Search

Protonation, Fe2+ and solvent can induce different acidic structures and Lewis activity of Fe-IL by analyzing the slope of IA(X) ∼ n(Py).

The oxidation activity and solvation effect of iron-based ionic liquid (BmimFeCl4) are significantly affected by the structure and polarity of the added solvents.

To investigate the role of Lin28A in ovariectomy-induced osteoporosis and to elucidate the underlying molecular mechanism.Bilateral ovariectomy was conducted to generate an ovariectomy (OVX) rat model. Western blotting was performed to assess the relative expression levels of Lin28A, osteocalcin (OCN), runt-related transcription factor 2 (RUNX2), adenosine monophosphate-activated protein kinase (AMPK) and phosphorylated AMPK (p-AMPK) proteins. Enzyme-linked immunosorbent assays were performed to detect the serum levels of calcium, E2, alkaline phosphatase (ALP) and interleukin (IL)-1β. Three-point bending test was used to assess biomechanical parameters of left femoral diaphysis. Hematoxylin and eosin (HE) staining was conducted to detect the trabecular structure of bone tissue. Dihydroethidium assay kit was used to measure the intracellular reactive oxygen species (ROS) level in osteoclasts. Alizarin red staining revealed the calcium deposit in bone marrow stromal cells (BMSC).The expression levels of Lin28A, OCN, RUNX2, AMPK and p-AMPK proteins were significantly decreased in OVX rats. The serum levels of calcium, E2, ALP and IL-1β were significantly declined in OVX rats. Biomechanical parameters of left femoral diaphysis were significantly decreased in OVX rats. OVX-induced trabecular abnormalities. ROS level was dramatically increased in the bone tissue of OVX rats, and calcium deposit was dramatically decreased in BMSC cells of OVX rats. These effects induced by OVX could be prevented by overexpression of Lin28A.Lin28A alleviates ovariectomy-induced osteoporosis through activation of AMPK pathway in rats.

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62–66. ©2017 AACR.

A figure showing the process of generating and using PDX models.

Objective To provide prenatal diagnosis for a pregnant woman with genetic history of intellectual disability. Case report A Chinese pedigree with intellectual disability was collected in this study. Cytogenetic analysis, chromosomal microarray analysis (CMA) and whole exome sequencing (WES) followed by Sanger validation were conducted to identify the genetic pathogenesis. A novel heterozygous deletion c.370_374delTTCCC in TBR1 gene was identified, leading to a frameshift mutation starting at Phe124 followed by a premature stop codon at position 141 (p.Phe124Valfs∗18). Segregation analysis identified that this novel mutation is co-segregated among the affected family members but absent in unaffected family members. Prenatal diagnosis indicated the absence of this mutation, and the family decided to continue the pregnancy after genetic counseling. Conclusion Our findings demonstrated the significance of genetic testing in the diagnosis of intellectual disability. This work also confirmed the effectiveness of WES in prenatal diagnosis.

Introduction. To explore the clinical value of noninvasive prenatal testing (NIPT) in screening the chromosomal abnormalities of the fetus in the elderly pregnant women. Materials and Methods. Between January 2020 and December 2021, 1949 elderly pregnant women underwent NIPT in our hospital. At the same time, 236 elderly pregnant women received invasive prenatal diagnosis, and the pregnancy outcomes were followed-up. Results. When NIPT was used for prenatal screening of fetal chromosomal aneuploidy, its diagnostic coincidence rate for trisomy 21 was the highest, with a coincidence rate of 90.00%, and the diagnostic coincidence rate for other chromosomal abnormalities was the lowest, only 22.22%. The sensitivity, specificity, positive predictive rate, and negative predictive rate for T21 by NIPT were 100%, 99.97%, 94.28%, and 100%; for T18 were 100%, 99.92%, 72.22%, and 100%, respectively; and for T13 were 100%, 99.95%, 50%, and 100%, respectively. Patients with high risks according to NIPT results further received invasive prenatal diagnosis, and 18 cases were excluded from the follow-up. For the remaining 1933 cases in the NIPT group, there was an incidence of 2.28% of adverse pregnancy outcomes. For the remaining 234 cases in the Amniocentesis group, there was an incidence of 1.28% of adverse pregnancy outcomes. There was no significant difference between the two groups ( P > 0.05 ). The diagnostic rate of fetal chromosomal abnormalities in pregnant women under 40 years old was about 0.39-0.79%; however, the risk for people over 40 is relatively high at 1.32-4.44%. Conclusion. The noninvasive prenatal screening of fetal DNA in the second trimester of pregnancy for elderly pregnant women has high application value in the prediction of pregnancy outcome. The high risk of pregnancy can be determined by detecting trisomy 21, 18, and 13 syndromes, and the probability of adverse pregnancy outcome increases.

