Gyrus rectus asymmetry predicts trait alexithymia, cognitive empathy, and social function in neurotypical adults.

Reduced empathy and elevated alexithymia are observed in autism spectrum disorder (ASD), which has been linked to altered asymmetry in brain morphology. Here, we investigated whether trait autism, empathy, and alexithymia in the general population is associated with brain morphological asymmetry. We determined left-right asymmetry indexes for cortical thickness and cortical surface area (CSA) and applied these features to a support-vector regression model that predicted trait autism, empathy, and alexithymia. Results showed that less leftward asymmetry of CSA in the gyrus rectus (a subregion of the orbitofrontal cortex) predicted more difficulties in social functioning, as well as reduced cognitive empathy and elevated trait alexithymia. Meta-analytic decoding of the left gyrus rectus annotated functional items related to social cognition. Furthermore, the link between gyrus rectus asymmetry and social difficulties was accounted by trait alexithymia and cognitive empathy. These results suggest that gyrus rectus asymmetry could be a shared neural correlate among trait alexithymia, cognitive empathy, and social functioning in neurotypical adults. Left-right asymmetry of gyrus rectus influenced social functioning by affecting the cognitive processes of emotions in the self and others. Interventions that increase leftward asymmetry of the gyrus rectus might improve social functioning for individuals with ASD.

Menstrually-related migraine shapes the structural similarity network integration of brain.

Menstrually-related migraine (MM) is a primary migraine in women of reproductive age. The underlying neural mechanism of MM was still unclear. In this study, we aimed to reveal the case-control differences in network integration and segregation for the morphometric similarity network of MM. Thirty-six patients with MM and 29 healthy females were recruited and underwent MRI scanning. The morphometric features were extracted in each region to construct the single-subject interareal cortical connection using morphometric similarity. The network topology characteristics, in terms of integration and segregation, were analyzed. Our results revealed that, in the absence of morphology differences, disrupted cortical network integration was found in MM patients compared to controls. The patients with MM showed a decreased global efficiency and increased characteristic path length compared to healthy controls. Regional efficiency analysis revealed the decreased efficiency in the left precentral gyrus and bilateral superior temporal gyrus contributed to the decreased network integration. The increased nodal degree centrality in the right pars triangularis was positively associated with the attack frequency in MM. Our results suggested MM would reorganize the morphology in the pain-related brain regions and reduce the parallel information processing capacity of the brain.

Examining Eye Tracking Metrics and Cognitive Function in Post-Stroke Individuals: A Comparison of Visual Searching Tasks Between Those with and without Cognitive Impairment.

INTRODUCTION: After a stroke, individuals commonly experience visual problems and impaired cognitive function, which can significantly impact their daily life. In addition to visual neglect and hemianopia, stroke survivors often have difficulties with visual search tasks. Researchers are increasingly interested in using eye tracking technology to study cognitive processing and determine whether eye tracking metrics can be used to screen and assess cognitive impairment in patients with neurological disorders. As such, assessing these areas and understanding their relationship is crucial for effective stroke rehabilitation. METHODS: We enrolled 60 stroke patients in this study and evaluated their eye tracking performance and cognitive function through a series of tests. Subsequently, we divided the subjects into two groups based on their scores on the HK-MoCA test, with scores below 21 out of 30 indicating cognitive impairment. We then compared the eye tracking metrics between the two groups and identified any significant differences that existed. Spearman correlation analysis was conducted to explore the relationship between clinical test scores and eye tracking metrics. Moreover, we employed a Mann-Whitney U test to compare eye tracking metrics between groups with and without cognitive impairment. RESULTS: Our results revealed significant correlations between various eye tracking metrics and cognitive tests (p=<.001-.041). Furthermore, the group without cognitive impairment demonstrated higher saccade velocity, gaze path velocity, and shorter time to target than the group with cognitive impairment (p=<.001-.040). ROC curve analyses were performed, and the optimal cut-off values for gaze path velocity and saccade velocity were 329.665 (px/s) (sensitivity= 0.80, specificity = 0.533) and 2.150 (px/s) (sensitivity= 0.733, specificity= 0.633), respectively. CONCLUSIONS: Our findings indicate a significant correlation between eye tracking metrics and cognitive test scores. Furthermore, the group with cognitive impairment exhibited a significant difference in these metrics, and a cut-off value was identified to predict whether a client was experiencing cognitive impairment.

