Bacterial cysteate dissimilatory pathway involves a racemase and d-cysteate sulfo-lyase.

The sulfite-reducing bacterium Bilophila wadsworthia, a common human intestinal pathobiont, is unique in its ability to metabolize a wide variety of sulfonates to generate sulfite as a terminal electron acceptor (TEA). The resulting formation of H2S is implicated in inflammation and colon cancer. l-cysteate, an oxidation product of l-cysteine, is among the sulfonates metabolized by B. wadsworthia, although the enzymes involved remain unknown. Here we report a pathway for l-cysteate dissimilation in B. wadsworthia RZATAU, involving isomerization of l-cysteate to d-cysteate by a cysteate racemase (BwCuyB), followed by cleavage into pyruvate, ammonia and sulfite by a d-cysteate sulfo-lyase (BwCuyA). The strong selectivity of BwCuyA for d-cysteate over l-cysteate was rationalized by protein structural modeling. A homolog of BwCuyA in the marine bacterium Silicibacter pomeroyi (SpCuyA) was previously reported to be a l-cysteate sulfo-lyase, but our experiments confirm that SpCuyA too displays a strong selectivity for d-cysteate. Growth of B. wadsworthia with cysteate as the electron acceptor is accompanied by production of H2S and induction of BwCuyA. Close homologs of BwCuyA and BwCuyB are present in diverse bacteria, including many sulfate- and sulfite-reducing bacteria, suggesting their involvement in cysteate degradation in different biological environments.

Kill Two Birds with One Stone: Dual-Metal MOF-Nanozyme-Decorated Hydrogels with ROS-Scavenging, Oxygen-Generating, and Antibacterial Abilities for Accelerating Infected Diabetic Wound Healing.

Diabetic wounds tend to develop into nonhealing wounds associated with the complex inflammatory microenvironment of uncontrollable bacterial infection, reactive oxygen species (ROS) accumulation, and chronic hypoxia. Damaged blood vessels hinder metabolic circulation, aggravating hypoxia, and ROS accumulation and further exacerbating the diabetic wound microenvironment. However, existing treatments with a single functionality have difficulty healing complicated diabetic wounds. Therefore, developing an integrative strategy to improve the hostility of the diabetic wound microenvironment is urgently needed. Herein, multifunctional genipin (GP)-crosslinked chitosan (CS)-based hydrogels decorated with the biomimetic metal-organic framework (MOF)-nanozymes and the natural antibacterial agent chlorogenic acid (CGA), which is named MOF/CGA@GP-CS (MCGC), are prepared. With catalase (CAT)-like activity, these dual-metal MOF-nanozymes are promising bioreactors for simultaneously alleviating ROS accumulation and hypoxia by converting elevated endogenous H2O2 into dissolved oxygen in diabetic wounds. In addition, the other component of natural polyphenolic CGA acts as a mild antibacterial agent, efficiently inhibiting wound infection and avoiding antibiotic resistance. Impressively, the MCGC hydrogels accelerate infected diabetic wound healing by eliminating oxidative stress, increasing oxygenation, and reversing bacterial infection in vivo. In this work, an effective strategy based on multifunctional hydrogel wound dressings is successfully developed and applied in diabetic wound management.

Effects of Training and Calibration Data on Surface Electromyogram-Based Recognition for Upper Limb Amputees.

Surface electromyogram (sEMG)-based gesture recognition has emerged as a promising avenue for developing intelligent prostheses for upper limb amputees. However, the temporal variations in sEMG have rendered recognition models less efficient than anticipated. By using cross-session calibration and increasing the amount of training data, it is possible to reduce these variations. The impact of varying the amount of calibration and training data on gesture recognition performance for amputees is still unknown. To assess these effects, we present four datasets for the evaluation of calibration data and examine the impact of the amount of training data on benchmark performance. Two amputees who had undergone amputations years prior were recruited, and seven sessions of data were collected for analysis from each of them. Ninapro DB6, a publicly available database containing data from ten healthy subjects across ten sessions, was also included in this study. The experimental results show that the calibration data improved the average accuracy by 3.03%, 6.16%, and 9.73% for the two subjects and Ninapro DB6, respectively, compared to the baseline results. Moreover, it was discovered that increasing the number of training sessions was more effective in improving accuracy than increasing the number of trials. Three potential strategies are proposed in light of these findings to enhance cross-session models further. We consider these findings to be of the utmost importance for the commercialization of intelligent prostheses, as they demonstrate the criticality of gathering calibration and cross-session training data, while also offering effective strategies to maximize the utilization of the entire dataset.

