Self-Powered Biomimetic Pressure Sensor Based on Mn-Ag Electrochemical Reaction for Monitoring Rehabilitation Training of Athletes.

Self-powered pressure detection using smart wearable devices is the subject of intense research attention, which is intended to address the critical need for prolonged and uninterrupted operations. Current piezoelectric and triboelectric sensors well respond to dynamic stimuli while overlooking static stimuli. This study proposes a dual-response potentiometric pressure sensor that responds to both dynamic and static stimuli. The proposed sensor utilizes interdigital electrodes with MnO2/carbon/polyvinyl alcohol (PVA) as the cathode and conductive silver paste as the anode. The electrolyte layer incorporates a mixed hydrogel of PVA and phosphoric acid. The optimized interdigital electrodes and sandpaper-like microstructured surface of the hydrogel electrolyte contribute to enhanced performance by facilitating an increased contact area between the electrolyte and electrodes. The sensor features an open-circuit voltage of 0.927 V, a short-circuit current of 6 µA, a higher sensitivity of 14 mV/kPa, and outstanding cycling performance (>5000 cycles). It can accurately recognize letter writing and enable capacitor charging and LED lighting. Additionally, a data acquisition and display system employing the proposed sensor, which facilitates the monitoring of athletes' rehabilitation training, and machine learning algorithms that effectively guide rehabilitation actions are presented. This study offers novel solutions for the future development of smart wearable devices.

Dietary patterns, metabolomics and frailty in a large cohort of 120 000 participants.

Objective: To examine the associations of dietary patterns with frailty and whether metabolic signatures (MSs) mediate these associations. Methods: We used UK Biobank data to examine (1) the associations of four dietary patterns (i.e., alternate Mediterranean diet [aMED], Recommended Food Score [RFS], Dietary Approaches to Stop Hypertension [DASH] and Mediterranean-DASH Intervention for Neurodegenerative Delay [MIND] diet) with frailty (measured by the frailty phenotype and the frailty index) using multivariable logistic regression (analytic sample 1: N = 124 261; mean age = 57.7 years), and (2) the mediating role of MSs (weighted sums of the metabolites selected from 168 plasma metabolites using the LASSO algorithm) in the above associations via mediation analysis (analytic sample 2: N = 26 270; mean age = 57.7 years). Results: Four dietary patterns were independently associated with frailty (all P < 0.001). For instance, compared to participants in the lowest tertile for RFS, those in the intermediate (odds ratio [OR]: 0.81; 95% confidence interval [CI]: 0.74, 0.89) and highest (OR: 0.62; 95% CI: 0.56, 0.68) tertiles had a lower risk of frailty. We found that 98, 68, 123 and 75 metabolites were associated with aMED, RFS, DASH and MIND, respectively, including 16 common metabolites (e.g., fatty acids, lipoproteins, acetate and glycoprotein acetyls). The MSs based on these metabolites partially mediated the association of the four dietary patterns with frailty, with the mediation proportion ranging from 26.52% to 45.83%. The results were robust when using another frailty measure, the frailty index. Conclusions: The four dietary patterns were associated with frailty, and these associations were partially mediated by MSs. Adherence to healthy dietary patterns may potentially reduce frailty development by modulating metabolites.

Investigating the synergy of Shikonin and Valproic acid in inducing apoptosis of osteosarcoma cells via ROS-mediated EGR1 expression.

