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Biliary tract cancer (BTC) is a rare malignancy with rising incidence. The therapeutic options are limited and the overall survival remains poor. Cyclin-dependent kinases, drivers of cell cycle and transcription have numerous biological functions and are known to be dysregulated in numerous tumor entities. Dinaciclib is a selective Cdk1/2/5/9 inhibitor with anti-tumor activity. In the present study, the efficacy of dinaciclib was tested on a comprehensive BTC cell-line model. The results indicate a heterogeneous expression pattern of Cdk1/2/5/9, as well as various differentiation tumor markers in BTC cells. We demonstrated that dinaciclib reduces cell viability, ATP levels, and proliferation rates. Moreover, dinaciclib induces apoptosis via increased caspase 3/7 activity and reduced expression levels of the anti-apoptotic protein Mcl-1 in a concentration- and cell line -dependent manner. 3D cell culture confirms the cytotoxic impact of dinaciclib under more physiologic tumor conditions. Additionally, dinaciclib affects different cell growth regulators like EGFR and STAT3 on gene and protein level, thus decreasing tumor growth. In summary, our study indicates that dinaciclib acts as a promising anti-tumorigenic agent in 2D and 3D in vitro BTC models and thus encourages further investigation.

IntroductionMulti-channel electrophysiology systems for recording of neuronal activity face significant data throughput limitations, hampering real-time, data-informed experiments. These limitations impact both experimental neurobiology research and next-generation neuroprosthetics.MethodsWe present a novel solution that leverages the high integration density of 22nm fully-depleted silicon-on-insulator technology to address these challenges. The proposed highly integrated programmable System-on-Chip (SoC) comprises 68-channel 0.41 μW/Ch recording frontends, spike detectors, 16-channel 0.87–4.39 μW/Ch action potentials and 8-channel 0.32 μW/Ch local field potential codecs, as well as a multiply-accumulate-assisted power-efficient processor operating at 25 MHz (5.19 μW/MHz). The system supports on-chip training processes for compression, training, and inference for neural spike sorting. The spike sorting achieves an average accuracy of 91.48 or 94.12% depending on the utilized features. The proposed programmable SoC is optimized for reduced area (9 mm2) and power. On-chip processing and compression capabilities free up the data bottlenecks in data transmission (up to 91% space saving ratio), and moreover enable a fully autonomous yet flexible processor-driven operation.DiscussionCombined, these design considerations overcome data-bottlenecks by allowing on-chip feature extraction and subsequent compression.

Power hardware-in-the-loop (PHIL) testing has become indispensable for the rapid, modular, and cost-saving development of automotive components. This article focuses on PHIL tests composed of entire powertrains that exchange speed and torque signals with vehicle simulations. Previous studies pointed out the importance of promptly following the references from the virtual simulation environment to replicate realistic driving conditions and introduced control strategies to cope with the challenges associated with this setup. However, a comprehensive comparison of the different control strategies has not yet been carried out. To fill this gap, the concepts are first investigated in-depth in simulations and are then, rigorously validated on a state-of-the-art powertrain test bed under highly dynamic driving scenarios, including full-braking. Furthermore, an improvement of existing shaft torque control approaches, which are mainly based on feedforward control, is proposed to better compete with the other methods. The proposed extension shows higher resilience to low accuracy of torque actuators, while the other concepts exhibit greater robustness against time delays. The results from the direct comparisons are summarized and allow the appropriate selection of control strategies for specific use cases.

This research presents and examines the first power and speed adaptive 60 GHz receiver, combining the potential of high data rates with low energy consumption. Hence, enabling a range of Tactile Internet applications such as a compact wireless robotic skin. Designed and fabricated in a 22 nm fully depleted silicon-on-insulator (FD-SOI) CMOS process, the required area is only 0.67 mm2. Low energy consumption is achieved by using on-off keying (OOK) and aggressive duty cycling. For data rates up to 25 Mbps, synchronization is achieved by oversampling. In this case, the sampling clock is directly related to the data rate. The duty cycle is generated from the sampling clock and defines the average energy consumption. Consequently, a truly data rate dependent energy consumption can be achieved, which is especially beneficial in low communication load scenarios. At a maximum data rate of 2.8 Gbps, the energy consumption is 15.3 mW, while at 25 kbps the receiver consumes only $\mathrm {1.1~\mu \text {W} }$ . Moreover, the achieved sensitivity is -20.5 dBm at 2.8 Gbps for a bit error rate (BER) below 1E-12 and -25 dBm at 25 kbps respectively.