Microbiological and Clinical Effects of a Proanthocyanidin-enriched Extract from Rumex acetosa in Periodontally Healthy Carriers of Porphyromonas gingivalis: a Randomized Controlled Pilot Study.

Rumex acetosa significantly inhibits the adhesion of Porphyromonas gingivalis (P. g.) to eukaryotic host cells in vitro. The objective of this randomized placebo-controlled pilot-trial was to analyze effects of a mouth rinse containing 0.8% (w/w) of a quantified proanthocyanidin-enriched extract from Rumex acetosa (RA1) on microbiological, clinical, and cytological parameters in systemically healthy individuals without history of periodontitis, harboring P. g. intraorally. 35 subjects received a supragingival debridement (SD) followed by mouth rinsing (3 times daily) with either RA1 mouth rinse solution (test) or placebo (control) for 7 days as adjunct to routine oral hygiene. Supragingival biofilm samples were taken at screening visit, baseline (BL), 2, 4, 7 and 14 days after SD. P. g. and 11 other oral microorganisms were detected and quantified by rtPCR. Changes in the oral microbiota composition of one test and one control subject were assessed via high throughput 16S rRNS gene amplicon sequencing. Approximal Plaque Index (API) and the modified Sulcular Bleeding Index (SBI) were assessed at BL, 7- and 14-days following SD. Brush biopsies were taken at BL and 14 d following SD. Intergroup comparisons revealed no significant microbiological, cytological, and clinical differences at any timepoint. However, a significant reduction in SBI at day 14 (p = 0.003) and API at day 7 (p = 0.02) and day 14 (p = 0.009) was found in the test group by intragroup comparison. No severe adverse events were observed. The results indicate that RA1 mouth rinse is safe but does not seem to inhibit colonization of P. g. or improve periodontal health following SD.

An End-to-End Dynamic Posture Perception Method for Soft Actuators Based on Distributed Thin Flexible Porous Piezoresistive Sensors.

This paper proposes a method for accurate 3D posture sensing of the soft actuators, which could be applied to the closed-loop control of soft robots. To achieve this, the method employs an array of miniaturized sponge resistive materials along the soft actuator, which uses long short-term memory (LSTM) neural networks to solve the end-to-end 3D posture for the soft actuators. The method takes into account the hysteresis of the soft robot and non-linear sensing signals from the flexible bending sensors. The proposed approach uses a flexible bending sensor made from a thin layer of conductive sponge material designed for posture sensing. The LSTM network is used to model the posture of the soft actuator. The effectiveness of the method has been demonstrated on a finger-size 3 degree of freedom (DOF) pneumatic bellow-shaped actuator, with nine flexible sponge resistive sensors placed on the soft actuator's outer surface. The sensor-characterizing results show that the maximum bending torque of the sensor installed on the actuator is 4.7 Nm, which has an insignificant impact on the actuator motion based on the working space test of the actuator. Moreover, the sensors exhibit a relatively low error rate in predicting the actuator tip position, with error percentages of 0.37%, 2.38%, and 1.58% along the x-, y-, and z-axes, respectively. This work is expected to contribute to the advancement of soft robot dynamic posture perception by using thin sponge sensors and LSTM or other machine learning methods for control.

Ongoing first-hand pain facilitates somatosensory resonance but inhibits affective sharing in empathy for pain.

Alterations of empathy for others' pain among patients with chronic pain remained inconsistent. Here, applying a capsaicin-based ongoing pain model on healthy participants, this study investigated how ongoing first-hand pain influences empathic reactions to vicarious pain stimuli. Healthy participants were randomly treated with topical capsaicin cream (capsaicin group) or hand cream (control group) on the left forearm. Video clips showing limbs in painful and non-painful situations were used to induce empathic responses. The capsaicin group showed greater empathic neural responses in the right primary somatosensory cortex (S1) than the control group but smaller responses in the left anterior insula (AI) accompanied with smaller empathic pain-intensity ratings. Notably, the intensity of ongoing pain negatively correlated with empathy-related neural responses in the left AI. Inter-subject phase synchronization analysis was used to assess stimulus-dependent dynamic functional connectivity within or between brain regions engaged in pain empathy. The capsaicin group showed greater empathy-related neural synchronization within S1 and between S1 and AI, but less synchronization within AI and between AI and MCC. Behaviorally, the differential inter-subject pain-intensity rating alignment between painful and non-painful videos was more positive for the capsaicin group than for the control group, and this effect was partially mediated by the inter-subject neural synchronization between S1 and AI. These results suggest that ongoing first-hand pain facilitates neural activation and synchronization within brain regions associated with empathy-related somatosensory resonance at the cost of inhibiting activation and synchronization within brain regions engaged in empathy-related affective sharing.