BACKGROUND: Osteosarcoma is the most prevalent malignant bone tumour with a poor prognosis. Shikonin (SHK) is derived from the traditional Chinese medicine Lithospermum that has been extensively studied for its notable anti-tumour effects, including for osteosarcoma. However, its application has certain limitations. Valproic acid (VPA) is a histone deacetylase inhibitor (HDACI) that has recently been employed as an adjunctive therapeutic agent that allows chromatin to assume a more relaxed state, thereby enhancing anti-tumour efficacy. PURPOSE: This study was aimed to investigate the synergistic anti-tumour efficacy of SHK in combination with VPA and elucidate its underlying mechanism. METHODS/STUDY DESIGN: CCK-8 assays were utilized to calculate the combination index. Additional assays, including colony formation, acridine orange/ethidium bromide double fluorescent staining, and flow cytometry, were employed to evaluate the effects on osteosarcoma cells. Wound healing and transwell assays were utilized to assess cell mobility. RNA sequencing, PCR, and Western blot analyses were conducted to uncover the underlying mechanism. Rescue experiments were performed to validate the mechanism of apoptotic induction. The impact of SHK and VPA combination treatment on primary osteosarcoma cells was also assessed. Finally, in vivo experiments were conducted to validate its anti-tumour effects and mechanism. RESULTS: The combination of SHK and VPA synergistically inhibited the proliferation and migration of osteosarcoma cells in vitro and induced apoptosis in these cells. Through a comprehensive analysis involving RNA sequencing, PCR, Western blot, and rescue experiments, we have substantiated our hypothesis that the combination of SHK and VPA induced apoptosis via the ROS-EGR1-Bax axis. Importantly, our in vivo experiments corroborated these findings, demonstrating the potential of the SHK and VPA combination as a promising therapeutic approach for osteosarcoma. CONCLUSION: The combination of SHK and VPA exerted an anti-tumour effect by inducing apoptosis through the ROS-EGR1-Bax pathway. Repurposing the old drug VPA demonstrated its effectiveness as an adjunctive therapeutic agent for SHK, enhancing its anti-tumour efficacy and revealing its potential value. Furthermore, our study expanded the application of natural compounds in the anti-tumour field and overcame some of their limitations through combination therapy. Finally, we enhanced the understanding of the mechanistic pathways linking reactive oxygen species (ROS) accumulation and apoptosis in osteosarcoma cells. Additionally, we elucidated the role of EGR1 in osteosarcoma cells, offering novel strategies and concepts for the treatment of osteosarcoma.

Naringin ameliorates obesity via stimulating adipose thermogenesis and browning, and modulating gut microbiota in diet-induced obese mice.

Naringin, a natural flavanone primarily found in citrus fruits, has garnered increased attention due to its recognized antioxidative, anti-inflammatory, and cardioprotective attributes. However, the functions of naringin in regulating energy expenditure are poorly understood. In the present study, we observed that twelve weeks of naringin supplementation substantially reshaped the metabolic profile of high-fat diet (HFD)-fed mice, by inhibiting body weight gain, reducing liver weight, and altering body compositions. Notably, naringin exhibited a remarkable capacity to augment whole-body energy expenditure of the tested mice by enhancing the thermogenic activity of brown adipose tissue (BAT) and stimulating browning of inguinal white adipose tissue (iWAT). Furthermore, our results showed naringin supplementation modified gut microbiota composition, specifically increasing the abundance of Bifidobacterium and Lachnospiraceae_bacterium_28-4, while reducing the abundance of Lachnospiraceae_bacterium_DW59 and Dubosiella_newyorkensis. Subsequently, we also found naringin supplementation altered fecal metabolite profile, by significantly promoting the production of taurine, tyrosol, and thymol, which act as potent activators of thermoregulation. Interestingly, the metabolic effects of naringin were abolished upon gut microbiota depletion through antibiotic intervention, concurrently leading the disappearance of naringin-induced thermogenesis and protective actions on diet-induced obesity. This discovery revealed a novel food-driven cross-sectional communication between gut bacteria and adipose tissues. Collectively, our data indicate that naringin supplementation stimulates BAT thermogenesis, alters fat distribution, promotes the browning process, and consequently inhibits body weight gain; importantly these metabolic effects require the participation of gut bacteria.

A High Working Temperature Multiferroic Induced by Inverse Temperature Symmetry Breaking.

Molecular-based multiferroic materials that possess ferroelectric and ferroelastic orders simultaneously have attracted tremendous attention for their potential applications in multiple-state memory devices, molecular switches, and information storage systems. However, it is still a great challenge to effectively construct novel molecular-based multiferroic materials with multifunctionalities. Generally, the structure of these materials possess high symmetry at high temperatures, while processing an obvious order-disorder or displacement-type ferroelastic or ferroelectric phase transition triggered by symmetry breaking during the cooling processes. Therefore, these materials can only function below the Curie temperature (Tc), the low of which is a severe impediment to their practical application. Despite great efforts to elevate Tc, designing single-phase crystalline materials that exhibit multiferroic orders above room temperature remains a challenge. Here, an inverse temperature symmetry-breaking phenomenon was achieved in [FPM][Fe3(µ3-O)(µ-O2CH)8] (FPM stands for 3-(3-formylamino-propyl)-3,4,5,6-tetrahydropyrimidin-1-ium, which acts as the counterions and the rotor component in the network), enabling a ferroelastoelectric phase at a temperature higher than Tc (365 K). Upon heating from room temperature, two-step distinct symmetry breaking with the mm2Fm species leads to the coexistence of ferroelasticity and ferroelectricity in the temperature interval of 365-426 K. In the first step, the FPM cations undergo a conformational flip-induced inverse temperature symmetry breaking; in the second step, a typical ordered-disordered motion-induced symmetry breaking phase transition can be observed, and the abnormal inverse temperature symmetry breaking is unprecedented. Except for the multistep ferroelectric and ferroelastic switching, this complex also exhibits fascinating nonlinear optical switching properties. These discoveries not only signify an important step in designing novel molecular-based multiferroic materials with high working temperatures, but also inspire their multifunctional applications such as multistep switches.