Acoustic perception of the automotive environment has the potential to advance driving potentials with enhanced safety. The challenge arises when these acoustic perception systems need to perform under resource and power constraints on edge devices. Neuromorphic computing has introduced spiking neural networks in the context of ultra-low power sensory edge devices. Spiking architectures leverage biological plausibility to achieve computational capabilities, accurate performance, and great compatibility with neuromorphic hardware. In this work, we explore the depths of spiking neurons and feature components with the acoustic scene analysis task for siren sounds. This research work aims to address the qualitative analysis of sliding windows’ variation on the feature extraction front of the preprocessing pipeline. Optimization of the parameters to exploit the feature extraction stage facilitates the advancement of the performance of the acoustics anomaly detection task. We exploit the parameters for mel spectrogram features and FFT calculations, prone to be suitable for computations in hardware. We conduct experiments with different window sizes and the overlapping ratio within the windows. We present our results for performance measures like accuracy and onset latency to provide an insight on the choice of optimal window. The non-trivial motivation of this research is to understand the effect of encoding behavior of spiking neurons with different windows. We further investigate the heterogeneous nature of membrane and synaptic time constants and their impact on the accuracy of anomaly detection. On a large scale audio dataset comprising of siren sounds and road traffic noises, we obtain accurate predictions of siren sounds using a recurrent spiking neural network. The baseline dataset comprising siren and noise sequences is enriched with a bird dataset to evaluate the model with unseen samples.

IntroductionBiliary tract cancer (BTC) is a lethal disease with a bad overall survivability, partly arising from inadequate therapeutic alternatives, detection at a belated stage, and a resistance to common therapeutic approaches. Ferroptosis is a form of programmed cell death that depends on reactive oxygen species (ROS) and iron, causing excessive peroxidation of polyunsaturated fatty acids (PUFAs). Therefore, the objective of this investigation is, whether ferroptosis can be induced in BTC in vitro and whether this induction is dependent on specific molecular markers.MethodsThe study conducted resazurin assay and IC25/50 calculation to explore the possible cytotoxic outcomes of different classes of ferroptosis-inducing substances (FINs) on a comprehensive in vitro model of 11 BTC cell lines. Combinatory treatments with different cell death inhibitors were performed to evaluate the magnitude of ferroptosis induction. To ascertain whether ferroptotic cell death occurred, liperfluo and iron assay kits were employed to evaluate lipid ROS and intracellular iron abundance. Potential biomarkers of ferroptosis sensitivity were then assessed via western blot analysis, a rtPCR panel and functional assay kits.ResultsThe study found that different FINs reduced cell viability in a cell line-dependent manner. In addition, we measured increased lipid ROS and intracellular Fe2+ levels upon exposure to FINs in BTC cells. Combining FINs with inhibitors of ferroptosis, necroptosis or apoptosis suggests the occurrence of ferroptotic events in BTC cell lines CCC-5, HuH-28 and KKU-055. Furthermore, we found that BTC cells display a heterogeneous profile regarding different molecular genes/markers of ferroptosis. Subsequent analysis revealed that sensitivity of BTC cells towards IKE and RSL3 positively correlated with CD71 and SLC7A11 protein expression.ConclusionOur results demonstrate that induction of ferroptosis is a promising approach to inhibit BTC cell growth and that the sensitivity of BTC cells towards ferroptosis induction might be dependent on molecular markers such as CD71 and SLC7A11.

The microRNA-200 family has wide-ranging regulatory functions in cancer development and progression. Above all, it is strongly associated with the epithelial-to-mesenchymal transition (EMT), a process during which cells change their epithelial to a mesenchymal phenotype and acquire invasive characteristics. More recently, miR-200 family members have also been reported to impact the immune evasion of cancer cells by regulating the expression of immunoinhibitory immune checkpoints (ICs) like PD-L1. Therefore, we aimed to comprehensively characterize this miR-200 family as a regulatory interface between EMT and immune evasion mechanisms in biliary tract cancer. Initial correlation analyses and transient overexpression experiments using miRNA mimics suggested miR-200c-3p as a putative regulator of ICs including PD-L1, LGALS9, and IDO1. However, these effects could not be confirmed in stable miR-200c-3p overexpression cell lines, nor in cells transiently transfected with miR-200c-3p mimic from an independent manufacturer. By shifting our efforts towards dissecting the mechanisms leading to these disparate effects, we observed that the initially used miR-200c-3p mimic triggered a double-stranded (ds)RNA-dependent antiviral response. Besides upregulating the ICs, this had substantial cellular consequences including an induction of interferon type I and type III expression, increased levels of intracellular dsRNA sensors, and a significantly altered cellular growth and apoptotic activity.Our study highlights the capability of miRNA mimics to non-specifically induce a dsRNA-mediated antiviral interferon response. Consequently, phenotypic alterations crucially distort physiological miRNA functions and might result in a major misinterpretation of previous and future miRNA studies, especially in the context of IC regulation.