Augmented reality for stroke rehabilitation during COVID-19.

BACKGROUND: The lack of the rehabilitation professionals is a global issue and it is becoming more serious during COVID-19. An Augmented Reality Rehabilitation System (AR Rehab) was developed for virtual training delivery. The virtual training was integrated into the participants' usual care to reduce the human trainers' effort so that the manpower scarcity can be eased. This also resulted in the reduction of the contact rate in pandemics. OBJECTIVE: To investigate the feasibility of the AR Rehab-based virtual training when integrated into the usual care in a real-world pandemic setting, by answering questions of whether the integrated trials can help fulfill the training goal and whether the trials can be delivered when resources are limited because of COVID-19. METHODS: Chronic stroke participants were randomly assigned to either a centre-based group (AR-Centre) or a home-based group (AR-Home) for a trial consisting of 20 sessions delivered in a human-machine integrated intervention. The trial of the AR-Centre was human training intensive with 3/4 of each session delivered by human trainers (PTs/OTs/Assistants) and 1/4 delivered by the virtual trainer (AR Rehab). The trial of the AR-Home was virtual training intensive with 1/4 and 3/4 of each session delivered by human and virtual trainers, respectively. Functional assessments including Fugl-Meyer Assessment for Upper Extremity (FMA-UE) and Lower Extremity (FMA-LE), Functional Ambulation Category (FAC), Berg Balance Scale (BBS), Barthel Index (BI) of Activities of Daily Living (ADL), and Physical Component Summary (SF-12v2 PCS) and Mental Component Summary (SF-12v2 MCS) of the 12-Item Short Form Health Survey (SF-12v2), were conducted before and after the intervention. User experience (UX) using questionnaires were collected after the intervention. Time and human resources required to deliver the human and virtual training, respectively, and the proportion of participants with clinical significant improvement were also used as supplementary measures. RESULTS: There were 129 patients from 10 rehabilitation centres enrolled in the integrated program with 39 of them were selected for investigation. Significant functional improvement in FMA-UE (AR-Centre: p = 0.0022, AR-Home: p = 0.0043), FMA-LE (AR-Centre: p = 0.0007, AR-Home: p = 0.0052), SF-12v2 PCS (AR-Centre: p = 0.027, AR-Home: p = 0.036) were observed in both groups. Significant improvement in balance ability (BBS: p = 0.0438), and mental components (SF-12v2 MCS: p = 0.017) were found in AR-Centre group, while activities of daily living (BI: p = 0.0007) was found in AR-Home group. Contact rate was reduced by 30.75-72.30% within AR-All, 0.00-60.00% within AR-Centre, and 75.00-90.00% within AR-Home. CONCLUSION: The human-machine integrated mode was effective and efficient to reduce the human rehabilitation professionals' effort while fulfilling the training goals. It eased the scarcity of manpower and reduced the contact rate during the pandemics.

Soft Robots' Dynamic Posture Perception Using Kirigami-Inspired Flexible Sensors with Porous Structures and Long Short-Term Memory (LSTM) Neural Networks.

Soft robots can create complicated structures and functions for rehabilitation. The posture perception of soft actuators is critical for performing closed-loop control for a precise location. It is essential to have a sensor with both soft and flexible characteristics that does not affect the movement of a soft actuator. This paper presents a novel end-to-end posture perception method that employs flexible sensors with kirigami-inspired structures and long short-term memory (LSTM) neural networks. The sensors were developed with conductive sponge materials. With one-step calibration from the sensor output, the posture of the soft actuator could be calculated by the LSTM network. The method was validated by attaching the developed sensors to a soft fiber-reinforced bending actuator. The results showed the accuracy of posture prediction of sponge sensors with three kirigami-inspired structures ranged from 0.91 to 0.97 in terms of R2. The sponge sensors only generated a resistive torque value of 0.96 mNm at the maximum bending position when attached to a soft actuator, which would minimize the effect on actuator movement. The kirigami-inspired flexible sponge sensor could in future enhance soft robotic development.