Background Down syndrome is characterized by trisomy 21 or partial duplication of chromosome 21. Extensive studies have focused on the identification of the Down Syndrome Critical Region (DSCR). We aim to provide evidence that duplication of 21q21.1-q21.2 should not be included in the DSCR and it has no clinical consequences on the phenotype. Case presentation Because serological screening was not performed at the appropriate gestational age, noninvasive prenatal testing (NIPT) analysis was performed for a pregnant woman with normal prenatal examinations at 22 weeks of gestation. The NIPT results revealed a 5.8 Mb maternally inherited duplication of 21q21.1-q21.2. To assess whether the fetus also carried this duplication, ultrasound-guided amniocentesis was conducted, and the result of chromosomal microarray analysis (CMA) with amniotic fluid showed a 6.7 Mb duplication of 21q21.1-q21.2 (ranging from position 18,981,715 to 25,707,009). This partial duplication of 21q21.1-q21.2 in the fetus was maternally inherited. After genetic counseling, the pregnant woman and her family decided to continue the pregnancy. Conclusion Our case clearly indicates that 21q21.1-q21.2 duplication is not included in the DSCR and most likely has no clinical consequences on phenotype.

To provide genetic counseling and prenatal diagnosis for a fetus with mosaic trisomy 20.Chromosomal karyotyping, chromosomal microarray analysis (CMA) and fluorescence in situ hybridization (FISH) were carried out for a pregnant woman with advanced maternal age.The karyotype of amniotic fluid sample was 47,XN,+20, whilst the result of CMA was normal. To verify this discrepancy, CMA was performed again with the cultured amniotic fluid, which yielded a result of 47,XN,+20. FISH assay of the amniotic fluid sample was nuc ish(D20Z1)×3[11]/(D20Z1)×2[89], which indicated that about 11% of fetal cells were trisomy 20. After the fetus was born, the karyotype of peripheral blood sample was normal.The amniotic fluid sample might be mosaic trisomy 20, and a dominant growth of 47,XN,+20 cells had occurred during the culture process, resulting in alteration of amniotic fluid cell composition. Mosaic trisomy 20 indicated by FISH may be attributed to confined placental mosaicism or somatic mosaicism of trisomy 20.

Osteosarcoma is the most prevalent primary bone malignancy in children and adolescents. Neoadjuvant chemotherapy combined with surgical resection, the current standard treatment of osteosarcoma, is associated with a 5-year survival rate of only ~70%. Therefore, it is necessary to identify new, more effective treatment strategies for patients with this lethal disease. Enoxacin is a highly effective broad-spectrum fluoroquinolone antibiotic with low toxicity. The drug inhibits the growth and metastasis of numerous tumour types, but its efficacy has not been studied in osteosarcoma. This study assessed the antitumour effects of enoxacin in osteosarcoma 143B cells and in a murine tumour xenograft model. Enoxacin inhibited the proliferation, invasion and migration of 143B cells, as well as inducing their apoptosis. These effects were thought to be mediated by downregulation of Bcl-xL, Bxl-2, matrix metalloproteinase (MMP)2 and MMP9 expression. Enoxacin also significantly impaired the growth of bone tumours in nude mice without affecting their liver or kidney function, or blood cell count. Collectively, these results indicate that enoxacin is a promising new drug for osteosarcoma that warrants further evaluation in clinical studies.

Post-operative infections in orthopaedic implants are severe complications that require urgent solutions. Although conventional antibiotics limit bacterial biofilms formation, they ignore the bone loss caused by osteoclast formation during post-operative orthopaedic implant-related infections. Fortunately, enoxacin exerts dual antibacterial and osteoclast inhibitory effects, playing a pivot in limiting infection and preventing bone loss. However, enoxacin lacks specificity in bone tissue and low bioavailability-relate side effects, which hinders translational practice. Herein, we developed a nanosystem (Eno@MSN-D) based on enoxacin (Eno)-loaded mesoporous silica nanoparticles (MSN), decorated with the eight repeating sequences of aspartate (D-Asp8), and coated with polyethylene glycol (PEG). This Eno@MSN-D delivery nanosystem exhibited both antibacterial and anti-osteoclast properties in vitro. More importantly, Eno@MSN-D allowed the targeted release of enoxacin in infected bone tissues and prevented implant-related infection and bone loss in vivo. Therefore, our work highlights the significance of novel biomaterials that offer new alternatives to treat and prevent orthopaedic staphylococcus aureus-related implantation infections and bone loss.

Background Cleft lip with or without cleft palate (CL/P) is the most common craniofacial anomaly with a high incidence of live births. The specific pathogenesis of CL/P is still unclear, although plenty of studies have been conducted. Variations of tumor protein 63 (TP63) was reported to be related to the phenotype of CL/P. The case discussed in this report involves a pedigree with mutation at TP63 gene, and the variation was not reported before. Case presentation A Chinese pedigree with CL/P was collected in this study. The proband is a 3-year-old boy with the phenotype of CL/P, while his global development and intelligence are normal. After two CL/P repair operations, he looks almost normal. The proband's uncle and grandmother both have the phenotype of CL/P. Cytogenetic analysis and chromosomal microarray analysis (CMA) were performed, followed by whole exome sequencing (WES) and sanger validation. Analysis of WES revealed a variant of C>T at nucleotide position 1324 (1324C>T) of TP63 gene, possibly producing a truncated protein with a premature stop codon at amino acid position 442 (p.Q442*). This mutation was localized at the oligomerization domain (OD) of TP63 and might impair the capacity of p63 oligomerization. Conclusion The mutation in TP63 was recognized to be the possible cause of the phenotype of CL/P in this pedigree. This report provides some evidence for the clinical diagnosis of CL/P. And our study also provides clinical evidence for the molecular mechanism of TP63 gene causing nonsyndromic cleft lip with or without cleft palate (NSCL/P).

