Astragalus polysaccharides-induced gut microbiota play a predominant role in enhancing of intestinal barrier function of broiler chickens.

BACKGROUND: The intestinal barrier is the first line of defense against intestinal invasion by pathogens and foreign antigens and is closely associated with the gut microbiota. Astragalus polysaccharides (APS) have a long history of use in traditional Chinese medicine owing to its protective properties against intestinal barrier function. The mechanism of APS-induced gut microbiota enhancing intestinal barrier function is urgently needed. RESULTS: Dietary polysaccharide deprivation induced intestinal barrier dysfunction, decreased growth performance, altered microbial composition (Faecalibacterium, Dorea, and Coprobacillus), and reduced isobutyrate concentration. The results showed that APS facilitates intestinal barrier function in broiler chickens, including a thicker mucus layer, reduced crypt depth, and the growth of tight junction proteins. We studied the landscape of APS-induced gut microbiota and found that APS selectively promoted the growth of Parabacteroides, a commensal bacterium that plays a predominant role in enhancing intestinal barrier function. An in vitro growth assay further verified that APS selectively increased the abundance of Parabacteroides distasonis and Bacteroides uniformis. Dietary APS supplementation increased the concentrations of isobutyrate and bile acid (mainly chenodeoxycholic acid and deoxycholate acid) and activated signaling pathways related to intestinal barrier function (such as protein processing in the endoplasmic reticulum, tight junctions, and adherens junction signaling pathways). CONCLUSIONS: APS intervention restored the dietary polysaccharide-induced dysfunction of the intestinal barrier by selectively promoting the abundance of Parabacteroides distasonis, and increasing the concentrations of isobutyrate and bile acids (mainly CDCA and DCA). These findings suggest that APS-induced gut microbiota and metabolic niches are promising strategies for enhancing intestinal barrier function.

Comparative study of the effects of custom-made insole and ordinary insole in adults with flexible flatfoot on different slopes.

BACKGROUND: Flatfoot (pes planus) is a common foot deformity, and its causes are mainly related to age, gender, weight, and genetics. Previous studies have shown that custom-made insoles could have a positive effect in improving plantar pressure and symptoms in individuals with flexible flatfeet, but it remains to be explored whether they can still show benefits in daily walking on different slopes. OBJECTIVE: This study aims to investigate a custom-made insole based on plantar pressure redistribution and to verify its effectiveness by gait analysis on different slopes. METHODS: We recruited 10 subjects and compared the peak pressure and impulse in each area between custom-made insole (CI) and ordinary insole (OI) groups. RESULTS: The results illustrate that CI raises the pressure in T area, improves the ability of the subjects to move forward in the slope walking, which was beneficial to gait stability. CONCLUSION: The redistribution of pressure in MF and MH area is promoted to provide active protection for subjects. Meanwhile, CI could decrease the impulse in MF area during uphill and level walking, which effectively reduces the accumulation of fatigue during gait. Moreover, avoiding downhill walking could be able to protect foot from injury in daily life.

Clinical validation of automated depth camera-based measurement of the Fugl-Meyer assessment for upper extremity.

OBJECTIVE: Depth camera-based measurement has demonstrated efficacy in automated assessment of upper limb Fugl-Meyer Assessment for paralysis rehabilitation. However, there is a lack of adequately sized studies to provide clinical support. Thus, we developed an automated system utilizing depth camera and machine learning, and assessed its feasibility and validity in a clinical setting. DESIGN: Validation and feasibility study of a measurement instrument based on single cross-sectional data. SETTING: Rehabilitation unit in a general hospital. PARTICIPANTS: Ninety-five patients with hemiparesis admitted for inpatient rehabilitation unit (2021-2023). MAIN MEASURES: Scores for each item, excluding those related to reflexes, were computed utilizing machine learning models trained on participant videos and readouts from force test devices, while the remaining reflex scores were derived through regression algorithms. Concurrent criterion validity was evaluated using sensitivity, specificity, percent agreement and Cohen's Kappa coefficient for ordinal scores of individual items, as well as correlations and intraclass correlation coefficients for total scores. Video-based manual assessment was also conducted and compared to the automated tools. RESULT: The majority of patients completed the assessment without therapist intervention. The automated scoring models demonstrated superior validity compared to video-based manual assessment across most items. The total scores derived from the automated assessment exhibited a high coefficient of 0.960. However, the validity of force test items utilizing force sensing resistors was relatively low. CONCLUSION: The integration of depth camera technology and machine learning models for automated Fugl-Meyer Assessment demonstrated acceptable validity and feasibility, suggesting its potential as a valuable tool in rehabilitation assessment.

