N-acetylglucosamine kinase (BbHxk1) has pleiotropic effects on vegetative growth, cell wall integrity, morphological transition, cuticle infection, and metabolic modulation in the biological pesticide Beauveria bassiana.

Beauveria bassiana is a popular and eco-friendly biopesticide. During its pathogen-pest interaction, both N-acetylglucosamine (GlcNAc) catabolism and anabolism are crucial for nutrient supply and cell-wall construction. The initiation of GlcNAc metabolism relies on the catalysis of GlcNAc kinase, which has been extensively studied in the human pathogen Candida albicans. However, the physiological function of GlcNAc kinase remains poorly understood in entomopathogenic fungi. In the present study, a GlcNAc kinase homolog was identified and designated as BbHxk1 in B. bassiana. Deletion of BbHxk1 resulted in viable but reduced vegetative growth on various carbon sources. ΔBbHxk1 mutants displayed severe defects in cell wall integrity, making them more susceptible to cell wall stress cues. Furthermore, the absence of BbHxk1 resulted in an increase in conidial yield and blastospore production, and a faster rate of germination and filamentation, potentially attributed to higher intracellular ATP levels. BbHxk1 deficiency led to a reduction in the activities of cuticle-degrading enzymes, which might contribute to the attenuated pathogenicity specifically through cuticle penetration rather than hemocoel infection towards Galleria mellonella larvae. Being different from C. albicans Hxk1, which facultatively acts as a catalyzing enzyme and transcriptional regulator, BbHxk1 primarily acts as a catalyzing enzyme and metabolic regulator. The altered metabolomic profiling correlated with the phenotypic defects in ΔBbHxk1 mutants, further implicating a potential metabolism-dependent mechanism of BbHxk1 in mediating physiologies of B. bassiana. These findings not only unveil a novel role for GlcNAc kinase in B. bassiana, but also provide a solid theoretical basis to guide metabolic reprogramming in order to maintain or even enhance the efficiency of fungi for practical applications.

Essential roles of Rad6 in conidial property, stress tolerance, and pathogenicity of Beauveria bassiana.

Rad6 functions as a ubiquitin-conjugating protein that regulates cellular processes in many fungal species. However, its role in filamentous entomopathogenic fungi remains poorly understood. This study characterizes Rad6 in Beauveria bassiana, a filamentous fungus widely employed as a critical fungicide globally. The results demonstrate a significant association between Rad6 and conidial properties, heat shock response, and UV-B tolerance. Concurrently, the mutant strain exhibited heightened sensitivity to oxidative stress, cell wall interfering agents, DNA damage stress, and prolonged heat shock. Furthermore, the absence of Rad6 significantly extended the median lethal time (LT50) of Galleria mellonella infected by B. bassiana. This delay could be attributed to reduced Pr1 proteases and extracellular cuticle-degrading enzymes, diminished dimorphic transition rates, and dysregulated antioxidant enzymes. Additionally, the absence of Rad6 had a more pronounced effect on genetic information processing, metabolism, and cellular processes under normal conditions. However, its impact was limited to metabolism in oxidative stress. This study offers a comprehensive understanding of the pivotal roles of Rad6 in conidial and hyphal stress tolerance, environmental adaptation, and the pathogenesis of Beauveria bassiana.

A complex metabolic network and its biomarkers regulate laccase production in white-rot fungus Cerrena unicolor 87613.