DeepRisk network: an AI-based tool for digital pathology signature and treatment responsiveness of gastric cancer using whole-slide images.

BACKGROUND: Digital histopathology provides valuable information for clinical decision-making. We hypothesized that a deep risk network (DeepRisk) based on digital pathology signature (DPS) derived from whole-slide images could improve the prognostic value of the tumor, node, and metastasis (TNM) staging system and offer chemotherapeutic benefits for gastric cancer (GC). METHODS: DeepRisk is a multi-scale, attention-based learning model developed on 1120 GCs in the Zhongshan dataset and validated with two external datasets. Then, we assessed its association with prognosis and treatment response. The multi-omics analysis and multiplex Immunohistochemistry were conducted to evaluate the potential pathogenesis and spatial immune contexture underlying DPS. RESULTS: Multivariate analysis indicated that the DPS was an independent prognosticator with a better C-index (0.84 for overall survival and 0.71 for disease-free survival). Patients with low-DPS after neoadjuvant chemotherapy responded favorably to treatment. Spatial analysis indicated that exhausted immune clusters and increased infiltration of CD11b+CD11c+ immune cells were present at the invasive margin of high-DPS group. Multi-omics data from the Cancer Genome Atlas-Stomach adenocarcinoma (TCGA-STAD) hint at the relevance of DPS to myeloid derived suppressor cells infiltration and immune suppression. CONCLUSION: DeepRisk network is a reliable tool that enhances prognostic value of TNM staging and aid in precise treatment, providing insights into the underlying pathogenic mechanisms.

A circRNA ceRNA network involved in cognitive dysfunction after chronic cerebral hypoperfusion.

Chronic Cerebral Hypoperfusion (CCH) is associated with cognitive dysfunction, the underlying mechanisms of which remain elusive, hindering the development of effective therapeutic approaches. In this study, we employed an established CCH animal model to delve into neuropathological alterations like oxidative stress, inflammation, neurotransmitter synthesis deficits, and other morphological alterations. Our findings revealed that while the number of neurons remained unchanged, there was a significant reduction in neuronal fibers post-CCH, as evidenced by microtubule-associated protein 2 (MAP2) staining. Moreover, myelin basic protein (MBP) staining showed exacerbated demyelination of neuronal fibers. Furthermore, we observed increased neuroinflammation, proliferation, and activation of astrocytes and microglia, as well as synaptic loss and microglial-mediated synapse engulfment post-CCH. Utilizing RNA sequencing, differential expression analysis displayed alterations in both mRNAs and circRNAs. Following gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses, both showed significant enrichment in immunological and inflammation-related terms and pathways. Importantly, the differentially expressed circular RNAs (DE circRNAs) exhibited a notable coexpression pattern with DE mRNAs. The ternary circRNA-miRNA-mRNA competing endogenous RNAs (ceRNA) network was constructed, and subsequent analysis reiterated the significance of neuroimmunological and neuroinflammatory dysfunction in CCH-induced neuropathological changes and cognitive dysfunction. This study underscores the potential role of circRNAs in these processes, suggesting them as promising therapeutic targets to mitigate the detrimental effects of CCH.

Micropyramid Array Bimodal Electronic Skin for Intelligent Material and Surface Shape Perception Based on Capacitive Sensing.