Anatomical variations of the brachial plexus in adult cadavers: A descriptive study and clinical significance.

BACKGROUND: Brachial plexus injury is recognized as one of the most severe clinical challenges due to the complex anatomical configuration of the brachial plexus and its propensity for variation, which complicates safe clinical interventions. This study aimed to ascertain the prevalence and characterize the types of brachial plexus variations, and to elucidate their clinical implications. MATERIALS AND METHODS: We conducted meticulous dissections of 60 formalin-fixed cadavers' upper arm, axilla and lower neck to reveal and assess the roots, trunks, divisions, cords, and branches of the brachial plexus. The pattern of branching was noted by groups of dissecting medical students and confirmed by the senior anatomists. The variations discovered were record and photographed using a digital camera for further analysis. RESULTS: Variations in the brachial plexus were identified in 40 of the 60 cadavers, yielding a prevalence rate of 66.7%. These variations were classified into root anomalies (2.1%), trunk anomalies (8.5%), division anomalies (2.1%), and cord anomalies (4.3%). Notably, anomalies in communicating branches were observed in 39 cadavers (83.0%): 14 with bilateral anomalies, 14 with anomalies on the left side, and 11 on the right side. These communicating branches formed connections between the roots and other segments, including trunks, cords, and terminal nerves, and involved the median, musculocutaneous, and ulnar nerves. CONCLUSION: The frequency and diversity of brachial plexus variations, particularly in communicating branches, are significant in cadavers. It is imperative that these variations are carefully considered during the diagnostic process, treatment planning, and prior to procedures such as supraclavicular brachial plexus blocks and nerve transfers, to mitigate the risk of iatrogenic complications.

Deciphering the nutritional strategies for polysaccharides effects on intestinal barrier in broilers: Selectively promote microbial ecosystems.

The gut microbiota, a complex and dynamic microbial ecosystem, plays a crucial role in regulating the intestinal barrier. Polysaccharide foraging is specifically dedicated to establishing and maintaining microbial communities, contributing to the shaping of the intestinal ecosystem and ultimately enhancing the integrity of the intestinal barrier. The utilization and regulation of individual polysaccharides often rely on distinct gut-colonizing bacteria. The products of their metabolism not only benefit the formation of the ecosystem but also facilitate cross-feeding partnerships. In this review, we elucidate the mechanisms by which specific bacteria degrade polysaccharides, and how polysaccharide metabolism shapes the microbial ecosystem through cross-feeding. Furthermore, we explore how selectively promoting microbial ecosystems and their metabolites contributes to improvements in the integrity of the intestinal barrier.

Microbiota-accessible fiber activates short-chain fatty acid and bile acid metabolism to improve intestinal mucus barrier in broiler chickens.

IMPORTANCE: The intestinal mucus barrier, located at the interface of the intestinal epithelium and the microbiota, is the first line of defense against pathogenic microorganisms and environmental antigens. Dietary polysaccharides, which act as microbiota-accessible fiber, play a key role in the regulation of intestinal microbial communities. However, the mechanism via which dietary fiber affects the intestinal mucus barrier through targeted regulation of the gut microbiota is not clear. This study provides fundamental evidence for the benefits of dietary fiber supplementation in broiler chickens through improvement in the intestinal mucus barrier by targeted regulation of the gut ecosystem. Our findings suggest that the microbiota-accessible fiber-gut microbiota-short-chain fatty acid/bile acid axis plays a key role in regulating intestinal function.

Dietary oregano aqueous extract improves growth performance and intestinal health of broilers through modulating gut microbial compositions.