BACKGROUND: White-rot fungi are known to naturally produce high quantities of laccase, which exhibit commendable stability and catalytic efficiency. However, their laccase production does not meet the demands for industrial-scale applications. To address this limitation, it is crucial to optimize the conditions for laccase production. However, the regulatory mechanisms underlying different conditions remain unclear. This knowledge gap hinders the cost-effective application of laccases. RESULTS: In this study, we utilized transcriptomic and metabolomic data to investigate a promising laccase producer, Cerrena unicolor 87613, cultivated with fructose as the carbon source. Our comprehensive analysis of differentially expressed genes (DEGs) and differentially abundant metabolites (DAMs) aimed to identify changes in cellular processes that could affect laccase production. As a result, we discovered a complex metabolic network primarily involving carbon metabolism and amino acid metabolism, which exhibited contrasting changes between transcription and metabolic patterns. Within this network, we identified five biomarkers, including succinate, serine, methionine, glutamate and reduced glutathione, that played crucial roles in co-determining laccase production levels. CONCLUSIONS: Our study proposed a complex metabolic network and identified key biomarkers that determine the production level of laccase in the commercially promising Cerrena unicolor 87613. These findings not only shed light on the regulatory mechanisms of carbon sources in laccase production, but also provide a theoretical foundation for enhancing laccase production through strategic reprogramming of metabolic pathways, especially related to the citrate cycle and specific amino acid metabolism.

A rapid and simple non-radioactive assay for measuring uptake by solute carrier transporters.

Introduction: Solute carrier (SLC) transport proteins play a crucial role in maintaining cellular nutrient and metabolite homeostasis and are implicated in various human diseases, making them potential targets for therapeutic interventions. However, the study of SLCs has been limited due to the lack of suitable tools, particularly cell-based substrate uptake assays, necessary for understanding their biological functions and for drug discovery purposes. Methods: In this study, a cell-based uptake assay was developed using a stable isotope-labeled compound as the substrate for SLCs, with detection facilitated by liquid chromatography-tandem mass spectrometry (LC-MS/MS). This assay aimed to address the limitations of existing assays, such as reliance on hazardous radiolabeled substrates and limited availability of fluorescent biosensors. Results: The developed assay was successfully applied to detect substrate uptakes by two specific SLCs: L-type amino acid transporter 1 (LAT1) and sodium taurocholate co-transporting polypeptide (NTCP). Importantly, the assay demonstrated comparable results to the radioactive method, indicating its reliability and accuracy. Furthermore, the assay was utilized to screen for novel inhibitors of NTCP, leading to the identification of a potential NTCP inhibitor compound. Discussion: The findings highlight the utility of the developed cell-based uptake assay as a rapid, simple, and environmentally friendly tool for investigating SLCs' biological roles and for drug discovery purposes. This assay offers a safer alternative to traditional methods and has the potential to contribute significantly to advancing our understanding of SLC function and identifying therapeutic agents targeting SLC-mediated pathways.

Ascorbic acid enhanced the circulation between Fe(II) and Fe(III) in peroxymonosulfate system for fluoranthene degradation.

In this research, ascorbic acid (AA) was used to enhance Fe(II)/Fe(III)-activated permonosulfate (PMS) systems for the degradation of fluoranthene (FLT). AA enhanced the production of ROS in both PMS/Fe(II) and PMS/Fe(III) systems through chelation and reduction and thus improved the degradation performance of FLT. The optimal molar ratio in PMS/Fe(II)/AA/FLT and PMS/Fe(III)/AA/FLT processes were 2/2/4/1 and 5/10/5/1, respectively. In addition, the experimental results on the effect of FLT degradation under different groundwater matrixes indicated that PMS/Fe(III)/AA system was more adaptable to different water quality conditions than the PMS/Fe(II)/AA system. SO4·- was the major reactive oxygen species (ROS) responsible for FLT removal through the probe and scavenging tests in both systems. Furthermore, the degradation intermediates of FLT were analyzed using gas chromatograph-mass spectrometry (GC-MS), and the probable degradation pathways of FLT degradation were proposed. In addition, the removal of FLT was also tested in actual groundwater and the results showed that by increasing the dose and pre-adjusting the solution pH, 88.8 and 100% of the FLT was removed for PMS/Fe(II)/AA and PMS/Fe(III)/AA systems. The above experimental results demonstrated that PMS/Fe(II)/AA and PMS/Fe(III)/AA processes have a great perspective in practice for the rehabilitation of FLT-polluted groundwater.