Developing electronic skins (e-skins) that are comparable to or even beyond human tactile perception holds significant importance in advancing the process of intellectualization. In this context, a machine-learning-motivated micropyramid array bimodal (MAB) e-skin based on capacitive sensing is reported, which enables spatial mapping applications based on bimodal sensing (proximity and pressure) implemented via fringing and iontronic effects, such as contactless measurement of 3D objects and contact recognition of Braille letters. Benefiting from the iontronic effect and single-micropyramid structure, the MAB e-skin in pressure mode yields impressive features: a maximum sensitivity of 655.3 kPa-1 (below 0.5 kPa), a linear sensitivity of 327.9 kPa-1 (0.5-15 kPa), and an ultralow limit of detection of 0.2 Pa. With the assistance of multilayer perceptron and convolutional neural network, the MAB e-skin can accurately perceive 6 materials and 10 surface shapes based on the training and learning using the collected datasets from proximity and pressure modes, thus allowing it to achieve the precise perception of different objects within one proximity-pressure cycle. The development of this MAB e-skin opens a new avenue for robotic skin and the expansion of advanced applications.

A highly sensitive flexible capacitive pressure sensor with hierarchical pyramid micro-structured PDMS-based dielectric layer for health monitoring.

Herein, a flexible pressure sensor with high sensitivity was created using a dielectric layer featuring a hierarchical pyramid microstructure, both in simulation and fabrication. The capacitive pressure sensor comprises a hierarchically arranged dielectric layer made of polydimethylsiloxane (PDMS) with pyramid microstructures, positioned between copper electrodes at the top and bottom. The achievement of superior sensing performance is highly contingent upon the thickness of the dielectric layer, as indicated by both empirical findings and finite-element analysis. Specifically, the capacitive pressure sensor, featuring a dielectric layer thickness of 0.5 mm, exhibits a remarkable sensitivity of 0.77 kPa-1 within the pressure range below 1 kPa. It also demonstrates an impressive response time of 55 ms and recovery time of 42 ms, along with a low detection limit of 8 Pa. Furthermore, this sensor showcases exceptional stability and reproducibility with up to 1,000 cycles. Considering its exceptional achievements, the pressure sensor has been effectively utilized for monitoring physiological signals, sign language gestures, and vertical mechanical force exerted on objects. Additionally, a 5 × 5 sensor array was fabricated to accurately and precisely map the shape and position of objects. The pressure sensor with advanced performance shows broad potential in electronic skin applications.

Deep learning radiopathomics based on preoperative US images and biopsy whole slide images can distinguish between luminal and non-luminal tumors in early-stage breast cancers.

BACKGROUND: For patients with early-stage breast cancers, neoadjuvant treatment is recommended for non-luminal tumors instead of luminal tumors. Preoperative distinguish between luminal and non-luminal cancers at early stages will facilitate treatment decisions making. However, the molecular immunohistochemical subtypes based on biopsy specimens are not always consistent with final results based on surgical specimens due to the high intra-tumoral heterogeneity. Given that, we aimed to develop and validate a deep learning radiopathomics (DLRP) model to preoperatively distinguish between luminal and non-luminal breast cancers at early stages based on preoperative ultrasound (US) images, and hematoxylin and eosin (H&E)-stained biopsy slides. METHODS: This multicentre study included three cohorts from a prospective study conducted by our team and registered on the Chinese Clinical Trial Registry (ChiCTR1900027497). Between January 2019 and August 2021, 1809 US images and 603 H&E-stained whole slide images (WSIs) from 603 patients with early-stage breast cancers were obtained. A Resnet18 model pre-trained on ImageNet and a multi-instance learning based attention model were used to extract the features of US and WSIs, respectively. An US-guided Co-Attention module (UCA) was designed for feature fusion of US and WSIs. The DLRP model was constructed based on these three feature sets including deep learning US feature, deep learning WSIs feature and UCA-fused feature from a training cohort (1467 US images and 489 WSIs from 489 patients). The DLRP model's diagnostic performance was validated in an internal validation cohort (342 US images and 114 WSIs from 114 patients) and an external test cohort (270 US images and 90 WSIs from 90 patients). We also compared diagnostic efficacy of the DLRP model with that of deep learning radiomics model and deep learning pathomics model in the external test cohort. FINDINGS: The DLRP yielded high performance with area under the curve (AUC) values of 0.929 (95% CI 0.865-0.968) in the internal validation cohort, and 0.900 (95% CI 0.819-0.953) in the external test cohort. The DLRP also outperformed deep learning radiomics model based on US images only (AUC 0.815 [0.719-0.889], p = 0.027) and deep learning pathomics model based on WSIs only (AUC 0.802 [0.704-0.878], p = 0.013) in the external test cohort. INTERPRETATION: The DLRP can effectively distinguish between luminal and non-luminal breast cancers at early stages before surgery based on pretherapeutic US images and biopsy H&E-stained WSIs, providing a tool to facilitate treatment decision making in early-stage breast cancers. FUNDING: Natural Science Foundation of Guangdong Province (No. 2023A1515011564), and National Natural Science Foundation of China (No. 91959127; No. 81971631).

