Cortical-like mini-columns of neuronal cells on zinc oxide nanowire surfaces

The role of elasticity on adhesion and clustering of neurons on soft surfaces

The question of whether material stiffness enhances cell adhesion and clustering is still open to debate. Results from the literature are seemingly contradictory, with some reports illustrating that adhesion increases with surface stiffness and others suggesting that the performance of a system of cells is curbed by high values of elasticity. To address the role of elasticity as a regulator in neuronal cell adhesion and clustering, we investigated the topological characteristics of networks of neurons on polydimethylsiloxane (PDMS) surfaces - with values of elasticity (E) varying in the 0.55-2.65 MPa range. Results illustrate that, as elasticity increases, the number of neurons adhering on the surface decreases. Notably, the small-world coefficient - a topological measure of networks - also decreases. Numerical simulations and functional multi-calcium imaging experiments further indicated that the activity of neuronal cells on soft surfaces improves for decreasing E. Experimental findings are supported by a mathematical model, that explains adhesion and clustering of cells on soft materials as a function of few parameters - including the Young's modulus and roughness of the material. Overall, results indicate that - in the considered elasticity interval - increasing the compliance of a material improves adhesion, improves clustering, and enhances communication of neurons.

Multicancer screening test based on the detection of circulating non haematological proliferating atypical cells

BACKGROUND

the problem in early diagnosis of sporadic cancer is understanding the individual's risk to develop disease. In response to this need, global scientific research is focusing on developing predictive models based on non-invasive screening tests. A tentative solution to the problem may be a cancer screening blood-based test able to discover those cell requirements triggering subclinical and clinical onset latency, at the stage when the cell disorder, i.e. atypical epithelial hyperplasia, is still in a subclinical stage of proliferative dysregulation.

METHODS

a well-established procedure to identify proliferating circulating tumor cells was deployed to measure the cell proliferation of circulating non-haematological cells which may suggest tumor pathology. Moreover, the data collected were processed by a supervised machine learning model to make the prediction.

RESULTS

the developed test combining circulating non-haematological cell proliferation data and artificial intelligence shows 98.8% of accuracy, 100% sensitivity, and 95% specificity.

CONCLUSION

this proof of concept study demonstrates that integration of innovative non invasive methods and predictive-models can be decisive in assessing the health status of an individual, and achieve cutting-edge results in cancer prevention and management.

The free energy landscape of small-world networks of cells

The properties of organs, tissues, organoids, and other systems of cells, are influenced by the spatial localization and distribution of their elements. Here, we used networks to describe distributions of cells on a surface where the small-world coefficient (SW) of the networks was varied between SW~1 (random uniform distributions) and SW~10 (clustered distributions). The small-world coefficient is a topological measure of graphs: networks with SW>1 are topologically biased to transmit information. For each system configuration, we then determined the total energy U as the sum of the energies that describe cell-cell interactions - approximated by a harmonic potential. The graph of energy (U) across the configuration space of the networks (SW) is the energy landscape: it indicates which configuration a system of cells will likely assume over time. We found that, depending on the model parameters, the energy landscapes of 2D distributions of cells may be of different types: from type I to type IV. Type I and type II systems have high probability to evolve into random distributions. Type III and type IV systems have a higher probability to form clustered architectures. A great many of simulations indicated that cultures of cells with high initial density and limited sensing range could evolve into clustered configurations with enhanced topological characteristics. Moreover, the strongest the binding between cells, the greater the likelihood that they will assume configurations characterized by finite values of SW. Results of the work are relevant for those working the field of tissue engineering, regenerative medicine, the formation of in-vitro-models, the analysis of neuro-degenerative diseases.

