Biosynthesis and Biomimetic Synthesis of Flavonoid Diels-Alder Natural Products

This chapter describes the biosynthesis and biomimetic synthesis of naturally occurring flavonoid Diels‐Alder adducts found either from the family Moraceae or Zingiberaceae. The main topics addressed are biosynthetic studies by employing Morus alba L. cell cultures through feeding experiments of various exogenous substrates and putative precursors, as well as a various biomimetic approach for the chemical syntheses of flavonoid Diels‐Alder natural products

Publishing perishing? Towards tomorrow's information architecture

Scientific articles are tailored to present information in human-readable aliquots. Although the Internet has revolutionized the way our society thinks about information, the traditional text-based framework of the scientific article remains largely unchanged. This format imposes sharp constraints upon the type and quantity of biological information published today. Academic journals alone cannot capture the findings of modern genome-scale inquiry. Like many other disciplines, molecular biology is a science of facts: information inherently suited to database storage. In the past decade, a proliferation of public and private databases has emerged to house genome sequence, protein structure information, functional genomics data and more; these digital repositories are now a vital component of scientific communication. The next challenge is to integrate this vast and ever-growing body of information with academic journals and other media. To truly integrate scientific information we must modernize academic publishing to exploit the power of the Internet. This means more than online access to articles, hyperlinked references and web-based supplemental data; it means making articles fully computer-readable with intelligent markup and Structured Digital Abstracts. Here, we examine the changing roles of scholarly journals and databases. We present our vision of the optimal information architecture for the biosciences, and close with tangible steps to improve our handling of scientific information today while paving the way for an expansive central index in the future

The impact of viral mutations on recognition by SARS-CoV-2 specific T cells

We identify amino acid variants within dominant SARS-CoV-2 T cell epitopes by interrogating global sequence data. Several variants within nucleocapsid and ORF3a epitopes have arisen independently in multiple lineages and result in loss of recognition by epitope-specific T cells assessed by IFN-γ and cytotoxic killing assays. Complete loss of T cell responsiveness was seen due to Q213K in the A∗01:01-restricted CD8+ ORF3a epitope FTSDYYQLY207-215; due to P13L, P13S, and P13T in the B∗27:05-restricted CD8+ nucleocapsid epitope QRNAPRITF9-17; and due to T362I and P365S in the A∗03:01/A∗11:01-restricted CD8+ nucleocapsid epitope KTFPPTEPK361-369. CD8+ T cell lines unable to recognize variant epitopes have diverse T cell receptor repertoires. These data demonstrate the potential for T cell evasion and highlight the need for ongoing surveillance for variants capable of escaping T cell as well as humoral immunity

Center of Excellence in Research Reporting in Neurosurgery - Diagnostic Ontology

Motivation: Evidence-based medicine (EBM), in the field of neurosurgery, relies on diagnostic studies since Randomized Controlled Trials (RCTs) are uncommon. However, diagnostic study reporting is less standardized which increases the difficulty in reliably aggregating results. Although there have been several initiatives to standardize reporting, they have shown to be sub-optimal. Additionally, there is no central repository for storing and retrieving related articles. Results: In our approach we formulate a computational diagnostic ontology containing 91 elements, including classes and sub-classes, which are required to conduct Systematic Reviews - Meta Analysis (SR-MA) for diagnostic studies, which will assist in standardized reporting of diagnostic articles. SR-MA are studies that aggregate several studies to come to one conclusion for a particular research question. We also report high percentage of agreement among five observers as a result of the interobserver agreement test that we conducted among them to annotate 13 articles using the diagnostic ontology. Moreover, we extend our existing repository CERR-N to include diagnostic studies. Availability: The ontology is available for download as an.owl file at: http://bioportal.bioontology.org/ontologies/3013

A classification-based framework for predicting and analyzing gene regulatory response