Alteration of Cognitive Function in Aging and Alzheimer's Disease Mice Is Related to Dysfunction of the Neuroimmune System.

BACKGROUND: Both Alzheimer's disease (AD) and aging have aging-related cognitive dysfunction with a high incidence. These neurological diseases cause serious cognitive problems in patients' daily life. But the cognitive dysfunction mechanism in-depth of aging is far less known than that of AD. OBJECTIVE: To reveal the different mechanisms of AD and aging-related cognitive dysfunction, we compared the mechanisms of aging and AD through analysis of differentially expressed genes. METHODS: Mice were divided into four groups (3-month C57BL, 16-month C57BL, 3-month 3xTg AD mice, and 16-month 3xTg AD mice) according to genotype and age. The Morris water maze was employed to investigate the spatial cognition of mice. Differential expressions of genes of AD and aging were analyzed through RNA sequencing and GO, KEGG, Reactome analysis, and the dynamic change trend analysis. Microglia was stained with immunofluorescence and its numbers were counted for analysis. RESULTS: The cognitive function of elderly mice were worse through testing with the Morris water maze. The cognitive function of 16-month 3xTg AD mice were worse than 16-month C57BL mice. The alteration tendencies of DE genes were uncovered, and microglia numbers increased during aging and AD progression through immunofluorescence. CONCLUSION: These results suggest that immune-related pathways might play a critical role in aging and AD-related cognitive dysfunction. Our research will help to provide some new potential targets for treating cognitive dysfunction in aging and AD.

White matter injury detection based on preterm infant cranial ultrasound images.

Introduction: White matter injury (WMI) is now the major disease that seriously affects the quality of life of preterm infants and causes cerebral palsy of children, which also causes periventricular leuko-malacia (PVL) in severe cases. The study aimed to develop a method based on cranial ultrasound images to evaluate the risk of WMI. Methods: This study proposed an ultrasound radiomics diagnostic system to predict the WMI risk. A multi-task deep learning model was used to segment white matter and predict the WMI risk simultaneously. In total, 158 preterm infants with 807 cranial ultrasound images were enrolled. WMI occurred in 32preterm infants (20.3%, 32/158). Results: Ultrasound radiomics diagnostic system implemented a great result with AUC of 0.845 in the testing set. Meanwhile, multi-task deep learning model preformed a promising result both in segmentation of white matter with a Dice coefficient of 0.78 and prediction of WMI risk with AUC of 0.863 in the testing cohort. Discussion: In this study, we presented a data-driven diagnostic system for white matter injury in preterm infants. The system combined multi-task deep learning and traditional radiomics features to achieve automatic detection of white matter regions on the one hand, and design a fusion strategy of deep learning features and manual radiomics features on the other hand to obtain stable and efficient diagnostic performance.

Corrigendum: Treatment of avulsion fracture of posterior cruciate ligament tibial insertion by a minimally invasive approach in the posterior medial knee.

[This corrects the article DOI: 10.3389/fsurg.2022.885669.].

Development of a deep pathomics score for predicting hepatocellular carcinoma recurrence after liver transplantation.