A scaffold containing zinc oxide for Schwann cell-mediated axon growth

Objective.Schwann cells (SCs) transplanted in damaged nervous tissue promote axon growth, which may support the recovery of function lost after injury. However, SC transplant-mediated axon growth is often limited and lacks direction.Approach.We have developed a zinc oxide (ZnO) containing fibrous scaffold consisting of aligned fibers of polycaprolactone (PCL) with embedded ZnO nanoparticles as a biodegradable, bifunctional scaffold for promoting and guiding axon growth. This scaffold has bifunctional properties wherein zinc is released providing bioactivity and ZnO has well-known piezoelectric properties where piezoelectric materials generate electrical activity in response to minute deformations. In this study, SC growth, SC-mediated axon extension, and the presence of myelin basic protein (MBP), as an indicator of myelination, were evaluated on the scaffolds containing varying concentrations of ZnOin vitro. SCs and dorsal root ganglion (DRG) neurons were cultured, either alone or in co-culture, on the scaffolds.Main results.Findings demonstrated that scaffolds with 1 wt.% ZnO promoted the greatest SC growth and SC-mediated axon extension. The presence of brain-derived neurotrophic factor (BDNF) was also determined. BDNF increased in co-cultures for all scaffolds as compared to SCs or DRGs cultured alone on all scaffolds. For co-cultures, cells on scaffolds with low levels of ZnO (0.5 wt.% ZnO) had the highest amount of BDNF as compared to cells on higher ZnO-containing scaffolds (1 and 2 wt.%). MBP immunostaining was only detected in co-cultures on PCL control scaffolds (without ZnO).Significance.The results of this study demonstrate the potential of the ZnO-containing scaffolds for SC-mediated axon growth and its potential for use in nervous tissue repair.

The effective enhancement of information in 3D small-world networks of biological neuronal cells

The cardiovascular system, the kidney, or the brain, are examples of complex systems - where the properties of the systems arise because of the layout of cells in those systems. One way to characterize systems is using networks, where elements and interactions of the systems are represented as nodes and links of a graph. Network's topology can be, in turn, measured by the small-world coefficient. Small world networks feature increased clustering and shorter paths compared to random or periodic networks of the same size. This suggests that systems with small world attributes can also efficiently transport signals, nutrients, or information within their body. While several reports in literature have illustrated that real biological systems are small-world, yet little is known about how information varies as a function of the small-world-ness (sw) of three dimensional graphs. Here, we used a model of the brain to estimate quantitatively the information processed in 3D networks. In the model, nodes of the graph are neuronal units capable to receive, integrate and transmit signals to other neurons of the system in parallel. The information encoded in the signals was then extracted using the techniques of information theory. In simulations where the topology of networks of400nodes was varied over large intervals, we found that in the0-9swrange information scales linearly with the small world coefficient, with a five-fold increase. Results of the paper and review of the existing literature on model organisms suggest that a small-world architecture may offer an evolutionary advantage to biological systems.

Impact of Magnetite Nanowires on In Vitro Hippocampal Neural Networks

Nanomaterials design, synthesis, and characterization are ever-expanding approaches toward developing biodevices or neural interfaces to treat neurological diseases. The ability of nanomaterials features to tune neuronal networks' morphology or functionality is still under study. In this work, we unveil how interfacing mammalian brain cultured neurons and iron oxide nanowires' (NWs) orientation affect neuronal and glial densities and network activity. Iron oxide NWs were synthesized by electrodeposition, fixing the diameter to 100 nm and the length to 1 µm. Scanning electron microscopy, Raman, and contact angle measurements were performed to characterize the NWs' morphology, chemical composition, and hydrophilicity. Hippocampal cultures were seeded on NWs devices, and after 14 days, the cell morphology was studied by immunocytochemistry and confocal microscopy. Live calcium imaging was performed to study neuronal activity. Using random nanowires (R-NWs), higher neuronal and glial cell densities were obtained compared with the control and vertical nanowires (V-NWs), while using V-NWs, more stellate glial cells were found. R-NWs produced a reduction in neuronal activity, while V-NWs increased the neuronal network activity, possibly due to a higher neuronal maturity and a lower number of GABAergic neurons, respectively. These results highlight the potential of NWs manipulations to design ad hoc regenerative interfaces.