The identification of signature genes and their relationship with immune cell infiltration in age-related macular degeneration.

BACKGROUND: Age-related macular degeneration (AMD) is a prevalent source of visual impairment among the elderly population, and its incidence has risen in tandem with the increasing longevity of humans. Despite the progress made with anti-VEGF therapy, clinical outcomes have proven to be unsatisfactory. METHOD: We obtained differentially expressed genes (DEGs) of AMD patients and healthy controls from the GEO database. GO and KEGG analyses were used to enrich the DEGs. Weighted gene coexpression network analysis (WGCNA) was used to identify modules related to AMD. SVM, random forest, and least absolute shrinkage and selection operator (LASSO) were employed to screen hub genes. Gene set enrichment analysis (GSEA) was used to explore the pathways in which these hub genes were enriched. CIBERSORT was utilized to analyze the relationship between the hub genes and immune cell infiltration. Finally, Western blotting and RT‒PCR were used to explore the expression of hub genes in AMD mice. RESULTS: We screened 1084 DEGs in GSE29801, of which 496 genes were upregulated. These 1084 DEGs were introduced into the WGCNA, and 94 genes related to AMD were obtained. Seventy-nine overlapping genes were obtained by the Venn plot. These 79 genes were introduced into three machine-learning methods to screen the hub genes, and the genes identified by the three methods were TNC, FAP, SREBF1, and TGF-ß2. We verified their diagnostic function in the GSE29801 and GSE103060 datasets. Then, the hub gene co-enrichment pathways were obtained by GO and KEGG analyses. CIBERSORT analysis showed that these hub genes were associated with immune cell infiltration. Finally, we found increased expression of TNC, FAP, SREBF1, and TGF-ß2 mRNA and protein in the retinas of AMD mice. CONCLUSION: We found that four hub genes, namely, FAP, TGF-ß2, SREBF1, and TNC, have diagnostic significance in patients with AMD and are related to immune cell infiltration. Finally, we determined that the mRNA and protein expression of these hub genes was upregulated in the retinas of AMD mice.

EMG-Constrained and Ultrasound-Informed Muscle-Tendon Parameter Estimation in Post-Stroke Hemiparesis.

Secondary morphological and mechanical property changes in the muscle-tendon unit at the ankle joint are often observed in post-stroke individuals. These changes may alter the force generation capacity and affect daily activities such as locomotion. This work aimed to estimate subject-specific muscle-tendon parameters in individuals after stroke by solving the muscle redundancy problem using direct collocation optimal control methods based on experimental electromyography (EMG) signals and measured muscle fiber length. Subject-specific muscle-tendon parameters of the gastrocnemius, soleus, and tibialis anterior were estimated in seven post-stroke individuals and seven healthy controls. We found that the maximum isometric force, tendon stiffness and optimal fiber length in the post-stroke group were considerably lower than in the control group. We also computed the root mean square error between estimated and experimental values of muscle excitation and fiber length. The musculoskeletal model with estimated subject-specific muscle tendon parameters (from the muscle redundancy solver), yielded better muscle excitation and fiber length estimations than did scaled generic parameters. Our findings also showed that the muscle redundancy solver can estimate muscle-tendon parameters that produce force behavior in better accordance with the experimentally-measured value. These muscle-tendon parameters in the post-stroke individuals were physiologically meaningful and may shed light on treatment and/or rehabilitation planning.

Edge-by-Edge Lateral Heterostructure through Interfacial Sliding.

van der Waals heterostructures (vdWHs) based on two-dimensional (2D) semiconductors have attracted considerable attention. However, the reported vdWHs are largely based on vertical device structure with large overlapping area, while the realization of lateral heterostructures contacted through 2D edges remains challenging and is majorly limited by the difficulties of manipulating the lateral distance of 2D materials at nanometer scale (during transfer process). Here, we demonstrate a simple interfacial sliding approach for realizing an edge-by-edge lateral contact. By stretching a vertical vdWH, two 2D flakes could gradually slide apart or toward each other. Therefore, by applying proper strain, the initial vertical vdWH could be converted into a lateral heterojunction with intimately contacted 2D edges. The lateral contact structure is supported by both microscope characterization and in situ electrical measurements, exhibiting carrier tunneling behavior. Finally, this approach can be extended to 3D thin films, as demonstrated by the lateral 2D/3D and 3D/3D Schottky junction.