BACKGROUND: We have recently introduced a predictive framework for studying gene transcriptional regulation in simpler organisms using a novel supervised learning algorithm called GeneClass. GeneClass is motivated by the hypothesis that in model organisms such as Saccharomyces cerevisiae, we can learn a decision rule for predicting whether a gene is up- or down-regulated in a particular microarray experiment based on the presence of binding site subsequences ("motifs") in the gene's regulatory region and the expression levels of regulators such as transcription factors in the experiment ("parents"). GeneClass formulates the learning task as a classification problem — predicting +1 and -1 labels corresponding to up- and down-regulation beyond the levels of biological and measurement noise in microarray measurements. Using the Adaboost algorithm, GeneClass learns a prediction function in the form of an alternating decision tree, a margin-based generalization of a decision tree. METHODS: In the current work, we introduce a new, robust version of the GeneClass algorithm that increases stability and computational efficiency, yielding a more scalable and reliable predictive model. The improved stability of the prediction tree enables us to introduce a detailed post-processing framework for biological interpretation, including individual and group target gene analysis to reveal condition-specific regulation programs and to suggest signaling pathways. Robust GeneClass uses a novel stabilized variant of boosting that allows a set of correlated features, rather than single features, to be included at nodes of the tree; in this way, biologically important features that are correlated with the single best feature are retained rather than decorrelated and lost in the next round of boosting. Other computational developments include fast matrix computation of the loss function for all features, allowing scalability to large datasets, and the use of abstaining weak rules, which results in a more shallow and interpretable tree. We also show how to incorporate genome-wide protein-DNA binding data from ChIP chip experiments into the GeneClass algorithm, and we use an improved noise model for gene expression data. RESULTS: Using the improved scalability of Robust GeneClass, we present larger scale experiments on a yeast environmental stress dataset, training and testing on all genes and using a comprehensive set of potential regulators. We demonstrate the improved stability of the features in the learned prediction tree, and we show the utility of the post-processing framework by analyzing two groups of genes in yeast — the protein chaperones and a set of putative targets of the Nrg1 and Nrg2 transcription factors — and suggesting novel hypotheses about their transcriptional and post-transcriptional regulation. Detailed results and Robust GeneClass source code is available for download from

Diffractive Dijet Production at sqrt(s)=630 and 1800 GeV at the Fermilab Tevatron

We report a measurement of the diffractive structure function $F_{jj}^D$ of the antiproton obtained from a study of dijet events produced in association with a leading antiproton in $\bar pp$ collisions at $\sqrt s=630$ GeV at the Fermilab Tevatron. The ratio of $F_{jj}^D$ at $\sqrt s=630$ GeV to $F_{jj}^D$ obtained from a similar measurement at $\sqrt s=1800$ GeV is compared with expectations from QCD factorization and with theoretical predictions. We also report a measurement of the $\xi$ ($x$-Pomeron) and $\beta$ ($x$ of parton in Pomeron) dependence of $F_{jj}^D$ at $\sqrt s=1800$ GeV. In the region $0.035<\xi<0.095$, $|t|<1$ GeV$^2$ and $\beta<0.5$, $F_{jj}^D(\beta,\xi)$ is found to be of the form $\beta^{-1.0\pm 0.1} \xi^{-0.9\pm 0.1}$, which obeys $\beta$-$\xi$ factorization.Comment: LaTeX, 9 pages, Submitted to Phys. Rev. Letter

A Study of B0 -> J/psi K(*)0 pi+ pi- Decays with the Collider Detector at Fermilab

We report a study of the decays B0 -> J/psi K(*)0 pi+ pi-, which involve the creation of a u u-bar or d d-bar quark pair in addition to a b-bar -> c-bar(c s-bar) decay. The data sample consists of 110 1/pb of p p-bar collisions at sqrt{s} = 1.8 TeV collected by the CDF detector at the Fermilab Tevatron collider during 1992-1995. We measure the branching ratios to be BR(B0 -> J/psi K*0 pi+ pi-) = (8.0 +- 2.2 +- 1.5) * 10^{-4} and BR(B0 -> J/psi K0 pi+ pi-) = (1.1 +- 0.4 +- 0.2) * 10^{-3}. Contributions to these decays are seen from psi(2S) K(*)0, J/psi K0 rho0, J/psi K*+ pi-, and J/psi K1(1270)

