Relating the rate of growth of metal nanoparticles to cluster size distribution in electroless deposition

Electroless deposition on patterned silicon substrates enables the formation of metal nanomaterials with tight control over their size and shape. In the technique, metal ions are transported by diffusion from a solution to the active sites of an autocatalytic substrate where they are reduced as metals upon contact. Here, using diffusion limited aggregation models and numerical simulations, we derived relationships that correlate the cluster size distribution to the total mass of deposited particles. We found that the ratio ξ between the rates of growth of two different metals depends on the ratio γ between the rates of growth of clusters formed by those metals through the linearity law ξ = 14(γ - 1). We then validated the model using experiments. Different from other methods, the model derives k using as input the geometry of metal nanoparticle clusters, decoded by SEM or AFM images of samples, and a known reference

Vascular endothelial growth factor-A and Poly(A) binding protein-interacting protein 2 expression in human head and neck carcinomas: correlation and prognostic significance

Vascular endothelial growth factor-A (VEGF-A) has been demonstrated to play an important role in tumour angiogenesis and to influence prognosis in many cancers. However its prognostic value in head and neck squamous cell carcinomas (HNSCCs) remains controversial. Therefore, we investigated the clinical relevance of VEGF-A expression in HNSCCs and analysed whether its expression was associated with PAIP2 protein levels, a VEGF-A mRNA-binding partner that strongly regulates VEGF-A expression in tissue culture. We determined the correlation of VEGF-A and PAIP2 protein levels, quantitatively evaluated in tumour tissue homogenates from 54 patients with HNSCC, to clinicopathological parameters. We showed that VEGF-A expression in HNSCC is correlated to the stage of tumour differentiation (P=0.050) and is an independent prognostic factor for progression-free survival (P=0.001) and overall survival (P=0.0004). In a pharynx carcinoma cell line, we demonstrated by RNA interference that VEGF-A expression is closely controlled by PAIP2. Moreover, in human HNSCCs, VEGF-A expression is significantly correlated to PAIP2 protein levels (P=0.0018). Nevertheless, PAIP2 expression is associated with neither clinicopathological factors nor patient's survival. Our data suggest that, in contrast to PAIP2 protein levels, which are unrelated to tumour prognosis, VEGF-A expression could serve as a prognostic marker in head and neck cancer and may be helpful for targeted therapies

Synthesis of plasmonic gold nanoparticles on soft materials for biomedical applications

Plasmonic metal nanomaterials are usually supported by rigid substrates, typically made of silicon or glass. Recently, there has been growing interest in developing soft plasmonic devices. Such devices are low weight, low cost, exhibit elevated flexibility and improved mechanical properties. Moreover, they maintain the features of conventional nano-optic structures, such as the ability to enhance the local electromagnetic field. On account of these characteristics, they show promise as efficient biosensors in biological, medical, and bio-engineering applications. Here, we demonstrate the fabrication of soft polydimethylsiloxane (PDMS) plasmonic devices. Using a combination of techniques, including electroless deposition, we patterned thin membranes of PDMS with arrays of gold nanoparticle clusters. Resulting devices show regular patterns of gold nanoparticles extending over several hundreds of microns and are moderately hydrophilic, with a contact angle of about 80°. At the nanoscale, scanning electron and atomic force microscopy of samples reveal an average particle size of ∼50 nm. The nanoscopic size of the particles, along with their random distribution in a cluster, promotes the enhancement of electromagnetic fields, evidenced by numerical simulations and experiments. Mechanical characterization and the stress-strain relationship indicate that the device has a stiffness of 2.8 MPa. In biological immunoassay tests, the device correctly identified and detected anti-human immunoglobulins G (IgG) in solution with a concentration of 25 μg/ml

Nano-topography Enhances Communication in Neural Cells Networks

Abstract Neural cells are the smallest building blocks of the central and peripheral nervous systems. Information in neural networks and cell-substrate interactions have been heretofore studied separately. Understanding whether surface nano-topography can direct nerve cells assembly into computational efficient networks may provide new tools and criteria for tissue engineering and regenerative medicine. In this work, we used information theory approaches and functional multi calcium imaging (fMCI) techniques to examine how information flows in neural networks cultured on surfaces with controlled topography. We found that substrate roughness S a affects networks topology. In the low nano-meter range, S a  = 0–30 nm, information increases with S a . Moreover, we found that energy density of a network of cells correlates to the topology of that network. This reinforces the view that information, energy and surface nano-topography are tightly inter-connected and should not be neglected when studying cell-cell interaction in neural tissue repair and regeneration

Probing Single-Cell Fermentation Fluxes and Exchange Networks via pH-Sensing Hybrid Nanofibers

The homeostatic control of their environment is an essential task of living cells. It has been hypothesized that, when microenvironmental pH inhomogeneities are induced by high cellular metabolic activity, diffusing protons act as signaling molecules, driving the establishment of exchange networks sustained by the cell-to-cell shuttling of overflow products such as lactate. Despite their fundamental role, the extent and dynamics of such networks is largely unknown due to the lack of methods in single-cell flux analysis. In this study, we provide direct experimental characterization of such exchange networks. We devise a method to quantify single-cell fermentation fluxes over time by integrating high-resolution pH microenvironment sensing via ratiometric nanofibers with constraint-based inverse modeling. We apply our method to cell cultures with mixed populations of cancer cells and fibroblasts. We find that the proton trafficking underlying bulk acidification is strongly heterogeneous, with maximal single-cell fluxes exceeding typical values by up to 3 orders of magnitude. In addition, a crossover in time from a networked phase sustained by densely connected "hubs" (corresponding to cells with high activity) to a sparse phase dominated by isolated dipolar motifs (i.e., by pairwise cell-to-cell exchanges) is uncovered, which parallels the time course of bulk acidification. Our method addresses issues ranging from the homeostatic function of proton exchange to the metabolic coupling of cells with different energetic demands, allowing for real-time noninvasive singlecell metabolic flux analysis