BACKGROUND AND PURPOSE: Tumor recurrence after liver transplantation (LT) impedes the curative chance for hepatocellular carcinoma (HCC) patients. This study aimed to develop a deep pathomics score (DPS) for predicting tumor recurrence after liver transplantation using deep learning. PATIENTS AND METHODS: Two datasets of 380 HCC patients who underwent LT were enrolled. Residual convolutional neural networks were used to identify six histological structures of HCC. The individual risk score of each structure and DPS were derived by a modified DeepSurv network. Cox regression analysis and Concordance index were used to evaluate the prognostic significance. The cellular exploration of prognostic immune biomarkers was performed by quantitative and spatial proximity analysis according to three panels of 7-color immunofluorescence. RESULTS: The overall classification accuracy of HCC tissue was 97%. At the structural level, immune cells were the most significant tissue category for predicting post-LT recurrence (HR 1.907, 95% CI 1.490-2.440). The C-indices of DPS achieved 0.827 and 0.794 in the training and validation cohorts, respectively. Multivariate analysis for recurrence-free survival (RFS) showed that DPS (HR 4.795, 95% CI 3.017-7.619) was an independent risk factor. Patients in the high-risk subgroup had a shorter RFS, larger tumor diameter and a lower proportion of clear tumor borders. At the cellular level, a higher infiltration of intratumoral NK cells was negatively correlated with recurrence risk. CONCLUSIONS: This study established an effective DPS. Immune cells were the most significant histological structure related to HCC recurrence. DPS performed well in post-LT recurrence prediction and the identification of clinicopathological features.

Upregulation of RasGRF1 ameliorates spatial cognitive dysfunction in mice after chronic cerebral hypoperfusion.

Chronic cerebral hypoperfusion (CCH)-mediated cognitive impairment is a serious problem worldwide. However, given its complexity, the underlying mechanisms by which CCH induces cognitive dysfunction remain unclear, resulting in a lack of effective treatments. In this study, we aimed to determine whether changes in the expression of RasGRF1, an important protein associated with cognition and synaptic plasticity, underlie the associated impairments in cognition after CCH. We found that RasGRF1 levels markedly decreased following CCH. Through prediction and validation studies, we observed that miRNA-323-3p was upregulated after CCH and could bind to the 3'-untranslated region of Rasgrf1 mRNA and regulate its expression in vitro. Moreover, the inhibition of miRNA-323-3p upregulated Rasgrf1 expression in the hippocampus after CCH, which was reversed by Rasgrf1 siRNA. This suggests that miRNA-323-3p is an important regulator of Rasgrf1. The Morris water maze and Y maze tests showed that miRNA-323-3p inhibition and Rasgrf1 upregulation improved spatial learning and memory, and electrophysiological measurements revealed deficits in long-term potentiation after CCH that were reversed by Rasgrf1 upregulation. Dendritic spine density and mature mushroom spine density were also improved after miRNA-323-3p inhibition and Rasgrf1 upregulation. Furthermore, Rasgrf1 upregulation by miRNA-323-3p inhibition improved dendritic spine density and mature mushroom spine density and ameliorated the deterioration of synapses and postsynaptic density. Overall, RasGRF1 regulation attenuated cognitive impairment, helped maintain structural and functional synaptic plasticity, and prevented synapse deterioration after CCH. These results suggest that Rasgrf1 downregulation by miRNA-323-3p plays an important role in cognitive impairment after CCH. Thus, RasGRF1 and miRNA-323-3p may represent potential therapeutic targets for cognitive impairment after CCH.

Electrical stimulation therapy for peripheral nerve injury.

Peripheral nerve injury is common and frequently occurs in extremity trauma patients. The motor and sensory impairment caused by the injury will affect patients' daily life and social work. Surgical therapeutic approaches don't assure functional recovery, which may lead to neuronal atrophy and hinder accelerated regeneration. Rehabilitation is a necessary stage for patients to recover better. A meaningful role in non-pharmacological intervention is played by rehabilitation, through individualized electrical stimulation therapy. Clinical studies have shown that electrical stimulation enhances axon growth during nerve repair and accelerates sensorimotor recovery. According to different effects and parameters, electrical stimulation can be divided into neuromuscular, transcutaneous, and functional electrical stimulation. The therapeutic mechanism of electrical stimulation may be to reduce muscle atrophy and promote muscle reinnervation by increasing the expression of structural protective proteins and neurotrophic factors. Meanwhile, it can modulate sensory feedback and reduce neuralgia by inhibiting the descending pathway. However, there are not many summary clinical application parameters of electrical stimulation, and the long-term effectiveness and safety also need to be further explored. This article aims to explore application methodologies for effective electrical stimulation in the rehabilitation of peripheral nerve injury, with simultaneous consideration for fundamental principles of electrical stimulation and the latest technology. The highlight of this paper is to identify the most appropriate stimulation parameters (frequency, intensity, duration) to achieve efficacious electrical stimulation in the rehabilitation of peripheral nerve injury.

Ultrahigh-sensitivity multi-parameter tacrolimus solution detection based on an anchor planar millifluidic microwave biosensor.

