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Background Accurate prediction of motor recovery after stroke is critical for treatment decisions and planning. Machine learning has been proposed to be a promising technique for outcome prediction because of its high accuracy and ability to process large volumes of data. It has been used to predict acute stroke recovery; however, whether machine learning would be effective for predicting rehabilitation outcomes in chronic stroke patients for common contemporary task-oriented interventions remains largely unexplored. This study aimed to determine the accuracy and performance of machine learning to predict clinically significant motor function improvements after contemporary task-oriented intervention in chronic stroke patients and identify important predictors for building machine learning prediction models. Methods This study was a secondary analysis of data using two common machine learning approaches, which were the k-nearest neighbor (KNN) and artificial neural network (ANN). Chronic stroke patients (N = 239) that received 30 h of task-oriented training including the constraint-induced movement therapy, bilateral arm training, robot-assisted therapy and mirror therapy were included. The Fugl-Meyer assessment scale (FMA) was the main outcome. Potential predictors include age, gender, side of lesion, time since stroke, baseline functional status, motor function and quality of life. We divided the data set into a training set and a test set and used the cross-validation procedure to construct machine learning models based on the training set. After the models were built, we used the test data set to evaluate the accuracy and prediction performance of the models. Results Three important predictors were identified, which were time since stroke, baseline functional independence measure (FIM) and baseline FMA scores. Models for predicting motor function improvements were accurate. The prediction accuracy of the KNN model was 85.42% and area under the receiver operating characteristic curve (AUC-ROC) was 0.89. The prediction accuracy of the ANN model was 81.25% and the AUC-ROC was 0.77. Conclusions Incorporating machine learning into clinical outcome prediction using three key predictors including time since stroke, baseline functional and motor ability may help clinicians/therapists to identify patients that are most likely to benefit from contemporary task-oriented interventions. The KNN and ANN models may be potentially useful for predicting clinically significant motor recovery in chronic stroke.

Ammonium has long been used as the predominant form of nitrogen source for paddy rice ( Oryza sativa ). Recently, increasing evidence suggests that nitrate also plays an important role for nitrogen acquisition in the rhizosphere of waterlogged paddy rice. Ammonium and nitrate have a synergistic effect on promoting rice growth. However, the molecular responses induced by simultaneous treatment with ammonium and nitrate have been less studied in rice. Here, we performed transcriptome analysis to identify genes that are rapidly regulated by ammonium nitrate (1.43 mM, 30 min) in rice roots. The combination of ammonium and nitrate preferentially induced the expression of nitrate-responsive genes. Gene ontology enrichment analysis revealed that the early ammonium nitrate-responsive genes were enriched in “regulation of transcription, DNA-dependent” and “protein amino acid phosphorylation” indicating that some of the genes identified in this study may play an important role in nitrogen sensing and signaling. Several defense/stress-responsive genes, including some encoding transcription factors and mitogen-activated protein kinase kinase kinases, were also rapidly induced by ammonium nitrate. These results suggest that nitrogen metabolism, signaling, and defense/stress responses are interconnected. Some of the genes identified here may be involved in the interaction of nitrogen signaling and defense/stress-response pathways in plants.

Background Our previous study demonstrated that a 6-month combined physical and cognitive training program improved mismatch negativity (MMN)—an event-related potential reflecting the brain’s automatic detection of environmental changes—in older adults with subjective cognitive decline (SCD). However, not all individuals benefited equally from the intervention. Identifying baseline predictors of intervention outcomes could enable the prediction of individual responsiveness and support the development of personalized, stratified intervention strategies to promote brain health in this at-risk population. This study aimed to identify baseline predictors of response to a 6-month combined cognitive and physical training program among older adults with SCD. Methods We conducted a secondary analysis of a cluster-randomized trial involving 33 older adults with SCD who participated in twice-weekly integrated training sessions. MMN was assessed for the analytic sample ( n  = 21) as the primary outcome measure. Baseline predictors included age, general cognitive function, physical and cognitive activity engagement, and apolipoprotein E (APOE) genotype. Linear regression analyses were performed to examine predictors of change in MMN amplitude from baseline to post-intervention. Results Regression analysis indicated that APOE ε4 non-carriers showed significantly greater improvement in MMN amplitude (β = ‒0.449, p  = 0.027). Additionally, lower baseline levels of physical activity demonstrated a trend toward association with greater MMN gains (β = ‒0.392, p  = 0.050), suggesting that individuals with more sedentary lifestyles may derive greater benefit from the intervention. Conclusions APOE ε4 carrier status and baseline physical activity levels may be associated with the effectiveness of multidomain interventions in older adults with SCD.