Patient-derived tumor xenograft (PDX) mouse models have emerged as an important oncology research platform to study tumor evolution, mechanisms of drug response and resistance, and tailoring chemotherapeutic approaches for individual patients. The lack of robust standards for reporting on PDX models has hampered the ability of researchers to find relevant PDX models and associated data. Here we present the PDX models minimal information standard (PDX-MI) for reporting on the generation, quality assurance, and use of PDX models. PDX-MI defines the minimal information for describing the clinical attributes of a patient's tumor, the processes of implantation and passaging of tumors in a host mouse strain, quality assurance methods, and the use of PDX models in cancer research. Adherence to PDX-MI standards will facilitate accurate search results for oncology models and their associated data across distributed repository databases and promote reproducibility in research studies using these models. Cancer Res; 77(21); e62–66. ©2017 AACR.

Short-head and long-tail distributed data are widely observed in the real world. The same is true of recommender systems (RSs), where a small number of popular items dominate the choices and feedback data while the rest only account for a small amount of feedback. As a result, most RS methods tend to learn user preferences from popular items since they account for most data. However, recent research in e-commerce and marketing has shown that future businesses will obtain greater profit from long-tail selling. Yet, although the number of long-tail items and users is much larger than that of short-head items and users, in reality, the amount of data associated with long-tail items and users is much less. As a result, user preferences tend to be popularity-biased. Furthermore, insufficient data makes long-tail items and users more vulnerable to shilling attack. To improve the quality of recommendations for items and users in the tail of distribution, we propose a coupled regularization approach that consists of two latent factor models: C-HMF, for enhancing credibility, and S-HMF, for emphasizing specialty on user choices. Specifically, the estimates learned from C-HMF and S-HMF recurrently serve as the empirical priors to regularize one another. Such coupled regularization leads to the comprehensive effects of final estimates, which produce more qualitative predictions for both tail users and tail items. To assess the effectiveness of our model, we conduct empirical evaluations on large real-world datasets with various metrics. The results prove that our approach significantly outperforms the compared methods.

Additional file 1. Full search strategy for Pubmed database.

Post-operative infections in orthopaedic implants are severe complications that require urgent solutions. Owing to the presence of implants and the formation of bacterial biofilms, the efficacy of antibiotics is limited. Furthermore, osteoclasts can become extremely active, accompanied by bone loss in the infected microenvironment. Therefore, implants often need to be removed. To improve the concentrations of antibiotics in bony tissues and enhance their effectiveness in preventing bacterial biofilm formation, the infection rate must be controlled to preserve the implants. Enoxacin exerts combined antibacterial and osteoclast inhibitory effects. It also plays a role in limiting infections and preventing bone loss. Aspartic acid octapeptide (ASP8) can also recognize and combine with hydroxyapatite crystals in bones and can be targeted to increase antibiotic concentrations in bones. Our previous research showed that preparing mesoporous nanomaterials resulted in optimal drug loading, releasing, and bone-targeting properties. Based on earlier research, a new bone-targeted antibiotic release system was developed. Enoxacin and ASP8 were loaded on mesoporous silica nanoparticles (MSNs) to increase antibiotic concentrations, prevent bacterial biofilm formation, inhibit aberrant osteoclast activities, and reduce bone loss. Enoxacin-loaded MSNs (Gen@MSN-D) were assessed using a variety of experimental methods, including rat models. We studied the in vitro antibacterial properties of the new drug delivery system. We found that these materials had antibacterial properties in vivo, inhibitory effects on osteoclasts, and can be used to prevent and treat post-implantation infections and bone loss. Therefore, we believe these materials will provide a new method for preventing and treating post-operative, orthopaedic implant-associated infections.

Recommender systems (RS) have become an integral part of our daily life. However, most current RS often repeatedly recommend items to users with similar profiles. We argue that recommendation should be diversified by leveraging session contexts with personalized user profiles. For this, current session-based RS (SBRS) often assume a rigidly ordered sequence over data which does not fit in many real-world cases. Moreover, personalization is often omitted in current SBRS. Accordingly, a personalized SBRS over relaxedly ordered user-session contexts is more pragmatic. In doing so, deep-structured models tend to be too complex to serve for online SBRS owing to the large number of users and items. Therefore, we design an efficient SBRS with shallow wide-in-wide-out networks, inspired by the successful experience in modern language modelings. The experiments on a real-world e-commerce dataset show the superiority of our model over the state-of-the-art methods.

The Influenza Research Database (IRD) is a U.S. National Institute of Allergy and Infectious Diseases (NIAID)-sponsored Bioinformatics Resource Center dedicated to providing bioinformatics support for influenza virus research. IRD facilitates the research and development of vaccines, diagnostics and therapeutics against influenza virus by providing a comprehensive collection of influenza-related data integrated from various sources, a growing suite of analysis and visualization tools for data mining and hypothesis generation, personal workbench spaces for data storage and sharing, and active user community support. Here, we describe the recent improvements in IRD including the use of cloud and high performance computing resources, analysis and visualization of user-provided sequence data with associated metadata, predictions of novel variant proteins, annotations of phenotype-associated sequence markers and their predicted phenotypic effects, hemagglutinin (HA) clade classifications, an automated tool for HA subtype numbering conversion, linkouts to disease event data and the addition of host factor and antiviral drug components. All data and tools are freely available without restriction from the IRD website at https://www.fludb.org.