Suffer together, bond together: Brain-to-brain synchronization and mutual affective empathy when sharing painful experiences.

Previous behavioral studies have shown that sharing painful experiences can strengthen social bonds and promote mutual prosociality, yet the neural mechanisms underlying this phenomenon remain unclear. We hypothesized that sharing a painful experience induces brain-to-brain synchronization and mutual empathy for each other's pain between pain-takers and pain-observers, which then leads to enhanced social bonding. To test this hypothesis, we adopted an electroencephalographic (EEG) hyper-scanning technique to assess neuronal and behavioral activity during a Pain-Sharing task in which high- or low-intensity pain stimulation was randomly delivered to one participant of a dyad on different experimental trials. Single-brain analysis showed that sensorimotor α-oscillation power was suppressed more when expecting high-intensity pain than when expecting low-intensity pain similarly for self-directed or partner-directed pain. Dual-brain analysis revealed that expecting high-intensity pain induced greater brain-to-brain synchronization of sensorimotor α-oscillation phases between pain-takers and pain-observers than did expecting low-intensity pain. Mediation analysis further revealed that brain-to-brain synchronization of sensorimotor α-oscillations mediated the effects of pain-stimulation intensity on mutual affective sharing for partner-directed pain. This mutual affective empathy during the task predicted the social bonding, as indexed by prosocial inclinations measured after the task. These results support the hypothesis that sharing a painful experience triggers emotional resonance between pairs of individuals through brain-to-brain synchronization of neuronal α-oscillations recorded over the sensorimotor cortex, and this emotional resonance further strengthens social bonds and motivates prosocial behavior within pairs of individuals.

Hyperconnection and hyperperfusion of overlapping brain regions in patients with menstrual-related migraine: a multimodal neuroimaging study.

PURPOSE: Menstrual-related migraine (MRM) results in moderate to severe intensity headaches accompanied by physical and emotional disability over time in women. Neuroimaging methodologies have advanced our understanding of migraine; however, the neural mechanisms of MRM are not clearly understood. METHODS: In this study, fourteen MRM patients in the interictal phase and fifteen age- and education-matched healthy control females were recruited. Resting-state functional magnetic resonance imaging (fMRI) and pulsed arterial spin labeling (PASL) MRI were collected for both the subject groups outside of their menstrual periods. Eigenvector centrality mapping (ECM) was performed on resting-state fMRI, and the relative cerebral blood flow (relCBF) was assessed using PASL-MRI. RESULTS: MRM patients showed a significantly increased eigenvector centrality in the right medial frontal gyrus compared to healthy controls. Seed-based ECM analysis revealed that increased centrality was associated with the right medial frontal gyrus's hyperconnectivity with the left insula and the right supplementary motor area. The perfusion MRI revealed significantly increased relCBF in the hyperconnected regions. Furthermore, the hyperconnection positively correlated with the attack frequency, while the hyperperfusion showed a positive correlation with the disease duration. CONCLUSION: The results suggest that menstrual-related migraine is associated with cerebral hyperconnection and hyperperfusion in critical pain-processing brain regions. Furthermore, this elevated cerebral activity is correlated with different aspects of functional impairment in MRM patients suggesting that perfusion analysis, along with whole-brain connectivity analysis, can provide a comprehensive understanding of neural mechanisms of MRM.

Neural Correlates of Motor Recovery after Robot-Assisted Training in Chronic Stroke: A Multimodal Neuroimaging Study.