BACKGROUND: Intestinal health plays a pivotal role in broiler chicken growth. Oregano aqueous extract (OAE) effectively exerts anti-inflammatory and antibacterial effects. However, the protective effects of OAE on intestinal health in broilers and the underlying mechanism remain unclear. This study aimed to investigate the potential effects of OAE on growth performance, the gut microbiota and intestinal health. A total of 840 1-d-old male and female broilers (Arbor Acres) were randomly allocated into 6 groups as follows: basal diet (Con), Con + antibiotics (Anti, colistin sulfate 7 g/kg, roxarsone 35 g/kg), Con + 400, 500, 600 and 700 mg/kg OAE (OAE400, OAE500, OAE600 and OAE700). Subsequently, fermentation in vitro together with oral administration trials were carried out to further assess the function of OAE on intestinal health of broilers. RESULTS: Dietary 700 mg/kg OAE supplementation resulted in an increase (P < 0.05) in body weight and a decrease (P < 0.05) in feed conversion ratio when compared with the control during d 22 to 42 of the trial. OAE addition resulted in lower (P < 0.05) jejunal crypt depth and mRNA expression of IL-4 and IL-10 at d 42. In addition, dietary OAE addition increased the abundance of Firmicutes (P = 0.087) and Lactobacillus (P < 0.05) in the cecum, and increased (P < 0.05) the content of acetic acid and butyric acid. In the in vitro fermentation test, OAE significantly increased (P < 0.05) the abundance of Lactobacillus, decreased (P < 0.05) the abundance of unspecified_Enterobacteriaceae, and increased the content of acetic acid (P < 0.05). In the oral administration trial, higher (P < 0.05) IL-4 expression was found in broilers when oral inoculation with oregano fermentation microorganisms at d 42. And SIgA content in the ileum was significantly increased (P = 0.073) when giving OAE fermentation supernatant. CONCLUSIONS: Dietary OAE addition could maintain intestinal health and improve growth performance through enhancing intestinal mucosal immunity and barrier function mediated by gut microbiota changes.

Evolution of elemental nitrogen involved in the carbonization mechanism and product features from wet biowaste.

Hydrothermal carbonization (HTC) represents elegant thermochemical conversion technology suitable for energy and resource recovery from wet biowaste, while the elemental nitrogen is bound to affect the HTC process and the properties of the products. In this review, the nitrogen fate during HTC of typical N-containing-biowaste were presented. The relationship between critical factors involved in HTC like N/O, N/C, N/H, solid ratio, initial N in feedstock, hydrothermal temperature and residence time and N content in hydrochar were systematic analyzed. The distribution and conversion of N species along with hydrothermal severity in hydrochar and liquid phase was discussed. Additionally, the chemical forms of nitrogen in hydrochar were elaborated coupled with the role of N element during hydrochar formation mechanism and the morphology features. Finally, the future challenges of nitrogen in biowaste involved in HTC about the formation and regulation mechanism of hydrochar were given, and perspectives of more accurate regulation of the physicochemical characteristics of hydrochar from biowaste based on the N evolution is expected.

Cecal Microbial Succession and Its Apparent Association with Nutrient Metabolism in Broiler Chickens.