Health related quality of life (HRQOL) reflects individuals perceived of wellness in health domains and is often deteriorated after stroke. Precise prediction of HRQOL changes after rehabilitation interventions is critical for optimizing stroke rehabilitation efficiency and efficacy. Machine learning (ML) has become a promising outcome prediction approach because of its high accuracy and easiness to use. Incorporating ML models into rehabilitation practice may facilitate efficient and accurate clinical decision making. Therefore, this study aimed to determine if ML algorithms could accurately predict clinically significant HRQOL improvements after stroke sensorimotor rehabilitation interventions and identify important predictors. Five ML algorithms including the random forest (RF), k-nearest neighbors (KNN), artificial neural network, support vector machine and logistic regression were used. Datasets from 132 people with chronic stroke were included. The Stroke Impact Scale was used for assessing multi-dimensional and global self-perceived HRQOL. Potential predictors included personal characteristics and baseline cognitive/motor/sensory/functional/HRQOL attributes. Data were divided into training and test sets. Tenfold cross-validation procedure with the training data set was used for developing models. The test set was used for determining model performance. Results revealed that RF was effective at predicting multidimensional HRQOL (accuracy: 85%; area under the receiver operating characteristic curve, AUC-ROC: 0.86) and global perceived recovery (accuracy: 80%; AUC-ROC: 0.75), and KNN was effective at predicting global perceived recovery (accuracy: 82.5%; AUC-ROC: 0.76). Age/gender, baseline HRQOL, wrist/hand muscle function, arm movement efficiency and sensory function were identified as crucial predictors. Our study indicated that RF and KNN outperformed the other three models on predicting HRQOL recovery after sensorimotor rehabilitation in stroke patients and could be considered for future clinical application.

Many individuals with stroke experience upper-limb motor deficits, and a recent trend is to develop novel devices for enhancing their motor function. This study aimed to develop a new upper-limb rehabilitation system with the integration of two rehabilitation therapies into one system, digital mirror therapy (MT) and action observation therapy (AOT), and to test the usability of this system. In the part I study, the new system was designed to operate in multiple training modes of digital MT (i.e., unilateral and bilateral modes) and AOT (i.e., pre-recorded and self-recorded videos) with self-developed software. In the part II study, 4 certified occupational therapists and 10 stroke patients were recruited for evaluating usability. The System Usability Scale (SUS) (maximum score = 100) and a self-designed questionnaire (maximum score = 50) were used. The mean scores of the SUS were 79.38 and 80.00, and those of the self-designed questionnaire were 41.00 and 42.80, respectively, for the therapists and patients after using this system, which indicated good usability and user experiences. This novel upper-limb rehabilitation system with good usability might be further used to increase the delivery of two emerging rehabilitation therapies, digital AOT and MT, to individuals with stroke.

Whether muscle properties gradually change with age and how muscle properties are affected by sex remain unclear. In this study, we investigated the influence of age and sex on the biomechanical and viscoelastic properties of arm muscles in middle-aged and older adults. In this cross-sectional study, 80 healthy participants were divided by sex (male and female), and each sex group, by 10-year age ranges (40–49, 50–59, 60–69, and 70–79 years). Muscle properties, including tone, stiffness, elasticity, and mechanical stress relaxation time, were measured with the MyotonPRO. Our results showed that the muscle tone and elasticity of the deltoid and flexor carpi radialis, and the muscle tone of the flexor carpi ulnaris, were significantly greater in men than in women, whereas the stress relaxation time of the triceps was significantly greater in women than in men. Significantly greater muscle stiffness in the biceps brachii was found in the participants over 50 years old. Less muscle elasticity was found in the deltoid, triceps, and flexor carpi ulnaris in those over 70 years old. In conclusion, age and sex have considerable impacts on upper-limb muscle properties in middle-aged and older adults, which should be taken into consideration when planning health promotion projects.

Background The timing of transcranial direct current stimulation (tDCS) with neurorehabilitation interventions may affect its modulatory effects. Motor function has been reported to be modulated by the timing of tDCS; however, whether the timing of tDCS would also affect restoration of daily function and upper extremity motor control with neurorehabilitation in stroke patients remains largely unexplored. Mirror therapy (MT) is a potentially effective neurorehabilitation approach for improving paretic arm function in stroke patients. This study aimed to determine whether the timing of tDCS with MT would influence treatment effects on daily function, motor function and motor control in individuals with chronic stroke. Methods This study was a double-blinded randomized controlled trial. Twenty-eight individuals with chronic stroke received one of the following three interventions: (1) sequentially combined tDCS with MT (SEQ), (2) concurrently combined tDCS with MT (CON), and (3) sham tDCS with MT (SHAM). Participants received interventions for 90 min/day, 5 days/week for 4 weeks. Daily function was assessed using the Nottingham Extended Activities of Daily Living Scale. Upper extremity motor function was assessed using the Fugl-Meyer Assessment Scale. Upper extremity motor control was evaluated using movement kinematic assessments. Results There were significant differences in daily function between the three groups. The SEQ group had greater improvement in daily function than the CON and SHAM groups. Kinematic analyses showed that movement time of the paretic hand significantly reduced in the SEQ group after interventions. All three groups had significant improvement in motor function from pre-intervention to post-intervention. Conclusion The timing of tDCS with MT may influence restoration of daily function and movement efficiency of the paretic hand in chronic stroke patients. Sequentially applying tDCS prior to MT seems to be advantageous for enhancing daily function and hand movement control, and may be considered as a potentially useful strategy in future clinical application. Trial registration ClinicalTrials.gov Identifier: NCT02827864 . Registered on 29th June, 2016.