Polycomb-mediated silencing in neuroendocrine prostate cancer

BACKGROUND: Neuroendocrine prostate cancer (NEPC) is a highly aggressive subtype of prostate cancer (PCa) for which the median survival remains less than a year. Current treatments are only palliative in nature, and the lack of suitable pre-clinical models has hampered previous efforts to develop novel therapeutic strategies. Addressing this need, we have recently established the first in vivo model of complete neuroendocrine transdifferentiation using patient-derived xenografts. Few genetic differences were observed between parental PCa and relapsed NEPC, suggesting that NEPC likely results from alterations that are epigenetic in nature. Thus, we sought to identify targetable epigenetic regulators whose expression was elevated in NEPC using genome-wide profiling of patient-derived xenografts and clinical samples. RESULTS: Our data indicate that multiple members of the polycomb group (PcG) family of transcriptional repressors were selectively upregulated in NEPC. Notably, CBX2 and EZH2 were consistently the most highly overexpressed epigenetic regulators across multiple datasets from clinical and xenograft tumor tissues. Given the striking upregulation of PcG genes and other transcriptional repressors, we derived a 185-gene list termed 'neuroendocrine-associated repression signature' (NEARS) by overlapping transcripts downregulated across multiple in vivo NEPC models. In line with the striking upregulation of PcG family members, NEARS was preferentially enriched with PcG target genes, suggesting a driving role for PcG silencing in NEPC. Importantly, NEARS was significantly associated with high-grade tumors, metastatic progression, and poor outcome in multiple clinical datasets, consistent with extensive literature linking PcG genes and aggressive disease progression. CONCLUSIONS: We have explored the epigenetic landscape of NEPC and provided evidence of increased PcG-mediated silencing associated with aberrant transcriptional regulation of key differentiation genes. Our results position CBX2 and EZH2 as potential therapeutic targets in NEPC, providing opportunities to explore novel strategies aimed at reversing epigenetic alterations driving this lethal disease

Russian roulette with unlicensed fat-burner drug 2,4-dinitrophenol (DNP) : evidence from a multidisciplinary study of the internet, bodybuilding supplements and DNP users

BACKGROUND: 2,4-Dinitrophenol (DNP) poses serious health-risks to humans. The aims of this three-stage multidisciplinary project were, for the first time, to assess the risks to the general public from fraudulent sale of or adulteration/contamination with DNP; and to investigate motives, reasons and risk-management among DNP-user bodybuilders and avid exercisers. METHODS: Using multiple search-engines and guidance for Internet research, online retailers and bodybuilding forums/blogs were systematically explored for availability of DNP, advice offered on DNP use and user profiles. Ninety-eight pre-workout and weight-loss supplements were purchased and analysed for DNP using liquid-chromatography-mass-spectrometry. Psychosocial variables were captured in an international sample of 35 DNP users (26.06 ± 6.10 years, 94.3 % male) with an anonymous, semi-qualitative self-reported survey. RESULTS: Although an industrial chemical, evidence from the Internet showed that DNP is sold 'as is', in capsules or tablets to suit human consumption, and is used 'uncut'. Analytical results confirmed that DNP is not on the supplement market disguised under fictitious supplement names, but infrequently was present as contaminant in some supplements (14/98) at low concentration (<100mcg/kg). Users make conscious and 'informed' decisions about DNP; are well-prepared for the side-effects and show nonchalant attitude toward self-experimentation with DNP. Steps are often taken to ensure that DNP is genuine. Personal experience with performance- and appearance enhancing substances appears to be a gateway to DNP. Advice on DNP and experiences are shared online. The significant discrepancy between the normative perception and the actual visibility suggests that DNP use is-contrary to the Internet accounts-a highly concealed and lonesome activity in real life. Positive experiences with the expected weight-loss prevail over the negative experiences from side effects (all but two users considered using DNP again) and help with using DNP safely is considered preferable over scare-tactics. CONCLUSION: Legislation banning DNP sale for human consumption protects the general public but DNP is sold 'as is' and used 'uncut' by determined users who are not dissuaded from experimenting with DNP based on health threats. Further research with stakeholders' active participation is imperative for targeted, proactive public health policies and harm-reduction measures for DNP, and other illicit supplements