Biliary tract cancer is a deadly disease with limited therapeutic options. Ouabain is a well-known inhibitor of the pumping function of Na+/K+-ATPase, though there is evidence that low concentrations of ouabain lead to a reduction of cell viability of cancer cells independent of its inhibition of the pumping function of the Na+/K+-ATPase. Regarding the impact of ouabain on biliary tract cancer, no data is currently available. Therefore, we aimed for a first-time investigation of ouabain as a potential anti-neoplastic biliary tract cancer agent using comprehensive human biliary tract cancer in vitro models. We found that ouabain has a strong cell line-dependent cytotoxic effect with IC50 levels in the (low) nanomolar-range and that this effect was not associated with the mRNA expression levels of the Na+/K+-ATPase α, β and fxyd-subunits. Regarding the mode of cytotoxicity, we observed induction of apoptosis in biliary tract cancer cells upon treatment with ouabain. Interestingly, cytotoxic effects of ouabain at sub-saturating (< μM) levels were independent of cellular membrane depolarization and changes in intracellular sodium levels. Furthermore, using a 3D cell culture model, we found that ouabain disturbs spheroid growth and reduces the viability of biliary tract cancer cells within the tumor spheroids. In summary, our data suggest that ouabain possesses anti-biliary tract cancer potential at low μM-concentration in 2D and 3D in vitro biliary tract cancer models and encourage further detailed investigation.

Background and study aims Endoscopic optical diagnosis is crucial to the therapeutic strategy for early gastrointestinal cancer. It accurately (> 85 %) predicts pT category based on microsurface (SP) and vascular patterns (VP). However, interobserver variability is a major problem. We have visualized and digitalized the graded irregularities based on bioinformatically enhanced quantitative endoscopic image analysis (BEE) of high-definition white-light images. Methods In a pilot study of 26 large colorectal lesions (LCLs, mean diameter 39 mm), we retrospectively compared BEE variables with corresponding histopathology of the resected LCLs. Results We included 10 adenomas with low-grade intraepithelial neoplasia (LGIN), nine with high-grade intraepithelial neoplasia (HGIN) and early adenocarcinoma (EAC), and seven deeply submucosal invasive carcinomas. Quantified density (d) and nonuniformity (CU) of vascular and surface structures correlated with histology (rs d VP: –0.77, rs CU VP: 0.13, rs d SP: –0.76, and rs CU SP: 0.45, respectively). A computed BEE score showed a sensitivity and specificity of 90 % and 100 % in the group with LGINs, 89 % and 41 % in the group with HGINs and EACs, and 100 % and 95 % in the group with deeply invasive carcinoma, respectively. Conclusions In this pilot study, BEE showed promise as a tool for endoscopic characterization of LCLs during routine endoscopy. Prospective clinical studies are needed.

Hardware-in-the-Loop tests have become a key factor in decreasing development time of various drive systems. In this context, high performance test beds, where feedback control plays a major role, are necessary to meet the demanding requirements such as real driving emissions in the automotive industry. Particularly for combustion engine test beds, periodic combustion strokes cause large oscillations in different measurement signals on engine test beds, which causes severe problems since conventional controllers try to compensate for these periodic disturbances. The control settings are a trade-off between fast reference tracking and undesirably strong disturbance rejection, which may compromise test results. An ordinary two-degree-of-freedom (2-DOF) control with flatness-based feedforward control produces relief in separating reference and disturbance behavior but cannot handle input constraints. Thus, a model predictive feedforward controller (MPFFC) in combination with the 2-DOF strategy is introduced for high-dynamic speed control in this contribution. The MPFFC generates optimal input and output trajectories, which respect constraints of the system. Fast reference tracking is achieved without the risk of falsification by high feedback. Comparisons between the proposed method, a simple feedback and a standard 2-DOF controller with a conventional flatness-based feedforward control are performed on a state-of-the-art 4-cylinder engine test bed. The experiments constitute a rare implementation of a MPFFC on a real system and demonstrate its capabilities of separating reference and disturbance response as well as taking advantage of certain situations to even further improve reference tracking speed.