Low-loss, ultracompact n-adjustable waveguide bends for photonic integrated circuits.

Countless waveguides have been designed based on four basic bends: circular bend, sine/cosine bend, Euler bend (developed in 1744) and Bezier bend (developed in 1962). This paper proposes an n-adjustable (NA) bend, which has superior properties compared to other basic bends. Simulations and experiments indicate that the NA bends can show lower losses than other basic bends by adjusting n values. The circular bend and Euler bend are special cases of the proposed NA bend as n equals 0 and 1, respectively. The proposed bend are promising candidates for low-loss compact photonic integrated circuits.

Quinoline derivatives as potential anti-tubercular agents: Synthesis, molecular docking and mechanism of action.

Development of new drugs with novel mechanisms of action is required to combat the problem of drug-resistant Mycobacterium tuberculosis. The present investigation is aimed at combining two pharmacophores (quinoline or isoquinolines and thiosemicarbazide) to synthesize a series of compounds. Seven compounds were synthesized based on combination principle in this study. The compound 1-7 showed activities against M. tuberculosis H37Rv strain with MIC values rang from 2 to 8 µg/ml. Compound 5 exhibited remarkable antimycobacterial activity (MIC = 2 µg/ml), and was therefore selected for study of the mechanism of action. Molecular docking suggested initially that compound 5 could occupy the active site of KatG of M. tuberculosis. Furthermore compound 5 exhibited potent inhibitory effect on activity of KatG. RT-PCR finally displayed that compound 5 could up-regulate the transcription of katG of M. tuberculosis. Together, these studies reveal that compound 5 might be the inhibitor of KatG of Mycobacterium tuberculosis. One of the more significant findings to emerge from this study is that KatG of M.tuberculosis can be used as a putative novel target for new anti-tubercular drug design.

Effect of current conduction for local epileptiform discharges in patients with temporal lobe epilepsy.

OBJECTIVES: The effects of current conduction were researched to confirm that it can decrease focal epileptogenicity in patients with temporal lobe epilepsy (TLE). METHODS: Data from 13 patients with mesial TLE were collected. After no less than two habitual seizures were captured during stereo-electroencephalogram monitoring, current conduction was measured in the hippocampus to a homemade, zero potential circuit board. The interictal spike, ripple, fast ripple, and ictal epileptogenicity index (EI) changes were analyzed in the hippocampus, amygdala, and anterior and middle temporal neocortex regions. RESULTS: Significant differences were found in the percentage of patients without spikes in the temporal neocortex between pre- and post-current conduction. Significant decreases in average ripple rates were found in the hippocampus and amygdala after current conduction. The percentage of fast ripple rate decrease in the hippocampus and amygdala was significantly higher than that in the temporal neocortex, and significant decreases were found in the fast ripple rate in the hippocampus from post- to pre-current conduction. Significant decreases were found in the EI values after current conduction in the amygdala and middle temporal lobe compared to the EI values before current conduction. CONCLUSION: After current conduction in patients with TLE, the spike rate decreases in the hippocampus, amygdala, and anterior and middle temporal neocortex, the ripple rate decreases in the hippocampus and amygdala, the fast ripple decreases in the hippocampus, and the EI decreases in the amygdala and middle temporal neocortex. Current conduction can reduce epileptogenicity in the hippocampus in mesial TLE.

Hand Gesture Recognition on a Resource-Limited Interactive Wristband.

