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This study investigates the effect of spatial release from masking (SRM) in bilateral bone conduction (BC) stimulation at the mastoid. Nine adults with normal hearing were tested to determine SRM based on speech recognition thresholds (SRTs) in simulated spatial configurations ranging from 0 to 180 degrees. These configurations were based on nonindividualized head-related transfer functions. The participants were subjected to sound stimulation through either air conduction (AC) via headphones or BC. The results indicated that both the angular separation between the target and the masker, and the modality of sound stimulation, significantly influenced speech recognition performance. As the angular separation between the target and the masker increased up to 150 degrees, both BC and AC SRTs decreased, indicating improved performance. However, performance slightly deteriorated when the angular separation exceeded 150 degrees. For spatial separations less than 75 degrees, BC stimulation provided greater spatial benefits than AC, although this difference was not statistically significant. For separations greater than 75 degrees, AC stimulation offered significantly more spatial benefits than BC. When speech and noise originated from the same side of the head, the "better ear effect" did not significantly contribute to SRM. However, when speech and noise were located on opposite sides of the head, this effect became dominant in SRM., Funding Agencies|Overseas Experts Initiative of Department of Technology and Science of Guangdong Province

Circular Economy concept (CE) revolves aims enhancing resource efficiency through product lifecycle in technical or biological cycles. The former aims to enhance resource efficiency through waste reduction, recycling, reuse, reducing material consumption, and so on. While in the latter, biodegradable materials are returned to earth through processes like composting. There is a lack of comprehensive theorization of CE concept, when focus is supply chain management/value regeneration at technical cycle. Such a lack and consequently a generic understanding can hinder realizing the full potential of CE. This research aims to propose a theorization of CE in the technical cycle through a supply chain management lens. To this end, the systems engineering approach and life cycle assessment (LCA) are integrated to analyse and theorize the circular supply chain/value regeneration. This paper proposed the novel perspective of supply chain as a system of systems (SoS), which allows identifying the enablers, players, and interactions that influence the realization of CE by implementing its known R-strategies. This paper suggested modification of the existing functional unit definition in LCA method such that the proposed definition takes into account the dynamic/evolving boundary of a supply chain when integrating the R-strategies. Moreover, this paper proposed the 'CE system context' for the supply chain SoS. The proposed structured approach allows the development of the Supply chain SoS within its CE context (Supply Chain SoS-CE context). Certain measures are introduced to assess the effectiveness of integrating R-strategies assuring they contribute to CE realization while network theory concepts are used to assess the criticality of various players in Supply Chain SoS-CE context. A roadmap for development of 'Supply Chain SoS-CE context' is introduced in the light of Industry 4.0.

In order to better understand the brain and brain diseases, in vitro human brain models need to include not only a chemically and physically relevant microenvironment, but also structural network complexity. This complexity reflects the hierarchical architecture in brain tissue. Here, a method has been developed that adds complexity to a 3D cell culture by means of nanogrooved substrates. SH-SY5Y cells were grown on these nanogrooved substrates and covered with Matrigel, a hydrogel. To quantitatively analyze network behavior in 2D neuronal cell cultures, we previously developed an automated image-based screening method. We first investigated if this method was applicable to 3D primary rat brain cortical (CTX) cell cultures. Since the method was successfully applied to these pilot data, a proof of principle in a reductionist human brain cell model was attempted, using the SH-SY5Y cell line. The results showed that these cells also create an aligned network in the 3D microenvironment by maintaining a certain degree of guidance by the nanogrooved topography in the z-direction. These results indicate that nanogrooves enhance the structural complexity of 3D neuronal cell cultures for both CTX and human SH-SY5Y cultures, providing a basis for further development of an easy access brain-on-chip model.

