Insights into the Crystal Chemistry of the Serandite–Schizolite–Pectolite Series

ABSTRACT The compositional series {Na} [[M1+M2](Ca2XMn2–2X)Si3O8(OH)] includes the minerals serandite (X = 0), schizolite (X = 0.5), and pectolite (X = 1). Six crystals are structurally and chemically characterized in detail (four from Ilímaussaq, Greenland; two from Mont Saint-Hilaire, Québec, Canada): one serandite, one pectolite, and four schizolite crystals. Those originating from Greenland show up to 0.05 apfu LREE3+ (La + Ce + Pr + Nd + Eu + Gd). For each, all H atoms were located, and final R1 factors were below 4.4% (<R1> = 2.35%). The results are compared with previously published crystal structure data from an additional 16 samples, originating from worldwide (mostly) igneous environments. Across the series, for all investigated samples, Ca and Mn order preferentially at the octahedral M1 and M2 sites, respectively, following the exchange M2Ca + M1Mn ↔ M1Ca + M2Mn. Site-occupancies closely adhere to a two-site distribution coefficient, calculated here to be K = 20.0(5), for ideal mixing where activity coefficients approach unity. For the above order-disorder exchange, ΔHex is calculated to be –1.77 kcal. With knowledge of K, site assignment and species determination may be accurately made solely with compositional data, where 0 ≤ ΣCa < 0.55 apfu, serandite; 0.55 ≤ ΣCa < 1.45 apfu, schizolite; and 1.45 ≤ ΣCa ≤ 2 apfu, pectolite, with the dominant-constituent rule mandating M1Ca < M1Mn (M2Ca < M2Mn), serandite; M1Ca > M1Mn (M2Ca < M2Mn), schizolite; and M1Ca > M1Mn (M2Ca > M2Mn), pectolite. Polyhedral distortion and structural strain at the M1 and M2 sites, calculated using the equations of Robinson et al. (1971) and solutions to Kirchhoff network equations, respectively, show a predictable, cooperative variation across the entire compositional series; however, prominent discontinuities in distortion and strain behavior are observed for the schizolite composition.

Magnetic resonance imaging findings of extrauterine high-grade serous carcinoma based on new pathologic criteria for primary site assignment

Background There has been no study that has reported magnetic resonance imaging (MRI) findings of extrauterine high-grade serous carcinomas (HGSCs) that have been histologically determined by the new criteria. Purpose To assess MRI findings of extrauterine HGSCs based on new pathologic criteria. Material and Methods Fifty patients with histopathologically proven extrauterine HGSCs, who underwent pretreatment gadolinium-enhanced MRI, were included in this study. After surgery, the primary sites were histopathologically determined based on new criteria for primary site assignment in extrauterine HGSCs as follows: fallopian tube (n = 34); ovary (n = 9); primary peritoneal HGSC (n = 1); and tubo-ovarian (n = 6). We retrospectively reviewed MR images and compared the MR findings between tubal and ovarian primaries. Results MRI patterns with tubal primaries were classified as ovarian cancer (62%), peritoneal cancer (35%), and fallopian tube cancer (3%). MRI patterns with ovarian primaries were classified as ovarian cancer (78%) and peritoneal cancer (22%). The frequency of the involvement of the fallopian tube, ovary, peritoneum, uterus, and lymph node was not significantly different between the two pathologies. There was no significant difference in the abnormal amount of ascites, hemorrhagic ascites, or characteristics of the ovarian lesions between the two pathologies. Conclusion On MR images, tubal primaries almost always exhibited ovarian or peritoneal cancer pattern, but rarely exhibited fallopian tube cancer pattern. MR findings could not accurately differentiate between tubal and ovarian primaries; therefore, histopathologic investigation is essential for determination of the primary site of extrauterine HGSCs.

Dellagiustaite: A Novel Natural Spinel Containing V2+

Dellagiustaite, ideally Al2V2+O4, is a new spinel-group mineral from Sierra de Comechingones, San Luis, Argentina, where it is found associated with hibonite (containing tubular inclusions, 5–100 μm, of metallic vanadium), grossite, and two other unknown phases with ideal stoichiometry of Ca2Al3O6F and Ca2Al2SiO7. A very similar rock containing dellagiustaite has been found at Mt Carmel (northern Israel), where super-reduced mineral assemblages have crystallized from high-T melts trapped in corundum aggregates (micro-xenoliths) within picritic-tholeiitic lavas ejected from Cretaceous volcanoes. In the holotype, euhedral grains of dellagiustaite are found as inclusions in grossite. The empirical average chemical formula of dellagiustaite is (Al1.09 V 0.91 2 + V 0.87 3 + Mg0.08 Ti 0.04 3 + Mn0.01)Σ3O4, but it may show limited replacement of V2+ by Mg and of V3+ by Al. As Al is the dominant trivalent cation, the ideal formula is Al2V2+O4 according to the current IMA rules. Dellagiustaite shows the usual space group of spinel-group minerals (Fd 3 ¯ m, R1 = 1.46%) with a = 8.1950(1) Å. The observed mean bond lengths <T–O> = 1.782(2) Å and <M–O> = 2.0445(9) Å, the observed site scattering (T = 13.3 eps, M = 22.5 eps), and the chemical composition show that dellagiustaite is an inverse spinel: T tetrahedra are occupied by Al3+, whereas M octahedra are occupied by V2+ and V3+, leading to the site assignment as TAlM( V 0.91 2 + V 0.88 3 + Al 0.09 3 + Mg0.08 Ti 0.03 3 + Mn0.01)O4.

UniLoc: A universal protein localization site predictor for eukaryotes and prokaryotes

ABSTRACTThere is a growing gap between protein subcellular localization (PSL) data and protein sequence data, raising the need for computation methods to rapidly determine subcellular localizations for uncharacterized proteins. Currently, the most efficient computation method involves finding sequence-similar proteins (hereafter referred to as similar proteins) in the annotated database and transferring their annotations to the target protein. When a sequence-similarity search fails to find similar proteins, many PSL predictors adopt machine learning methods for the prediction of localization sites. We proposed a universal protein localization site predictor - UniLoc - to take advantage of implicit similarity among proteins through sequence analysis alone. The notion of related protein words is introduced to explore the localization site assignment of uncharacterized proteins. UniLoc is found to identify useful template proteins and produce reliable predictions when similar proteins were not available.

Designing a Framework for Target-Site Assignment in Naval Combat Management

<p>In this study, using operational research techniques, a model has been presented to assess battlefield threat, to prioritise aggressive targets, to evaluate the capability of own sites and the risks of the conflict with the targets, to define conflict scenarios and finally to select the best scenario using an assignment model. The above proceedings were added as an intermediate phase of target-site assignment, called ‘deciding the best conflict scenario’, to the ‘threat assessment’ and ‘weapon-target assignment’ in the naval combat management system. For each of the own site, the data collected from the environment together with the panels of experts are shown in a two-dimensional matrix, in which the four areas of the matrix represent the conflict scenarios. Considering that the study was done in a simulated environment, the expert’s verification and the convergence of the results in Monte Carlo method were used to validate the research. The proposed model can offer optimised decision to the operational commander through predicting the battlefield and managing the site’s capacity and the interaction in between during the combat.</p>