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The magnetic excitation spectrum of AgCrS2, a layered multiferroic compound with a collinear four-sublattice antiferromagnetic order, has been investigated by means of time-of-flight inelastic neutron scattering between 5 and 300 K. Coupling mean-field and spin-wave calculations, the experimental spectrum is well reproduced introducing, in the model Hamiltonian, a ferromagnetic exchange interaction between nearest neighbors and a non-negligible antiferromagnetic in-plane next-nearest-neighbor interaction. This study shows that the sign of the magnetic interaction between chromium ions depends on the Cr-Cr distance with a threshold value above which it becomes ferromagnetic and emphasizes the role of the magnetoelastic coupling in the understanding of the physical properties of AgCrS2. [ABSTRACT FROM AUTHOR]

Objective. Micro-electrocorticographic ( μ ECoG) arrays are able to record neural activities from the cortical surface, without the need to penetrate the brain parenchyma. Owing in part to small electrode sizes, previous studies have demonstrated that single-unit spikes could be detected from the cortical surface, and likely from Layer I neurons of the neocortex. Here we tested the ability to use μ ECoG arrays to decode, in rats, body position during open field navigation, through isolated single-unit activities. Approach. μ ECoG arrays were chronically implanted onto primary motor cortex (M1) of Wistar rats, and neural recording was performed in awake, behaving rats in an open-field enclosure. The signals were band-pass filtered between 300-3000 Hz. Threshold-crossing spikes were identified and sorted into distinct units based on defined criteria including waveform morphology and refractory period. Body positions were derived from video recordings. We used gradient-boosting machine to predict body position based on previous 100 ms of spike data, and correlation analyses to elucidate the relationship between position and spike patterns. Main results. Single-unit spikes could be extracted during chronic recording from μ ECoG, and spatial position could be decoded from these spikes with a mean absolute error of prediction of 0.135 and 0.090 in the x- and y- dimensions (of a normalized range from 0 to 1), and Pearson's r of 0.607 and 0.571, respectively. Significance. μ ECoG can detect single-unit activities that likely arise from superficial neurons in the cortex and is a promising alternative to intracortical arrays, with the added benefit of scalability to cover large cortical surface with minimal incremental risks. More studies should be performed in human related to its use as brain-machine interface., (Creative Commons Attribution license.)

There is increasing demand for direct in situ metabolite monitoring from cell cultures and in vivo using implantable devices. Electrochemical biosensors are commonly preferred due to their low-cost, high sensitivity, and low complexity. Metabolite detection, however, in cultured cells or sensitive tissue is rarely shown. Commonly, glucose sensing occurs indirectly by measuring the concentration of hydrogen peroxide, which is a by-product of the conversion of glucose by glucose oxidase. However, continuous production of hydrogen peroxide in cell media with high glucose is toxic to adjacent cells or tissue. This challenge is overcome through a novel, stacked enzyme configuration. A primary enzyme is used to provide analyte sensitivity, along with a secondary enzyme which converts H 2 O 2 back to O 2 . The secondary enzyme is functionalized as the outermost layer of the device. Thus, production of H 2 O 2 remains local to the sensor and its concentration in the extracellular environment does not increase. This "biostack" is integrated with organic electrochemical transistors to demonstrate sensors that monitor glucose concentration in cell cultures in situ. The "biostack" renders the sensors nontoxic for cells and provides highly sensitive and stable detection of metabolites., (© 2021 The Authors. Advanced Science published by Wiley-VCH GmbH.)

Future drug discovery and toxicology testing could benefit significantly from more predictive and multi-parametric readouts from in vitro models. Despite the recent advances in the field of microfluidics, and more recently organ-on-a-chip technology, there is still a high demand for real-time monitoring systems that can be readily embedded with microfluidics. In addition, multi-parametric monitoring is essential to improve the predictive quality of the data used to inform clinical studies that follow. Here we present a microfluidic platform integrated with in-line electronic sensors based on the organic electrochemical transistor. Our goals are two-fold, first to generate a platform to host cells in a more physiologically relevant environment (using physiologically relevant fluid shear stress (FSS)) and second to show efficient integration of multiple different methods for assessing cell morphology, differentiation, and integrity. These include optical imaging, impedance monitoring, metabolite sensing, and a wound-healing assay. We illustrate the versatility of this multi-parametric monitoring in giving us increased confidence to validate the improved differentiation of cells toward a physiological profile under FSS, thus yielding more accurate data when used to assess the effect of drugs or toxins. Overall, this platform will enable high-content screening for in vitro drug discovery and toxicology testing and bridges the existing gap in the integration of in-line sensors in microfluidic devices., Competing Interests: The authors declare no conflict of interest.

A biosensing platform based on an organic transistor circuit for metabolite detection in highly complex biological media is introduced. The sensor circuit provides inherent background subtraction allowing for highly specific, sensitive lactate detection in tumor cell cultures. The proposed sensing platform paves the way toward rapid, label-free, and cost-effective clinically relevant in vitro diagnostic tools., (© 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

Organic electrochemical transistors (OECTs) are receiving a great deal of attention as amplifying transducers for electrophysiology. A key limitation of this type of transistors, however, lies in the fact that their output is a current, while most electrophysiology equipment requires a voltage input. A simple circuit is built and modeled that uses a drain resistor to produce a voltage output. It is shown that operating the OECT in the saturation regime provides increased sensitivity while maintaining a linear signal transduction. It is demonstrated that this circuit provides high quality recordings of the human heart using readily available electrophysiology equipment, paving the way for the use of OECTs in the clinic.

A compact multianalyte biosensing platform is reported, composed of an organic electrochemical transistor (OECT) microarray integrated with a pumpless "finger-powered" microfluidic, for quantitative screening of glucose, lactate, and cholesterol levels. A biofunctionalization method is designed, which provides selectivity towards specific metabolites as well as minimization of any background interference. In addition, a simple method is developed to facilitate multi-analyte sensing and avoid electrical crosstalk between the different transistors by electrically isolating the individual devices. The resulting biosensing platform, verified using human samples, offers the possibility to be used in easy-to-obtain biofluids with low abundance metabolites, such as saliva. Based on our proposed method, other types of enzymatic biosensors can be integrated into the array to achieve multiplexed, noninvasive, personalized point-of-care diagnostics., (© 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)