Most of the reported hand gesture recognition algorithms require high computational resources, i.e., fast MCU frequency and significant memory, which are highly inapplicable to the cost-effectiveness of consumer electronics products. This paper proposes a hand gesture recognition algorithm running on an interactive wristband, with computational resource requirements as low as Flash < 5 KB, RAM < 1 KB. Firstly, we calculated the three-axis linear acceleration by fusing accelerometer and gyroscope data with a complementary filter. Then, by recording the order of acceleration vectors crossing axes in the world coordinate frame, we defined a new feature code named axis-crossing code. Finally, we set templates for eight hand gestures to recognize new samples. We compared this algorithm's performance with the widely used dynamic time warping (DTW) algorithm and recurrent neural network (BiLSTM and GRU). The results show that the accuracies of the proposed algorithm and RNNs are higher than DTW and that the time cost of the proposed algorithm is much less than those of DTW and RNNs. The average recognition accuracy is 99.8% on the collected dataset and 97.1% in the actual user-independent case. In general, the proposed algorithm is suitable and competitive in consumer electronics. This work has been volume-produced and patent-granted.

Synergistic effects of xanthan gum and ß-cyclodextrin on properties and stability of vegetable oil-based whipped cream.

The synergistic effects between xanthan gum (XG) and ß-cyclodextrin (ß-CD) on the properties and stability of vegetable oil-based whipped cream stabilized by kidney bean protein aggregates was investigated. The visual appearance, SEM, TEM, CLSM, FT-IR and LF-NMR results showed that when the ratio of XG to ß-CD in the XG-ß-CD complex was appropriate, the hydrogen bonding effect between ß-CD and XG was significant enhanced, the three-dimensional network structure has the highest density, the emulsion droplets were the smallest and evenly distributed. The unique tapered microstructure of ß-CD acted as a bridge between the hydrophilic and hydrophobic components, effectively preventing the aggregation of oil droplets and establishing a flexible support system between oil droplets; while the flexible molecular structure of XG could support Pickering emulsion system. The XG-ß-CD complex had a synergistic effect with protein aggregates, making it ideal for use in whipped cream products. This study explored the stability mechanism of ß-CD in the Pickering emulsion-based whipped cream system, providing valuable insights into producing whole plant-based whipped cream by texturizing highly unsaturated oils. This effectively solves the problem of inadequate intake of unsaturated oil for individuals who consume excessive amounts of animal-derived fats.

FPGA-based Lightweight QDS-CNN System for sEMG Gesture and Force Level Recognition.

Deep learning (DL) has been used for electromyographic (EMG) signal recognition and achieved high accuracy for multiple classification tasks. However, implementation in resource-constrained prostheses and human-computer interaction devices remains challenging. To overcome these problems, this paper implemented a low-power system for EMG gesture and force level recognition using Zynq architecture. Firstly, a lightweight network model structure was proposed by Ultra-lightweight depth separable convolution (UL-DSC) and channel attention-global average pooling (CA-GAP) to reduce the computational complexity while maintaining accuracy. A wearable EMG acquisition device for real-time data acquisition was subsequently developed with size of 36mm×28mm×4mm. Finally, a highly parallelized dedicated hardware accelerator architecture was designed for inference computation. 18 gestures were tested, including force levels from 22 healthy subjects. The results indicate that the average accuracy rate was 94.92% for a model with 5.0k parameters and a size of 0.026MB. Specifically, the average recognition accuracy for static and force-level gestures was 98.47% and 89.92%, respectively. The proposed hardware accelerator architecture was deployed with 8-bit precision, a single-frame signal inference time of 41.9µs, a power consumption of 0.317W, and a data throughput of 78.6 GOP/s.

Three-dimensional micro strain gauges as flexible, modular tactile sensors for versatile integration with micro- and macroelectronics.

Flexible tactile sensors play important roles in many areas, like human-machine interface, robotic manipulation, and biomedicine. However, their flexible form factor poses challenges in their integration with wafer-based devices, commercial chips, or circuit boards. Here, we introduce manufacturing approaches, device designs, integration strategies, and biomedical applications of a set of flexible, modular tactile sensors, which overcome the above challenges and achieve cooperation with commercial electronics. The sensors exploit lithographically defined thin wires of metal or alloy as the sensing elements. Arranging these elements across three-dimensional space enables accurate, hysteresis-free, and decoupled measurements of temperature, normal force, and shear force. Assembly of such sensors on flexible printed circuit boards together with commercial electronics forms various flexible electronic systems with capabilities in wireless measurements at the skin interface, continuous monitoring of biomechanical signals, and spatial mapping of tactile information. The flexible, modular tactile sensors expand the portfolio of functional components in both microelectronics and macroelectronics.

