Microscopic determination of nuclear deformation energy surfaces at very high spins

The deformation energy surfaces of a number of rare-earth nuclei are calculated microscopically as a function of the Bohr-Mottelson deformation parameters (β,γ), for the very high spin states $\text{(30}\text{h}\text{?}\text{?J?70}\text{h}\text{?}\text{)}$ and compared with semiphenomenological Strutinsky based calculations. The possibility of rotational isomers (yrast traps) is discussed.     

An integrated mass spectrometry imaging and digital pathology workflow for objective detection of colorectal tumours by unique atomic signatures

Tumours are abnormal growths of cells that reproduce by redirecting essential nutrients and resources from surrounding tissue. Changes to cell metabolism that trigger the growth of tumours are reflected in subtle differences between the chemical composition of healthy and malignant cells. We used LA-ICP-MS imaging to investigate whether these chemical differences can be used to spatially identify tumours and support detection of primary colorectal tumours in anatomical pathology. First, we generated quantitative LA-ICP-MS images of three colorectal surgical resections with case-matched normal intestinal wall tissue and used this data in a Monte Carlo optimisation experiment to develop an algorithm that can classify pixels as tumour positive or negative. Blinded testing and interrogation of LA-ICP-MS images with micrographs of haematoxylin and eosin stained and Ki67 immunolabelled sections revealed Monte Carlo optimisation accurately identified primary tumour cells, as well as returning false positive pixels in areas of high cell proliferation. We analysed an additional 11 surgical resections of primary colorectal tumours and re-developed our image processing method to include a random forest regression machine learning model to correctly identify heterogenous tumours and exclude false positive pixels in images of non-malignant tissue. Our final model used over 1.6 billion calculations to correctly discern healthy cells from various types and stages of invasive colorectal tumours. The imaging mass spectrometry and data analysis methods described, developed in partnership with clinical cancer researchers, have the potential to further support cancer detection as part of a comprehensive digital pathology approach to cancer care through validation of a new chemical biomarker of tumour cells.

Digital pathology and laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) imaging reveals a unique elemental signature of colorectal cancer.     

Unsymmetrical indirect covariance processing of hyphenated and long‐range heteronuclear 2D NMR spectra ‐ Enhanced visualization of 2JCH and 4JCH correlation responses

Recent reports have demonstrated the unsymmetrical indirect covariance combination of discretely acquired 2D NMR experiments into spectra that provide an alternative means of accessing the information content of these spectra. The method can be thought of as being analogous to the Fourier transform conversion of time domain data into the more readily interpreted frequency domain. Hyphenated 2D‐NMR spectra such as GHSQC‐TOCSY, when available, provide an investigator with the means of sorting proton‐proton homonuclear connectivity networks as a function of the ¹³C chemical shift of the carbon directly bound to the proton from which propagation begins. Long‐range heteronuclear chemical shift correlation experiments establish proton‐carbon correlations via heteronuclear coupling pathways, most commonly across three bonds (³J_CH), but in more general terms across two (²J_CH) to four bonds (⁴J_CH). In many instances ³J_CH correlations dominate GHMBC spectra. We demonstrate in this report the improved visualization of ²J_CH and ⁴J_CH correlations through the unsymmetrical indirect covariance processing of GHSQC‐TOCSY and GHMBC 2D spectra.