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Cell sedimentation in 3D hydrogel cultures refers to the vertical migration of cells towards the bottom of the space. Understanding this poorly examined phenomenon may allow us to design better protocols to prevent it, as well as provide insights into the mechanobiology of cancer development. We conducted a multiscale experimental and mathematical examination of 3D cancer growth in triple negative breast cancer cells. Migration was examined in the presence and absence of Paclitaxel, in high and low adhesion environments and in the presence of fibroblasts. The observed behaviour was modeled by hypothesizing active migration due to self-generated chemotactic gradients. Our results did not reject this hypothesis, whereby migration was likely to be regulated by the MAPK and TGF-β pathways. The mathematical model enabled us to describe the experimental data in absence (normalized error<40%) and presence of Paclitaxel (normalized error<10%), suggesting inhibition of random motion and advection in the latter case. Inhibition of sedimentation in low adhesion and co-culture experiments further supported the conclusion that cells actively migrated downwards due to the presence of signals produced by cells already attached to the adhesive glass surface.

Chemical vapor deposition (CVD) methods to create carbon nanotubes (CNTs) with specific dopant atoms have been of interest in biomedical applications due to the relative ease of synthesis of doped CNTs with controlled physical properties. However, CNTs generated from CVD are often heterogeneous in chemical functionality, size, aspect ratio, number of walls, and conducting properties resulting in potential inconsistencies during measurement of the physiological activity of cell-CNT interactions. In this work, the biocompatibility of nitrogen-doped multiwalled carbon nanotubes (CNx) with both murine fibroblasts and human hematopoietic stem cells (hHSC) was evaluated. CNx were synthesized by CVD, purified, characterized, and classified into three fractions designated as small-CNx (S-CNx), medium (M-CNx), and large (L-CNx). Mammalian cells were incubated with CNx doses between 0.07 and 70 μg/mL, and cell viability was evaluated. hHSC and murine fibroblast both demonstrated non-significant differences in proliferation rates when exposed to M-CN, whereas, either cells experienced inhibited growth following exposure to either S-CNx and L-CNx under the same conditions. In this work, it has been demonstrated that CNTs produced by CVD have differences on the biocompatibility with mammalian cells, but the M-CNx could be a great candidate for biomedical applications.

The invasion of cancer cells into the surrounding tissues is one of the hallmarks of cancer. However, a precise quantitative understanding of the spatiotemporal patterns of cancer cell migration and invasion still remains elusive. A promising approach to investigate these patterns are 3D cell cultures, which provide more realistic models of cancer growth compared to conventional 2D monolayers. Quantifying the spatial distribution of cells in these 3D cultures yields great promise for understanding the spatiotemporal progression of cancer. In the present study, we present an image processing and segmentation pipeline for the detection of 3D GFP-fluorescent triple-negative breast cancer cell nuclei, and we perform quantitative analysis of the formed spatial patterns and their temporal evolution. The performance of the proposed pipeline was evaluated using experimental 3D cell culture data, and was found to be comparable to manual segmentation, outperforming four alternative automated methods. The spatiotemporal statistical analysis of the detected distributions of nuclei revealed transient, non-random spatial distributions that consisted of clustered patterns across a wide range of neighbourhood distances, as well as dispersion for larger distances. Overall, the implementation of the proposed framework revealed the spatial organization of cellular nuclei with improved accuracy, providing insights into the 3 dimensional inter-cellular organization and its progression through time.