In the real-world environment, users have sufficient experience in their focused domains but lack experience in other domains. Recommender systems are very helpful for recommending potentially desirable items to users in unfamiliar domains, and cross-domain collaborative filtering is therefore an important emerging research topic. However, it is inevitable that the cold-start issue will be encountered in unfamiliar domains due to the lack of feedback data. The Bayesian approach shows that priors play an important role when there are insufficient data, which implies that recommendation performance can be significantly improved in cold-start domains if informative priors can be provided. Based on this idea, we propose a Weighted Irregular Tensor Factorization (WITF) model to leverage multi-domain feedback data across all users to learn the cross-domain priors w.r.t. both users and items. The features learned from WITF serve as the informative priors on the latent factors of users and items in terms of weighted matrix factorization models. Moreover, WITF is a unified framework for dealing with both explicit feedback and implicit feedback. To prove the effectiveness of our approach, we studied three typical real-world cases in which a collection of empirical evaluations were conducted on real-world datasets to compare the performance of our model and other state-of-the-art approaches. The results show the superiority of our model over comparison models.

Several viruses within the Coronaviridae family have been categorized as either emerging or re-emerging human pathogens, with Severe Acute Respiratory Syndrome Coronavirus (SARS-CoV) being the most well known. The NIAID-sponsored Virus Pathogen Database and Analysis Resource (ViPR, www.viprbrc.org) supports bioinformatics workflows for a broad range of human virus pathogens and other related viruses, including the entire Coronaviridae family. ViPR provides access to sequence records, gene and protein annotations, immune epitopes, 3D structures, host factor data, and other data types through an intuitive web-based search interface. Records returned from these queries can then be subjected to web-based analyses including: multiple sequence alignment, phylogenetic inference, sequence variation determination, BLAST comparison, and metadata-driven comparative genomics statistical analysis. Additional tools exist to display multiple sequence alignments, view phylogenetic trees, visualize 3D protein structures, transfer existing reference genome annotations to new genomes, and store or share results from any search or analysis within personal private ‘Workbench’ spaces for future access. All of the data and integrated analysis and visualization tools in ViPR are made available without charge as a service to the Coronaviridae research community to facilitate the research and development of diagnostics, prophylactics, vaccines and therapeutics against these human pathogens.

The Virus Pathogen Database and Analysis Resource (ViPR, www.ViPRbrc.org) is an integrated repository of data and analysis tools for multiple virus families, supported by the National Institute of Allergy and Infectious Diseases (NIAID) Bioinformatics Resource Centers (BRC) program. ViPR contains information for human pathogenic viruses belonging to the Arenaviridae, Bunyaviridae, Caliciviridae, Coronaviridae, Flaviviridae, Filoviridae, Hepeviridae, Herpesviridae, Paramyxoviridae, Picornaviridae, Poxviridae, Reoviridae, Rhabdoviridae and Togaviridae families, with plans to support additional virus families in the future. ViPR captures various types of information, including sequence records, gene and protein annotations, 3D protein structures, immune epitope locations, clinical and surveillance metadata and novel data derived from comparative genomics analysis. Analytical and visualization tools for metadata-driven statistical sequence analysis, multiple sequence alignment, phylogenetic tree construction, BLAST comparison and sequence variation determination are also provided. Data filtering and analysis workflows can be combined and the results saved in personal 'Workbenches' for future use. ViPR tools and data are available without charge as a service to the virology research community to help facilitate the development of diagnostics, prophylactics and therapeutics for priority pathogens and other viruses.

We introduce a simple, broadly applicable method for obtaining estimates of nucleotide diversity θ from genomic shotgun sequencing data. The method takes into account the special nature of these data: random sampling of genomic segments from one or more individuals and a relatively high error rate for individual reads. Applying this method to data from the Celera human genome sequencing and SNP discovery project, we obtain estimates of nucleotide diversity in windows spanning the human genome and show that the diversity to divergence ratio is reduced in regions of low recombination. Furthermore, we show that the elevated diversity in telomeric regions is mainly due to elevated mutation rates and not due to decreased levels of background selection. However, we find indications that telomeres as well as centromeres experience greater impact from natural selection than intrachromosomal regions. Finally, we identify a number of genomic regions with increased or reduced diversity compared with the local level of human–chimpanzee divergence and the local recombination rate.

Anopheles gambiae is the principal vector of malaria, a disease that afflicts more than 500 million people and causes more than 1 million deaths each year. Tenfold shotgun sequence coverage was obtained from the PEST strain of A. gambiae and assembled into scaffolds that span 278 million base pairs. A total of 91% of the genome was organized in 303 scaffolds; the largest scaffold was 23.1 million base pairs. There was substantial genetic variation within this strain, and the apparent existence of two haplotypes of approximately equal frequency (“dual haplotypes”) in a substantial fraction of the genome likely reflects the outbred nature of the PEST strain. The sequence produced a conservative inference of more than 400,000 single-nucleotide polymorphisms that showed a markedly bimodal density distribution. Analysis of the genome sequence revealed strong evidence for about 14,000 protein-encoding transcripts. Prominent expansions in specific families of proteins likely involved in cell adhesion and immunity were noted. An expressed sequence tag analysis of genes regulated by blood feeding provided insights into the physiological adaptations of a hematophagous insect.

