iP3T: an interpretable multimodal time-series model for enhanced gait phase prediction in wearable exoskeletons.

Introduction: Wearable exoskeletons assist individuals with mobility impairments, enhancing their gait and quality of life. This study presents the iP3T model, designed to optimize gait phase prediction through the fusion of multimodal time-series data. Methods: The iP3T model integrates data from stretch sensors, inertial measurement units (IMUs), and surface electromyography (sEMG) to capture comprehensive biomechanical and neuromuscular signals. The model's architecture leverages transformer-based attention mechanisms to prioritize crucial data points. A series of experiments were conducted on a treadmill with five participants to validate the model's performance. Results: The iP3T model consistently outperformed traditional single-modality approaches. In the post-stance phase, the model achieved an RMSE of 1.073 and an R2 of 0.985. The integration of multimodal data enhanced prediction accuracy and reduced metabolic cost during assisted treadmill walking. Discussion: The study highlights the critical role of each sensor type in providing a holistic understanding of the gait cycle. The attention mechanisms within the iP3T model contribute to its interpretability, allowing for effective optimization of sensor configurations and ultimately improving mobility and quality of life for individuals with gait impairments.

A Novel Personalized Strategy for Hip Joint Flexion Assistance Based on Human Physiological State.

Soft exosuits have emerged as potent assistive tools for walking support and rehabilitation training. However, most existing soft exosuit systems rely on preset assistance modes, which may not accurately align with individual physiological states and movement requirements, leading to variable user experiences and efficacy. While existing human-in-the-loop (HIL) research predominantly focuses on optimizing metabolic cost and torque difference parameters, there is a notable absence of real-time monitoring methods that closely reflect the human body's physiological state and strategies that dynamically indicate walking efficiency. Motivated by this, we developed a novel personalized power-assist system. This system optimizes the power-assist output of the hip joint by monitoring the user's physiological and motion signals in real time, including heart rate (HR), blood oxygen saturation (SpO2), and inertial measurement unit (IMU) data, to assist hip flexion based on feedback. The findings from a metabolic expenditure trial demonstrate that the innovative soft exosuit, which is based on a Physiological State Monitoring Control (PSMC) system, achieves a reduction of 7.81% in metabolic expenditure during treadmill walking at a speed of 3.5 km/h compared to walking without the assistance of the exosuit. Additionally, during continuous exercise with varying intensities, the metabolic consumption level is reduced by 5.1%, 5.8%, and 8.2% at speeds of 2, 4, and 6 km per hour, respectively. These results support the design of a novel hip flexion-assisting soft exosuit, demonstrating that applying different assistance forces in consideration of different physiological states is a reasonable approach to reducing metabolic consumption.

3-ketoacyl-CoA synthase 19 contributes to the biosynthesis of seed lipids and cuticular wax in Arabidopsis and abiotic stress tolerance.

Very-long-chain fatty acids (VLCFAs) are essential precursors for plant membrane lipids, cuticular waxes, suberin, and storage oils. Integral to the fatty acid elongase (FAE) complex, 3-ketoacyl-CoA synthases (KCSs) function as crucial enzymes in the VLCFA pathway, determining the chain length of VLCFA. This study explores the in-planta role of the KCS19 gene. KCS19 is predominantly expressed in leaves and stem epidermis, sepals, styles, early silique walls, beaks, pedicels, and mature embryos. Localized in the endoplasmic reticulum, KCS19 interacts with other FAE proteins. kcs19 knockout mutants displayed reduced total wax and wax crystals, particularly alkanes, while KCS19 overexpression increased these components and wax crystals. Moreover, the cuticle permeability was higher for the kcs19 mutants compared to the wild type, rendering them more susceptible to drought and salt stress, whereas KCS19 overexpression enhanced drought and salt tolerance. Disrupting KCS19 increased C18 species and decreased C20 and longer species in seed fatty acids, indicating its role in elongating C18 to C20 VLCFAs, potentially up to C24 for seed storage lipids. Collectively, KCS19-mediated VLCFA synthesis is required for cuticular wax biosynthesis and seed storage lipids, impacting plant responses to abiotic stress.

Effects of vitrectomy combined with internal limiting membrane peeling in patients with diabetic macular edema.

