3D cultures of prostate cancer cells cultured in a novel high-throughput culture platform are more resistant to chemotherapeutics compared to cells cultured in monolayer

Despite monolayer cultures being widely used for cancer drug development and testing, 2D cultures tend to be hypersensitive to chemotherapy and are relatively poor predictors of whether a drug will provide clinical benefit. Whilst generally more complicated, three dimensional (3D) culture systems often better recapitulate true cancer architecture and provide a more accurate drug response. As a step towards making 3D cancer cultures more accessible, we have developed a microwell platform and surface modification protocol to enable high throughput manufacture of 3D cancer aggregates. Herein we use this novel system to characterize prostate cancer cell microaggregates, including growth kinetics and drug sensitivity. Our results indicate that prostate cancer cells are viable in this system, however some non-cancerous prostate cell lines are not. This system allows us to consistently control for the presence or absence of an apoptotic core in the 3D cancer microaggregates. Similar to tumor tissues, the 3D microaggregates display poor polarity. Critically the response of 3D microaggregates to the chemotherapeutic drug, docetaxel, is more consistent with in vivo results than the equivalent 2D controls. Cumulatively, our results demonstrate that these prostate cancer microaggregates better recapitulate the morphology of prostate tumors compared to 2D and can be used for high-throughput drug testing.

Influence of kaolinite particle size on cross-link density, microstructure and mechanical properties of latex blending styrene butadiene rubber composites

Cross-link density, microstructure and mechanical properties of styrene butadiene rubber (SBR) composites filled with different particle sized kaolinites are investigated. With the increase of kaolinite particle size, the cross-link density of the filled SBR composites, the dispersibility and orientation degree of kaolinite particles gradually decrease. Some big cracks in filled rubber composites are distributed along the fringe of kaolinite aggregates, and the absorbance of all the absorption bands of kaolinites gradually increase with the increase of kaolinite particle size. All mechanical property indexes of kaolinite filled SBR composites decrease due to the decrease of cross-linking and reduction of interface interaction between filler and rubber matrix.

Pentacene on Ni(111): room-temperature molecular packing and temperature-activated conversion to graphene

We investigate, using scanning tunnelling microscopy, the adsorption of pentacene on Ni(111) at room temperature and the behaviour of these monolayer films with annealing up to 700 °C. We observe the conversion of pentacene into graphene, which begins from as low as 220 °C with the coalescence of pentacene molecules into large planar aggregates. Then, by annealing at 350 °C for 20 minutes, these aggregates expand into irregular domains of graphene tens of nanometers in size. On surfaces where graphene and nickel carbide coexist, pentacene shows preferential adsorption on the nickel carbide phase. The same pentacene to graphene transformation was also achieved on Cu(111), but at a higher activation temperature, producing large graphene domains that exhibit a range of moiré superlattice periodicities.

A Bayesian model of source monitoring

The Source Monitoring Framework is a promising model of constructive memory, yet fails because it is connectionist and does not allow content tagging. The Dual-Process Signal Detection Model is an improvement because it reduces mnemic qualia to a single memory signal (or degree of belief), but still commits itself to non-discrete representation. By supposing that ‘tagging’ means the assignment of propositional attitudes to aggregates of anemic characteristics informed inductively, then a discrete model becomes plausible. A Bayesian model of source monitoring accounts for the continuous variation of inputs and assignment of prior probabilities to memory content. A modified version of the High-Threshold Dual-Process model is recommended to further source monitoring research.

The rapid manufacture of uniform composite multicellular-biomaterial micropellets, their assembly into macroscopic organized tissues, and potential applications in cartilage tissue engineering

We and others have published on the rapid manufacture of micropellet tissues, typically formed from 100-500 cells each. The micropellet geometry enhances cellular biological properties, and in many cases the micropellets can subsequently be utilized as building blocks to assemble complex macrotissues. Generally, micropellets are formed from cells alone, however when replicating matrix-rich tissues such as cartilage it would be ideal if matrix or biomaterials supplements could be incorporated directly into the micropellet during the manufacturing process. Herein we describe a method to efficiently incorporate donor cartilage matrix into tissue engineered cartilage micropellets. We lyophilized bovine cartilage matrix, and then shattered it into microscopic pieces having average dimensions < 10 μm diameter; we termed this microscopic donor matrix "cartilage dust (CD)". Using a microwell platform, we show that ~0.83 μg CD can be rapidly and efficiently incorporated into single multicellular aggregates formed from 180 bone marrow mesenchymal stem/stromal cells (MSC) each. The microwell platform enabled the rapid manufacture of thousands of replica composite micropellets, with each micropellet having a material/CD core and a cellular surface. This micropellet organization enabled the rapid bulking up of the micropellet core matrix content, and left an adhesive cellular outer surface. This morphological organization enabled the ready assembly of the composite micropellets into macroscopic tissues. Generically, this is a versatile method that enables the rapid and uniform integration of biomaterials into multicellular micropellets that can then be used as tissue building blocks. In this study, the addition of CD resulted in an approximate 8-fold volume increase in the micropellets, with the donor matrix functioning to contribute to an increase in total cartilage matrix content. Composite micropellets were readily assembled into macroscopic cartilage tissues; the incorporation of CD enhanced tissue size and matrix content, but did not enhance chondrogenic gene expression.

