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.

Pedothem carbonates reveal anomalous North American atmospheric circulation 70,000-55,000 years ago.

Our understanding of climatic conditions, and therefore forcing factors, in North America during the past two glacial cycles is limited in part by the scarcity of long, well-dated, continuous paleoclimate records. Here, we present the first, to our knowledge, continuous, millennial-resolution paleoclimate proxy record derived from millimeter-thick pedogenic carbonate clast coatings (pedothems), which are widely distributed in semiarid to arid regions worldwide. Our new multiisotope pedothem record from the Wind River Basin in Wyoming confirms a previously hypothesized period of increased transport of Gulf of Mexico moisture northward into the continental interior from 70,000 to 55,000 years ago based on oxygen and carbon isotopes determined by ion microprobe and uranium isotopes and U-Th dating by laser ablation inductively coupled plasma mass spectrometry. This pronounced meridional moisture transport, which contrasts with the dominant zonal transport of Pacific moisture into the North American interior by westerly winds before and after 70,000-55,000 years ago, may have resulted from a persistent anticyclone developed above the North American ice sheet during Marine Isotope Stage 4. We conclude that pedothems, when analyzed using microanalytical techniques, can provide high-resolution paleoclimate records that may open new avenues into understanding past terrestrial climates in regions where paleoclimate records are not otherwise available. When pedothem paleoclimate records are combined with existing records they will add complimentary soil-based perspectives on paleoclimate conditions.

Correction: Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging.

[This corrects the article DOI: 10.1039/C5SC02231B.].

Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging.

Metals have a number of important roles within the brain. We used laser ablation-inductively coupled plasma-mass spectrometry (LA-ICP-MS) to map the three-dimensional concentrations and distributions of transition metals, in particular iron (Fe), copper (Cu) and zinc (Zn) within the murine brain. LA-ICP-MS is one of the leading analytical tools for measuring metals in tissue samples. Here, we present a complete data reduction protocol for measuring metals in biological samples, including the application of a pyramidal voxel registration technique to reproducibly align tissue sections. We used gold (Au) nanoparticle and ytterbium (Yb)-tagged tyrosine hydroxylase antibodies to assess the co-localisation of Fe and dopamine throughout the entire mouse brain. We also examined the natural clustering of metal concentrations within the murine brain to elucidate areas of similar composition. This clustering technique uses a mathematical approach to identify multiple 'elemental clusters', avoiding user bias and showing that metal composition follows a hierarchical organisation of neuroanatomical structures. This work provides new insight into the distinct compartmentalisation of metals in the brain, and presents new avenues of exploration with regard to region-specific, metal-associated neurodegeneration observed in several chronic neurodegenerative diseases.

Correction: Visualising mouse neuroanatomy and function by metal distribution using laser ablation-inductively coupled plasma-mass spectrometry imaging.

[This corrects the article DOI: 10.1039/C5SC02231B.].