The chicken gut microbiota plays an influential role in nutrient absorption and metabolism. A clear picture of microbiota succession can enhance host nutrition and disease resistance. This study investigated the cecal microbiota succession of broilers between 3 and 42 days after hatching using 16S rRNA gene sequencing and analyzed its potential association with intestinal nutrient metabolism. Microbiota structure differed significantly at different time points depending on the microbiota alpha-diversity or beta-diversity. Proteobacteria and Bacteroidetes promoted succession on days 3 to 7 and days 28 to 35, respectively. Firmicutes and Tenericutes maintained homeostasis on days 7 to 28 and days 35 to 42. Shigella, [Ruminococcus], Erysipelotrichaceae_Clostridium, and Coprobacillus promoted succession on days 3 to 7; Faecalibacterium modified microbial composition on days 7 to 14; Faecalibacterium and Bacteroides regulated microbial structure from days 21 to 28. The microbiota structure was relatively stable on days 14 to 21 and days 28 to 35. Spearman's correlation analysis indicated a positive correlation between Lactobacillus and villus height and crypt depth (P < 0.01). Faecalibacterium and Shigella were correlated with propionate, butyrate, and valerate concentrations (P < 0.01). Ruminococcus was correlated with sodium-glucose cotransporters 1 and cationic amino acid transporter 1 expression (P < 0.05). Erysipelotrichaceae_Clostridium and Shigella were positively correlated with serum levels of total cholesterol, tryglucerides, and high- and low-density lipoprotein cholesterol (P < 0.01). Bacteroides, Parabacteroides, Lactobacillus, and Shigella were correlated with serum VB6 levels (P < 0.01). Bacteroides, Erysipelotrichaceae_Clostridium, and Coprobacillus were correlated with the moisture content of cecal contents (P < 0.05). The identification of the microbiota in correlation with nutrient metabolism will promote microbial nutrition through microbiota intervention or nutritional regulation. IMPORTANCE The poultry industry has become a global leader in livestock farming over the past few decades. Poultry production has a large consumer market as an integrated industry producing high-protein foods. Establishing the association between microbiota and nutrient metabolism processes provides fresh insights for precise nutrient regulation. This study aimed to describe the development of cecal microbiota in broiler chickens throughout the production cycle and to assess the correlation of nutrient metabolism phenotypes with temporal changes in the microbiota. The results suggested that changes in cecal microbes with age partly explain changes in gut nutrient metabolic processes, and numerous microbes were significantly associated with the processes. Therefore, this study attempts to further find efficient ways of improving poultry production. One is to promote nutrient metabolism by identifying potential candidates for probiotics, and another is to foster the dominant colonization of the microbiota by regulating nutrient metabolism.

Repetitive Impedance Learning-Based Physically Human-Robot Interactive Control.

Model-based impedance learning control can provide variable impedance regulation for robots through online impedance learning without interaction force sensing. However, the existing related results only guarantee the closed-loop control systems to be uniformly ultimately bounded (UUB) and require the human impedance profiles being periodic, iteration-dependent, or slowly varying. In this article, a repetitive impedance learning control approach is proposed for physical human-robot interaction (PHRI) in repetitive tasks. The proposed control is composed of a proportional-differential (PD) control term, an adaptive control term, and a repetitive impedance learning term. Differential adaptation with projection modification is designed for estimating robotic parameters uncertainties in the time domain, while fully saturated repetitive learning is proposed for estimating time-varying human impedance uncertainties in the iterative domain. Uniform convergence of tracking errors is guaranteed by the PD control and the use of projection and full saturation in the uncertainties estimation and is theoretically proved based on a Lyapunov-like analysis. In impedance profiles, the stiffness and damping are composed of an iteration-independent term and an iteration-dependent disturbance, which are estimated by repetitive learning and compressed by the PD control, respectively. Therefore, the developed approach can be applied to the PHRI where iteration-dependent disturbances exist in the stiffness and damping. The control effectiveness and advantages are validated by simulations on a parallel robot in a repetitive following task.

Pretherapy investigations using highly robust visualized biomarkers from CT imaging by multiple machine-learning techniques toward its prognosis prediction for ALK-inhibitor therapy in NSCLC: a feasibility study.

PURPOSE: Molecularly targeted therapy has revolutionized the therapeutic landscape and is emerging as the first-line treatment option for ALK-rearranged non-small-cell lung cancer (NSCLC). In this study, the highly informative and robust biomarkers based on pre-treatment CT images and clinicopathologic features will be developed and validated to predict the prognosis for ALK-inhibitor therapy in NSCLC patients. METHODS: A total of 161 ALK-positive NSCLC patients treated with ALK inhibitors were retrospectively collected as training, validation and test sets from multi-center institutions. Cox proportional hazard regression (CPH) penalized by LASSO and random survival forest (RSF) coupled with recursive feature elimination (RFE) were used for radiomics and clinical features identification and model construction. An overlapping post-processing method was extra added to training process to investigate the stronger biomarker on the whole set. RESULTS: 123 of the collected cases progressed after a median follow-up of 15.5 months (IQR, 8.3-25.3). The T and M staging, pericardial effusion, age and ALK inhibitor-alectinib were determined as significant predictors in the survival analysis. Furthermore, we visualized the finally retained 4 radiomics feature. The RSF models built from overlapping-processed clinical and radiomics features respectively reached the maximum C-index of 0.68 and 0.75,but the combination of them,radioclinical signature, improved the score to 0.78. The model on the validation and external test datasets yielded the C-index of 0.73 and 0.79, with the iAUC of 0.76 and 0.83, the IBS of 0.119 and 0.112. CONCLUSION: With respect to a simple selection strategy of overlapping optimal radiomics and clinical features from different survival models may promote better progression-free survival(PFS) prediction than conventional survival analysis, which provides a potential method for guiding personalized pre-treatment options of NSCLC.