Transcriptomic and metabolomic analysis unveils a negative effect of glutathione metabolism on laccase activity in Cerrena unicolor 87613.

The white rot fungus Cerrena unicolor 87613 has been previously shown to be a promising resource in laccase production, an enzyme with significant biotechnological applications. Conventional methods face technical challenges in improving laccase activity. Attempts are still being made to develop novel approaches for further enhancing laccase activity. This study aimed to understand the regulation of laccase activity in C. unicolor 87613 for a better exploration of the novel approach. Transcriptomic and metabolomic analyses were performed to identify key genes and metabolites involved in extracellular laccase activity. The findings indicated a strong correlation between the glutathione metabolism pathway and laccase activity. Subsequently, experimental verifications were conducted by manipulating the pathway using chemical approaches. The additive reduced glutathione (GSH) dose-dependently repressed laccase activity, while the GSH inhibitors (APR-246) and reactive oxygen species (ROS) inducer (H2O2) enhanced laccase activity. Changes in GSH levels could determine the intracellular redox homeostasis in interaction with ROS and partially affect the expression level of laccase genes in C. unicolor 87613 in turn. In addition, GSH synthetase was found to mediate GSH abundance in a feedback loop. This study suggests that laccase activity is negatively influenced by GSH metabolism and provides a theoretical basis for a novel strategy to enhance laccase activity by reprogramming glutathione metabolism at a specific cultivation stage.IMPORTANCEThe production of laccase activity is limited by various conventional approaches, such as heterologous expression, strain screening, and optimization of incubation conditions. There is an urgent need for a new strategy to meet industrial requirements more effectively. In this study, we conducted a comprehensive analysis of the transcriptome and metabolome of Cerrena unicolor 87613. For the first time, we discovered a negative role played by reduced glutathione (GSH) and its metabolic pathway in influencing extracellular laccase activity. Furthermore, we identified a feedback loop involving GSH, GSH synthetase gene, and GSH synthetase within this metabolic pathway. These deductions were confirmed through experimental investigations. These findings not only advanced our understanding of laccase activity regulation in its natural producer but also provide a theoretical foundation for a strategy to enhance laccase activity by reprogramming glutathione metabolism at a specific cultivation stage.

Development of a ferroptosis-based molecular markers for predicting RFS in prostate cancer patients.

The goal of this study was to develop a ferroptosis-based molecular signature that can predict recurrence-free survival (RFS) in patients with prostate cancer (PCa). In this study, we obtained ferroptosis-related genes (FRGs) in FerrDb database and clinical transcriptome data in TCGA database and GEO database. Consensus cluster analysis was used to identify three molecular markers of ferroptosis in PCa with differential expression of 40 FRGs, including PD-L1 expression levels. We conducted a new ferroptosis-related signature for PCa RFS using four FRGs identified through univariate and multivariate Cox regression analyses. The signature was validated in the training, testing, and validation cohorts, and it demonstrated remarkable results in the area under the time-dependent receiver operating characteristic (ROC) curve of 0.757, 0.715, and 0.732, respectively. Additionally, we observed that younger patients, those with stage T III and stage T IV, stage N0, cluster 1, and cluster 2 PCa were more accurately predicted by the signature as independent predictors of RFS. DU-145 and RWPE-1 cells were successfully analyzed by qRT-PCR and Western blot for ASNS, GPT2, RRM2, and NFE2L2. In summary, we developed a novel ferroptosis-based signature for RFS in PC, utilizing four FRGs identified through univariate and multivariate Cox regression analyses. This signature was rigorously validated across training, testing, and validation cohorts, demonstrating exceptional performance as evidenced by its ROC curves. Notably, our findings indicate that this signature is particularly effective as an independent predictor of RFS in younger patients or those with stage T III and T IV, stage N0, and in clusters 1 and 2. Finally, we confirmed the expression of these four FRGs in DU-145 and RWPE-1 cell lines.