Advanced theragnostics for the central nervous system (CNS) and neurological disorders using functional inorganic nanomaterials

Various types of inorganic nanomaterials are capable of diagnostic biomarker detection and the therapeutic delivery of a disease or inflammatory modulating agent. Those multi-functional nanomaterials have been utilized to treat neurodegenerative diseases and central nervous system (CNS) injuries in an effective and personalized manner. Even though many nanomaterials can deliver a payload and detect a biomarker of interest, only a few studies have yet to fully utilize this combined strategy to its full potential. Combining a nanomaterial's ability to facilitate targeted delivery, promote cellular proliferation and differentiation, and carry a large amount of material with various sensing approaches makes it possible to diagnose a patient selectively and sensitively while offering preventative measures or early disease-modifying strategies. By tuning the properties of an inorganic nanomaterial, the dimensionality, hydrophilicity, size, charge, shape, surface chemistry, and many other chemical and physical parameters, different types of cells in the central nervous system can be monitored, modulated, or further studies to elucidate underlying disease mechanisms. Scientists and clinicians have better understood the underlying processes of pathologies for many neurologically related diseases and injuries by implementing multi-dimensional 0D, 1D, and 2D theragnostic nanomaterials. The incorporation of nanomaterials has allowed scientists to better understand how to detect and treat these conditions at an early stage. To this end, having the multi-modal ability to both sense and treat ailments of the central nervous system can lead to favorable outcomes for patients suffering from such injuries and diseases.

Human lung-cancer-cell radioresistance investigated through 2D network topology

Radiation therapy (RT) is now considered to be a main component of cancer therapy, alongside surgery, chemotherapy and monoclonal antibody-based immunotherapy. In RT, cancer tissues are exposed to ionizing radiation causing the death of malignant cells and favoring cancer regression. However, the efficiency of RT may be hampered by cell-radioresistance (RR)—that is a feature of tumor cells of withstanding RT. To improve the RT performance, it is decisive developing methods that can help to quantify cell sensitivity to radiation. In acknowledgment of the fact that none of the existing methods to assess RR are based on cell graphs topology, in this work we have examined how 2D cell networks, within a single colony, from different human lung cancer lines (H460, A549 and Calu-1) behave in response to doses of ionizing radiation ranging from 0 to 8 Gy. We measured the structure of resulting cell-graphs using well-assessed networks-analysis metrics, such as the clustering coefficient (cc), the characteristic path length (cpl), and the small world coefficient (SW). Findings of the work illustrate that the clustering characteristics of cell-networks show a marked sensitivity to the dose and cell line. Higher-than-one values of SW coefficient, clue of a discontinuous and inhomogeneous cell spatial layout, are associated to elevated levels of radiation and to a lower radio-resistance of the treated cell line. Results of the work suggest that topology could be used as a quantitative parameter to assess the cell radio-resistance and measure the performance of cancer radiotherapy.

The small world coefficient 4.8 ± 1 optimizes information processing in 2D neuronal networks

Small world networks have recently attracted much attention because of their unique properties. Mounting evidence suggests that communication is optimized in networks with a small world topology. However, despite the relevance of the argument, little is known about the effective enhancement of information in similar graphs. Here, we provide a quantitative estimate of the efficiency of small world networks. We used a model of the brain in which neurons are described as agents that integrate the signals from other neurons and generate an output that spreads in the system. We then used the Shannon Information Entropy to decode those signals and compute the information transported in the grid as a function of its small-world-ness (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{SW}}$$\end{document}SW), of the length (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\triangle t$$\end{document}∆t) and frequency (\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f$$\end{document}f) of the originating stimulus. In numerical simulations in which \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{SW}}$$\end{document}SW was varied between \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$0$$\end{document}0 and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$14$$\end{document}14 we found that, for certain values of \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\triangle t$$\end{document}∆t and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f$$\end{document}f, communication is enhanced up to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$30$$\end{document}30 times compared to unstructured systems of the same size. Moreover, we found that the information processing capacity of a system steadily increases with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{SW}}$$\end{document}SW until the value \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{SW}}=4.8\pm 1$$\end{document}SW=4.8±1, independently on \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\triangle t$$\end{document}∆t and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$f$$\end{document}f. After this threshold, the performance degrades with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\rm{SW}}$$\end{document}SW and there is no convenience in increasing indefinitely the number of active links in the system. Supported by the findings of the work and in analogy with the exergy in thermodynamics, we introduce the concept of exordic systems: a system is exordic if it is topologically biased to transmit information efficiently.

