Reduction-induced facile isomerisation of metallacarboranes:synthesis and crystallographic characterisation of 4-Cp-4,1,2-closo-CoC₂B₉H₁₁

One-electron reduction of 3-Cp-3,1,2-closo-CoC2B9H11 followed by heating to reflux in DME (b.p. 85 °C) induces isomerisation to 4-Cp-4,1,2-closo-CoC2B9H11.</p

Molecular sexing in Kea Nestor notabilis

DNAによる性判別法のミヤマオウムへの利用を目的として､鳥類の性染色体上に存在するCHD(chromo-helicase-DNA binding protein)遺伝子を標的とする2種類のプライマーセットについて検討した。その結果､ミヤマオウムでは､2種類のプライマーセットでDNAの増幅が認められた。しかし､オウム､インコ類においで性判別の報告があるプライマーAの雌雄間で認められる型が異なること から判別ができなかった。一方､ワシ､タカ類のCHD-Wの配列を基に設計されたプライマーBを用いた方法では､ミヤマオウムのW染色体由来の増幅産物のみが検出されることから性判別が可能となった。また､対照として用いたヨウムは､2種類のプライマーセットで性判別が可能であったことから､プライマーBは､他の鳥種でも性判別のできる可能性が示唆された

The photochemical mediated ring contraction of 4H-1,2,6-thiadiazines to afford 1,2,5-thiadiazol-3(2H)-one 1-oxides

E.B. and C.G.T. are grateful to Heriot-Watt University and the EPSRC CRITICAT Centre for Doctoral Training (E.B. Ph.D. Studentship: EP/L016419/1, C.G.T Ph.D. Studentship: EP/LO14419/1) for funding and training. C.G.T. is grateful to the Heriot-Watt Annual Fund for financial support. P.A.K. and A.S.K. thank the University of Cyprus for the Internal Grant “Thiadiazine-Based Organic Photovoltaics”, and the Cyprus Research Promotion Foundation (Grant Nos. ΣΤΡΑΤΗΙΙ/0308/06, NEKYP/0308/02 ΥΓΕΙΑ/0506/19, and ΕΝΙΣΧ/0308/83). M.J.P. thanks the EPSRC for funding (Grant Nos. EP/T021675 and EP/V006746), and the Leverhulme Trust (Grant No. PG-2020-208). S.A.M. thanks the EPSRC for funding (Grant No. EP/T019867/1).1,2,6-Thiadiazines treated with visible light and 3O2 under ambient conditions are converted into difficult-to-access 1,2,5-thiadiazole 1-oxides (35 examples, yields of 39–100%). Experimental and theoretical studies reveal that 1,2,6-thiadiazines act as triplet photosensitizers that produce 1O2 and then undergo a chemoselective [3 + 2] cycloaddition to give an endoperoxide that ring contracts with selective carbon atom excision and complete atom economy. The reaction was optimized under both batch and continuous-flow conditions and is also efficient in green solvents.Publisher PDFPeer reviewe

AVID: An integrative framework for discovering functional relationships among proteins

BACKGROUND: Determining the functions of uncharacterized proteins is one of the most pressing problems in the post-genomic era. Large scale protein-protein interaction assays, global mRNA expression analyses and systematic protein localization studies provide experimental information that can be used for this purpose. The data from such experiments contain many false positives and false negatives, but can be processed using computational methods to provide reliable information about protein-protein relationships and protein function. An outstanding and important goal is to predict detailed functional annotation for all uncharacterized proteins that is reliable enough to effectively guide experiments. RESULTS: We present AVID, a computational method that uses a multi-stage learning framework to integrate experimental results with sequence information, generating networks reflecting functional similarities among proteins. We illustrate use of the networks by making predictions of detailed Gene Ontology (GO) annotations in three categories: molecular function, biological process, and cellular component. Applied to the yeast Saccharomyces cerevisiae, AVID provides 37,451 pair-wise functional linkages between 4,191 proteins. These relationships are ~65–78% accurate, as assessed by cross-validation testing. Assignments of highly detailed functional descriptors to proteins, based on the networks, are estimated to be ~67% accurate for GO categories describing molecular function and cellular component and ~52% accurate for terms describing biological process. The predictions cover 1,490 proteins with no previous annotation in GO and also assign more detailed functions to many proteins annotated only with less descriptive terms. Predictions made by AVID are largely distinct from those made by other methods. Out of 37,451 predicted pair-wise relationships, the greatest number shared in common with another method is 3,413. CONCLUSION: AVID provides three networks reflecting functional associations among proteins. We use these networks to generate new, highly detailed functional predictions for roughly half of the yeast proteome that are reliable enough to drive targeted experimental investigations. The predictions suggest many specific, testable hypotheses. All of the data are available as downloadable files as well as through an interactive website at . Thus, AVID will be a valuable resource for experimental biologists

Carborane: Dedicated to the Work of Professor Alan Welch

In the 1950s, borohydrides arose as promising components of new rocket and aviation fuels [...