Neuromusculoskeletal model-informed machine learning-based control of a knee exoskeleton with uncertainties quantification.

Introduction: Research interest in exoskeleton assistance strategies that incorporate the user's torque capacity is growing rapidly. However, the predicted torque capacity from users often includes uncertainty from various sources, which can have a significant impact on the safety of the exoskeleton-user interface. Methods: To address this challenge, this paper proposes an adaptive control framework for a knee exoskeleton that uses muscle electromyography (EMG) signals and joint kinematics. The framework predicted the user's knee flexion/extension torque with confidence bounds to quantify the uncertainty based on a neuromusculoskeletal (NMS) solver-informed Bayesian Neural Network (NMS-BNN). The predicted torque, with a specified confidence level, controlled the assistive torque provided by the exoskeleton through a TCP/IP stream. The performance of the NMS-BNN model was also compared to that of the Gaussian process (NMS-GP) model. Results: Our findings showed that both the NMS-BNN and NMS-GP models accurately predicted knee joint torque with low error, surpassing traditional NMS models. High uncertainties were observed at the beginning of each movement, and at terminal stance and terminal swing in self-selected speed walking in both NMS-BNN and NMS-GP models. The knee exoskeleton provided the desired assistive torque with a low error, although lower torque was observed during terminal stance of fast walking compared to self-selected walking speed. Discussion: The framework developed in this study was able to predict knee flexion/extension torque with quantifiable uncertainty and to provide adaptive assistive torque to the user. This holds significant potential for the development of exoskeletons that provide assistance as needed, with a focus on the safety of the exoskeleton-user interface.

Estimation of Joint Torque by EMG-Driven Neuromusculoskeletal Models and LSTM Networks.

Accurately predicting joint torque using wearable sensors is crucial for designing assist-as-needed exoskeleton controllers to assist muscle-generated torque and ensure successful task performance. In this paper, we estimated ankle dorsiflexion/plantarflexion, knee flexion/extension, hip flexion/extension, and hip abduction/adduction torques from electromyography (EMG) and kinematics during daily activities using neuromusculoskeletal (NMS) models and long short-term memory (LSTM) networks. The joint torque ground truth for model calibrating and training was obtained through inverse dynamics of captured motion data. A cluster approach that grouped movements based on characteristic similarity was implemented, and its ability to improve the estimation accuracy of both NMS and LSTM models was evaluated. We compared torque estimation accuracy of NMS and LSTM models in three cases: Pooled, Individual, and Clustered models. Pooled models used data from all 10 movements to calibrate or train one model, Individual models used data from each individual movement, and Clustered models used data from each cluster. Individual, Clustered and Pooled LSTM models all had relatively high joint torque estimation accuracy. Individual and Clustered NMS models had similarly good estimation performance whereas the Pooled model may be too generic to satisfy all movement patterns. While the cluster approach improved the estimation accuracy in NMS models in some movements, it made relatively little difference in the LSTM neural networks, which already had high estimation accuracy. Our study provides practical implications for designing assist-as-needed exoskeleton controllers by offering guidelines for selecting the appropriate model for different scenarios, and has potential to enhance the functionality of wearable exoskeletons and improve rehabilitation and assistance for individuals with motor disorders.

Genome-wide study of Cerrena unicolor 87613 laccase gene family and their mode prediction in association with substrate oxidation.

