We report the synthesis of Fe₃O₄/graphene (Fe₃O₄/Gr) nanocomposite for highly selective and highly sensitive peroxide sensor application. The nanocomposites were produced by a modified co-precipitation method. Further, structural, chemical, and morphological characterization of the Fe₃O₄/Gr was investigated by standard characterization techniques, such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscope (TEM) and high-resolution TEM (HRTEM), Fourier transform infrared (FTIR), and X-ray photoelectron spectroscopy (XPS). The average crystal size of Fe₃O₄ nanoparticles was calculated as 14.5 nm. Moreover, nanocomposite (Fe₃O₄/Gr) was employed to fabricate the flexible electrode using polymeric carbon fiber cloth or carbon cloth (pCFC or CC) as support. The electrochemical performance of as-fabricated Fe₃O₄/Gr/CC was evaluated toward H₂O₂ with excellent electrocatalytic activity. It was found that Fe₃O₄/Gr/CC-based electrodes show a good linear range, high sensitivity, and a low detection limit for H₂O₂ detection. The linear range for the optimized sensor was found to be in the range of 10–110 μM and limit of detection was calculated as 4.79 μM with a sensitivity of 0.037 µA μM⁻¹ cm⁻². The cost-effective materials used in this work as compared to noble metals provide satisfactory results. As well as showing high stability, the proposed biosensor is also highly reproducible.

Objective . Our goal is to develop an interface that integrates chronic monitoring of lower urinary tract (LUT) activity with stimulation of peripheral pathways. Approach . Penetrating microelectrodes were implanted in sacral dorsal root ganglia (DRG) of adult male felines. Peripheral electrodes were placed on or in the pudendal nerve, bladder neck and near the external urethral sphincter. Supra-pubic bladder catheters were implanted for saline infusion and pressure monitoring. Electrode and catheter leads were enclosed in an external housing on the back. Neural signals from microelectrodes and bladder pressure of sedated or awake-behaving felines were recorded under various test conditions in weekly sessions. Electrodes were also stimulated to drive activity. Main results . LUT single- and multi-unit activity was recorded for 4–11 weeks in four felines. As many as 18 unique bladder pressure single-units were identified in each experiment. Some channels consistently recorded bladder afferent activity for up to 41 d, and we tracked individual single-units for up to 23 d continuously. Distension-evoked and stimulation-driven (DRG and pudendal) bladder emptying was observed, during which LUT sensory activity was recorded. Significance . This chronic implant animal model allows for behavioral studies of LUT neurophysiology and will allow for continued development of a closed-loop neuroprosthesis for bladder control.

Interpreting machine learning models is facilitated by the widely employed locally interpretable model-agnostic explanation (LIME) technique. However, when extending LIME to signal data, its credibility falters due to perturbation techniques used to generate local datasets. These techniques disrupt temporal dependencies among features, leading to unrealistic data points and potentially misleading explanations. Additionally, LIME faces instability and local fidelity issues, limiting its suitability for real-world applications. The absence of a dedicated LIME package tailored for interpreting signal data further diminishes comprehensibility, especially when applied to models trained on such data. In this paper, we introduce Signal-based LIME (Sig-LIME) to address these limitations. Sig-LIME leverages a novel data generation technique that captures temporal dependence among features, enhancing credibility and stability. It combines a random forest model and heatmaps to provide illuminating explanations for predictions drawn from electrocardiogram (ECG) signals, improving model transparency. Empirical findings underscore the enhanced interpretability and comprehension of model predictions attained by Sig-LIME compared to baseline LIME. Our quantitative evaluation based on an analysis of variance (ANOVA) framework, reveals a notable improvement in stability with Sig-LIME, evidenced by an f-statistic of 0.0 and p-values of 1, indicating a complete absence of variation between multiple runs. Regarding local fidelity, Sig-LIME surpasses the baseline LIME, exhibiting a lower average Euclidean distance of 0.49 compared to 17.24. Sig-LIME excels in generating data more akin to the original, achieving remarkable stability and significantly enhancing credibility and local fidelity in the explanations it generates.

The role of the kidney in glucose homeostasis has gained global interest. Kidneys are innervated by renal nerves, and renal denervation animal models have shown improved glucose regulation. We hypothesized that stimulation of renal nerves at kilohertz frequencies, which can block propagation of action potentials, would increase urine glucose excretion. Conversely, we hypothesized that low frequency stimulation, which has been shown to increase renal nerve activity, would decrease urine glucose excretion. We performed non-survival experiments on male rats under thiobutabarbital anesthesia. A cuff electrode was placed around the left renal artery, encircling the renal nerves. Ureters were cannulated bilaterally to obtain urine samples from each kidney independently for comparison. Renal nerves were stimulated at kilohertz frequencies (1–50 kHz) or low frequencies (2–5 Hz), with intravenous administration of a glucose bolus shortly into the 25–40-min stimulation period. Urine samples were collected at 5–10-min intervals, and colorimetric assays were used to quantify glucose excretion and concentration between stimulated and non-stimulated kidneys. A Kruskal-Wallis test was performed across all stimulation frequencies (α = 0.05), followed by a post-hoc Wilcoxon rank sum test with Bonferroni correction (α = 0.005). For kilohertz frequency trials, the stimulated kidney yielded a higher average total urine glucose excretion at 33 kHz (+ 24.5%; n = 9) than 1 kHz (− 5.9%; n = 6) and 50 kHz (+ 2.3%; n = 14). In low frequency stimulation trials, 5 Hz stimulation led to a lower average total urine glucose excretion (− 40.4%; n = 6) than 2 Hz (− 27.2%; n = 5). The average total urine glucose excretion between 33 kHz and 5 Hz was statistically significant (p < 0.005). Similar outcomes were observed for urine flow rate, which may suggest an associated response. No trends or statistical significance were observed for urine glucose concentrations. To our knowledge, this is the first study to investigate electrical stimulation of renal nerves to modulate urine glucose excretion. Our experimental results show that stimulation of renal nerves may modulate urine glucose excretion, however, this response may be associated with urine flow rate. Future work is needed to examine the underlying mechanisms and identify approaches for enhancing regulation of glucose excretion.

The measurement of glucose concentration is a fundamental daily care for diabetes patients, and therefore, its detection with accuracy is of prime importance in the field of health care. In this study, the fabrication of an electrochemical sensor for glucose sensing was successfully designed. The electrode material was fabricated using polyaniline and systematically characterized using scanning electron microscopy, high-resolution transmission electron microscopy, X-ray diffraction, Fourier transform infrared spectroscopy, and UV-visible spectroscopy. The polyaniline nanofiber-modified electrode showed excellent detection ability for glucose with a linear range of 10 μM to 1 mM and a detection limit of 10.6 μM. The stability of the same electrode was tested for 7 days. The electrode shows high sensitivity for glucose detection in the presence of interferences. The polyaniline-modified electrode does not affect the presence of interferences and has a low detection limit. It is also cost-effective and does not require complex sample preparation steps. This makes it a potential tool for glucose detection in pharmacy and medical diagnostics.