Stroke is a leading cause of motor disability worldwide, and robot-assisted therapies have been increasingly applied to facilitate the recovery process. However, the underlying mechanism and induced neuroplasticity change remain partially understood, and few studies have investigated this from a multimodality neuroimaging perspective. The current study adopted BCI-guided robot hand therapy as the training intervention and combined multiple neuroimaging modalities to comprehensively understand the potential association between motor function alteration and various neural correlates. We adopted EEG-informed fMRI technique to understand the functional regions sensitive to training intervention. Additionally, correlation analysis among training effects, nonlinear property change quantified by fractal dimension (FD), and integrity of M1-M1 (M1: primary motor cortex) anatomical connection were performed. EEG-informed fMRI analysis indicated that for iM1 (iM1: ipsilesional M1) regressors, regions with significantly increased partial correlation were mainly located in contralesional parietal, prefrontal, and sensorimotor areas and regions with significantly decreased partial correlation were mainly observed in the ipsilesional supramarginal gyrus and superior temporal gyrus. Pearson's correlations revealed that the interhemispheric asymmetry change significantly correlated with the training effect as well as the integrity of M1-M1 anatomical connection. In summary, our study suggested that multiple functional brain regions not limited to motor areas were involved during the recovery process from multimodality perspective. The correlation analyses suggested the essential role of interhemispheric interaction in motor rehabilitation. Besides, the underlying structural substrate of the bilateral M1-M1 connection might relate to the interhemispheric change. This study might give some insights in understanding the neuroplasticity induced by the integrated BCI-guided robot hand training intervention and further facilitate the design of therapies for chronic stroke patients.

Kinect-based rapid movement training to improve balance recovery for stroke fall prevention: a randomized controlled trial.

BACKGROUND: Falls are more prevalent in stroke survivors than age-matched healthy older adults because of their functional impairment. Rapid balance recovery reaction with adequate range-of-motion and fast response and movement time are crucial to minimize fall risk and prevent serious injurious falls when postural disturbances occur. A Kinect-based Rapid Movement Training (RMT) program was developed to provide real-time feedback to promote faster and larger arm reaching and leg stepping distances toward targets in 22 different directions. OBJECTIVE: To evaluate the effectiveness of the interactive RMT and Conventional Balance Training (CBT) on chronic stroke survivors' overall balance and balance recovery reaction. METHODS: In this assessor-blinded randomized controlled trial, chronic stroke survivors were randomized to receive twenty training sessions (60-min each) of either RMT or CBT. Pre- and post-training assessments included clinical tests, as well as kinematic measurements and electromyography during simulated forward fall through a "lean-and-release" perturbation system. RESULTS: Thirty participants were recruited (RMT = 16, CBT = 14). RMT led to significant improvement in balance control (Berg Balance Scale: pre = 49.13, post = 52.75; P = .001), gait control (Timed-Up-and-Go Test: pre = 14.66 s, post = 12.62 s; P = .011), and motor functions (Fugl-Meyer Assessment of Motor Recovery: pre = 60.63, post = 65.19; P = .015), which matched the effectiveness of CBT. Both groups preferred to use their non-paretic leg to take the initial step to restore stability, and their stepping leg's rectus femoris reacted significantly faster post-training (P = .036). CONCLUSION: The RMT was as effective as conventional balance training to provide beneficial effects on chronic stroke survivors' overall balance, motor function and improving balance recovery with faster muscle response. TRIAL REGISTRATION: The study was registered at Clinicaltrials.gov ( https://clinicaltrials.gov/ct2/show/NCT03183635 , NCT03183635) on 12 June 2017.

Effects of wearable ankle robotics for stair and over-ground training on sub-acute stroke: a randomized controlled trial.

BACKGROUND: Wearable ankle robotics could potentially facilitate intensive repetitive task-specific gait training on stair environment for stroke rehabilitation. A lightweight (0.5 kg) and portable exoskeleton ankle robot was designed to facilitate over-ground and stair training either providing active assistance to move paretic ankle augmenting residual motor function (power-assisted ankle robot, PAAR), or passively support dropped foot by lock/release ankle joint for foot clearance in swing phase (swing-controlled ankle robot, SCAR). In this two-center randomized controlled trial, we hypothesized that conventional training integrated with robot-assisted gait training using either PAAR or SCAR in stair environment are more effective to enhance gait recovery and promote independency in early stroke, than conventional training alone. METHODS: Sub-acute stroke survivors (within 2 months after stroke onset) received conventional training integrated with 20-session robot-assisted training (at least twice weekly, 30-min per session) on over-ground and stair environments, wearing PAAR (n = 14) or SCAR (n = 16), as compared to control group receiving conventional training only (CT, n = 17). Clinical assessments were performed before and after the 20-session intervention, including functional ambulatory category as primary outcome measure, along with Berg balance scale and timed 10-m walk test. RESULTS: After the 20-session interventions, all three groups showed statistically significant and clinically meaningful within-group functional improvement in all outcome measures (p < 0.005). Between-group comparison showed SCAR had greater improvement in functional ambulatory category (mean difference + 0.6, medium effect size 0.610) with more than 56% independent walkers after training, as compared to only 29% for CT. Analysis of covariance results showed PAAR had greater improvement in walking speed than SCAR (mean difference + 0.15 m/s, large effect size 0.752), which was in line with the higher cadence and speed when wearing the robot during the 20-session robot-assisted training over-ground and on stairs. CONCLUSIONS: Robot-assisted stair training would lead to greater functional improvement in gait independency and walking speed than conventional training in usual care. The active powered ankle assistance might facilitate users to walk more and faster with their paretic leg during stair and over-ground walking. TRIAL REGISTRATION: ClinicalTrials.gov NCT03184259. Registered on 12 June 2017.