Spatial hybrid adaptive impedance learning control for robots in repetitive interactive tasks.

The existing model-based impedance learning control methods can provide variable impedance regulation for physical human-robot interaction (PHRI) in repetitive tasks without interactive force sensing, however, these methods require the completion of the repetitive tasks with constant time, which restricts their applications. For PHRI in repetitive tasks with different completion time, this paper proposes a spatial hybrid adaptive impedance learning control (SHAILC) strategy by using the spatial periodic characteristics of the tasks. In the spatial hybrid adaptation, spatial periodic adaptation is used for estimating time-varying human impedance and differential adaptation is designed for estimating robotic constant unknown parameters. The use of deadzone modifications in hybrid adaptation maintains the accuracy of the parameter estimation when the tracking error is small relative to the modeling error. The control stability is analyzed by a Lyapunov-based analysis in the spatial domain, and the control effectiveness and superiority is illustrated on a parallel robot in repetitive tasks with different task completion time.

Automatic range of motion measurement via smartphone images for telemedicine examination of the hand.

BACKGROUND: Telemedicine support virtual consultations and evaluations in hand surgery for patients in remote areas during the COVID-19 era. However, traditional physical examination is challenging in telemedicine and it is inconvenient to manually measure the hand range of motion (ROM) from images or videos. Here, we propose an automatic method using the hand pose estimation technique, aiming to measure the hand ROM from smartphone images. METHODS: Twenty-eight healthy volunteers participated in the study. An eight-hand gestures measurement protocol and the Google MediaPipe Hands were used to analyze images and calculate the ROM automatically. Manual goniometry was also performed according to the guideline of the American Medical Association. The correlation between the automatic and manual methods was analyzed by the intraclass correlation coefficient and Pearson correlation coefficient. The clinical acceptance was testified using Bland-Altman plots. RESULTS: A total of 32 parameters of each hand were measured by both methods, and 1792 measurement results were compared. The mean difference between automatic and manual methods is -2.21 ± 9.29° in the angle measurement and 0.48 ± 0.48 cm in the distance measurement. The intraclass correlation coefficient of 75% of parameters was higher than 0.75, the Pearson correlation coefficient of 84% of parameters was over 0.6, and 40.6% of parameters reached well-accepted clinical agreements. CONCLUSIONS: The proposed method provides a helpful protocol for automatic hand ROM measurement based on smartphone images and the MediaPipe Hands pose estimation technique. The automatic measurement is acceptable and comparable with existing methods, showing a possible application in the telemedicine examination of hand surgery.

Predicting the efficacy of immune checkpoint inhibitors monotherapy in advanced non-small cell lung cancer: a machine learning method based on multidimensional data.

Immunotherapy has improved the prognosis of patients with advanced non-small cell lung cancer (NSCLC), but only a small subset of patients achieved clinical benefit. The purpose of our study was to integrate multidimensional data using a machine learning method to predict the therapeutic efficacy of immune checkpoint inhibitors (ICIs) monotherapy in patients with advanced NSCLC. We retrospectively enrolled 112 patients with stage IIIB-IV NSCLC receiving ICIs monotherapy. The random forest (RF) algorithm was used to establish efficacy prediction models based on five different input datasets, including precontrast computed tomography (CT) radiomic data, postcontrast CT radiomic data, a combination of the two CT radiomic data, clinical data, and a combination of radiomic and clinical data. The 5-fold cross-validation was used to train and test the random forest classifier. The performance of the models was assessed according to the area under the curve (AUC) in the receiver operating characteristic curve. Survival analysis was performed to determine the difference in progression-free survival (PFS) between the two groups with the prediction label generated by the combined model. The radiomic model based on the combination of precontrast and postcontrast CT radiomic features and the clinical model produced an AUC of 0.92±0.04 and 0.89±0.03, respectively. By integrating radiomic and clinical features together, the combined model had the best performance with an AUC of 0.94±0.02. The survival analysis showed that the two groups had significantly different PFS times (p<0.0001). The baseline multidimensional data including CT radiomic and multiple clinical features were valuable in predicting the efficacy of ICIs monotherapy in patients with advanced NSCLC.