Cell sedimentation in 3D culture environments refers to the vertical migration of cells towards the bottom of the space. This occurs despite the use of hydrogel materials in 3D cell cultures, which would be expected to prevent this behavior. To better understand and explain these experimental observations, we conducted a multiscale experimental and mathematical examination of 3D cancer growth and sedimentation in triple negative breast cancer cells. The migration of cells towards the bottom was examined in the presence and absence of the migrastatic drug Paclitaxel, as well as in a low adhesion environment and the presence of fibroblasts. The observed behaviour was modeled mathematically by hypothesizing self-generated chemotactic gradients. Our results reveal that active migration mechanisms, specifically collective migration regulated by the MAPK and TGF-β pathways, play an important role in sedimentation. The mathematical model was able to describe the experimental data in the absence and presence of Paclitaxel, suggesting the inhibition of random motion and advection mechanism in the latter case. Low adhesion environment and multiple cell type experiments resulted in an inhibition of sedimentation. Overall, our results suggest that cells, initially uniformly distributed in the 3D space, actively migrate towards the bottom due to the presence of signals produced by cells already attached to it, providing mechanistic insights into this unexpected behavior.Competing Interest StatementThe authors have declared no competing interest.Footnotes* https://nmdimitriou.github.io/HyMetaGrowthXTreat/

Mathematical models of cancer growth have become increasingly more accurate both in the space and time domains. However, the limited amount of data typically available has resulted in a larger number of qualitative rather than quantitative studies. In the present study, we provide an integrated experimental-computational framework for the quantification of the morphological characteristics and the mechanistic modelling of cancer progression in 3D environments. The proposed framework allows for the calibration of multiscale, spatiotemporal models of cancer growth using state-of-the-art 3D cell culture data, and their validation based on the resulting experimental morphological patterns using spatial point-pattern analysis techniques. We applied this framework to the study of the development of Triple Negative Breast Cancer cells cultured in Matrigel scaffolds, and validated the hypothesis of chemotactic migration using a multiscale, hybrid Keller-Segel model. The results revealed transient, non-random spatial distributions of cancer cells that consist of clustered, and dispersion patterns. The proposed model was able to describe the general characteristics of the experimental observations and suggests that cancer cells exhibited chemotactic migration and accumulation, as well as random motion during the examined time period of development. The developed framework enabled us to pursue two goals; first, the quantitative description of the morphology of cancer growth in 3D cultures using point-pattern analysis, and second, the relation of tumour morphology with underlying biophysical mechanisms that govern cancer growth and migration. Competing Interest Statement The authors have declared no competing interest. Footnotes * corrected figure in supplementary * https://nmdimitriou.github.io/HyMetaGrowth/

The invasion of cancer cells into the surrounding tissues is one of the hallmarks of cancer. However, a precise quantitative understanding of the spatiotemporal patterns of cancer cell migration and invasion still remains elusive. A promising approach to investigate these patterns are 3D cell cultures, which provide more realistic models of cancer growth compared to conventional 2D monolayers. Quantifying the spatial distribution of cells in these 3D cultures yields great promise for understanding the spatiotemporal progression of cancer. In the present study, we present an image processing and segmentation pipeline for the detection of 3D GFP-fluorescent Triple-Negative Breast Cancer cell nuclei, and we perform quantitative analysis of the formed spatial patterns and their temporal evolution. The performance of the proposed pipeline was evaluated using experimental 3D cell culture data, and was found to be comparable to manual segmentation, outperforming four alternative automated methods. The spatiotemporal statistical analysis of the detected distributions of nuclei revealed transient, non-random spatial distributions that consisted of clustered patterns across a wide range of neighbourhood distances, as well as dispersion for larger distances. Overall, the implementation of the proposed framework revealed the spatial organization of cellular nuclei with improved accuracy, providing insights into the 3 dimensional inter-cellular organization and its progression through time. Competing Interest Statement The authors have declared no competing interest. Footnotes * https://figshare.com/projects/3D-GROWTH-MDA-MB-231-SERIES-12/118989 * https://github.com/NMDimitriou/3D-Preprocessing-Nuclei-Segmentation.git * https://github.com/NMDimitriou/3D-spatial-analysis-cell-nuclei.git

Healthcare workers (HCWs) have a theoretically increased risk of contracting severe acute respiratory coronavirus virus 2 (SARS-CoV-2) given their occupational exposure. We tested 2,167 HCWs in a London Acute Integrated Care Organisation for antibodies to SARS-CoV-2 in May and June 2020 to evaluate seroprevalence. We found a seropositivity rate of 31.6% among HCWs.