Highly selective and sensitive determination of dopamine using Nafion coated microelectrode arrays.

The present study concerns methodological issue of electrochemical recordings using Nafion-coated microelectrode arrays fabricated by MEMS technology for voltammetric and amperometric measurements of dopamine (DA). The properties of Nafion-coated different temperature dried microelectrodes were determined by cyclic voltammetry. The electrochemical characteristics of the 120 degrees C dried Nafion-coated microelectrode for measures of dopamine and ascorbic acid (AA) were studied by chronoamperometry. These studies showed that the 120 degrees C dried Nafion-coated microelectrode had better recording properties: enlarged electrochemical signal for DA and high selectivity for DA versus AA. The linear response was obtained in the range of 0.1 to 50 microM with a low detection limit. The modified microelectrode arrays providing 30 microm diameter multiple sites showed the capability to simultaneously detect DA from cells, neurons and brain slices.

Planar microelectrode chip for synchronous simulative neurochemical and neuroelectrial monitoring.

The microfabricated microelectrode arrays on glass substrate combined with homemade multichannel detection system as a powerful tool for synchronous neurochemical and neuroelectrial monitoring was described. The dual-mode (neurochemical and neuroelectrial: simultaneous recording of spikes, and dopamine overflow on the same spatiotemporal scale) recording was carried in PBS buffer. The neurochemical constant potential amperometry was carried at +0.4 V working potential for nM-microM dopamine detection and nM level dopamine concentration increase can be detected by the device. The microelectrode chip showed high sensitivity of 0.88 nA/nM mm2 during nM range and 0.43 nA/nM mm2 during microM range for the determination of DA. The amperometric method used to detect dopamine (DA) did not significantly influence electrophysiological activity at low concentration (< 200 nM) and have a quickly clear away strike at high concentration (> 2 microM). The system uniquely affords synchronous measurement of chemical and electrical neural activity at the adjacent recording sites on the same chip. The sensitivity and resolution of the device allows for simultaneous recoding of electrical and chemical signaling, which may be useful for examining specific spatiotemporal relationships between electrical and chemical signaling in vitro.

The Non-Nutritional Factor Types, Mechanisms of Action and Passivation Methods in Food Processing of Kidney Bean (Phaseolus vulgaris L.): A Systematic Review.

Kidney beans (KBs), as a traditional edible legume, are an important food crop of high nutritional and economic value worldwide. KBs contain a full range of amino acids and a high proportion of essential amino acids, and are rich in carbohydrates as well as vitamins and minerals. However, KBs contain a variety of non-nutritional factors that impede the digestion and absorption of nutrients, disrupt normal metabolism and produce allergic reactions, which severely limit the exploitation of KBs and related products. Suppressing or removing the activity of non-nutritional factors through different processing methods can effectively improve the application value of KBs and expand the market prospect of their products. The aim of this review was to systematically summarize the main types of non-nutritional factors in KBs and their mechanisms of action, and to elucidate the effects of different food processing techniques on non-nutritional factors. The databases utilized for the research included Web of Science, PubMed, ScienceDirect and Scopus. We considered all original indexed studies written in English and published between 2012 and 2023. We also look forward to the future research direction of producing KB products with low non-nutritional factors, which will provide theoretical basis and foundation for the development of safer and healthier KB products.

Conduction treatment of temporal lobe epilepsy in rats: the dose-effect relationship between current resistance and therapeutic effect.