Primate-specific segmental duplications are considered important in human disease and evolution. The inability to distinguish between allelic and duplication sequence overlap has hampered their characterization as well as assembly and annotation of our genome. We developed a method whereby each public sequence is analyzed at the clone level for overrepresentation within a whole-genome shotgun sequence. This test has the ability to detect duplications larger than 15 kilobases irrespective of copy number, location, or high sequence similarity. We mapped 169 large regions flanked by highly similar duplications. Twenty-four of these hot spots of genomic instability have been associated with genetic disease. Our analysis indicates a highly nonrandom chromosomal and genic distribution of recent segmental duplications, with a likely role in expanding protein diversity.

This paper describes a new approach to normalizing microarray expression data. The novel feature is to unify the tasks of estimating normalization coefficients and identifying control gene set. Unification is realized by constructing a window function over the scatter plot defining the subset of constantly expressed genes and by affecting optimization using an iterative procedure. The structure of window function gates contributions to the control gene set used to estimate normalization coefficients. This window measures the consistency of the matched neighborhoods in the scatter plot and provides a means of rejecting control gene outliers. The recovery of normalizational regression and control gene selection are interleaved and are realized by applying coupled operations to the mean square error function. In this way, the two processes bootstrap one another. We evaluate the technique on real microarray data from breast cancer cell lines and complement the experiment with a data cluster visualization study.

Animal models remain a cornerstone of research efforts in Oncology to model the complexity of cancer progression and to discover new therapeutic approaches to disease management. With the advent of new genomic manipulation techniques such as CRISPR, and advances in mouse modeling with genetically engineered mice (GEM) and patient-derived xenografts (PDX), we can expect the development of novel and powerful animal models in the near future. These techniques are expanding our capability for pre-clinical testing of novel therapeutic agents or for n-of-1 patient-specific disease modeling. However, the reliability of animal models to faithfully recapitulate human disease, especially cancer, remains controversial, as evidenced by numerous therapeutic agents that show promise in animal models but fail in clinical trials. We propose a new scoring system called the Oncology Model Fidelity Scores, which allow researchers and clinicians to compare animal models and select those most suited for the question at hand, whether in basic science, for translational research, or within clinical applications. The formalism and tools we are developing for the analysis of mouse models and other model organisms are based on the Hallmarks of Cancer and therapeutic pathways as well as The Cancer Genome Atlas (TCGA) and other comprehensive systems. The scoring system begins with RNASEQ expression data and DNA variation analysis, and is designed for use in mapping animal models both to individual patients and to a TCGA cohort. We are applying this scoring system to mouse models available through NCI’s Oncology Model Forum and we are analyzing how these animal models compare to human cancers based on TCGA data. Ultimately, the development of an Oncology Model Fidelity Score will help to advance patient care through efficient identification and validation of animal models for a variety of applications, from pre-clinical testing of novel therapeutics to the use of patient-specific animal models. Citation Format: Debajyoti Datta, Theodore Goldstein, Zhiping Gu, Atul Butte. Oncology model fidelity scores [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2017; 2017 Apr 1-5; Washington, DC. Philadelphia (PA): AACR; Cancer Res 2017;77(13 Suppl):Abstract nr LB-006. doi:10.1158/1538-7445.AM2017-LB-006

© 2014 IEEE. Choice modeling (CM) aims to describe and predict choices according to attributes of subjects and options. If we presume each choice making as the formation of link between subjects and options, immediately CM can be bridged to link analysis and prediction (LAP) problem. However, such a mapping is often not trivial and straightforward. In LAP problems, the only available observations are links among objects but their attributes are often inaccessible. Therefore, we extend CM into a latent feature space to avoid the need of explicit attributes. Moreover, LAP is usually based on binary linkage assumption that models observed links as positive instances and unobserved links as negative instances. Instead, we use a weaker assumption that treats unobserved links as pseudo negative instances. Furthermore, most subjects or options may be quite heterogeneous due to the long-tail distribution, which is failed to capture by conventional LAP approaches. To address above challenges, we propose a Bayesian heteroskedastic choice model to represent the non-identically distributed linkages in the LAP problems. Finally, the empirical evaluation on real-world datasets proves the superiority of our approach.

A 2.91-billion base pair (bp) consensus sequence of the euchromatic portion of the human genome was generated by the whole-genome shotgun sequencing method. The 14.8-billion bp DNA sequence was generated over 9 months from 27,271,853 high-quality sequence reads (5.11-fold coverage of the genome) from both ends of plasmid clones made from the DNA of five individuals. Two assembly strategies—a whole-genome assembly and a regional chromosome assembly—were used, each combining sequence data from Celera and the publicly funded genome effort. The public data were shredded into 550-bp segments to create a 2.9-fold coverage of those genome regions that had been sequenced, without including biases inherent in the cloning and assembly procedure used by the publicly funded group. This brought the effective coverage in the assemblies to eightfold, reducing the number and size of gaps in the final assembly over what would be obtained with 5.11-fold coverage. The two assembly strategies yielded very similar results that largely agree with independent mapping data. The assemblies effectively cover the euchromatic regions of the human chromosomes. More than 90% of the genome is in scaffold assemblies of 100,000 bp or more, and 25% of the genome is in scaffolds of 10 million bp or larger. Analysis of the genome sequence revealed 26,588 protein-encoding transcripts for which there was strong corroborating evidence and an additional ∼12,000 computationally derived genes with mouse matches or other weak supporting evidence. Although gene-dense clusters are obvious, almost half the genes are dispersed in low G+C sequence separated by large tracts of apparently noncoding sequence. Only 1.1% of the genome is spanned by exons, whereas 24% is in introns, with 75% of the genome being intergenic DNA. Duplications of segmental blocks, ranging in size up to chromosomal lengths, are abundant throughout the genome and reveal a complex evolutionary history. Comparative genomic analysis indicates vertebrate expansions of genes associated with neuronal function, with tissue-specific developmental regulation, and with the hemostasis and immune systems. DNA sequence comparisons between the consensus sequence and publicly funded genome data provided locations of 2.1 million single-nucleotide polymorphisms (SNPs). A random pair of human haploid genomes differed at a rate of 1 bp per 1250 on average, but there was marked heterogeneity in the level of polymorphism across the genome. Less than 1% of all SNPs resulted in variation in proteins, but the task of determining which SNPs have functional consequences remains an open challenge.

