Deuterium MRS of early treatment-induced changes in tumour lactate in vitro.

Elevated production of lactate is a key characteristic of aberrant tumour cell metabolism and can be non-invasively measured as an early marker of tumour response using deuterium (2 H) MRS. Following treatment, changes in the 2 H-labelled lactate signal could identify tumour cell death or impaired metabolic function, which precede morphological changes conventionally used to assess tumour response. In this work, the association between apoptotic cell death, extracellular lactate concentration, and early treatment-induced changes in the 2 H-labelled lactate signal was established in an in vitro tumour model. Experiments were conducted at 7 T on acute myeloid leukaemia (AML) cells, which had been treated with 10 µg/mL of the chemotherapeutic agent cisplatin. At 24 and 48 h after cisplatin treatment the cells were supplied with 20 mM of [6,6'-2 H2 ]glucose and scanned over 2 h using a two-dimensional 2 H MR spectroscopic imaging sequence. The resulting signals from 2 H-labelled glucose, lactate, and water were quantified using a spectral fitting algorithm implemented on the Oxford Spectroscopy Analysis MATLAB toolbox. After scanning, the cells were processed for histological stains (terminal deoxynucleotidyl transferase UTP nick end labelling and haematoxylin and eosin) to assess apoptotic area fraction and cell morphology respectively, while a colorimetric assay was used to measure extracellular lactate concentrations in the supernatant. Significantly lower levels of 2 H-labelled lactate were observed in the 48 h treated cells compared with the untreated and 24 h treated cells, and these changes were significantly correlated with an increase in apoptotic fraction and a decrease in extracellular lactate. By establishing the biological processes associated with treatment-induced changes in the 2 H-labelled lactate signal, these findings suggest that 2 H MRS of lactate may be valuable in evaluating early tumour response.

FOCAL3D: A 3-dimensional clustering package for single-molecule localization microscopy.

Single-molecule localization microscopy (SMLM) is a powerful tool for studying intracellular structure and macromolecular organization at the nanoscale. The increasingly massive pointillistic data sets generated by SMLM require the development of new and highly efficient quantification tools. Here we present FOCAL3D, an accurate, flexible and exceedingly fast (scaling linearly with the number of localizations) density-based algorithm for quantifying spatial clustering in large 3D SMLM data sets. Unlike DBSCAN, which is perhaps the most commonly employed density-based clustering algorithm, an optimum set of parameters for FOCAL3D may be objectively determined. We initially validate the performance of FOCAL3D on simulated datasets at varying noise levels and for a range of cluster sizes. These simulated datasets are used to illustrate the parametric insensitivity of the algorithm, in contrast to DBSCAN, and clustering metrics such as the F1 and Silhouette score indicate that FOCAL3D is highly accurate, even in the presence of significant background noise and mixed populations of variable sized clusters, once optimized. We then apply FOCAL3D to 3D astigmatic dSTORM images of the nuclear pore complex (NPC) in human osteosaracoma cells, illustrating both the validity of the parameter optimization and the ability of the algorithm to accurately cluster complex, heterogeneous 3D clusters in a biological dataset. FOCAL3D is provided as an open source software package written in Python.