Objective: To investigate the effect of current resistance on therapeutic outcomes, and the mechanism of current conduction treatment in a rat model of temporal lobe epilepsy (TLE). Methods: Rats were randomly divided into four groups: normal control, epileptic group, low-resistance conduction (LRC) and high-resistance conduction (HRC) group. The content of glutamate (Glu) and gamma-amino butyric acid (GABA) in the hippocampus was determined using a neurotransmitter analyzer. mRNA and protein expression of interleukin 1ß (IL-1ß) /IL-1 receptor 1(IL-1R1) and high mobility group protein B1 (HMGB-1)/toll-like receptor-4 (TLR-4) in hippocampal neurons were tested. Video electroencephalogram monitoring was used to record seizures and EEG discharges. Cognitive function in the rats was tested using the Morris water maze. Results: Glu/GABA ratio in the epileptic control and HRC groups was significant differences from LRC group. The levels of HMGB1/TLR4 and IL-1ß/IL-1R1 in the LRC group and normal control group were significantly lower than those in epileptic control group (p < 0.01) and the HRC group. The mRNA levels of HMGB1/TLR4 and IL-1ß/IL-1R1 in the LRC group and normal control group were significantly lower than those in epileptic control group. The frequency of total and propagated seizures was lower in the LRC group than in the epileptic control and HRC groups (p < 0.01). The numbers of platform crossings in the LRC group and normal control group were significantly higher than those in the epileptic control and HRC groups in the space exploration experiment. Conclusion: Current resistance affected seizure control and cognitive protection in rats with TLE treated by current conduction. The lower current resistance, the better seizure control and cognitive protection in rats with TLE treated by current conduction. Glu/GABA, IL-1ß/IL-1R1, and HMGB1/TLR-4 may participate in the anti-seizure mechanism of current conduction treatment.

Elderly Fall Detection Based on GCN-LSTM Multi-Task Learning Using Nursing Aids Integrated with Multi-Array Flexible Tactile Sensors.

Due to the frailty of elderly individuals' physical condition, falling can lead to severe bodily injuries. Effective fall detection can significantly reduce the occurrence of such incidents. However, current fall detection methods heavily rely on visual and multi-sensor devices, which incur higher costs and complex wearable designs, limiting their wide-ranging applicability. In this paper, we propose a fall detection method based on nursing aids integrated with multi-array flexible tactile sensors. We design a kind of multi-array capacitive tactile sensor and arrange the distribution of tactile sensors on the foot based on plantar force analysis and measure tactile sequences from the sole of the foot to develop a dataset. Then we construct a fall detection model based on a graph convolution neural network and long-short term memory network (GCN-LSTM), where the GCN module and LSTM module separately extract spatial and temporal features from the tactile sequences, achieving detection on tactile data of foot and walking states for specific time series in the future. Experiments are carried out with the fall detection model, the Mean Squared Error (MSE) of the predicted tactile data of the foot at the next time step is 0.0716, with the fall detection accuracy of 96.36%. What is more, the model can achieve fall detection on 5-time steps with 0.2-s intervals in the future with high confidence results. It exhibits outstanding performance, surpassing other baseline algorithms. Besides, we conduct experiments on different ground types and ground morphologies for fall detection, and the model showcases robust generalization capabilities.

Recent Advancements in Physiological, Biochemical, and Multimodal Sensors Based on Flexible Substrates: Strategies, Technologies, and Integrations.

Flexible wearable devices have been widely used in biomedical applications, the Internet of Things, and other fields, attracting the attention of many researchers. The physiological and biochemical information on the human body reflects various health states, providing essential data for human health examination and personalized medical treatment. Meanwhile, physiological and biochemical information reveals the moving state and position of the human body, and it is the data basis for realizing human-computer interactions. Flexible wearable physiological and biochemical sensors provide real-time, human-friendly monitoring because of their light weight, wearability, and high flexibility. This paper reviews the latest advancements, strategies, and technologies of flexibly wearable physiological and biochemical sensors (pressure, strain, humidity, saliva, sweat, and tears). Next, we systematically summarize the integration principles of flexible physiological and biochemical sensors with the current research progress. Finally, important directions and challenges of physiological, biochemical, and multimodal sensors are proposed to realize their potential applications for human movement, health monitoring, and personalized medicine.

Miniature Fourier Transform Spectrometer Based on Thin-Film Lithium Niobate.

