Low-cost Sensor System for Non-invasive Monitoring of Cell Growth in Disposable Bioreactors

AbstractTo ensure productivity and product quality, the parameters of biotechnological processes need to be monitored. Along temperature or pH, one important parameter is the cell density in the culture medium. In this work, we present a low-cost sensor system for online cell growth monitoring in bioreactors via permittivity measurements based on coplanar transmission lines. To evaluate the sensor, E. coli cultivations are performed. We found a good correlation between optical density of the culture medium and the effective permittivity at a frequency of 1kHz when the sensor is submerged into the culture medium. Measurements at higher frequencies additionally allow monitoring the osmolarity. Furthermore, an improved sensor was successfully used for first non-invasive measurements through the polymer wall of a disposable bioreactor

A conceptual-model-based sediment connectivity assessment for patchy agricultural catchments

The accelerated sediment supply from agricultural soils to riverine and lacustrine environments leads to negative off-site consequences. In particular, the sediment connectivity from agricultural land to surface waters is strongly affected by landscape patchiness and the linear structures that separate field parcels (e.g. roads, tracks, hedges, and grass buffer strips). Understanding the interactions between these structures and sediment transfer is therefore crucial for minimising off-site erosion impacts. Although soil erosion models can be used to understand lateral sediment transport patterns, model-based connectivity assessments are hindered by the uncertainty in model structures and input data. Specifically, the representation of linear landscape features in numerical soil redistribution models is often compromised by the spatial resolution of the input data and the quality of the process descriptions. Here we adapted the Water and Tillage Erosion Model and Sediment Delivery Model (WaTEM/SE-DEM) using high-resolution spatial data (2 m x 2 m) to analyse the sediment connectivity in a very patchy mesoscale catchment (73 km(2)) of the Swiss Plateau. We used a global sensitivity analysis to explore model structural assumptions about how linear landscape features (dis)connect the sediment cascade, which allowed us to investigate the uncertainty in the model structure. Furthermore, we compared model simulations of hillslope sediment yields from five sub-catchments to tributary sediment loads, which were calculated with long-term water discharge and suspended sediment measurements. The sensitivity analysis revealed that the assumptions about how the road network (dis)connects the sediment transfer from field blocks to water courses had a much higher impact on modelled sediment yields than the uncertainty in model parameters. Moreover, model simulations showed a higher agreement with tributary sediment loads when the road network was assumed to directly connect sediments from hillslopes to water courses. Our results ultimately illustrate how a high-density road network combined with an effective drainage system increases sediment connectivity from hillslopes to surface waters in agricultural landscapes. This further highlights the importance of considering linear landscape features and model structural uncertainty in soil erosion and sediment connectivity research

Criticality in biocomputation

Complexity in biological computation is one of the recognised means by which biological systems manage to function in a complex chaotic world. The ability to function and solve problems irrespective of scale and relative complexity, including higher-order interactions, is essential to the efficacy of biological systems. However, it has been unclear how the required complexity can be introduced to allow these functions to be realised. Nonlinear local interactions are required to combine into a global stable system. The property of criticality, that is exhibited by many nonlinear physical systems, can be exploited to allow local nonlinear oscillators to interact, resulting in a globally stable system. This concept introduces robustness, as well as, a means to control global stability

Controlled bio-inspired self-organised criticality

Complex biological systems are considered to be controlled using feedback mechanisms. Reduced systems modelling has been effective to describe these mechanisms, but this approach does not sufficiently encompass the required complexity that is needed to understand how localised control in a biological system can provide global stable states. Self-Organised Criticality (SOC) is a characteristic property of locally interacting physical systems, which readily emerges from changes to its dynamic state due to small nonlinear perturbations. These small changes in the local states, or in local interactions, can greatly affect the total system state of critical systems. It has long been conjectured that SOC is cardinal to biological systems, that show similar critical dynamics, and also may exhibit near power-law relations. Rate Control of Chaos (RCC) provides a suitable robust mechanism to generate SOC systems, which operates at the edge of chaos. The bio-inspired RCC method requires only local instantaneous knowledge of some of the variables of the system, and is capable of adapting to local perturbations. Importantly, connected RCC controlled oscillators can maintain global multi-stable states, and domains where power-law relations may emerge. The network of oscillators deterministically stabilises into different orbits for different perturbations, and the relation between the perturbation and amplitude can show exponential and power-law correlations. This can be considered to be representative of a basic mechanism of protein production and control, that underlies complex processes such as homeostasis. Providing feedback from the global state, the total system dynamic behaviour can be boosted or reduced. Controlled SOC can provide much greater understanding of biological control mechanisms, that are based on distributed local producers, with remote consumers of biological resources, and globally defined control