Effector-attenuating Substitutions That Maintain Antibody Stability and Reduce Toxicity in Mice.

The antibody Fc region regulates antibody cytotoxic activities and serum half-life. In a therapeutic context, however, the cytotoxic effector function of an antibody is often not desirable and can create safety liabilities by activating native host immune defenses against cells expressing the receptor antigens. Several amino acid changes in the Fc region have been reported to silence or reduce the effector function of antibodies. These earlier studies focused primarily on the interaction of human antibodies with human Fc-γ receptors, and it remains largely unknown how such changes to Fc might translate to the context of a murine antibody. We demonstrate that the commonly used N297G (NG) and D265A, N297G (DANG) variants that are efficacious in attenuating effector function in primates retain potent complement activation capacity in mice, leading to safety liabilities in murine studies. In contrast, we found an L234A, L235A, P329G (LALA-PG) variant that eliminates complement binding and fixation as well as Fc-γ-dependent, antibody-dependent, cell-mediated cytotoxity in both murine IgG2a and human IgG1. These LALA-PG substitutions allow a more accurate translation of results generated with an "effectorless" antibody between mice and primates. Further, we show that both human and murine antibodies containing the LALA-PG variant have typical pharmacokinetics in rodents and retain thermostability, enabling efficient knobs-into-holes bispecific antibody production and a robust path to generating highly effector-attenuated bispecific antibodies for preclinical studies.

Blocking neuropilin-1 function has an additive effect with anti-VEGF to inhibit tumor growth.

Neuropilin-1 (NRP1) guides the development of the nervous and vascular systems. Binding to either semaphorins or VEGF, NRP1 acts with plexins to regulate neuronal guidance, or with VEGFR2 to mediate vascular development. We have generated two monoclonal antibodies that bind to the Sema- and VEGF-binding domains of NRP1, respectively. Both antibodies reduce angiogenesis and vascular remodeling, while having little effect on other VEGFR2-mediated events. Importantly, anti-NRP1 antibodies have an additive effect with anti-VEGF therapy in reducing tumor growth. Vessels from tumors treated with anti-VEGF show a close association with pericytes, while tumors treated with both anti-NRP1 and anti-VEGF lack this organization. We propose that blocking NRP1 function inhibits vascular remodeling, rendering vessels more susceptible to anti-VEGF therapy.

Efficacy of robot-assisted fingers training in chronic stroke survivors: a pilot randomized-controlled trial.

BACKGROUND: While constraint-induced movement therapy (CIMT) is one of the most promising techniques for upper limb rehabilitation after stroke, it requires high residual function to start with. Robotic device, on the other hand, can provide intention-driven assistance and is proven capable to complement conventional therapy. However, with many robotic devices focus on more proximal joints like shoulder and elbow, recovery of hand and fingers functions have become a challenge. Here we propose the use of robotic device to assist hand and fingers functions training and we aim to evaluate the potential efficacy of intention-driven robot-assisted fingers training. METHODS: Participants (6 to 24 months post-stroke) were randomly assigned into two groups: robot-assisted (robot) and non-assisted (control) fingers training groups. Each participant underwent 20-session training. Action Research Arm Test (ARAT) was used as the primary outcome measure, while, Wolf Motor Function Test (WMFT) score, its functional tasks (WMFT-FT) sub-score, Fugl-Meyer Assessment (FMA), its shoulder and elbow (FMA-SE) sub-score, and finger individuation index (FII) served as secondary outcome measures. RESULTS: Nineteen patients completed the 20-session training ( TRIAL REGISTRATION: HKClinicalTrials.com HKCTR-1554); eighteen of them came back for a 6-month follow-up. Significant improvements (p < 0.05) were found in the clinical scores for both robot and control group after training. However, only robot group maintained the significant difference in the ARAT and FMA-SE six months after the training. The WMFT-FT score and time post-training improvements of robot group were significantly better than those of the control group. CONCLUSIONS: This study showed the potential efficacy of robot-assisted fingers training for hand and fingers rehabilitation and its feasibility to facilitate early rehabilitation for a wider population of stroke survivors; and hence, can be used to complement CIMT.