BACKGROUND: Diabetic macular edema (DME), a chronic microvascular complication of diabetes, is a leading cause of visual impairment and blindness. Pars plana vitrectomy (PPV) can restore the normal macular structure and reduce macular edema, whereas internal limiting membrane (ILM) peeling is used to treat tractional macular diseases. Despite the advantages, there is limited research on the combined effects of PPV with ILM peeling. AIM: To observe the effects of PPV combined with ILM peeling on postoperative central macular thickness (CMT), best-corrected visual acuity (BCVA), cystoid macular edema (CME) volume, and complications in patients with DME. METHODS: Eighty-one patients (92 eyes) diagnosed with DME at the Beijing Shanqu Liangxiang Hospital between January and December 2022 were randomly divided to undergo PPV alone (control group: 41 patients, 47 eyes) or PPV + ILM peeling (stripping group: 40 patients, 45 eyes); a single surgeon performed all surgeries. The two groups were compared preoperatively and 1 and 3 months postoperatively. RESULTS: Preoperatively, both groups had comparable values of CMT, BCVA, and CME volume (P > 0.05). After surgery (both 1 and 3 months), both groups showed significant reductions in CMT, BCVA, and CME volume compared to preoperative levels, with the stripping group showing more significant reductions compared to the control group (P < 0.05). Further repeated-measures ANOVA analysis for within-group differences revealed significant effects of group and time, and interaction effects for CMT, BCVA, and CME volume (P < 0.05). There were no significant differences in the incidence of complications between the groups (retinal detachment: control = 2, stripping = 1; endophthalmitis: Control = 4, stripping = 1; no cases of secondary glaucoma or macular holes; χ 2 = 0.296, P = 0.587). CONCLUSION: PPV with ILM peeling can significantly improve the visual acuity of patients with DME, reduce CMT, and improve CME with fewer complications.

Effects of cold acclimation on serum biochemical parameters and metabolite profiles in Schizothorax prenanti.

BACKGROUND: Environmental temperature is critical in regulating biological functions in fish. S. prenanti is a kind of cold-water fish, but of which we have little knowledge about the metabolic adaptation and physiological responses to long-term cold acclimation. RESULTS: In this study, we determined the physiological responses of S. prenanti serum after 30 days of exposure to 6℃. Compared with the control group, the levels of TC, TG, and LDL-C in the serum were significantly (P < 0.05) increased, and the level of glucose was significantly (P < 0.05) decreased under cold acclimation. Cold acclimation had no effect on the gene expression of pro-inflammatory factors and anti-inflammatory factors of S. prenanti. Metabolomics analysis by LC-MS showed that a total of 60 differential expressed metabolites were identified after cold acclimation, which involved in biosynthesis of amino acids, biosynthesis of unsaturated fatty acids, steroid degradation, purine metabolism, and citrate cycle pathways. CONCLUSION: The results indicate that cold acclimation can alter serum metabolites and metabolic pathways to alter energy metabolism and provide insights for the physiological regulation of cold-water fish in response to cold acclimation.

A Wearable Upper Limb Exoskeleton System and Intelligent Control Strategy.

Heavy lifting operations frequently lead to upper limb muscle fatigue and injury. In order to reduce muscle fatigue, auxiliary force for upper limbs can be provided. This paper presents the development and evaluation of a wearable upper limb exoskeleton (ULE) robot system. A flexible cable transmits auxiliary torque and is connected to the upper limb by bypassing the shoulder. Based on the K-nearest neighbors (KNN) algorithm and integrated fuzzy PID control strategy, the ULE identifies the handling posture and provides accurate active auxiliary force automatically. Overall, it has the quality of being light and easy to wear. In unassisted mode, the wearer's upper limbs minimally affect the range of movement. The KNN algorithm uses multi-dimensional motion information collected by the sensor, and the test accuracy is 94.59%. Brachioradialis muscle (BM), triceps brachii (TB), and biceps brachii (BB) electromyogram (EMG) signals were evaluated by 5 kg, 10 kg, and 15 kg weight conditions for five subjects, respectively, during lifting, holding, and squatting. Compared with the ULE without assistance and with assistance, the average peak values of EMG signals of BM, TB, and BB were reduced by 19-30% during the whole handling process, which verified that the developed ULE could provide practical assistance under different load conditions.

A Fusion Network with Stacked Denoise Autoencoder and Meta Learning for Lateral Walking Gait Phase Recognition and Multi-Step-Ahead Prediction.

Lateral walking gait phase recognition and prediction are the premise of hip exoskeleton application in lateral resistance walk exercise. In this work, we presented a fusion network with stacked denoise autoencoder and meta learning (SDA-NN-ML) to recognize gait phase and predict gait percentage from IMU signals. Experiments were conducted to detect the four lateral walking gait phases and predict their percentage in 10 healthy subjects across different speeds. The performance of SDA-NN-ML and other widely used algorithms including Support Vector Machine (SVM), Adaptive Boosting (AdaBoost) and Long Short Term Memory (LSTM) were evaluated. The cross-subject recognition accuracy of SDA-NN-ML (89.94%) decreased by 4.62% compared to the training accuracy, which outperformed SVM (8.60%), AdaBoost (5.61%), and LSTM (7.12%). For real-time and cross-subject prediction of gait phase percentage, the RMSE of SDA-NN-ML (0.2043) outperformed that of a single regression network (0.2426). With a signal noise ratio of 100:30, the cross-subject recognition accuracy decreased by a mere 5.70%, while the prediction result (RMSE) of SDA-NN-ML increased by 0.0167 when compared to the noise-free results. SDA-NN-ML demonstrates a stable multi-step-ahead prediction ability with an accuracy higher than 82.50% and an RMSE of less than 0.23 when the ahead time is less than 200 ms. The results demonstrated that the proposed method has high accuracy and robust performance in lateral walking gait recognition and prediction.