BACKGROUND: Laccases are green biocatalysts with wide industrial applications. The study of efficient and specific laccase producers remains a priority. Cerrena species have been shown to be promising basidiomycete candidates for laccase production. Although two sets of Cerrena genome data have been publicly published, no comprehensive bioinformatics study of laccase gene family in C. unicolor has been reported, particularly concerning the analysis of their three-dimensional (3D) structures and molecular docking to substrates, like ABTS and aflatoxin B1 (AFB1). RESULTS: In this study, we conducted a comprehensive genome-wide analysis of laccase gene family in C. unicolor 87613. We identified eighteen laccase genes (CuLacs) and classified them into three clades using phylogenetic analysis. We characterized these laccases, including their location in contig 5,6,9,12,15,19,26,27, gene structures of different exon-intron arrangements, molecular weight ranging from 47.89 to 141.41 kDa, acidic pI value, 5-15 conserved protein motifs, signaling peptide of extracellular secretion (harbored by 13 CuLacs) and others. In addition, the analysis of cis-acting element in laccase promoters indicated that the transcription response of CuLac gene family was regulatable and complex under different environmental cues. Furthermore, analysis of transcription pattern revealed that CuLac8, 12 and CuLac2, 13 were the predominant laccases in response to copper ions or oxidative stress, respectively. Finally, we focused on the 3D structure analysis of CuLac proteins. Seven laccases with extra transmembrane domains or special sequences were particularly interesting. Predicted structures of each CuLac protein with or without these extra sequences showed altered interacting amino acid residues and binding sites, leading to varied affinities to both ABTS and AFB1. As far as we know, it is the first time to discuss the influence of the extra sequence on laccase's affinity to substrates. CONCLUSIONS: Our findings provide robust genetic data for a better understanding of the laccase gene family in C. unicolor 87613, and create a foundation for the molecular redesign of CuLac proteins to enhance their industrial applications.

Corrigendum: Prostaglandin reductase 1 as a potential therapeutic target for cancer therapy.

[This corrects the article DOI: 10.3389/fphar.2021.717730.].

Characterisation of a laccase isolated from Trametes hirsuta and its application in the oligomerisation of phenolic compounds.

Phenolic compounds are widely distributed in nature and industrial environment, and their detoxification or bioactive enhancement is of great value to environmental protection and industrial development. Laccases are multicopper oxidases that catalyse the oligo- or polymerisation of phenolic compounds. Identifying new laccase producers and investigating their application potential are of great importance. In this study, a white-rot fungus, Trametes hirsuta EZ1, with significantly high laccase productivity was isolated. The optimum conditions were studied for the maximum fermentation of extracellular laccase, which was achieved at 150 U/mL with a medium containing 10% strain EZ1, 7% maltodextrin, 1.5% peptone, and 0.5 mM Cu2+, and incubation at initial pH 6.0, 32 °C, and 180 rpm for nine days. Subsequently, a 70-kDa laccase was purified that showed activity over a wide range of temperature and pH, sensitivity to many metal ions and sodium dodecyl sulphate, and high tolerance to organic solvents. Purified laccase showed a significant unreported effect by catalysing catechol or ferulic acid into dimers, trimers, and tetramers or caffeic acid into dimers, trimers, tetramers, and pentamers. The oligomeric mixtures exhibited increased antioxidative capacity compared to that of each parent monomer, except for caffeic acid derivatives. Our study offers a novel strain source for laccase production and broadens its application in the enhancement of bioactive compounds.

Arch-related alteration in foot loading patterns affected by the increasing extent of body mass index in children: A follow-up study.

