic treatment for HFMD. In this review, we summarize genotype classification, temporal and spatial distribution, evolutionary characteristics and modes of EV71 as well as typical EV71 epidemics. Further studies on EV71 and HFMD may lead to better understanding of pathological mechanisms of EV71, development of antiviral drugs and prevention and control of HFMD.

[Advances on gene-based association analysis].

Genome-wide association studies (GWAS) have been widely used for hunting the susceptibility genes for common diseases in the past years; however, the abundant information for the disease mechanism based on the GWAS data has not been fully mined. Recently, some researchers focused on the biological network and pathway analysis for the GWAS data to explore the potential disease mechanism. Since genes are the basic units for the biological network and pathway, the genetic effects from all or part of single nucleotide polymorphisms (SNPs) in the genes should be integrated into genetic scores, which are so-called "gene-based association analysis". Gene-based association analysis takes into account some important factors such as genetic effects of the SNPs, the number of the SNPs in the genes and the linkage disequilibrium structure of the SNPs. In this review, we will focus on the progress, principle and application of gene-based association analysis.

In silico epitope prediction and evolutionary analysis reveals capsid mutation patterns for enterovirus B.

Enterovirus B (EVB) is a common species of enterovirus, mainly consisting of Echovirus (Echo) and Coxsackievirus B (CVB). The population is generally susceptible to EVB, especially among children. Since the 21st century, EVB has been widely prevalent worldwide, and can cause serious diseases, such as viral meningitis, myocarditis, and neonatal sepsis. By using cryo-electron microscopy, the three-dimensional (3D) structures of EVB and their uncoating receptors (FcRn and CAR) have been determined, laying the foundation for the study of viral pathogenesis and therapeutic antibodies. A limited number of epitopes bound to neutralizing antibodies have also been determined. It is unclear whether additional epitopes are present or whether epitope mutations play a key role in molecular evolutionary history and epidemics, as in influenza and SARS-CoV-2. In the current study, the conformational epitopes of six representative EVB serotypes (E6, E11, E30, CVB1, CVB3 and CVB5) were systematically predicted by bioinformatics-based epitope prediction algorithm. We found that their epitopes were distributed into three clusters, where the VP1 BC loop, C-terminus and VP2 EF loop were the main regions of EVB epitopes. Among them, the VP1 BC loop and VP2 EF loop may be the key epitope regions that determined the use of the uncoating receptors. Further molecular evolution analysis based on the VP1 and genome sequences showed that the VP1 C-terminus and VP2 EF loop, as well as a potential "breathing epitope" VP1 N-terminus, were common mutation hotspot regions, suggesting that the emergence of evolutionary clades was driven by epitope mutations. Finally, footprints showed mutations were located on or near epitopes, while mutations on the receptor binding sites were rare. This suggested that EVB promotes viral epidemics by breaking the immune barrier through epitope mutations, but the mutations avoided the receptor binding sites. The bioinformatics study of EVB epitopes may provide important information for the monitoring and early warning of EVB epidemics and developing therapeutic antibodies.

Dimethylation of histone H3 lysine 36 (H3K36me2) as a potential biomarker for glioma diagnosis, grading, and prognosis.

Abnormal histone methylation plays a key role in glioma development but the clinical value of specific alterations is still unclear. Here, the potential significance of histone H3 lysine 36 dimethylation (H3K36me2) was investigated as a biomarker for glioma. Seventy-three glioma patients were included in the study and the level of H3K36me2 in the tumor tissues was determined by immunohistochemistry. The χ2 test was used to explore the influence of clinical and pathological characteristics on H3K36me2 levels. The Kaplan-Meier method was used to estimate progression-free survival (PFS) and overall survival (OS). COX regression was used to explore the relationship between H3K36me2 levels and glioma prognosis. The results indicated that the H3K36me2 level increases with glioma grade. The proportion of high H3K36me2 levels was lower in glioma patients under the age of 52 years. H3K36me2 levels were negatively correlated with IDH1 mutation and MGMT promoter methylation, and positively correlated with p53 expression. Thus, high H3K36me2 levels positively correlated with poor prognosis of gliomas. In conclusion, H3K36me2 may be considered as a potential biomarker for glioma diagnosis, grading, and prognosis, but the overall clinical value of H3K36me2 determination deserves further investigation. These results may have important implications for accurate diagnosis and future precision treatment of gliomas.

Jujuboside B inhibits febrile seizure by modulating AMPA receptor activity.

