The synthesis and characterisation of 4,1,2-MC2B10 metallacarboranes

Reduction of the tethered carborane 1,2-(CH2)3-1,2-closo-C2B10H10 followed by treatment with CoCl2/NaCp, [(p-cymene)RuCl2]2(p-cymene=C6H4MeiPr-1,4), (PMe2Ph)2PtCl2 or (dppe)NiCl2(dppe=Ph2PCH2CH2PPh2) affords reasonable yields of the new 13-vertex metallacarboranes 1,2-(CH2)3-4-Cp-4,1,2-closo-CoC2B10H10 (1), 1,2-(CH2)3-4-(p-cymene)-4,1,2-closo-RuC2B10H10 (2), 1,2-(CH2)3-4,4-(PMe2Ph)2-4,1,2-closo-PtC2B10H10 (3) and 1,2-(CH2)3-4,4-(dppe)-4,1,2-closo-NiC2B10H10 (4), respectively. All compounds were characterised spectroscopically and crystallographically. The cobalt and ruthenium species 1 and 2 have Cs symmetry in both solution and the solid state, having henicosahedral cage structures featuring a trapezoidal C1C2B9B5 face. The platinum and nickel compounds 3 and 4 have asymmetric docosahedral cage structures in the crystal (the more so for 4 than for 3) although both appear, by 11B and 31P NMR spectroscopy, to have Cs symmetry in solution. Low-temperature experiments on the more soluble platinacarborane could not freeze out the diamond-trapezium-diamond fluctional process that we assume is operating in solution, and we therefore conclude that this process has a relatively low activation barrier, probably <35 kJ mol-1.     

Orientation of Na(3p) states excited in Na-He collisions

The orientation of Na(3p) states created in 3–13 keV Na(3s)-He collisions has been studied by the polarised photon-scattered particle coincidence technique at scattering angles corresponding to the impact-parameter range 1–2 a.u. In the standard geometry, at large impact parameters the excitation process exhibits a very high degree of orientation with about 90% of the Na(3p) states havingm ₁=?1. Strong reduction in this propensity is observed at impact parameters smaller than about 1.3 a.u., where a molecular curve crossing causes simultaneous He(n=2) excitation. In this region, also ionisation becomes important.     

Total Synthesis of Jiadifenolide

As a potent neurotrophic agent, the sesquiterpenoid jiadifenolide represents a valuable small‐molecule lead for the potential therapeutic treatment of neurodegenerative diseases. A stereocontrolled total synthesis of this densely functionalized natural product is reported, central to which is an adventurous samarium‐mediated cyclization reaction to establish the tricyclic core and the adjacent C5 and C6 quaternary stereocenters.     

Toward the synthesis of spirastrellolide a: construction of a tetracyclic C26-C40 subunit containing the DEF-bis-spiroacetal

[reaction: see text] A stereo-controlled synthesis of the fully elaborated C26-C40 tricyclic [5,6,6]-bis-spiroacetal of spirastrellolide A containing the C28 chlorine substituent is reported, exploiting asymmetric Sharpless dihydroxylation and boron-mediated allylation methodology.     

Transmission measurements of soft X-ray absorption fine structure in solids by a new scintillation technique

Transmission measurements of the extended X-ray absorption fine structure above the oxygen K-edge have been made by using a new scintillation detection technique. The absorption spectrum is in close resemblance with the total electron yield spectrum recorded at the same time. This new technique is of interest for studies of soft X-ray absorption spectroscopy for thin films of solid materials.     

Predicting the phosphorylation sites using hidden Markov models and machine learning methods

Accurately predicting phosphorylation sites in proteins is an important issue in postgenomics, for which how to efficiently extract the most predictive features from amino acid sequences for modeling is still challenging. Although both the distributed encoding method and the bio-basis function method work well, they still have some limits in use. The distributed encoding method is unable to code the biological content in sequences efficiently, whereas the bio-basis function method is a nonparametric method, which is often computationally expensive. As hidden Markov models (HMMs) can be used to generate one model for one cluster of aligned protein sequences, the aim in this study is to use HMMs to extract features from amino acid sequences, where sequence clusters are determined using available biological knowledge. In this novel method, HMMs are first constructed using functional sequences only. Both functional and nonfunctional training sequences are then inputted into the trained HMMs to generate functional and nonfunctional feature vectors. From this, a machine learning algorithm is used to construct a classifier based on these feature vectors. It is found in this work that (1) this method provides much better prediction accuracy than the use of HMMs only for prediction, and (2) the support vector machines (SVMs) algorithm outperforms decision trees and neural network algorithms when they are constructed on the features extracted using the trained HMMs.