Super-resolution GSDIM microscopy unveils distinct nanoscale characteristics of DNA repair foci under diverse genotoxic stress.

DNA double-strand breaks initiate the DNA damage response (DDR), leading to the accumulation of repair proteins at break sites and the formation of the-so-called foci. Various microscopy methods, such as wide-field, confocal, electron, and super-resolution microscopy, have been used to study these structures. However, the impact of different DNA-damaging agents on their (nano)structure remains unclear. Utilising GSDIM super-resolution microscopy, here we investigated the distribution of fluorescently tagged DDR proteins (53BP1, RNF168, MDC1) and γH2AX in U2OS cells treated with γ-irradiation, etoposide, cisplatin, or hydroxyurea. Our results revealed that both foci structure and their nanoscale ultrastructure, including foci size, nanocluster characteristics, fluorophore density and localisation, can be significantly altered by different inducing agents, even ones with similar mechanisms. Furthermore, distinct behaviours of DDR proteins were observed under the same treatment. These findings have implications for cancer treatment strategies involving these agents and provide insights into the nanoscale organisation of the DDR.

Using picoliter droplet deposition to track clonal competition in adherent and organoid cancer cell cultures.

Clonal growth and competition underlie processes of key relevance in etiology, progression and therapy response across all cancers. Here, we demonstrate a novel experimental approach, based on multi-color, fluorescent tagging of cell nuclei, in combination with picoliter droplet deposition, to study the clonal dynamics in two- and three-dimensional cell cultures. The method allows for the simultaneous visualization and analysis of multiple clones in individual multi-clonal colonies, providing a powerful tool for studying clonal dynamics and identifying clonal populations with distinct characteristics. Results of our experiments validate the utility of the method in studying clonal dynamics in vitro, and reveal differences in key aspects of clonal behavior of different cancer cell lines in monoculture conditions, as well as in co-cultures with stromal fibroblasts.

High-Content and High-Throughput Clonogenic Survival Assay Using Fluorescence Barcoding.

The Clonogenic Survival Assay (CSA) is a fundamental tool employed to assess cell survival and proliferative potential in cancer research. Despite its importance, CSA faces limitations, primarily its time- and labor-intensive nature and its binary output. To overcome these limitations and enhance CSA's utility, several approaches have been developed, focusing on increasing the throughput. However, achieving both high-content and high-throughput analyses simultaneously has remained a challenge. In this paper, we introduce LeGO-CSA, an extension of the classical CSA that employs the imaging of cell nuclei barcoded with fluorescent lentiviral gene ontology markers, enabling both high-content and high-throughput analysis. To validate our approach, we contrasted it with results from a classical assay and conducted a proof-of-concept screen of small-molecule inhibitors targeting various pathways relevant to cancer treatment. Notably, our results indicate that the classical CSA may underestimate clonogenicity and unveil intriguing aspects of clonal cell growth. We demonstrate the potential of LeGO-CSA to offer a robust approach for assessing cell survival and proliferation with enhanced precision and throughput, with promising implications for accelerating drug discovery and contributing to a more comprehensive understanding of cellular behavior in cancer.

Deep learning-based segmentation of the thorax in mouse micro-CT scans.

For image-guided small animal irradiations, the whole workflow of imaging, organ contouring, irradiation planning, and delivery is typically performed in a single session requiring continuous administration of anaesthetic agents. Automating contouring leads to a faster workflow, which limits exposure to anaesthesia and thereby, reducing its impact on experimental results and on animal wellbeing. Here, we trained the 2D and 3D U-Net architectures of no-new-Net (nnU-Net) for autocontouring of the thorax in mouse micro-CT images. We trained the models only on native CTs and evaluated their performance using an independent testing dataset (i.e., native CTs not included in the training and validation). Unlike previous studies, we also tested the model performance on an external dataset (i.e., contrast-enhanced CTs) to see how well they predict on CTs completely different from what they were trained on. We also assessed the interobserver variability using the generalized conformity index ([Formula: see text]) among three observers, providing a stronger human baseline for evaluating automated contours than previous studies. Lastly, we showed the benefit on the contouring time compared to manual contouring. The results show that 3D models of nnU-Net achieve superior segmentation accuracy and are more robust to unseen data than 2D models. For all target organs, the mean surface distance (MSD) and the Hausdorff distance (95p HD) of the best performing model for this task (nnU-Net 3d_fullres) are within 0.16 mm and 0.60 mm, respectively. These values are below the minimum required contouring accuracy of 1 mm for small animal irradiations, and improve significantly upon state-of-the-art 2D U-Net-based AIMOS method. Moreover, the conformity indices of the 3d_fullres model also compare favourably to the interobserver variability for all target organs, whereas the 2D models perform poorly in this regard. Importantly, the 3d_fullres model offers 98% reduction in contouring time.

Zinc finger protein ZNF384 is an adaptor of Ku to DNA during classical non-homologous end-joining.

DNA double-strand breaks (DSBs) are among the most deleterious types of DNA damage as they can lead to mutations and chromosomal rearrangements, which underlie cancer development. Classical non-homologous end-joining (cNHEJ) is the dominant pathway for DSB repair in human cells, involving the DNA-binding proteins XRCC6 (Ku70) and XRCC5 (Ku80). Other DNA-binding proteins such as Zinc Finger (ZnF) domain-containing proteins have also been implicated in DNA repair, but their role in cNHEJ remained elusive. Here we show that ZNF384, a member of the C2H2 family of ZnF proteins, binds DNA ends in vitro and is recruited to DSBs in vivo. ZNF384 recruitment requires the poly(ADP-ribosyl) polymerase 1 (PARP1)-dependent expansion of damaged chromatin, followed by binding of its C2H2 motifs to the exposed DNA. Moreover, ZNF384 interacts with Ku70/Ku80 via its N-terminus, thereby promoting Ku70/Ku80 assembly and the accrual of downstream cNHEJ factors, including APLF and XRCC4/LIG4, for efficient repair at DSBs. Altogether, our data suggest that ZNF384 acts as a 'Ku-adaptor' that binds damaged DNA and Ku70/Ku80 to facilitate the build-up of a cNHEJ repairosome, highlighting a role for ZNF384 in DSB repair and genome maintenance.