The ACT domain ( a spartate kinase, c horismate mutase and T yrA), an allosteric effector binding domain, is commonly found in amino acid metabolic enzymes. In addition to ACT domain-containing enzymes, plants have a novel family of AC T domain r epeat (ACR) proteins, which do not contain any recognizable catalytic domain. Arabidopsis has 12 ACR proteins, whose functions are largely unknown. To study the functions of Arabidopsis ACR11, we have characterized two independent T-DNA insertion mutants, acr11-2 and acr11-3 . RNA gel-blot analysis revealed that the expression of wild-type ACR11 transcripts was not detectable in the acr11 mutants. Interestingly, a lesion-mimic phenotype occurs in some rosette leaves of the acr11 mutants. In addition, high levels of reactive oxygen species (ROS), salicylic acid (SA), and callose accumulate in the mutant leaves when grown under normal conditions. The expression of several SA marker genes and the key SA biosynthetic gene ISOCHORISMATE SYNTHASE1 is up-regulated in the acr11 mutants. Furthermore, the acr11 mutants are more resistant to the infection of bacterial pathogen Pseudomonas syringae pathovar tomato DC3000. These results suggest that ACR11 may be directly or indirectly involved in the regulation of ROS and SA accumulation, which in turn modulates SA-associated defense responses and disease resistance in Arabidopsis.

Background. Action observation therapy and mirror therapy, two promising rehabilitation strategies, are aimed at enhancing the motor learning and functional improvement of stroke patients through different patterns of visual feedback and observation. Objective. This study investigated and compared the treatment effects of the action observation therapy, mirror therapy, and active control intervention on motor and functional outcomes of stroke patients. Methods. Twenty-one patients with subacute stroke were recruited in this study. All patients were randomly assigned to the action observation therapy, mirror therapy, or active control intervention for 3 weeks. Outcome measures were conducted at baseline, immediately after treatment, and at 3-month follow-up. The primary outcome was the Fugl-Meyer Assessment, and secondary outcomes included the Box and Block Test, Functional Independence Measure, and Stroke Impact Scale. Descriptive analyses and the number of patients whose change score achieved minimal clinically important difference were reported. Results. Both the action observation therapy and active control intervention showed similar improvements on the Fugl-Meyer Assessment, Box and Block Test, and Stroke Impact Scale. Moreover, the action observation therapy had a greater improvement on the Functional Independence Measure than the other 2 groups did. However, the mirror therapy group gained the least improvements on the outcomes. Conclusion. The preliminary results found that the patients in the action observation therapy and active control intervention groups had comparable benefits, suggesting that the 2 treatments might be used as an alternative to each other. A further large-scale study with at least 20 patients in each group to validate the study findings is needed. This trial is registered with NCT02871700.

This study examined the treatment efficacy of proximal-emphasized robotic rehabilitation by using the InMotion ARM (P-IMT) versus distal-emphasized robotic rehabilitation by using the InMotion WRIST (D-IMT) in patients with stroke. A total of 40 patients with stroke completed the study. They received P-IMT, D-IMT, or control treatment (CT) for 20 training sessions. Primary outcomes were the Fugl-Meyer Assessment (FMA) and Medical Research Council (MRC) scale. Secondary outcomes were the Motor Activity Log (MAL) and wrist-worn accelerometers. The differences on the distal FMA, total MRC, distal MRC, and MAL quality of movement scores among the 3 groups were statistically significant ( P  = 0.02 to 0.05). Post hoc comparisons revealed that the D-IMT group significantly improved more than the P-IMT group on the total MRC and distal MRC. Furthermore, the distal FMA and distal MRC improved more in the D-IMT group than in the CT group. Our findings suggest that distal upper-limb robotic rehabilitation using the InMotion WRIST system had superior effects on distal muscle strength. Further research based on a larger sample is needed to confirm long-term treatment effects of proximal versus distal upper-limb robotic rehabilitation.