Cascade oxime formation, cyclization to a nitrone, and intermolecular dipolar cycloaddition.

Simple haloaldehydes, including enolisable aldehydes, were found to be suitable for the formation of cyclic products by cascade (domino) condensation, cyclisation, dipolar cycloaddition chemistry. This multi-component reaction approach to heterocyclic compounds was explored by using hydroxylamine, a selection of aldehydes, and a selection of activated dipolarophiles. Initial condensation gives intermediate oximes that undergo cyclisation with displacement of halide to give intermediate nitrones; these nitrones undergo in situ intermolecular dipolar cycloaddition reactions to give isoxazolidines. The cycloadducts from using dimethyl fumarate were treated with zinc/acetic acid to give lactam products and this provides an easy way to prepare pyrrolizinones, indolizinones, and pyrrolo[2,1-a]isoquinolinones. The chemistry is illustrated with a very short synthesis of the pyrrolizidine alkaloid macronecine and a formal synthesis of petasinecine

Sudden switch of generalized Lieb-Robinson velocity in a transverse field Ising spin chain

The Lieb-Robinson theorem states that the speed at which the correlations between two distant nodes in a spin network can be built through local interactions has an upper bound, which is called the Lieb-Robinson velocity. Our central aim is to demonstrate how to observe the Lieb-Robinson velocity in an Ising spin chain with a strong transverse field. We adopt and compare four correlation measures for characterizing different types of correlations, which include correlation function, mutual information, quantum discord, and entanglement of formation. We prove that one of correlation functions shows a special behavior depending on the parity of the spin number. All the information-theoretical correlation measures demonstrate the existence of the Lieb-Robinson velocity. In particular, we find that there is a sudden switch of the Lieb-Robinson speed with the increasing of the number of spin

Snakes on a Spaceship - An Overview of Python in Heliophysics

Computational analysis has become ubiquitous within the heliophysics community. However, community standards for peer review of codes and analysis have lagged behind these developments. This absence has contributed to the reproducibility crisis, where inadequate analysis descriptions and loss of scientific data have made scientific studies difficult or impossible to replicate. The heliophysics community has responded to this challenge by expressing a desire for a more open, collaborative set of analysis tools. This article summarizes the current state of these efforts and presents an overview of many of the existing Python heliophysics tools. It also outlines the challenges facing community members who are working toward the goal of an open, collaborative, Python heliophysics toolkit and presents guidelines that can ease the transition from individualistic data analysis practices to an accountable, communalistic environment

Atypical ductal hyperplasia is a multipotent precursor of breast carcinoma

The current model for breast cancer progression proposes independent “low‐grade (LG) like” and “high‐grade (HG) like” pathways but lacks a known precursor to HG cancer. We applied low coverage whole genome sequencing to atypical ductal hyperplasia (ADH) with and without carcinoma to shed light on breast cancer progression. 14/20 isolated ADH cases harboured at least one copy number alteration (CNA), but had fewer aberrations than LG or HG ductal carcinoma in situ (DCIS). ADH carried more HG‐like CNA than LG DCIS (eg. 8q gain). Correspondingly, 64% (7/11) of ADH cases with synchronous HG carcinoma were clonally related, similar to LG carcinoma (67%, 6/9). This study represents a significant shift in our understanding of breast cancer progression, with ADH as a common precursor lesion to the independent “low‐grade like” and “high‐grade like” pathways. These data suggest that ADH can be a precursor of HG breast cancer and that LG and HG carcinomas can evolve from a similar ancestor lesion. We propose that although LG DCIS may be committed to a LG molecular pathway, ADH may remain multipotent, progressing to either LG or HG carcinoma. This multipotent nature suggests that some ADH could be more clinically significant than LG DCIS, requiring biomarkers for personalising management

Low dose cranial irradiation-induced cerebrovascular damage is reversible in mice