Computer-Aided Diagnosis Evaluation of the Correlation Between Magnetic Resonance Imaging With Molecular Subtypes in Breast Cancer.

BACKGROUND: There is a demand for additional alternative methods that can allow the differentiation of the breast tumor into molecular subtypes precisely and conveniently. PURPOSE: The present study aimed to determine suitable optimal classifiers and investigate the general applicability of computer-aided diagnosis (CAD) to associate between the breast cancer molecular subtype and the extracted MR imaging features. METHODS: We analyzed a total of 264 patients (mean age: 47.9 ± 9.7 years; range: 19-81 years) with 264 masses (mean size: 28.6 ± 15.86 mm; range: 5-91 mm) using a Unet model and Gradient Tree Boosting for segmentation and classification. RESULTS: The tumors were segmented clearly by the Unet model automatically. All the extracted features which including the shape features,the texture features of the tumors and the clinical features were input into the classifiers for classification, and the results showed that the GTB classifier is superior to other classifiers, which achieved F1-Score 0.72, AUC 0.81 and score 0.71. Analyzed the different features combinations, we founded that the texture features associated with the clinical features are the optimal features to different the breast cancer subtypes. CONCLUSION: CAD is feasible to differentiate the breast cancer subtypes, automatical segmentation were feasible by Unet model and the extracted texture features from breast MR imaging with the clinical features can be used to help differentiating the molecular subtype. Moreover, in the clinical features, BPE and age characteristics have the best potential for subtype.

A simple microscopy setup for visualizing cellular responses to DNA damage at particle accelerator facilities.

Cellular responses to DNA double-strand breaks (DSBs) not only promote genomic integrity in healthy tissues, but also largely determine the efficacy of many DNA-damaging cancer treatments, including X-ray and particle therapies. A growing body of evidence suggests that activation of the mechanisms that detect, signal and repair DSBs may depend on the complexity of the initiating DNA lesions. Studies focusing on this, as well as on many other radiobiological questions, require reliable methods to induce DSBs of varying complexity, and to visualize the ensuing cellular responses. Accelerated particles of different energies and masses are exceptionally well suited for this task, due to the nature of their physical interactions with the intracellular environment, but visualizing cellular responses to particle-induced damage - especially in their early stages - at particle accelerator facilities, remains challenging. Here we describe a straightforward approach for real-time imaging of early response to particle-induced DNA damage. We rely on a transportable setup with an inverted fluorescence confocal microscope, tilted at a small angle relative to the particle beam, such that cells can be irradiated and imaged without any microscope or beamline modifications. Using this setup, we image and analyze the accumulation of fluorescently-tagged MDC1, RNF168 and 53BP1-key factors involved in DSB signalling-at DNA lesions induced by 254 MeV α-particles. Our results provide a demonstration of technical feasibility and reveal asynchronous initiation of accumulation of these proteins at different individual DSBs.

Selection and techno-economic analysis of hybrid ground source heat pumps used in karst regions.

In order to take advantage of different forms of heat pumps and to mitigate thermal imbalance underground caused by long-term operation of ground source heat pumps, hybrid ground source heat pump systems have received an increasing attention. In this research, based on the fact that abundant groundwater resources are commonly available in karst regions, a new strategy is introduced for selecting and determining hybrid ground source heat pump capacity. Five scenarios of hybrid ground source heat pump system coupling groundwater source heat pumps with other supplementary heat pumps are proposed in this article to provide appropriate options to eliminate heat buildup under different hydrogeologic conditions. Methodologies for sizing and selection are established. Then, a case study of techno-economic analysis was performed for a project in the karst region in South China. The results showed that these scenarios can effectively mitigate heat buildup, and under the hydrogeologic condition in the case study. Compared to the solo ground-coupled heat pump solution, the optimal solution (Solution 4 in this study) can reduce the annual costs by 16.10% and reduce the capital investment by 60%. Methodologies developed in this study are beneficial for selecting appropriate approaches to mitigate heat buildup and enhance competitiveness of ground source heat pumps.

Catalytic transport of molecular cargo using diffusive binding along a polymer track.

Transport at the molecular scale is a prerequisite for the development of future molecular factories. Here, we have designed oligoanionic molecular sliders on polycationic tracks that exploit Brownian motion and diffusive binding to transport cargo without using a chemical fuel. The presence of the polymer tracks increases the rate of bimolecular reactions between modified sliders by over two orders of magnitude. Molecular dynamics simulations showed that the sliders not only diffuse, but also jump and hop surprisingly efficiently along polymer tracks. Inspired by acetyl-coenzyme A transporting and delivering acetyl groups in many essential biochemical processes, we developed a new and unconventional type of catalytic transport involving sliders (including coenzyme A) picking up, transporting and selectively delivering molecular cargo. Furthermore, we show that the concept of diffusive binding can also be utilized for the spatially controlled transport of chemical groups across gels. This work represents a new concept for designing functional nanosystems based on random Brownian motion.