In this work, nanogroove dimensions as a design input parameter for neuronal differentiation and neurite outgrowth in brain-on-a-chip (BOC) applications are investigated. Soft lithography in polydimethylsiloxane (PDMS) is used extensively in organ-on-a-chip applications to create environments for in vitro models. As such, here it is used to fabricate cell culture substrates with nanogrooved patterns. Using a newly developed analysis method, the effect of the nanogrooved, biomimetic PDMS substrates is compared with lateral and height variations within the nanometer range as measured by means of atomic force microscopy (AFM). PDMS culture substrates were replicated from a cyclic olefin copolymer template, which was fabricated either directly by thermal nanoimprinting from a jet and flash imprint lithography (J-FIL) resist pattern (process I) on a polished silicon wafer or via an intermediate reactive ion etched all-silicon mold (process II) that was fabricated by using the J-FIL resist pattern as in process I as a mask. To study the interplay between the lateral and height dimensions of nanogrooves on the differentiation process of SH-SY5Y cells, which are a well-established model for neuronal cells that form networks in culture, the authors first characterized the feature sizes of the PDMS substrates received from both processes by AFM. On average, nanogrooved patterns from process I had a 1.8 ± 1.1% decrease in pattern period, a 15.5 ± 12.2% increase in ridge width compared to the designed dimensions, and a height of 95.3 ± 10.6 nm. Nanogrooved patterns for process II had a 1.7 ± 1.7% decrease in pattern period, a 43.1 ± 33.2% increase in ridge width, and a height of 118.8 ± 13.6 nm. Subsequently, they demonstrated that neurite outgrowth alignment was particularly strong if the pattern period was 600 nm or 1000 nm with the additional constraint for these patterns that the ridge width is <0.4 times the pattern period. Increasing pattern height increased the fra

Research on neuronal differentiation and neuronal network guidance induced through nanotopographical cues generates large datasets, and therefore the analysis of such data can be aided by automatable, unbiased image screening tools. To link such tools, we present an image-based screening method to evaluate the influence of nanogroove pattern dimensions on neuronal differentiation. This new method consists of combining neuronal feature detection software, here HCA-Vision, and a Frangi vesselness algorithm to calculate neurite alignment values and quantify morphological aspects of neurons, which are measured via neurite length, neuronal polarity, and neurite branching, for differentiated SH-SY5Y cells cultured on nanogrooved polydimethylsiloxane (PDMS) patterns in the 200–2000 nm range. The applicability of this method is confirmed by our results, which find that the level of alignment is dependent on nanogroove dimensions. Furthermore, the screening method reveals that differentiation and alignment are correlated. In particular, patterns with groove widths >200 nm and with a low ridge width to pattern period ratio have a quantifiable influence on alignment, neurite length, and polarity. In summary, the novel combination of software that forms a base for this statistical analysis method demonstrates good potential for evaluating tissue microarchitecture, which depends on subtle design variation in substrate topography. Using the screening method, we obtained automated and sensitive quantified readouts from large datasets.

In order to investigate the hypothesis that dynamic nanoscale stimuli can influence the functional response of the brain, in this paper we describe the development of a membrane actuator chip based on polydimethylsiloxane (PDMS) soft lithography. The chip exerts a local nanoscale mechanical load on an in vitro neuronal cell network by microfluidic pneumatic deformation of the membrane. The deformation provides a topographical change in the substrate as an input stimulus for the study of response functions of a neuronal cell network in vitro. Calcium ions (Ca2+) imaging within a neuronal cell network grown from dissociated cortical cells of the rat's brain used as a brain model indicates that a neural networks response can be provoked by means of our new method. This actuator chip provides a relatively mild and localised mechanical stimulus by means of a 2% elongation of the membrane's width during the application of a pressure pulse underneath the membrane using a microfluidic channel design. We found an average 50% increase of the intracellular Ca2+ flux activity for 2D neuronal cell networks among 4 independent samples cultured on flat membranes. Additionally, we have proven the applicability of the actuator chip for networks on nanogrooved membranes by the observation of Ca2+ traces and we also observed the Ca2+ waves response upon stimulation in a three dimensional (3D) in vivo-like neuronal cell network using Matrigel on flat membranes. Hence, the chip potentially provides a novel technology platform for the in vitro modelling of brain tissues with topographically and 3D hydrogel-defined network architectures.