Separated collaborative learning for semi-supervised prostate segmentation with multi-site heterogeneous unlabeled MRI data.

Segmenting prostate from magnetic resonance imaging (MRI) is a critical procedure in prostate cancer staging and treatment planning. Considering the nature of labeled data scarcity for medical images, semi-supervised learning (SSL) becomes an appealing solution since it can simultaneously exploit limited labeled data and a large amount of unlabeled data. However, SSL relies on the assumption that the unlabeled images are abundant, which may not be satisfied when the local institute has limited image collection capabilities. An intuitive solution is to seek support from other centers to enrich the unlabeled image pool. However, this further introduces data heterogeneity, which can impede SSL that works under identical data distribution with certain model assumptions. Aiming at this under-explored yet valuable scenario, in this work, we propose a separated collaborative learning (SCL) framework for semi-supervised prostate segmentation with multi-site unlabeled MRI data. Specifically, on top of the teacher-student framework, SCL exploits multi-site unlabeled data by: (i) Local learning, which advocates local distribution fitting, including the pseudo label learning that reinforces confirmation of low-entropy easy regions and the cyclic propagated real label learning that leverages class prototypes to regularize the distribution of intra-class features; (ii) External multi-site learning, which aims to robustly mine informative clues from external data, mainly including the local-support category mutual dependence learning, which takes the spirit that mutual information can effectively measure the amount of information shared by two variables even from different domains, and the stability learning under strong adversarial perturbations to enhance robustness to heterogeneity. Extensive experiments on prostate MRI data from six different clinical centers show that our method can effectively generalize SSL on multi-site unlabeled data and significantly outperform other semi-supervised segmentation methods. Besides, we validate the extensibility of our method on the multi-class cardiac MRI segmentation task with data from four different clinical centers.

Uncovering the Neural Mechanisms of Inter-Hemispheric Balance Restoration in Chronic Stroke Through EMG-Driven Robot Hand Training: Insights From Dynamic Causal Modeling.

EMG-driven robot hand training can facilitate motor recovery in chronic stroke patients by restoring the interhemispheric balance between motor networks. However, the underlying mechanisms of reorganization between interhemispheric regions remain unclear. This study investigated the effective connectivity (EC) between the ventral premotor cortex (PMv), supplementary motor area (SMA), and primary motor cortex (M1) using Dynamic Causal Modeling (DCM) during motor tasks with the paretic hand. Nineteen chronic stroke subjects underwent 20 sessions of EMG-driven robot hand training, and their Action Reach Arm Test (ARAT) showed significant improvement ( ß =3.56, [Formula: see text]). The improvement was correlated with the reduction of inhibitory coupling from the contralesional M1 to the ipsilesional M1 (r=0.58, p=0.014). An increase in the laterality index was only observed in homotopic M1, but not in the premotor area. Additionally, we identified an increase in resting-state functional connectivity (FC) between bilateral M1 ( ß =0.11, p=0.01). Inter-M1 FC demonstrated marginal positive relationships with ARAT scores (r=0.402, p=0.110), but its changes did not correlate with ARAT improvements. These findings suggest that the improvement of hand functions brought about by EMG-driven robot hand training was driven explicitly by task-specific reorganization of motor networks. Particularly, the restoration of interhemispheric balance was induced by a reduction in interhemispheric inhibition from the contralesional M1 during motor tasks of the paretic hand. This finding sheds light on the mechanistic understanding of interhemispheric balance and functional recovery induced by EMG-driven robot training.

Can oral microbiome predict low birth weight infant delivery?