Validity and Reliability of a Depth Camera-Based Quantitative Measurement for Joint Motion of the Hand.

Purpose: Quantitative measurement of hand motion is essential in evaluating hand function. This study aimed to investigate the validity and reliability of a novel depth camera-based contactless automatic measurement system to assess hand range of motion and its potential benefits in clinical applications. Methods: Five hand gestures were designed to evaluate the hand range of motion using a depth camera-based measurement system. Seventy-one volunteers were enrolled in performing the designed hand gestures. Then, the hand range of motion was measured with the depth camera and manual procedures. System validity was evaluated based on 3 dimensions: repeatability, within-laboratory precision, and reproducibility. For system reliability, linear evaluation, the intraclass correlation coefficient, paired t -test and bias were employed to test the consistency and difference between the depth camera and manual procedures. Results: When measuring phalangeal length, repeatability, within-laboratory precision, and reproducibility were 2.63%, 12.87%, and 27.15%, respectively. When measuring angles of hand motion, the mean repeatability and within-laboratory precision were 1.2° and 3.3° for extension of 5 digits, 2.7° and 10.2° for flexion of 4 fingers, and 3.1° and 5.3° for abduction of 4 metacarpophalangeal joints, respectively. For system reliability, the results showed excellent consistency (intraclass correlation coefficient = 0.823; P < .05) and good linearity with the manual procedures (r = 0.909-0.982, approximately; P < .001). Besides, 78.3% of the measurements were clinically acceptable. Conclusions: Our depth camera-based evaluation system provides acceptable validity and reliability in measuring hand range of motion and offers potential benefits for clinical care and research in hand surgery. However, further studies are required before clinical application. Clinical relevance: This study suggests a depth camera-based contactless automatic measurement system holds promise for assessing hand range of motion in hand function evaluation, diagnosis, and rehabilitation for medical staff. However, it is currently not adequate for all clinical applications.

Precision and accuracy of measuring finger motion with a depth camera: a cross-sectional study of healthy participants.

The purpose of this cross-sectional study was to determine the precision and accuracy of the measurement of finger motion with a depth camera. Fifty-five healthy adult hands were included. Measurements were done with a depth camera and compared with traditional manual goniometer measurements. Repeated measuring showed that the overall repeatability and reproducibility of extension measured with the depth camera were within 3° and 4° and that of flexion were within 13° and 14°. Compared with traditional manual goniometry, biases of extension of all finger joints and flexion of metacarpophalangeal joints were less than 5°, and the average bias of flexion of proximal and distal interphalangeal joints was 29°. We conclude that the measurement of finger extension and flexion of the metacarpophalangeal joints with a depth camera was reliable, but improvement is required in the precision and accuracy of interphalangeal joint flexion.

Dietary folic acid addition reduces abdominal fat deposition mediated by alterations in gut microbiota and SCFA production in broilers.

Intensive selective breeding for high growth rate and body weight cause excess abdominal fat in broilers. Gut microbiota and folic acid were reported to regulate lipid metabolism. A total of 210 one-day-old broilers were divided into the control (folic acid at 1.3 mg/kg) and folic acid groups (folic acid at 13 mg/kg) to illustrate the effects of folic acid on growth performance, abdominal fat deposition, and gut microbiota, and the experiment lasted 28 d. Results revealed that dietary folic acid addition decreased abdominal fat percentage (P < 0.05) and down-regulated genes expression related to cell proliferation and differentiation in abdominal fat including IGF1, EGF, C/EBPα, PPARγ, PLIN1, FABP4 and PCNA (P < 0.05). Folic acid addition decreased caecal Firmicutes-to-Bacteroidetes ratio (P < 0.01) and increased the proportions of Alistipes, Oscillospira, Ruminococcus, Clostridium, Dehalobacterium and Parabacteroides (P < 0.05). Caecal acetic acid, and propionic acid contents were found to be higher under folic acid treatment (P < 0.05), which were negatively related to genes expression associated with adipocyte proliferation and differentiation (P < 0.05). Ruminococcus was positively correlated with caecal acetic acid content, and the same phenomenon was detected between propionic acid and Oscillospira and Ruminococcus (P < 0.05). Acetic acid and Oscillospira were identified to be negatively associated with abdominal fat percentage (P < 0.05). In conclusion, our data demonstrated that dietary supplementation of folic acid reduced fat deposition in broilers by inhibiting abdominal adipocyte proliferation and differentiation, which might be mediated by changes in gut microbiota and short chain fatty acid production.

