Synthesis of a magnetic π-extended carbon nanosolenoid with Riemann surfaces

Riemann surfaces are deformed versions of the complex plane in mathematics. Locally they look like patches of the complex plane, but globally, the topology may deviate from a plane. Nanostructured graphitic carbon materials resembling a Riemann surface with helicoid topology are predicted to have interesting electronic and photonic properties. However, fabrication of such processable and large π-extended nanographene systems has remained a major challenge. Here, we report a bottom-up synthesis of a metal-free carbon nanosolenoid (CNS) material with a low optical bandgap of 1.97 eV. The synthesis procedure is rapid and possible on the gram scale. The helical molecular structure of CNS can be observed by direct low-dose high-resolution imaging, using integrated differential phase contrast scanning transmission electron microscopy. Magnetic susceptibility measurements show paramagnetism with a high spin density for CNS. Such a π-conjugated CNS allows for the detailed study of its physical properties and may form the base of the development of electronic and spintronic devices containing CNS species

Somatic SF3B1 hotspot mutation in prolactinomas.

The genetic basis and corresponding clinical relevance of prolactinomas remain poorly understood. Here, we perform whole genome sequencing (WGS) on 21 patients with prolactinomas to detect somatic mutations and then validate the mutations with digital polymerase chain reaction (PCR) analysis of tissue samples from 227 prolactinomas. We identify the same hotspot somatic mutation in splicing factor 3 subunit B1 (SF3B1R625H) in 19.8% of prolactinomas. These patients with mutant prolactinomas display higher prolactin (PRL) levels (p = 0.02) and shorter progression-free survival (PFS) (p = 0.02) compared to patients without the mutation. Moreover, we identify that the SF3B1R625H mutation causes aberrant splicing of estrogen related receptor gamma (ESRRG), which results in stronger binding of pituitary-specific positive transcription factor 1 (Pit-1), leading to excessive PRL secretion. Thus our study validates an important mutation and elucidates a potential mechanism underlying the pathogenesis of prolactinomas that may lead to the development of targeted therapeutics

Instance-driven TBox revision in DL-Lite

The development and maintenance of large and complex ontologies are often time-consuming and error-prone. Thus, automated ontology learning and revision have attracted intensive research interest. In data-centric applications where ontologies are designed or automatically learnt from the data, when new data instances are added that contradict to the ontology, it is often desirable to incrementally revise the ontology according to the added data. This problem can be intuitively formulated as the problem of revising a TBox by an ABox. In this paper we introduce a model-theoretic approach to such an ontology revision problem by using a novel alternative semantic characterisation of DL-Lite ontologies. We show some desired properties for our ontology revision. We have also developed an algorithm for reasoning with the ontology revision without computing the revision result. The algorithm is efficient as its computational complexity is in coNP in the worst case and in PTIME when the size of the new data is bounded

Contraction and Revision over DL-Lite TBoxes

Two essential tasks in managing Description Logic (DL) ontologies are eliminating problematic axioms and incorporating newly formed axioms. Such elimination and incorporation are formalised as the operations of contraction and revision in belief change.In this paper, we deal with contraction and revision for the DL-Lite family through a model-theoretic approach.Standard DL semantics yields infinite numbers of models for DL-Lite TBoxes, thus it is not practical to develop algorithms for contraction and revision that involve DL models. The key to our approach is the introduction of an alternative semantics called type semantics which is more succinct than DL semantics. More importantly, with a finite signature, type semantics always yields finite humber of models.We then define model-based contraction and revision for DL-Lite TBoxesunder type semantics and provide representation theorems for them.Finally, the succinctness of type semantics allows us to develop tractable algorithms for both operations

Instance-Driven Ontology Evolution in DL-Lite

The development and maintenance of large and complex ontologies are often time-consuming and error-prone. Thus, automated ontology learning and evolution have attracted intensive research interest. In data-centric applications where ontologies are designed from the data or automatically learnt from it, when new data instances are added that contradict the ontology, it is often desirable to incrementally revise the ontology according to the added data. In description logics, this problem can be intuitively formulated as the operation of TBox contraction, i.e., rational elimination of certain axioms from the logical consequences of a TBox, and it is w.r.t. an ABox. In this paper we introduce a model-theoretic approach to such a contraction problem by using an alternative semantic characterisation of DL-Lite TBoxes. We show that entailment checking (without necessarily first computing the contraction result) is in coNP, which does not shift the corresponding complexity in propositional logic, and the problem is tractable when the size of the new data is bounded