A miniature Fourier transform spectrometer is proposed using a thin-film lithium niobate electro-optical modulator instead of the conventional modulator made by titanium diffusion in lithium niobate. The modulator was fabricated by a contact lithography process, and its voltage-length and optical waveguide loss were 2.26 V·cm and 1.01 dB/cm, respectively. Based on the wavelength dispersion of the half-wave voltage of the fabricated modulator, the emission spectrum of the input signal was retrieved by Fourier transform processing of the interferogram, and the analysis of the experimental data of monochromatic light shows that the proposed miniaturized FTS can effectively identify the input signal wavelength.

Multichannel Flexible Pulse Perception Array for Intelligent Disease Diagnosis System.

Pressure sensors with high sensitivity, a wide linear range, and a quick response time are critical for building an intelligent disease diagnosis system that directly detects and recognizes pulse signals for medical and health applications. However, conventional pressure sensors have limited sensitivity and nonideal response ranges. We proposed a multichannel flexible pulse perception array based on polyimide/multiwalled carbon nanotube-polydimethylsiloxane nanocomposite/polyimide (PI/MPN/PI) sandwich-structure pressure sensor that can be applied for remote disease diagnosis. Furthermore, we established a mechanical model at the molecular level and guided the preparation of MPN. At the structural level, we achieved high sensitivity (35.02 kPa-1) and a broad response range (0-18 kPa) based on a pyramid-like bilayer microstructure with different upper and lower surfaces. A 27-channel (3 × 9) high-density sensor array was integrated at the device level, which can extract the spatial and temporal distribution information on a pulse. Furthermore, two intelligent algorithms were developed for extracting six-dimensional pulse information and automatic pulse recognition (the recognition rate reaches 97.8%). The results indicate that intelligent disease diagnosis systems have great potential applications in wearable healthcare devices.

Wearable and flexible electrochemical sensors for sweat analysis: a review.

Flexible wearable sweat sensors allow continuous, real-time, noninvasive detection of sweat analytes, provide insight into human physiology at the molecular level, and have received significant attention for their promising applications in personalized health monitoring. Electrochemical sensors are the best choice for wearable sweat sensors due to their high performance, low cost, miniaturization, and wide applicability. Recent developments in soft microfluidics, multiplexed biosensing, energy harvesting devices, and materials have advanced the compatibility of wearable electrochemical sweat-sensing platforms. In this review, we summarize the potential of sweat for medical detection and methods for sweat stimulation and collection. This paper provides an overview of the components of wearable sweat sensors and recent developments in materials and power supply technologies and highlights some typical sensing platforms for different types of analytes. Finally, the paper ends with a discussion of the challenges and a view of the prospective development of this exciting field.

An iEEG Recording and Adjustable Shunt-Current Conduction Platform for Epilepsy Treatment.

This paper proposes a compact bioelectronics sensing platform, including a multi-channel electrode, intracranial electroencephalogram (iEEG) recorder, adjustable galvanometer, and shunt-current conduction circuit pathway. The developed implantable electrode made of polyurethane-insulated stainless-steel materials is capable of recording iEEG signals and shunt-current conduction. The electrochemical impedance of the conduction, ground/reference, and working electrode were characterized in phosphate buffer saline solution, revealing in vitro results of 517.2 Ω@1 kHz (length of 0.1 mm, diameter of 0.8 mm), 1.374 kΩ@1 kHz (length of 0.3 mm, diameter of 0.1 mm), and 3.188 kΩ@1 kHz (length of 0.1 mm, diameter of 0.1 mm), respectively. On-bench measurement of the system revealed that the input noise of the system is less than 2 µVrms, the signal frequency bandwidth range is 1 Hz~10 kHz, and the shunt-current detection range is 0.1~3000 µA with an accuracy of above 99.985%. The electrode was implanted in the CA1 region of the right hippocampus of rats for the in vivo experiments. Kainic acid (KA)-induced seizures were detected through iEEG monitoring, and the induced shunt-current was successfully measured and conducted out of the brain through the designed circuit-body path, which verifies the potential of current conduction for the treatment of epilepsy.