The chloramphenicol (Cm)-inducible cmlA gene of Tn1696 specifies nonenzymatic resistance to Cm and is regulated by attenuation. The first eight codons of the leader specify a peptide that inhibits peptidyl transferase in vitro. Functionally similar, but less inhibitory, peptides are encoded by the leaders of Cm-inducible cat genes. However, the cat and cmlA coding sequences are unrelated and specify proteins of unrelated function. The inhibition of peptidyl transferase by the leader peptides is additive with that of Cm. Erythromycin competes with the inhibitory action of the peptides, and erythromycin and the peptides footprint to overlapping sites at the peptidyl transferase center of 23S rRNA. It is proposed that translation of the cmlA and cat leaders transiently pauses upon synthesis of the inhibitor peptides. The predicted site of pausing is identical to the leader site where long-term occupancy by a ribosome (ribosome stalling) will activate downstream gene expression. We therefore propose the inducer, Cm, converts a peptide-paused ribosome to the stalled state. We discuss the idea that cooperativity between leader peptide and inducer is necessary for ribosome stalling and may link the activation of a specific drug-resistance gene with a particular antibiotic.

Induction of chloramphenicol (Cm) acetyltransferase-encoding genes (cat) by Cm has been proposed to result from the destabilization of a stem-loop that sequesters the ribosome-binding site for the cat coding sequence. Destabilization is caused by the stalling of a ribosome at a specific site in the leader of cat transcripts that immediately precedes the stem-loop. By use of in vivo dimethylsulfate probing of cat-86 leader mRNA, we demonstrate the existence of the stemloop structure in cat transcripts isolated from uninduced cells and its release during induction. Leader mutations chosen to provide the mRNA with an alternative folding pattern that destabilizes the stem-loop cause constitutive cat expression. Our results establish the occurrence in vivo of the stem-loop in cat-86 transcripts and its role as a negative regulator of cat expression.

The site of ribosome stalling in the leader of cat transcripts is critical to induction of downstream translation. Site-specific stalling requires translation of the first five leader codons and the presence of chloramphenicol, a sequence-independent inhibitor of ribosome elongation. We demonstrate in this report that a synthetic peptide (the 5-mer) corresponding to the N-terminal five codons of the cat-86 leader inhibits peptidyl transferase in vitro. The N-terminal 2-, 3-, and 4-mers and the reverse 5-mer (reverse amino acid sequence of the 5-mer) are virtually without effect on peptidyl transferase. A missense mutation in the cat-86 leader that abolishes induction in vivo corresponds to an amino acid replacement in the 5-mer that completely relieves peptidyl transferase inhibition. In contrast, a missense mutation that does not interfere with in vivo induction corresponds to an amino acid replacement in the 5-mer that does not significantly alter peptidyl transferase inhibition. Our results suggest that peptidyl transferase inhibition by the nascent cat-86 5-mer peptide may be the primary determinant of the site of ribosome stalling in the leader. A model based on this concept can explain the site specificity of ribosome stalling as well as the response of induction to very low levels of the antibiotic inducer.

Service discovery is one of the most vital components involved in almost all service applications. A lot of researches have paid attention to improving the matching accuracy for the given user requirement. Without a clarified requirement specification to describe the goals user really wants to achieve, any matching algorithm is useless. Goal-oriented requirement engineering is a formal requirement analysis methodology which recursively decompose a complex requirement into a set of finer grained goals. Such a hierarchical granulation structure partitions a requirement into a family of fine grain-sized granules. In order to handle uncertainties, rough set theory is employed in granular computing. For any given imprecise user requirement, a set of ordered stratified rough set approximations can be induced over all possible partitions. These approximations are used to iteratively refine imprecise requirement and recommend goals most probably desired. A matching algorithm based on six types of granule approximation is also given to describe different matching strategies for satisfying user requirement. Through the theoretical analysis and case study, it shows that rough set theory combining with granular computing is powerful to handle imprecise requirements and also provide better service quality.

In this paper, based on the theory of sliding mode control and fuzzy logic control, a new fuzzy sliding mode controller with a fixed-order compensator (FSMCC and the simulation results show preliminarily that the new control method is quite effective.