Abstract Background Tuberculous meningitis (TBM) disproportionately impacts high–HIV prevalence, resource-limited settings where diagnosis is challenging. The GeneXpert platform has utility in TBM diagnosis, but uptake remains limited. In Botswana, before the introduction of GeneXpert, tuberculosis (TB) testing was only available through mycobacterial culture at the National TB Reference Laboratory. Data describing routine use of Xpert MTB/RIF for cerebrospinal fluid (CSF) testing in resource-limited settings are scarce. Methods Electronic records for patients with CSF tested in government facilities in Botswana between 2016 and 2022 were obtained from a central online repository as part of ongoing national meningitis surveillance. Samples were excluded from 1 site where Xpert MTB/RIF is performed universally. The proportion receiving TB-specific investigation on CSF and the number positive for Mycobacterium tuberculosis following increased Xpert MTB/RIF capacity were determined. Results The proportion of CSF samples receiving TB-specific investigation increased from 4.5% (58/1288) in 2016 to 29.0% (201/693) in 2022, primarily due to increased analysis with Xpert MTB/RIF from 0.9% (11/1288) to 23.2% (161/693). There was an overall decline in the annual number of CSF samples analyzed, but the proportion with microbiologically confirmed TBM increased from 0.4% to 1.2%. The proportion of samples tested for TB that were collected from health care facilities >100 km from the National TB Reference Laboratory increased with Xpert MTB/RIF rollout from 65.9% (87/132) to 78.0% (494/633). Conclusions In Botswana, access to TB culture is challenging in remote populations; more accessible near-patient testing using Xpert MTB/RIF increased the number of patients receiving TB-specific testing on CSF and the number of confirmed TBM cases.

Genetic disruption of the RAS binding domain (RBD) of PI 3-kinase (PI3K) prevents the growth of mutant RAS driven tumors in mice and does not impact PI3K's role in insulin mediated control of glucose homeostasis. Selectively blocking the RAS-PI3K interaction may represent an attractive strategy for treating RAS-dependent cancers as it would avoid the toxicity associated with inhibitors of PI3K lipid kinase activity such as alpelisib. Here we report compounds that bind covalently to cysteine 242 in the RBD of PI3K p110α and block the ability of RAS to activate PI3K activity. These inhibitors have a profound impact on the growth of RAS mutant and also HER2 over-expressing tumors, particularly when combined with other inhibitors of the RAS/MAPK pathway, without causing hyperglycemia.

Genetic disruption of the RAS binding domain (RBD) of PI 3-kinase (PI3K) prevents the growth of mutant RAS driven tumors in mice and does not impact PI3Ks role in insulin mediated control of glucose homeostasis. Selectively blocking the RAS-PI3K interaction may represent an attractive strategy for treating RAS-dependent cancers as it would avoid the toxicity associated with inhibitors of PI3K lipid kinase activity such as alpelisib. Here we report compounds that bind covalently to cysteine 242 in the RBD of PI3K p110a and block the ability of RAS to activate PI3K activity. These inhibitors have a profound impact on the growth of RAS mutant and also HER2 over-expressing tumors, particularly when combined with other inhibitors of the RAS/MAPK pathway, without causing hyperglycemia.Competing Interest StatementJ.E.K., N.R., S.M.B., S.G., M.A.H., H.M., J.T., J.W., C.B., A.E.O., R.L., Y.L., M.P., H.P., I.M., A.N.S., E.J.W., T.E.W., E.A., K.B., B.D.H., K.N.L., W.L., J.M., M.K.P., J.P., J.J.S., G.M.S., D.S.W., M.P.P are current employees of Vividion Therapeutics. J.C.B., J.M.C., K.H., E.T. and T.M.K. are former employees of Vividion Therapeutics. J.D. has acted as a consultant for AstraZeneca, Jubilant, Theras, Roche, Boehringer Ingelheim and Kestrel Therapeutics and has funded research agreements with Bristol Myers Squibb, Revolution Medicines, Vividion, Novartis and AstraZeneca. M.M.A., M.I., S.R., and M.T. have no competing interests to declare.Footnotes* Corrected typos/mislabeling on Figure 2 and Figure 5E