Time dependent adhesion of cells on nanorough surfaces

Understanding and controlling the mechanisms of cell adhesion to nanomaterials is essential in tissue engineering, regenerative medicine, the development of experimental models for the study of neurodegenerative diseases. Nonetheless, despite the great many of studies that have examined how cells interact with nanoscale surfaces, little is known about the temporal dimension of the process of adhesion. In a previous work, Decuzzi and Ferrari, by examining how the energy of a cell changes while binding to a nanoscale surface, determined a criterion to decide whether nanoroughness can either enhance or retard cell adhesion. While accurate, however their model template disregards the time variable. Here, starting from the work of Decuzzi and Ferrari, we have developed a mathematical model based on chemotaxis that describes how cells adhere to a nanorough surface over time. Relaxing the originating constraint of a fixed density of ligand molecules expressed by the cell membrane, we show that the strength of adhesion depends on time and that, for certain values of the model parameters, a cell can arrive to establish a stable adhesion to a substrate even if the process of binding is initially energetically unfavourable. We show that, for a cell-membrane stiffness of 10kPa, an initial density of receptors of 500bonds/μm², a specific and non-specific energy density of adhesion of 10^-5J/m² and 10^-7J/m², and roughness in the low nanometer range, cell adhesion forces can be completely activated from few seconds to some tens of minutes from the initial contact with the surface.

A Promising Approach: Artificial Intelligence Applied to Small Intestinal Bacterial Overgrowth (SIBO) Diagnosis Using Cluster Analysis

Small intestinal bacterial overgrowth (SIBO) is characterized by abnormal and excessive amounts of bacteria in the small intestine. Since symptoms and lab tests are non-specific, the diagnosis of SIBO is highly dependent on breath testing. There is a lack of a universally accepted cut-off point for breath testing to diagnose SIBO, and the dilemma of defining "SIBO patients" has made it more difficult to explore the gold standard for SIBO diagnosis. How to validate the gold standard for breath testing without defining "SIBO patients" has become an imperious demand in clinic. Breath-testing datasets from 1071 patients were collected from Xiangya Hospital in the past 3 years and analyzed with an artificial intelligence method using cluster analysis. K-means and DBSCAN algorithms were applied to the dataset after the clustering tendency was confirmed with Hopkins Statistic. Satisfying the clustering effect was evaluated with a Silhouette score, and patterns of each group were described. Advantages of artificial intelligence application in adaptive breath-testing diagnosis criteria with SIBO were discussed from the aspects of high dimensional analysis, and data-driven and regional specific dietary influence. This research work implied a promising application of artificial intelligence for SIBO diagnosis, which would benefit clinical practice and scientific research.

Cell aggregation on nanorough surfaces

The ability to control adhesion and the spatial organization of cells over nanoscale surfaces is essential in tissue engineering, regenerative medicine, the growth of organoids and spheroids as an in-vitro-model of human development and disease. Nonetheless, despite the several different works that have explored the influence of nanotopography on cell adhesion and clustering, little is known about how the forces arising from membrane conformational change developing during cell adaptation to a nanorough surface, and the cell-cell adhesion forces, interact to guide cell assembly. Here, starting from the works of Decuzzi and Ferrari, who examined how the energy of a cell varies while adhering to a nanoscale surface, and of Armstrong and collaborators, who developed a continuous model of cell-cell adhesion and morphogenesis, we provide a description of how nanotopography can modulate cellular clustering. In simulations where the parameters of the model were varied over large intervals, we found that nanoroughness may induce cell aggregation from a homogenous, uniform state, also for weak cell-cell adhesion. Results of the model are relevant in bio-engineering and biomedical nanotechnology, and may be of interest for those involved in the design and fabrication of biomaterials and scaffolds for tissue formation and repair.

On the Interaction between 1D Materials and Living Cells

One-dimensional (1D) materials allow for cutting-edge applications in biology, such as single-cell bioelectronics investigations, stimulation of the cellular membrane or the cytosol, cellular capture, tissue regeneration, antibacterial action, traction force investigation, and cellular lysis among others. The extraordinary development of this research field in the last ten years has been promoted by the possibility to engineer new classes of biointerfaces that integrate 1D materials as tools to trigger reconfigurable stimuli/probes at the sub-cellular resolution, mimicking the in vivo protein fibres organization of the extracellular matrix. After a brief overview of the theoretical models relevant for a quantitative description of the 1D material/cell interface, this work offers an unprecedented review of 1D nano- and microscale materials (inorganic, organic, biomolecular) explored so far in this vibrant research field, highlighting their emerging biological applications. The correlation between each 1D material chemistry and the resulting biological response is investigated, allowing to emphasize the advantages and the issues that each class presents. Finally, current challenges and future perspectives are discussed.