Rapid Microfluidic Preparation of Niosomes for Targeted Drug Delivery

Niosomes are non-ionic surfactant-based vesicles with high promise for drug delivery applications. They can be rapidly prepared via microfluidics, allowing their reproducible production without the need of a subsequent size reduction step, by controlled mixing of two miscible phases of an organic (lipids dissolved in alcohol) and an aqueous solution in a microchannel. The control of niosome properties and the implementation of more complex functions, however, thus far are largely unknown for this method. Here we investigate microfluidics-based manufacturing of topotecan (TPT)-loaded polyethylene glycolated niosomes (PEGNIO). The flow rate ratio of the organic and aqueous phases was varied and optimized. Furthermore, the surface of TPT-loaded PEGNIO was modified with a tumor homing and penetrating peptide (tLyp-1). The designed nanoparticular drug delivery system composed of PEGNIO-TPT-tLyp-1 was fabricated for the first time via microfluidics in this study. The physicochemical properties were determined through dynamic light scattering (DLS) and zeta potential analysis. In vitro studies of the obtained formulations were performed on human glioblastoma (U87) cells. The results clearly indicated that tLyp-1-functionalized TPT-loaded niosomes could significantly improve anti-glioma treatment

Employing QbD strategies to assess the impact of cell viability and density on the primary recovery of monoclonal antibodies

Quality by Design (QbD) is one of the most important tools for the implementation of Process Analytical Technology (PAT) in biopharmaceutical production. For optimal characterization of a monoclonal antibody (mAb) upstream process a stepwise approach was implemented. The upstream was divided into three process stages, namely inoculum expansion, production, and primary recovery, which were investigated individually. This approach enables analysis of process parameters and associated intermediate quality attributes as well as systematic knowledge transfer to subsequent process steps. Following previous research, this study focuses on the primary recovery of the mAb and thereby marks the final step toward a holistic characterization of the upstream process. Based on gained knowledge during the production process evaluation, the cell viability and density were determined as critical parameters for the primary recovery. Directed cell viability adjustment was achieved using cytotoxic camptothecin in a novel protocol. Additionally, the cell separation method was added to the Design of Experiments (DoE) as a qualitative factor and varied between filtration and centrifugation. To assess the quality attributes after cell separation, the bioactivity of the mAb was analyzed using a cell-based assay and the purity of the supernatant was evaluated by measurement of process related impurities (host cell protein proportion, residual DNA). Multivariate data analysis of the compiled data confirmed the hypothesis that the upstream process has no significant influence on the bioactivity of the mAb. Therefore, process control must be tuned towards high mAb titers and purity after the primary recovery, enabling optimal downstream processing of the product. To minimize amounts of host cell proteins and residual DNA the cell viability should be maintained above 85% and the cell density should be controlled around 15 × 106 cells/ml during the cell removal. Thereby, this study shows the importance of QbD for the characterization of the primary recovery of mAbs and highlights the useful implementation of the stepwise approach over subsequent process stages

Harmonic Versus Chaos Controlled Oscillators in Hexapedal Locomotion

The behavioural diversity of chaotic oscillator can be controlled into periodic dynamics and used to model locomotion using central pattern generators. This paper shows how controlled chaotic oscillators may improve the adaptation of the robot locomotion behaviour to terrain uncertainties when compared to nonlinear harmonic oscillators. This is quantitatively assesses by the stability, changes of direction and steadiness of the robotic movements. Our results show that the controlled Wu oscillator promotes the emergence of adaptive locomotion when deterministic sensory feedback is used. They also suggest that the chaotic nature of chaos controlled oscillators increases the expressiveness of pattern generators to explore new locomotion gaits

The spike generation processes: a case for low level computation

Over the last couple of years, it can be said that the focus of the computational aspects of neurons has moved from synaptic weight and firing rate encoding to temporal firing encoding. On the other hand, several elements of these models have been based on some conceptual assumptions that imply relative simple dynamic behaviour of neuronal membrane activity in an active-passive process. In line with recent advances that have produced a better understanding of the biochemical processes that occur within cells, it is proposed that the processes that are involved in a membrane depolarisation cascade are less static than have been assumed so far. In particular, the possibilities of low level computation at the membrane level need to be explored more extensively. In this chapter some computational properties of the spike generation processes are explored using phenomenological models

Live reporting for hypoxia : Hypoxia sensor–modified mesenchymal stem cells as in vitro reporters

Natural oxygen gradients occur in tissues of biological organisms and also in the context of three-dimensional (3D) in vitro cultivation. Oxygen diffusion limitation and metabolic oxygen consumption by embedded cells produce areas of hypoxia in the tissue/matrix. However, reliable systems to detect oxygen gradients and cellular response to hypoxia in 3D cell culture systems are still missing. In this study, we developed a system for visualization of oxygen gradients in 3D using human adipose tissue–derived mesenchymal stem cells (hAD-MSCs) modified to stably express a fluorescent genetically engineered hypoxia sensor HRE-dUnaG. Modified cells retained their stem cell characteristics in terms of proliferation and differentiation capacity. The hypoxia-reporter cells were evaluated by fluorescence microscopy and flow cytometry under variable oxygen levels (2.5%, 5%, and 7.5% O2). We demonstrated that reporter hAD-MSCs output is sensitive to different oxygen levels and displays fast decay kinetics after reoxygenation. Additionally, the reporter cells were encapsulated in bulk hydrogels with a variable cell number, to investigate the sensor response in model 3D cell culture applications. The use of hypoxia-reporting cells based on MSCs represents a valuable tool for approaching the genuine in vivo cellular microenvironment and will allow a better understanding of the regenerative potential of AD-MSCs. © 2020 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals LL