To detect drug concentration in tacrolimus solution, an anchor planar millifluidic microwave (APMM) biosensor is proposed. The millifluidic system integrated with the sensor enables accurate and efficient detection while eliminating interference caused by the fluidity of the tacrolimus sample. Different concentrations (10-500 ng mL-1) of the tacrolimus analyte were introduced into the millifluidic channel, where it completely interacts with the radio frequency patch electromagnetic field, thereby effectively and sensitively modifying the resonant frequency and amplitude of the transmission coefficient. Experimental results indicate that the sensor has an extremely low limit of detection (LoD) of 0.12 pg mL-1 and a frequency detection resolution (FDR) of 1.59 (MHz (ng mL-1)). The greater the FDR and the lower the LoD, the more the feasibility of a label-free biosensing method. Regression analysis revealed a strong linear correlation (R2 = 0.992) between the concentration of tacrolimus and the frequency difference of the two resonant peaks of APMM. In addition, the difference in the reflection coefficient between the two formants was measured and calculated, and a strong linear correlation (R2 = 0.998) was found between the difference and tacrolimus concentration. Five measurements were performed on each individual sample of tacrolimus to validate the biosensor's high repeatability. Consequently, the proposed biosensor is a potential candidate for the early detection of tacrolimus drug concentration levels in organ transplant recipients. This study presents a simple method for constructing microwave biosensors with high sensitivity and rapid response.

Virtual elastography ultrasound via generative adversarial network for breast cancer diagnosis.

Elastography ultrasound (EUS) imaging is a vital ultrasound imaging modality. The current use of EUS faces many challenges, such as vulnerability to subjective manipulation, echo signal attenuation, and unknown risks of elastic pressure in certain delicate tissues. The hardware requirement of EUS also hinders the trend of miniaturization of ultrasound equipment. Here we show a cost-efficient solution by designing a deep neural network to synthesize virtual EUS (V-EUS) from conventional B-mode images. A total of 4580 breast tumor cases were collected from 15 medical centers, including a main cohort with 2501 cases for model establishment, an external dataset with 1730 cases and a portable dataset with 349 cases for testing. In the task of differentiating benign and malignant breast tumors, there is no significant difference between V-EUS and real EUS on high-end ultrasound, while the diagnostic performance of pocket-sized ultrasound can be improved by about 5% after V-EUS is equipped.

High-Resolution Magnetoelectric Sensor and Low-Frequency Measurement Using Frequency Up-Conversion Technique.

The magnetoelectric (ME) sensor is a new type of magnetic sensor with ultrahigh sensitivity that suitable for the measurement of low-frequency weak magnetic fields. In this study, a metglas/PZT-5B ME sensor with mechanical resonance frequency fres of 60.041 kHz was prepared. It is interesting to note that its magnetic field resolution reached 0.20 nT at fres and 0.34 nT under a DC field, respectively. In order to measure ultralow-frequency AC magnetic fields, a frequency up-conversion technique was employed. Using this technique, a limit of detection (LOD) under an AC magnetic field lower than 1 nT at 8 Hz was obtained, and the minimum LOD of 0.51 nT was achieved at 20 Hz. The high-resolution ME sensor at the sub-nT level is promising in the field of low-frequency weak magnetic field measurement technology.

Pressure-Tuned Multicolor Emission of 2D Lead Halide Perovskites with Ultrahigh Color Purity.

The chemical diversity and structural flexibility of lead halide perovskites (LHPs) offer tremendous opportunities to tune their optical properties through internal molecular engineering and external stimuli. Herein, we report the wide-range and ultrapure photoluminescence emissions in a family of homologous 2D LHPs, [MeOPEA]2 PbBr4-4x I4x (MeOPEA=4-methoxyphenethylammonium; x=0, 0.2, 0.425, 0.575, 1) enabled through internal chemical pressure and external hydrostatic pressure. The chemical pressure, induced by the C-H⋅⋅⋅π interactions and halogen doping/substitution strengthens the structural rigidity to give sustained narrow emissions, and regulates the emission energy, respectively. Further manipulation of physical pressure leads to wide-range emission tuning from 412 to 647 nm in a continuous and reversible manner. This work could open up new pathways for developing 2D LHP emitters with ultra-wide color gamut and high color purity which are highly useful for pressure sensing.