ETHNOPHARMACOLOGICAL RELEVANCE: Febrile seizure is a common neurologic disorder with limited treatment occurring in infants and children under the age of five. Jujuboside B (JuB) is a main bioactive saponin component isolated from the Chinese anti-insomnia herbal medicine Ziziphi Spinosae Semen (ZSS), seed of Ziziphus jujuba Mill, which has been proved to exhibit neuroprotective effects recently. AIM OF THE STUDY: In this study, we aimed at elucidating the effect of JuB on suppressing febrile seizure and the potential mechanisms. METHODS: Electroencephalogram (EEG) recording was used to monitor the severity of febrile seizures. The JuB in the brain was identified by mass spectrometry. Neuronal excitability was investigated using patch clamp. RESULTS: JuB (30 mg/kg) significantly prolonged seizure latency and reduced the severity in hyperthermia-induced seizures model mice. Hippocampal neuronal excitability was significantly decreased by JuB. And JuB significantly reduced the excitatory synaptic transmission mediated by α-amino-3-hydroxy-5-methyl-4-iso-xazolepropionic acid receptor (AMPAR), including evoked excitatory postsynaptic currents (eEPSCs), and miniature EPSCs (mEPSCs) in hippocampal neurons. Furthermore, JuB also significantly inhibited recombinant GluA1 and GluA2 mediated AMPA current in HEK293 cell and decreased the upregulation of [Ca2+]i induced by AMPA in primary cultured cortex neurons. CONCLUSIONS: JuB suppressed the excitability of hippocampal neurons by inhibiting the activity of AMPAR and reducing the intracellular free calcium, thereby relieving febrile seizures.

Detecting transmission and reassortment events for influenza A viruses with genotype profile method.

Evolutionary events of transmission and reassortment for influenza A viruses were traditionally detected by phylogenetic analysis for influenza viruses' eight gene segments. Because the phylogenetic analysis can be complex, we developed genotype profile method which packaged the phylogenetic algorithms to analyze combination patterns of gene segments and integrated epidemiology knowledge. With the method, the analysis of reassortment and transmission becomes a simple and reliable process that combines genotypes, which is identical for the biological process of the virus. An application called IVEE that implements the method is available for all academic users to apply the method http://snptransformer.sourceforge.net. Furthermore, we found that a previous summary of the reassortment events in swine influenza A viruses may be inaccurate.

[Advances on genomic evolution of influenza virus].

Four influenza virus pandemics occurred since the beginning of the 20th century. In 1918, 1957, 1968 and 2009, this disease threatened human health and social living greatly. The progress in genomic evolution of influenza virus promoted exploring pathogenic mechanism, surveilling epidemic, preparing influenza vaccine and developing anti-virus drugs. Here, we reviewed the progress in genomic evolution of influenza virus that included evolution mechanism, antigenic evolution, and anti-drug.

[Sleep quality and influencing factors of perimenopausal women in Ningbo region].

OBJECTIVE: To investigate the sleep quality and influencing factors of perimenopausal women in Ningbo region. METHODS: A total of 527 perimenopausal women who lived in Ningbo for more than 5 years were enrolled in the study. The subjects were surveyed by self-designed questionnaire and Pittsburgh sleep quality index (PSQI); PSQI > 7 was defined as the cut-off value for sleep quality. Data were analyzed by software SPSS 11.0. RESULT: The mean PSQI score was 5.79 ± 3.08 and 23.6 % of perimenopausal women in the study showed poor sleep quality. The proportion of poor sleep in 55-60 age group was 40.2%, significantly higher than that of 40-44, 45-49 and 50-54 age groups (P < 0.05). The sleep quality was associated with physical exercise, social activity, sleep circumstance, anxiety and family income in perimenopausal women. CONCLUSION: The sleep quality of perimenopausal women and the influencing factors are associated with mental health, life style and social environment, which suggests that some interventions should be undertaken to improve the sleep quality of perimenopausal women.

The role of conformational epitopes in the evolutionary divergence of enterovirus D68 clades: A bioinformatics-based study.