OBJECTIVES: This study aimed to identify the oral microbiota factors contributing to low birth weight (LBW) in Chinese pregnant women and develop a prediction model using machine learning. METHODS: A nested case-control study was conducted in a prospective cohort of 580 Chinese pregnant women, with 23 LBW cases and 23 healthy delivery controls matched for age and smoking habit. Saliva samples were collected at early and late pregnancy, and microbiome profiles were analyzed through 16S rRNA gene sequencing. RESULTS: The relative abundance of Streptococcus was over-represented (median 0.259 vs. 0.116) and Saccharibacteria_TM7 was under-represented (median 0.033 vs. 0.068) in the LBW case group than in controls (p < 0.001, p = 0.015 respectively). Ten species were identified as microbiome biomarkers of LBW by LEfSe analysis, which included 7 species within the genus of Streptococcus or as part of 'nutritionally variant streptococci' (NVS), 2 species of opportunistic pathogen Leptotrichia buccalis and Gemella sanguinis (all LDA score>3.5) as risk biomarkers, and one species of Saccharibacteria TM7 as a beneficial biomarker (LDA= -4.5). The machine-learning model based on these 10 distinguished oral microbiota species could predict LBW, with an accuracy of 82 %, sensitivity of 91 %, and specificity of 73 % (AUC-ROC score 0.89, 95 % CI: 0.75-1.0). Results of α-diversity showed that mothers who delivered LBW infants had less stable salivary microbiota construction throughout pregnancy than the control group (measured by Shannon, p = 0.048; and Pielou's, p = 0.021), however the microbiome diversity did not improve the prediction accuracy of LBW. CONCLUSIONS: A machine-learning oral microbiome model shows promise in predicting low-birth-weight delivery. Even in cases where oral health is not significantly compromised, opportunistic pathogens or rarer taxa associated with adverse pregnancy outcomes can still be identified in the oral cavity. CLINICAL SIGNIFICANCE: This study highlights the potential complexity of the relationship between oral microbiome and pregnancy outcomes, indicating that mechanisms underlying the association between oral microbiota and adverse pregnancy outcomes may involve complex interactions between host factors, microbiota, and systemic conditions. Using machine learning to develop a predictive model based on specific oral microbiota biomarkers provides a potential for personalized medicine approaches. Future prediction models should incorporate clinical metadata to be clinically useful for improving maternal and child health.

Task-Oriented Training by a Personalized Electromyography-Driven Soft Robotic Hand in Chronic Stroke: A Randomized Controlled Trial.

BACKGROUND: Intensive task-oriented training has shown promise in enhancing distal motor function among patients with chronic stroke. A personalized electromyography (EMG)-driven soft robotic hand was developed to assist task-oriented object-manipulation training effectively. Objective. To compare the effectiveness of task-oriented training using the EMG-driven soft robotic hand. METHODS: A single-blinded, randomized controlled trial was conducted with 34 chronic stroke survivors. The subjects were randomly assigned to the Hand Task (HT) group (n = 17) or the control (CON) group (n = 17). The HT group received 45 minutes of task-oriented training by manipulating small objects with the robotic hand for 20 sessions, while the CON group received 45 minutes of hand-functional exercises without objects using the same robot. Fugl-Meyer assessment (FMA-UE), Action Research Arm Test (ARAT), Modified Ashworth Score (MAS), Box and Block test (BBT), Maximum Grip Strength, and active range of motion (AROM) of fingers were assessed at baseline, after intervention, and 3 months follow-up. The muscle co-contraction index (CI) was analyzed to evaluate the session-by-session variation of upper limb EMG patterns. RESULTS: The HT group showed more significant improvement in FMA-UE (wrist/hand, shoulder/elbow) compared to the CON group (P < .05). At 3-month follow-up, the HT group demonstrated significant improvements in FMA-UE, ARAT, BBT, MAS (finger), and AROMs (P < .05). The HT group exhibited a more significant decrease in muscle co-contractions compared to the CON group (P < .05). CONCLUSIONS: EMG-driven task-oriented training with the personalized soft robotic hand was a practical approach to improving motor function and muscle coordination. CLINICAL TRIAL REGISTRY NAME: Soft Robotic Hand System for Stroke Rehabilitation. CLINICAL TRIAL REGISTRATION-URL: https://clinicaltrials.gov/. UNIQUE IDENTIFIER: NCT03286309.