BACKGROUND: High-dose radiation-induced blood-brain barrier breakdown contributes to acute radiation toxicity syndrome and delayed brain injury, but there are few data on the effects of low dose cranial irradiation. Our goal was to measure blood-brain barrier changes after low (0.1 Gy), moderate (2 Gy) and high (10 Gy) dose irradiation under in vivo and in vitro conditions. METHODOLOGY: Cranial irradiation was performed on 10-day-old and 10-week-old mice. Blood-brain barrier permeability for Evans blue, body weight and number of peripheral mononuclear and circulating endothelial progenitor cells were evaluated 1, 4 and 26 weeks postirradiation. Barrier properties of primary mouse brain endothelial cells co-cultured with glial cells were determined by measurement of resistance and permeability for marker molecules and staining for interendothelial junctions. Endothelial senescence was determined by senescence associated β-galactosidase staining. PRINCIPLE FINDINGS: Extravasation of Evans blue increased in cerebrum and cerebellum in adult mice 1 week and in infant mice 4 weeks postirradiation at all treatment doses. Head irradiation with 10 Gy decreased body weight. The number of circulating endothelial progenitor cells in blood was decreased 1 day after irradiation with 0.1 and 2 Gy. Increase in the permeability of cultured brain endothelial monolayers for fluorescein and albumin was time- and radiation dose dependent and accompanied by changes in junctional immunostaining for claudin-5, ZO-1 and β-catenin. The number of cultured brain endothelial and glial cells decreased from third day of postirradiation and senescence in endothelial cells increased at 2 and 10 Gy. CONCLUSION: Not only high but low and moderate doses of cranial irradiation increase permeability of cerebral vessels in mice, but this effect is reversible by 6 months. In-vitro experiments suggest that irradiation changes junctional morphology, decreases cell number and causes senescence in brain endothelial cells

Long term productivity and collaboration in information science

This is an accepted manuscript of an article published by Springer in Scientometrics on 02/07/2016, available online: https://doi.org/10.1007/s11192-016-2061-8 The accepted version of the publication may differ from the final published version.Funding bodies have tended to encourage collaborative research because it is generally more highly cited than sole author research. But higher mean citation for collaborative articles does not imply collaborative researchers are in general more research productive. This article assesses the extent to which research productivity varies with the number of collaborative partners for long term researchers within three Web of Science subject areas: Information Science & Library Science, Communication and Medical Informatics. When using the whole number counting system, researchers who worked in groups of 2 or 3 were generally the most productive, in terms of producing the most papers and citations. However, when using fractional counting, researchers who worked in groups of 1 or 2 were generally the most productive. The findings need to be interpreted cautiously, however, because authors that produce few academic articles within a field may publish in other fields or leave academia and contribute to society in other ways

Machine learning-based prediction of breast cancer growth rate in-vivo

BackgroundDetermining the rate of breast cancer (BC) growth in vivo, which can predict prognosis, has remained elusive despite its relevance for treatment, screening recommendations and medicolegal practice. We developed a model that predicts the rate of in vivo tumour growth using a unique study cohort of BC patients who had two serial mammograms wherein the tumour, visible in the diagnostic mammogram, was missed in the first screen.MethodsA serial mammography-derived in vivo growth rate (SM-INVIGOR) index was developed using tumour volumes from two serial mammograms and time interval between measurements. We then developed a machine learning-based surrogate model called Surr-INVIGOR using routinely assessed biomarkers to predict in vivo rate of tumour growth and extend the utility of this approach to a larger patient population. Surr-INVIGOR was validated using an independent cohort.ResultsSM-INVIGOR stratified discovery cohort patients into fast-growing versus slow-growing tumour subgroups, wherein patients with fast-growing tumours experienced poorer BC-specific survival. Our clinically relevant Surr-INVIGOR stratified tumours in the discovery cohort and was concordant with SM-INVIGOR. In the validation cohort, Surr-INVIGOR uncovered significant survival differences between patients with fast-growing and slow-growing tumours.ConclusionOur Surr-INVIGOR model predicts in vivo BC growth rate during the pre-diagnostic stage and offers several useful applications