Cell Theranostics on Mesoporous Silicon Substrates

The adhesion, proliferation, and migration of cells over nanomaterials is regulated by a cascade of biochemical signals that originate at the interface of a cell with a substrate and propagate through the cytoplasm to the nucleus. The topography of the substrate plays a major role in this process. Cell adhesion molecules (CAMs) have a characteristic size of some nanometers and a range of action of some tens of nanometers. Controlling details of a surface at the nanoscale-the same dimensional over which CAMs operate-offers ways to govern the behavior of cells and create organoids or tissues with heretofore unattainable precision. Here, using electrochemical procedures, we generated mesoporous silicon surfaces with different values of pore size (PS≈11 nm and PS≈21 nm), roughness (Ra≈7 nm and Ra≈13 nm), and fractal dimension (Df≈2.48 and Df≈2.15). Using electroless deposition, we deposited over these substrates thin layers of gold nanoparticles. Resulting devices feature (i) nanoscale details for the stimulation and control of cell assembly, (ii) arrays of pores for drug loading/release, (iii) layers of nanostructured gold for the enhancement of the electromagnetic signal in Raman spectroscopy (SERS). We then used these devices as cell culturing substrates. Upon loading with the anti-tumor drug PtCl (O,O'-acac)(DMSO) we examined the rate of adhesion and growth of breast cancer MCF-7 cells under the coincidental effects of surface geometry and drug release. Using confocal imaging and SERS spectroscopy we determined the relative importance of nano-topography and delivery of therapeutics on cell growth-and how an unbalance between these competing agents can accelerate the development of tumor cells.

Small-world networks of neuroblastoma cells cultured in three-dimensional polymeric scaffolds featuring multi-scale roughness

Understanding the mechanisms underlying cell-surface interaction is of fundamental importance for the rational design of scaffolds aiming at tissue engineering, tissue repair and neural regeneration applications. Here, we examined patterns of neuroblastoma cells cultured in three-dimensional polymeric scaffolds obtained by two-photon lithography. Because of the intrinsic resolution of the technique, the micrometric cylinders composing the scaffold have a lateral step size of ~200 nm, a surface roughness of around 20 nm, and large values of fractal dimension approaching 2.7. We found that cells in the scaffold assemble into separate groups with many elements per group. After cell wiring, we found that resulting networks exhibit high clustering, small path lengths, and small-world characteristics. These values of the topological characteristics of the network can potentially enhance the quality, quantity and density of information transported in the network compared to equivalent random graphs of the same size. This is one of the first direct observations of cells developing into 3D small-world networks in an artificial matrix.

Water-in-PDMS Emulsion Templating of Highly Interconnected Porous Architectures for 3D Cell Culture

The development of advanced techniques of fabrication of three-dimensional (3D) microenvironments for the study of cell growth and proliferation has become one of the major motivations of material scientists and bioengineers in the past decade. Here, we present a novel residueless 3D structuration technique of poly(dimethylsiloxane) (PDMS) by water-in-PDMS emulsion casting and subsequent curing process in temperature-/pressure-controlled environment. Scanning electron microscopy and X-ray microcomputed tomography allowed us to investigate the impact of those parameters on the microarchitecture of the porous structure. We demonstrated that the optimized emulsion casting process gives rise to large-scale and highly interconnected network with pore size ranging from 500 μm to 1.5 mm that turned out to be nicely adapted to 3D cell culture. Experimental cell culture validations were performed using SaOS-2 (osteosarcoma) cell lines. Epifluorescence and deep penetration imaging techniques as two-photon confocal microscopy unveiled information about cell morphology and confirmed a homogeneous cell proliferation and spatial distribution in the 3D porous structure within an available volume larger than 1 cm³. These results open alternative scenarios for the fabrication and integration of porous scaffolds for the development of 3D cell culture platforms.