Joint torques estimation in human gait based on Gaussian process.

BACKGROUND: Human gait involves activities in nervous and musculoskeletal dynamics to modulate joint torques with time continuously for adapting to varieties of walking conditions. OBJECTIVE: The goal of this paper is to estimate the joint torques of lower limbs in human gait based on Gaussian process. METHOD: The potential uses of this study include optimization of exoskeleton assistance, control of the active prostheses, and modulating the joint torque for human-like robots. To achieve this, Gaussian process (GP) based data fusion algorithm is established with joint angles as the inputs. RESULTS: The statistic nature of the proposed model can explore the correlations between joint angles and joint torques, and enable accurate joint-torque estimations. Experiments were conducted for 5 subjects at three walking speed (0.8 m/s, 1.2 m/s, 1.6 m/s). CONCLUSION: The results show that it is possible to estimate the joint torques at different scenarios.

Adaptive Interaction Control of Compliant Robots Using Impedance Learning.

This paper presents an impedance learning-based adaptive control strategy for series elastic actuator (SEA)-driven compliant robots without the measurement of the robot-environment interaction force. The adaptive controller is designed based on the command filter-based adaptive backstepping approach, where a command filter is used to decrease computational complexity and avoid the requirement of high derivatives of the robot position. In the controller, environmental impedance profiles and robotic parameter uncertainties are estimated using adaptive learning laws. Through a Lyapunov-based theoretical analysis, the tracking error and estimation errors are proven to be semiglobally uniformly ultimately bounded. The control effectiveness is illustrated through simulations on a compliant robot arm.

Automatic detection of abnormal hand gestures in patients with radial, ulnar, or median nerve injury using hand pose estimation.

Background: Radial, ulnar, or median nerve injuries are common peripheral nerve injuries. They usually present specific abnormal signs on the hands as evidence for hand surgeons to diagnose. However, without specialized knowledge, it is difficult for primary healthcare providers to recognize the clinical meaning and the potential nerve injuries through the abnormalities, often leading to misdiagnosis. Developing technologies for automatically detecting abnormal hand gestures would assist general medical service practitioners with an early diagnosis and treatment. Methods: Based on expert experience, we selected three hand gestures with predetermined features and rules as three independent binary classification tasks for abnormal gesture detection. Images from patients with unilateral radial, ulnar, or median nerve injuries and healthy volunteers were obtained using a smartphone. The landmark coordinates were extracted using Google MediaPipe Hands to calculate the features. The receiver operating characteristic curve was employed for feature selection. We compared the performance of rule-based models with logistic regression, support vector machine and of random forest machine learning models by evaluating the accuracy, sensitivity, and specificity. Results: The study included 1,344 images, twenty-two patients, and thirty-four volunteers. In rule-based models, eight features were finally selected. The accuracy, sensitivity, and specificity were (1) 98.2, 91.7, and 99.0% for radial nerve injury detection; (2) 97.3, 83.3, and 99.0% for ulnar nerve injury detection; and (3) 96.4, 87.5, and 97.1% for median nerve injury detection, respectively. All machine learning models had accuracy above 95% and sensitivity ranging from 37.5 to 100%. Conclusion: Our study provides a helpful tool for detecting abnormal gestures in radial, ulnar, or median nerve injuries with satisfying accuracy, sensitivity, and specificity. It confirms that hand pose estimation could automatically analyze and detect the abnormalities from images of these patients. It has the potential to be a simple and convenient screening method for primary healthcare and telemedicine application.