The undue chattering effect is the major disadvantage of conventional variable structure controllers. Therefore, based on the advantage of the fuzzy logic control, we propose a new discrete-time fuzzy variable structure control method that can not only reduce seismological response but can also avoid undue chattering effect. Considering the time delay effect, in the presence of time delay, the motion equation of the discrete-time control system is transformed into standard discrete form which contains no time delay by augmenting the state parameters. Finally we give numerical simulations for MDOF (Multiple-Degree-of-Freedom) shear building model containing an active brace system. The results of numerical simulations have been presented in graphical and tabular form, and the effectiveness of the proposed control method has been compared with that of the conventional discrete-time variable structure control method.

The undue chattering effect is the major disadvantage of conventional sliding mode controllers. In this study, based on the advantage of RBF neural network control method, a new adaptive sliding mode control method, which is one of the active control algorithms, has been applied for seismically-excited building structures. The undue chattering effect, the major disadvantage of conventional sliding mode controller, has been avoided by introducing the new control method. First, we build the motion equation and design the switching surfaces. Next, based on the RBF neural network control algorithm, we adjust the control gain parameter and then design the neurocontroller. For numerical applications, a three-storey shear building model subjected to ground excitations has been considered. The ground accelerations recorded in two different earthquake events have been used to evaluate the effectiveness of the control algorithm for varied disturbances. The simulation results show preliminarily that our new adaptive sliding mode control method is quite effective: not only can it reduce the peak-response of the ground motion, but also it can keep the chattering effect sufficiently low.

Web services have been widely used recent years. In order to enable the intelligent discovery and use by machine, the semantic information should be provided to represent various aspects of Web services. If it always need build complex semantic information from scratch to describe every aspect of Web service, it will lead to not only large redundancy and inconsistency but also low maintainability and extensibility. The customizable semantic template is proposed to resolve such issues, which enables to semantically model any aspect of Web service in a more flexible and efficient way. A universal method to automatically generate semantic template instance is also proposed to resolve the issues like high workload for building semantic information for every aspect of Web service manually and high specialized domain knowledge required.

In this paper, a new variable structure control method involving fuzzy adaptive regulation of reaching law is presented for seismically-excited building structures. The undue chattering effect, the major disadvantage of conventional variable structure controllers, has been avoided by introducing this new method without losing the robustness against parametric uncertainties and modelling inaccuracies. Finally we give numerical simulations for MDOF (Multiple-Degree-of-Freedom) shear building model containing an active brace system; and the simulation results show preliminarily that the new control method is quite effective: not only can it reduce the peak response of the ground motion, but also it can keep the chattering effect sufficiently low so as to ensure the system stable.

Enterovirus D68 (EV-D68) caused a severe respiratory illness outbreak in the United States in 2014. Reports of acute flaccid myelitis (AFM)/paralysis (AFP) in several independent epidemiological clusters of children with detectable EV-D68 have raised concerns that genetic changes in EV-D68 could be causing increased disease severity and neurological symptoms. To explore the potential link between EV-D68 genetic variations and symptom changes, we performed a series of comparative genomic analyses of EV-D68 2014 outbreak isolate sequences using data and analytical tools in the Virus Pathogen Resource (ViPR; www.viprbrc.org). Our results suggest that (1) three distinct lineages of EV-D68 were co-circulating in 2013 and 2014; (2) isolates associated with AFM/AFP belong to a single phylogenetic subclade – B1; (3) the majority of isolates from the B1 subclade have 21 unique substitutions that distinguish them from other isolates, including amino acid substitutions in the VP1, VP2, and VP3 capsid proteins and the 3D RNA-dependent RNA polymerase, and nucleotide substitutions in the internal ribosome entry sequence (IRES); (4) at 12 of these positions, B1 isolates carry the same residues observed at equivalent positions in paralysis-causing enteroviruses, including poliovirus, EV-D70 and EV-A71. Based on these results, we hypothesize that unique B1 substitutions may be responsible for the apparent increased incidence of neuropathology associated with the 2014 outbreak.

Gene microarray technologies provide powerful tools for the large scale analysis of gene expression in cancer research. Clinical applications often aim to facilitate a molecular classification of cancers based on discriminatory genes associated with different clinical stages or outcomes. However, gene expression profiles often represent a composite of more than one distinct source due to tissue heterogeneity, and could result in extracting signatures reflecting the proportion of stromal contamination in the sample, rather than underlying tumor biology. We therefore wish to introduce a computational approach, which allows for a blind decomposition of gene expression profiles from mixed cell populations. The algorithm is based on a linear latent variable model, whose parameters are estimated using partially-independent component analysis, supported by a subset of differentially-expressed genes. We demonstrate the principle of the approach on the data sets derived from mixed cell lines of small round blue cell tumors. Because accurate source separation can be achieved blindly and numerically, we anticipate that computational correction of tissue heterogeneity would be useful in a wide variety of gene microarray studies.

Expression of the chloramphenicol resistance gene cat-86 is regulated by translation attenuation. Among the three ribosomally targeted antibiotics that can induce the gene, only amicetin has an unknown mode of action. Here we demonstrate that the nucleoside antibiotic amicetin is an inhibitor of bacterial peptidyl transferase. Thus, the three inducers of cat-86, chloramphenicol, erythromycin, and amicetin, interact with the peptidyl transferase region of bacterial ribosomes.