BACKGROUND: A high load on children 's feet can cause arch deformation and negatively affect their normal development. Studies have yet to document how the foot arch varied with different body mass index (BMI) increments and its influence on foot loading patterns. METHODS: Barefoot walking trails were conducted using a Footscan® plate system. A follow-up check was performed after twenty-four months. Participants were selected with an initial BMI between 14.5 kg/m2 and 16.5 kg/m2. Totally 75 participants were classified into groups 0-7 according to the BMI increment levels of 0-0.49 kg/m2, 0.50-1.49 kg/m2, 1.50-2.49 kg/m2, 2.50-3.49 kg/m2, 3.50-4.49 kg/m2, 4.50-5.49 kg/m2, 5.50-6.49 kg/m2, 6.50-7.49 kg/m2, respectively. Paired t-tests and effect sizes were used to compare the data. RESULTS: The arch index significantly decreased when the BMI reached 20.8 kg/m2. Significantly increased normalized maximum forces were found in the great toe and 1st MTPJ in groups 4-5. Meanwhile, the absence of significance showed under the 3rd-5th, midfoot, and rearfoot in those groups. The normalized maximum force increments under the 3rd-5th MTPJs, midfoot and rearfoot regions in groups 4-5 after the follow-up study were significantly decreased compared with the increments found in groups 0-3, followed by a sudden increase arising under those regions in group 6. It indicates a transition period that leads to alteration in gait pattern characteristics when BMI increases to 18.6-19.9 kg/m2 (between group 3 and group 4). Group 6 displayed significantly increased peak pressure amplitudes under the great toe, 1st-3rd MTPJs, midfoot, and medial rearfoot compared to other groups. SIGNIFICANCE: There was a transition period when the BMI of normal-weighted children increased to a certain extent and failed to reach the obesity level, resulting in changes in foot arch structure and loading patterns.

Development of a monitoring system for disassembled towers with internal suspension poles.

The traditional construction monitoring methods of suspended pole-mounted decomposed towers are mostly manual monitoring. The monitoring personnel has multiple blind spots, and the possibility of misjudgment based on personal experience is relatively large. It is difficult to ensure the construction safety of the suspended pole decomposing tower. For this reason, combined with the current power Internet of Things technology, this paper develops an intelligent monitoring system for suspended pole-mounted decomposing towers. According to the construction technology and its safety requirements of inner suspension derrick for transmission tower erection in sections, this system is classified into intellisense layer, wireless transport layer and information integration layer. According to the physical characteristics of the seven major risk points of the inner suspension pole group tower, the intellisense layer developed corresponding sensing equipment to obtain risk information. In the wireless transport layer, the ZigBee and 4G communication technologies are selected to interconnect self-constituted LAN and 4G wide area networks, to complete on-site data interaction and long-distance transmission. In the information integration layer, the force of cable, the inclination and height of derrick, and the distance between derrick and tower are determined. The system has been verified by the 500 kV delivery project of Fujian Zhouning Pumped Storage Power Station. The average error of critical monitoring point data is 4.14%, and the average data transmission delays in the far and near fields of the system are 18 ms and 176 ms.

Ankle Joint Torque Prediction Using an NMS Solver Informed-ANN Model and Transfer Learning.

In this work, we predicted ankle joint torque by combining a neuromusculoskeletal (NMS) solver-informed artificial neural network (hybrid-ANN) model with transfer learning based on joint angle and muscle electromyography signals. The hybrid-ANN is an ANN augmented with two kinds of features: 1) experimental measurements - muscle signals and joint angles, and 2) informative physical features extracted from the underlying NMS solver, such as individual muscle force and joint torque. The hybrid-ANN model accuracy in torque prediction was studied in both intra- and inter-subject tests, and compared to the baseline models (NMS and standard-ANN). For each prediction model, seven different cases were studied using data from gait at different speeds and from isokinetic ankle dorsi/plantarflexion motion. Additionally, we integrated a transfer learning method in inter-subject models to improve joint torque prediction accuracy by transferring the learned knowledge from previous participants to a new participant, which could be useful when training data is limited. Our results indicated that better accuracy could be obtained by integrating informative NMS features into a standard ANN model, especially in inter-subject cases; overall, the hybrid-ANN model predicted joint torque with higher accuracy than the baseline models, most notably in inter-subject prediction after adopting the transfer learning technique. We demonstrated the potential of combining physics-based NMS and standard-ANN models with a transfer learning technique in different prediction scenarios. This procedure holds great promise in applications such as assistance-as-needed exoskeleton control strategy design by incorporating the physiological joint torque of the users.