Enterovirus D68 (EV-D68), as one of the major pathogens of paediatric respiratory disease, has been widely spread in the population in recent years. As the basis of virus antigenicity, antigenic epitopes are essential to monitoring the transformation of virus antigenicity. However, there is a lack of systematic studies on the antigenic epitopes of EV-D68. In this study, a bioinformatics-based prediction algorithm for human enteroviruses was used to predict the conformational epitopes of EV-D68. The prediction results showed that the conformational epitopes of EV-D68 were clustered into three sites: site 1, site 2, and site 3. Site 1 was located in the "north rim" region of the canyon near the fivefold axis; site 2 was located in the "puff" region near the twofold axis; and site 3 consisted of two parts, one in the "knob" region on the south rim of the canyon and the other in the threefold axis region. The predicted epitopes overlapped highly with the binding regions of four reported monoclonal antibodies (mAbs), indicating that the predictions were highly reliable. Phylogenetic analysis showed that amino acid mutations in the epitopes of the VP1 BC loop, DE loop, C-terminus, and VP2 EF loop played a crucial role in the evolutionary divergence of EV-D68 clades/subclades and epidemics. This finding indicated that the VP1 BC loop, DE loop, C-terminus, and VP2 EF loop were the most important epitopes of EV-D68. Research on the epitopes of EV-D68 will contribute to outbreak surveillance and to the development of diagnostic reagents and recombinant vaccines.

Bioinformatics-based prediction of conformational epitopes for Enterovirus A71 and Coxsackievirus A16.

Enterovirus A71 (EV-A71), Coxsackievirus A16 (CV-A16) and CV-A10 are the major causative agents of hand, foot and mouth disease (HFMD). The conformational epitopes play a vital role in monitoring the antigenic evolution, predicting dominant strains and preparing vaccines. In this study, we employed a Bioinformatics-based algorithm to predict the conformational epitopes of EV-A71 and CV-A16 and compared with that of CV-A10. Prediction results revealed that the distribution patterns of conformational epitopes of EV-A71 and CV-A16 were similar to that of CV-A10 and their epitopes likewise consisted of three sites: site 1 (on the "north rim" of the canyon around the fivefold vertex), site 2 (on the "puff") and site 3 (one part was in the "knob" and the other was near the threefold vertex). The reported epitopes highly overlapped with our predicted epitopes indicating the predicted results were reliable. These data suggested that three-site distribution pattern may be the basic distribution role of epitopes on the enteroviruses capsids. Our prediction results of EV-A71 and CV-A16 can provide essential information for monitoring the antigenic evolution of enterovirus.

Bioinformatics-based prediction of conformational epitopes for human parechovirus.

Human parechoviruses (HPeVs) are human pathogens that usually cause diseases ranging from rash to neonatal sepsis in young children. HPeV1 and HPeV3 are the most frequently reported genotypes and their three-dimensional structures have been determined. However, there is a lack of systematic research on the antigenic epitopes of HPeVs, which are useful for understanding virus-receptor interactions, developing antiviral agents or molecular diagnostic tools, and monitoring antigenic evolution. Thus, we systematically predicted and compared the conformational epitopes of HPeV1 and HPeV3 using bioinformatics methods in the study. The results showed that both epitopes clustered into three sites (sites 1, 2 and 3). Site 1 was located on the "northern rim" near the fivefold vertex; site 2 was on the "puff"; and site 3 was divided into two parts, of which one was located on the "knob" and the other was close to the threefold vertex. The predicted epitopes highly overlapped with the reported antigenic epitopes, which indicated that the prediction results were accurate. Although the distribution positions of the epitopes of HPeV1 and HPeV3 were highly consistent, the residues varied largely and determined the genotypes. Three amino acid residues, VP3-91N, -92H and VP0-257S, were the key residues for monoclonal antibody (mAb) AM28 binding to HPeV1 and were also of great significance in distinguishing HPeV1 and HPeV3. We also found that two residues, VP1-85N and -87D, might affect the capability of mAb AT12-015 to bind to HPeV3.

Gene expression module-based chemical function similarity search.

Investigation of biological processes using selective chemical interventions is generally applied in biomedical research and drug discovery. Many studies of this kind make use of gene expression experiments to explore cellular responses to chemical interventions. Recently, some research groups constructed libraries of chemical related expression profiles, and introduced similarity comparison into chemical induced transcriptome analysis. Resembling sequence similarity alignment, expression pattern comparison among chemical intervention related expression profiles provides a new way for chemical function prediction and chemical-gene relation investigation. However, existing methods place more emphasis on comparing profile patterns globally, which ignore noises and marginal effects. At the same time, though the whole information of expression profiles has been used, it is difficult to uncover the underlying mechanisms that lead to the functional similarity between two molecules. Here a new approach is presented to perform biological effects similarity comparison within small biologically meaningful gene categories. Regarding gene categories as units, a reduced similarity matrix is generated for measuring the biological distances between query and profiles in library and pointing out in which modules do chemical pairs resemble. Through the modularization of expression patterns, this method reduces experimental noises and marginal effects and directly correlates chemical molecules with gene function modules.