The trend towards ubiquitous electronics drives the development of autonomous hardware components with longer operating times. This work presents a novel ultra-low power analog sensor frontend (AFE) for environmental sensing applications. Relevant operation parameters like resolution (6 to 13 bit), sample rate (1 to 7.5 kS/s), voltage gain (−6 to 12 dB), transimpedance (1.5 to 12 M $ \boldsymbol {\Omega }$ ), and moving average (1 to 128 taps) are real-time programmable. Four input channels are separately configurable to process voltage, current and potentiometric signals of external or internal sources. The flexible channel-wise configuration enables processing of various signal types and therefore offers a versatile solution for sensors from the Internet-of-Things (IoT) market segment. The AFE integrates switched-capacitor amplifiers, 13 bit, 10 kS/s successive approximation analog-to-digital converter (SAR ADC), bias references, oscillator, digital signal pre-processing and communication in a system-on-chip. A novel sensor power regime supports the flexible read-out of commercial IoT sensors, resulting in excellent power consumption. Fabricated samples in 180nm technology show an ultra-low power consumption of $8.8\,\mu \text{W}$ . The SAR ADC achieves 10.6 effective bits while consuming $1.8\,\mu \text{W}$ , resulting in a Figure-of-Merit of 116.0 fJ/conv.-step. Measurements with commercial sensors prove the AFE’s suitability for an energy-harvester-powered IoT environmental sensor node.

Frequency-modulated continuous wave radar sensors play an essential role for assisted and autonomous driving as they are robust under all weather and light conditions. However, the rising number of transmitters and receivers for obtaining a higher angular resolution increases the cost for digital signal processing. One promising approach for energy-efficient signal processing is the usage of brain-inspired spiking neural networks (SNNs) implemented on neuromorphic hardware. In this article we perform a step-by-step analysis of automotive radar processing and argue how spiking neural networks could replace or complement the conventional processing. We provide SNN examples for two processing steps and evaluate their accuracy and computational efficiency. For radar target detection, an SNN with temporal coding is competitive to the conventional approach at a low compute overhead. Instead, our SNN for target classification achieves an accuracy close to a reference artificial neural network while requiring 200 times less operations. Finally, we discuss the specific requirements and challenges for SNN-based radar processing on neuromorphic hardware. This study proves the general applicability of SNNs for automotive radar processing and sustains the prospect of energy-efficient realizations in automated vehicles.

Summary: Neuromorphic systems take inspiration from the principles of biological information processing to form hardware platforms that enable the large-scale implementation of neural networks. The recent years have seen both advances in the theoretical aspects of spiking neural networks for their use in classification and control tasks and a progress in electrophysiological methods that is pushing the frontiers of intelligent neural interfacing and signal processing technologies. At the forefront of these new technologies, artificial and biological neural networks are tightly coupled, offering a novel “biohybrid” experimental framework for engineers and neurophysiologists. Indeed, biohybrid systems can constitute a new class of neuroprostheses opening important perspectives in the treatment of neurological disorders. Moreover, the use of biologically plausible learning rules allows forming an overall fault-tolerant system of co-developing subsystems. To identify opportunities and challenges in neuromorphic biohybrid systems, we discuss the field from the perspectives of neurobiology, computational neuroscience, and neuromorphic engineering.

Cellular migration is essential in diverse physiological and pathophysiological processes. Here, we present a protocol for quantitative analysis of migration using confluence detection allowing continuous, non-endpoint measurement with minimal hands-on time under cell incubator conditions. Applicability was tested using substances which enhance (EGF) or inhibit (cytochalasin D, ouabain) migration. Using a gap-closure assay we demonstrate that automated confluence detection monitors cellular migration in the 96-well microplate format. Quantification by % confluence, % cell free-area or % confluence in cell-free area against time, allows detailed analysis of cellular migration. The study describes a practicable approach for continuous, non-endpoint measurement of migration in 96-well microplates and for detailed data analysis, which allows for medium/high-throughput analysis of cellular migration in vitro.

