Extractable energy from erbium-ytterbium co-doped pulsed fiber amplifiers and lasers

An analytic model is developed for evaluating the extractable energy from high energy pulsed erbium-ytterbium co-doped fiber amplifiers and lasers. The energy extraction capabilities under the limitation of spurious lasing, due to amplified spontaneous emission (ASE), are mapped for various numerical apertures, single and multi transverse mode evolution and operating wavelengths. The model provides an assessment for the maximum pulse energy that can be extracted from a given erbium-ytterbium co-doped fiber. In addition, the model can be used to determine the repetition rate and optimal length, under which the laser source will be optimally operated in order to achieve a required extracted energy, without spurious lasing. The results show a clear advantage in using 915 nm wavelength pump source over 975 nm, at high average power operation, due to augmented 1 μm ASE at 975 nm pump wavelength, as a result of the Yb³⁺ population inversion.     

The structure of a silicon analog of the psychotropic drug perathiepin: 5,5-dimethyl-10-(4-methylpiperazinyl)-10,11-dihydro-5H-dibenzo[b,f]silepin hydrofumarate

The solid state structure of the hydrofumarate salt of 5,5-dimethyl-10-(4-methylpiperazinyl)-1O,11-dihydro-5H-dibenzo[b,f]silepin (II), a silicon analog of perathiepin (I) in which divalent sulfur is replaced by the (CH₃)₂Si moiety, has been determined by X-ray diffraction methods. The compound, C₂₅H₃₂N₂O₄Si, crystallizes in the orthorhombic space group, Pbc2₁ with a 9.304(2), b 23.010(7), c 11.599(3) Å; the structure was refined by full-matrix least-squares techniques to a conventional R of 0.039 for 1858 counter reflections. The structure consists of a network of hydrogen-bonded hydrofumarate anions and the protonated heterocyclic unit. The tricyclic framework of the cation adopts a folded boat conformation with a dihedral angle between benzo group planes of 151.2°. In contrast to related systems, the piperazinyl substituent which has the expected chair conformation occupies a pseudoaxial site on the ethano bridge. Structural parameters of the tricyclic framework of the title compound and related compounds are compared.     

Activity-aware clustering of high throughput screening data and elucidation of orthogonal structure-activity relationships

From a medicinal chemistry point of view, one of the primary goals of high throughput screening (HTS) hit list assessment is the identification of chemotypes with an informative structure-activity relationship (SAR). Such chemotypes may enable optimization of the primary potency, as well as selectivity and phamacokinetic properties. A common way to prioritize them is molecular clustering of the hits. Typical clustering techniques, however, rely on a general notion of chemical similarity or standard rules of scaffold decomposition and are thus insensitive to molecular features that are enriched in biologically active compounds. This hinders SAR analysis, because compounds sharing the same pharmacophore might not end up in the same cluster and thus are not directly compared to each other by the medicinal chemist. Similarly, common chemotypes that are not related to activity may contaminate clusters, distracting from important chemical motifs. We combined molecular similarity and Bayesian models and introduce (I) a robust, activity-aware clustering approach and (II) a feature mapping method for the elucidation of distinct SAR determinants in polypharmacologic compounds. We evaluated the method on 462 dose-response assays from the Pubchem Bioassay repository. Activity-aware clustering grouped compounds sharing molecular cores that were specific for the target or pathway at hand, rather than grouping inactive scaffolds commonly found in compound series. Many of these core structures we also found in literature that discussed SARs of the respective targets. A numerical comparison of cores allowed for identification of the structural prerequisites for polypharmacology, i.e., distinct bioactive regions within a single compound, and pointed toward selectivity-conferring medchem strategies. The method presented here is generally applicable to any type of activity data and may help bridge the gap between hit list assessment and designing a medchem strategy.     

The pentagram map and Y-patterns

The pentagram map, introduced by R. Schwartz, is defined by the following construction: given a polygon as input, draw all of its “shortest” diagonals, and output the smaller polygon which they cut out. We employ the machinery of cluster algebras to obtain explicit formulas for the iterates of the pentagram map.