Micro paddy lysimeter for monitoring solute transport in paddy environment

The micro paddy lysimeter (MPL) was developed and evaluated for its performance to simulate solute transport in paddy environment under laboratory conditions. MPLs were constructed using soil collected from Field Museum Honmachi of Tokyo University of Agriculture and Technology, Japan. For the physical characteristics of the hardpan layer, parameters such as thickness, and soil aggregate size, affecting the percolation rate were studied. For the plow layer, two types of plow soils, sieved and un-sieved soils were compared. The sieved soil plow layer was produced by mixing air-dried soils of different aggregate sizes of D > 9.50, 9.50 ≥ D > 4.75, 4.75 ≥ D > 2.0 mm and D ≤ 2.0 mm at 47.1, 19.5, 20.6, and 12.8%, respectively. The un-sieved plow layer soil was directly used after collecting from the field. Inert tracer was applied to ponding water with controlled boundary conditions to evaluate the reproducibility of the soil hydraulic characteristics. HYDRUS-1D was used to evaluate the movement of bromide tracer in the MPL. The proposed conditions of the MPL were that the hardpan layer can be made from soil aggregates smaller than 0.425 mm with 2 cm thickness and that the plow layer can be prepared with sieved or un-sieved soils. With these conditions, the obtained results proved that MPLs can be a useful tool to simulate solute transport in paddy environment.

Ship Seakeeping Operability, Motion Control, and Autonomy - A Bayesian Perspective

Ship seakeeping operability refers to the quantification of motion performance in waves relative to mission requirements. This is used to make decisions about preferred vessel designs, but it can also be used as comprehensive assessment of the benefits of ship-motion-control systems. Traditionally, operability computation aggregates statistics of motion computed over over the envelope of likely environmental conditions in order to determine a coefficient in the range from 0 to 1 called operability. When used for assessment of motion-control systems, the increase of operability is taken as the key performance indicator. The operability coefficient is often given the interpretation of the percentage of time operable. This paper considers an alternative probabilistic approach to this traditional computation of operability. It characterises operability not as a number to which a frequency interpretation is attached, but as a hypothesis that a vessel will attain the desired performance in one mission considering the envelope of likely operational conditions. This enables the use of Bayesian theory to compute the probability of that this hypothesis is true conditional on data from simulations. Thus, the metric considered is the probability of operability. This formulation not only adheres to recent developments in reliability and risk analysis, but also allows incorporating into the analysis more accurate descriptions of ship-motion-control systems since the analysis is not limited to linear ship responses in the frequency domain. The paper also discusses an extension of the approach to the case of assessment of increased levels of autonomy for unmanned marine craft.

Spectral analysis of pair-correlation bandwidth: Application to cell biology images

Images from cell biology experiments often indicate the presence of cell clustering, which can provide insight into the mechanisms driving the collective cell behaviour. Pair-correlation functions provide quantitative information about the presence, or absence, of clustering in a spatial distribution of cells. This is because the pair-correlation function describes the ratio of the abundance of pairs of cells, separated by a particular distance, relative to a randomly distributed reference population. Pair-correlation functions are often presented as a kernel density estimate where the frequency of pairs of objects are grouped using a particular bandwidth (or bin width), Δ>0. The choice of bandwidth has a dramatic impact: choosing Δ too large produces a pair-correlation function that contains insufficient information, whereas choosing Δ too small produces a pair-correlation signal dominated by fluctuations. Presently, there is little guidance available regarding how to make an objective choice of Δ. We present a new technique to choose Δ by analysing the power spectrum of the discrete Fourier transform of the pair-correlation function. Using synthetic simulation data, we confirm that our approach allows us to objectively choose Δ such that the appropriately binned pair-correlation function captures known features in uniform and clustered synthetic images. We also apply our technique to images from two different cell biology assays. The first assay corresponds to an approximately uniform distribution of cells, while the second assay involves a time series of images of a cell population which forms aggregates over time. The appropriately binned pair-correlation function allows us to make quantitative inferences about the average aggregate size, as well as quantifying how the average aggregate size changes with time.