An Unexpected Dual-Emissive Luminogen: Tunable Aggregation-Induced Emission with Cyan-White-Red Colors, Stable Inherent Chirality, and Enhanced Chiroptical Property

Herein we report a novel chiral bismacrocycle with unexpected dual emission and tunable aggregation-induced emission colors. A facile four-step synthesis strategy is developed to construct this rigid bismacrocycle, (1,4)[8]cycloparaphenylenophane (SCPP[8]), which possesses a 1,2,4,5-tetraphenylbenzene core locked by two intersecting polyphenylene-based macrocycles. The luminescent behavior of SCPP[8] shows the unique characteristics of both aggregation-caused quenching effect and aggrega-tion-induced emission (AIE) effect, inducing remarkable redshift emission including near white-light emission. SCPP[8] is configurationally stable and possesses a novel shape-persistent bismacrocycle scaffold with a high strain energy (up to 127.83 kcal/mol). In addition, SCPP[8] displays enhanced circularly polarized luminescence properties due to AIE effect

Approximating Model-Based ABox Revision in DL-Lite: Theory and Practice

Model-based approaches provide a semantically well justified way to revise ontologies. However, in general, model-based revision operators are limited due to lack of efficient algorithms and inexpressibility of the revision results. In this paper, we make both theoretical and practical contribution to efficient computation of model-based revisions in DL-Lite. Specifically, we show that maximal approximations of two well-known model-based revisions for DL-Lite_R can be computed using a syntactic algorithm. However, such a coincidence of model-based and syntactic approaches does not hold when role functionality axioms are allowed. As a result, we identify conditions that guarantee such a coincidence for DL-Lite_FR. Our result shows that both model-based and syntactic revisions can co-exist seamlessly and the advantages of both approaches can be taken in one revision operator. Based on our theoretical results, we develop a graph-based algorithm for the revision opera

A metal-free photoactive nitrogen-doped carbon nanosolenoid with broad absorption in visible region for efficient photocatalysis

Abstract Riemann surfaces inspired chemists to design and synthesize such multidimensional curved carbon architectures. It has been predicted that carbon nanosolenoid materials with Riemann surfaces have unique structures and novel physical properties. Here we report the first synthesis of a nitrogen-doped carbon nanosolenoid (N-CNS) using bottom-up approach with a well-defined structure. N-CNS was obtained by a rational Suzuki polymerization, followed by oxidative cyclodehydrogenation. The successful synthesis of N-CNS was fully characterized by GPC, FTIR, solid-state 13C NMR and Raman techniques. The intrinsic single-strand molecular structures of N-CNS helices can be clearly resolved using low-dose integrated differential phase contrast scanning transmission electron microscopy (iDPC-STEM) technique. Possessing unique structural and physical properties, this long π-extended polymer N-CNS can provide new insight towards bottom-up syntheses of curved nanoribbons and potential applications as a metal-free photocatalyst for visible-light-driven H2 evolution and highly efficient photocatalyst for photoredox organic transformations

Advances in B-lymphoblastic leukemia: cytogenetic and genomic lesions

The genomic profiling of B-cell lymphoblastic leukemia (B-ALL) subtypes are characterized by a constellation of genetic changes involving structural rearrangements, submicroscopic DNA copy number alterations, and sequence mutations. Several of these genetic changes have relevant implications for risk stratification and targeted therapeutic interventions. In this review, we summarize some of the well-known and recently identified genomic risk factors for B-ALL, with emphasis on their associated prognoses and methods of detection. Alterations in genes that regulate B-cell development are hallmarks of B-ALL In particular, deletions of IKZF1, a gene determining early lymphoid differentiation, are associated with high-risk Ph+ and Ph-like B-ALL subtypes. About 20% of B-ALL patients harbor genetic alterations that result in aberrant activation of protein tyrosine kinases. The genetic alterations include rearrangements of the cytokine receptor gene CRLF2; rearrangements of ABL1, JAK2, and PDGFRB; and mutations of JAK1 and JAK2. B-ALL with these genetic alterations may respond to targeted therapy using tyrosine kinase inhibitors. Recurrent genetic alterations involving TP53, CREBBP, and NT5C2 are enriched in relapsed B-ALL and may confer drug resistance. Future challenges include implementing genomic profiling into the clinic to guide risk stratification and the use of targeted therapies. (C) 2016 Elsevier Inc. All rights reserved