Pancreatic ductal adenocarcinoma (PDAC) is characterized by a prominent desmoplastic/stromal reaction, which contributes to the poor clinical outcome of this disease. Therefore, greater understanding of the stroma development and tumor-stroma interactions is highly required. Pancreatic stellate cells (PSC) are myofibroblast-like cells that located in exocrine areas of the pancreas, which as a result of inflammation produced by PDAC migrate and accumulate in the tumor mass, secreting extracellular matrix components and producing the dense PDAC stroma. Currently, only a few orthotopic or ectopic animal tumor models, where PDAC cells are injected into the pancreas or subcutaneous tissue layer, or genetically engineered animals offer tumors that encompass some stromal component. Herein, we report generation of a simple 3D PDAC in vitro micro-tumor model without an addition of external extracellular matrix, which encompasses a rich, dense and active stromal compartment. We have achieved this in vitro model by incorporating PSCs into 3D PDAC cell culture using a modified hanging drop method. It is now known that PSCs are the principal source of fibrosis in the stroma and interact closely with cancer cells to create a tumor facilitatory environment that stimulates local and distant tumor growth. The 3D micro-stroma models are highly reproducible with excellent uniformity, which can be used for PDAC-stroma interaction analysis and high throughput automated drug-screening assays. Additionally, the increased expression of collagenous regions means that molecular based perfusion and cytostaticity of gemcitabine is decreased in our Pancreatic adenocarcinoma stroma spheroids (PDAC-SS) model when compared to spheroids grown without PSCs. We believe this model will allow an improved knowledge of PDAC biology and has the potential to provide an insight into pathways that may be therapeutically targeted to inhibit PSC activation, thereby inhibiting the development of fibrosis in PDAC and interrupting PSCPDAC cell interactions so as to inhibit cancer progression.

Detecting various types of cells in and aroundthe tumor matrix holds a special significance in characterizing the tumor micro-environment for cancer prognostication and research. Automating the tasks of detecting, segmenting, and classifying nuclei can free up the pathologists' time for higher value tasks and reduce errors due to fatigue and subjectivity. To encourage the computer vision research community to develop and test algorithms for these tasks, we prepared a large and diverse dataset of nucleus boundary annotations and class labels. The dataset has over 46,000 nuclei from 37 hospitals, 71 patients, four organs, and four nucleus types. We also organized a challenge around this dataset as a satellite event at the International Symposium on Biomedical Imaging (ISBI) in April 2020. The challenge saw a wide participation from across the world, and the top methods were able to match inter-human concordance for the challenge metric. In this paper, we summarize the dataset and the key findings of the challenge, including the commonalities and differences between the methods developed by various participants. We have released the MoNuSAC2020 dataset to the public.

Aim: Glycoconjugated C 60 derivatives are of particular interest as potential cancer targeting agents due to an upregulated metabolic glucose demand, especially in the case of pancreatic adenocarcinoma and its dense stroma, which is known to be driven by a subset of pancreatic stellate cells. Materials & methods: Herein, we describe the synthesis and biological characterization of a hexakis-glucosamine C 60 derivative (termed 'Sweet-C 60 '). Results: Synthesized fullerene derivative predominantly accumulates in the nucleus of pancreatic stellate cells; is inherently nontoxic up to concentrations of 1 mg/ml; and is photoactive when illuminated with blue and green light, allowing its use as a photodynamic therapy agent. Conclusion: Obtained glycoconjugated nanoplatform is a promising nanotherapeutic for pancreatic cancer.

Aims Simultaneous positron emission tomography/MRI has recently been introduced to the clinic and dual positron emission tomography/MRI probes are rare and of growing interest. We have developed a strategy for producing multimodal probes based on a carbon nanotube platform without the use of chelating ligands. Materials & methods Gd3+ and 64Cu2+ ions were loaded into ultra-short single-walled carbon nanotubes by sonication. Normal, tumor-free athymic nude mice were injected intravenously with the probe and imaged over 48 h. Results & conclusion The probe was stable for up to 24 h when challenged with phosphate-buffered saline and mouse serum. Positron emission tomography imaging also confirmed the stability of the probe in vivo for up to 48 h. The probe was quickly cleared from circulation, with enhanced accumulation in the lungs. Stable encapsulation of contrast agents within ultra-short single-walled carbon nanotubes represents a new strategy for the design of advanced imaging probes with variable multimodal imaging capabilities.

There is an ever increasing interest in developing new stem cell therapies. However, imaging and tracking stem cells in vivo after transplantation remains a serious challenge. In this work, we report new, functionalized and high-performance Gd(3+)-ion-containing ultra-short carbon nanotube (US-tube) MRI contrast agent (CA) materials which are highly-water-dispersible (ca. 35 mg ml(-1)) without the need of a surfactant. The new materials have extremely high T1-weighted relaxivities of 90 (mM s)(-1) per Gd(3+) ion at 1.5 T at room temperature and have been used to safely label porcine bone-marrow-derived mesenchymal stem cells for MR imaging. The labeled cells display excellent image contrast in phantom imaging experiments, and TEM images of the labeled cells, in general, reveal small clusters of the CA material located within the cytoplasm with 10(9) Gd(3+) ions per cell.