Neurophysiology

Contains research objectives and reports on three research projects.U. S. Air Force Office of Scientific Research under Contract AF49(638)-398National Institutes of HealthTeagle Foundation, IncorporatedBell Telephone Laboratories, Incorporate

Probing Single-Cell Fermentation Fluxes and Exchange Networks via pH-Sensing Hybrid Nanofibers [Dataset]

37 pages. -- Further details on experimental methods: Synthesis of particle-based pH-sensors. -- Fabrication of pH-sensing hybrid nanofibers. -- Characterization of pH-sensing hybrid nanofibers. -- Calibration of pH-sensing hybrid nanofibers. -- Cell proliferation assay. -- Cell co-cultures on pH-sensing hybrid nanofibers. -- Extracellular lactate quantification. -- Statistical significance. -- Sensing of pH in the cell cultures over time. -- Further details on image analysis: [A] Particle (cell or sensor) detection. -- [B] Intensity Evaluation. -- [C] Tracking cells and probes across frames. -- Further details on computational methods: Gaussian approximation. -- Enforcing positivity constraints of the reconstructed concentration profile. -- Priors and Lagrange multipliers: Tikhonov regularizer for the scale !1. -- Time continuity across frames !2. -- Matching the bulk trend !3. -- The Monte Carlo Markov chain. -- Errors and confidence interval. -- Ruling out flow contributions from advection. -- Flux distributions conditioned on the cell type. -- pH maps. -- Supporting files description. - Data. -- Codes. -- Supplementary Figures.The homeostatic control of their environment is an essential task of living cells. It has been hypothesized that, when microenvironmental pH inhomogeneities are induced by high cellular metabolic activity, diffusing protons act as signaling molecules, driving the establishment of exchange networks sustained by the cell-to-cell shuttling of overflow products such as lactate. Despite their fundamental role, the extent and dynamics of such networks is largely unknown due to the lack of methods in single-cell flux analysis. In this study, we provide direct experimental characterization of such exchange networks. We devise a method to quantify single-cell fermentation fluxes over time by integrating high-resolution pH microenvironment sensing via ratiometric nanofibers with constraint-based inverse modeling. We apply our method to cell cultures with mixed populations of cancer cells and fibroblasts. We find that the proton trafficking underlying bulk acidification is strongly heterogeneous, with maximal single-cell fluxes exceeding typical values by up to 3 orders of magnitude. In addition, a crossover in time from a networked phase sustained by densely connected “hubs” (corresponding to cells with high activity) to a sparse phase dominated by isolated dipolar motifs (i.e., by pairwise cell-to-cell exchanges) is uncovered, which parallels the time course of bulk acidification. Our method addresses issues ranging from the homeostatic function of proton exchange to the metabolic coupling of cells with different energetic demands, allowing for real-time noninvasive single-cell metabolic flux analysis.Peer reviewe

Microenvironment Changes (in pH) Affect VEGF Alternative Splicing

Vascular endothelial growth factor-A (VEGF-A) has several isoforms, which differ in their capacity to bind extracellular matrix proteins and also in their affinity for VEGF receptors. Although the relative contribution of the VEGF isoforms has been studied in tumor angiogenesis, little is known about the mechanisms that regulate the alternative splicing process. Here, we tested microenvironment cues that might regulate VEGF alternative splicing. To test this, we used endometrial cancer cells that produce all VEGF isoforms as a model, and exposed them to varying pH levels, hormones, glucose and CoCl2 (to mimic hypoxia). Low pH had the most consistent effects in inducing variations in VEGF splicing pattern (VEGF121 increased significantly, p < 0.001, when compared to VEGF145, 165 or 189). This was accompanied by activation of the p38 stress pathway and SR proteins (splicing factors) expression and phosphorylation. SF2/ASF, SRp20 and SRp40 down-regulation by siRNA impaired the effects of pH stimulation, blocking the shift in VEGF isoforms production. Taken together, we show for the first time that acidosis (low pH) regulates VEGF-A alternative splicing, may be through p38 activation and suggest the possible SR proteins involved in this process

Superhydrophobic lab-on-chip measures secretome protonation state and provides a personalized risk assessment of sporadic tumour

Secretome of primary cultures is an accessible source of biological markers compared to more complex and less decipherable mixtures such as serum or plasma. The protonation state (PS) of secretome reflects the metabolism of cells and can be used for cancer early detection. Here, we demonstrate a superhydrophobic organic electrochemical device that measures PS in a drop of secretome derived from liquid biopsies. Using data from the sensor and principal component analysis (PCA), we developed algorithms able to efficiently discriminate tumour patients from non-tumour patients. We then validated the results using mass spectrometry and biochemical analysis of samples. For the 36 patients across three independent cohorts, the method identified tumour patients with high sensitivity and identification as high as 100% (no false positives) with declared subjects at-risk, for sporadic cancer onset, by intermediate values of PS. This assay could impact on cancer risk management, individual’s diagnosis and/or help clarify risk in healthy populations

Neurophysiology

Contains research objectives.Bell Telephone Laboratories, Inc.The Teagle Foundation, Inc.National Institutes of Health (Grant NB-01865-05)National Institutes of Health (Grant MH-04737-02)U.S. Air Force (Aeronautical Systems Division) under Contract AF33(616)-778