Continuous Locomotion Mode and Task Identification for an Assistive Exoskeleton Based on Neuromuscular-Mechanical Fusion.

Human walking parameters exhibit significant variability depending on the terrain, speed, and load. Assistive exoskeletons currently focus on the recognition of locomotion terrain, ignoring the identification of locomotion tasks, which are also essential for control strategies. The aim of this study was to develop an interface for locomotion mode and task identification based on a neuromuscular-mechanical fusion algorithm. The modes of level and incline and tasks of speed and load were explored, and seven able-bodied participants were recruited. A continuous stream of assistive decisions supporting timely exoskeleton control was achieved according to the classification of locomotion. We investigated the optimal algorithm, feature set, window increment, window length, and robustness for precise identification and synchronization between exoskeleton assistive force and human limb movements (human-machine collaboration). The best recognition results were obtained when using a support vector machine, a root mean square/waveform length/acceleration feature set, a window length of 170, and a window increment of 20. The average identification accuracy reached 98.7% ± 1.3%. These results suggest that the surface electromyography-acceleration can be effectively used for locomotion mode and task identification. This study contributes to the development of locomotion mode and task recognition as well as exoskeleton control for seamless transitions.

Phenotypic diversity observed in a Chinese patient cohort with biallelic variants in Bardet-Biedl syndrome genes.

PURPOSE: Bardet-Biedl syndrome (BBS) is a rare multisystem ciliopathy. The aim of this study was to describe the clinical and genetic features of a cohort of Chinese patients carrying biallelic BBS gene variants. METHODS: We recruited 34 patients from 31 unrelated pedigrees who carried biallelic pathogenic variants in BBS genes. All patients underwent ophthalmic and systematic evaluations, as well as comprehensive molecular genetic analyses. Ultimately, 14 patients were followed up over time. RESULTS: We identified 47 diseasing-causing variants in 10 BBS genes; 33 were novel. Diagnosis of BBS and non-syndromic retinitis pigmentosa (RP) were established in 28 patients from 27 pedigrees and 6 patients, respectively. The two most prevalent genes in patients with BBS were BBS2 and BBS4, accounting for 51.8% of the probands. The patients exhibited clinical heterogeneity, from patients with all six primary clinical components to patients suffering from non-syndromic RP. The common components were retinal dystrophy, polydactyly, and obesity, with frequencies of 78.6% to 100%, while renal anomaly frequencies were only 7.1%. Patients exhibited early and severe visual defects and retinal degeneration. Patients with biallelic missense variants in BBS2 suffered fewer clinical symptoms and mild visual impairment. Patients with BBS10 variants tended to have cone dystrophy. CONCLUSIONS: Our study defined the mutated gene profiles and established the configuration of the variation frequencies for each BBS gene in Chinese patients. Overall, our patients showed early and severe visual defects and retinal degeneration. Genetic analysis is therefore crucial for diagnosis, genetic counseling, and future gene therapy in these patients.

Brassica napus BnaC9.DEWAX1 Negatively Regulates Wax Biosynthesis via Transcriptional Suppression of BnCER1-2.

Very-long-chain alkane plays an important role as an aliphatic barrier. We previously reported that BnCER1-2 was responsible for alkane biosynthesis in Brassica napus and improved plant tolerance to drought. However, how the expression of BnCER1-2 is regulated is still unknown. Through yeast one-hybrid screening, we identified a transcriptional regulator of BnCER1-2, BnaC9.DEWAX1, which encodes AP2\ERF transcription factor. BnaC9.DEWAX1 targets the nucleus and displays transcriptional repression activity. Electrophoretic mobility shift and transient transcriptional assays suggested that BnaC9.DEWAX1 repressed the transcription of BnCER1-2 by directly interacting with its promoter. BnaC9.DEWAX1 was expressed predominantly in leaves and siliques, which was similar to the expression pattern of BnCER1-2. Hormone and major abiotic stresses such as drought and high salinity affected the expression of BnaC9.DEWAX1. Ectopic expression of BnaC9.DEWAX1 in Arabidopsis plants down-regulated CER1 transcription levels and resulted in a reduction in alkanes and total wax loads in leaves and stems when compared with the wild type, whereas the wax depositions in the dewax mutant returned to the wild type level after complementation of BnaC9.DEWAX1 in the mutant. Moreover, both altered cuticular wax composition and structure contribute to increased epidermal permeability in BnaC9.DEWAX1 overexpression lines. Collectively, these results support the notion that BnaC9.DEWAX1 negatively regulates wax biosynthesis by binding directly to the BnCER1-2 promoter, which provides insights into the regulatory mechanism of wax biosynthesis in B. napus.