The laboratory rat (Rattus norvegicus) is an indispensable tool in experimental medicine and drug development, having made inestimable contributions to human health. We report here the genome sequence of the Brown Norway (BN) rat strain. The sequence represents a high-quality 'draft' covering over 90% of the genome. The BN rat sequence is the third complete mammalian genome to be deciphered, and three-way comparisons with the human and mouse genomes resolve details of mammalian evolution. This first comprehensive analysis includes genes and proteins and their relation to human disease, repeated sequences, comparative genome-wide studies of mammalian orthologous chromosomal regions and rearrangement breakpoints, reconstruction of ancestral karyotypes and the events leading to existing species, rates of variation, and lineage-specific and lineage-independent evolutionary events such as expansion of gene families, orthology relations and protein evolution.

Antiestrogens include agents such as tamoxifen, toremifene, raloxifene, and fulvestrant. Currently, tamoxifen is the only drug approved for use in breast cancer chemoprevention, and it remains the treatment of choice for most women with hormone receptor positive, invasive breast carcinoma. While antiestrogens have been available since the early 1970s, we still do not fully understand their mechanisms of action and resistance. Essentially, two forms of antiestrogen resistance occur: de novo resistance and acquired resistance. Absence of estrogen receptor (ER) expression is the most common de novo resistance mechanism, whereas a complete loss of ER expression is not common in acquired resistance. Antiestrogen unresponsiveness appears to be the major acquired resistance phenotype, with a switch to an antiestrogen-stimulated growth being a minor phenotype. Since antiestrogens compete with estrogens for binding to ER, clinical response to antiestrogens may be affected by exogenous estrogenic exposures. Such exposures include estrogenic hormone replacement therapies and dietary and environmental exposures that directly or indirectly increase a tumor's estrogenic environment. Whether antiestrogen resistance can be conferred by a switch from predominantly ERalpha to ERbeta expression remains unanswered, but predicting response to antiestrogen therapy requires only measurement of ERalpha expression. The role of altered receptor coactivator or corepressor expression in antiestrogen resistance also is unclear, and understanding their roles may be confounded by their ubiquitous expression and functional redundancy. We have proposed a gene network approach to exploring the mechanistic aspects of antiestrogen resistance. Using transcriptome and proteome analyses, we have begun to identify candidate genes that comprise one component of a larger, putative gene network. These candidate genes include NFkappaB, interferon regulatory factor-1, nucleophosmin, and the X-box binding protein-1. The network also may involve signaling through ras and MAPK, implicating crosstalk with growth factors and cytokines. Ultimately, signaling affects the expression/function of the proliferation and/or apoptotic machineries.

DNA sequence and annotation of the entire human chromosome 7, encompassing nearly 158 million nucleotides of DNA and 1917 gene structures, are presented. To generate a higher order description, additional structural features such as imprinted genes, fragile sites, and segmental duplications were integrated at the level of the DNA sequence with medical genetic data, including 440 chromosome rearrangement breakpoints associated with disease. This approach enabled the discovery of candidate genes for developmental diseases including autism., link_to_OA_fulltext

Spotted cDNA microarrays are emerging as a cost effective tool for the large scale analysis of gene expression. To reveal the patterns of genes expressed within a specific cell essentially responsible for its phenotype, this paper reports our progress in cluster discovery using a newly developed data mining method. The discussion entails: (1) statistical modeling of gene microarray data with a standard finite normal mixture distribution, (2) development of a joint supervised and unsupervised discriminative mining to discover sample clusters in a visual pyramid, and (3) evaluation of the data clusters produced by such scheme with phenotype-known microarray experiments.

To identify genes associated with survival from antiestrogens, both serial analysis of geneexpression and gene expression microarrays were used to explore the transcriptomes of antiestrogen-responsive (MCF7/LCC1) and -resistant variants(MCF7/LCC9) of the MCF-7 human breast cancer cell line. Structure of the gene microarray expression data was visualized at the top level using a novel algorithm that derives the first three principal components,fitted to the antiestrogen-resistant and -responsive gene expression data, from Fisher's information matrix. The differential regulation of several candidate genes was confirmed. Functional studies of the basal expression and endocrine regulation of transcriptional activation of implicated transcription factors were studied using promoter-reporter assays. The putative tumor suppressor interferon regulatory factor-1 is down-regulated in resistant cells, whereas its nucleolar phosphoprotein inhibitor nucleophosmin is up-regulated. Resistant cells also up-regulate the transcriptional activation of cyclic AMP response element (CRE) binding and nuclear factor kappaB (NFkappaB) while down-regulating epidermal growth factor receptor protein expression. Inhibition of NFkappaB activity by ICI 182,780 is lost in resistant cells, but CRE activity is not regulated by ICI 182,780 in either responsive or resistant cells. Parthenolide, a potent and specific inhibitor of NFkappaB, inhibits the anchorage-dependent proliferation of antiestrogen-resistant but not antiestrogen-responsive cells. This observation implies a greater reliance on their increased NFkappaB signaling for proliferation in cells that have survived prolonged exposure to ICI 182,780. These data from serial analysis of gene expression and gene microarray studies implicate changes in a novel signaling pathway, involving interferon regulatory factor-1, nucleophosmin, NFkappaB, and CRE binding in cell survival after antiestrogen exposure. Cells can up-regulate some estrogen-responsive genes while concurrently losing the ability of antiestrogens to regulate their expression. Signaling pathways that are not regulated by estrogens also can be up-regulated. Thus, some breast cancer cells may survive antiestrogen treatment by bypassing specific growth inhibitory signals induced by antagonist-occupied estrogen receptors.