Background/Aims: The neutral, non-essential amino acid glycine has manifold functions and effects under physiological and pathophysiological conditions. Besides its function as a neurotransmitter in the central nervous system, glycine also exerts immunomodulatory effects and as an osmolyte it participates in cell volume regulation. During phagocytosis, glycine contributes to (local) cell volume-dependent processes like lamellipodium formation. Similar to the expansion of the lamellipodium we assume that glycine also affects the migration of microglial cells in a cell volume-dependent manner. Methods: Mean cell volume (MCV) and cell migration were determined using flow cytometry and trans-well migration assays, respectively. Electrophysiological recordings of the cell membrane potential (Vmem) and swelling-dependent chloride (Cl-) currents (IClswell, VSOR, VRAC) were performed using the whole-cell patch clamp technique. Results: In the murine microglial cell line BV-2, flow cytometry analysis revealed that glycine (5 mM) increases the MCV by ∼9%. The glycine-dependent increase in MCV was suppressed by the partial sodium-dependent neutral amino acid transporter (SNAT) antagonist MeAIB and augmented by the Cl- current blocker DCPIB. Electrophysiological recordings showed that addition of glycine activates a Cl- current under isotonic conditions resembling features of the swelling-activated Cl- current (IClswell). The cell membrane potential (Vmem) displayed a distinctive time course after glycine application; initially, glycine evoked a rapid depolarization mediated by Na+-coupled glycine uptake via SNAT, followed by a further gradual depolarization, which was fully suppressed by DCPIB. Interestingly, glycine significantly increased migration of BV-2 cells, which was suppressed by MeAIB, suggesting that SNAT is involved in the migration process of microglial cells. Conclusion: We conclude that glycine acts as a chemoattractant for microglial cells presumably by a cell volume-dependent mechanism involving SNAT-mediated cell swelling.

Background/Aims: For in vitro cytotoxicity testing, discrimination of apoptosis and necrosis represents valuable information. Viability analysis performed at two different time points post treatment could serve such a purpose because the dynamics of metabolic activity of apoptotic and necrotic cells is different, i.e. a more rapid decline of cellular metabolism during necrosis whereas cellular metabolism is maintained during the entire execution phase of apoptosis. This study describes a straightforward approach to distinguish apoptosis and necrosis. Methods: A431 human epidermoid carcinoma cells were treated with different concentrations/doses of actinomycin D (Act-D), 4,5,6,7-tetrabromo-2-azabenzimidazole (TBB), Ro 31-8220, H2O2 and photodynamic treatment (PDT). The resazurin viability signal was recorded at 2 and 24 hrs post treatment. Apoptosis and necrosis were verified by measuring caspase 3/7 and membrane integrity. Results: Calculation of the difference curve between the 2 and 24 hrs resazurin signals yields the following information: a positive difference signal indicates apoptosis (i.e. high metabolic activity at early time points and low signal at 24 hrs post treatment) while an early reduction of the viability signal indicates necrosis. For all treatments, this dose-dependent sequence of cellular responses could be confirmed by independent assays. Conclusion: Simple and cost-effective viability analysis provides reliable information about the dose ranges of a cytotoxic agent where apoptosis or necrosis occurs. This may serve as a starting point for further in-depth characterisation of cytotoxic treatments.

Endoscopic submucosal dissection (ESD) is an effective treatment of early esophageal adenocarcinomas (EACs). The decision of ESD over esophagectomy is based on clinical evaluation of tumor depth and invasion. On a molecular level, tumor invasion is strongly associated with epithelial-to-mesenchymal transition (EMT). Here, we investigated whether localized ESD-resected and surgically resected EAC samples displayed different expression profiles of EMT protein and microRNA markers and whether these different expression profiles were able to retrospectively discriminate localized and surgically resected samples. By doing this, we aimed to evaluate whether preoperative measurement of EMT marker expression might support the decision regarding ESD over surgery. The results showed that ESD-resected samples displayed an epithelial expression profile, i.e., high expression of epithelial protein markers, whereas surgically resected samples displayed high expression of mesenchymal markers. In addition, the anti-EMT microRNA-205 was significantly more expressed in ESD-resected samples, whereas we found no significant differences in the expression levels of microRNA-200 family members. Furthermore, in our retrospective approach, we have demonstrated that measurement of selected EMT markers and microRNA-205 has significant discrimination power to distinguish ESD-resected and surgically resected samples. We suggest that the assessment of EMT status of EAC samples on a molecular level may support clinical evaluation regarding the applicability of ESD.

First-stage feature computation and data rate reduction play a crucial role in an efficient visual information processing system. Hardware-based first stages usually win out where power consumption, dynamic range, and speed are the issue, but have severe limitations with regard to flexibility. In this paper, the local orientation coding (LOC), a nearest neighborhood grayscale operator, is investigated and enhanced for hardware implementation. The features produced by this operator are easy and fast to compute, compress the salient information contained in an image, and lend themselves naturally to various medium-to-high-level postprocessing methods such as texture segmentation, image decomposition, and feature tracking. An image sensor architecture based on the LOC has been elaborated, that combines high dynamic range (HDR) image aquisition, feature computation, and inherent pixel-level ADC in the pixel cells. The mixed-signal design allows for simple readout as digital memory.